POLITECNICO DI MILANO DEPARTMENT OF MANAGEMENT, ECONOMICS AND INDUSTRIAL ENGINEERING DOCTORAL PROGRAM IN MANAGEMENT, ECONOMICS AND INDUSTRIAL ENGINEERING The unexpected implications of opening up innovation A multi-perspective study of the role of Open Innovation practices in mature industries Doctoral Dissertation of: Andrés Ramírez Portilla Supervisors: Prof. Enrico Cagno Prof. Terrence Brown Tutor: Prof. Paolo Trucco The Chair of the Doctoral Program: Prof. Paolo Trucco February 2016 XXVII Cycle In cooperation with:
Transcript
POLITECNICO DI MILANO
DEPARTMENT OF MANAGEMENT, ECONOMICS AND INDUSTRIAL ENGINEERING
DOCTORAL PROGRAM IN MANAGEMENT, ECONOMICS AND INDUSTRIAL ENGINEERING
The unexpected implications of opening up innovation
A multi-perspective study of the role of Open Innovation practices in mature industries
Doctoral Dissertation of: Andrés Ramírez Portilla
Supervisors: Prof. Enrico Cagno
Prof. Terrence Brown
Tutor: Prof. Paolo Trucco
The Chair of the Doctoral Program:
Prof. Paolo Trucco
February 2016
XXVII Cycle
In cooperation with:
The unexpected implications of opening up
innovation
A multi-perspective study of the role of Open Innovation practices in mature industries
ANDRÉS RAMÍREZ PORTILLA
Doctoral Thesis 2016 Politecnico di Milano, School of Management
Department of Management, Economics and Industrial Engineering 20133 Milan, Italy
and KTH Royal Institute of Technology
School of Industrial Engineering and Management Department of Industrial Economics and Management
This research was conducted within the framework of the “European Doctorate in
Industrial Management”—EDIM—which is funded by The Education,
Audiovisual and Culture Executive Agency (EACEA) of European Commission
under Erasmus Mundus Action 1 programmes.
EDIM is run by a consortium consisting of the industrial management
departments of three institutions:
• KTH Royal Institute of Technology, Stockholm, Sweden
• Politecnico de Milano (POLIMI), Milan, Italy
• Universidad Politécnica de Madrid (UPM), Madrid, Spain
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The mind is like a parachute. It doesn’t work if it’s not open. - Frank Zappa -
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Abstract
The way firms innovate has notably changed in recent years. A clear example is the manufacturing sector which has been experiencing a new revolution in production and innovation. Linked to this industrial shift, manufacturing firms have been adopting more open and collaborative practices to innovate. This phenomenon, known as Open Innovation (OI), is helping firms to acquire and explore knowledge from external sources (inbound process) and to exploit knowledge via the commercialisation of ideas and technology (outbound process). Even though numerous researchers have studied the adoption of OI and its relation to numerous strategic and organisational results, very few studies have focused on investigating the positive influence of diverse OI approaches and practices on multiple dimensions of firm performance from different angles. These drawbacks hinder the diffusion of OI practices and raise the question of whether it is convenient for any firm in any industry to adopt or not to adopt OI. Thus, this thesis helps to fill this gap by examining the extent to which OI practices are adopted by firms and other actors in unexplored mature manufacturing industries and by understanding the unidentified roles that these practices play in relation to different dimensions of firm and industrial performance. This thesis brings together different methodologies and data to investigate OI practices with a novel multi-perspective approach. Hence, OI practices are framed within the industrial context of manufacturing firms in Italy and Sweden, several actors in the food industry, small and medium-sized enterprises (SMEs) from the Italian foundry industry, and also within worldwide SMEs designing and producing supercars. More specifically, using data from 247 European manufacturing firms collected through a tailored OI survey, this thesis supports the relevance of internal context characteristics such as firm size and provides evidence of the relation between configurations of OI models and innovation performance. Through two case studies in the food industry, this thesis demonstrates novel forms of OI practices that can be characterised and adopted by different innovation actors within and around this mature industry. Likewise, drawing from 30 rigorous case studies of small and medium-sized foundries, this research for the first time illuminates the relation between the aggregations of some innovation practices (specifically internal R&D and inbound OI) with a contemporarily relevant dimension of environmental and industrial performance such as energy efficiency. Although foregrounding the practical implications of adopting OI practices, this project also investigates and attempts to contrast some of the theoretical perspectives used when researching OI in mature manufacturing industries. This thesis concludes with an integrative study of the main aspects of the research project to demonstrate the advantages of using a multi-perspective approach to study OI. This last study, originally inspired from two case studies of small carmakers, involved collecting data from 48 small and medium-sized manufacturers of supercars with a survey designed to evaluate OI influence on several types of firm performance. Collectively, the results from this thesis confirm the validity of OI in new research contexts and reveal a combined influence of specific innovation practices on innovativeness, but also on the dimensions of industrial, environmental, and social
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performance. This thesis contributes to theory and practice by empirically showing that even though OI and the results of practicing it are highly context dependent, adopting OI practices can definitely have a positive influence in the overall performance of firms in mature manufacturing industries, including SMEs and other small actors. Keywords: open innovation, practices, innovation performance, industrial performance, sustainability, SMEs, manufacturing sector, automotive industry, foundry industry, food industry
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Sommario
Il modo in cui le imprese stanno innovando è notevolmente cambiato negli ultimi anni. Un chiaro esempio è il settore manifatturiero, che sta reagendo a una nuova rivoluzione nella produzione e innovazione. Collegato a questo cambiamento industriale, le aziende del settore della manifattura stanno acquisendo nuove pratiche più aperte e collaborative per innovare. Questo fenomeno, noto come ‘Open Innovation’ (OI), sta aiutando alle aziende ad acquistare e esplorare le conoscenze dalle fonti esterne (processo ‘inbound’) e di sfruttare la conoscenza tramite la commercializzazione delle idee e delle tecnologie (processo ‘outbound’). Anche se numerosi ricercatori hanno studiato l’adozione della OI e la sua relazione con numerosi risultati strategici ed organizzativi, in pochi studi si sono concentrati sullo studio dell’influenza positiva di diversi approcci e pratiche sulle multipli dimensioni della performance aziendale di diverse angolature della OI. Questi inconvenienti ostacolano la diffusione delle pratiche OI ed evidenziano la questione se è pure conveniente per qualsiasi tipo d’azienda in qualsiasi tipo d’industria adottare o non adottare OI. Così, questa tesi contribuisce a riempire questa lacuna tramite la esaminazione delle misure in cui le pratiche della OI vengono adottate dalle aziende ed altri attori nelle inesplorate industrie mature della manifattura e attraverso la comprensione dei ruoli non identificati che queste pratiche giocano in relazione alle diverse dimensioni della performance aziendale e industriale. Questa tesi mette insieme le diverse metodologie e i dati ad indagare sulle pratiche della OI con un nuovo approccio multi-prospettico. Quindi, le pratiche OI sono inquadrate nel contesto industriale delle aziende manifatturiere in Italia e in Svezia, i diversi attori nel settore alimentare, le piccole e medie imprese (PMI) del settore della fonderia italiana, e anche nelle PMI di tutto il mondo che disegnano e producono i supercars. In particolare, utilizzando i dati di 247 aziende manifatturiere europee raccolti attraverso un sondaggio, questa tesi sostiene la rilevanza delle caratteristiche del contesto interno come la dimensione della azienda e fornisce la prova della relazione tra configurazioni dei modelli OI e la capacità di innovazione. Attraverso due casi di studio nel settore alimentare, questa tesi dimostra delle nuove forme di pratiche OI che possono essere caratterizzate e adottate dai diversi attori dell’innovazione all’interno ed all’intorno di questo settore maturo. Allo stesso modo, raccolto da 30 rigorosi casi di studio delle piccole e delle medie fonderie, questa ricerca per la prima volta illumina la relazione tra le aggregazioni di alcune pratiche di innovazione (in particolare le pratiche interne di R&S e di OI inbound) con una dimensione contemporaneamente rilevante delle prestazioni ambientali ed industriali quali l’efficienza energetica. Anche se in primo piano le implicazioni pratiche dell’adozione delle pratiche della OI sono accentate, il progetto indaga anche e cerca di contrastare alcune delle prospettive teoriche utilizzate nella ricerca nelle mature industrie manifatturiere. Questa tesi finisce con uno studio integrativo degli aspetti principali del progetto di ricerca per dimostrare i vantaggi di utilizzare un approccio multi-prospettiva per studiare la OI. Quest’ultimo studio, originariamente ispirato da due casi di studio di piccole case automobilistiche, ha coinvolto la raccolta dei dati provenienti da 48 piccole e medie produttori di supercars tramite un sondaggio per valutare
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l’influenza dei diversi tipi di performance aziendale. Collettivamente, i risultati di questa tesi confermano la validità di OI in nuovi contesti di ricerca e rivelano una influenza combinata di pratiche d’innovazione specifica su innovazione, ma anche sulle dimensioni della performance industriale, ambientale e sociale. Questa tesi contribuisce alla teoria e alla pratica, che empiricamente mostra che se anche la OI ed i risultati di praticarla sono molto dipendenti dal contesto, l’adozione delle pratiche OI può sicuramente avere un effetto positivo nelle prestazioni complessive delle aziende nella industria manifatturiere matura, comprese le PMI ed altri piccoli attori. Parole chiave: innovazione aperta, pratiche, capacità d’innovazione, prestazioni industriali, sostenibilità, PMI, settore manifatturiero, industria automobilistica, industria della fonderia, industria alimentare
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Sammanfattning
Det sätt på vilket företagen innoverar har förändrats märkbart under de senaste åren. Den här situationen syns tydligt inom tillverkningssektorn, som upplever en ny produktions- och innovationsrevolution. Med tanke på detta inför tillverkningsföretagen öppnare och mer samarbetsbaserade metoder. Detta fenomen, benämnt öppen innovation (Open Innovation, OI), hjälper organisationer att förvärva och utforska kunskaper från externa källor (ingående process) och att utforska kunskaper genom kommersialisering av idéer och teknik (utgående process). Även om ett flertal forskare har studerat införandet av OI och hur det hänger samman med olika strategiska och organisatoriska resultat, har endast mycket få studier lagt fokus på att undersöka de positiva effekter som olika former av OI-metoder och -praxis har på flera dimensioner av företagens resultat och ur olika synvinklar. Den här bristen hindrar spridningen av OI-praxis och väcker frågan om huruvida det är fördelaktigt för ett företag i en viss bransch att införa eller inte införa OI. Denna avhandling hjälper till att fylla det här tomrummet genom att undersöka i vilken utsträckning öppen innovationspraxis har införts av företag och andra aktörer i outforskade, mogna tillverkningsbranscher och vilka oidentifierade roller sådan praxis spelar i förhållande till olika dimensioner av företagsresultat och branschresultat. Denna avhandling för samman olika metoder och data för att undersöka OI-praxis ur ett nytt multiperspektiv. Det industriella sammanhanget för studien av OI-praxis är därför tillverkningsföretag i Italien och Sverige, flera aktörer inom livsmedelsindustrin, små och medelstora företag från den italienska gjuteriindustrin samt små och medelstora företag världen över som utformar och tillverkar superbilar. Denna avhandling använder data från 247 europeiska tillverkningsföretag, som samlats in genom en skräddarsydd enkät om öppen innovation, för att bekräfta betydelsen av det interna sammanhangets egenskaper, t.ex. företagets storlek, och lägga fram bevis för relationen mellan OI-modellkonfigurationer och innovationsresultat. Genom två fallstudier inom livsmedelsindustrin visar denna avhandling nya sätt på vilka OI-praxis kan karakteriseras och införas av olika innovationsaktörer inom och omkring den här mogna branschen. Forskningsprojektet utgår även från 30 noggrant genomförda fallstudier av små och medelstora gjuterier för att för första gången belysa relationen mellan samlingar av vissa former av innovationspraxis (nämligen intern FoU och ingående OI) och en samtida relevant dimension av miljö- och branschresultat, t.ex. energieffektivitet. Detta projekt bildar förgrunden till de praktiska följderna av att införa OI-praxis, men undersöker även och försöker kontrastera till några av de teoretiska perspektiv som används vid forskning kring OI i mogna tillverkningsbranscher. Denna avhandling avslutas med en integrerande studie av forskningsprojektets huvudsakliga aspekter för att påvisa fördelarna med att använda en multiperspektivmetod vid studier av OI. Den sista studien, till vilken inspirationen ursprungligen hämtades från två fallstudier av små biltillverkare, innebar insamling av data från 48 små och medelstora tillverkare av superbilar med en enkät avsedd att utvärdera OI:s påverkan på flera typer av företagsresultat. De sammantagna resultaten från denna avhandling bekräftar OI:s giltighet i nya forskningssammanhang och avslöjar en
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kombinerad effekt av vissa former av innovationspraxis på innovationsförmåga, men även på dimensionerna industriella, miljömässiga och sociala resultat. Avhandlingen bidrar till teori och praktik genom att empiriskt påvisa att även om OI och resultaten av OI-praxis är starkt kontextberoende, kan införande av OI-praxis säkerligen ha ett positivt inflytande på det totala resultatet för företag i mogna tillverkningsbranscher, däribland små och medelstora företag och andra mindre aktörer. Nyckelord: öppen innovation, praxis, innovationsresultat, branschresultat, hållbarhet, små och medelstora företag, tillverkningssektor, bilindustri, gjuteriindustri, livsmedelsindustri
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Acknowledgements
I would like to acknowledge the help and support from a large number of people and institutions, without whom, this thesis would not have been possible. So first and foremost, I would like to thank my two supervisors: Terrence Brown from KTH Royal Institute of Technology and Enrico Cagno from Politecnico di Milano (POLIMI). Terrence, thank you for your patience and for trusting on my competences and skills as an academic. Your continuous support and advices have greatly helped me to challenge myself but also not to get lost in the labyrinth of PhD studies. Enrico, thank you for your constant direction and so needed motivation especially during the last stages of my PhD. Besides your support on academic subjects, you have taught me how to be an efficient scholar while balancing my personal life, and for this I will always remember you as one of my mentors. Second, I would like to thank the orchestrators and administrators of the EDIM programme, in which I was fortunate to be a pioneer through participating in its 1st generation. In general, my gratitude goes to many people at INDEK department in KTH and at DIG department in POLIMI who directly and indirectly supported me during my PhD journey. However, I would like to thank specially some persons. A big thank you to Mats Engwall and Cali Nuur who believed in my research potential since my admission interview and have supported me until now. Likewise, thank you to Paolo Trucco who has also continuously trusted in my research capabilities. Other members from the EDIM community that I would like to thank are Guido Micheli, Gustavo Morales, Antonio Hidalgo and Felipe Ruiz. Also, because the academic activities are only one part of PhD studies, I must acknowledge two persons who have been key to enjoy my overall EDIM experience. Kristin Lohse, thank you for helping with countless administrative process in KTH and for always having the doors of your office open when needed. Martina Sani, thank you for always having a ready to help attitude in POLIMI, openness, and above all, thanks for your true friendship. You made our stay in Milan one of the best episodes in our lives. Third, I would like to express my gratitude and admiration for all my co-authors in the papers appended in this thesis and in conference papers related with my research. Without a doubt your commitment, resources, research skills, motivation, and ideas helped me to explore new academic perspectives and ultimately to materialize this thesis. These co-authors, in addition to my two supervisors Enrico and Terrence, include: Andrea Trianni from POLIMI, Raffaella Manzini and Valentina Lazzarotti from LIUC university, Anna Öhrwall-Rönnbäck from Luleå University of Technology, Adrianni Zanatta and Javier Ramirez from Tec de Monterrey, Carmen Gonzalez and Margarita Portilla from UAM Azcapotzalco and my EDIM colleagues Anna Darmani, Nidal Dwaikat, and Marin Jovanovic. A very special recognition goes to the academics that acted as my discussants in the official seminars and presentations that I had during different stages of my PhD studies. Although their busy agendas, they all provided invaluable ideas to improve my research and ultimately this thesis. These discussants were Davide Chiaroni and Claudio Dell’Era from POLIMI, Mattia Bianchi and Robin Teigland from Stockholm School of Economics, and Johan Packendorff from KTH.
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Because money does matter when conducting research, I would like to express my gratitude to the next institutions for providing me different forms of support during my studies:
The Education, Audiovisual and Culture Executive Agency (EACEA) of European Commission under the Erasmus Mundus Action 1 program (SGA: 2011- 1531).
Both of the departments in the universities where I studied this doctoral program, INDEK at KTH Royal Institute of Technology and DIG at Politecnico di Milano
The Mexican National Council for Science and Technology - CONACYT (Grant: 312625). The Italian Ministry of Foreign Affairs under the scholarships for Mexican students
administered by the Italian Cultural Institute in Mexico City (Period 2013/2014). The Knut and Alice Wallenberg Foundation "Jubilee appropriation" (Travel grants Dnrs:
V-2015-0009 and V-2013-0015). I would like to thank my PhD colleagues and friends because without them this journey would have been certainly unbearable. So, a first thanks goes to all the EDIMers for sharing this experience with me. I am indeed fortunate to belong to the unique EDIM community. A special thanks to Raul Pulido, Seyoum Eshetu Birkie, Jing Shao, Isaac Lemus, Hakan Karaosman, Claudia Manca, Julia Lapko, and Ed Saiedi for their friendship and for always drawing a big smile on my stressed face. Besides EDIMers, I was also privileged to have other friends who made this PhD journey more stimulating and fun. Thus, thanks to Caroline Ingvarsson and Matthew Stogsdill from KTH, and to Irene Roda and Andrea Consonni from POLIMI. Needless to say, I consider some friends as the cherry on top of the cake during my studies that in one way or another have provided me with priceless support and motivation to endure and finish my PhD. I am talking about Anna Darmani, Monia Lougui, Veronica Leon, Emrah Karakaya, Jonatan Freilich, Frano Barbic, Maxim Miterev, and Nidal Dwaikat. A truthful and sincere thanks to you guys, I will always admire and remember you with great affection. Because I firmly believe that to know where you are going you must know where you come from, I would like to thank all my relatives and friends back in Mexico. Wherever I go you are always part of my values, beliefs, and ideas that I feel very proud of. Special thanks to Quique, Graciela, Alberto, Andrea, Yuri, and of course my oldest friend, my sister Laura, whose continuous encouragement helped me to endure this PhD experience. A very special and huge thanks goes to the best parents in the world, Margarita and Javier, both academics who taught me the real value of education and continuous personal development. I love you and I hope with all my heart that when I have my own kids, I can be at least half the parent and role model that you were to me. Finally, the biggest thanks of all should to go my beautiful wife, Brenda. Since the first time I met you I knew our destiny was meant to be together. This tiring, confusing, but also exciting and enriching PhD journey has been a crucial test to confirm this idea. Thank you not only for being my life partner and best friend but also for being my personal designer, photographer, travel companion, research assistant, therapist, doctor, psychologist, chef, co-author, and even my life coach. It was only thanks to your unconditional love and support during my whole PhD journey that I am standing here now. I hope that by now you already know that part of this thesis is also yours, just as my heart and my life will be yours for eternity.
// Andrés Ramírez Portilla
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List of appended papers
This thesis encompasses an introductory chapter and the subsequent seven appended papers. The papers are referred to in the text by the letter prior to each title (A-G). Paper A: Ramirez-Portilla, A. (2015) “Which one goes well with? Exploring the Link between Theoretical Perspectives and Research Contexts in Open Innovation Research”, Procedia Social and Behavioral Sciences, Vol. 213, pp. 1034 – 1039. Paper B: Ramirez-Portilla, A., Manzini, R., Lazzarotti, V., and Cagno, E. (2016) “The role of internal context characteristics on the adoption of Open Innovation: Evidence from manufacturing firms”, presented in the 12th International Conference on Industrial Engineering – ICIE), Tehran, Iran, January. Paper C: Ramirez-Portilla, A., Brown, T., and Cagno, E. (2014) “Unravelling the integration mechanisms in open innovation projects: the case of inter-organizational networks”, Journal of Global Strategic Management, Vol. 8, No. 2, pp. 82-95. Paper D: Ramirez-Portilla, A., Cagno, E. and Zanatta-Alarcón, A. (2016) “Open Food: Revisiting the role of Open Innovation actors in the Food Industry”, submitted to an international peer-reviewed journal. Paper E: Ramirez-Portilla, A., Cagno, E., and Trianni, A. (2014) “Is Innovation an enabler of Energy Efficiency? An exploratory study of the foundry sector”, Energy Procedia, Vol. 61, pp. 1191 –1195. Paper F: Cagno, E., Ramirez-Portilla, A., and Trianni, A. (2015) “Linking Energy Efficiency and Innovation Practices: Empirical evidence from the foundry sector”, Energy Policy, Vol. 83, pp. 240–256. Paper G: Ramirez-Portilla, A., Brown, T., and Cagno, E. (2016) “Open Innovation and Sustainability Performance: The case of supercars as specialized manufacturing SMEs”, submitted to Business Process Management Journal (under review)
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List of additional publications
In addition to the appended papers, I have been the author and co-author of other publications related to my research during my doctoral studies. The publications appear in chronological order. Ramirez-Portilla, A. (2013) “Project manager’s characteristics influence in the entrepreneurial process: A project-based entrepreneurship model”, DRUID Academy, Aalborg, Denmark, January. Darmani, A., Dwaikat, N., and Ramirez-Portilla, A., (2013) “20 years of scholarly research: Content and trend analysis of the journal Creativity and Innovation Management”, 22nd International Conference for the International Association of Management of Technology – IAMOT, Porto Alegre, Brazil, April. Ramirez-Portilla, A., Cagno, E., Brown, T., and Trianni, A. (2013) “Can Open Innovation practices leverage Industrial Energy Efficiency Performance?”, 6th ISPIM Innovation Symposium, Melbourne, Australia, December. Ramirez-Portilla, A., Jovanovic, M., Viveros, A., and Ramírez, J. (2014) “Exploring the creation of disruptive innovations by student start-ups through an open innovation perspective: The case of Stu:Drive”, International Conference on Research and Innovation 2014, Guanajuato, Mexico, April. Ramirez-Portilla, A., Cagno, E., and Trianni, A. (2014) “Can open innovation drive more sustainable SMEs? Evidence from energy-intensive sectors in Italy”, 1st Annual EDIM PhD Conference, Milan, Italy, June. Ramirez-Portilla, A., Brown, T., and Cagno, E. (2014) “Open Innovation in the Automotive Industry: What can carmakers’ annual reports tell us?”, 8th International Conference on Industrial Engineering and Industrial Management - CIO-ICIEOM-IIIE, Malaga, Spain, July. Ramirez-Portilla, A. (2014) “Open and Collaborative Innovation in Mature Industries: Literature Review, Synthesis, and Research Agenda”, Poster presentation at the 8th International Conference on Industrial Engineering and Industrial Management - CIO-ICIEOM-IIIE, Malaga, Spain, July. Ramirez-Portilla, A., Cagno, E., and Brown, T. (2014) “Open Innovation Practices in SMEs: The case of the Mexican supercar VUHL”, IV Symposium CONACyT fellows in Europe, Strasbourg, France, November. (In Spanish)
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Ramirez-Portilla, A., Cagno, E., and Zanatta-Alarcon, A. (2015) “The era of Open Food? Exploring the influence of collaborative and open innovation in the food industry”, 2nd Annual EDIM PhD Conference on Management Engineering, Milan, Italy, June. Viveros-Eulogio, B., Öhrwall-Rönnbäck, A., and Ramirez-Portilla, A. (2015) “Production innovation in manufacturing firms: The case of Swedish SMEs”, International Conference on Engineering Design ICED 2015, Milan, Italy, July. Ramirez-Portilla, A., Viveros-Eulogio, B., Portilla, M., Gonzalez, M.C., and Ramirez, J., (2015) “Fostering sustainability-driven innovation in tomorrow’s engineers: The case of UAM Azcapotzalco”, 32nd International Conference on Case Method Research & Application – WACRA, Odense, Denmark, July. (In Spanish) Ramirez-Portilla, A., Öhrwall-Rönnbäck, A., and Enrico Cagno (2015) “Determinants of the adoption of open innovation models: Evidence from Swedish manufacturing firms”, Open Innovation and Collaboration (OIC) Conference, Osaka, Japan, September. Ramirez-Portilla, A., Cagno, E., Brown, T., and Zanatta-Alarcón, A. (2015) “3D Printing: Intellectual Property challenges in a new industrial revolution”, 16th International CINet Conference, Stockholm, Sweden, September. Ramirez-Portilla, A., Brown, T., and Cagno, E. (2015) “Open Innovation Practices in manufacturing SMEs: The case of supercars”, 16th International CINet Conference, Stockholm, Sweden, September. Portilla-Pineda, M., Ramirez-Portilla, A., Viveros-Eulogio, B., Ramirez-Angulo, J., and Gonzalez-Cortes, M. C. (2015) “Sustainable Development and Innovation as a learning process for engineering”, International Conference on Human Sciences, Mexicali, Mexico, November. (In Spanish) Ramirez-Portilla, A., Brown, T., and Cagno, E. (2015) “Open Innovation practices and firm performance: The case of supercars manufacturers as an exemplar of open specialized SMEs”, 3rd Scandinavian Academy of Industrial Engineering and Management (ScAIEM) Conference, Copenhagen, Denmark, November.
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Table of Contents
1. Introduction ......................................................................................................................... 1 1.1. Research background ............................................................................................................... 1 1.2. Problem statement and its relevance ...................................................................................... 2 1.3. Research purpose and research questions .............................................................................. 5 1.4. Thesis outline (linking the appended papers) ........................................................................ 8 1.5. Research delimitations ........................................................................................................... 11
2. Literature and Knowledge Domains ............................................................................... 14 2.1. Innovation and OI ................................................................................................................... 14
2.1.1. Innovation and its management ......................................................................................... 14 2.1.2. Basic notions of OI ............................................................................................................ 16 2.1.3. What is new about OI? ...................................................................................................... 20 2.1.4. What is missing in OI research? ........................................................................................ 22
2.2. Choosing theoretical perspectives to study OI ..................................................................... 26 2.2.1. Available theories used in OI research .............................................................................. 27 2.2.2. Contingency theory as an ‘oldie but goodie’ for OI .......................................................... 30 2.2.3. A practice-based view of OI .............................................................................................. 33 2.2.4. OI as practices and habitual modes ................................................................................... 36 2.2.5. OI as models of interacting practices ................................................................................ 39
2.3. OI relevance for specific industrial contexts ........................................................................ 41 2.3.1. OI and manufacturing industries ....................................................................................... 42 2.3.2. OI and mature industries ................................................................................................... 44 2.3.3. Matching potential industrial contexts to study OI ........................................................... 45 2.3.4. OI and manufacturing SMEs in mature industries ............................................................ 46
3. Research Design ................................................................................................................ 50 3.1. Philosophical and methodological motivation ...................................................................... 50 3.2. Philosophical positioning and approach ............................................................................... 51 3.3. Research strategies ................................................................................................................. 52 3.4. Data collection and analysis techniques ................................................................................ 54 3.5. Research contexts and sample ............................................................................................... 58
4. Summary of Appended Papers ........................................................................................ 62 4.1. Paper A. Theoretical perspectives and contexts in OI research ......................................... 63 4.2. Paper B. Influence of the firm’s internal context in OI adoption ...................................... 65 4.3. Paper C. OI mechanisms as practices in F&B industry ...................................................... 67 4.4. Paper D. Practices by small actors in F&B industry ........................................................... 69 4.5. Paper E. OI practices and energy efficiency in foundries ................................................... 71 4.6. Paper F. OI and industrial performance in foundries ........................................................ 73 4.7. Paper G. OI and other dimensions of SMEs performance ................................................. 75
5. Results and Discussion ...................................................................................................... 77 5.1. Context matters in OI research and practice ....................................................................... 77 5.2. OI adoption by ‘small’ actors within and around mature manufacturing industries ..... 80 5.3. Different forms OI practices .................................................................................................. 83 5.4. The role of OI practices on diverse performance dimensions ............................................ 87 5.5. The ‘dark side’ of OI practices .............................................................................................. 91
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5.6. The unexpected implications of opening up innovation in brief ........................................ 96
6. Conclusions and Future Research ................................................................................... 97 6.1. Revisiting the purpose and research question ...................................................................... 97 6.2. Research contribution ............................................................................................................ 99
6.2.1. Implications for theory ...................................................................................................... 99 6.2.2. Implications for practice and policy ................................................................................ 102
6.3. Suggestions for future research ........................................................................................... 104
Appendixes .............................................................................................................................. 129 Appendix A – Interview guide for case study of OI projects in the food industry .................... 129 Appendix B – Interview guide for pilot case studies of small and medium-sized manufacturers of supercars ...................................................................................................................................... 131 Appendix C – Questionnaire for case studies of small and medium-sized foundries ................ 135 Appendix D – Questionnaire for survey of small and medium-sized manufacturers of supercars ........................................................................................................................................... 145
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Lists of figures and tables
List of figures FIGURE 1-1. AN OVERVIEW OF THE MANUFACTURING SECTOR BY TYPE OF INNOVATION ............................................ 3 FIGURE 1-2. PAPER ALIGNMENT THROUGH THE ‘BLUE THREAD’ OF OI PRACTICES ...................................................... 8 FIGURE 2-1. CLOSED VERSUS OPEN INNOVATION MODELS ......................................................................................... 19 FIGURE 2-2. LINKING THEORETICAL PERSPECTIVES AND RESEARCH CONTEXTS IN OI STUDIES ................................. 25 FIGURE 2-3. CAPABILITIES AND ACTIVITIES INTERLINKED UNDER AN OI APPROACH ................................................ 39 FIGURE 2-4. OI MODELS BASED ON THE POSSIBLE VARIETY ON THREE KEY ELEMENTS ............................................. 41 FIGURE 2-5. OPEN INNOVATION POTENTIAL IN DIFFERENT INDUSTRIES ..................................................................... 43 FIGURE 2-6. INDUSTRIAL CONTEXTS TO STUDY OI BASED ON ITS MATURITY AND TECHNOLOGY INTENSITY. ........... 46 FIGURE 3-1. VISUAL SUMMARY OF THE RESEARCH STRATEGIES USED IN THE THESIS PAPERS ................................... 53 FIGURE 3-2. PROPORTION OF ACTORS INVESTIGATED FOR THE DIFFERENT STUDIES IN THE THESIS ........................... 58 FIGURE 3-3. PROPORTION OF LARGE, MEDIUM, AND SMALL MANUFACTURERS OF SUPERCAR ................................... 60 FIGURE 3-4. NAMES AND LOCATION OF SMMS SAMPLED FOR PAPER G .................................................................... 61 FIGURE 5-1. CONTINUUM OF APPLICABILITY OF OI PRACTICES IN INDUSTRIAL CONTEXTS ........................................ 80 FIGURE 5-2. POTENTIAL INNOVATION ACTORS TO BE INVOLVED IN AN ‘OPEN INDUSTRY’ ......................................... 82 FIGURE 5-3. REVISITING THE LATENT VARIETY OF OI ADOPTION .............................................................................. 87 FIGURE 5-4. MAPPING THE ‘DRIVING’ INFLUENCE OF OIPS ON DIVERSE PERFORMANCE DIMENSIONS ....................... 91 FIGURE 6-1. PROSPECTIVE APPLICABILITY OF THE THESIS RESULTS TO OTHER INDUSTRIES .................................... 101 List of tables TABLE 1-1. FIT BETWEEN THE THESIS OBJECTIVES, RESEARCH QUESTIONS, AND PAPERS. ........................................... 7 TABLE 1-2. INFORMATION ABOUT THE SEVEN PAPERS APPENDED IN THIS THESIS ...................................................... 10 TABLE 2-1. SOME CATEGORISATIONS OF INNOVATIONS ACCORDING TO SELECTED AUTHORS ................................... 15 TABLE 2-2. PAST TRENDS AND POTENTIAL RESEARCH DIRECTIONS BASED ON OI LITERATURE ................................. 23 TABLE 2-3. THE MOST RELEVANT LITERATURE REVIEW IN OI ACCORDING TO ITS CITATION IMPACT ........................ 24 TABLE 2-4. POTENTIAL THEORIES AND THEORETICAL PERSPECTIVES TO STUDY OI .................................................. 27 TABLE 2-5. TERMS COMMONLY ASSOCIATED TO THE CONCEPT OF ‘PRACTICE’ ......................................................... 34 TABLE 3-1. SUMMARY OF KEY ELEMENTS OF THE THESIS RESEARCH DESIGN ............................................................ 57 TABLE 4-1. LEGEND OF KEY ELEMENTS IN A PAPER USEFUL AS A VISUAL SUMMARY ................................................ 62
xviii
Abbreviations
BAT – Best Available Technology BEE – Barriers to Energy Efficiency CIS – Community Innovation Survey CV – Content Variety (in Open Innovation) CT – Contingency Theory EE – Energy Efficiency ECP – Economic Performance ENP – Environmental Performance FP – Firm Performance F&B – Food and Beverage Industry IDP – Industrial Performance IM – Innovation Management INNO – Innovativeness level INP – Innovation Performance IPV – Innovation Phase Variety (in Open Innovation) IRD – Internal Research and Development (R&D) ITM – Innovation and Technology Management LR – Literature Review OEM – Original Equipment Manufacturer OI – Open Innovation OIM – Open Innovation Models OIP – Open Innovation Practices OIPR – Open Innovation Project OIS – Open Innovation Survey PV – Partner Variety (in Open Innovation) RS – Research Strategy SEC – Specific Energy Consumption SME – Small and Medium-sized Enterprise SMMS – Small and Medium-sized Manufacturer of Supercars SOP – Social Performance
Introduction
1
1. Introduction
1.1. Research background
Currently, the world is changing at an astounding pace due to science, technology and innovation. This pace is so astonishing that some people claim that the world is not experiencing an era of changes, but the change of an era (Muñoz-Gutierrez, 2014). The economist Lester Thurow (1996) predicted the weight that technology and knowledge were going to have on the economic system during the first decades of this century. For him, while everything else falls outside the equation of competitiveness, knowledge and capabilities are the main sources of a competitive and sustainable advantage. Thus in the current knowledge economy, the capacity for innovation based on knowledge is essential for productivity and competitiveness of firms. Even though the process of innovation can be challenging, if managed correctly it can provide a competitive advantage for firms (Brem, Maier, & Wimschneider, 2016). Thus, innovation is a key element in economic growth, technological progress, and sustainability; it is at the centre of industry, academia, government, and society (European Commission, 2010). However, the way in which innovation is managed and achieved has notably changed during the previous years. More than ever organisations are using more collaborative approaches driven by megatrends such as cooperation, globalisation, digitalisation, and sustainability (De Backer & Cervantes, 2008; European Commission, 2013a; Nordström & Schlingmann, 2014). In particular, firms from mature industries in the manufacturing sector are experiencing radical changes due to increasingly innovative approaches and technologies to produce goods but also services (Anderson, 2012). This change in the manufacturing sector possibly signals the beginning of a paradigm shift (Kuhn, 1963) and thus, the start of the next production revolution (De Backer, 2015). Coinciding with this revolution, there is an increasing trend on collaborative approaches and also on the generation of services by manufacturing firms in mature industries. Nevertheless, collaborative business models and strategies merging services with production, e.g. product-service systems, should not be seen solely as challenges but also as opportunities for manufacturing firms (Isaksson, Larsson, & Öhrwall-Rönnbäck, 2009). This indicates that the focus of research and practice should not be asking whether manufacturing or services are better for the economy, but rather how do firms in these sectors together with other actors collaboratively innovate to continue contributing to economic growth (OECD, 2015). In addition, in this new industrial revolution, the manufacturing world is characterised as being digitalised and personalised (European Commission, 2013a; Frey & Osborne, 2013; Vallistu, 2013). According to Anderson (2012) we will soon see the end of the monopoly of mass production by large manufacturing firms. Accordingly, in this new era novel technologies and approaches to innovate diffuse more rapidly than before across all types of manufacturing industries. This means that this phenomenon occurs in low-tech industries such as foundries, to
The unexpected implications of opening up innovation
2
more advanced but still mature industries such as food. It seems then that the democratisation of innovation and new technologies (von Hippel, 2005) is fostering innovators who do not necessarily need to have high levels of knowledge and experience, but just the appropriate capabilities and skills obtained from different sources in various ways. Most of the above mentioned ideas converge in one clear effect of this revolution. This effect is that due to the diffusion of new technologies and innovation practices more quickly than before; manufacturing firms in mature industries need to continue innovating or face extinction. In the past, many manufacturing firms did not need to be innovative to survive crises since they based most of their survival strategies on having competitive productivity. Nevertheless in recent times, manufacturing firms regardless of limited resources are changing their strategies and approaches based on different knowledge inputs across a broad set of technologies as a key aspect to survive, profit, and remain competitive (De Backer, 2015). However, adopting new technologies should not be confused as a key aspect to succeed (Muñoz-Gutierrez, 2014). Instead, the focus should be directed towards an organisation’s capacity to innovate based on knowledge and new approaches that support its capacity to continuously improve (Boer, Kuhn, & Gertsen, 2006). This is where certain innovation practices adopted by a firm could have a differential and key role in its survival, growth, and evolution.
1.2. Problem statement and its relevance
Considering the ideas of a new industrial revolution driven by a knowledge-based era (Anderson, 2012; Koen De Backer, 2015; Muñoz-Gutierrez, 2014), manufacturing firms have been open to using more approaches to innovate and remain competitive (Markillie, 2012). A clear case has been the widespread phenomenon used by manufacturing firms of all sizes and most industries to adopt more open collaborative practices to discover, explore, and exploit innovations within and outside the firm’s boundaries (Idrissia, Amaraa, & Landrya, 2012; Laursen & Salter, 2006; Lazzarotti, Manzini, & Pellegrini, 2010; Tidd, 2013). This phenomenon, coined more than a decade ago as the Open Innovation model (Chesbrough, 2003a), has helped to frame and understand numerous innovation approaches in practice, but it has also gradually become an established research field (Huizingh, 2011; West, Salter, Vanhaverbeke, & Chesbrough, 2014). However, Open Innovation (OI) still has some important practical and theoretical gaps to be addressed. From a practical viewpoint, although it is possible to find countless success stories of firms using OI, it is also common to find many firms that are not familiar with this model. Some internal and external context characteristics of a firm such as size or industry (Huizingh, 2011) could contribute to the lack of recognition of OI as a useful model to manage innovation while collaborating with outside partners. Additionally, firms might be more concerned about innovating with their products and processes rather than organisational practices. Figure 1-1 taken from a recent report by the OECD (2014) depicts these two ideas based on the results from the Community Innovation Survey from 2010. The chart compares the percentage of
Introduction
3
innovative firms in Information and Communications Technology (ICT) manufacturing sector with the ones in total manufacturing sector by type of innovation.
Figure 1-1. An overview of the manufacturing sector by type of innovation
In this chart we can see that even though firms belong to the same sector, i.e. manufacturing, they still show different trends in the number of innovative firms. In this case, firms belonging to the information economy sector including firms manufacturing computer, electronic and optical products are more innovative than the average more mature manufacturing firms. Correspondingly, while 54% of firms in ICT manufacturing engaged in collaboration, only 34% of innovative firms in the overall manufacturing sector have embraced collaboration (OECD, 2014). Also, we can see that marketing and organisational innovations are being implemented less than product or process innovations. According to the OECD, organisational innovation is the implementation of a new organisational method in a firm´s business practices, workplace organisation or external relations (OECD, 2005). Therefore, even though models to manage innovation, such as OI, are being developed and proposed in the industry, many firms prefer to focus on other more tangible innovation outcomes. From a theoretical viewpoint, examining different streams of literature we can see that OI can be different in nature, context, and scope depending on the perspective considered. Nonetheless, OI has been depicted consistently as a model to manage innovation with multiple flows of knowledge and ideas. In this sense, OI has helped firms to rethink and redesign their innovation process by highlighting the opportunities and advantages to acquire and explore knowledge from external sources - the inbound process - and to exploit knowledge via the commercialisation of ideas and technology - the outbound process - (Chesbrough, 2003a; 2003b). In academia, research on OI has gained incredible momentum, albeit with some detractors (e.g. Trott & Hartmann, 2009), but in general researchers believe that the best of OI is still to come (West et al., 2014). Nevertheless, in parallel with this enthusiasm, the community of Innovation Management (IM) researchers and in general of IM professionals (a good example is ISPIM1) seem to agree that a tighter theory on OI is still needed and this can only be achieved by being more critical when investigating OI (Tidd, 2014).
1 The International Society for Professional Innovation Management (ISPIM) is a network of researchers, industrialists, consultants and public bodies who share an interest in IM. It is the oldest, largest and most active innovation association in Europe.
The unexpected implications of opening up innovation
4
Amongst the different questions that are still not consistently answered by researchers is whether an organisation should adopt OI or not. Aligned with this interrogation, a firm might be unsure if the benefits obtained by adopting OI are solely related to increasing levels of innovation or whether it could have other multiple benefits (Elmquist, Fredberg, & Ollila, 2009; Giannopoulou, Yström, Ollila, Fredberg, & Elmquist, 2010; Schroll & Mild, 2012; Wikhamn & Wikhamn, 2013). In this regard, numerous researchers have studied the adoption of OI by firms and its relation to different strategic and organisational results such as innovation and economic performance. However, to date, researchers have not found consistent results regarding the influence of OI on the overall performance of firms (Gambardella & Panico, 2014; Manzini et al., 2013; Mazzola, Bruccoleri, & Perrone, 2012; West et al., 2014). Moreover, studies have rarely examined the effects of different configurations of OI practices on dimensions of firm performance other than economic or innovation indicators. So it can be said that even though numerous researchers have studied the adoption of OI and its relation to organisational results, very few studies have focused on investigating the positive influence of different OI approaches on multiple strategic dimensions of firm performance. These drawbacks are relevant because they can hinder the diffusion of OI practices by questioning whether it is convenient for every type of actor even with limited resources such as small and medium-sized enterprises (SMEs) in mature manufacturing industries to adopt OI or not. Considering the above, one of the main theoretical problems with OI is its potential to trigger paradoxes with common innovation ideas and conceptions (Bogers, 2011; Laursen & Salter, 2005; 2014; West & Gallagher, 2006). For instance, in principle it could be said that the relation between successful innovations and profit is practically a tautology (Maital & Seshadri, 2012). Therefore, firms excelling at innovation levels should also be more profitable than less innovative firms. Nevertheless, several literature reviews (see Table 1 from Paper A: Ramirez-Portilla, 2015) have remarked that in various settings it is not always the case that firms adopting OI practices and approaches are also more profitable. Another known example of a paradox is the openness paradox (Laursen & Salter, 2005; 2014) related to finding the equilibrium between the knowledge shared and protected simultaneously. From a traditional organisational perspective this issue is logical if considering the idea of a firm wanting to develop or acquire ‘VRIN’2 resources to sustain its competitive advantage (Barney, 1991). Thus, if a firm opens too many of its boundaries and shares too much knowledge, it could risk losing or diluting its unique resources. This rationale could be even more ingrained in managers from SMEs who carefully guard their current resources together with a very specialised and deep knowledge (Parida, Larsson, Isaksson, & Oghazi, 2011). Together these and other paradoxes signal that there could be some built-in trade-offs between OI and multiple dimensions of firm performance, especially within smaller actors.
2 According to Barney (1991) a resource is a source of sustainable competitive advantage when it fulfils the criteria of the VRIN framework: Valuable, Rare, Inimitable, and Nonsubstitutable.
Introduction
5
Additional stimulating gaps in research can be found if considering the largely accepted assumption that OI and its related concepts are highly context dependent (Huizingh, 2011). This idea has already guided researchers to better understand when, where, how, and why OI should be adopted. But it also opens the door to studying OI under a contingency perspective (e.g. Luthans, 1973) where investigating the influence of context characteristics is a key aspect to further advance a robust OI theory (Tidd, 2014). In this regard, just as the context can greatly influence a project (Engwall, 2003), the context characteristics of a firm can also influence the endeavour of adopting OI (Lazzarotti, Manzini, & Pellegrini, 2011; Manzini et al., 2013). Considering the above, my thesis can be summarised as follows. To contribute building an OI theory and to provide firms with wide-ranging and rigorous evidence of the benefits of adopting OI, researchers should confirm the relevance of certain context elements with a multi-perspective approach. These elements include but are not limited to firm size, age, industry, sector, nature of products, organisational mechanisms, strategic capabilities, and firm resources. However, above all, the key elements to focus on are the type of activities actually practiced by firms, because these could greatly influence the degree of adoption of OI but also several dimensions of firm and industrial performance obtained from this adoption.
1.3. Research purpose and research questions
The argument above answers the call for more evidence about how firms can combine different ways of managing openness (Dahlander & Gann, 2010) and understanding how this openness relates to different dimensions of performance while being influenced by key contextual factors (Bengtsson et al., 2015; Lazzarotti, Manzini, & Pellegrini, 2015). Therefore based on all the previous ideas, the purpose of this thesis was to investigate from multiple perspectives the role that adopting OI practices and approaches could have on different dimensions of firm performance, while highlighting the context dependency of OI. Aligned to this purpose, multiple theoretical perspectives were examined from several research contexts that although diverse relate to organisations and actors operating in mature industries from the manufacturing sector. It is important to clarify that a multi-perspective approach was chosen because OI is a complex multi-dimensional phenomenon that compels us to combine different perspectives to better understand it (Vanhaverbeke & Cloodt, 2014). Therefore, in this thesis a multi-perspective approach was considered as a broad term that encompasses multiple and heterogeneous viewpoints, representations, theoretical perspectives, research contexts, level of analysis, and even research methodologies. Thus this approach could help better understand the benefits that firms and other actors could experience by adopting and implementing Open Innovation. Considering all these previous ideas, the specific objectives of this thesis were:
• To identify and verify if some of the main assumptions proposed about OI also apply to few but relevant understudied industrial contexts;
• To propose and describe different forms of characterising practices related to open and collaborative approaches used by different actors;
The unexpected implications of opening up innovation
6
• To explore and explain the link between the adoption of OI concepts and varied performance indicators relevant for specific organisational scenarios.
To achieve these objectives together with the research purpose, this thesis specifically sought to answer the following main research question (MRQ):
To what extent are OI practices adopted by firms and other actors in unexplored mature manufacturing industries and which are the unidentified roles that these practices play in
relation to different dimensions of firm and industrial performance? To support answering the MRQ, three additional research sub-questions (RSQ1, RSQ2 and RSQ3) were proposed and answered through different studies. It should be noted that the specific research questions included in each appended paper (A to G) were different from the three RSQs. This was due to the more specific focus of the research questions in each paper usually suggested for a conference or journal publication. Instead, the RSQs while still focused, are more related to the overall thesis purpose. In any case, it is possible to interrelate all the research questions of each paper with the thesis’ RSQs and consequently with the MRQ. Having clarified this, the three RSQs are listed below:
§ RSQ1: How relevant are context and contextual factors to understand the adoption and practice of OI?
§ RSQ2: How can OI be characterised as varied forms of practices adopted by different types of innovation actors?
§ RSQ3: To what degree can OI practices influence innovativeness and other performance indicators relevant to certain industrial contexts?
With the three RSQs, the three objectives, and the appended papers, this thesis sought to address the research problem and answering the MRQ from different angles. Although this could seem intricate at first sight, when considering the overall picture of the thesis, all the elements fit together with only one purpose. The full picture of this thesis is better depicted in Table 1-1 which helps summarise the key aspects of each appended paper and its interrelation with the thesis’ key elements. In addition, this table shows how different theoretical perspectives together with OI concepts have been used throughout the different papers to better understand OI (Vanhaverbeke & Cloodt, 2014). This approach was adopted to achieve the thesis objectives in conjunction with the use of empirical data collected with a combination of methods used in every paper (and explained in Chapter 3). Such a combination of several methods has been suggested for answering research questions in studies researching complex phenomena (Brewer & Hunter, 2006). Finally, the use of several methods in a research project is also suggested to study relations between elements generating innovation at various levels in order to disclose patterns promoting innovation in organisations and systems (Johannessen, 2009). The next section details how the seven appended papers are linked with each other and linked to this thesis.
Introduction
7
Table 1-1. Fit between the thesis objectives, research questions, and papers.
Tabl
e 1-
1. F
it be
twee
n th
e th
esis
obj
ectiv
es, r
esea
rch
ques
tions
, and
pap
ers
Lite
ratu
re
Rev
iew
(L
R)
APu
blis
hed
x
O
Surv
eyB
Pres
ente
dx
x
OO
Cas
e st
udy
CPu
blis
hed
x
x
O
LR +
Cas
e st
udy
DSu
bmitt
ed
xx
O
EPu
blis
hed
x
x
O
FPu
blis
hed
x
x
O
Surv
eyG
Und
er R
ev.
xx
x
O
O
Res
earc
h Q
uest
ion
(s)
RSQ
1H
ow re
leva
nt a
re c
onte
xt
and
cont
extu
al fa
ctor
s to
unde
rsta
nd th
e ad
optio
n an
d pr
actic
e of
OI?
MR
Q:
To w
hat e
xten
t are
Ope
n In
nova
tion
prac
tices
ado
pted
by
firm
s and
oth
er a
ctor
s in
unex
plor
ed m
atur
e m
anuf
actu
ring
indu
strie
s and
whi
ch a
re th
e un
iden
tifie
d ro
les
that
thes
e pr
actic
es p
lay
in re
latio
n to
diff
eren
t dim
ensi
ons o
f firm
and
indu
stria
l pe
rfor
man
ce?
RSQ
2H
ow c
an O
I be
char
acte
rised
as v
arie
d fo
rms o
f pra
ctic
es a
dopt
ed
by d
iffer
ent t
ypes
of
inno
vatio
n ac
tors
?
RSQ
3To
wha
t deg
ree
can
OI
prac
tices
influ
ence
in
nova
tiven
ess a
nd o
ther
pe
rfor
man
ce in
dica
tors
re
leva
nt to
cer
tain
in
dust
rial c
onte
xts?
Pape
rPa
per
Stat
us
Con
tigen
cy
and
cont
ext
depe
nden
cy
OI M
odel
s (p
artn
er +
ph
ase
+ co
nten
t)
Org
aniz
atio
-na
l the
ory
Use
rs a
nd
com
mun
ities
Prac
tice-
base
d vi
ew
• To
iden
tify
and
verif
y if
som
e of
the
mai
n as
sum
ptio
ns p
ropo
sed
abou
t O
I als
o ap
ply
to fe
w b
ut
rele
vant
und
erst
udie
d in
dust
rial c
onte
xts.
• To
prop
ose
and
desc
ribe
diffe
rent
form
s of
char
acte
risin
g pr
actic
es
rela
ted
to o
pen
and
colla
bora
tive
appr
oach
es
used
by
diffe
rent
act
ors.
• To
expl
ore
and
expl
ain
the
link
betw
een
OI c
once
pts
and
prac
tical
org
anis
atio
nal
scen
ario
s and
firm
pe
rfor
man
ce.
Thes
is O
bjec
tives
Ope
n In
nova
tion
Prac
tices
Mul
tiple
C
ase
stud
ies
Res
earc
h D
esig
n
Ope
n In
nova
tion
(OI)
+ o
ther
theo
retic
al p
ersp
ectiv
es
The unexpected implications of opening up innovation
8
1.4. Thesis outline (linking the appended papers)
This thesis is organised as a compilation of papers (A to G) with a cover essay. First, the cover essay is a manuscript that stands on its own and throughout it there are several connections to the appended papers supporting the consistency of this thesis. Figure 1-2 shows the interrelatedness of the appended papers emphasising OI practices as the ‘red thread’ providing a coherent thesis flow through five research stages.
Figure 1-2. Paper alignment through the ‘blue thread’ of OI practices
Second, although different in scope, each appended paper contributes cumulatively to the thesis as explained below. Paper A was written to stress the importance that both context and contingency perspectives can have on the practical adoption of OI but also on the theories that can be used to study and understand it. Although this paper was published at a later stage of my studies, the idea about investigating the relationship between context and theory in OI started from the project’s conception. In addition, paper A provided justification for the context and theories studied in subsequent papers based on a systematic review of the most relevant Open Innovation literature.
Paper B jumps from the theoretical side to the empirical one by using data from a tailor-made OI Survey collected between 2011 and 2013. This paper had a general research context because of the 240 manufacturing firms studied from different ages, sizes and industries. Yet, the paper focused on a triad of OI elements (varieties). This combination of elements provided an appropriate setting to study the relevance of a contingency perspective in mature manufacturing industries by focusing on the internal context characteristics. The findings of this paper provided empirical evidence showing that both industry (external context characteristic) and firm size (internal context characteristic) matter in the adoption of OI, especially for medium-size manufacturing firms. Consequently, although examining the OI phenomena in large firms was not discarded from subsequent studies, this paper paved the way to focus on manufacturing SMEs. In Paper C while the research context was narrowed to the food industry, OI practices were characterised and studied as integration mechanisms. These mechanisms considered as formal and informal practices under several views from organisational theory, provided some insights to understand how firms in the food industry implement OI projects with universities as close partners. Important findings of this paper showed that a small innovation intermediary is a key actor supporting most of the integration mechanisms used as common practices in the OI projects. This situation also provided a clear indication that the adoption and diffusion of Open Innovation in certain mature industries do not depend solely on established firms but also on other smaller actors. Considering the ideas above, paper D explored the relevant role that small actors practicing collaborative and open initiatives can play in influencing innovation in the food industry. Thus, in this paper it was necessary to consider the perspective of community and users adopting and driving OI practices. The results showed that contrary to most literature portraying OI in the food industry, large firms were not the only actors who can start OI practices. Instead, communities of users and consumers (citizens in general) can use OI practices and related approaches to have an impact in the overall innovation level of the food industry. Thus, paper D provided another view of how Open Innovation practices (OIPs) can be characterised as collaborative initiatives not necessarily driven by large firms in a mature industry, but also by other potential innovators. Papers E and F had a strong connection since both investigated the relation of OI practices adopted in foundries and its levels of energy efficiency (EE). However, each paper had a slightly different aim related to the thesis. More specifically, paper E initially proposed to characterise OI practices as three types of interlinked innovation activities, i.e. internal research and development (IRD), inbound (INB) and outbound (OUT) practices. Also, it provided preliminary evidence through a few pilot case studies supporting the idea that these practices can influence innovativeness levels (INNO) and other performance indicators relevant to the foundries such as EE. Moreover, in small and medium-sized foundries the EE levels are closely linked to the firm performance. Therefore some of the conclusions in this paper extend the pilot case studies used to understand if OI practices can impact overall industrial
The unexpected implications of opening up innovation
10
performance in foundries. Thus, paper F extended the number of cases studied providing more robust evidence about the improvement of EE indicators due to the adoption of OI practices. Consequently, paper F also provided support to answer the RSQ3 since it showed that OI practices can influence INNO and also EE which is an extremely important performance indicator in the foundry industry. Overall, both papers E and F directly suggested (and provided preliminary evidence) that OI practices could influence environmental indicators and thus probably also sustainability in firms. Finally, paper G integrated most of the ideas, views, and findings from the previous papers. Through a survey of small and medium-sized carmakers, it explored the influence of OI models and practices on different dimensions of firm performance. Thus, besides its integrating goal, paper G contributed to the thesis by providing robust evidence that OI practices and models can influence INNO but also the sustainability performance of specialised manufacturing SMEs. More specifically, even though the sustainability dimension of economic performance (ECP) is not significantly improved by adopting OI, the findings showed that adopting OI practices can positively influence both environmental performance (ENP) and social performance (SOP). A summary of the strategy and channels used to disseminate and publish the seven appended papers is shown in Table 1-2.
Table 1-2. Information about the seven papers appended in this thesis
Paper Publication (strategy) details
A
- Ramirez-Portilla, A. (2015) “Which one goes well with? Exploring the Link between Theoretical Perspectives and Research Contexts in Open Innovation Research”, Procedia Social and Behavioral Sciences, Vol. 213, pp. 1034 – 1039. - Special issue from the 20th International Scientific Conference Economics and Management – ICEM 2015.
B
- Ramirez-Portilla, A., Manzini, R., Lazzarotti, V., and Cagno, E. (2016) “The role of internal context characteristics on the adoption of Open Innovation: Evidence from manufacturing firms”, presented in the 12th International Conference on Industrial Engineering (ICIE), Tehran, Iran, 2016.
C
- Ramirez-Portilla, A., Brown, T., and Cagno, E. (2014) “Unravelling the integration mechanisms in open innovation projects: the case of inter-organizational networks”, Journal of Global Strategic Management, Vol. 8, No. 2, pp. 82-95. - A previous version of this paper was presented in the 4th International Conference on Technology, Innovation, and Business Management in Istanbul, Turkey, 2014.
Introduction
11
Paper Publication (strategy) details D
- Ramirez-Portilla, A., Cagno, E. and Zanatta-Alarcon, A. (2015) “Open Food: Revisiting the role of Open Innovation actors in the Food Industry”, submitted to an international peer-reviewed journal. - A previous version of this paper was presented in the 2nd Annual EDIM PhD Conference on Management Engineering, Milan, Italy, 2015.
E
- Ramirez-Portilla, A., Cagno, E., and Trianni, A. (2014) “Is Innovation an enabler of Energy Efficiency? An exploratory study of the foundry sector”, Energy Procedia, Vol. 61, pp. 1191 –1195. - Special Issue from the 6th International Conference on Applied Energy – ICAE, Taipei, Taiwan, 2013.
F
- Cagno, E., Ramirez-Portilla, A., and Trianni, A. (2015) “Linking Energy Efficiency and Innovation Practices: Empirical evidence from the foundry sector”, Energy Policy, Vol. 83, pp. 240–256. - Special issue on Challenges for R&D and Innovation in Energy. - A previous version of this paper was presented in the 1st EDIM PhD Conference, Milan, Italy, 2014.
G
- Ramirez-Portilla, A., Brown, T., and Cagno, E. (2015) “Open Innovation and Sustainability Performance: The case of supercars as specialized manufacturing SMEs”, submitted to Business Process Management Journal (under review) - Special Issue on Implementing Open Innovation. - A previous version of this paper was presented in the 16th International CINet Conference, Stockholm, Sweden, 2015.
1.5. Research delimitations
Simply stated, four aspects have mainly restricted the scope of this research: the time limitation, the availability of data, the methodological output, and the theoretical stance. While it is relevant to explain all these aspects, the selected theoretical position is emphasised at the end of this section since it greatly delimits and guides most parts of this research project. First, the aspects of availability of time and data are obviously intertwined. Thus, a correlation between the period of time to collect data and the data actually collected and analysed is expected. In the case of this project, there was an implicit trade-off between the available time allocated for each study and the amount (i.e. breadth and depth) of the data obtained. Considering that part of the thesis’ purpose was to use a multi-perspective approach to analyse OI, it was considered appropriate to conduct several studies with limited time frames. In
The unexpected implications of opening up innovation
12
addition, these numerous studies also provided an opportunity to practice and improve different data collection strategies and consequently various analysis methods and techniques. Second, although this thesis provides a specific contribution to methods in OI literature (explained in section 6), the extent of the methodological outputs is clearly delimited. Therefore, the scope of this research does not include the development of a comprehensive measurement instrument to gauge the degree of openness or the level of collaborative INNO. Likewise, even if some of the instruments to collect data share some similarities (see e.g. Appendixes B, C, and D) the intention is not to propose a generic approach to measure and evaluate OI practices applicable to all type of firms in mature industries. In fact, proposing such an approach would directly contradict one of the key thesis idea about the importance and implications of OI being highly context dependent (Huizingh, 2011; Tidd, 2014). Similarly, the aim of this project does not include testing the results of a previous OI framework on a massive sample of firms or other innovation actors. Undeniably, it would have been desired to ultimately propose a new or revised framework compatible with OI and useful for certain firms in a specific industry. Actually, because an accepted and inclusive Open Innovation measurement instrument applicable for all mature or manufacturing industries has not been recognised thus far, this would have been an interesting research goal. However, due to the limited scope and resources of this doctoral project, these types of challenging and ambitious research outputs were not possible. Third, and most importantly, as shown in one of the studies included in this thesis (paper A), OI has been studied and thus, continuously developed, together with numerous theoretical perspectives. Therefore, it would be complicated and to some extent confusing to apply all of them in one single research project. For this reason, this research considers mainly a handful of theoretical perspectives with the aim to make a clearer and more focused contribution. In this regard and as explained before, part of the objectives of this thesis are to extend the understanding of the OI model and not specifically suggest a new model or complementary framework. On the other side and from a pragmatic viewpoint, even if no new frameworks or theories are produced within a specific research project, it is equally relevant and valuable to actually operationalise already proposed ones (see e.g. Brown, Davidsson, & Wiklund, 2001). In this regard, this thesis attempted to operationalise, extend, and push forward the idea of the implementation and adoption of OI with a practice-based view together with other more recognised theoretical perspectives. Even if a detailed delimitation and justification of the theoretical perspectives used in this thesis are presented in section 2, some clarifications here are appropriate. For instance, because the focus of this thesis was on the role of adopted OI practices, the research scope did not analyse the dynamics of the studied mature industries in the manufacturing sector, i.e. food, foundries, automotive, among others. In any case, in some of the appended papers the relation between adopting OI and the dynamics of the studied industries is mentioned together with the consequences on the nature of product and process innovations (Abernathy & Utterback, 1978; Utterback, 1994). However, the reason to not focus solely on theories or the patterns or
Introduction
13
dynamics of industrial innovation is because first, a great amount of the empirical data collected during the studies did not focused solely on technological innovation (Abernathy & Utterback, 1978) but mainly on organisational innovation characterised as innovation practices (OECD, 2005). Second, I believe basic and fundamental discussions about OI in under researched industries should be addressed first before jumping into more complex debates. However, I should also clarify that this thesis does not neglect the contribution of these other perspectives to understand the role of OI in mature industries. For example, much of the work of Abernathy (1978) and Utterback (1994) was based on a large amount of data from different manufacturing mature industries, including automotive. Therefore, even if none of the studies in this thesis focused solely on large firms (e.g. large carmakers), it could be possible to revisit ideas such as ‘dominant design’ and its relation with government regulations. In fact, some SMEs are increasingly adopting OI practices to incubate some of the most radical innovations in new vehicles (Dodourova & Bevis, 2012); however, disentangling the dynamics of product (open) innovation in the chosen industries falls outside the scope of this thesis. Similarly, even though in one of the appended papers (paper C) the perspective includes mechanisms from organisational theorists, this thesis was not built using these theories as a key element. Thus, while it is recognised the possibility to investigate OI with organisational theories e.g. organisational design (Tushman, Lakhani, & Lifshitz-Assaf, 2012), some limitations are also foreseen with this choice. For instance, even though theories such as the evolutionary theory of organisations (Nelson & Winter, 1982), or its antecedents (Cyert & March, 1963), could be useful to explain innovation-related phenomena, its stress on the emergent and path-dependent nature of organisational activities could blur the emphasis on the new and actual adoption and practice of OI in the studied firms. In addition, a great number of moderators could affect the interaction, communication, and coordination used for the organisational structures and activities (Palmié et al., 2015) which in turn could notably broaden the scope of this research project. Hence, to maintain the focus of this research project, limiting the various theoretical perspectives chosen to investigate the role of OI practices was deemed appropriate.
The unexpected implications of opening up innovation
14
2. Literature and Knowledge Domains
2.1. Innovation and OI
2.1.1. Innovation and its management
Today, people use the concept of innovation indiscriminately to refer to many different things. Fortunately, from a scholar viewpoint it seems that researchers have agreed that innovation can be both a process and an outcome (Crossan & Apaydin, 2010; Maital & Seshadri, 2012; Tidd & Bessant, 2014). Based on this agreement defining innovation can be more straightforward. A good example is the definition provided by Tidd and Bessant (2014, p. 19) who mentioned that ‘innovation is the process of turning ideas into reality and capturing value from them through four key phases namely search, select, implementation, and capturing value’. Even though this definition narrows the concept to only four key phases, the important message is that innovation is a process that involves a set of other activities that can be practiced by different types of actors. Reflecting on these ideas, innovation is considered mainly as a process rather than an outcome in this research project. Therefore, in this thesis innovation is any change based on knowledge that generates and captures value through a series of systematic stages. Conversely, defining value could be more complex. Its definition could range from concrete notions such as a function of the features of an artefact or offer divided by its related costs, to more abstract ideas in different disciplines (see e.g. Bowman & Ambrosini, 2000). In any case, the importance lies on reflecting not only on the definition of value but in its general purpose of being a desired outcome when involved in an innovation process. In addition, if talking about value as an outcome it would be unfair not to mention the idea of innovation as an outcome. Thus, because any process should have a related output, when talking about innovation it is possible to talk about the kinds of opportunities to create change commonly known as type of innovations (Tidd & Bessant, 2014). For the sake of recognising taxonomies of innovations, Table 2-1 lists a handful of available categorisations of innovations according to some renowned authors. Moreover, if innovation is a process involving different activities and practices during a determined number of phases, it could be assumed that each phase should have its own related activities. Consequently, it is possible to talk about a larger number of activities, also labelled and categorised as techniques, tools, methods, resources, and mechanisms to manage innovation that if implemented in a regular manner can become practices within an organisation (Hidalgo & Albors, 2008).
Literature and Knowledge Domains
15
Table 2-1. Some categorisations of innovations according to selected authors
Types of innovations Schumpeter (1947) Abernathy and Utterback (1978)
• New products • New methods of production • New sources of supply • The exploitation of new markets
Tidd, Pavitt, and Bessant (2001) West (2002) • Disruptive innovation • Radical innovation • Complex innovation • Continuous incremental innovation
• Innovation that creates an industry • Brand innovation • Reformulation innovation • Design innovation • Service innovation • Packaging innovation • Innovation that extends the capabilities • Technological reorganisation innovation • Process innovation
OECD (2005) Maital and Seshadri (2012) • Product innovation • Process innovation • Marketing innovation • Organisational innovation
Tidd and Bessant (2014) Christensen and van Bever (2014) • Product innovation • Process innovation • Position innovation (context) • Paradigm innovation (mental model)
Because each phase of the innovation process has different aims, these activities are also used with different objectives. For instance, there could be a large amount of techniques used solely for the purpose of generating ideas. Idea generation techniques can also be subdivided into the ones using stimuli related to the problem such as assumption reversals and attribute association chains, but also in techniques using stimuli unrelated to the problem such as modifier noun associations and product improvement checklists (VanGundy, 1992). In fact, Smith (1998) identified more than 170 methods and techniques solely for the idea-generation phase. These results describing the methods to start the creative and innovation processes revealed that these
The unexpected implications of opening up innovation
16
activities can also be recognised with several different labels. Similarly, but on a different literature stream, it is possible to talk about creativity techniques. These could range from popular ones such as brainstorming (Osborn, 1942), the theory of inventive problem solving – TRIZ (Altshuller, 1984), and the six hats of critical thinking (De Bono, 1989), to less common ones like morphological forced connections (Koberg & Bagnall, 1981), the Scamper method (Eberle, 1982), and even the Quality Function Deployment – QFD (Akao, 1990) used in quality management but also convenient for solving problems through creative thinking. Since we are talking about the concept of innovation, it is reasonable to encompass many of these activities and techniques under the label of Innovation Management techniques. However, it should be recognised that even under this label, further categorisations could be found. For example, IM techniques oriented to the conception and design phases include TRIZ, virtual reality, QFD, value analysis, and the Functional Analysis Systems Technique – FAST. IM techniques oriented to the engineering and development phases could comprise concurrent engineering, Failure Modes and Effects Analysis - FMEA, and rapid prototyping (Maital & Seshadri, 2012). Overall, this situation signals two important aspects. First, activities related to innovation could take several forms and involve different means to practice them. Second, to manage the innovation process there is a whole ‘arsenal’ of techniques and tools (for a comprehensive review see Hidalgo & Albors, 2008) and to seize them properly, they need to be organised and managed under a perspective, framework or a model. Also, it is common when talking about innovation inside firms to relate it immediately to Internal Research and Development (IRD) activities and thus, to the management of an R&D unit and its processes. However, many activities that lead to innovation are not R&D-based (Santamaría, Nieto, & Barge-Gil, 2009). Thus, it is equally common that firms engage in a series of activities that enables the creation of innovations and the ability to adopt innovations created by others (OECD, 2005). It seems then that in current dynamic and collaborative organisational environments having a process solely for managing IRD is a limited approach. In addition, it is necessary to visualise the context in the last decades where firms have had constant pressure to innovate franticly. But even if by probability the quantity of innovations might provide innovations of quality, the costs associated with failure would highly damage a firm’s overall performance (Freeman, 1974). Therefore, as Tidd et al. (2001) correctly highlighted, IM models can help in organising the practices and techniques related to the innovation process and lower the risk of innovation. One of these models that has gained the attention of scholars and practitioners in the last years is the OI model.
2.1.2. Basic notions of OI
It can be said that innovation, and consequently its management, have always been understood as a positive noun, especially in the business environment (van der Meer, 2007). There is evidence to a large extent that identifies innovation as the principal driver for companies to flourish, grow, maintain a high profitability and sustain in the long term (Elmquist et al., 2009). But even so if an organisation employs IM and embraces its innovation strategy, it may
Literature and Knowledge Domains
17
encounter barriers obstructing the innovation process (Rahman & Ramos, 2013). Therefore, organisations have historically invested substantial resources and efforts in specialised closed units (usually IRD units) focusing on driving innovation to ultimately obtain a sustainable strategy (West, 2002). However, Chesbrough and Crowther (2006) asserted that in the last years there is a practice of a more open model where companies are aware that not all good ideas will come from the inside and not all innovations created within the company can be successfully marketed internally. Gassmann (2006) also remarked that during the last decade stronger global competition has guided greater knowledge sharing and collaboration between a firm’s innovation processes. Considering these phenomena, the OI model (Chesbrough, 2003a) was conceived using ideas from traditional IM and improved to represent current and emerging practices in organisations (van der Meer, 2007). When defining the concept of OI it is fundamental to reference Chesbrough (2003a; 2003b). He called this the ‘New era of Open Innovation’ pointing out how the industry newcomers made little or no research with their own resources, but instead obtained innovative ideas through an alternative process to bring them to the market. Due to major advances in technology, information can be transferred more easily than ever before, thus the OI model theorised that since companies cannot stop this phenomenon, they must learn to adapt their practices so they can take advantage of it using proper business models (Kirschbaum, 2005). Although not specified as some axioms of OI, the idea of processes, practices, and models managing the flow of knowledge inside and outside the firm, has been the cornerstone to define it. This can be clearly seen if considering some of the most recognised OI definitions (West et al., 2014) shown below. For instance, the first OI definition balanced external and internal elements saying:
‘…firms can and should use external ideas as well as internal ideas, and internal and external paths to market…’ (Chesbrough, 2003a, p. XXIV). Later, a new definition balanced the two existing knowledge flows stating that OI:
‘…is the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively’ (Chesbrough, 2006, p. 1). Similarly and almost simultaneously, an approach to complement the practices and models was stressed by defining OI as:
‘…exploring a wide range of internal and external sources for innovation opportunities…and broadly exploiting those opportunities through multiple channels’ (West & Gallagher, 2006, p. 320). More recently, a balance between the known mechanisms and the dimension of value redefined OI as a:
‘…process based on purposively managed knowledge flows across organizational boundaries, using pecuniary and non-pecuniary mechanisms in line with the organization’s business model’ (Chesbrough & Bogers, 2014, p. 12).
The unexpected implications of opening up innovation
18
All these, but also other definitions in the OI literature, help to provide an initial understanding of the concept of OI. First, the definitions implicitly consider that OI models, modes, processes, and practices are not mutually exclusive. Second, these definitions show that similar concepts are branded with different labels. Third, finding multiple but sequential definitions adding on each other, shows that the OI model and its related theoretical perspectives have greatly developed in the last decade (West et al., 2014). Favourably, it seems the essence of the OI model remains today and this can be seen in its three main elements: culture, structure, and business model (Chesbrough, 2003a). Hence, it is important to mention them, especially when talking about the practices of OI since the practices are a common denominator embedded in all these elements (Chesbrough, 2003a). To begin with, OI needs a different mind-set not only from managers, but also from a cultural shift in the whole firm (Boscherini, Chiaroni, Chiesa, & Frattini, 2010). This implies that within the organisation a change should take place in the way people perceive the organisation and its environment, i.e. it involves a new culture (Chesbrough, Vanhaverbeke, & West, 2006). Having an OI culture relates towards shifting to an open systems view and it requires a different way of thinking (van der Meer, 2007). This basic set of beliefs, norms, and values involved in an OI culture has been proposed since Chesbrough’s seminal work (2003a). Also, it is widely accepted by the academic community that the use of OI by a firm is more appropriate as it corresponds with a firm’s idiosyncrasy for current trends like globalisation, knowledge leveraging, new business models, technology fusion, and technology intensity (Gassmann, 2006). However, the relation of these trends to OI adoption has already been studied in mature industries confirming that technology intensity is only a part of the OI equation (see e.g. Chiaroni, Chiesa, & Frattini, 2010; 2011; Ili, 2013). In addition, a clear way to explain the OI structure is by comparing a model of closed or conventional innovation process and an open process, as seen in Figure 2-1 (image adapted from Chesbrough, 2003a). On the one hand, traditionally companies apply a process that limits the utilisation of internal knowledge within the company and makes no use of external knowledge; this paradigm is described as a closed innovation model (Chesbrough, 2003). In other words, a closed model represents a firm pursuing innovation within its boundaries, and once innovative ideas have been developed these are protected with intellectual property (IP) rights. Then the generated profit of these innovations is used to reinvest in IRD in a virtuous, but closed, circle of innovation. As Gassmann (2006) mentioned, the nuclear and military industries, in which confidentiality of technology and process is essential, are typical examples of closed models. Within this paradigm companies keep their inventions highly secret and make no effort to give away information outside their own R&D labs. However Chesbrough (2003) argued that factors like the availability of educated people, venture capital, external ideas and technology, and more actors involved in the innovation process, have eroded closed IRD and closed innovation and thus, this is no longer a condition providing a competitive advantage (Teece, Pisano, & Shuen, 1997).
Literature and Knowledge Domains
19
Figure 2-1. Closed versus open innovation models
On the other hand and in contrast, the OI model refers to combining internal and external ideas as well as inner and outer pathways to market to advance innovation development (Chesbrough, 2003). In the OI model, the ideal environment is the one where exchange and collaboration efforts between companies and experts facilitate the introduction and implementation of more open processes and exchange of knowledge between companies, suppliers, scientists, universities, and customers among other stakeholders in the value chain. To support the generalisation of the model applicability, Chesbrough and Crowther (2006) provided numerous cases that identified how many OI concepts were already in use in a variety of industries. However, this argument was also used as a criticism by some scholars (see e.g. Trott & Hartmann, 2009) to challenge the novelty of the Open Innovation model, which is a topic discussed later in this section. Besides shifting the culture and the proper structure in place, opening up the innovation process involves new business models (Chesbrough, 2007; van der Meer, 2007), including new approaches for systems, practices, mechanisms, and tools (Chesbrough, 2013). Such mechanisms include arrangements, practices, and methods at every different stage of the innovation process that allows inflow and outflow of ideas (Lazzarotti et al., 2011). Regarding a firm’s process point of view, three key processes (sometimes also labelled as modes) can be differentiated in the OI model (Chesbrough, 2007; Enkel, Gassmann, & Chesbrough, 2009; Gassmann, 2006; Gassmann & Enkel, 2004):
ü The outside-in process: also referred to as ‘Inbound’ process consists of gaining knowledge for the firm by the integration of suppliers, customers, universities, research centres, and even competitors. Innovation can flow into the organisation from any kind of external source.
Innovation projects
Innovation projects
Markets
New Markets
Established Markets
Organization Boundaries
The unexpected implications of opening up innovation
20
ü The inside-out process: also referred as ‘Outbound’ process involves gaining profits by bringing ideas to market, selling intellectual property, and increasing technology by transferring ideas to the external environment.
ü The coupled process: is a balance of the two previous processes and includes co-creation with partners, alliances, cooperation and different types of joint ventures, to give and receive beneficial profits and knowledge.
Since Chesbrough (2003) first introduced the concept of OI and reframed the capacity of the innovation paradigm, more and more firms have been trying to adopt this model in their innovation practices (Cricelli, Greco, & Grimaldi, 2015). Even though Chesbrough’s paradigm has been criticised by some scholars for being too prescriptive (Trott & Hartmann, 2009), in general, the OI model has contributed to previous concepts and ideas for managing innovation (Huizingh, 2011). For instance, OI has added the idea of using competitors as possible external sources of innovation to the concept of user innovation (von Hippel, 1986; 2005). So it seems then, that even though concepts such as supplier innovation have been around for decades, OI has been able to provide new insights to them (Rosell & Lakemond, 2012). This idea of the usefulness and novelty of OI is briefly but critically presented in the next section.
2.1.3. What is new about OI?
During the first years after its origin, OI was proposed as a new paradigm (Chesbrough et al., 2006) and it has steadily develop to be recognised as one. Even from a traditionalist point of view (Kuhn, 1963), OI can be considered as a paradigm for two reasons. First, most members of the IM scientific community have recognised it at a given time. Second, there is a large set of ‘exemplars’ that have been solved and evaluated by means of a specific set of OI assumptions providing positive evidence of its value. In addition, some scholars, but also practitioners, have argued that the emergence of OI was expected to happen eventually as the innovation process itself should be innovated and not restricted to be inflexible (Diener & Piller, 2013; Salmelin, 2013). Thus, it could be said that OI not only suggests a new perspective to see the innovation process but it also has a novel value proposition different from other innovation models. To understand the novelty of OI, it is necessary to review in general other innovation frameworks, models, and paradigms. According to Tidd and Bessant (2014) even if most innovation is messy, turbulent, and with a constant recycling between stages, its related process has still some degree of sequence. Van de Ven et al. (1999) compared this sequence with the metaphor of an ‘innovation journey’ in which according to contingent circumstances during the key phases of the innovation process, different specific models of the process could emerge. However, the idea of a sequence (journey) should not be confused with linearity, because while the former is related to continuous progression the latter is more narrow and limited. This can also be seen in the evolving appreciation of the nature of the innovation process. For instance, Rothwell (1992) suggested five generations of innovation models: simple linear models such as technology-push (up to 1960s) and need-pull (1960s to 1970), coupling models with feedback
Literature and Knowledge Domains
21
loop (1970s), parallel models with integrated innovation (1980s), and systems integration and networking (from 1990s). More recently Berkhout et al. (2006) argued that the evolution process should be synthesised to only four major progressions, with the last one ‘Open R&D’ being where innovation occurs within networks of specialised innovation actors such as in OI. Therefore, even from different angles the perception of the innovation models is progressing towards having more open and collaborative ones (van der Meer, 2007). Indeed, being critical towards the novelty of the OI model would involve comparing its strengths and weaknesses with all the other existing innovation models. However, this seems an impossible task considering that there are dozens of recognised innovation models in the literature. Moreover, if we consider that many organisations develop their own models to manage their innovation, then the number of available innovation models is practically unlimited (Marinova & Phillimore, 2003). For the sake of the argument of the novelty of OI, a comparison could be made with at least one well-known model such as the chain-link model of innovation proposed by Kline and Rosenberg (1986). In brief, this model suggests that innovation involves many interactions and feedback to create knowledge, including multiple inputs as a learning process, evading invention as a pre-process while still undertaking problem-solving, and it also includes non-R&D inputs such as design, training or exploration of new markets. So even though this model has proposed similar ideas on the use of non-R&D inputs or external knowledge, the OI model has some notable differences. For instance, the chain-linked model depicts the innovation process inside a firm where the innovator occasionally takes ideas from a common pool of knowledge to try to solve an internal design problem. However, in OI, the knowledge can come from different actors who can help the firm not only explore new knowledge but also exploit it. This exploitation usually takes the form of the commercialisation of an unused innovation to expand the market or create new ones (Chesbrough et al., 2006). This situation highlights the difference that in the chain-linked model, as in other IM models, innovation materialises only if a market already exists for it, whereas in OI, a market-push strategy is not needed to profit from innovations. In addition, the use of external actors for innovation could also resemble models, such as R&D networks where universities, large companies, and government labs build links to create and enforce IP rights (Wen & Kobayashi, 2001). However, the use of several actors in OI has wider applicability because it is also useful for small firms, where formal protection methods to capture value, e.g., IP rights such as patents, are less feasible (De Backer & Cervantes, 2008; Huizingh, 2011). Other comparisons could be possible, but the main idea here is that the essence of OI, and thus one key difference with other innovation models, is that it connects the processes of acquiring external knowledge and exploiting internal knowledge externally (Huizingh, 2011). Moreover, many researchers and practitioners consider OI as part of an on-going phenomenon in the way organisations innovate in a more open and collaborative way. Conversely, a trend towards adopting and studying OI practices has increased because the model has been seen as a relevant means through which firms can explore external knowledge and exploit its own internal one (Jaspers & van den Ende, 2010). In fact, a review of the empirical research in OI adoption by
The unexpected implications of opening up innovation
22
Schroll and Mild (2012) showed that the concept of OI was adopted in up to 45% of the firms in the studies and that OI can now be considered as a global trend occurring in almost all industries, sectors, and markets. Similarly and more recently, through a large-scale analysis using four waves of the Community Innovation Survey (CIS), Cricelli et al. (2015) confirmed that the proportion of firms adopting OI approaches has been increasing at a continuous and steady pace. All of the arguments mentioned above are indicators that researchers and practitioners have been convinced of the novelty and usefulness of OI as a model to manage innovation. Moreover, the originality of OI could be claimed on its holistic approach (Altmann & Li, 2011) that has provided a novel and a specific ‘face’ to a large collection of theories to study the innovation processes (Huizingh, 2011), but also guided the assumptions of how these theories and other notions relate to each other under one ‘Open Innovation umbrella’ (Wikhamn & Wikhamn, 2013).
2.1.4. What is missing in OI research?
Since the concept of OI started to spread amongst the academic community, it has triggered several research agendas to fill the missing gaps in OI. The biggest and most ambitious research agendas are usually justified through a comprehensive literature review (LR) following suggestions for future research directions in OI. Therefore, ideas for relevant and fresh research in OI can emerge by considering these publications. For instance, Elmquist et al. (2009) proposed a model to better understand OI in the future based on two dimensions: locus of the innovation process and extent of collaboration. In the same year and as editors of a special issue in OI, Enkel et al. (2009) claimed that research shows more and more situations where OI is seen as valid. By being in the research frontier as key OI researchers and by using a firm’s process perspective they highlighted further research opportunities. These opportunities included studying with the same weight the outbound and coupled processes or focusing on cross-industry innovations (Gassmann, Wolff, & Stahl, 2004). Other highly cited LRs follow the same approach by directing the attention of future research towards different but related gaps in OI literature. For example, Gassmann, Enkel, and Chesbrough (2010) drew attention towards nine perspectives vital for developing an OI theory further. Lichtenthaler (2011) evaluated past literature in order to provide a framework for discussing OI processes at the organisational, project, and individual levels. In his multilevel framework Lichtenthaler emphasised knowledge exploration, retention and exploitation both internally and externally. He concluded with six specific research fields which OI could contribute. With a slightly different approach, Huizingh (2011) reviewed OI literature categorising it by the questions to which the concept relates more directly, i.e. what (the content of OI), when (the context dependency) and how (the process). Instead of giving a specific number of broad trends, he provided more specific research suggestions. More recently, Schroll and Mild (2012) reviewed most large-scale quantitative studies mainly focusing on OI adoption. A summary of these four literature reviews is shown in Table 2-2 to exemplify the different but convergent research opportunities in OI literature.
Literature and Knowledge Domains
23
Table 2-2. Past trends and potential research directions based on OI literature
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s4.
I
nnov
atio
n m
arke
ts
a.
Cha
ract
eris
tics,
prac
tices
and
tool
s of O
I pro
cess
esb.
T
ypol
ogie
s of a
ctiv
ities
to fi
nd a
rche
type
styl
esc.
P
erfo
rman
ce e
ffect
s of O
I at m
ultip
le le
vels
d.
D
eter
min
ants
, mec
hani
sms a
nd d
river
s of O
I e.
T
echn
olog
y tra
nsac
tions
: foc
usin
g on
inbo
und
rete
ntio
n/ex
ploi
tatio
n, a
nd o
utbo
und
expl
oita
tion
f.
Em
piric
al, l
ongi
tudi
nal a
nd c
ross
-leve
l stu
dies
Ope
n in
nova
tion:
Sta
te o
f th
e ar
t and
futu
re
pers
pect
ives
(Hui
zing
h,
2011
)
1.
Con
tent
of O
I- C
lass
ifica
tion
of o
penn
ess
- Inb
ound
vs.
outb
ound
inno
vatio
n- E
ffect
iven
ess
2.
Con
text
of O
pen
Inno
vatio
n- I
nter
nal c
onte
xt c
hara
cter
istic
s- E
xter
nal c
onte
xt c
hara
cter
istic
s3.
O
pen
inno
vatio
n pr
oces
s- T
owar
ds o
pen
inno
vatio
n- O
pen
inno
vatio
n pr
actic
es
a.
Con
text
dep
ende
ncy
of O
I nee
ds m
ore
rese
arch
by
focu
sing
on
envi
ronm
enta
l cha
ract
eris
tics
b.
Dev
elop
an
inte
grat
ed O
I fra
mew
ork
or th
eory
c.
The
re is
a n
eed
of m
ore
quan
titat
ive
stud
ies w
ith la
rge
sam
ples
in v
ario
us in
dust
ries a
nd c
ount
ries
d.
Stu
dies
in o
ther
regi
ons (
not o
nly
US
and
Euro
pe)
e.
Des
crip
tive
stud
ies n
eed
to in
clud
e pe
rfor
man
ce m
easu
res (
eith
er c
ase
stud
ies o
r sur
veys
)f.
Q
uant
itativ
e st
udie
s can
use
surv
eys,
finan
cial
and
pat
ent d
ata,
or c
onte
nt a
naly
sis e
.g. c
ompa
ny re
ports
A c
ritic
al re
view
of
empi
rical
rese
arch
on
open
inno
vatio
n ad
optio
n (S
chro
ll &
Mild
, 201
2)
1. M
easu
rem
ent o
f OI a
dopt
ion
2. L
evel
of O
I ado
ptio
n 3.
Lev
el o
f OI m
ode
(inbo
und
and
outb
ound
)4.
Var
iabl
es th
at in
fluen
ce th
e ad
optio
n of
OI
a.
Res
earc
h m
ore
outb
ound
pro
cess
es a
nd d
river
s of O
Ib.
S
tudy
at t
he sa
me
time
inbo
und
&ou
tbou
nd p
roce
sses
c.
Em
piric
al re
sear
ch o
n A
sia
and
Sout
h A
mer
ica
d.
Gen
eric
mea
sure
s of O
I ado
ptio
n e.
g. a
t pro
ject
leve
le.
M
onito
r OI e
volu
tion
as a
glo
bal t
rend
by
usin
g la
rge-
scal
e cr
oss-
indu
stry
and
cro
ss-c
ount
ry st
udie
sf.
S
tudi
es in
tegr
atin
g bo
th: i
nbou
nd &
out
boun
d pr
oces
sg.
I
mpa
ct o
f OI o
n a
firm
´s fi
nanc
ial p
erfo
rman
ce
Tabl
e 2-
2. P
ast t
rend
s and
pot
entia
l res
earc
h di
rect
ions
bas
ed o
n O
I lite
ratu
re
The unexpected implications of opening up innovation
24
However, it should be noted that the previous four publications are only a handful of the reviews available. Thus, to find other important gaps in OI research it could be useful to conduct an extrapolation between the most relevant OI LRs in the form of a meta-review of literatures. An example of how this approach was useful to find a research gap for this thesis is shown in one of the appended papers (paper A). In this case, the criteria used to select the most relevant LRs was by choosing the ones with the highest Normalised Citation Impact Index (NCII; Holsapple, Johnson, Manakyan, & Tanner, 1994). The NCII is calculated as the total citations per publication divided by the publication longevity in years. According to this criterion, mainly 10 LRs were considered as the most relevant ones since the concept of OI was coined and these are listed in Table 2-3.
Table 2-3. The most relevant literature review in OI according to its citation impact
Title of publication Author/s (year) NCII
How open is innovation? Dahlander & Gann (2010) 168.0
Open innovation: State of the art and future perspectives Huizingh (2011) 127.5
The future of open innovation Gassmann et al. (2010) 106.2
Open innovation: Past Research, Current Debates, and Future Directions Lichtenthaler (2011) 72.8
Leveraging External Sources of Innovation: A Review of Research on Open Innovation West & Bogers (2013) 47.5
Exploring the field of open innovation Elmquist et al. (2009) 26.3
Broadening the scope of OI: past research, current state and future directions
van de Vrande, Vanhaverbeke, & Gassmann (2010) 16.6
A critical review of empirical research on open innovation adoption Schroll & Mild (2012) 6.0
Implications of Openness: A Study into (All ) the Growing Literature on Open Innovation Giannopoulou et al. (2010) 5.6
Structuring of the Open Innovation Field Wikhamn & Wikhamn (2013) 2.5
A detailed explanation of the methodology followed to conduct this meta-review and the analysis of 159 articles is provided in paper A (Ramirez-Portilla, 2015). In brief, the study in this paper focused on using a qualitative analysis comparing the theoretical perspectives used and the contexts studied in OI research. By analysing the trends on these two dimensions, it was possible to identify some research gaps and directions. In this sense, one of the main results of this study showed that OI is a complex multi-dimensional phenomenon that compels
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us to use different perspectives in order to better understand it (Vanhaverbeke & Cloodt, 2014). Additional findings showed the extent to which several perspectives and contexts have been used so far to investigate OI, and consequently the combinations of these elements that could contribute to OI literature. Figure 2-2 shows part of the clusters resulting from the analysis together with the three clearest patterns of relationships between perspectives and contexts in OI research, which are:
• SMEs and large firms in mature industries from the manufacturing sector studied mostly with organisational theory and views related to practices and modes of openness, but also with absorptive capacity and dynamic capabilities;
• Large firms in high-tech industries from the service sector together with value chain stakeholders studied with processes and practices views, as well as views related to resources, knowledge, and capabilities;
• Firms in high-tech emerging industries collaborating with external stakeholders and communities studied with lead user innovation, strategy and business models views, but complemented with network and systems theories.
Figure 2-2. Linking theoretical perspectives and research contexts in OI studies
The unexpected implications of opening up innovation
26
In conclusion, the study in paper A highlighted the importance of recognising the context and contingency dependency of OI for better understanding its scope, application, and results. In other words, we could say that one OI model does not fit all contexts. Therefore, to continue developing OI research that integrates earlier theories, contexts, and findings to arrive at a coherent OI body of knowledge (Lichtenthaler, 2011), it seems promising to use a partial narrowing-widening approach. This approach would entail narrowing the selected theories to a few but relevant ones and contrariwise, to widen the contexts where OI could be studied to confirm the validity of OI with these other theories. Based on these ideas, this thesis aims to contribute to the stream of research that focuses on investigating the adoption and effects of OI practices in manufacturing firms from mature industries. Moreover, it attempts to fill the gap of using a multi-perspective approach in Open Innovation that could provide novel evidence of unexpected implications by examining under-studied empirical contexts with varied but focused theoretical views.
2.2. Choosing theoretical perspectives to study OI
A constant rising trend in literature related to OI shows that it continues to receive great attention from scholars. Likewise, companies seem more and more willing to open up their innovation processes in order to exploit the opportunities offered by the external technological environment (Cricelli et al., 2015). However, the debate in Innovation and Technology Management (ITM) literature shows that there is also some strong criticism with respect to OI (see e.g. Trott & Hartmann, 2009). Some authors underlined that the concept is not particularly new, but, on the contrary, there is a long tradition on the topic of collaborative approaches for innovation (Freeman, 1974; Pavitt, 1984; von Hippel, 1986). Furthermore, other scholars claimed that the dichotomy between open and closed innovation models seems ‘artificial’ (Dahlander & Gann, 2010). This criticism builds on the idea that in the real world different degrees and different models of OI can be conceived in a continuum of possibilities highly influenced by the organisational and environmental contextual factors. Hence, investigations based on the analysis of OI degrees (Dahlander & Gann, 2010; Gassmann, 2006) with different arrangements of practices while considerably considering the firm context (Tidd, 2014) would be far more relevant for both scholars and organisations. Considering these ideas, characterising OI as practices more than any other type of endeavour could provide some interesting insights. Even though using practices, or a practice-based approach, could help study a wide spectrum of innovation related activities, it would be wise to leverage it with other theoretical perspectives. Therefore, in this research project two theoretical perspectives are mainly considered: a practice-based view and contingency theory. Both of these perspectives are better described and justified in further sections. In addition and for the purpose of using a multi-perspective approach, some of the studies take ideas from OI modes (although later characterised as a form of OI practices), elements from organisational theory, and also from views highlighting innovation driven by users and communities. In the next sections the rationale behind these choices is examined showing that the scope continues to be narrow enough to study OI while combining a few but relevant theoretical perspectives.
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2.2.1. Available theories used in OI research
It is often a challenge when conducting research to choose between different available theories to study a phenomenon. Similarly, when studying OI there are some theoretical perspectives that could have opposing views while others could add and converge towards understanding it better (Elmquist et al., 2009). Actually, it is not surprising to see different perspectives used in OI research, mostly because Chesbrough (2003b; 2006) recognised a vast source of antecedents when proposing the OI model. For an idea of the available theoretical perspectives to investigate OI refer to Table 2-4, which is adapted from the LR analysis in paper A.
Table 2-4. Potential theories and theoretical perspectives to study OI
Author/s (year) Theories / theoretical perspectives and views
Dahlander & Gann (2010)
A. archetypes (modes) of openness, B. network theory, C. transaction costs economics, D. absorptive capacity, E. practice-based view, F. complementary assets, G. user-driven innovation. H. exploration and exploitation, I. contingency theory, J. resource (knowledge)-based view
Huizingh (2011)
A, B, C, D, E, F, G, H, I, J, K. real options theory, L. competence-based view, M. organisational theory (change theory), N. business models perspective
Gassmann et al. (2010)
A, D, G, O. dynamic capabilities, P. process perspective, Q. tool perspective, R. institutional theory
Lichtenthaler (2011)
A, B, C, D, E, G, H, I, J, L, M (org. capabilities, learning, design), N, O, S. firm boundaries
West & Bogers (2013)
A, B, D, F, G, J, L, M (org. culture), N, O, T. technology-based view, U. market-feedback
Elmquist et al. (2009)
A, B, D, F, G, I, M, N, S, T, V. leadership, W. evolutionary economics, X. innovation systems (national, regional), Y. industrial dynamics
van de Vrande et al. (2010)
A, B, D, E, G, J, K, L, M, N, O, X, Z. value creation and value capture, AA. relational view
Schroll & Mild (2012)
A, D, F, G, I, J, L, M, N, O, S, T, V, Y, AB. technology transactions, AC. upper echelons theory,
Giannopoulou et al. (2010)
A, B, D, G, H, J, L, M, N, O, Q, S, T, V, X, Y, AB, AD. strategy, AE. ambidexterity, AF. technology-push, AG. market-pull
Wikhamn & Wikhamn (2013)
A, B, C, D, F, G, I, M, N, O, Q, R, S, T, V, X, Y, AD, AH. promoter theory, AI. enactment theory, AJ. ecosystems theory, AK. social brokerage theory, AL. open system/society, AM. stakeholder theory
As we can see in the previous list of LRs, researchers have proposed studying OI with numerous theories. Therefore an additional challenge with OI is to choose a theoretical view
The unexpected implications of opening up innovation
28
appropriate for the research purpose and context while acknowledging and linking previous theoretical developments in IM. For instance, before OI was proposed the involvement of different stakeholders was widely recognised in the innovation process such as suppliers (see e.g. Bozdogan, Deyst, Hoult, & Lucas, 1998; Ragatz, Handfield, & Scannell, 1997) but also customers, consumers, and users (see e.g. Kaulio, 1998; von Hippel, 1986). Thus, a more valuable outcome besides mentioning previous theories would be to attempt to reconcile OI with these theories. From these endeavours, three of them are worth mentioning because of the focused attempt to find patterns in the OI literature. First, Bogers (2012) reviewed some of the main theoretical perspectives related to knowledge sharing in open collaborative innovation. Framing the discussion within theories of economic organisation and strategic management, he stressed the relevance of five perspectives: transaction cost economics, resource-based view, dynamic capabilities, knowledge-based view, and technology-based view. Second and more recently, Randhawa, Wilden, and Hohberger (2014) investigated OI theoretical foundations with a bibliometric approach where they noticed that OI literature could fall within different clusters. These included clusters related to technology integration and business models which have a close bond with other clusters related to absorptive capacity, exploration and exploitation of knowledge, and complementary assets. Also related but more distant, there are clusters related to the knowledge-based view, resource-based view, dynamic capabilities, user-driven innovation, and network theory. Third, and with a more focused approach Vanhaverbeke and Cloodt (2014) related Open Innovation ideas to existing theories of the firm. While the relationship between these theories is more demarcated, they also recognised and emphasised the potential of understudied perspectives in OI such as business and corporate strategy, but also more traditional ones such as transaction costs, transaction value, resource-based view, knowledge-based view, relational view, and the resource dependency theory. Based on the LRs in Table 2-4 and the three above-mentioned publications it is possible to spot some of the most popular theories used to research OI phenomena. Three of them that seem to be used quite often to study OI are the resource-based view, absorptive capacity, and dynamic capabilities. However, it is appropriate to highlight at this point that an implicit goal of this research project is to provide novel outputs by not following conventional approaches to study OI. Therefore, these three theoretical views are not used as the theoretical core of this thesis. In any case and for the sake of clarity, a brief rationale of this choice is explained next. To begin with, a key aspect in the resource-based view (RBV) is that a firm needs a unique collection of resources, including capabilities and competencies, to be competitive (Barney, 1986; Wernerfelt, 1984). These resources need to be valuable, rare, inimitable, scarce, and durable to better capture return rates and consequently create a sustained competitive advantage (Barney, 1991). Besides providing a clear definition of the nature of unique resources, the RBV has offered for many years a valuable explanation of how intangible resources can play a key role in achieving and maintaining competitive success for many firms (Jiménez-Barrionuevo, García-Morales, & Molina, 2011). However, it should be noted that the
Literature and Knowledge Domains
29
RBV emphasises that a sustainable competitive advantage is based on the resources and capabilities owned and controlled within the boundaries of a firm (Vanhaverbeke & Cloodt, 2014). Consequently, using this view would inherently direct the main research focus inside the firm and its internal manageable characteristics. The other two perspectives, absorptive capacity and dynamic capabilities, are both related to a capabilities-based perspective of a firm which considers capabilities as the organisation´s knowledge, skills, and experience (Richardson, 1972). Firstly, absorptive capacity (ACAP) is defined as ‘…the ability of a firm to recognise the value of new, external information, assimilate it, and apply it to commercial ends…’ (Cohen & Levinthal, 1990, p. 128). Because ACAP can be considered a multidisciplinary concept, it can be useful to link and understand phenomena in knowledge management, organisational learning, and IM (Jiménez-Barrionuevo et al., 2011). A specific case is the constant use of ACAP in OI literature (e.g. Brunswicker & Vanhaverbeke, 2011; Huang & Rice, 2009; Lazzarotti, Manzini, & Pellegrini, 2015; Spithoven, Clarysse, & Knockaert, 2010). Similar to OI, ACAP stresses a required balance between internal and external knowledge. Hence, a firm needs IRD capabilities to identify relevant technologies developed elsewhere and also to exploit external know-how (Arora & Gambardella, 1994). Nevertheless there is affinity between OI and ACAP, a weakness of ACAP to study OI is that it is mainly associated with the assimilation of external knowledge and is therefore limited to the inbound process (Vanhaverbeke & Cloodt, 2014). Although it has been proposed to complement ACAP with the idea of desorptive capacity (DCAP) defined as ‘a firm’s ability to externally exploit knowledge’ (Lichtenthaler & Lichtenthaler, 2009, p.1322), DCAP has not gained as much attention as ACAP in OI research. Secondly, and with a more broad scope on skills and competences, there is the concept of dynamic capabilities (DCs). DCs were initially defined as ‘the firm’s ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments’ (Teece et al., 1997, p. 516). These capabilities can be classified into the capacity to sense and shape opportunities and threats, to seize opportunities, and to maintain competitiveness through enhancing, combining, protecting, and, reconfiguring the firm’s intangible and tangible assets (Teece, 2007, p. 1319). Due to the idea of changing environments, a DC view considers that to obtain a sustainable competitive advantage the VRIN-ness of resources (Valuable, Rare, Inimitable and Non-Substitutable) is not enough and firms also need inimitable DCs. So it can be said that due to the dynamic nature of capabilities, the DC view complements the static focus of the RBV but also addresses issues of human agency and implementation of resources (Katkalo, Pitelis, & Teece, 2010). Moreover, the DC view is compatible with OI since it explicitly addresses important elements of OI such as the balance between internal and external knowledge (Teece, 2007). Nevertheless, both ACAP and DC views focus on the inbound process and somehow disregard the outbound process which is also a key element of the OI model (Vanhaverbeke & Cloodt, 2014). In summary, it seems that even though the outbound process is partially disregarded in the RBV, ACAP and DCs, there is some affinity between these perspectives and Open Innovation.
The unexpected implications of opening up innovation
30
For instance, all perspectives directly and indirectly stress the relevance of developing or acquiring the resources, capabilities, capacities, and competences to create a sustainable competitive advantage (Vanhaverbeke & Cloodt, 2014). Aligned with this idea, some authors have related the required capabilities with routines (e.g. Nelson & Winter, 1982). For instance, the DCs can be formed from intentional routines (Eisenhardt & Martin, 2000) and these include in their microfoundations distinct skills, process, procedures, structure, decision rules, and disciplines (Teece, 2007). Still, it seems that resources and capabilities are more commonly rooted in creative managerial and entrepreneurial acts rather than rooted in certain change routines (Katkalo et al., 2010). Moreover, it is critical to consider that competitive advantage not only occurs from the control or acquirement of specific resources and capabilities, but mainly from the way in which these are used (Penrose, 1959). A similar situation happens in the Open Innovation paradigm where the existence of valuable external (re)sources of knowledge should not be implied as an automatic process of inflow of new ideas into a firm (Vanhaverbeke & Cloodt, 2014). No, external knowledge can only be identified and incorporated when a firm develops certain practices to facilitate OI processes (Dahlander & Gann, 2007). Thus, it could be said that it is mainly the daily practices through which specific resources and capabilities are used that are the mechanisms bringing together, identifying, and seizing valuable internal and external knowledge dependent on the organisation and its (changing) environment. Considering the arguments above, instead of views based on capabilities or resources, this research project emphasises the OI practices and the context where they occur. More specifically, first it considers a well-established perspective such as contingency theory to recognise the context dependency of OI. Second, it considers and pushes forward the relevance of a practice-based view in OI to provide a more realistic but still theory-based perspective on the role of the OI activities adopted and practiced.
2.2.2. Contingency theory as an ‘oldie but goodie’ for OI
The word contingency is commonly associated with an emergency or eventuality that might happen when in fact its meaning could have a more significant scope. Contingency is defined in the dictionary as ‘something liable to happen as an adjunct to or result of something else’ (Merriam-Webster Inc., 2004, p. 261). It is in the last part of this definition where the effect of ‘something’ is recognised and thus signals an important aspect of the term. This can be further established with the definition of the related word contingent as ‘the quality or state of being dependent on or conditioned by something else’ (Merriam-Webster Inc., 2004, p. 261). Therefore, it could be said that from a semantic point of view, even if contingency and dependency are not synonyms, the two concepts are closely interlinked and they might be used as proxies of each other. In social sciences contingency has been used as a concept to propose theories that could explain how some few but relevant constructs are influenced by many internal and external constraints. Because of its varied applicability, there could be different contingency theories such as the ones related to leadership (Fiedler, 1964), decision making (Vroom & Yetton,
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31
1973), and organisational communication (Wiio, 1978). Even if these theories are different, what all of them have in common is the recognition that certain constrains (factors) determine the status of the firm, its subsystems, and the environmental suprasystem. Thus, it has been acknowledged for many years that the interaction between an organisation and the environment is contingent upon internal and external stimuli but also upon the degree of freedom allowed by these constraints (Lawrence & Lorsch, 1967). Because of this similitude, then it is possible to talk about a Contingency Theory (CT) but with numerous and possible applications. In general, the CT could be one of the many approaches considered in organisation theory. However, because its nature focuses more on an environmental perspective it seems therefore appropriate to consider them distinctly. Historically, CT has had several precursors, some more and others less recognised, which have gradually contributed to its development. For instance, some of the first management theorists such as Henri Fayol and Fredrick Taylor although not explicitly mentioning it, have acknowledged that situational factors were relevant for managing an organisation. Several years later it was formally proposed that successful firms in varied industries with different technologies were conditional on specific organisational structures (Woodward, 1958). Similarly, and more related to innovation, it was emphasised that the suitability of different forms of organisations were contingent on specific environmental variables (Burns & Stalker, 1961). Even if it was Lawrence and Lorsch (1967) who explicitly mentioned the term CT, other previous authors already proposed some of its basic assumptions (Fiedler, 1964). In this regard, due to the work of several researchers in different disciplines (e.g. Fiedler, 1964; Vroom & Yetton, 1973; Wiio, 1978), it is now possible to talk about the main ideas of CT which are listed below:
• There is no universal or one best way to manage • The design of organisations and its subsystems must ‘fit’ with the environment • Effective organisations not only have a proper ‘fit’ with the environment but also
between subsystems • The needs of an organisation are better satisfied when it is properly designed and the
management style is appropriate both to the tasks undertaken and the nature of the work group
It is also important to acknowledge that studies using CT are not free of critiques. For instance, contingency-based research could (1) presume contingency relationships that may not exist, (2) neglect the fact that there are different means to achieve the same end, and (3) causality could run either way (Fisher, 1998). In any case, just as a contingency perspective has long governed the discourse on organisation design (Mintzberg, 1979) it seems that CT offers a possible alternative to understand organisational phenomena (Barney, 1985) such as innovation. Moreover, IM phenomena is not only complex and dynamic but it is subject to the contingencies of time and history (Teece, 2006). This idea indicates that contingent factors could be characterised by a wide range of intricate constructs but also possibly by simple variables. Considering this, it would be impossible to list all of them, and thus below only some relevant factors related to management, IM, and Open Innovation are mentioned.
The unexpected implications of opening up innovation
32
First, it is relevant to remember that CT of management was initially proposed as an approach to be applied and solve problems situationally. In this sense, systems and contingency views were assumed to represent a step towards the unification of science, less abstraction, and more unambiguous patterns of relationships (Kast & Rosenzweig, 1972). Similarly, CT was considered as a unifying solution to the issue that many other approaches such as the process, the quantitative, and the behavioural cannot be applied to every organisation because of critical factors (Luthans, 1973). Aligned with this idea, critical factors include, but are not limited to the technologies used, industry, firm size, strategies, competitors, cost of capital, firm age, markets, laws, policies, and available resources amongst many others. In fact, the variety of potential factors implicitly shows that a contingency perspective does not neglect the relevance of resources (e.g. RBV) and capabilities (e.g. DCs) since the studied phenomenon can also be dependent on these. In management literature, as in other disciplines, the development of CT included the demarcation of key contingent factors. In this regard, the performance of an organisation is dependent on the alignment of its strategies and main factors in which the organisation operates (Duncan, 1972). These factors comprise the organisational (or internal) environment and the external environment. This category of factors or characteristics in internal (related to the organisational context) and external (related to the environmental context) became widely accepted. For instance, organisational and environmental characteristics helped to describe the key dimensions of informal social relations in organisations (Barney, 1985). Certainly, other categorisations of factors have been proposed. In information management systems, elements such as strategy, structure, size, environment, technology, task, and even individuals are highlighted as contingency variables (Weill & Olson, 1989). In business strategy, the categories of contingent control variables include (1) uncertainty, (2) technology and interdependence, (3) industry, firm, and size, (4) competitive strategy and mission, and (5) observable factors (Hofer, 1975). Similarly, in management control systems, contingent factors are environment, technology, age and size, structure, strategy, and culture (Fisher, 1998). A number of studies have used contingency views to study management phenomena. These can range from linking project success to history and context (Engwall, 2003), programme management competences dependent on programme types (Miterev, Engwall, & Jerbrant, 2015) to specific contingency factors supporting the implementation of performance measurement systems (Brem, Kreusel, & Neusser, 2008). Consequently, it is not surprising to find studies focusing on the effect and weight of organisational, environmental, and strategic factors on INNO and firm performance (see e.g. Brem, 2011 or Vij & Bedi, 2015). Likewise, CT and other contingency views have proven to be useful to understand open and collaborative innovation phenomena. For example, researchers have proposed theoretical frameworks stressing that different collaboration and OI modes are dependent on the coherence with certain contextual factors related to managerial, strategic, and organisational characteristics (Lazzarotti & Manzini, 2009). Others have emphasised the importance of the ‘right conditions’ to implement OI in new product
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development projects (NPD). Such contingent conditions include the breadth and depth of collaborations, ambidexterity of relationships, type of innovation, product complexity, and the appropriate regime (Bahemia & Squire, 2010). Moreover, recent studies have clearly argued in favour of emphasising context-dependency, CT, and particular contextual factors to analyse OI. In this regard, it has been suggested that the managerial focus of OI collaborations is contingent on different strategies namely networking, co-ordination, co-operation, and collaboration (Ollila & Yström, 2013). Openness at the project level could also be affected by team and task characteristics, such as team size, learning distance, strategic importance, technology and market uncertainty, and relevance to the main business (Kim, Kim, & Lee, 2015). More recently, it seems that a research stream is recognising the relevance of contextual factors influencing the degree of openness, INNO, performance, and other outcomes (Bengtsson et al., 2015; Lazzarotti, Manzini, Nosella, & Pellegrini, 2015; Lazzarotti, Manzini, & Pellegrini, 2015; Stefan & Bengtsson, 2014) suggesting the usefulness of CT in OI studies. To conclude, it is worthwhile to mention that almost a decade ago a contingency approach was called for to comprehend the contextual characteristics that determine OI effectiveness (Gassmann, 2006). Linked with this, even if different levels of contingency analyses are possible, it seems appropriate to focus only on few: to study the simultaneous presence of multiple contingency factors in determing an optimal outcome variable (Fisher, 1998). Withouth a doubt, these factors need to include routines and practices, which although they involve the automated selection of ‘choices’ (Nelson & Winter, 1982), adaptive and behavioural rules are also contextual (Smith, 1984). Moreover, OI is driven by its sorrounding ecosystem, including all the stakeholders and the activities they actually experiment with and practice (Salmelin, 2015). Therefore, critical factors associated with the ecosystem where certain OI practices happen also need to be considered. Consequently and as Huizingh (2011) asserted, contextual factors are essential in OI studies because they can be related to the adoption level of OI, moderate the relationship between OI and performance, and also be linked to the application of particular OI practices.
2.2.3. A practice-based view of OI
The previous sections have stressed and justified the importance of developing certain practices that facilitate OI (Dahlander & Gann, 2007) while considering the influence of contextual factors. Linked with this argument, this section further describes the idea of a practice-based view (PBV) useful to study OI. To begin with and since it is the main term used in this thesis; it is useful to clarify the selection of practices and not other similar concepts. According to the dictionary, the word practice can be defined as doing or performing customarily or habitually so as to become proficient (Merriam-Webster Inc., 2004). While this definition provides clarity of the regular nature of a practice, the possible synonyms of practice complicate its meaning and scope. To exemplify this, Table 2-5 lists terms commonly associated with the word practice with some of their usual synonyms.
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Table 2-5. Terms commonly associated to the concept of ‘practice’
Term Examples of Synonyms*
Practice As routine or usual procedure: habit, method, proceeding, mode, rule, process
Practice As exercise or application of something: action, operation, discipline
Technique Approach, capability, capacity, mode, procedure, routine, system
Mode Approach, form, mechanism, method, procedure, process, technique, practice * Taken from Merriam-Webster Online Thesaurus From the synonyms included in the table, we can make some important assumptions. First, a large number of words are associated with the term practice even though the table only includes a handful of the available ones. Second, many of the synonyms of the terms overlap with each other signalling that in reality there is not much difference between using one or another. Third, although some of the terms seem to have more affinity with the concept of practice, these present some semantic drawbacks. For instance, the term activity presents a more limited number of synonyms compared to practices, which indicates its relative limited scope. Also, the term effort has some negative value-laden synonyms such as intention, attempt or undertaking related to something unfinished or even just attempted. Fourth and most relevant for the argument of using practice (and thus, a PBV), the term practice implies some unique features in comparison to the others. More specifically, practice involves the notion of being a routine or usual procedure which is not frequently indicated by other terms. Moreover, practice does not appear as a common synonym for all the other terms (but the term mode) suggesting it has the potential to encompass other terms (including the ones in Table 2-5). However, it should be mentioned that because there is a clear link between the terms mode and practice, this term is also included in the proposed PBV. Likewise, and as explained further, models are included as another way of characterising OI practices. While the previous statements provide sound arguments to choose practice over other terms, a brief comparison with the term activity is provided next. According to the dictionary, the word activity can be defined as organised behaviours or actions done for a particular purpose (Merriam-Webster Inc., 2004). Comparing this definition with the one of practice previously stated, the main difference of the habitual or routine nature of the performed actions becomes apparent. This important contrast could be related to management literature in the sense that organisations can be seen as systems of routines (Nelson & Winter, 1982) rather than sporadic actions. Indeed, organisations can also be analysed as networks of activity systems by using theories related to knowledge (Blackler, Crump, & McDonald, 2000). However, before talking
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about knowledge (as a resource or a capability), the focus should be on how knowing is attained in the course of practice while considering social contexts (Blackler, 1995). It seems then that focusing on practices, and consequently using a PBV, could provide similar insights than using other terms. Besides, another advantage is that a practice-based perspective could be used with other perspectives (Nicolini, Gherardi, & Yanow, 2003). Moreover and based on the ideas above, using a PBV could be useful not only to focus exclusively on knowledge transfer activities, but also to consider other type of practices used to spur and manage OI. In this regard, it also needs to be acknowledged that besides practices, OI can also be characterised in real contexts in terms of processes, activities, approaches, and many other concepts. However, as Elmquist et al. (2009) noticed, OI can be mainly described as a group of specific practices. Another view is that OI can be ‘both a set of practices for profiting from innovation and a cognitive model for creating, interpreting and researching those practices’ (West, Vanhaverbeke, & Chesbrough, 2006, p. 286). Therefore, focusing on practices, including models as a type of variation, could be used to understand the adoption of OI. This approach can be justified since several researchers have implicitly investigated OI under a PBV while others have stated it more clearly (see e.g. Russo-Spena & Mele, 2012). In any case, and for clarifying the scope of a PBV, some assumptions need to be stated. First of all, it should be recognised that although the notion of practice (praxis) has been understood for centuries, there is no such thing as a unified practice theory but instead different traditions connected by theoretical resemblances offering a practice-based approach (Nicolini et al., 2003). Next, based on the Marxist notion of practice, it can be said that a practice is an epistemological principle because we only know that which becomes the subject of our practice (Nicolini et al., 2003). In this tradition, practice is seen as a system of activities reflecting the social and historical context of that practice. Similarly, the phenomenological concept of practice assumes that it is a system of activities in which knowing is not separate from doing (Gherardi, 2000). This meaning-making notion is directly related to the idea that knowledge in the organisational context could be understood from several perspectives. Although two of them, the cognitive and the structural, seem to be the most conventionally used, the practice-based approach can also provide enhanced explanatory power. Thus, it seems that using a PBV on organisations considers that practice as an organisational routine is the carrier of operational knowledge in organisations (Gherardi, 2000). So, a PBV implies and accentuates that knowing precedes knowledge, for the latter is an institutionalised version of the former (Nicolini et al., 2003). By adopting a PBV, it could be possible to use a different perspective to understand knowledge and innovation in organisational settings. For instance, a study could provide novel findings related to knowledge and knowledge creation by using a practiced-based epistemology instead of more traditional approaches such as the cognitive or structural perspectives (Nascimento Souto, 2014). In this regard and more related to studying innovation, the notion of practice is commonly used in organisation studies but with several different perspectives, e.g. organisational routines (Nelson & Winter, 1982). However, it seems there are two broad
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notions of practice in social sciences research: practice as what actors do, and practice as a epistemic-normative concept (Geiger, 2009). The first notion relates practices to activities within organisations performed by certain actors and it is usually used as synonymous with routines, processes, and activities (as exemplified in the beginning of this section). Practice as this notion could help reflect the fluid nature of OI and signal that this research project is closer to the reality (and problems) of practitioners by providing practical knowledge. However, this notion has been criticised for using the term practice in colloquial ways, which might not help in understanding what happens within organisations. Contrariwise, the second notion of practice as an epistemic-normative concept emphasises that organisations are a socially constructed interconnection of practices with a collective, contingent, institutionalised and normative character (Gherardi, 2000). Because this notion stresses the subjective and emotional character of knowledge, it can be useful to reveal socially constructed phenomena like the emergence of innovations or technology (Geiger, 2009). Based on the advantages and disadvantages of these two logics, a mix of the two notions of practice is considered in this project in order to study OI phenomena more critically. To conclude, it is relevant to notice that the role of managerial and organisational practices in explaining OI phenomena has increased consistently in the last years (Elmquist et al., 2009; Giannopoulou et al., 2010; Ollila & Yström, 2013). This was expected because since almost a decade ago, Open Innovation has been recognised as ‘both a set of practices for profiting from innovation and a cognitive model for creating, interpreting and researching those practices’ (West et al., 2006, p. 286). Because the idea of OI derives to a great extent from managerial practice, there is an opportunity to integrate the actual practices to manage innovation with other organisational approaches (van de Vrande et al., 2010). For instance, some views conceptualise knowledge as core capabilities which are required for a firm to perform certain practices (Gherardi, 2000). However, solely using a view like this (e.g. DCs) would obscure the relevance of practices. Conversely, it is recognised that a possible critique of solely using a PBV to study OI could be the obvious connection between this approach and the OI model. But on the other side and from a real-world viewpoint, practices cannot be disregarded since they are part of human existence and thus they are co-present in everyday organisational life, learning, communication, and innovation (Gherardi, 2000), regardless of the management theories or models that researchers choose to study them.
2.2.4. OI as practices and habitual modes
Once the choice of using a PBV has been explained and justified, it is then vital to describe better how practices can be related to OI. In this regards, two perspectives are chosen in this thesis: (1) OI as practices and modes that are regularly performed, and (2) OI as models of interacting practices with multiple possibilities of configurations based on the varieties of three specific elements.
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To elaborate on the first perspective, it is important to remember that organisations have historically invested a great amount of resources in IRD to drive innovation. However, current stronger global competition has influenced higher knowledge sharing and collaboration on the innovation process in firms (Gassmann, 2006). OI as the idea of opening the firm’s innovation processes was conceived by using ideas from traditional management but enriched to represent modern innovation practices by firms (van der Meer, 2007). Therefore, a common way to operationalise OI is through three main types of practices by firms: INB (or outside-in), OUT (or inside-out) and coupled activities (Gassmann & Enkel, 2004).
The adoption of these practices does not imply that a firm should stop its established internal innovation. Instead, the OI model suggests that internal innovation in a firm, e.g. R&D, should be balanced with other sources of knowledge and paths to market (Huizingh, 2011). In other words, to benefit the most from its technology a firm ‘can and should use external ideas as well as internal ones, and internal and external paths to market’ (Chesbrough, 2003, p. 16). Thus, by opening up the innovation process firms can complement and leverage their R&D investments with outside partners (Colin C J Cheng & Huizingh, 2014). These outside partners, e.g. individuals or universities, have been studied less often as paths to new markets outside the firm and more frequently as external sources of innovation (West & Bogers, 2013). According to OI literature, it seems that the three main types of practices, i.e. INB, OUT, and coupled, can be more or less be open (Huizingh 2011). Thus, OI should not be considered as a dichotomy but as a continuum with different degrees of openness (Dahlander & Gann, 2010). Moreover, these assumptions seem to be applicable in most type of industries, including mature ones. For instance, one of the first studies of OI in mature industries by Chesbrough and Crowther (2006) showed INB innovation to be the dominant mode in practice. Similarly, Vanhaverbeke’s (2006) and van der Meer’s (2007) studies on Dutch SMEs from mature industries indicates that in this context, the activities to import innovation from external sources are more frequent than the exporting ones, which is due to great barriers perceived in mechanisms to exploit internal innovation. Both studies have influenced research agendas including the ones focusing mainly on INB practices, in mature industries or even a combination of both (Lazzarotti et al., 2010). Based on this, we can see that studies focusing mainly on INB OI are frequent and equally valuable even if not considering the three modes of OI (e.g. Chiaroni et al., 2010; West & Bogers, 2013). Likewise, recent research confirms the existence of greater adoption of INB versus OUT in firms from mature manufacturing industries. For example, Chiaroni et al.’s (2011) study on the largest cement firm in Italy confirmed that INB OI is already widely adopted in practice, however the OUT dimension has not been completely implemented. Similarly, Ili et al.’s (2010) study on the German automotive industry, a widely known mature asset-intensive industry, shows INB activities having a higher rate of implementation over OUT ones. These findings together with other studies seem to indicate that while coupled activities are not so clearly differentiated in all industries, OUT activities are more diffused in high-tech firms, and INB activities are more frequent in low-tech firms (Gassmann & Enkel, 2004) and mature industries (Chiaroni et al., 2010). These findings suggest that a suitable way
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to investigate OI in mature industries is by setting aside coupled practices and keeping the INB and OUT practices theoretically and empirically separated (Chiaroni et al., 2011). In addition, it is vital to recognise that the construct of internal innovation could also be considered as a particular and key concept for empirical studies on the adoption of Open Innovation. ITM literature has long recognised firms cooperating with external partners in its internal innovation process (De Backer & Cervantes, 2008). The same case is visible with the enrichment of internal innovation processes, mainly R&D inside firms, by external knowledge. For example, the concept of ACAP (Cohen & Levinthal, 1990), relates to the firm’s ability to identify information from external sources, assimilate it, and further employ it to commercial ends. Related to this, R&D inside a firm plays a major role as the ACAP might be created as a by-product of a firm´s R&D investment (Cohen & Levinthal, 1990, p. 129). Thus, this example shows the relevance of IRD for developing ACAP but also that an increase in IRD efforts could also increase external knowledge sourcing (Veugelers, 1997). Another example is the notion of exploration and exploitation (March, 1991) which has also been used recurrently as a reference for OI studies (Dahlander & Gann, 2010; Huizingh, 2011). More specifically, INB OI relates to the firm´s capabilities to explore sources of innovation, while OUT OI is more related to the firm´s capabilities to exploit current knowledge and technology (Bianchi, Cavaliere, Chiaroni, Frattini, & Chiesa, 2011; Chiaroni et al., 2011). These concepts could also be related to practical capacities inside the firm namely R&D of new technologies. In addition, when trying to gauge OI in the most analytical way it seems necessary to clearly divide OI practices while still considering IRD in order to have a better measure of OI. Examples of this include using empirical measures for each key innovation practice such as firm´s patents (De Backer, López-Bassols, & Martinez, 2008) or proposing validated measurement scales for all types of OI practices (Colin C J Cheng & Huizingh, 2014). In this regard, several approaches to fully measure and grasp OI have not only considered the two main OI practices (INB and OUT) but also IRD. For instance, studies have included using an index depending on the level of OI policies within a firm and its network in terms of producing, consuming and distributing knowledge and technology (Yun, Won, Hwang, Jung, & Kim, 2013). In this case, a firm has a higher OI index (or openess) if it is involved in the three types of practices but also if it uses a larger number of activities. This index could be similar to the idea of breath and depth in the adoption of OI (Laursen & Salter, 2006) but with a higher emphasis on the role of IRD. In any case, it seems widely accepted that the capacity to innovate internally also needs to be accounted for as part of the empirical indicators measuring OI (OECD, 2008a). This trend has started since the incorporation of some OI-related questions in the Oslo Manual (OECD, 2005) and have continued in all the waves of the CIS (Eurostat, 2013). Likewise, the recognition of IRD and OI practices is clear in managerial tools to gauge the INNO of firms such as the IMP3rove assessment (Brunswicker & Vanhaverbeke, 2011) or the Open2-Innova8ion Tool (Caird, Hallett, & Potter, 2013). Based on these rationales, Figure
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2-3 depicts how all the innovation practices inside a firm could be considered as three non-sequential but closely related constructs to the adoption of OI.
Figure 2-3. Capabilities and activities interlinked under an OI approach
Based on the above, before looking for innovative solutions through external sources of technology, a firm must have a strong R&D ability (Veugelers, 1997; Xiaobao et al., 2013). A lack of this type of ability would suggest a weak internal innovation capacity, or IRD, that would not allow a firm to attract partners and thus, would lack external sources to innovative (Negassi 2004). Actually, the importance of this ability is documented in literature that confirms the positive effect of a firm’s innovation capacity when competing and surviving against others. In addition, the OI model suggests neither stopping IRD nor fully outsourcing it; rather the model suggests completing IRD through external ideas (Chesbrough & Crowther, 2006). So in brief, we can say that the internal innovation capacity driving a firm’s IRD relies greatly on the critical knowledge inside the firm. Thus, key IRD practices and routines can help to integrate internal and external resources and ideas. Because this integration can be made through (INB and OUT) OI practices, it is correct to assume that internal R&D continues to be a key element in the OI model (Xiaobao et al., 2013).
2.2.5. OI as models of interacting practices
Besides OI practices as regularly performed activities, the second perspective considered in this thesis relates to OI as models of interacting practices with multiple possibilities of configurations. The notion of models are considered because OI can be implemented through these but also because different models of OI are linked to different strategic, managerial, and organisational practices (Manzini et al., 2013).
To#research#
To#exploit#
Producing**(Tech.#&#know.)#
Distribu/ng##(Tech.#&#know.)#
Consuming##(Tech.#&#know.)#
Open#Innova9on#
Inbound*prac/ces*
Internal#Innova9on##
R&D*prac/ces*
To#explore#
To#develop#
Open#Innova9on#
Outbound*prac/ces*
Theore9cal#direc9on#
Prac9cal#direc9on##
Knowledge#and#
Technology#Prac/ces*
Innova9on#capabili9es#
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Therefore, the degree to which a firm can adopt OI models can be framed in a variety of ways according to literature. For instance, Laursen and Salter (2006) introduced the concepts of partners’ breadth (i.e., number of sources used for OI) and depth (i.e., intensity of collaboration with each source) of external sources. This approach was later revisited by Keupp and Gassmann (2009) but still widely accepted in OI literature. Researchers such as van de Vrande et al. (2009) studied different degrees of openness in terms of level of integration and time horizon. Pisano and Verganti (2008) studied the differences in governance and participation models related to OI. Lazzarotti and Manzini (2009) introduced two variables influencing OI models: the partner variety (number and type of different partners), and innovation phase variety (the number and type of phases of the innovation process opened to external contributions in and/or out). Bianchi et al. (2011) further developed this idea by adding INB and OUT as organisational modes of OI to be used with certain R&D phases and partners. Likewise, other researchers (Huizingh, 2011; Oh & Rhee, 2010; Wu, 2006) have emphasised the possibility of different model configurations based upon the different types of content provided by the partners while stressing the weight of context characteristics. Following these contributions, it is logical to assume that firms may tailor their specific OI model and this choice is inherently related to some context characteristics of a firm´s environment. Although a specific OI model may have different dimensions according to different authors, a parsimonious perspective may focus on the variety of ways a firm collaborates with different partners, during different innovation phases and interacting with different objectives. Considering this idea, this thesis adopts one of the first and most accepted works on partner variety by Laursen and Salter (2006). Similarly, it considers the variety of the innovation phases when collaboration and OI practices take place. In this respect, several authors have proposed a variety of specific phases. For instance, Bergström et al. (2010) suggested four phases where collaborations can support product development: inspiration, identification, ideation, and implementation. Dewangan and Godse (2014) proposed four phases: generation, incubation, commercialisation, and realisation. More focused on co-creation but still related to OI ideas, Russo-Spena and Mele (2012) suggested ‘five co-s’ for innovating practices: co-ideation, co-valuation, co-design, co-test and co-launch. While the proposition of the later phases is valuable, there are a variety of phases well recognised in OI literature. These were proposed by Lazzarotti and Manzini (2009) who labelled them as idea generation, experimentation, engineering, manufacturing, and commercialisation. These five phases have been revisited and confirmed with subsequent studies (e.g. Lazzarotti et al., 2011) demonstrating its validity and usefulness. Moreover, these phases have been recently proposed to be studied with a third dimension of openness related to content variety (Manzini et al., 2013). In fact, studies addressing and extending the understanding of content variety in OI have been urgently called for (see e.g. Huizingh, 2011). Following this call, in recent years some researchers have started to empirically investigate this dimension of OI with positive results. For instance, Bengtsson et al. (2015) considered content variety with two dimensions: explorative knowledge content such as access to new technologies or markets by suppliers (Azadegan & Dooley, 2010; Yan, Azadegan, & Oke,
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2014) and exploitative knowledge content such as technological and supply chain management capabilities (Oh & Rhee, 2010; Wu, 2006). Considering the ideas above, the adoption of OI as a model of interacting practices between partner, innovation phase, and content variety is also considered. Figure 2-4 shows a representation of these three varieties inspired from similar three-dimensional conceptual models suggested to understand OI (e.g. Bianchi et al., 2011). The figure also shows the operationalisation of these dimensions taken from recognised literature (Azadegan & Dooley, 2010; Gassmann & Enkel, 2004; He & Wong, 2004; Laursen & Salter, 2006; Lazzarotti et al., 2011; Lazzarotti & Manzini, 2009; Oh & Rhee, 2010).
Figure 2-4. OI models based on the possible variety on three key elements
2.3. OI relevance for specific industrial contexts
As previously stated, it is widely accepted that OI is highly context-dependent. Therefore, in order to analyse OI phenomena this situation needs to be emphasised in research. In fact, this idea is continuously stressed in this thesis to the extent that it is visible in the thesis objectives (section 1.3) where a constant factor is the allusion to context in terms of understudied industrial contexts, different actors, and specific organisational scenarios. To begin with it is key to recall that the innovation processes in general greatly differ in several respects according to the economic sector, type of innovation, and country concerned, but also to the firm’s size, its technology intensity, and its corporate strategy (Pavitt, 2004). Likewise, the
Partner Variety Innovation
Phase Variety
Content Variety
• Universities and research centers • Innovation intermediaries • Government agencies • Customers (i.e. retailers) • Suppliers • Consumers • Competitors • Companies in other industries
• Access to leading edge of technology • Innovative products and/or services • Innovative processes • Opening up new markets • Reliable deliveries • System responsibility • Project management capability • Improvement capability
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adoption of OI could equally depend on these factors considering that the sources and purposes of innovation are contingent upon the internal and environmental context (Pavitt, 1984). In fact, the idea that OI models and practices are sensitive to context and contingency, is not surprising since the nature and patterns of innovation are contingent and can differ deeply by strategy, firm, and sector (Tidd, 2014). Thus, the relevance for firms to adopt Open Innovation can also differ depending on other factors including their sector, industry maturity, technology intensity, and mostly size.
2.3.1. OI and manufacturing industries
The importance of the manufacturing sector should not be doubted. In fact, it is relevant to the economy solely by its output, number of workers and number of enterprises falling into this category. Manufacturing firms not only support local, regional, and national economies but they are also the cornerstone of innovation. In fact, they fund most corporate R&D and the resulting innovations can improve life standards and drive the development of other sectors and industries (Langdon & Lehrman, 2012). Thus, it is not surprising that some firms used initially to study OI belonged to this sector (Chesbrough, 2003a; 2003b; Gassmann & Enkel, 2004). In fact, trends researching OI in empirical settings logically paralleled other trends in innovation studies including the manufacturing sector as a recurrent source of data. A clear case is the use of surveys, which were amongst the earliest and most popular sources of empirical data for OI (West et al., 2014). For example, when Laursen and Salter (2006) used Europe’s CIS to highlight the limitations of OI, they started (without foreseeing it) a trend on using the CIS as a reliable source of OI data. In this sense, while they mainly focused on OI practices in some industries from the manufacturing sector, their publication triggered the use of the CIS to study a variety of phenomena related to external sources of collaborative innovation in other sectors and industries also included in the CIS (Eurostat, 2013). Certainly, it is not surprising that the CIS is used in several studies as a source of reliable innovation data since it was designed to measure several aspects of it. What it is more interesting about the CIS is that it is mostly used to study innovation using sectors or industries as a key contextual factor. Examples of these can be found in several studies (e.g. Conte, 2002; Mothe & Thi, 2010; Robertson, Smith, & Tunzelmann, 2009) in which industry diversity is considered a key external characteristic of the firm’s environmental context influencing several organisational phenomena. Similarly, data from the CIS has been used to investigate different aspects of OI adoption and implementation. While some studies focused only on the manufacturing sector, others underlined its difference from other sectors. Thus currently, using the CIS data to research OI is a common practice (e.g. Barge-Gil, 2013; Cricelli et al., 2015; Ebersberger, Bloch, Herstad, & van de Velde, 2012). So, it is recognised by the ITM community that the CIS provides a great amount of data about collaborative approaches to innovate. However, it has been cautiously criticised as not being the best option to collect OI related data since its purpose is more general and it is addressed to
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a broader sample (Martini, Aloini, & Neirotti, 2012). In addition, some researchers have sporadically mentioned (certainly not published) that the results of the CIS can only be a proxy of OI constructs, and thus a survey specifically tailored to collect OI constructs would be more appropriate. For instance, a tailor-made Open Innovation Survey (OIS) can be equally valuable to investigate OI solely in manufacturing SMEs (Theyel, 2013) or most types of manufacturing firms (e.g. Bengtsson et al., 2015; Grundström, Sjöström, & Öhrwall Rönnbäck, 2013; Manzini et al., 2013; Podmetina & Smirnova, 2013; Stefan & Bengtsson, 2014). Likewise, an OIS can support investigating more specific manufacturing industries such as automotive (De Massis, Lazzarotti, Pizzurno, & Salzillo, 2012; Di Minin, Frattini, & Piccaluga, 2010; Ili, Albers, & Miller, 2010; Karlsson & Sköld, 2013; Lazzarotti, Manzini, Pellegrini, & Pizzurno, 2013; Sierzchula, Bakker, Maat, & Wee, 2015). Perhaps a more balanced view to study OI in the manufacturing sector should include using different types of data, either CIS or tailor-made surveys, as long as it helps to understand OI in specific industries (Salmelin, 2015). In any case, as we can see from some of the previous studies, the industries in the manufacturing sector seem to be highly investigated in the OI literature. Nevertheless, the empirical evidence on OI practices in some specific manufacturing industries is still limited (Tidd, 2014). This gap in the literature is expected since many understudied industries have a great potential to adopt OI practices. Figure 2-4 shows the percentage of potential to adopt and implement OI in certain industries in Germany according to practitioners, policy makers, and academics surveyed in the Open Innovation Accelerator Study (Diener & Piller, 2013).
Figure 2-5. Open Innovation potential in different industries
Finally, it should be briefly stated that while studying the adoption of OI practices in manufacturing industries there could be the opportunity to investigate their link with other challenges specific to this industrial context. A clear and relevant example is the case of energy management and energy efficiency (EE). In this respect, it is well known that manufacturing
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industries account for almost one-third of total energy use worldwide (European Commission, 2013b). Electricity comprises one quarter of this energy, while fossil fuels provide most of the rest either as process heat, self-generation of electricity, and co-generation of heat and power (IEA, 2013). Thus, it is evident that the correct conservation, recovery and management of energy are of crucial importance for the productivity of manufacturing industries and even more of energy-intensive ones (IIP, 2013). This situation can be translated into researching and finding novel practices for these industries to be more energy efficient. Considering the above, it is possible to find numerous links between manufacturing firms searching for the improvement of their INNO but also its EE. For instance, besides its environmental and competitiveness benefits, EE provides a return on investment that can directly contribute to the expenditure in innovation practices and to the profitability of firms (Brown, Cortes, & Cox, 2010). This connection has gone unnoticed for energy-intensive manufacturing industries and thus, it has been proposed that innovation and organisational networks could decrease barriers to EE (Lutzenhiser, 1994). Similarly, a connection between innovation and adoption of EE technologies, or best available technologies (BATs) for EE, has been suggested in the foundry industry (Trianni, Cagno, & Worrell, 2013). Finally, because only limited studies have researched collective innovation in the iron industry (Allen, 1983) or suggested the potential of OI in the energy sector (Arnold & Barth, 2012; Hakkim & Heidrick, 2008), more can be done in this regard.
2.3.2. OI and mature industries
Despite great advances in technology in the last years, currently most firms are competing in mature industries. This suggests that although mature industries are usually more profitable, firms competing in mature industries need to deal with a saturated and slow-growing demand, consolidated competitors, and eroded margins and returns (Forbes & Kirsch, 2011). On the other hand, in mature industries there are fewer firms, and those that survive will be larger and more dominant. An interesting phenomenon in mature industries is that while innovations continue at a slower pace in comparison with emerging and growing industries, they are mostly incremental and not radical as the market is already established (Caiazza, 2015). Likewise, many years ago it was noticed that process innovations, and not products, are the dominant ones in mature industries (Abernathy & Utterback, 1978). These dynamics and constraints in mature industries suggest that organisations operating inside these industries could use OI in order to differentiate their innovations and value proposition. Some firms have spotted this opportunity, as well as researchers who have studied the benefits for these firms when adopting OI. Studies in mature industries such as food and beverage (F&B), machinery, or chemicals, have found that mechanisms to import external sources of innovation are common in firms from this type of industry, while mechanisms to export and exploit their technologies are less frequent (van der Meer, 2007; Vanhaverbeke, 2006). More recent studies in firms operating in industries like cement and concrete, steel pipes, adhesives and even aerospace, have contributed to better explain the OI adoption process in mature
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industries (Chiaroni et al., 2010; Parida et al., 2011). Additionally, most previous OI research has greatly focused on emerging and growing industries with high-tech profiles such as biotech, ICT, and pharmaceuticals. Therefore, the technology intensity both of the industry and from its firms should be noted to demarcate the focus of OI research. After the concept of OI was coined, research increasingly focused on high-tech sectors. A few years later, a research stream was proposed to study OI in firms beyond high-tech emergent industries (Chesbrough & Crowther, 2006). With these studies, it was noted that industries such as chemicals, medical devices, lubricants, and aerospace could also benefit from applying OI practices. More recent studies on the characteristics of OI in low-tech mature environments such as the cement industry have provided further evidence of this (see e.g. Chiaroni et al., 2010). These studies have opened the door to studying the adoption of OI in other mature industries with different technology intensity and other particular characteristics. However, it should be remarked that a common debate often appears on how to define an industry as having high, medium, or low technology. This confusion arises mainly because it is not yet fully clear if an industry is high-tech because it is producing high technology, i.e. direct R&D intensity, or because it is using high technology, i.e. indirect R&D intensity (Robertson et al., 2009). This signals that other characteristics besides sector and maturity level need to be considered when choosing industrial contexts with a potential to shed more light on OI.
2.3.3. Matching potential industrial contexts to study OI
Even if the potential to study the adoption of OI in mature manufacturing industries is clear (Figure 2-4), other elements should be examined including the life cycle stages, the technology intensity levels, and mostly the firm size. However, if considering the latter, selecting a firm or an industry based on its technology intensity can be complex. This issue arises when categorising the firms operating in an industrial sector, because it can be composed of a mix of low, medium, and high-tech firms. This means that although an industry may be classified in any of these levels, they could be composed of firms that do not match this classification, suggesting a high degree of inter-sectorial heterogeneity (Hirsch-Kreinsen & Jacobson, 2008). Moreover, low and medium-tech firms are often seen as old-fashioned and expectedly, their markets are mostly mature (Robertson et al., 2009). Therefore, it seems equally critical to focus on the life cycle of the firm and also on the life cycle and maturity level of its industry when studying innovation activities (Hirsch-Kreinsen & Jacobson, 2008). Based on these issues, a useful approach to investigate OI practices could focus on firms and industries with corresponding degrees of life cycle and technology intensity. This narrower industrial context to investigate further the role of OI practices is indicated with the coloured boxes in Figure 2-5.
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Figure 2-6. Industrial contexts to study OI based on its maturity and technology intensity.
While categorising all sectors and firms within the above framework would be rather complex, specifying some specific research contexts is more straightforward. For instance, if focusing on some mature industries from the manufacturing sector such as the food, foundry, and the automotive, all of these use low and medium-technology (indirect R&D intensity). Similarly, while some of the firms in these industries produce medium-tech products (direct R&D intensity), others produce less technology-intensity ones. Of course, this categorisation is not free of subjectivity. For instance, the automotive or the food industry could be considered as a high, medium-high or medium-low technology-intensive industry depending on the viewpoint used. More precisely, the automotive industry as a whole can be classified as high-tech due to the technology used on the end products, however based on a sectorial approach (i.e. manufacturing) it is considered as medium-tech due to its major manufacturing processes (Hatzichronoglou, 1997). Also, if considering the firms operating along the value chain in this industry, then almost 50% of them are low-tech due to the average annual investment of less than 2.5% in R&D (Hirsch-Kreinsen & Jacobson, 2008). This circumstance makes it more difficult to catalogue industries and firms according to innovation levels (Pavitt, 1984), but still shows that a specific industrial context where innovation occurs frequently are manufacturing firms in mature industries.
2.3.4. OI and manufacturing SMEs in mature industries
As previously stated, besides maturity and technology intensity, firm size is a key internal context characteristic defining innovation endeavours. Interestingly, the manufacturing sector is largely composed by SMEs, which overall are defined as firms with less than 250 employees and €50 million of turn over (Verheugen, 2003). Manufacturing SMEs have limited resources in comparison with large firms which in turn makes the implementation of solutions difficult to have better industrial performance (Trianni et al., 2013). Moreover, although an increasing
Technology*intensity* Life*cycle**
Firms*
Industry*and*Sectors*
*
Low*
Medium*
High*
Low*
Medium*
High*
Emerging*
Mature*
Growing*
Emerging*
Mature*
Growing*
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number of SMEs are offering services (Baines, Lightfoot, Benedettini, & Kay, 2009), a majority of SMEs remain as more traditional manufacturing firms (OECD, 2015). Thus, it is not surprising that traditional or mature industries are predominantly characterised by SMEs that commonly have a limited R&D intensity but not necessary a low innovation capacity (A. Spithoven et al., 2010). Probably, only a few of these SMEs are performing better than average and multiple efforts of different kinds have been or are undertaken to improve their performance, including new approaches to manage innovation (Grundström et al., 2013). For these reasons, even if it is not so obvious for all organisations, the adoption of OI practices could be a performance differentiator, especially in manufacturing SMEs. This idea can be confirmed with large-scale surveys establishing that SMEs are collaborating as frequently with external innovation partners as large firms (Brunswicker & Vanhaverbeke, 2014; Eurostat, 2013; Idrissia et al., 2012). Still, a note of caution is appropriate: the CIS from 2012 showed that large firms were collaborating on average with more external partners than small firms (Salmelin, 2013). This idea is aligned with recent findings suggesting that large firms leverage external resources for innovation more often than SMEs (Dooley, Kenny, & Cronin, 2016). However, the emphasis should not be on the frequency of collaboration but rather on the impact of it (OECD, 2014). In this sense, if considering the ‘OI intensity’, i.e. number of collaborations divided by the number of employees, it is clear that smaller firms rely more on OI than large organisations. Thus, it can be surely assumed that OI is more important for SMEs than for large firms (Vanhaverbeke, Vermeersch, & Zutter, 2012). In addition to the above, studying SMEs is inherently relevant since most of the world’s businesses fall under this categorisation. In addition, the input that SMEs generate to the economy has been acknowledged for decades. Just in the European region, 98% of the enterprises comprise SMEs (European Commission, 2013b; Verheugen, 2003) and the percentage is similar in underdeveloped regions. An interesting phenomenon in SMEs is that although most of them lack systemic processes and they focus on one or few technological developments, they are highly specialised and possess deep knowledge that allows them to innovate (Parida, Johansson, & Larsson, 2009). Also even if SMEs do not have the same amount of resources as large firms, due to their size and organisational structure they are flexible, responsive to the market, with a high focus on their costumers, which makes them highly competent (Rahman & Ramos, 2013). Therefore, the potential to adopt OI by SMEs supposes a further advantage in their innovation process. However, there are important challenges related to it. One of the current problems is that SMEs most of the time struggle with OI implementation due to their low level of absorptive capacity, perceived management challenges, and policy constraints (Brunswicker & Vanhaverbeke, 2011; Spithoven et al., 2010; van de Vrande et al., 2009). Moreover, a difference between implementation and adoption of OI practices can have different outcomes. While the former relates more to a firm being aware of an OI practice and trying it, the latter relates to the idea of an OI practice being used in a dynamic process requiring sustained effort and actually driving better performance (Brunswicker & Ehrenmann, 2013). Also it is
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necessary to distinguish between diffusion and adoption. While diffusion signifies how a certain innovation (practice) spreads in a certain group (e.g. within a sector), adoption is linked to the series of stages within the individual adoption process that could include stages such as knowledge, persuasion, decision, implementation, and confirmation (Rogers, 1962). In addition, the lack of clear understanding of the relation between OI adoption and firm performance including SMEs in mature industries remains an open issue (Mazzola et al., 2012). Therefore, although available evidence from numerous cases in other industries, managers in SMEs from mature industries will be reluctant first to implement and then to fully adopt OI if they are not fully convinced that some of its practices can enhance to some degree different types of firm performance (Idrissia et al., 2012). In this regard, managers could benefit more by understanding which OI practices could have the highest probability to be useful in their specific industrial context, but also by knowing if they should focus on certain (INB and OUT) practices separately or use them simultaneously (De Backer & Cervantes, 2008; Frishammar & Ake Horte, 2005; Schroll & Mild, 2011).
Considering the ideas above, when looking for literature in Open Innovation adoption by SMEs, the articles can be grouped in a number of ways. One option is to suggest a research agenda as one of the most cited articles in this topic by van de Vrande et al. (2009). This contribution can be described as an early explorative research on Dutch SMEs, which investigated OI in these firms from a perspective of exploitation and exploration noting that a variety of OI methods and practices were already applied. The article also pointed out that the aim for SMEs using OI was to improve their market position and that applying OI was more common among medium-sized firms. Still, how much small firms use OI compared to large firms can vary a lot between industries (Wyckoff & Koreen, 2010). Another article comparing groups of manufacturing SMEs was the one by Idrissia et al. (2012). Although focusing on clustering manufacturing SMEs, it stated that not only the internal environment of firms can explain a higher degree of openness, but also the external or environmental factors. Other highly cited articles on the topic of OI and SMEs have used an ACAP perspective. Since companies within the traditional industry do not have, or have only minor ACAP, Spithoven et al. (2010) investigated how intermediaries in the form of research centres could help traditional sector SMEs to enhance their ACAP. Huang and Rice (2009) reached similar conclusions with regard to the importance for management to arrange or facilitate ACAP in manufacturing SMEs. Caetano and Amaral (2011) on the other hand proposed a method for technology push (technology road mapping) and stated that this was suitable for SMEs and independent research centres as a means to expand the capabilities of SMEs. However, as Kim and Park (2010) noticed not all OI activities have a positive impact on the innovation output. For instance, external R&D but not external ideas have a positive impact on the innovation outcome. This was particularly true for low-tech manufacturing SMEs since these firms usually have problems setting up regimes to absorb the technology or knowledge and apply them through specific practices.
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Indeed, a high number of studies have focused on OI in high-tech SMEs. However, this is considered outside this research scope mainly because high-tech firms are not the majority of SMEs in mature manufacturing industries. Having clarified this, there is another research stream about Open Innovation adoption in SMEs highlighting the relevance of networks. For instance, studies focusing on networks involving SMEs which adopt OI have found that governance in NPD networks (Lazzarotti, Manzini, & Pizzurno, 2012) and goal complementarity are important for success of SMEs in traditional sectors (Pullen, Weerd-Nederhof, Goren, & Fisscher, 2012). Similarly, researchers have studied the role that SMEs networks play on R&D performance (Suh & Kim, 2012) and the effects of network openness in SMEs (Xiaobao, Wei, & Yuzhen, 2013). Another research stream of OI in SMEs has focused explicitly on OI practices while involving various aspects. For instance, Tranekjer and Knudsen (2012) found that providers of knowledge, compared to receivers, can be characterised as younger, more R&D intense, having higher ACAP, more prone to use OI practices, and more open to sharing knowledge. Bianchi et al. (2010) presented methods to assess opportunities for OUT OI practices, while Spithoven, Vanhaverbeke and Roijakkers (2012) found that SMEs can use various OI practices when introducing innovations. Teirlinck and Spithoven (2013) stated that the propensity to collaborate varies with size, and small firms (i.e. 10-49 employees) are most likely to collaborate. Regardless of size, formal qualification positively affects the propensity to outsource R&D. This contradicts somewhat the findings by van de Vrande et al. (2009), who found that medium-sized firms overall were more involved in OI practices and activities. Finally, researchers have emphasised the relevance of selecting proper OI partners in any kind of industrial scenario (see e.g. Gürtler & Lindemann, 2013), but also in specific situations such as in collaborations by manufacturing SMEs. Examples include studies stressing the benefits of collaborating with partners who have a similar knowledge base (e.g. Tranekjer & Søndergaard, 2013). Such studies provide evidence that the partners with whom manufacturing SMEs practice OI need to be carefully selected (Theyel, 2013). In this respect, researchers have suggested a model to align performers of outsourced R&D with firms adopting OI (Albors-Garrigos, Etxebarria, Hervas-Oliver, & Epelde, 2011). Also, researchers have proposed how managers in a manufacturing R&D unit should apply management tools and techniques to implement OI strategy (Igartua, Albors-Garrigós, & Hervas-Oliver, 2010). Other studies have highlighted the importance of universities and spin-offs (Padilla-Meléndez, Del Aguila-Obra, & Lockett, 2013) while others have emphasised institutions and competitors (Hemert, Nijkamp, & Masurel, 2013) as important means for manufacturing SMEs to explore technology and innovation opportunities. These are just a few of the research streams in which this thesis can contribute when focusing on manufacturing SMEs.
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3. Research Design
3.1. Philosophical and methodological motivation
For many years, researchers in the IM field have used a wide range of approaches, methods, and techniques to study phenomena with different perspectives. In fact, different from other social sciences like economics, in general, the field of IM seems to have become more diverse methodologically (Fagerberg, Fosaas, & Sapprasert, 2012). Therefore, it is not surprising to find researchers studying the same IM phenomenon with similar or contrasting methods. The same tendency happens in the case of researching OI where methodologies can differ widely since OI is a construct that cannot be measured directly (Schroll & Mild, 2012). Certainly, it would be quite a task to use all of these methods for a single doctoral research project; however, combining some of them could add to the desired multi-perspective study and provide valuable results. Based on these ideas, to study OI practices in mature manufacturing industries, a change is needed to see a specific type of IM tied to a certain industry. In my case, I followed a Kuhnian perspective by not considering OI as a right or wrong model for these types of industries but as an IM model that can be developed in parallel with traditional ones. However, it should be highlighted that my position is not that the closed and OI paradigms are incompatible, as both models share common frameworks and fundamental concepts. Thus, from my viewpoint the Open Innovation paradigm is not better than the ‘closed’ one, they are just different (Kuhn, 1963). Moreover, because of the heterogeneity and contingent nature of innovation, it is improbable that there is a one ‘global best model’ innovation (Pavitt, 2004). Therefore, if being critical of Open Innovation it is necessary to consider that it might be more appropriate for some firms than for others. Some researchers have noted a debate (still on-going) on whether the OI model displays relevant characteristics for being considered a paradigm in a Kuhnian sense (Lichtenthaler, 2011). In addition and as previously explained in the introduction, even though someone may not believe that the manufacturing sector could be experiencing a complete paradigm shift (Kuhn, 1963), there are clear signals that at least the sector could have been experimenting with a partial shift in its industrial R&D (Chesbrough et al., 2006; Chesbrough, 2003a). Therefore, from a theoretical and a practical view, I agree that in the last years different players in mature manufacturing industries have adopted more open and collaborative practices to innovate, although in different degrees. Therefore, this industrial phenomenon should be studied through different approaches and methods in order to triangulate and validate the empirical evidence of it.
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3.2. Philosophical positioning and approach
It is important to state the philosophical assumptions adopted in my research, as this directly influenced the development of my studies in terms of research design and method for collecting data (Saunders, Lewis, & Thornhill, 2003). Thus to begin with, in my research I adopted an interpretivist ontology as I considered that the entities to be studied are part of a socially constructed and subjective world (Easterby-Smith, Thorpe, & Lowe, 2002). In turn, this choice influenced the main research strategies selected because I assumed in advance that due to several realities and the difficulty in measuring them, I cannot obtain an absolute truth in a subjective world but rather the facts and truth are relative to the paradigm I have chosen to study (Kuhn, 1963). Also, I adopted an interpretivist epistemology as I considered that situations and knowledge in the world are complex, unique and meaning-centric and thus, they cannot be studied with definite and universal laws (Saunders et al., 2003). In addition, the philosophical stance considered not only links all these assumptions but it contextualises my research methodologically. Because numerous philosophical stances could be chosen, it could be said that one is not better than the other. Instead, a philosophical stance should aim to indicate and drive consistency in terms of epistemological, ontological, and methodological assumptions (Morais, 2010). Based on this, the choice of having a subjectivist discovery and justification stance entails developing and testing a theory mainly about meanings (but if necessary also facts), which confirms a consistency between the research project choices. Also, it should be clarified that this thesis did not focus on using only a deductive or an inductive approach but rather a recurring combination of both, i.e. an abductive approach. This was useful because such an approach puts a real phenomenon into play to generate new theoretical backgrounds about it, rather than merely apply or prove a previous theoretical framework or model (Dubois & Gadde, 2002; Garcia Martinez, 2014). Moreover, the general aim of my research involved understanding the role of OI practices and their effect on firm performance considering contingency elements, which involves complex interactions. Therefore, together with the interpretivist perspectives chosen, using both quantitative and qualitative methods was deemed appropriate. This combination of data was probably more realistic, less subjective, and rich by nature reflecting that the OI phenomenon was studied within the real world and in a natural context (Mertens, 1998). Also it is worth noting that for me there was no right or wrong when deciding between a quantitative or a qualitative approach, instead the importance centres on the idea that it should fit the research aims, questions, purposes and be coherent with the research design (Robson, 2002). In any case, the distinction between qualitative and quantitative research has hardly been questioned, in part by the growing significance given to mixed methods (Adams, Khan, Raeside, & White, 2007; Bryman & Bell, 2007; Tashakkori & Teddlie, 2003). Therefore, a combination of both provides the opportunity to investigate diverse Open Innovation phenomena from different angles and with various research strategies, which is explained in more detail below.
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3.3. Research strategies
A research strategy (RS) can be defined as set of procedures and assumptions for acquiring knowledge which are coherent with sociological and logical forms (Morais, Martins, & Kansikas, 2009). Choosing and defining the most appropriate one is crucial because it links the philosophical approaches selected and the data collection and analysis techniques used to answer the MRQs (Morais, 2010). Thus, an issue arises when deciding which RS to use or even more, if several research strategies are needed. In this respect, it is useful to consider that ‘all research strategies and methods are seriously flawed, often with their very strengths in regard to one desideratum functioning as serious weaknesses in regard to other, equally important, goals’ (McGrath, 1982, p. 70). For instance, there is an intrinsic trade-off between qualitative RS and quantitative ones. Qualitative RSs can provide many analytical variables but there is a statistical sampling error due to few cases. Conversely, quantitative RSs can provide statistical data integrity but there is an analytical measurement error due to few analytical variables (Bonoma, 1985). It seems then that there is no perfect RS which allows for deep description and broad measurement of a phenomena (Morais, 2010). Instead, a possible alternative between choosing one or the other, could be the use of mixed methods and strategies (Bryman & Bell, 2007). In this respect, a multistrategy or multimethod approach would involve using numerous combinations of methods for answering research questions either in single studies or in projects researching complex phenomena (Brewer & Hunter, 2006). A rationale for choosing different strategies and a multimethod approach is that this option offers unique advantages of coordination and comparison of different methods and the corresponding findings (Birkie, 2015). Moreover, some researchers (e.g. Johannessen, 2009) have strongly argued in favour of applying several methods in the same research project when studying the relations of elements generating innovation in social and organisational systems. Considering the above, since this thesis consists of seven papers in order to present a multi-perspective study, several research strategies were used. These included obviously desk research, but mostly qualitative RSs like case studies, and also quantitative RSs such as surveys. Figure 3-1 depicts in general the different research strategies applied in each paper. It should be noted that both papers B and G used data collected with a survey. However, in paper B the database was already available since a research group collected it during 2011-2013. In the case of paper G, the whole survey was designed and applied from scratch and thus the database obtained is original and it could be said, one of a kind. Another clarification is the case of paper C applying a mixed strategy based on grounded theory, ethnography, but mostly case study norms. For this reason, it is positioned in the area of a single case study. Although desk research is properly not considered a RS but a research technique, it is included to recognise that the data for paper A and for paper D was obtained from secondary sources.
Research Design
53
Figure 3-1. Visual summary of the research strategies used in the thesis papers
At this point is necessary to talk about the quality criteria, determined by the philosophical stance and the RS, because this shows the specific tactics used to improve the research outcome. However, it is necessary to bear in mind that different quality criterion were considered because the papers differ in the type of RSs and techniques used to collect and analyse data. In this sense, we3 attempted to ensure external validity (or generalisability) by using theoretical perspectives that can explain Open Innovation phenomena not only in the studied contexts but also in other settings (McGrath, 1982). Thus, this approach included analytical generalisation requiring small samples analysed with descriptive statistics - papers A, C, D, E, and F - but also statistical generalisation requiring large samples analysed with inferential statistics - papers B and G (Yin, 1994). We also constantly ensured to fulfil internal (or logical) validity by assessing the causal relations between the theoretical keywords and the results. To do this we applied three actions: formulating clear research frameworks, comparison of empirically observed patterns with predicted ones in previous studies and in other contexts, and theory triangulation to verify results by considering multiple perspectives (Eisenhardt, 1989; Yin, 1994). Moreover, in all studies construct validity was a priority since it determined the quality of the operationalisation of the relevant research constructs. Thus, in every study we guaranteed that there was not a major distortion in the interpretation of the research constructs both by the researched people and us, the researchers (Morais, 2010). Likewise, in all studies we achieved convergent validity depending on the RS and the data analysis techniques. For instance, when analysing survey data, convergent validity was evaluated with recognised measurements such
3 When talking about the studies and papers the pronoun ‘we’ refers to my coauthors and myself.
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as the average variance extracted (Hair, Hult, Ringle, & Sarstedt, 2014). Even in case studies, this type of validity was also increased by means of triangulating the streams of thought, the origin of data, and the collection techniques (Cox & Hassard, 2010). Similarly, several quality criteria were used to enhance reliability in all studies providing transparency and replication. Thus overall, several recognised criteria were diligently considered for the qualitative data obtained from case studies (Denzin & Lincoln, 1994; Eisenhardt, 1989; Yin, 1994) as well as for the quantitative data collected through surveys (Aloini, Martini, & Pellegrini, 2011; Field, 2009; Hair et al., 2014; Liao & Barnes, 2015; Pallant, 2011; Storey & Kahn, 2010).
3.4. Data collection and analysis techniques
Because techniques (or methods) to collect and analyse data vary with the chosen RS (Bryman & Bell, 2007), this thesis used several of them. In any case, most of these techniques and methods were linked to two of the primary research strategies used, i.e. case studies and surveys. Thus, the description and justification of such techniques is presented considering both RSs. In addition, it is also important to clarify the chosen level and unit of analysis. While the former specifies the contextual scale of the data needed to answer the RQs, the former relates to the empirical entity, process or ‘thing’ to be studied (Yurdusev, 1993). In OI literature, researchers have identified five units of analysis: individuals, firms, dyads, inter-organisational networks and national innovation systems (Vanhaverbeke & Cloodt, 2006). In this thesis, organisational was the most common level of analysis considered while individual and inter-organisational levels were briefly explored. In turn, the units of analysis investigated in all studies but the LR, are practices. In this regard, different characterisations of OI practices were studied, in some cases as clear innovation practices but in others as routine mechanisms, interactions, and initiatives. More details about how data were collected and analysed are described next for each paper. In paper A, a LR, desk research was used to conduct a meta-LR. Through the software ‘Publish or Perish’ (Harzing, 2007) more than 1,450 publications were retrieved and then filtered based on the NCII (Holsapple et al., 1994). This resulted in analysing 159 articles through different techniques such as content analysis (frequency of themes and emphasis) and quasi-statistics (interpretation of frequencies). In paper B, a database from an Open Innovation Survey conducted from 2011 to 2013 with information from more than 400 manufacturing firms in Italy, Sweden, and Finland was used (Manzini et al., 2013). However, this data was collected by different research groups and not exclusively by myself with the exception of the variable related to firm age, which was information retrieved manually. For the analysis of the data different statistical methods were employed using the software SPSS. More specifically, regressions and multivariate statistical analysis such as MANOVA were diligently conducted according to procedures in literature (see e.g. Field, 2009 and Pallant, 2011).
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In paper C, a single case study of inter-organisational networks between firms in the F&B industry, universities, and an innovation intermediary was used. Besides the case study, a mixed RS using grounded theory and ethnography (Seidel, 1998; Strauss & Corbin, 1998) was also employed. The data was collected through semi-structured interviews with key persons involved in OI projects collaborating with different innovation actors. Please refer to Appendix A to see the interview guide used for this study. The collected data was not analysed using specific software but instead with a simple but robust manual qualitative data analysis (QDA) involving techniques such as constant comparison (grounded theory coding) and content analysis (Bryman & Bell, 2007; Ezzy, 2009; Mayring, 2000). In paper D, another combination of strategies was used, which included a thorough LR including the evaluation of known case studies and then complemented with a single case study related to the F&B industry. However, in this study both organisational and individual levels were considered to explore a phenomenon that we labelled as ‘Open Food’. Thus to explore this, direct observation and the Internet were used to collect data about collaborative initiatives driven by individuals and communities of them not necessarily driven by large firms in the F&B industry. The data was analysed with the collaborative software Dedoose, which included techniques such as content and taxonomy analysis (hierarchical typology). In papers E and F, case studies were used as the main RS and an important distinction with previous papers is that in both studies, multiple case studies were used. In this sense, both papers investigated OI practices in the foundry industry; however, the studied firms produced different types of alloys, i.e. aluminium, steel, and cast iron. Thus, these different contexts (i.e. different types of alloys) within the overall foundry industry in Italy provided the opportunity to have a multiple-case design (Yin, 1994). Although papers E and F shared the same RS, units and levels of analysis, the techniques used to collect and analyse the data were slightly different. In paper E, direct observation, documents and semi-structured interviews were used to begin exploring and understanding the research setting of foundries. Once the data was collected though these means, it was analysed with techniques such as analytical induction (case-based propositions) and logical analysis (cause-effect relationships) (Denzin & Lincoln, 1994; Faff, 2015; Mertens, 1998; Saunders et al., 2003). Once the potential of OI practices in the foundry industry was discovered, in paper F the data collection method was modified and improved from semi-structured interviews to more standardised questionnaires. Thus, considering the setting of multiple case studies in the foundry industry, the questionnaire used to collect data was carefully designed to include several types of small and medium-sized foundries. Please refer to Appendix C to see the questionnaire. The collected data was then analysed with different qualitative and quantitative methods and techniques but mostly quasi-statistics (e.g. interpretation of frequencies) as well as other mixed methods and analyses (Adams et al., 2007; Tashakkori & Teddlie, 2003).
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Finally in paper G, a convergence of many of the above-mentioned research strategies as well as methods to collect and analyse data were used. While most of the firms studied in papers E and F also serve as Tier-2 suppliers to the automotive industry, a more novel actor in this industry was selected. Thus, two exploratory case studies of small and medium manufacturers of supercars (SMMS) were conducted. One was a cross-sectional case study in the South of Sweden and the other one a longitudinal case study in Mexico City. Please refer to Appendix B to see the interview guide of these pilot case studies. The analyses of data such as internal documents, news, videos, interviews, and mostly direct observation collected from these case studies provided an initial opportunity to investigate OI elements in detail (Yin, 1994) while replication was a challenge (Eisenhardt, 1989). After these case studies, a large-scale survey of SMMS was conducted, which included a thorough design of a questionnaire presented in Appendix D. Thus, it could be said that in overall the data for this paper was collected through observation, internal documents, Internet, semi-structured interviews, and on-line questionnaires. In turn, the data was analysed by means of multivariate statistical analyses but mostly by Partial Least Square Structural Equation Modelling (PLS –SEM). More precisely, we used the software Smart PLS (Hair et al., 2014) while following recognised procedures and quality criteria for PLS-SEM in literature (e.g. Hair, Ringle, & Sarstedt, 2011; Lowry & Gaskin, 2014; Sarstedt, Henseler, & Ringle, 2011). Table 3-1 summarises all the research strategies, methods and techniques to collect and analyse data in the different studies.
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Table 3-1. Summary of key elements of the thesis research design
Rel
ated
thes
is
RQ
RSQ
1
RSQ
1 R
SQ3
RSQ
2
RSQ
2
RSQ
2
RSQ
3
RSQ
1 R
SQ3
Ana
lysi
s tec
hniq
ues /
sp
ecia
l sof
twar
e
Con
tent
ana
lysi
s, qu
asi-
stat
istic
s
Mul
tivar
iate
stat
istic
al
anal
ysis
/ SP
SS
Con
stan
t com
paris
on,
cont
ent a
naly
sis /
man
ual
QD
A
Con
tent
ana
lysi
s, ta
xono
my
/ Ded
oose
Ana
lytic
al in
duct
ion,
lo
gica
l ana
lysi
s
Qua
si-s
tatis
tics
Mul
tivar
iate
stat
istic
al
anal
ysis
, PLS
-SEM
/ Sm
art P
LS
Col
lect
ion
tech
niqu
es /
spec
ial
softw
are
Arc
hive
s (i.e
. pub
licat
ions
) /
Publ
ish
or P
eris
h
Que
stio
nnai
res /
em
ail,
on-li
ne
surv
ey to
ol
Doc
umen
ts, s
emi-s
truct
ured
in
terv
iew
s / V
oIP
softw
are
Arc
hive
s (i.e
. pub
licat
ions
), ob
serv
atio
n, In
tern
et
Obs
erva
tion,
doc
umen
ts, s
emi-
stru
ctur
ed in
terv
iew
s
Obs
erva
tion,
doc
umen
ts,
ques
tionn
aire
s
Obs
erva
tion,
doc
umen
ts,
inte
rnet
, sem
i-stru
ctur
ed
inte
rvie
ws,
ques
tionn
aire
s /
emai
l, on
-line
surv
ey to
ol
Res
earc
h st
rate
gy
Des
k re
sear
ch
(Lite
ratu
re re
view
)
Surv
ey
Cas
e st
udy
(sin
gle)
+
Mix
ed m
etho
d
Cas
e st
udy
(sin
gle)
Cas
e st
udy
(mul
tiple
)
Cas
e st
udy
(mul
tiple
)
Expl
orat
ory
case
st
udie
s + S
urve
y
Uni
t of a
naly
sis
Jour
nal a
rticl
es
Mod
els (
that
are
pr
actic
ed)
Mec
hani
sms (
that
ar
e pr
actic
ed)
Prac
tices
and
in
itiat
ives
Prac
tices
Prac
tices
Prac
tices
Leve
l of a
naly
sis
Ope
n In
nova
tion
liter
atur
e
Org
anis
atio
nal
(firm
s)
Inte
r-or
gani
satio
nal
netw
orks
Org
anis
atio
nal a
nd
indi
vidu
al
Org
anis
atio
nal
(firm
s)
Org
anis
atio
nal
(firm
s)
Org
anis
atio
nal
(firm
s)
Pape
r A
B
C
D
E F G
Tabl
e 3-
1. S
umm
ary
of k
ey e
lem
ents
of t
he th
esis
rese
arch
des
ign
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3.5. Research contexts and sample
In the contemporary context of extremely fast global innovation, new technologies and innovation can be found in all industries. Thus, it could be challenging to choose suitable settings to understand OI practices in the manufacturing sector because of the variety of industries. Methodically studying the practices in unique cases can expedite the comprehension of the drivers that can influence manufacturing innovation (APQC, 2015). Likewise, focusing on researching novel contexts can also contribute to validating previous OI findings and finding new ones (Giannopoulou et al., 2010; Huizingh, 2011; Randhawa et al., 2014; Tidd, 2013). Hence, a mixed selection of manufacturing industries was considered. This selection included industries already known for adopting OI such as the F&B and automotive industries, but it also investigated two industrial contexts seldom studied under an OI lens, namely foundries and SMMS. While not all the previous mature manufacturing industries were studied in one paper, all settings were useful to investigate the differential role of OI practices. To be more precise, while papers C and D focused on the food industry, papers E and F focused on the foundry industry. Although the firms investigated in paper B were a mix of manufacturing industries, the data collected from these industries were consistent with the contexts researched in this thesis. For instance, more than 20% of the firms in the survey in paper B were from the food industry (i.e. 49 firms), and around 32% were either from industries related to metal such as the foundry industry (i.e. 37 firms) or related to the automotive industry (i.e. 41 firms). In addition, 3 firms (paper C) and 13 organisations (paper D) operating within and around the F&B industry were also studied. Finally the count of firms included 30 foundries (papers E and F) and 48 SMMS (paper G). Considering the numbers of organisations investigated directly for the studies in this thesis, the proportion of firms studied in each industry and other investigated actors is shown in Figure 3-2.
Figure 3-2. Proportion of actors investigated for the different studies in the thesis
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In regards to the idea of researching OI in novel contexts, papers E and F investigated small and medium-sized foundries that also happened to serve as Tier-2 suppliers to the automotive industry. The main justification to study these firms comes from the idea that in order to reveal the different and unidentified roles of OI practices, these should be explored and be valid in understudied industrial scenarios. The sample for the foundry study comprised a considerable number of SMEs from Northern Italy (mainly in Lombardy) operating in different foundry industries. This thesis considers the SME definition promoted by the European Commission based on number of employees and annual turnover (i.e. small firms – fewer than 50 employees and less than 10 million euro; medium firms – fewer than 250 employees and less than 250 million euro). The selected foundry industries produce and transform three types of commodities: cast iron, aluminium, and steel. Also, these industrial sectors were selected because they are well known globally for being concerned not solely on innovation and financial performance indicators, but also on the industrial performance, which is commonly operationalised by the EE in their production processes (IIP, 2013). Similarly, paper G focused on an under studied context in OI research while still focusing on manufacturing SMEs from a mature industry. This context was one of SMMS, which according to the respondents of the survey clearly saw themselves as belonging to the automotive industry. In brief, SMMS are an interesting research context for OI because these SMEs could play the role of explorers of markets too small for large firms or as technical specialists (Chesbrough, 2010). In addition, smaller makers of supercars have proven to be a source of innovation for technology later incorporated in mainstream vehicles due to safety, performance, regulatory, and economic drivers (Zapata & Nieuwenhuis, 2010). Examples of these technologies include disc brakes, 4-wheel brakes, 5-speed gearbox, and 4-wheel drive. Indeed, it is common to believe that there are only a few brands of supercars in the market but this is mainly because they belong to groups of large carmakers producing most supercars in the market. However in reality, dozens of SMEs worldwide are specialised in designing and manufacturing supercars with the same design, features, and performance as the ones made by large carmakers. Therefore, even if almost all the market share of supercars is produced by large firms (i.e. 98%), SMMS complement the rest of the supercars industry(Cheetham, 2006). To depict better this idea, Figure 3-3 shows the contrast between the amount of large brands of supercars brands and the brands of SMMS surveyed in paper G.
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Figure 3-3. Proportion of large, medium, and small manufacturers of supercar
In addition to the innovation provided by SMMS, this context is also useful to show that large carmakers are not the only players in the automotive industry with the capabilities to build supercars. A supercar can be defined as a very expensive and fast sports car with limited production often considered as a one-of-a-kind vehicle. These vehicles can include muscle cars, sports cars, and grand touring vehicles modified for power and performance and updated with the latest sport and racing technology (Cheetham, 2006). Thus, SMMS focus on niche markets and usually do not compete directly with large OEMs. Some people may criticise small and medium carmakers for not being representative of the automotive industry. However, the production processes of SMEs producing cars are very similar to the ones of heavy trucks, buses, and industrial trucks that are often considered as part of the automotive industry. For instance, both of their production processes are similar as they have production rates typically slower than large OEMs, their volumes are smaller, and the manufacturing processes is less mechanised. Moreover, the high level of design and technology that a SMMS uses in their vehicles makes it interesting for two reasons. First, because the processes that these firms use to acquire (explore), develop, and enhance (exploit) technologies and the latest innovations is a convincing scenario where OI could be adopted, and thus studied. Second, considering that one of the inherent characteristics of supercars is its high level of design compared to mass production vehicles, it makes the firms in this context interesting since they could have similitudes with design-intensive and knowledge-intensive SMEs. Finally, and although not
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61
explored in this thesis, these firms could also be studied as SMEs producing luxury goods. This perspective could be interesting to study OI since research has shown that luxury firms can have its own specific practices and challenges (e.g. Brun et al., 2008; Catry, 2003). So overall, SMMS provided a novel and relevant context to examine Open Innovation practices in several ways. Figure 3-4 shows the location and names of the SMMS that were considered as the sample for the survey in paper G.
Figure 3-4. Names and location of SMMS sampled for paper G
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4. Summary of Appended Papers
In comparison to creative writing, the structure and process followed in academic writing seems fairly straightforward. However, one of the greatest challenges when writing academically is to create the connections between different but related ideas. This challenge is inherent when writing a PhD thesis with the format of a compilation of papers. Therefore, the purpose of this section is to present a summary of the appended papers and emphasise their relation with the whole thesis. It should be noted that the papers are not chronologically arranged but rather in a coherent sequence for the arguments presented in this thesis. In all the papers where several authors contributed, my role and contribution is clarified. In addition, a visual legend of the key elements in each paper complementing the thesis is illustrated according to Table 4-1. After the paper summary, the relation of the paper to this thesis is clarified and the main paper contributions are explained.
Table 4-1. Legend of key elements in a paper useful as a visual summary
Key element Description Applicable Symbol
Theoretical perspectives
Main theoretical perspectives considered
Various options
OI practices adoption
Adoption level of the OI practices by the actors or organisations studied
Knowledge, persuasion, decision, implementation, and confirmation
Firm performance
Dimensions of firm performance influenced by OI practices
Innovation (INP), economic (ECP), social (SOP), industrial (IDP), and environmental (ENP)
Size of actors Size of the firms and actors studied
micro, small, medium, and large
Industry Main sector and industry to which the studied firms belong
Various industries, only food, only automotive, only foundry
OI practices diffusion
Diffusion level of OI practices in the industry or sector studied
Introduction, expansion, condensation, and saturation
Main results Major results found and highlighted in the paper
Various options
Contribution to thesis
Key outputs useful to answer the RQs and contribute to the thesis
Various options
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4.1. Paper A. Theoretical perspectives and contexts in OI research
Title and authors Ramirez-Portilla, A. (2015) “Which one goes well with? Exploring the link between theoretical perspectives and research contexts in Open Innovation research” Status of manuscript Published in Procedia Social and Behavioral Sciences (Special issue from the 20th International Scientific Conference Economics and Management – ICEM 2015) Visual legend of the paper
Contingency and context dependency
All industries and sectors
All levels of adoption
All levels of diffusion
Firm performance in general
OI adoption depends on specific contexts
All firm sizes
Use few theories in more new contexts
Summary of the paper The purpose of this paper was to investigate the possible relation between the most mentioned theoretical perspectives and the most studied research contexts in OI literature. To do this, a meta-review of highly cited LRs on OI was conducted to identify the most acknowledged theories and contexts in literature. Articles including these concepts were retrieved with the software ‘Publish or Perish’ and analysed with a qualitative approach to propose some clear relationships. The main results showed that researchers apply similar theories to study certain research contexts, and this seems driven by promising publication trends. However, researchers also proposed continuously studying OI in new and understudied contexts in order to prove its applicability. Altogether, the findings suggested that researchers are following a widening-narrowing approach of the theories and contexts used to study and validate OI. This paper provides managers with relevant contexts e.g. industries, in which OI has been already adopted, motivating the implementation of OI practices in their own organisations.
Relation to thesis and main contribution The aim of this paper was to understand the potential relation between the theoretical perspectives most emphasised and the most studied research contexts in OI literature. This paper directly contributed to my thesis by showing how OI and its related concepts can be studied with a wide range of different, and sometimes even opposing, theories and theoretical perspectives. Moreover, to support the development of OI as a research field this paper
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proposed the idea of using a narrowing-widening approach with theory and contexts, i.e. to narrow the use of some specific theoretical views and then to widen the validation of these views in novel and under-studied research contexts. Thus, the main contribution of this paper was to set an agenda in OI research and thus, the direction of my doctoral research, in two ways. First, it served as a useful reminder for researchers interested in studying OI to better align their efforts with the most recognised theoretical views in the literature in order to advance an OI theory and its research stream. Second, with the support of empirical evidence, I was able to decide the path that the studies included in my thesis followed regarding the most appropriate theoretical perspectives in conjunction with OI. Thus, overall, this paper helped me to acknowledge that while OI could be studied with several theories and views, for my doctoral project I only chose a handful of the most appropriate ones. This paper besides confirming my theoretical stance also helped me to justify the study of OI practices in different novel contexts. In this sense, paper A rationalised the study of both general contexts such as manufacturing SMEs or mature industries, but also other more specific contexts like the foundry industry or small and medium-sized manufacturers of one-of-a-kind vehicles, i.e. SMMS. My role and contribution I developed the original idea for this paper and fully wrote it as a single author. Nevertheless, I obtained very useful insights from two anonymous reviewers, my supervisors, and some participants in the International Scientific Conference Economics and Management – ICEM 2015 in Kaunas, Lithuania. It is also important to acknowledge that some of the ideas for the methodology used were inspired by the work of some of my colleagues from the EDIM programme (see e.g. Karakaya, Hidalgo, & Nuur, 2014).
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4.2. Paper B. Influence of the firm’s internal context in OI adoption
Title and authors Ramirez-Portilla, A., Manzini, R., Lazzarotti, V., and Cagno, E. (2016) “The role of internal context characteristics on the adoption of Open Innovation: Evidence from manufacturing firms” Status of manuscript Presented at the 12th International Conference on Industrial Engineering – ICIE 2016. A revised version of this manuscript will be submitted to an international peer-review journal during the first semester of 2016. Visual legend of the paper
Contingency + OI models
Manufacturing sector in Italy and Sweden
Implementation and confirmation
Condensation and saturation
Innovation (INP) and economic (ECP)
Firm size and not age matters for OI practice
Small and medium vs. large firms
Focus in smaller actors and other dimensions of firm performance
Summary of the paper Explaining the concept of OI could be less challenging from a theoretical than from a practical perspective. In this sense, while researchers have spent the last decade trying to develop and establish the ideas, models, and theories related to OI, more simple questions related to its practical adoption by firms have often been disregarded. Therefore, the purpose of this paper was to fill this gap by investigating the adoption of different types of inbound OI models influencing firm performance under a contingency perspective. With the data collected by an OI Survey in manufacturing firms, we sought to examine how different configurations of OI models in terms of partner, content, and innovation phase variety influence firm performance when moderated by internal context characteristics. The sample analysed included the responses of 247 manufacturing firms from Italy and Sweden with different profiles of size and age. Using a mix of approaches to analyse the data we first found three configurations of OI models, namely: super open innovators, selective collaborators, and conservative collaborators. Contrary to many studies showing that adopting OI does not have a relation with economic performance (ECP), we found that in some cases, i.e. selective collaborators, firms can adopt OI to some extent and also have a high turnover. Second, we found that medium-sized firms differ from their smaller and larger counterparts in the extent to which they collaborate with
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partners such as universities, innovation intermediaries and firms from other industries. This study introduced a perspective that integrates partner, content, and innovation phase variety, to understand different ways in which OI models could be adopted by firms. Moreover, this paper provided managerial implications showing that the idea of openness is not a dichotomy of adopting everything-nothing, but as a choice of diverse open degrees consistent with the firm’s context characteristics.
Relation to thesis and main contribution This paper contributed to my thesis by investigating the adoption of OI by firms in manufacturing industries with a perspective on OI models (that are practiced), as well as considering a contingency perspective on a firm’s internal context characteristics. In addition, while most of the other studies in my thesis mostly used a qualitative approach, this paper was the first one to use a qualitative one. More specifically, through the data collected by an OI Survey in manufacturing firms from Italy and Sweden, the paper attempted to find some OI configurations in terms of partner variety, innovation phase variety, and content variety. Although this paper has not been sent to a journal but just presented in a conference, the results seem quite interesting. For instance, we believe that the findings clearly showed that while some internal context characteristics like age do not affect the adoption of OI models, others like firm size do have a significant influence. Thus, these findings help justify the other studies in the thesis that focus on manufacturing SMEs and other small or collective actors in mature industries. Moreover, the preliminary results of this paper seem to provide further support on the complementary effect rather than a substitutive one in the case of OI models adoption. My role and contribution I wrote this paper based on a dataset provided by the second and third authors. Although another research group collected this dataset, I proposed the original idea of using the data to investigate optimal configurations of OI considering a contingency perspective (internal context characteristics). Therefore, I added the variable of firm age to the database by retrieving this variable manually from industry databases. Similarly, I conducted most of the analyses, results, and discussion.
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4.3. Paper C. OI mechanisms as practices in F&B industry
Title and authors Ramirez-Portilla, A., Brown, T., and Cagno, E. (2014) “Unravelling the integration mechanisms in open innovation projects: the case of inter-organizational networks” Status of manuscript Published in Journal of Global Strategic Management Visual legend of the paper
Organisational theory + practice-based view
Manufacturing: F&B
Persuasion and decision
Condensation
Innovation, integration
& project performance
New mechanisms are practiced during OI
Large firms and universities + a small intermediary
OI practices can be driven by small innovative actors
Summary of the paper In recent years, there has been a tendency to evolve the innovation process into a flexible model known as Open Innovation where innovation takes place with several external actors. Nevertheless, although organisations are applying OI within networks, there is still a poor understanding of the mechanisms practiced by firms that help integrate the innovation activities with other actors. This paper explored the integration mechanisms practiced in inter-organisational networks for OI Projects (OIPs) with six organisations representing two types of innovators, private firms and academic institutions, as well as a small nexus agency that acts as an integrator between them. Our results showed that besides the 21 categories of integration mechanisms obtained from an extensive LR, six new categories of mechanisms are practiced particularly during OIPs: strategic prioritisation, government incentives, specific trading controls, environmental exchange, learning curve techniques, and compatible technology infrastructure. In addition, we proposed a conceptual framework to study integration mechanisms in OIPs at the inter-organisational network level within several types of Open Innovation actors. Thus, this study expanded the literature on integration mechanisms that are practiced to optimise the integration in collaborative projects between an organisation and other actors. Likewise, it showed that in Open Innovation Projects it is not enough to manage the integration of the innovation process like an individual function, but it needs to be done as an integrated chain of processes and practices supported by specific mechanisms.
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Relation to thesis and main contribution This paper contributed to my thesis by investigating through an organisational theory perspective the use of practices and routines in the context of inter-organisational networks. More specifically, these practices were characterised by the integration mechanisms that food firms practice together with universities and innovation intermediaries during OIPs. This paper related to my thesis by introducing the F&B industry as a setting where OI is practiced through the collaboration of different partners. Although there was not an explicit comparison between the sizes of the organisations where the data was collected, the relevance of the smallest actor to adopt OI can be directly assumed. For instance, both the investigated firms from the F&B industry and the universities were large organisations. However, the nexus between them, i.e. the innovation intermediary, was a small organisation with less than 10 employees but still with the most important role in the success of implementing OI between the other two large organisations. Overall, this paper contributed to my thesis by providing a different perspective on OI practices as mechanisms (formal and informal) as well as introducing the context of the F&B industry as a relevant research context to study the scope of OI practices adopted and diffused between different industry actors. My role and contribution This paper was created based on some of the ideas from my master’s studies. Therefore, I collected all the data more than 3 years ago. Later with additional information, constructive comments from seminars and the support of the co-authors, I was able to better frame and extend some of the main results of this study as well as the related discussion to be fully aligned with the topic of my PhD thesis project.
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4.4. Paper D. Practices by small actors in F&B industry
Title and authors Ramirez-Portilla, A., Cagno, E., and Zanatta-Alarcon A. (2016) “Open Food: Revisiting the role of Open Innovation actors in the Food Industry” Status of manuscript Submitted to an international peer-reviewed journal. Visual legend of the paper
User and communities + practice-based view
Manufacturing: F&B
Decision and implementation
Condensation
Innovation (INP) and social (SOP)
Small actors can drive relevant OI practices
Small organisations and large communities
OI practices by small actors can influence INP but also SOP
Summary of the paper Researchers have claimed that we are in the era of Open Innovation (OI). This idea is supported by the vast evidence of OI adoption in firms from different industries. One industry in which OI has been gradually adopted by firms as an approach to innovate is the Food and Beverage (F&B) industry. Although several studies have investigated the F&B industry under an OI lens, most of them have mainly focused on activities conducted by large firms disregarding the role of other smaller actors. Therefore, the purpose of this paper was to explore the adoption of OI ideas influencing initiatives driven by actors other than large F&B firms, in order to complement a larger image of OI adoption in the manufacturing sector. To do this, we analysed through a qualitative approach several innovative initiatives related to food and created by different types of actors. The main results showed that large F&B firms were not the only actors proposing lasting OI initiatives, but also small and medium-sized organisations, foundations, communities, and even consumers. Lastly, we proposed the concept of ‘open food’ and provided two exemplars of it. We concluded this study with theoretical and managerial implications about the role of OI in the F&B industry. Relation to thesis and main contribution This paper contributed to my thesis by providing a clear-cut example of how OI ideas and practices adopted and driven by small and medium organisations and actors can be relevant for mature industries in the manufacturing sector. To make this idea more compelling, this paper
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focused on the F&B industry, a traditional industry with a relatively low level of technology and innovation which recently has been depicted as an industry highly influenced by open collaborative innovation. Moreover, the literature has mainly focused on the adoption of OI in large firms from the F&B industry. Therefore, this paper considered the role of SMEs, users, citizens, and communities to integrate OI ideas that drive innovations and create value. Hence, this paper contributed by showing how I am able to investigate the role of OI practices adoption with other perspectives such as user-driven innovation and open communities. In this sense, this paper also helped to delimit the scope of the theoretical perspectives emphasised in my thesis. For instance, perspectives related to users and communities could be relevant to study OI not only in contexts such as Open Source Software, but also in the F&B industry. However, based on the results of this study I decided to focus my research on other theoretical perspectives (i.e. OI models and the practice-based view) that seemed more appropriate to understand the role of OI in the performance of manufacturing SMEs in mature industries. Finally, an important message in this paper was that OI practices related to the F&B industry can take the form of initiatives and even small ‘organisations’ driven by users and citizens. In turn, these preliminary results suggest that OI practices can also have an impact on the dimension of SOP related to these ‘organisations’. My role and contribution I developed the original idea for this paper and advanced it further with the support of the other two co-authors. Specifically, I contributed to this paper by reviewing all of the literature as well as proposing the theoretical framework for this study. Even though the data used for this paper was collected through desk research and from secondary resources between all the co-authors, I helped collect most of the information (e.g. examples of cases) and contributed to a great extent by analysing it and discussing its implications. Finally, I directed the writing process of all the sections of the paper while trying to integrate the ideas from the other two authors.
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4.5. Paper E. OI practices and energy efficiency in foundries
Title and authors Ramirez-Portilla, A., Cagno, E., and Trianni, A. (2014) “Is Innovation an enabler of Energy Efficiency? An exploratory study of the foundry sector” Status of manuscript Published in Energy Procedia (Special Issue from the 6th International Conference on Applied Energy – ICAE 2013) Visual legend of the paper
Contingency + practice-based view
Manufacturing: foundry industries
Knowledge and persuasion
Beginning and expansion
Energy efficiency (EE)
Some OI practices can enable EE in SMEs
Small and medium-sized firms
OI practices could influence EE and thus, possibly IDP
Summary of the paper Recent research has provided evidence that using innovation in the form of new technologies, R&D activities, or new processes can support Energy Efficiency (EE). This relation is relevant because in energy-intensive industries EE can account for most of a firm’s performance and thus also for the overall performance of the industry, i.e. the industrial performance. Building on the relevance of this logic, this paper sought to explore whether a novel approach to foster EE in SMEs includes improving the overall innovation degree of a firm through the adoption of OI practices. To do this, a multiple case study was conducted with ten firms in Northern Italy operating in energy-intensive industries, i.e. alloy foundries. This paper analysed the firm's specific energy consumption, the adoption of energy-efficient technologies, the perception of barriers to EE, and their relation with the firms’ internal innovation and OI activities. Main results showed that more innovative firms, in terms of internal and inbound innovation practices, have better EE indicators albeit a lower adoption of energy-efficient technologies or the challenge of economic and technology barriers. Moreover, firm’s size seems to moderate the studied indicators since medium-large firms were more innovative and had better EE performance in general. This study offered preliminary evidence of a positive relation between adopting certain innovation practices and the increase of EE in SMEs.
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Relation to thesis and main contribution This paper contributed to my thesis by exploring the relevance of studying the adoption of OI practices and its effects in a novel context like the foundry industry. More specifically, this paper provided one of the first justifications to study the relation between the adoption of innovation practices: internal R&D, inbound OI and outbound OI, and three indicators of industrial EE: specific energy consumption (SEC), energy-efficient technologies (BATs) and barriers to EE (BEEs). Although this paper was based on preliminary data collected from 10 pilot case studies, it provided an initial framework and the empirical results justified investigating in a subsequent step the same assumptions but in a larger sample. Therefore, this paper provided some initial evidence regarding the influence that adopting OI practices by small and medium-sized foundries could have on different EE indicators. Moreover, it is in this paper where we rationalised and implied that in energy-intensive industries EE is a proxy to the industrial performance (IDP) and thus, OI could also influence it. In this sense, this paper prepared the conceptual and empirical setting to study the positive relationship that adopting OI practices could have with the IDP in SMEs from energy-intensive industries such as in the foundry industry. My role and contribution While all the authors developed the original idea for the study, my special contribution in this study was the knowledge regarding OI concepts and practices. I also was the one who collected the data during my research period in Italy through a series of case studies including onsite visits and interviews (in Italian) with managers and owners of firms. Although the collection of data was supported with the help of a master’s student (to ensure 100% accuracy in terms of language), I was the one analysing the collected data and writing the initial version of the paper. This version was later improved with the support of the other two authors and the comments received by colleagues at our universities and at an international conference.
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4.6. Paper F. OI and industrial performance in foundries
Title and authors Cagno, E., Ramirez-Portilla, A., and Trianni, A. (2015) “Linking energy efficiency and innovation practices: Empirical evidence from the foundry sector” Status of manuscript Published in Energy Policy (Special Issue on Energy and R&D) Visual legend of the paper
Contingency + practice-based view
Manufacturing: foundry industries
Persuasion and decision
Beginning and expansion
Energy efficiency (EE) and industrial performance (IDP)
Inbound OI improves EE related indicators
Small and medium-sized firms
Some OI practices can influence EE and IDP
Summary of the paper The Europe 2020 strategy currently promotes energy efficiency and innovation through disconnected targets focusing on either energy or R&D. Similar policies indicate that unfortunately in practice, these two concepts are usually perceived as mutually exclusive. Furthermore, evidence in the literature regarding the relationship between R&D and energy efficiency (EE) is still highly limited. This exploratory study aimed to address this gap by investigating the link between innovation practices and EE through a multiple case study of 30 foundries in Northern Italy. To achieve this goal we analysed the firms’ innovativeness, measured by IRD and OI practices (inbound and outbound), and the firms’ EE, measured by indicators of specific energy consumption (SEC), level of adoption of energy-efficient best available technologies (BATs) and barriers to energy efficiency (BEEs). The results showed that those foundries complementing IRD with inbound practices had a higher level of EE, a higher level of adoption of BATs, and a lower perception of barriers to EE improvements. This finding primarily suggested that by diversifying innovation practices a firm could achieve better performance with respect to the three analysed indicators of EE, and consequently also with the industrial performance (IDP) of foundries. In general, this study contributed to understanding how more innovative and ‘open’ SMEs in energy-intensive industries can be more EE, providing interesting highlights for managers and policymakers.
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Relation to thesis and main contribution Different from paper E, this paper contributed to my thesis by providing more robust evidence on the previous findings about the relation between adopting OI practices and IDP characterised as EE in the context of foundries. Particularly, the 30 multiple cases studies in this paper showed a clear demarcation between IRD, inbound OI, and outbound OI and its relation with three different but related indicators of EE. In general, the results of this paper directly supported the assumption that adopting OI practices can influence IDP and EE, which in turn opens the possibility to link it to other environmental performance (ENP) dimensions. Hence, it also indirectly supported the assumption that OI practices adopted by SMEs could equally influence the ENP not only in the foundry industry but also in other mature manufacturing industries. Finally, it should be noted that this article was published in a journal more oriented to energy topics through a special issue on ‘Challenges for R&D and innovation in energy’. Therefore, this paper showed implicitly that a multidisciplinary approach to study OI could help further advance the understanding of other roles and effects of OI adoption. My role and contribution This paper was inspired from paper E and thus I was part of its original idea. After writing paper E, I developed together with the first author the research design of this study. More specifically, I prepared and refined the questionnaire available in Appendix C. Also together with a master´s degree student, I collected the data visiting the companies with a group of experts from different Italian foundries associations (as better explained in the methodology section of paper F). Finally, I also conducted the first stage of the data analysis and supported the writing and editing process of the results, discussion and conclusions of the paper.
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4.7. Paper G. OI and other dimensions of SMEs performance
Title and authors Ramirez-Portilla, A., Brow, T., and Cagno, E. (2015) “Open Innovation in Specialized SMEs: The Case of Supercars” Status of manuscript Submitted to a Special Issue on “Implementing Open Innovation” in Business Process Management Journal. Visual legend of the paper
Contingency, practice-based view, OI models
Manufacturing: automotive industry
Decision and
implementation
Condensation
Innovativeness (INNO), social (SOP), economic (ECP), and environmental (ENP)
SMEs practicing OI are more innovative and partly sustainable
Small and medium-sized firms
Adopting models and practices influences INNO, ENP, and SOP
Summary of the paper The purpose of this paper was to explore how adopting OI influences the innovativeness (INNO) and performance of specialised SMEs. This paper also examined the adoption of OI within a firm’s practices and models, and within the three dimensions of firm sustainability. Survey data from 48 specialised SMEs manufacturing supercars were analysed using PLS-SEM. SmartPLS software was used to conduct a path analysis and test the proposed framework. The main findings suggested that high adoption of OI models (OIMs) tends to increase a firm’s INNO. Similarly, the adoption of OI practices (OIPs) has a positive effect on INNO but to a lesser extent than OIM. The moderation results of INNO further showed that OIM and OIP can benefit firm performance (FP) of SMEs. Specifically, two dimensions of FP – environmental (ENP) and social (SOP) – were found to be greatly influenced by OI. A research limitation was the parsimony in the investigated model; this study only focused on OI adoption as practices and models without considering its drivers or other contingency factors. In terms of practical implications, this paper could help practitioners in SMEs better understand the benefits of adopting OI to be more innovative but also more sustainable. Finally, this study contributed to the literature on the role of OIPs and OIMs regarding the
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dimensions of firm sustainability performance by being the first paper to investigate this relationship in the context of SMMS. Relation to thesis and main contribution The last paper included in this thesis was designed with an integrative purpose trying to encompass the most interesting elements from the other papers, as well as using different research methods to complement the study with different angles. In addition, one of its main contributions was to validate in one single paper the influence of adopting OIPs but also OIMs could have in an under studied but relevant context such as in SMMS. Similar to paper B, this paper also investigated the role of OIPs and OIMs through a quantitative approach by analysing data collected through a tailor-made survey. Moreover, in this paper we employed PLS-SEM, which is increasingly used to study management concepts. In fact, even though this method has started to be used in IM literature (e.g. Aç, Günsel, Kuzey, & Seçgin, 2015), to the best of our knowledge, this is the first paper in OI literature to apply this method to investigate both OIPs and OIMs. Even though the final findings of this paper were obtained from a ‘small’ sample, we consider it significant considering the novelty of the research context. In general, the main results of this study provided robust evidence indicating that firms highly adopting both OIMs and OIPs may not necessarily have better ECP, but in turn, significant effects can be found in relation to its INNO levels. Similarly, ENP and SOP indicators are positively influenced by adopting OI suggesting that SMEs could partially enhance their sustainability levels by opening up their innovation models and practices. My role and contribution The idea to conduct this study was proposed by me and thus I collected all the data. More specifically, I framed the relevance of studying OI in SMMS through initial case studies (although not reported in paper G) in order to better understand the role of OI in specialised manufacturing SMEs. The other authors helped in refining the research framework and the survey questionnaire. Finally, although I received support from my co-authors in editing the last version of this paper, I conducted all the analyses as well as writing the results, discussions, and conclusions.
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5. Results and Discussion
Before focusing on the discussion of the main results of the thesis, it is important to remark that the accumulative results of my research can be found in each of the papers appended. Therefore, in this section my first intention is to discuss the overall results in an interlinked way. In any case, to provide a more structured discussion, each section focuses on a specific set of ideas while highlighting the relevance of each paper when appropriate. A note of caution here is appropriate. As the design and analysis of the different data used in this thesis is already described in each of the appended papers, these are not extensively described in this section, but briefly mentioned when suitable. Also, it should be noted that some additional findings not included in the papers due to their narrow scope or word limitations are briefly included below, e.g. insights from the two case studies in SMMS.
5.1. Context matters in OI research and practice
The economic revival and development of a society in the present world situation confronts us with the need to assess how the management processes of innovation allow for the creation of productive capacities, especially in the business and industrial ‘glocal’ frameworks (Muñoz-Gutierrez, 2014). Similarly, the organisational circumstances in this fast changing world raise the question of the potential generalisation of any innovation theory, method, tool, or model (Tidd & Bessant, 2014) in most industrial settings. Thus, when studying OI phenomena it should be recognised that based on the practical or industrial context to be researched, certain theoretical perspectives would be more appropriate than others (Vanhaverbeke & Cloodt, 2014). Perhaps talking about one innovation model or theoretical perspective being better than another would be far too normative and inflexible. Instead, a more realistic, open, and responsive view would consider that IM models, theories, and paradigms are not worse or better but just different (Kuhn, 1963). Moreover, the ‘outputs’ we could observe and obtain by using specific IM perspectives or paradigms can also be dependent on the studied industrial contexts or scenarios. This idea has been exemplified and investigated in this thesis with the case of Open Innovation practices (OIPs). In doing so, RSQ1 was answered with diverse angles and studies that in aggregate show a significant relevance of context and contextual factors to understand the adoption and practice of OI. To begin with, we know that as with many other social and organisational phenomena, IM practices are contingent upon the type of context in which they are applied (Aas, Breunig, Hydle, & Pedersen, 2015; Huizingh, 2011; Ortt & van der Duin, 2008). So if this situation should also be expected for OI practices, why should this be confirmed? Well, probably the question is not whether context-dependency and contingency are applicable for OI, but instead how relevant are context and contextual factors to understand the adoption and practice of OI. To answer this question, this thesis (i.e. paper A) centred on the adoption of OI as a theoretical supposition based on the OI literature available. Based on the analysis of OI literature we can see that 83% of the publications focused on a specific setting. This high percentage should not be considered as a mere coincidence, but instead as a first indicator of the context relevancy for
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OI studies. Similarly, 51% of the publications explicitly emphasised, i.e. mentioned in the publication title, at least one theoretical perspective and a research context. This result clearly highlighted the relevance of acknowledging the context and contingency dependency by Open Innovation researchers. Also, another interesting result was that the number of both theoretical perspectives and research contexts reached its peak between 2010-2011 and 2011-2012, respectively. Although this trend was similar, it suggests two very different implications for studying OI. First, few theoretical perspectives were used when the OI model was introduced. With more time, more perspectives were proposed to complement the understanding of OI. While some were successful, e.g. modes or models, others were less so, causing a decrease in the perspectives used. This appears as a narrowing of the most critical and convergent theoretical lenses in OI that could ultimately create an OI theory (Gassmann et al., 2010; Gassmann & Enkel, 2004; Tidd, 2014). Second, few and recurrent research contexts were initially studied with the OI model. With time, more settings were investigated in almost every type of industry until it became clear that OI was more applicable in some industries or sectors. This could have signalled to most researchers to focus on studying phenomena related to OI in specific settings where it was likely to be found. Nevertheless, this does not mean that OI should not be investigated in novel contexts, but only that studies may not yield the same sharp or expected findings as in other known settings. It seems then than some important trade-offs (e.g. validate-explore contexts or consolidate-propose perspectives) are implicit when choosing how to research Open Innovation This thesis also demonstrated the relevance of context and contextual factors to understand OI practice through several studies. In fact, even though contingency and context-dependency perspectives were only stated clearly in five papers, in the other two the importance of the setting where OI practices were adopted and the results influenced by this adoption were emphasised. Thus, it could be said that all studies helped to validate the idea that specific organisations and environmental factors (i.e. the ones studied in each paper) can play an important role in the relationship between firm and industry innovativeness levels and their performance indicators (Vij & Bedi, 2015) when OI practices and variants of these are being adopted. Few examples of the most relevant studied internal and external contextual factors included the industry and sector (paper A), firm size (papers B to G), business models variety (papers B, G), integration capability (paper C), user practices (paper B), technological sophistication / specialisation (paper G), efficiency dependency (papers E, F), and business practices (papers B to G). Considering the above, the appended papers of this thesis have answered the call to advance the understanding of OI by investigating more propositions between its adoption and the context where the firm operates (Lazzarotti et al., 2011). Moreover, the multi-perspective approach used was designed with the intention to provide confirmation that it is highly unlikely that OI has the same effects in every situation but rather they are dependent on the context of the firms adopting it (Huizingh, 2011). Accordingly, the accumulative findings of this thesis
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provide robust and varied evidence that a contingency perspective is necessary when investigating the effectiveness and scope of OI in organisations (Gassmann, 2006). It should be noted that the studies in this thesis clearly differentiated the CT dichotomy between internal and external factors (Hofer, 1975; Luthans, 1973). However, in these studies one category was not deemed to have more weight as a determinant of OI. This demarcation was avoided on purpose not to avoid taking a stance, but to recognise the importance of both types of factors. In fact, supporting one category more than the other would inherently conflict with the essence of a contingency view. In any case, the question should not be directed towards choosing studying internal, external or both types of factors in OI studies, but rather to continue using a contingent and context perspective to develop a tighter theory of OI (Tidd, 2014). Aligned with the idea of contingency, we should remember that a central finding in the innovation literature is that a firm innovates in different forms through extensive interactions with its environment, system, and networks (Fagerberg, 2004). Thus, a contingent perspective of OI should recognise both the existence of several collaboration practices (Ollila & Yström, 2013) and the potential of different innovation outcomes (Bahemia & Squire, 2010). It is then conceivable to suggest that depending on the context used there could be a great difference in the potential to create new profit streams and business models (Chesbrough, 2013; Gassmann et al., 2010). Thus, depending on the context together with the OIPs used may provide firms with opportunities to propose and deliver value in different ways. In fact, OI has the advantage to be practiced together with other strategies which in turn could provide a unique position, especially for SMEs (Vanhaverbeke et al., 2012). For instance, OI could be used with other strategies ranging from generic approaches such as blue ocean strategies (Mauborgne & Kim, 2004), or a firm´s white space (Johnson, 2010) to more specific ones like the business model canvas (Osterwalder, 2004) or selecting a specific strategic orientation (Colin C J Cheng & Huizingh, 2014). It is crucial to stress that all the papers considered (directly or indirectly) that innovation process and IM practices are contingent (Aas et al., 2015; Pavitt, 2004). Therefore, it is possible to suggest that the contexts provided by certain industries could provide better opportunities to apply some OI practices rather than others. For instance, OI practices adopted by firms in the F&B industry (papers C and D) certainly vary from the ones adopted by firms in the foundry industry (papers E and F). This difference could be explained considering that the adoption and adaptation of particular practices may involve a gradual process that depends on the setting and experience of each firm (Santamaría et al., 2009). Moreover, some combinations of OI practices could have a complementary effect while others a substitution one (Michelino, Caputo, Cammarano, & Lamberti, 2014; Schroll & Mild, 2011; West & Bogers, 2013). Thus, it could be difficult to talk about a generic set of OI practices that work in every context and conversely, firms in a specific context (e.g. industry) that always apply the same OI practice. Instead, we should consider a continuum of OI practices and their applicability as shown in Figure 5-1. Such a continuum would simultaneously stress that only in a few contexts could many OI practices be applied and that only few OI practices could be adopted by several contexts.
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Figure 5-1. Continuum of applicability of OI practices in industrial contexts
All the suggestions above in no way seek to justify the inconsistency of OI practices adoption in mature manufacturing industries. Instead, it tries to signal an opportunity to explore the effectiveness of specific OI practices together with other innovation concepts in varied contexts. For instance, innovation contests if considered as OI practices could be studied in industries associated with a lack of transparency just as long as the participants are actually collaborating in a reciprocal way (Kathan, Hutter, Füller, & Hautz, 2015). Also collaborative tools and methodologies to spur creativity such as serious games could also be used by SMEs to exchange knowledge during the ideation process (Agogué, Levillain, & Hooge, 2015). Finally, firms could find synergies adopting OI practices together with other tools with a participatory nature. For example, firms could use the tools such as Design Thinking together with a variety of OI practices, which is something already proposed in the F&B industry by large organisations (Olsen, 2015) but that could also be useful for SMEs.
5.2. OI adoption by ‘small’ actors within and around mature manufacturing industries
New improvements in technology will continue to shift mature manufacturing industries. Just the global trend of computerisation has the potential to switch a high proportion of manual tasks to robots in production, construction, and agriculture (Frey & Osborne, 2013). For instance, new technologies supported by collaborative practices between firms and communities are making it possible to 3-D print shoes, metal components, cars, and even food. Considering these types of radical changes in today’s economy, this thesis considered as the main research context different types of manufacturing firms from mature industries. At the beginning the scope of this research considered every type of organisation in these industries. However, through the different studies and their findings the research focus was redirected from large firms to include other smaller actors adopting OI within and around these industries. It is common to believe that large manufacturing firms innovate as a common and straightforward practice since they produce many of the ‘fashionable’ technological innovations available in most markets e.g. electronics. However, this is far from true since a widespread outsourcing of production activities has put tremendous pressure on manufacturing managers to be cost competitive and offer unique customer value through innovative products and processes (APQC, 2015). Another misconception is that large firms are lonely innovation actors in manufacturing industries, while in reality much of the innovation they do is from
Industrial Contexts
Open Innovation Practices
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interactions and collaborations with other actors (Salmelin, 2013) as papers B to G have confirmed. A clear example is collaborations with SMEs, which have been credited to be more agile than large firms in the innovation stage of idea generation (Alvarez & Barney, 2001; Minshall, Mortara, Elia, & Probert, 2008; Smith, Dickson, & Smith., 1991). As a consequence, it is not surprising to see how large firms are interested in cooperating constantly with SMEs to be able to generate innovations faster (Katzy, Turgut, & Holzmann, 2013). Moreover, in the manufacturing sector technological resources and knowledge, usually attributed to large firms is not a prevailing competitive advantage. For instance, in mature low and medium-tech industries, creativity and not necessarily technological knowledge, is usually the platform for innovation (Santamaría et al., 2009). This idea was confirmed with the examined cases in the foundry industry (papers E and F) where not all the BATs were acquired or mastered but instead OI practices denoting creative ways to find innovations such as conducting trends scouting were adopted by most of the small and medium-sized foundries studied. These ideas indicate that even if large firms will seize most business opportunities in an industry, more radical innovations could be started by smaller actors (De Backer, 2015). But to recapitulate a bit on the distinction about organisational size, what is meant in this thesis by ‘smaller actors’ in terms of an industrial context? Well, a logical response would involve the category proposed by the EU of micro, small, medium, and large enterprises according to number of employees and annual turnover (Verheugen, 2003). However, this view only considers organisations involved in business-related purposes in a certain industry. While this view is correct if considering that industry is defined as the aggregate of manufacturing productive enterprises in a particular field, it neglects the innovation inputs by other actors. Thus, at this point, it is useful to consider the triple helix innovation model where innovation actors could belong to three institutional spheres: industry, government, and academia (Etzkowitz & Leydesdorff, 1995; 1997; 2000). Therefore, we can say that while the other two spheres do not form part of an industry, the innovation processes within it are certainly influenced by the interactions between them. Indeed, there is a considerable body of literature stressing the importance of the relationships for knowledge transfer between two of the three spheres such as academic engagement (Perkmann et al., 2013). However, to have an all-inclusive view of the industrial (open) innovation in current manufacturing scenarios it is necessary to consider the interactions between a wide range of small and medium different actors from government and academia including innovation intermediaries, foundations, incubators, technology transfer offices, research centres, science parks, and even venture capital firms (Etzkowitz, 2008). Furthermore, as investigated in the F&B industry, users and citizens can also adopt OI in terms of practices and initiatives closely linked with the innovations developed in mature manufacturing industries. Thus, the role of OIPs in these industries is not always about user-oriented innovations by firms (Grunert et al., 2008) but also about citizens and users as innovators (Bogers, Afuah, & Bastian, 2010). In this sense, we could refer to the model of quadruple helix collaboration (Katzy et al., 2013; Salmelin, 2013) where citizens (including users and
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communities of users) are recognised as potential innovators. Indeed, the role of users as innovators (von Hippel, 1986) or active co-creators (Galbraith & McAdam, 2011) has been widely recognised in the literature. However, an implication proposed (based on paper D) is that in some mature industries citizens and users can be closely engaged, through self-organised and collaborative practices, to the innovations that could potentially affect such an industry without the actual intervention of the large actors in it. This implication on the role of OIPs in mature industries is interesting in two respects. First, it adds users, consumers, and citizens as types of ‘small’ actors that equally to SMEs can use and integrate knowledge from different external sources to create innovations (van de Vrande et al., 2010). In fact, this idea confirms one key aspect of the OI model which stated that because knowledge is heterogeneously distributed among many agents, firms would be better off by collaborating with such agents (Chesbrough, 2003a). Second, it confirms that not only in high-tech industries but also in mature low and medium-tech manufacturing industries, users and consumers freely develop, share, and diffuse innovative ideas within their communities (Bogers et al., 2010). In turn, these innovative ideas, practices, and initiatives could affect the future organisation and performance of an industry (Baldwin, Hienerth, & Von Hippel, 2006). Considering the arguments above, it could be possible to picture the idea of an ‘open’ industry where different types of actors (see Figure 5-2) including the ‘small’ ones, are creating and driving OI practices. Such potential collaborative and ‘open’ manufacturing industries should not rely solely on OI practiced by large firms, but also by SMEs and other smaller but significant actors (Ball & Jolly, 2015).
Figure 5-2. Potential innovation actors to be involved in an ‘open industry’
‘Open’ Industry
SMEs
Large firms
Industry Associations
Hybrid Organizations
NGOs
Government
Innovation Intermediaries
Universities
Citizens
Users / Consumers
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Indeed, Figure 5-2 is only an ideal representation of the notion of fully adopting openness at an industry level. Thus, I am not claiming that any of the studied industries, e.g. F&B, foundry, or automotive, have evolved to the point to be considered as ‘fully open’. Similarly, another note of caution on this figure might be appropriate. It is possible to find researchers adding more ‘helixes’ to explain how innovation happens nowadays, see e.g. the Quintuple Helix innovation model (Carayannis, Barth, & Campbell, 2012). However, my intention with the ‘open industry’ idea is less pretentious because I am aware that when proposing ideas related to the interaction between actors of different institutional spheres it is necessary to provide more extensive evidence together with more normative or descriptive statements (Broström, 2011). In any case, I proposed this idea as an inspiration and as a starting point for future studies that could discuss more extensively the implications of OI practices and industry dynamics (Utterback, 1994) in mature manufacturing industries. For example, the rate of product and process innovations by firms in the food or automotive industry might seem to be on a ‘specific’ stage (Abernathy & Utterback, 1978). However, through an OI perspective, the dynamics of the process innovations could be alleged to be in a ‘transitional’ or even in a ‘fluid’ phase (Abernathy & Utterback, 1978). Even if these types of discussions are outside of the scope of this thesis, it is important to briefly mention and link them to the thesis findings.
5.3. Different forms OI practices
By now it should be clear that throughout this thesis the notion of practice has been the ‘red thread’ connecting all the related studies. However, what may need further clarification is what can be considered as an OI practice with the potential to be adopted. To clarify this, it is necessary to focus on answering RSQ2 related to the characterisation of OI as varied forms of practices. Thus, it would be helpful to remember first that in the practice-based view proposed (Section 2.2.3), OI adoption was initially foreseen both as practices (OIPs) and as models (OIMs), but still leaving open the option of other characterisations. Considering this possibility three studies provided empirical evidence on diverse forms in which OI regular practices could be characterised and adopted by different types of actors. More specifically, these studies found that adopting OI can involve practicing certain integration mechanisms with external collaborators (paper C), performing collaborative user-driven initiatives and approaches (paper D), and aggregating (not substituting) multiple innovation activities, including the IRD ones (paper E). Indeed, these forms of OI practices are distinctive from the usual and widely accepted concept of OI practices defined mainly as a typology of various process related to INB, OUT, and coupled activities (Huizingh, 2011). However, as we know many activities that lead to innovation are not R&D-based processes but can also include some forms of mechanisms, approaches, and combinations of activities (Santamaría et al., 2009). Thus, this unusual and fresh perspective on practices closely related to OI provides a more eclectic and flexible view of the habitual activities that organisations and other type of actors actually perform, implement, and adopt in order to be more open.
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To clarify why the proposed characterisations of practices are relevant to provide a complete depiction of a practice-based view of OI, some arguments are explained below. First, including integration mechanisms within the spectrum of OI practices offers a clear example of the potential ‘means’ that could be practiced to adopt OI. Alternative means may include, but not limited to, agencies, procedures, operations, processes, techniques, systems, and organisational structures. However, it should be emphasised that under a PBV of OI, these varied means would only be considered as OI practices when they are established as routines around the organisation regular innovation activities maximizing efficiency in the OI approaches adopted and the related outcomes. But then, why the focus on mechanisms, and more precisely integration mechanisms, and not other means mentioned before? From a general viewpoint, due to the evolving nature of organisational activities, the emphasis should be on properly integrating and coordinating certain activities because they can become organisational routines and practices contributing to superior performance (Nelson & Winter, 1982). From a specific viewpoint in the field of IM, the choice of stressing the case of integration mechanisms as a characterisation of OI practices seems more appropriate. For instance, considering integration mechanisms as OI practices contributes to the idea that because organisational practices are bound by habits of behaviour, practices supporting the OI model could be characterised as numerous and varied daily activities of the firm (Huang, Lai, Lin, & Chen, 2013). This idea is aligned to the steady trend in literature highlighting the relevance of modes and mechanisms for transferring and integrating knowledge within and between organisations before it can be internalised and adopted (Alexander, Neyer, & Huizingh, 2016). Also, integration mechanisms (or at this point and under a PBV we could also say integration practices) are important because if properly performed could help minimizing the coordination costs when collaborating with external partners (Dahlander & Gann, 2010). Considering the above, it may seem that practicing integration and coordination mechanisms may have the same weight when adopting OI approaches. However, the focus on the former rather than the later mechanisms (as it is visible in paper C) is due to their extensive scope of applicability in OI. To exemplify this idea we could consider a taxonomy of OI interactions strategies such as networking, co-ordinating, co-operating, collaborating, and co-creating (Ollila & Yström, 2013). Although these interaction strategies are different in nature and purpose, it seems integration rather than coordination is practiced and stressed during all of them. For instance, a typical form of interaction related to co-operating is supplier integration, but also the integration of users as co-producers is emblematic for co-creating. In sum, we could say that integration (in its form of mechanisms or practices) is vital to open the innovation process; however, organisations might not use always the proper practices when integrating knowledge in OIPRs. Therefore, to integrate properly with other innovators in the innovation process, firms need to analyse the innovation practices suitable to the underlying social interactions (Neyer, Bullinger, & Moeslein, 2009). This idea is further explored below in terms of the different dimensions to be considered when adopting OI practices.
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To complement a PBV of OI, including collaborative initiatives and approaches driven and practiced by users and other actors would confirm and add to previous ideas about the synergy between OI and user-centric innovation notions. For instance, it has been widely accepted that costumers, consumers, and users can be closely involved in new product development at different stages of the design process. During these stages (e.g. specification, concept development, detailed design, prototyping, and final product) different methods involving several actors can be used to design for users, design with users, and design by users (Kaulio, 1998). In most of these scenarios, firms are seen as the main orchestrators and coordinators of such stages and outcomes, even in the ‘design by users’ approach. However, users could also take this main role in other industrial settings where (if not heard and taken into account) they are more involved in suggesting and initiating, improvements and innovations in the products, processes, services, and systems they use and consume. At this point, it would be useful to remember that previous and extensive literature have already considered users as key sources of industrial research and marketing processes (e.g. von Hippel, 1986) or as complementary actors to a firm’s internal innovation process (e.g. Chesbrough, 2003a, 2006). So then, what is novel about the approaches practiced by users and communities of users studied and described in this thesis (paper D)? The main difference and as explained before is that this study provides evidence that in some nature manufacturing industries ‘small actors’ can be closely engaged, through self-organised and collaborative practices, to the innovations that could potentially affect such an industry without the actual intervention of the large actors in it. Therefore, we could say that although the innovations, practices, and initiatives by these actors are not fully integrated within large firms, this finding could add to studies that examine and identify users harnessing interactive and collaborative online tools (see e.g. Bilgram, Brem, & Voigt, 2008). Similarly, this study contributes showing that also in mature industries like the F&B, end-users – users of consumer goods – or communities of them can have a significant role in the collective invention, development, and diffusion of practices and innovations within their communities (Bogers et al., 2010). Considering the above, we could propose a generic version of the ‘open food’ definition (paper D) so it can fit similar phenomena in other mature manufacturing industries where users and communities are also interested in contributing collectively to the innovation process. Accordingly, we could said that an ‘open phenomenon’ in ‘X’ mature industry could be considered as the phenomenon of collective initiatives and practices empowered by small organisations, users, communities, and citizens sharing a common objective of creating, adapting, capturing, adopting, and disseminating ‘X’ related value, knowledge, and innovations, which could be or not leveraged by for-profit actors. While only in one industry, these findings provide initial evidence about other unexpected implications of adopting OI practices. Indeed, further studies are required to assess if the role of these actors and the approaches they practice are really for maximizing utility and not only profit (Bogers et al., 2010). In any case, the role of OI practices and initiatives adopted by users and communities of users within the scope of mature industries offer an opportunity to extend the firm-centric notion of OI as originally proposed (West & Lakhani, 2008).
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Having clarified diverse forms of OI practices explored in this thesis, it would then be possible to suggest their inclusion in the list of OI practices in literature. However, it should be noted that proposing this addition does not necessarily mean to categorise them to the list of already extensive OI practices suggested and available. For this reason and to avoid an extensive and redundant list of OI practices in this section, I kindly refer the reader to the different papers (B to G) where a variety of OI practices were studied. Also, to see in detail the way in which these practices were operationalized and collected please refer to Appendixes A, B, C, and D. More specifically, refer to sections C and D of Appendix A, sections C and D of Appendix B, section D of Appendix C, and section 1 of Appendix D. So instead of simply providing a list of practices, I believe that a more useful proposition would be to revisit the combination of possible varieties in OI adoption and include a dimension of variety on practices. Based on this idea, we can recall that the variety of the innovation phases is key to understand at what point in time during the innovation process OI should be adopted. In chapter 2 (exactly in page 40), some examples of the categories of innovation phases were provided (Bergström et al., 2010; Dewangan & Godse, 2014; Russo-Spena & Mele, 2012). However, these are just a few of the existing ones in the literature that can be linked with the adoption of OI. More examples of innovation phases include: want, find, get, and manage (Slowinski & Sagal., 2010; Slowinski, 2004), strategy, sourcing, integration, and metrics (Chesbrough & Crowther, 2006), concept, development, and business (van der Meer, 2007), exploration, retention, and exploitation (Lichtenthaler & Lichtenthaler, 2009), make-or-buy, integrate-or-relate, and keep-or-sell (Lichtenthaler, 2011), and obtaining, integrating, commercializing, interaction (West & Bogers, 2013), to name a few. In addition to the phase when firms could adopt OI, they need to decide the appropriate type of partners with whom they will collaborate and innovate. Thus, the challenge does not rely only on the identification of potential collaboration partners (Laursen & Salter, 2006) but on properly selecting the most suitable external actors according to the organisation's context (M. R. Gürtler & Lindemann, 2013). Moreover, partner variety is intrinsically linked to the extent that a firm has developed certain OI practices and capabilities because this situation would drive or delay the interactions to compensate for the lacking ones (Huizingh, 2011). Therefore, the dimension of content variety in OI causes firms to decide between obtaining general content such as explorative or exploitative knowledge (Bengtsson et al., 2015) or more specific like supply chain or project management capabilities (Manzini et al., 2013). Finally and as the different studies of this thesis suggest, variety on practices should be added as a key fourth dimension of OI adoption. First, because innovation and its outcomes not solely rely on (internal and external) collaborations, but also on the way the related interactions can be controlled through certain practices (Smith, 2004). It should be clarified that the suggested fourth dimension of variety on practices also contemplates approaches, methods, initiatives, methodologies, and mechanisms. This choice is justified with studies showing the usefulness of practicing certain IM techniques (Igartua et al., 2010) and methodologies (Bianchi, Campodall’Orto, Frattini, & Vercesi, 2010) to enable open and collaborative approaches, but
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mostly through the PBV of OI emphasised in this thesis. Indeed, this supposition could make the task of choosing an OIP more challenging; however, recent studies are starting to pave the way in this matter by investigating method models for distinguishing and selecting OI practices according to the firm context (see e.g. von Saucken, Gürtler, Schneider, & Lindemann, 2015). Considering the ideas above, Figure 5-3 depicts the fourth dimensions of the key possible varieties involved in OI adoption suggesting a focused view of the relevant choices that firms but also other actors need to consider when practicing OI.
Figure 5-3. Revisiting the latent variety of OI adoption
5.4. The role of OI practices on diverse performance dimensions
To conclude answering the research questions initially presented in this work, it is now necessary to focus on the RSQ3 and by doing so, an important part of the MRQ is also answered. But first, a brief clarification before discussing the findings related to the role and degree in which OIPs can influence multiple and different dimensions of performance. Similar to the presentation of the appended papers, the discussion below does not follow the timeline of the studies conducted but rather a logical sequence to converge the main ideas and findings. This clarification is important because while some studies were consecutive and correspond to the order of the papers (e.g. papers E and F), others started in the beginning of the research project but materialized and provided results until the end. An example of this situation are the pilot case studies of supercars which provided the first indication of studying environmental and social impacts of adopting OI, and consequently, these studies inspired other studies in the foundry industry. However, it was until the SMMS study (paper G) that more concrete and
Partner Variety
Practices Variety
Content Variety
• Universities and research centers • Innovation intermediaries • Government agencies • Customers (i.e. retailers) • Suppliers • Consumers • Competitors • Companies in other industries
• Integration mechanisms • Collaborative approaches • Licensing-in and licensing-out • Learning journeys • Alliances / partnerships • Trend and technology scouting • Online portal for entering ideas • Joint venture • Spin-offs / Spin-outs • Reciprocal license agreements • Grant-back license • Idea contests and platforms • Cross-industry innovation
• Access to leading edge of technology • Innovative products and/or services • Innovative processes • Opening up new markets • Reliable deliveries • System responsibility • Project management capability • Improvement capability
Innovation Phase Variety
• Idea generation
• Experimentation
• Engineering
• Manufacturing
• Commercialization
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robust evidence on these relationships in the automotive industry was found. Having clarified this, a discussion on the roles of OIPs is provided below which goes from the rather anticipated effects on performance dimensions to the less often identified in OI literature, and thus where this thesis provides a clear contribution. To begin with, OI researchers seem to have declared a ‘crusade’ to validate the impact of openness on firm performance. By reviewing the most relevant OI literature (paper A), we can certainly confirm that innovation and economic performance are two of the most studied dependent variables of OI adoption (Giannopoulou et al., 2010; Lichtenthaler, 2011; Schroll & Mild, 2012; West & Bogers, 2013). This is not surprising because as Mazzola et al. (2012) noticed, the question of how openness influences firms to innovate better and obtain higher economic returns is at the core of OI research (Dahlander & Gann, 2010; Gassmann et al., 2010). In addition, even if some studies have done it, more research is needed recognising and emphasising the idea that the context can certainly moderate the relationship between OI and performance, implying that the OI effects on performance are contingent on the internal and external context characteristics (Huizingh, 2011). In fact, all the empirical studies of this thesis have followed this trend by adopting a contingency perspective and therefore, they contribute to literature recognising the relevance of contextual factors on the degree of openness, performance, and other outcomes (Bengtsson et al., 2015; Bianchi, Croce, Dell’Era, Di Benedetto, & Frattini, 2015; Lazzarotti, Manzini, Nosella, et al., 2015; Lazzarotti, Manzini, & Pellegrini, 2015; Stefan & Bengtsson, 2014). Considering the above but also the context of manufacturing firms and mature industries we can find several studies investigating the relationship between adopting OI and an better innovation and economic performance (see e.g. Barge-Gil, 2013; Chiaroni et al., 2010; Cricelli et al., 2015; De Massis et al., 2012; Di Minin et al., 2010; Ebersberger et al., 2012; Ili et al., 2010; Karlsson & Sköld, 2013; Lazzarotti et al., 2013; Martini et al., 2012; Nitzsche, Wirtz, & Göttel, 2015; Parida et al., 2011; Sierzchula et al., 2015). While the findings on these and other studies have more or less consistently found that adopting OI (characterised as practices, models, approaches, initiatives, methods, amongst others forms) can positively influence firm innovativeness, the results of the effects on economic performance have been less coherent. Departing from this discrepancy, this thesis considers the study from paper B as a way to investigate first-hand these relationships by using a reliable source of data i.e. an OIS (Manzini et al., 2013). In other words, I was interested to confirm by myself the inconsistency of results in the literature regarding the relationship between adopting OI and different levels of innovation and economic performance. This goal was successfully achieved by providing other interesting findings. More specifically, based on the different analyses we found that firms with higher levels of OIMs also showed higher levels of Innovation Performance (INP). We also propose a categorization of firms based on the different levels of adoption of OIMs. These categories comprised the ‘super open innovators’, ‘selective collaborators’, and ‘conservative collaborators’, which are better explained in paper B. This result can complement other taxonomies of firms based on OI adoption (see e.g. Ahn, Minshall, & Mortara, 2015; Barge-
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Gil, 2013; Lazzarotti & Manzini, 2009) by proposing a categorization that also considers content variety as a determinant of using a specific OIMs. In overall, the findings of this study suggested that even though a mix of selective OIMs may not greatly enhance firm´s economic performance (e.g. ROA), it could increase innovation performance at least to some degree. Thus, these findings contributes to the very lively debate about why firms should adopt (or not) OI if the effects on innovation levels and economic performance are clear (or not so clear) (see e.g. Barge-Gil, 2013; Cheng & Huizingh, 2014; Ebersberger et al., 2012; Mazzola et al., 2012; Parida, Westerberg, & Frishammar, 2012; Spithoven, 2013; West et al., 2014). Although the studies included in paper C and D were not designed to directly investigate both innovation and economic performance, they provided preliminary but interesting findings of other indicators of organisational performance. To be more precise, paper C focused on understanding how does the integration between inter-organisational networks take place during collaborations in Open Innovation Projects (OIPRs). Therefore, an intrinsic assumption of this study included that an OIPR could be only successfully accomplished through appropriate integration mechanisms. While this assumption could proxy an indicator of project success, it was decided to focus the discussion and the implications of the study to the integration level during OIPRs. The results of this study are interesting in terms of organisational performance for different reasons. First, it confirms that the internal organisation of a firm can have a mutual relationship affecting the innovativeness level (INNO) and innovative behaviour (van Beers, Kleinknecht, Ortt, & Verburg, 2008). Second, it provides evidence to support the idea that ‘particular management mechanisms can primarily strengthen a firm’s organisational capabilities for managing open innovation, which may in turn enhance performance’ (Lichtenthaler, 2011: p. 84). In this regards, practicing integration mechanisms during OI help firms and external partners to establish proficient routine processes that can improve performance by facilitating capability development required for OIPs. Hence, the overall findings suggest that practicing certain mechanisms during OIPRs can benefit the integration level, support organising OI (Bianchi et al., 2015) and enhance the innovativeness capacity of the firms and external partners involved in collaborations (Palmié et al., 2015).
To continue examining other implications of OIPs, paper D focused in exploring the adoption of OI by actors other than large firms in the F&B industry. So even though the main purpose of this study was to examine OIPs influencing initiatives driven by actors other than large firms, the results are relevant to the industrial performance of these firms. For instance, this study provided clear examples of how OIPs adopted by actors such as consumers, communities, foundations, and civil society have the potential to influence consumer goods industries. This influence would involve firms not only proposing collaborative initiatives to innovate with this kind of actors but also to support the ones already created by them. Moreover, and probably most interesting from a firm-centric viewpoint, the findings suggest that large firms and SMEs could improve their performance in two ways by considering these actors and their initiatives. First and a bit more obvious, a firm could adapt and adopt ideas from these initiatives and practices in order to increase its innovativeness level. Second, a firm could also learn or, at least, increase its perception and awareness of the social trends most relevant for users and consumers. In this way, firms could increase their chances of proposing socially driven
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innovations that could ultimately improve the social performance (SOP) dimension within a sustainability perspective. These findings could also contribute to recent studies suggesting that ‘small’ actors driving collaborations can leverage simultaneously vertical and horizontal partner linkages with larger firms in inter-organisational contexts (Dooley et al., 2016). Considering that OIPs could have a significant link with the social dimension, it was also interesting to explore the link between OI and environmental indicators. While this idea originated from the pilot case studies in the automotive industry, we decided to explore it in a different but also relevant industrial context such as energy-intensive industries. Therefore, papers E and F rationalized, explored and examined the link between OIPs and energy efficiency (EE), which can also be considered as an indicator of environmental performance (ENP). More specifically, both studies in the foundry industry provided evidence showing a positive relationship between being more innovative through OIPs and having higher levels of EE in terms of three indicators i.e. SEC, BATs and BEE (Cagno, Worrell, Trianni, & Pugliese, 2013). In addition, because in energy-intensive industries such as foundries, being energy efficient has a direct relationship with the performance of all the firms in the industry, adopting OIPs can positively influence the industrial performance (IDP) of certain sectors. Moreover, the findings of the two studies contribute with empirical evidence to literature linking innovation and energy management fields (Costa-Campi, García-Quevedo, & Trujillo-Baute, 2015; Costa-Campi, García-Quevedo, & Segarra, 2015; Trianni et al., 2013) but also on the relevance of collective, open, and collaborative innovation in energy-intensive industries (Allen, 1983; Arnold & Barth, 2012; Hakkim & Heidrick, 2008) and the manufacturing inside eco-factories of the future (May, Stahl, & Taisch, 2016). Before discussing the implications of the findings in paper G, it should be mentioned that the link between OIPs and the three dimensions of sustainability performance were based on the findings of the pilot case studies of SMMS. For instance, one of the firms is very interested in practicing community service by providing undergrad and master students the opportunity to do their thesis in the company. Also, a common practice in this firm is that even it is often more costly, some details and parts of the interior of the vehicle are outsourced to local artisans since their approach is focused on innovating through tradition (De Massis, Kotlar, Frattini, Petruzelli, & Wright, 2016). In the case of the other firm, a common practice is extending the boundaries of R&D collaborations (Bäck & Kohtamäki, 2015) by conducting design and innovation competitions to provide internships to the winner. Similarly, this firm organises regular meetings with neighbours and other close stakeholders to understand how to minimize the environmental impact of the firm operations and how to spur economic activities within the community. This kind of activities provided the first signal of the possible link between OIPs and SOP and ENP. This was later confirmed in paper G where the findings show that SMEs, if characterised by their sophistication of technology level (Kaulich, 2012), could improve their levels of INNO, ENP, and SOP by adopting OIPs and OIMs. Moreover, adopting OI could be used as a strategy to diversify the sources of knowledge used by specialized SMEs. In this sense, the diversification is not on their products but in their approaches to innovate while they remain specialized retaining their (re)sources of competitive advantage (Barney, 1991).
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To conclude, Figure 5-4 summarises and maps in a simple way the thesis findings related to the role in which OIPs can influence multiple and different dimensions of performance.
Figure 5-4. Mapping the ‘driving’ influence of OIPs on diverse performance dimensions
5.5. The ‘dark side’ of OI practices
This section attempts to provide a critical and objective discussion on the limitations and drawbacks of OIPs according to the observations and findings of the studies conducted during this research project. First of all, it is vital to state that while Open Innovation has increasingly gained numerous adepts and popularity in the last decade, it should not be considered as a dogma4. Hence, even researchers focused in studying and understanding OI are advised to question and demonstrate its validity and usefulness through scholarly research. In fact, it is only using a critical approach when investigating OI that a formal and tighter theory on OI would be possible (hopefully) in the near future (Tidd, 2014). Indeed, while some researchers argue in favour of OI, others may claim that the empirical evidence on the value of OI is limited, and practical prescriptions overly general (Trott & Hartmann, 2009)5. In any case, the key point here is to recognise that OI, as any other IM model, has some limitations and conducting empirical studies is a way to find and tackle them.
4 In here, the word dogma is not used in the sense of a religious doctrine but rather as ‘a belief or set of beliefs that is accepted by the members of a group without being questioned or doubted’ (Merriam-Webster Inc., 2004, p. 369). 5 For an interesting and comprehensive response on such type of critiques please refer to a recent article by Chesbrough and Bogers (2014).
Open Innovation Practices
Innovation
Innovation Performance (INP)
Integration during OIPRs
Innovativeness level (INNO)
Economic Performance (ECP)Return on Assets (ROA)
Turnover / Revenues
Industrial Performance (IDP)
Energy Efficiency (EE)
Specific Energy Consumption (SEC)
Best Available Technologies (BATs)
Barriers to Energy Efficiency (BEE)
Environmental Performance (ENP)
GRI indicators
Social Performance (SOP)
Awareness of social trends
GRI indicators
Paper: B
Papers: E, F
Papers: E, F
Papers: E, F
Paper: G
Paper: D
Paper: G
Paper: C
Papers: C, D, E, F, G
Paper: G
Paper: B
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Aligned to the previous idea, the role of OI practices should not be considered dogmatic and thus some of its drawbacks need to be recognised. Firstly, it seems to be widely recognised that as there is no panacea6 in medicine, it is unlikely that OI has positive effects in all situations, implying the effectiveness of OI practices must also be context dependent (Huizingh, 2011). Second, being OI a type of model thought to manage innovation and technology, we could expect OI to have a ‘dark side’ since creativity and innovation can also have one (Cropley, Cropley, Kaufman, & Runco, 2010). Third, in an ideal industrial setting, besides aiming to develop economic growth through appropriately managed innovation, OIPs should also be directed towards human ends and planetary survival, just as creativity and technology (McLaren, 1993). Indeed, we could debate if OIPs are similar to technology in the sense that it ‘is never morally neutral, but always both good and evil’ (Adeney, 1994: p. 21). Hence we need to acknowledge the possibility of scenarios where a certain OIP impacts on (different forms of) inequality i.e. benefit the few at the expense of the many. Unfortunately, this thesis does not provide the final answers to this possibly philosophical questioning (Okasha, 2002) but it does raise the flag of the potential negative role that OIPs may have in mature industries. In any case, it is possible to provide some general but also specific examples of the issues mentioned above. From a general viewpoint, we could say that the benefits produced by adopting OI practices should compensate the issues that they may cause. Lo illustrate this idea let´s consider the example (although a bit alarmist) of the issues related with the development of the automobile. Even if the innovation of the automobile revolutionized the speed and comfort of travel, ‘the internal combustion engine created a society in which air pollution, traffic accidents, oil spills, cement cities, traffic congestion, environmental degradation, social inequality, changed perceptions of time, parking problems and a host of other effects are commonplace’ (Adeney, 1994: p. 21). Therefore, it is probable to see that equal to technological innovation, the adoption of OI may have some socio-technical challenges that might outweigh its benefits if it is not properly planned and practiced (Ran, 2013). From a specific viewpoint, we can translate these ideas into issues within the context of the studied industries in this thesis. For instance, in the F&B industry adopting several OI practices to obtain new flavours from users may increase disproportionately a line of products. This in turn could affect the procurement, production, and supply chain of the firm in addition to the all the environmental impacts of such choice. Indeed, every action in a firm has a reaction and thus, I am not claiming (even though it would be desired) that before adopting an OIP a complex analysis of its impacts e.g. a Life Cycle Assessment, needs to be conducted. Indeed, some specific analyses related to selecting the right partners, stakeholders, and OI practices should be conducted (see e.g. Guertler et al., 2013; Gürtler & Lindemann, 2013; von Saucken et al., 2015), but also other macro aspects could be considered. In fact, as paper D emphasises, these aspects should include not only the major trends in a certain industry but also the major trends in society. Hence, by taking into account these megatrends (e.g. sustainability or urbanisation) could help firms to plan, design, and practice OI with less negative impacts.
6 A panacea is defined as ‘a remedy for all ills and difficulties’ (Merriam-Webster Inc., 2004, p. 894).
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In the studies of SMEs in the foundry industry (papers E and F), we can see a similar issue but with a higher degree of complexity due to the dependent variable that was studied i.e. energy efficiency (EE). Firstly, we should remember that understanding the energy management practices of these firms is particularly important since they have relatively large improvement potentials in percentage terms (UNIDO, 2010). Therefore, it is rational to think that the more and better practices (including OIPs) adopted to manage energy and improve EE should directly provide an optimal industrial scenario. However, we should consider the possibility of a market negative feedback of EE. This feedback is as follows. The more effective EE initiatives are in place, the less amount of energy (demand in terms of kWh) would be required in the society. This lower demand would cause then a decrease in the price of energy. In turn, this lower energy price would reduce the demand of EE because energy would not be ‘so expensive’ anymore. Since high prices of energy were one of the key reasons that EE initiatives started in the first place, this closes the negative cycle. Although OIPs and energy management practices differ in nature and purpose, a similar phenomenon could happen with the former. Thus, it is advised to attempt to control or propose mechanisms that avoid this type of negative loops when adopting OIPs by firms in mature energy intensive industries. Finally, when considering the context of SMMS we could first reflect on the essence of the previously mentioned example of pros and cons of the automobile invention. Second and more interestingly, the analyses from the two pilot case studies and from paper G provided evidence of the degree of openness by this kind of firms. Thus, we can say that all the studied SMMS have adopted (at least in some extent) OI practices to produce vehicles with high levels of design and performance. However, performance in terms of vehicles has been commonly linked to more powerful engines. So even though OIPs can support the innovation process of SMMS, these could add some technological innovations with other impacts in the environment or the society. Fortunately, as one of the interviewees in the pilot study of the Mexican supercars firm (Ramirez-Portilla, Cagno, & Brown, 2014) mentioned, performance in supercars has also shifted in the last years from being horsepower oriented towards fuel efficiency. In addition, it seems SMMS could also offset potential negative impacts with the support of communities of users (or fans) interested in the co-creation of better vehicles through more collaborative and open practices (Langner & Seidel, 2014). In overall, we did not encounter direct negative impacts of adopting OI in the different studies. Nevertheless, I believe it is worthwhile to mention some of them (according to literature) to demonstrate that we were aware of the potential perils of OI. For instance, during the studies we were fully aware that OI is not the only alternative to a close innovation model (Galbraith & McAdam, 2011). Similarly, we considered the idea that innovation, in general, may have negative effects on firm performance when newly introduced knowledge or technologies are not compatible with the previous ones from the firm (Mariano & Casey, 2015). We also understood that some managers could take the role of harsh critiques of OI (e.g. Trott & Hartmann, 2009) considering the concept a ‘repacking’ of previous ideas. Moreover, we expected (in some extent) that firms could condemn the overrated potential of OI and being more concern about the challenges related to its actual execution (Gwynne, 2007).
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In addition, we also considered the findings from other researchers who, while not providing critiques, have demonstrated some disadvantages and limitations of opening up the innovation process. For instance, some studies have found negative effects of openness when developing new products including worse timing to market, slower product development, and more costly products (Knudsen & Mortensen, 2011). Similarly, studies have found curvilinear effects of the openness to external sources of knowledge (Laursen & Salter, 2006) where OI could provide variety useful for the ideation phase up to the point where increasing approval and integration costs cause negative returns (Salter, Wal, Criscuolo, & Alexy, 2014). Even though we did not find such curvilinear effects in any of the conducted studies, we did receive questions from managers enquiring about the break-even point until it is profitable and resource-efficient (i.e. time, money, persons, etc.) to implement or fully adopt OI practices in an organisation. Linked to the above, it is important to acknowledge that in the studies where there was a direct interaction with managers to collect data (papers C, E, F and G) in some cases, ingenuity or sarcasm was detected in some comments regarding the potential of OI. More specifically, few managers and owners would directly or indirectly imply that by using more and more OI practices and related notions their innovativeness levels were expected to eventually increase. While these types of comments appeared on few occasions, I related them with the panacea illusion. Moreover, elucidating on this matter, I came across an analogy of OI being a model that some managers expect to solve all the innovation problems and ‘save’ the firms. It seems then that for some practitioners, OI could resemble the idea of Deus ex Machina, or ‘God in a Machine’, a theatrical term related to the dramaturge Euripides’ habit of unexpectedly using a crane to lower an actor dressed up as God onto the stage, to resolve the problems of the characters in a way that most of the time was not logical to the initial situation. Similar to the idea of exploiting an external unexpected element to address an unsolvable problem, some managers may believe that innovation practices related to a more open and collaborative approach could take this role within their firms. However, this ideology presents a major issue because seeing OI as Deus ex Machina would imply that firms would rely mainly on external actors to resolve their innovation problems. However, as some studies in OI (including papers E, F, and G) have revealed, implementing and adopting OI is not only about exploring and exploiting external actors but also about internal innovation capacity and IRD. Another key implication and although a bit obvious is that OIPs do not happen alone but there should be a person or group of persons conducting it. In fact, recent studies are stressing the managerial roles that appear to be crucial for organising OI such as facilitators, tacticians, and sensegivers (Ollila & Yström, 2016). It is important to mention this kind of implications for managerial choice and agency when practicing OIPs since lacking them could hinder OI collaborations (Tushman et al., 2012). Although the thesis scope did not focus on such agency elements, one study (paper F) investigated and discussed the implications of having or lacking a full-time innovation manager. What's more, even if a firm has an experienced manager in OIPs, they could fail in attempting some of them. For instance, creating a community of users or crowdsourcing competitions could be unsuccessful due to the lack of user/adopter interest (Dahlander & Magnusson, 2005) or even personality dispositions (West & Lakhani, 2008).
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Finally, a demarcation should be considered between the OI practices that a firm may adopt and the ones that an external actor such as innovation intermediaries may support (see paper C). Aligned with this idea, innovation intermediaries are only one part of the support that resource-limited SMEs receive by public organisations. Other support can include entrepreneurship centres, business incubators or technology transfer offices (Katzy et al., 2013). Without this type of support provided to SMEs, it was noted in different cases that it would be desired that just as with other key business practices, firms could have a central and dedicated team to drive OI practices. This idea suggests that it could be better if these team members could have specialised skills related to OI. In turn, these OI teams could then serve as catalyst teams in innovation themes, or as an emerging technologies group. In this sense, it is imperative for manufacturing firms to integrate and align OI practices with other relevant practices in order to ensure that key (internal and external) actors are involved in critical milestones (Ahn et al., 2015). Similarly, it is also necessary to recognise that it could be useful to integrate OI practices with already existing project management (PM) practices. First, PM techniques could help execute and implement new OI practices. Second, this mix could allow an interdisciplinary integration of resources and projects that if well managed could create synergies and reduce complexity. After all, it is probable that no innovation project is an island and thus it is highly dependent on the current simultaneous activities in the organisation (Engwall, 2003). Lastly, a reluctance to adopt a great number of OI practices due to fear of change was seen in many firms. Therefore, firms should use notions of change management to drive the adoption of OI practices, for instance, to deal with the not-invented-here (Katz & Allen, 1982) or the not-share-here (De Araújo Burcharth, Knudsen, & Søndergaard, 2014) syndromes.
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5.6. The unexpected implications of opening up innovation in brief
The last sections have discussed in detail and in an interlinked way the findings of the different studies in this thesis. Knowing that some people (including myself) like to easily find and read the main take away messages of a book or an article, this section summarises what the thesis title promises. Although there are several implications in this thesis due to the multi-perspective approach used (e.g. different studies and RS) below I provide mainly the implications that I consider as more unexpected and interesting in relation to the role of OIPs. Context matters to a great extent in OI research and practice. In fact, not only
the adoption of OI is highly dependent on the context but the context can also influence the way in which OIPs can be characterised as well as the outcomes resulting from their implementation, adoption, and regular practice.
Although OI can be explained through several and even conflicting theoretical perspectives, using a practice-based view can allow us to understand different forms in which OI can be characterised and practiced within and around industrial settings where OIPs might seem not valid or relevant at first sight.
OIPs can be characterised in varied forms such as models, mechanisms, approaches, initiatives, and methods, amongst others. This variety of practices can complement other variety dimensions to provide a more comprehensive understanding of the different options and key choices related to adopting OI.
While adopting OI can certainly have a positive effect on higher levels of innovativeness, it may not guarantee better economic performance. However, practicing OI can also have a significant influence on other relevant indicators and dimensions also related to firm and industrial performance.
The adoption of certain OIPs can have a direct and positive relationship with higher levels of energy efficiency indicators. While this link is especially important in energy-intensive industries, it is also relevant for other contexts since it shows a clear connection between OIPs and environmental indicators.
Because in energy-intensive industries such as foundries, being energy efficient has a considerable and direct relationship with the performance of all the firms in the industry, it could be said that adopting OIPs can be a feasible approach to influence positively the industrial performance of certain sectors.
Whereas it can be expected that SMEs adopting OI in terms of practices and models could have higher levels of innovativeness (but not necessarily economic performance), it is also possible to anticipate a positive effect on sustainability indicators related to environmental and social performance.
Just as with technology or creativity, the adoption of OI practices and similar approaches is also likely to have a ‘dark’ side. Moreover, the potential issues and drawbacks related to this side are also contingent on the context of an organisation. Thus, it is advised that firms plan sensibly the adoption of OIPs.
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6. Conclusions and Future Research
The aim of this final section is neither to rewrite the introduction or abstract of this document nor to summarise everything that has been written before. Instead, in this section I would prefer to revisit the purpose and research question of this study, as well as providing the most relevant ‘take away messages’. These messages include a clear statement of my research contribution in terms of theoretical and practical implications. Lastly, departing from the main findings of this thesis, I suggest some interesting opportunities for future research.
6.1. Revisiting the purpose and research question
Throughout all the studies in this research project I have tried to always follow the essence of dialectics. This means that I have attempted to balance and critically assess as much as possible the two sides of the story (thesis and antithesis) related to OI. To recapitulate, my initial thesis stated that to contribute building an OI theory and to provide firms with wide-ranging and rigorous evidence of the benefits of adopting OI, researchers should confirm the relevance of certain firm contextual elements. Of all these elements, the key ones to focus on are the type of activities actually practiced and fully adopted by firms, because all these could greatly influence both the degree of adoption of Open Innovation and the project, firm, and industrial results obtained from this adoption. Consequently, it is logical to believe that my antithesis is defined as the opposite of the above. However, from my point of view, the antithesis (which I always had in mind when conducting my research) considered more than a reverse of the original arguments but being critical towards what I was studying. In essence, being critical while researching about OI implied first of all, remembering literature against or asking for a tighter theory and practice of OI (see e.g. Dąbrowska, Fiegenbaum, & Kutvonen, 2013; Galbraith & McAdam, 2011; Huizingh, 2011; Schroll & Mild, 2012; Tidd, 2014; Trott & Hartmann, 2009). Likewise, it also implied considering the viewpoints and arguments from colleagues and senior scholars not convinced with the OI model and its related ideas. Moreover and probably most importantly, it implied recognising that many of the studied firms, especially SMEs, did not know the meaning of OI until the time I disclosed details about my research. This does not necessarily mean that the responses were biased but that the firms studied have been using some OI practices routinely for some time. Considering this, the antithesis of this research could be recapped as potentially accepting the idea that ‘there is nothing new under the sun’ that could be said in OI literature. Fortunately, this was not the case and through the different studies I am confident I was able to accomplish the thesis’ purpose, achieve its objectives, and answer properly all the research questions. In any case and for the sake of clarity, let’s briefly review all of these elements. Firstly, the purpose of this thesis as explained in the beginning was to investigate with multiple perspectives the role that adopting OI practices and approaches could have on different dimensions of firm performance (FP), all this while highlighting the context dependency of OI. Moreover, the objectives of the thesis were: i) to identify and verify if some of the main
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assumptions proposed about OI also apply to few but relevant understudied industrial contexts, ii) to propose and describe different forms of characterising practices related to open and collaborative approaches used by different actors, and iii) to explore and explain the link between OI concepts and practical organisational scenarios and FP. Based on the multiple perspectives used throughout the different studies and reflected in the seven papers, I can confirm that a multi-perspective study of the adoption of OI practices was accomplished. In addition, since each of the studied industries posed a different context, I also feel confident asserting that contingency and context dependency perspectives of OI have been stressed, investigated, and exemplified in each of the studies. Likewise, through at least three different studies and the corresponding papers (C, D, and E) this thesis described other ways of characterising OI practices relevant to different innovation actors. Moreover, because the studies in each context provided different results related to different dimensions of FP, it was possible to explore and rationalise the link between OI practices and performance in terms of innovativeness, projects, industrial, environmental, and social dimensions. Therefore, based on the evidence obtained through this research project, it is possible to state that the adoption of OI practices can benefit organisations from and around mature manufacturing industries, including small and medium-sized firms, in more ways than just being more innovative. Equally important is to revisit the MRQ of this thesis and evaluate if it has been satisfactorily answered. This question was stated as to what extent are OI practices adopted by firms and other actors in unexplored mature manufacturing industries and which are the unidentified roles that these practices play in relation to different dimensions of firm and industrial performance? Accordingly, and based on the different studies conducted, it is possible to say first that the degree to which OI practices have been adopted differs even between similar mature manufacturing industries with no specific pattern or precondition. For instance, it was expected in the beginning to find little or null evidence of OI practices being adopted in the foundry industry. However, this industry was the one that provided some of the most interesting findings regarding the relation between adopting OI and improving some dimensions of firm and industrial performance. From the aggregated results of this thesis, I can also confirm that all of the studied organisations exhibited at least some degree of awareness of OI as a potential paradigm to increase its innovation levels. Nevertheless, not all of them adopted these practices as daily strategies or routines to boost their performance due to organisational inertia, lack of information, and the risks and costs of potential failure, amongst other reasons. Nevertheless in general, firms acknowledge the importance of creating innovations by different means in order to improve their own growth and survival but also to socialise its benefits. Aligned with this idea, it seems also that even small and medium-sized manufacturing firms, as well as other small actors from and around mature industries, see in some OI practices the ability to increase and externalise the benefits of innovation. Thus, even if OI practices have not completely diffused in mature manufacturing industries, it will gradually permeate due to its potential to incorporate solutions with greater added value to users, industry, and society.
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Finally, all the studies provided evidence to conclude that OIPs act as drivers of significant FP and INP indicators depending on the studied context. Thus, it could be said that the roles that OIPs and OIMs play in relation to performance dimensions are contingent to the firms’ organisational and environmental context where they are actually adopted. Therefore, based on the industrial contexts investigated in this thesis, it seems that the varied characterisations of OIPs could increase (paper B), integrate (paper C), diffuse (paper D), explore (paper E), improve (paper F), and diversify (paper G) distinct performance dimensions.
6.2. Research contribution
Demonstrating the contributions of a research project could include stating the implications that such research has accomplished in different aspects (Saunders et al., 2003). Therefore in the subsections below I chose to explain the implications of my research related on the one hand to theory, and in the other to practice and policy. It should also be noted that implications related to the methods used are existent but not completely novel. More specifically, some methods used to study OI are only novel in the sense of application rather than proposition. Some examples used in the studies of this thesis are the use of a tailor-made OI survey specialised for SMEs (i.e. supercars). Likewise, to the best of my knowledge, paper G is the first study to apply the PLS-SEM method to investigate the effects of reflective constructs related to OI models and practices. In any case, I believe implications of this nature have less weight because as some researchers suggest, a wiser option for PhD students conducting an innovation and entrepreneurship thesis would be to choose from the broad variety of methods (and almost without limits) instead of developing new methods (Sassmannshausen & Gladbach, 2011). In fact, these two authors also recommended leaving the development of methods to the most senior researchers and for the purpose of a PhD thesis it is sufficient to prove that the student acquired the ability to make proper or even better use of existing methods. I completely agree with their statements and therefore, I am confident in stating that I have shown the correct usage of different methods in my thesis. This can be seen with the variety of research strategies and techniques to collect and analyse data described in detail in Section 3 and summarised in Table 3-1.
6.2.1. Implications for theory
Researchers are constantly debating about the legitimacy of the OI model and the contribution it can provide to the IM literature (Dahlander & Gann, 2010; Trott & Hartmann, 2009). So even if academics are in favour of OI, they are clear that when a ‘new’ concept like OI is introduced its validity needs to be proven (Elmquist et al. 2009), both internally and externally. In addition, as Chiaroni et al. (2010) remarked, OI theories must account for phenomena that are not fully explained with earlier IM paradigms (Kuhn, 1963), and at the same time to prove external validity it must explain evidence beyond its initial area of inquiry (Yin, 1994). Thus a way to do this is through empirical studies that can prove that OI does exist in practice and in what forms it exists (Schroll & Mild, 2012).
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In this research project, I have studied the extent to which OI practices are adopted by firms in mature manufacturing industries. Therefore, part of my contribution to theory is that through the studies in different research contexts I have supported and extended the applicability and validity of the OI model. In the same way, my project helped to confirm that in mature manufacturing industries, different internal context characteristics can drive different adoptions of OI practices resulting in different effects (Lazzarotti et al., 2010). These effects and relationships have been clearly established in each of the papers not only for the sake of theoretical contributions but also as a way to provide accurate advice and direction to managers and owners, e.g. of SMEs, on the adoption of OI practices. Similarly, the results of this project indicated that firms are very aware of the different OI practices (although with other terms) that they can perform simultaneously. Thus, practices related with INB or OUT processes, or exploitation or exploration activities are usually not seen as exclusive to large firms as shown in some of the papers. Therefore the results of this thesis could also provide some insights about the temporal ambidexterity as a dynamic capability (O’Reilly III & Tushman, 2008) that some SMEs in mature manufacturing firms could have already developed. Furthermore, this thesis also contributed to OI ‘theory’ through three main aspects. First, this project investigated and attempted to contrast some of the theoretical perspectives used when researching OI in mature manufacturing industries. When doing so, it framed, investigated, and validated a practice-based view of OI while justifying its advantages over other theoretical perspectives more commonly used to study OI. Likewise, to anchor this PBV of OI, a context-dependency perspective was emphasised through CT. This mix of perspectives not only proved to be useful but also that OI could be studied from other theoretical angles. Second and linked to the previous idea, while this thesis was theoretically anchored mainly in two perspectives (PBV and CT), it also demonstrated the implications of studying OI with a multi-perspective approach. Such approach was useful for the general aim of exploring the differentiation of OIPs but also for more specific goals such as findings key internal context characteristics or discovering links to uncharted dependent variables (e.g. EE). In this regards, the third main theoretical contribution of this thesis was to provide empirical evidence of the link between adopting OIPs and EE. To the best of our knowledge, this is the first study to provide such findings and thus, we expect that a research bridge could be built between the disciplines of energy and innovation management. Moreover, based on the idea that EE proxies ENP, this thesis also provided preliminary evidence of the positive effect that adopting OIMs and OIPs could have in two of the three performance dimensions of sustainability i.e. ENP and SOP. Finally, one of the inherent goals of my research was to verify and support the process of external validity of the OI model. Therefore, this was done by testing, confirming and expanding OI theories and assumptions in new research contexts. It can be said then that the larger the number of contexts in which the final results can be applied the better the research outcome. This consideration takes us back to one of initial ideas to focus this research by narrowing the study of certain OI perspectives and practices in specific but novel contexts (paper A). So for instance, at first sight SMMS or small foundries may seem to be a very narrow empirical setting. However, if comparing the nature of the products produced, the
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resource-efficient production or its specialisation level, these firms could have similar characteristics to many other SMEs in different industries. This idea is visible in Figure 6-1 which shows other types of firms and industries in which the results and findings of this research could be further explored.
Figure 6-1. Prospective applicability of the thesis results to other industries
Most of these contexts have been analysed under other management and innovation ideas and therefore the final results of this thesis could complement these studies. A clear example of the above is the idea that SMMS have very similar characteristics to luxury goods since the products are targeted to a niche market, the volume of production is low, the quality is extremely high, and even though the level of innovation is not as high as other products, the end consumer pays a great amount of money for these products (Brun & Castelli, 2013; Riguelle & Van Caillie, 2010). Hence, if the luxury industry has its own specific dynamics and assumptions (Brun et al., 2008), SMMS could also be studied with a combination of OI and luxury perspectives. Similar relations could also exist for all the other contexts in Figure 6-1.
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6.2.2. Implications for practice and policy
As mentioned before, it is a common perception that the relation between successful innovations and profit is practically a tautology (Maital & Seshadri, 2012). Therefore, it is expected that adopting certain innovation practices should help firms to achieve high, sustained growth, profitability, and survival. However for firms in many industries and sectors attempting to create innovations is no longer a self-sustained strategy. Consequently, it is expected that firms will sooner or later attempt to use new innovation models, techniques, and tools to create, co-create and acquire technology and innovation with other actors of industry and society. It is in this scenario where a firm, depending on its context characteristics, could ultimately engage in more open and collaborative practices. Therefore, the next implications for practitioners are part of the managerial contribution that this research provides. But first, it needs to be noted that just as some academics claim, some practitioners also argue that OI practices have always been part of the innovation process within the firms (Trott & Hartmann, 2009). Nevertheless, the challenge lies in the firms really engaging in real OI efforts and not only with marketing purposes. As mentioned before a more clear challenge could be between the firms not being able to differentiate between the implementation and the adoption of OI practices. While the former implies that a firm may start using certain OI practices for the first time, the latter is more related to the firm actually using this practice correctly for firm performance benefit. Thus, the findings of this thesis showing the practices at an adoption level (not only with sporadic use) provides managers in mature industries clear evidence of its influence and benefits. It is expected then, that the overall thesis findings can convince managers that the adoption of OI practices is a dynamic process requiring a sustained effort for continuous and further development of innovation within the firm. Aligned with this, practitioners may find some of the OI practices studied useful in the different papers to conduct self-assessment of their own practices. This in turn, could allow them to understand if the collaborative and open practices used to innovate are part of the organisation´s best practices. When they are, this will indicate a high level of adoption that will likely enable a firm to positively increase FP in different dimensions. In case they are not being practiced in their organisations, before rushing to adopt each of them, the advice would be to consider the most relevant organisational and environmental factors that may determine if a certain Open Innovation practice, approach, or initiative would be successfully implemented and adopted. In other words, this advice centres on the idea that a contingency view is not only a theoretical idea but it is also a useful perspective for practitioners. Another practical contribution of this doctoral project is that all the results suggest that OI practices should be incorporated into the innovation strategy of a firm. Moreover, OI practices need to be designed within the innovation strategy which itself should be aligned with the business strategy. This alignment confirming a commitment rather than a campaign could then help firms to decide on an agenda for the innovation practices used to create and capture value
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(Pisano, 2015). Moreover, based on the idea of following the intrinsic drive of mastery (Pink, 2009), managers are advised not only to practice OI but to eventually master it. While mainly using the findings of one study (paper G), it is still important to mention that this thesis shows managers how even in mature traditional industries, SMEs can play an important role as explorers of markets or as technical specialists (Chesbrough, 2010) allowing them to generate innovation with a great potential for diffusion. In fact, this study was also relevant in terms of practical implications since it provided empirical evidence on the role that OI practices and models can have in influencing a manufacturing firm’s ENP and SOP, which is of considerable importance given the current policies encouraging sustainability in this sector (De Backer, 2015; European Commission, 2010; OECD, 2008b). Based on these findings, it is expected that practitioners from SMEs in mature industries might consider adopting OI as a viable option to increase their level of innovativeness but also to become sustainable, resource-efficient, and more competitive (European Commission, 2010). In terms of implications related to policy, this research includes suggestions for innovation policies in different levels. For instance, several government agencies (e.g. VINNOVA) or EU funded projects (e.g. PROSESC), are supporting research and best practices of OI in mature manufacturing industries. However it is only through further evidence of the OI model validity that future support will continue. My expectations are that the overall results of this research can provide some insights that can be used in the IM agendas of firms and hopefully also in regional innovation systems (e.g. association of foundries as described in papers E and F). Also, some of the results derived from the studies might be used as a guide to help evaluate grant proposals of Open Innovation projects that are aimed to support different types of actors (mostly SMEs) in mature industries. Finally, as noticed more than two decades ago, firms in mature industries such as large carmakers, wishing to seek more radical innovation may need to search for new knowledge beyond their traditional network of R&D suppliers (March, 1991). In this regard, an OI network could be the way to enlarge and strengthen an open regional or even national innovation system (Santonen, Kaivo-oja, & Suomala, 2007) in this type of industry. Moreover, OI could be used in several mature industries to integrate external partners into the innovation process of SMEs. This could help overcome the internal problems from a purely ‘closed’ innovation approach (Keupp & Gassmann, 2009) and attempt to find the right balance of OI practices for each organisation. Last but not least, some of the studies related to this thesis have helped to remark on the possibility of citizens, users, and small actors to actively collaborate with large firms and government agencies through a varied set of OI practices and initiatives. Hence, this thesis highlights the importance of strengthening the institutional framework that fosters the innovation process. In general, some of the results could help to develop strategies that guide policies to promote and diffuse OI practices further in industries.
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6.3. Suggestions for future research
From an optimistic point of view, OI can be considered an extremely versatile concept with the potential to be researched with many other concepts, phenomena, trends, and ideas. In fact, I must admit that it was quite challenging for me to maintain the scope of this research throughout my PhD studies. Actually, this can be seen in the list of additional publications (beginning of this manuscript) that illustrate some of the ideas that I needed to leave aside. In any case, after deliberating on the multiple research opportunities related to the adoption of OI practices, I explain below some that I deem as interesting, relevant, and promising. An interesting research opportunity would involve investigating the full effect of adopting OI practices on other aspects of the firm. More specifically, further research should focus on examining if adopting OI practices (as an organisational innovation) besides having an influence on the value created, also has an effect on the other two key variables of a firm business model, i.e. price and cost. Thus, further studies need to clarify how adopting a series of OI practices in different degrees could support the improvement of business models that can create sustained growth, profitability and competitive advantage (Maital & Seshadri, 2012). Considering a macro perspective, it also seems promising to study the adopted practices within OI National Systems (see e.g. Santonen, Kaivo-oja, & Suomala, 2007) based on the culture and not only on the geographical frontiers. For example, several SMEs in California are founded or managed by Hispanic people who participate in a broader Innovation System outside the U.S.A. These firms exchange knowledge and resources with other firms in the country of origin of the founders which in turn also further develop a more open innovation system (Graf & Braun, 2013). Hence, further studies could consider immigration and culture as key contingent elements from the social context influencing the adoption of OI practices. Aligned with the last idea, although this thesis has contributed to understanding the adoption of OI under a contingency perspective, other several contextual factors can be further studied. In fact, recent studies have revived the interest on the mediating and moderating roles that organisational elements (internal context) have on the openness of firms to achieve better collaboration and innovation performance (e.g. Lazzarotti, Manzini, Nosella et al., 2015). Amongst these internal elements a firm´s degree of absorptive capacity (e.g. Lazzarotti, Manzini, & Pellegrini, 2015) and entrepreneurial orientation (e.g. Cheng & Huizingh, 2014) seem promising to continue studying and explaining OI related phenomena. Moreover, these elements could add to already proposed innovation and entrepreneurship frameworks (Brem, 2011). Hence, future studies could investigate the suitability of certain OI practices to better manage the flow of knowledge during the different stages of new venture creation (Eftekhari & Bogers, 2015). Also, an interesting connection between OI and entrepreneurship is that both the adoption of OI and venture discovery and creation could be seen as a continuum. This similarity suggests that some OI practices could support effectuation and causation processes depending on the stage of organisational development (Becker, Aufseß, & Brem, 2015). Thus, further studies could examine if certain OI practices are more suitable for start-ups than for established companies and conversely.
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In addition, a firm’s internal characteristics are only one side of the environment and thus, external context characteristics should also be considered. Therefore, it would be relevant to study the influence of OI practices adopted not only by large firms but also by smaller actors in a context where most of them could and should happen but only some of them are actually used. A potential context could be science parks, which are contexts where small actors and firms can both play a vital role (Romijn & Albu, 2002). In fact, science parks have been recently positioned often in local or regional SME networks where OI activities play an important role (Katzy et al., 2013; Lee, Park, Yoon, & Park, 2010). Therefore, studies examining how OI practices may create competitive advantages depending on the capacity of the actors contexts and the practices used (Sadeghi & Sadabadi, 2015) seems relevant. Finally, future research on Open Innovation should address practical problems with a more holistic approach. For example, the promising role that Open Innovation approaches can have in the public sector has been recently stressed (Bakici, Almirall, & Wareham, 2013). A particular case involves open collaborative frameworks to promote Smart Cities (Paskaleva, 2011; Schaffers et al., 2011). These contexts present a particular mix of collaborative approaches used by unique innovation actors. Thus, it would be interesting to further investigate the scope of OI practices and its link with major trends (paper D) to design Open Cities (Bakici, 2011; Salmelin, 2015). Moreover, the variety of OI concepts driving these initiatives, signals the need to study how to select appropriate OI practices but also how to tailor them to a specific context. Methodologies such as Design Thinking (DT) could help design meaningful and creative OI practices with a more holistic and human-centred approach (Brown, 2008). In fact, DT main features include efficient prototyping which could also be linked to collaborative prototyping (Bogers & Horst, 2014) and together with other collaborative practices, it could have the potential to improve sustainability in manufacturing firms (Ball & Jolly, 2015). Therefore, further studies should consider the role that this and similar tools together with OI could have on driving sustainability in manufacturing firms in mature industries but also on other types of sectors and industries.
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References
Aas, T. H., Breunig, K. J., Hydle, K. M., & Pedersen, P. E. (2015). Innovation management practices in production-intensive service firms. International Journal of Innovation Management, 19(05), 1550055.
Abernathy, W. J. (1978). The Productivity Dilemma: Roadblock to Innovation in the Automobile Industry. Baltimore: Johns Hopkins University Press.
Abernathy, W. J., & Utterback, J. M. (1978). Patterns of industrial innovation. Technology Review, 80(7), 40–47.
Açıkgöz, A., Günsel, A., Kuzey, C., & Seçgin, G. (2015). Functional Diversity, Absorptive Capability and Product Success : The Moderating Role of Project Complexity in New Product Development Teams. Creativity and Innovation Management, 1–20. doi:10.1111/caim.12155
Adams, J., Khan H. T. A., Raeside, R., & White, D. (2007). Research Methods for GraduateBusiness and Social Science Students. London: Sage Publications Ltd.
Adeney, B. T. (1994). The Dark Side of Technology. Transformation, 11(2), 21–25. Agogué, M., Levillain, K., & Hooge, S. (2015). Gamification of Creativity: Exploring the
Usefulness of Serious Games for Ideation. Creativity and Innovation Management, 24(3), 415–429.
Ahn, J. M., Minshall, T., & Mortara, L. (2015). Open innovation: a new classification and its impact on firm performance in innovative SMEs. Journal of Innovation Management, 3(2), 33–54.
Akao, Y. (1990). Quality Function Deployment. Cambridge, MA: Productivity Press. Albors-Garrigos, J., Etxebarria, N. Z., Hervas-Oliver, J. L., & Epelde, J. G. (2011). Outsourced
innovation in SMEs; a field study of R&D units in Spain. International Journal of Technology Management, 55(1/2), 138–155.
Alexander, A. T., Neyer, A.-K., & Huizingh, K. R. E. (2016). Introduction to the special issue: transferring knowledge for innovation. R&D Management, n/a–n/a. doi:10.1111/radm.12195
Allen, R. C. (1983). Collective invention. Journal of Economic Behaviour and Organization, 4(1), 1–24.
Aloini, D., Martini, A., & Pellegrini, L. (2011). A structural equation model for continuous improvement: a test for capabilities, tools and performance. Production Planning & Control, 22(7), 628–648.
Altmann, P., & Li, J. (2011). The novelty of Open Innovation. Altshuller, G. S. (1984). Creativity as an exact science. New York, NY.: Gordon & Breach
Science Publisher. Alvarez, S., & Barney, B. (2001). How entrepreneurial firms can benefit from alliances with
large partners. The Academy of Management Executive, 15(1), 139–148. Anderson, C. (2012). Makers: The New Industrial Revolution. New York: Crown Business.
References
107
APQC. (2015). Blueprint for Success: Manufacturing. Houston. Arnold, M., & Barth, V. (2012). Open innovation in urban energy systems. Energy Efficiency,
5(3), 351–364. Arora, A., & Gambardella, A. (1994). Evaluating technological information and utilizing it:
Scientific knowledge, technological capability, and external linkages in biotechnology. Journal of Economic Behavior & Organization, 24(1), 91–114.
Azadegan, A., & Dooley, K. J. (2010). Supplier innovativeness, organizational learning styles and manufacturer performance: An empirical assessment. Journal of Operations Management, 28(6), 488–505.
Bäck, I., & Kohtamäki, M. (2015). Boundaries of R&D collaboration. Technovation, 45-46, 15–28.
Bahemia, H., & Squire, B. (2010). A contingent perspective of open innovation in new product development projects. International Journal of Innovation Management, 14(04), 603–627.
Baines, T. S., Lightfoot, H. W., Benedettini, O., & Kay, J. M. (2009). The servitization of manufacturing: A review of literature and reflection on future challenges. Journal of Manufacturing Technology Management, 20(5), 547–567.
Bakici, T. (2011). State of the Art – Open Innovation in Smart Cities. Barcelona. Bakici, T., Almirall, E., & Wareham, J. (2013). The role of public open innovation
intermediaries in local government and the public sector. Technology Analysis & Strategic Management, 25(3), 311–327.
Baldwin, C., Hienerth, C., & Von Hippel, E. (2006). How user innovations become commercial products: A theoretical investigation and case study. Research Policy, 35(9), 1291–1313. doi:How user innovations become commercial products: A theoretical investigation and case study
Ball, P., & Jolly, M. (2015). Sustainable Manufacturing for the Future: Investigating the current and future landscape across the food and drink industry in Great Britain. Cranfield, UK.
Barge-Gil, A. (2013). Open Strategies and Innovation Performance. Industry & Innovation, 20(7), 585–610.
Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), 99/120.
Barney, J. B. (1985). Dimensions of informal social network structure: Toward a contingency theory of informal relations in organizations. Social Networks, 7(1), 1–46.
Barney, J. B. (1986). Strategic factor markets: Expectations, luck, and business strategy. Management Science, 32(10), 1231–1241.
Becker, A., Aufseß, D. zu K., & Brem, A. (2015). Beyond traditional developmental models: a fresh perspective on entrepreneurial new venture creation. International Journal of Entrepreneurial Venturing, 7(2), 152–172.
The unexpected implications of opening up innovation
108
Bengtsson, L., Lakemond, N., Lazzarotti, V., Manzini, R., Pellegrini, L., & Tell, F. (2015). Open to a Select Few? Matching Partners and Knowledge Content for Open Innovation Performance. Creativity and Innovation Management, 24(1), 72–86.
Bergström, M., Ericson, Å., & Törlind, P. (2010). 4I4I: Four I:s for Innovation a book with easy to use methods and ideas to foster innovative product development.
Berkhout, A. J., Hartmann, D., Van der Duin, P., & Ortt, R. (2006). Innovating the innovation process. International Journal of Technology Management, 34(3/4), 390–404.
Bianchi, M., Campodall’Orto, S., Frattini, F., & Vercesi, P. (2010). Enabling open innovation in small- and medium-sized enterprises: how to find alternative applications for your technologies. R&D Management, 40(4), 414–431.
Bianchi, M., Cavaliere, A., Chiaroni, D., Frattini, F., & Chiesa, V. (2011). Organisational modes for Open Innovation in the bio-pharmaceutical industry: An exploratory analysis. Technovation, 31(1), 22–33.
Bianchi, M., Croce, A., Dell’Era, C., Di Benedetto, C. A., & Frattini, F. (2015). Organizing for Inbound Open Innovation: How External Consultants and a Dedicated R&D Unit Influence Product Innovation Performance. Journal of Product Innovation Management, n/a–n/a. doi:10.1111/jpim.12302
Bilgram, V., Brem, A., & Voigt, K. (2008). User-centric innovations in new product development-systematic identification of lead users harnessing interactive and collaborative online-tools. International Journal of InnovationManagement, 12(3), 419–458.
Birkie, S. E. (2015). Be lean to be resilient: Setting capabilities for turbulences. Blackler, F. (1995). Knowledge, Knowledge Work and Organizations: An Overview and
Interpretation. Organization Studies, 16(6), 1021–1046. Blackler, F., Crump, N., & McDonald, S. (2000). Organizing Processes in Complex Activity
Networks. Organization, 7(2), 277–300. Boer, H., Kuhn, J., & Gertsen, F. (2006). Continuous Innovation Managing Dualities through
Co-ordination. Bogers, M. (2011). The open innovation paradox: knowledge sharing and protection in R&D
collaborations. European Journal of Innovation Management, 14(1), 93–117. Bogers, M. (2012). Knowledge Sharing in Open Innovation: An Overview of Theoretical
Perspectives on Collaborative Innovation. In C. de P. Heredero & D. López (Eds.), Open Innovation at Firms and Public Administrations: Technologies for Value Creation (pp. 1–14). Hershey, PA: IGI Global.
Bogers, M., Afuah, A., & Bastian, B. (2010). Users as innovators: A review, critique, and future research directions. Journal of Management, 36(4), 857–875.
Bogers, M., & Horst, W. (2014). Collaborative prototyping: Cross‐fertilization of knowledge in prototype‐driven problem solving. Journal of Product Innovation Management, 31(4), 744–764.
References
109
Bonoma, T. V. (1985). Case Research in Marketing: Opportunities, Problems, and a Process. Journal of Marketing Research, 22(2), 199–208.
Boscherini, L., Chiaroni, D., Chiesa, V., & Frattini, F. (2010). How to use pilot projects to implement open innovation. International Journal of Innovation Management, 14(6), 1065–1097.
Bowman, C., & Ambrosini, V. (2000). Value creation versus value capture: towards a coherent definition of value in strategy. British Journal of Management, 11(1), 1–15.
Bozdogan, K., Deyst, J., Hoult, D., & Lucas, M. (1998). Architectural innovation in product development through early supplier integration. R&D Management, 28(3), 163–173.
Brem, A. (2011). Linking innovation and entrepreneurship - literature overview and introduction of a process-oriented framework. International Journal of Entrepreneurship and Innovation Management, 14(1), 6–35.
Brem, A., Kreusel, N., & Neusser, C. (2008). Performance measurement in SMEs: Literature review and results from a German case study. International Journal of Globalisation and Small Business, 2(4), 411–427.
Brem, A., Maier, M., & Wimschneider, C. (2016). Competitive advantage through innovation: the case of Nespresso. European Journal of Innovation Management, 19(1), 133–148.
Brewer, J., & Hunter, A. (2006). Foundations of Multimethod Research. London, UK: Sage Publications.
Broström, A. (2011). Book reviews - The Triple Helix: University–industry–government innovation in action. Papers in Regional Science, 90(2), 441–442.
Brown, M. A., Cortes, R., & Cox, M. (2010). Reinventing Industrial Energy Use in a Resource-Constrained World (No. 52). Atlanta, GA.
Brown, T. (2008). Design Thinking. Harvard Business Review, 86(6), 84–93. Brown, T. E., Davidsson, P., & Wiklund, J. (2001). An operationalization of Stevenson’s
conceptualization of entrepreneurship as opportunity-based firm behavior. Strategic Management Journal, 22(10), 953–968.
Brun, A., Caniato, F., Caridi, M., Castelli, C., Miragliotta, G., Ronchi, S., & Spina, G. (2008). Logistics and supply chain management in luxury fashion retail: Empirical investigation of Italian firms. International Journal of Production Economics, 114(2), 554–570.
Brun, A., & Castelli, C. (2013). The nature of luxury: a consumer perspective. International Journal of Retail & Distribution Management, 41(11/12), 823–847.
Brunswicker, S., & Ehrenmann, F. (2013). Managing Open Innovation in SMEs : A Good Practice Example of a German Software Firm. International Journal of Industrial Engineering and Management, 4(1), 33–41.
Brunswicker, S., & Vanhaverbeke, W. (2011). Beyond open innovation in large enterprises: How do small and medium-sized enterprises (SMEs) open up to external innovation sources?
The unexpected implications of opening up innovation
110
Brunswicker, S., & Vanhaverbeke, W. (2014). Open Innovation in Small and Medium-Sized Enterprises (SMEs): External Knowledge Sourcing Strategies and Internal Organizational Facilitators. Journal of Small Business Management (Vol. 8, pp. 1–23).
Bryman, A., & Bell, E. (2007). Business Research Methods (2nd ed.). Oxford: Oxford University Press.
Burns, T., & Stalker, G. M. (1961). The Management of Innovation. London, UK: Tavistock. Caetano, M., & Amaral, D. C. (2011). Roadmapping for technology push and partnership: A
contribution for open innovation environments. Technovation, 31(7), 320–335. Cagno, E., Worrell, E., Trianni, A., & Pugliese, G. (2013). A novel approach for barriers to
industrial energy efficiency. Renewable and Sustainable Energy Reviews, 19, 290–308. Caiazza, R. (2015). Explaining innovation in mature industries: evidences from Italian SMEs.
Technology Analysis & Strategic Management, 27(8), 975–985. Caird, S., Hallett, S., & Potter, S. (2013). The Open2-Innova8ion Tool—A software tool for
rating organisational innovation performance. Technovation, 33(10-11), 381–385. Carayannis, E. G., Barth, T. D., & Campbell, D. F. (2012). The Quintuple Helix innovation
model: global warming as a challenge and driver for innovation. Journal of Innovation and Entrepreneurship, 1(2), 12.
Catry, B. (2003). The great pretenders: the magic of luxury goods. Business Strategy Review, 14(3), 10–17.
Cheetham, C. (2006). Supercars: The World’s Most Exotic Sports Cars. (MotorBooks, Ed.). Cheng, C. C. J., & Huizingh, E. K. R. E. (2014). When is open innovation beneficial? The role
of strategic orientation. Journal of Product Innovation Management, 31(6), 1235–1253. Cheng, C. C. J., & Huizingh, E. K. R. E. (2014). When Is Open Innovation Beneficial? The
Role of Strategic Orientation. Journal of Product Innovation Management, 31(6), 1235–1253.
Chesbrough, H. (2003a). Open innovation: The new imperative for creating and profiting from technology. Boston: Harvard Business Press.
Chesbrough, H. (2003b). The era of open innovation. Sloan Management Review, 44(3), 35–41.
Chesbrough, H. (2006). Open innovation: A new paradigm for understanding industrial innovation. In H. Chesbrough, W. W.Vanhaverbeke, & J. West (Eds.), Open innovation: Researching a new paradigm (pp. 1–12). Oxford: Oxford University Press.
Chesbrough, H., & Bogers, M. (2014). Explicating open innovation: clarifying an emerging paradigm for understanding innovation. In H. Chesbrough, W. Vanhaverbeke, & J. West (Eds.), New Frontiers in Open Innovation (p. 368). Oxford: University Press.
Chesbrough, H., & Crowther, A. (2006). Beyond high tech: early adopters of open innovation in other industries. R&D Management, 36(3), 229–236.
Chesbrough, H., Vanhaverbeke, W., & West, J. (2006). Open Innovation: Researching a New Paradigm. Oxford: Oxford University Press.
References
111
Chesbrough, H. W. (2007). Why companies should have open business models. Mit Sloan Management Review, 48(2), 22–28.
Chesbrough, H. W. (2013). Open business models: How to thrive in the new innovation landscape. Boston, MA: Harvard Business School Press.
Chiaroni, D., Chiesa, V., & Frattini, F. (2010). Unravelling the process from Closed to Open Innovation: evidence from mature, asset-intensive industries. R&D Management, 40(3), 222–245.
Chiaroni, D., Chiesa, V., & Frattini, F. (2011). The Open Innovation Journey: How firms dynamically implement the emerging innovation management paradigm. Technovation, 31(1), 34–43.
Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Boston, MA: Harvard Business School Press.
Christensen, C. M., & van Bever, D. (2014). The capitalist’s dilemma. Harvard Business Review, 92(6), 60–68.
Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: a new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152.
Conte, A. (2002). Innovation in Italian industry : a firm-level analysis. Costa-Campi, M. T., García-Quevedo, J., & Segarra, A. (2015). Energy efficiency
determinants: An empirical analysis of Spanish innovative firms. Energy Policy, 83, 229–239.
Costa-Campi, M. T., García-Quevedo, J., & Trujillo-Baute, E. (2015). Challenges for R&D and innovation in energy. Energy Policy, 83, 193–196.
Cox, J., & Hassard, J. (2010). Triangulation. In A. Mills, G. Durepos, & E. Wiebe (Eds.), Encyclopedia of Case Study Research (pp. 944–948). Thousand Oaks, CA: Sage Publications.
Cricelli, L., Greco, M., & Grimaldi, M. (2015). Assessing the Open Innovation Trends By Means of the Eurostat Community Innovation Survey. International Journal of Innovation Management, 20(3), 1650039.
Cropley, D. H., Cropley, A. J., Kaufman, J. C., & Runco, M. A. (Eds.). (2010). The Dark Side of Creativity. In The Dark Side of Creativity (p. 406). Cambridge, UK: Cambridge University Press.
Crossan, M. M., & Apaydin, M. (2010). A multi-dimensional framework of organizational innovation: A systematic review of the literature. Journal of Management Studies, 47(6), 1154–1191.
Cyert, R., & March, J. (1963). A behavioral theory of the firm. Englewood Cliffs, NJ: Prentice-Hall.
Dąbrowska, J., Fiegenbaum, I., & Kutvonen, A. (2013). Mapping The Perception And Reality Of Open Innovation. International Journal of Innovation Management, 17(06), 1340016.
Dahlander, L., & Gann, D. (2007). Appropriability, proximity, routines and innovation: How open is open innovation. In DRUID Summer Conference (p. 23).
The unexpected implications of opening up innovation
112
Dahlander, L., & Gann, D. M. (2010). How open is innovation? Research Policy, 39(6), 699–709.
Dahlander, L., & Magnusson, M. G. (2005). Relationships between open source software companies and communities: Observations from Nordic firms. Research Policy, 34(4), 481–493.
De Araújo Burcharth, A. L., Knudsen, M. P., & Søndergaard, H. A. (2014). Neither invented nor shared here: The impact and management of attitudes for the adoption of open innovation practices. Technovation, 34(3), 149–161.
De Backer, K. (2015). The next production revolution. Paris. De Backer, K., & Cervantes, M. (2008). Open innovation in global networks. Paris: OECD
Publishing. De Backer, K., Cervantes, M., & van de Velde, E. (2008). Open Innovation in Global
Networks. Paris: OECD Publishing. De Backer, K., López-Bassols, V., & Martinez, C. (2008). Open innovation in a global
perspective: what do existing data tell us? De Bono, E. (1989). Six thinking hats. London, UK: Penguin Book Inc. De Massis, A., Kotlar, J., Frattini, F., Petruzelli, A., & Wright, M. (2016). Innovation Through
Tradition: Lessons From Innovative Family Businesses And Directions For Future Research. Academy of Management Perspectives. doi:10.5465/amp.2015.0017
De Massis, A., Lazzarotti, V., Pizzurno, E., & Salzillo, E. (2012). Open Innovation in the Automotive Industry: A Multiple Case-Study. In H. Sun (Ed.), Management of Technological Innovation in Developing and Developed Countries (pp. 217–235). Rijeka, Cro: InTech.
Denzin, N. K., & Lincoln, Y. S. (1994). Handbook of Qualitative Research. Thousand Oaks, CA: Sage Publications.
Dewangan, V., & Godse, M. (2014). Towards a holistic enterprise innovation performance measurement system. Technovation, 34(9), 536–545.
Di Minin, A., Frattini, F., & Piccaluga, A. (2010). Fiat: Open Innovation in a Downturn (1993-2003). California Management Review, 52(3), 132–159.
Diener, K., & Piller, F. (2013). The market for Open Innovation - OIA Survey 2013. Aachen. Dodourova, M., & Bevis, K. (2012). Networking innovation in the European car industry:
Does the open innovation model fit? Hertfordshire, UK. Dooley, L., Kenny, B., & Cronin, M. (2016). Interorganizational innovation across geographic
and cognitive boundaries: does firm size matter? R&D Management, 46(S1), 227–243. Drucker, P. F. (1985). Innovation and Entrepreneurship: practice and principles. Oxford:
Heinemann. Dubois, A., & Gadde, L.-E. (2002). Systematic combining: an abductive approach to case
research. Journal of Business Research, 55(7), 553–560. Duncan, R. B. (1972). Characteristics of Organizational Environments and Perceived
Easterby-Smith, M., Thorpe, R., & Lowe, A. (2002). Management research: an introduction (2nd Ed.). London: SAGE Publications Ltd.
Eberle, B. (1982). Visual Thinking: A “scamper” Tool for Useful Imaging. Buffalo, N.Y.: DOK Publishers.
Ebersberger, B., Bloch, C., Herstad, S. J., & van de Velde, E. (2012). Open Innovation Practices and their Effect on Innovation Performance. International Journal of Innovation and Technology Management, 9(6), 1–22.
Eftekhari, N., & Bogers, M. (2015). Open for Entrepreneurship: How Open Innovation Can Foster New Venture Creation. Creativity and Innovation Management, 24(4), 574–584.
Eisenhardt, K. M. (1989). Building Theories from Case Study Research. The Academy of Management Review, 14(4), 532–550.
Eisenhardt, K. M., & Martin, J. a. (2000). Dynamic capabilities: what are they? Strategic Management Journal, 21(10-11), 1105–1121.
Elmquist, M., Fredberg, T., & Ollila, S. (2009). Exploring the field of open innovation. European Journal of Innovation Management, 12(3), 326–345.
Engwall, M. (2003). No project is an island: linking projects to history and context. Research Policy, 32(5), 789–808.
Enkel, E., Gassmann, O., & Chesbrough, H. (2009). Open R&D and open innovation: exploring the phenomenon. R&D Management, 39(4), 311–316.
Etzkowitz, H. (2008). The Triple Helix: University–industry–government innovation in action. New York, NY.: Routledge.
Etzkowitz, H., & Leydesdorff, L. (1995). The triple helix – university-industry-government relations: a laboratory for knowledge-based economic development. EASST Rev, 14, 14–19.
Etzkowitz, H., & Leydesdorff, L. (1997). Universities and the Global Knowledge Economy: A Triple Helix of University- Industry-Government Relations. London: Pinter Publishers.
Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: from national systems and “Mode 2” to a triple helix of university-industry-government relations. Research Policy, 29(2), 109–123.
European Commission. (2010). Europe 2020: a strategy for smart, sustainable and inclusive growth: communication from the Commission. Brussels.
European Commission. (2013a). Digital Agenda for Europe: A Europe 2020 Initiative. Retrieved from http://ec.europa.eu/digital-agenda/en
European Commission. (2013b). EU energy in figures: Statistical pocketbook 2013. Luxemburg.
Eurostat. (2013). Community Innovation Survey (CIS). Retrieved from http://epp.eurostat.ec.europa.eu/portal/page/portal/microdata/cis
Ezzy, D. (2009). Qualitative analysis: Practice and innovation. Crows Nest, NSW: Allen and Unwin.
The unexpected implications of opening up innovation
114
Faff, R. W. (2015). Pitching Research. SSRN Electronic Journal, (January). doi:10.2139/ssrn.2462059
Fagerberg, J. (2004). Innovation: A guide to the literature. In The Oxford Handbook of Innovation (p. 656). Oxford, UK: Oxford University Press.
Fagerberg, J., Fosaas, M., & Sapprasert, K. (2012). Innovation: Exploring the knowledge base. Research Policy, 41(7), 1132–1153.
Fiedler, F. E. (1964). A contingency model of leadership effectiveness. Advances in Experimental Social Psychology, 1(1), 149–190.
Field, A. (2009). Discovering statistics using SPSS. London: Sage publications. Fisher, J. G. (1998). Contingency theory, management control systems and firm outcomes: past
results and future directions. Behavioral Research in Accounting, 10, 47–64. Forbes, D. P., & Kirsch, D. a. (2011). The study of emerging industries: Recognizing and
responding to some central problems. Journal of Business Venturing, 26(5), 589–602. Freeman, C. (1974). The Economics of Industrial Innovation. London: Frances Pinter. Frey, C. B., & Osborne, M. A. (2013). The future of employment: How susceptible are jobs to
computerisation? Oxford. Frishammar, J., & Ake Horte, S. (2005). Managing External Information in Manufacturing
Firms: The Impact on Innovation Performance. Journal of Product Innovation Management, 22(3), 251–266.
Galbraith, B., & McAdam, R. (2011). The promise and problem with open innovation. Technology Analysis & Strategic Management, 23(1), 1–6.
Gambardella, A., & Panico, C. (2014). On the management of open innovation. Research Policy, 1–11.
Garcia Martinez, M. (2014). Co-creation of Value by Open Innovation: Unlocking New Sources of Competitive Advantage. Agribusiness, 30(2), 132–147.
Gassmann, O. (2006). Opening up the innovation process: towards an agenda. R&D Management, 36(3), 223–228.
Gassmann, O., & Enkel, E. (2004). Towards a Theory of Open Innovation : Three Core Process Archetypes. In R&D Management Conference (RADMA) (pp. 1–18). Lisbon, Portugal.
Gassmann, O., Enkel, E., & Chesbrough, H. (2010). The future of open innovation. R&D Management, 40(3), 213–221.
Gassmann, O., Wolff, T., & Stahl, M. (2004). The Cross Industry Innovation Process: Opening up R&D in the Automotive Industry. In R&D Management Conference (RADMA). Lisbon, Portugal.
Geiger, D. (2009). Revisiting the Concept of Practice: Toward an Argumentative Understanding of Practicing. Management Learning, 40(2), 129–144.
Gherardi, S. (2000). Practice-Based Theorizing on Learning and Knowing in Organizations. Organization, 7(2), 211–223.
References
115
Giannopoulou, E., Yström, A., Ollila, S., Fredberg, T., & Elmquist, M. (2010). Implications of Openness : A Study into ( All ) the Growing Literature on Open Innovation. Journal of Technology Management & Innovation, 5(3), 162–180.
Graf, P., & Braun, A. (2013). A policy perspective on open innovation - the Mexican case. International Journal of Entrepreneurship and Innovation Management, 17(4/5/6), 296.
Grundström, C., Sjöström, R., & Öhrwall Rönnbäck, A. (2013). Manufacturing SMEs and Open Innovation – findings from Sweden. In The 6th ISPIM Innovation Symposium (pp. 1–18). Melbourne, Australia.
Grunert, K. G., Jensen, B. B., Sonne, A. M., Brunsø, K., Byrne, D. V., Clausen, C., … Scholderer, J. (2008). User-oriented innovation in the food sector: relevant streams of research and an agenda for future work. Trends in Food Science and Technology, 19(11), 590–602.
Gürtler, M. R., Lewandowski, P., Klaedtke, K., & Lindemann, U. (2013). Can Stakeholder-Analysis support Open Innovation? In The 6th ISPIM Innovation Symposium – Innovation in the Asian Century (p. 14). Melbourne, Australia.
Gürtler, M. R., & Lindemann, U. (2013). Situative open innovation – A model for selecting the right external actors and involving them in an efficient way. In Proceedings of the 19th International Conference on Engineering Design (ICED13) Design For Harmonies (pp. 19–22). Seoul, Korea.
Gwynne, P. (2007). Open Innovation’s Promise and Perils. Research Technology Management. Hair, J. F., Hult, G. T. oma. M., Ringle, C. M., & Sarstedt, M. (2014). A Primer on Partial
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–151.
Hakkim, R. P., & Heidrick, T. R. (2008). Open Innovation in the Energy Sector. In PICMET 2008 Proceedings (pp. 565–571). Cape Town, South Africa.
Harzing, A. W. (2007). Publish or Perish. Hatzichronoglou, T. (1997). Revision of the High-Technology Sector and Product
Classification (No. 1997/02). He, Z. L., & Wong, P. K. (2004). Exploration vs. Exploitation: An Empirical Test of the
Ambidexterity Hypothesis. Organization Science, 15(4), 481–494. Hemert, P., Nijkamp, P., & Masurel, E. (2013). From innovation to commercialization through
networks and agglomerations; analyses of sources of innovation, innovation capabilities and performance of Dutch SMEs. Annals of Regional Science, 50(2), 425–452.
Hidalgo, A., & Albors, J. (2008). Innovation management techniques and tools: a review from theory and practice. R&D Management, 38(2), 113–127.
Hirsch-Kreinsen, H., & Jacobson, D. (2008). Innovation in Low-tech Firms and Industries. Cheltenham, UK: Edward Elgar Publishing.
The unexpected implications of opening up innovation
116
Hofer, C. W. (1975). Toward a contingency theory of business strategy. Academy of Management Journal, 18(4), 784–810.
Holsapple, C. W., Johnson, L. E., Manakyan, H., & Tanner, J. (1994). Business computing research journals: a normalized citation analysis. Journal of Management Information Systems, 11(2), 131–141.
Huang, F., & Rice, J. (2009). The Role of Absorptive Capacity in Facilitating “Open Innovation” Outcomes: A Study of Australian SMEs in the Manufacturing Sector. International Journal of Innovation Management, 13(2), 201– 220.
Huang, H.-C., Lai, M.-C., Lin, L.-H., & Chen, C.-T. (2013). Overcoming organizational inertia to strengthen business model innovation. An open innovation perspective. Journal of Organizational Change Management, 26(6), 977–1002.
Huizingh, E. (2011). Open innovation: State of the art and future perspectives. Technovation, 31(1), 2–9.
Idrissia, M. O., Amaraa, N., & Landrya, R. (2012). SMEs’ Degree of Openness: The Case of Manufacturing Industries. Journal of Technology Management & Innovation, 7(1), 186–210.
IEA. (2013). Energy Balances of non-OECD Countries. Paris. doi:10.1787/energy_bal_non-oecd-2013-en
Igartua, J. I., Albors-Garrigós, J., & Hervas-oliver, J. L. (2010). How Innovation Management Techniques Support and Open Innovation Strategy. Technology Management, May-June, 41–53.
Ili, S. (2013). Open innovation studies. Retrieved from http://www.ili-consulting.de/en/index.html
Ili, S., Albers, A., & Miller, S. (2010). Open innovation in the automotive industry. R&D Management, 40(3), 246–255.
Isaksson, O., Larsson, T. C., & Öhrwall-Rönnbäck, A. (2009). Development of product-service systems: challenges and opportunities for the manufacturing firm. Journal of Engineering Design, 20(4), 329–348.
Jaspers, F., & van den Ende, J. (2010). Open innovation and systems integration: how and why firms know more than they make. International Journal of Technology Management, 52(3/4), 275.
Jiménez-Barrionuevo, M. M., García-Morales, V. J., & Molina, L. M. (2011). Validation of an instrument to measure absorptive capacity. Technovation, 31(5-6), 190–202.
Johannessen, J.-A. (2009). A systemic approach to innovation: the interactive innovation model. Kybernetes, 38(1/2), 158–176.
Johnson, M. W. (2010). Seizing the white space: business model innovation for growth and renewal. Boston, MA: Harvard Business Press.
Karakaya, E., Hidalgo, A., & Nuur, C. (2014). Diffusion of eco-innovations: A review. Renewable and Sustainable Energy Reviews, 33, 392–399.
References
117
Karlsson, C., & Sköld, M. (2013). Forms of innovation openness in global automotive groups. International Journal of Automotive Technology and Management, 13(1), 1–17.
Kast, F. E., & Rosenzweig, J. E. (1972). General System Theory: Applications for Organization and Management. Academy of Management Journal, 15(4), 447–465.
Kathan, W., Hutter, K., Füller, J., & Hautz, J. (2015). Reciprocity vs. Free-Riding in Innovation Contest Communities. Creativity and Innovation Management, 24(3), 537–549.
Katkalo, V. S., Pitelis, C. N., & Teece, D. J. (2010). Introduction: On the nature and scope of dynamic capabilities. Industrial and Corporate Change, 19(4), 1175–1186.
Katz, R., & Allen, T. J. (1982). Investigating the not- invented-here (NIH) syndrome: A look at performance, tenure and communication patterns of 50 R&D project groups. R&D Management, 12(1), 7–19.
Katzy, B., Turgut, E., & Holzmann, T. (2013). Innovation intermediaries: a process view on open innovation coordination. Technology Analysis & Strategic Management, 25(3), 295–309.
Kaulich, F. (2012). Diversification vs. specialization as alternative strategies for economic development: Can we settle a debate by looking at the empirical evidence? Vienna.
Kaulio, M. A. (1998). Customer, consumer and user involvement in product development: A framework and a review of selected methods. Total Quality Management, 9(1), 141–149.
Keupp, M. M., & Gassmann, O. (2009). Determinants and archetype users of open innovation. R&D Management, 39(4), 331–341.
Kim, H., & Park, Y. (2010). The effects of open innovation activity on performance of SMEs: the case of Korea. International Journal of Technology Management, 52(3), 236–256.
Kim, N., Kim, D.-J., & Lee, S. (2015). Antecedents of open innovation at the project level: empirical analysis of Korean firms. R&D Management, 45(5), 411–439.
Kline, S. J., & Rosenberg, N. (1986). An Overview of Innovation. In R. Landau & N. Rosenberg (Eds.), The Positive Sum Strategy: Harnessing Technology for Economic Growth (pp. 275–305). Washington, D.C.: National Academies Press.
Koberg, D., & Bagnall, J. (1981). The all new universal traveler: A soft-systems guide to creativity, problem-solving, and the process of reaching goals. Los Altos, CA: W. Kaufmann.
Kuhn, T. S. (1963). The Structure of Scientific Revolutions. Chicago: The University of Chicago Press.
Langdon, D., & Lehrman, R. (2012). The Benefits of Manufacturing Jobs. Langner, B., & Seidel, V. P. (2014). Sustaining the Flow of External Ideas: The Role of Dual
Social Identity across Communities and Organizations. Journal of Product Innovation Management, In Press, 32(4), 522–538.
Laursen, K., & Salter, A. (2005). The Paradox of “Openness”, in Appropriability and the Use of External Sources of Knowledge for Innovation. In Academy of Management Conference (p. 23). Honolulu, Hawaii, USA.
The unexpected implications of opening up innovation
118
Laursen, K., & Salter, A. (2006). Open for innovation: the role of openness in explaining innovation performance among U.K. manufacturing firms. Strategic Management Journal, 27(2), 131–150.
Laursen, K., & Salter, A. J. (2014). The paradox of openness: Appropriability, external search and collaboration. Research Policy, 43(5), 867–878.
Lawrence, P. R., & Lorsch, J. W. (1967). Organization and environment: managing differentiation and integration. Boston, MA: Harvard University Press.
Lazzarotti, V., & Manzini, R. (2009). Different Modes of Open Innovation: a Theoretical Framework and an Empirical Study. International Journal of Innovation Management, 13(04), 615–636.
Lazzarotti, V., Manzini, R., Nosella, A., & Pellegrini, L. (2015). Collaborations with Scientific Partners: The Mediating Role of the Social Context in Fostering Innovation Performance. Creativity and Innovation Management, n/a–n/a. doi:10.1111/caim.12158
Lazzarotti, V., Manzini, R., & Pellegrini, L. (2010). Open innovation models adopted in practice: an extensive study in Italy. Measuring Business Excellence, 14(4), 11–23.
Lazzarotti, V., Manzini, R., & Pellegrini, L. (2011). Contextual factors and open innovation: are there contradictory or yet little investigated propositions? International Journal of Innovation and Regional Development, 3(5), 486–514.
Lazzarotti, V., Manzini, R., & Pellegrini, L. (2011). Firm-specific factors and the openness degree: a survey of Italian firms. European Journal of Innovation Management, 14(4), 412–434.
Lazzarotti, V., Manzini, R., & Pellegrini, L. (2015). Is your open-innovation successful? The mediating role of a firm’s organizational and social context. The International Journal of Human Resource Management, 26(19), 2453–2485.
Lazzarotti, V., Manzini, R., Pellegrini, L., & Pizzurno, E. (2013). Open Innovation in the automotive industry: Why and How? Evidence from a multiple case study. International Journal of Technology Intelligence and Planning, 9(1), 37–56.
Lazzarotti, V., Manzini, R., & Pizzurno, E. (2012). Setting up Innovation Networks: The Case of a Small Company in the Calibration Industry. Asia Pacific Management Review, 17(3), 281–300.
Lee, S., Park, G., Yoon, B., & Park, J. (2010). Open innovation in SMEs-An intermediated network model. Research Policy, 39(2), 290–300.
Liao, Y., & Barnes, J. (2015). Knowledge acquisition and product innovation flexibility in SMEs. Business Process Management Journal, 21(6), 1257 – 1278.
Lichtenthaler, U. (2011). Open innovation: Past Research, Current Debates, and Future Directions. Academy of Management Perspectives, 25(1), 75–93.
Lichtenthaler, U., & Lichtenthaler, E. (2009). A Capability-Based Framework for Open Innovation: Complementing Absorptive Capacity. Journal of Management Studies, 46(8), 1315–1338.
References
119
Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, 57(2), 123–146.
Luthans, F. (1973). The contingency theory of management. Business Horizons, 16(3), 67–72. Lutzenhiser, L. (1994). Innovation and organizational networks: Barriers to energy efficiency
in the US housing industry. Energy Policy, 22(10), 867–876. Maital, S., & Seshadri, D. V. R. (2012). Innovation Management: Strategies, Concepts and
Tools for Growth and Profit. (Sage Publications Ltd, Ed.) (2nd ed.). New Delhi. Manzini, R., Lazzarotti, V., Pellegrini, L., Bengtsson, L., Lakemond, N., Tell, F., … Sanchez,
M. (2013). Are We Actually in the Open Innovation Era? Current Practices of European Manufacturing Companies. In 14th International Continuous Innovation Network (CINet) Conference “Business Development and Co-Creation” (pp. 592–614). Nijmegen, Netherlands.
March, J. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.
Mariano, S., & Casey, A. (2015). Is organizational innovation always a good thing? Management Learning, 46(5), 530–545.
Marinova, D., & Phillimore, J. (2003). Models of innovation. In L. V. Shavinina (Ed.), The international handbook on innovation (pp. 44–53). Oxford, UK: Elsevier Science Ltd.
Markillie, P. (2012). A third industrial revolution. The Economist, 1–5. Martini, A., Aloini, D., & Neirotti, P. (2012). Degree of Openness and Performance in the
Search for Innovation. International Journal of Engineering Business Management, 4(37), 1–15.
Mauborgne, R., & Kim, C. W. (2004). Blue Ocean Strategy. Harvard Business Review, 82(10), 76–84.
May, G., Stahl, B., & Taisch, M. (2016). Energy management in manufacturing: Toward eco-factories of the future – A focus group study. Applied Energy, 164, 628–638.
Mayring, P. (2000). Qualitative Content Analysis. Forum: Qualitative Social Research, 1(2). Mazzola, E., Bruccoleri, M., & Perrone, G. (2012). The effect of inbound, outbound and
coupled innovation on performance. International Journal of Innovation Management, 16(6), 27.
McGrath, J. (1982). Dilemmatics: the study of research choices and dilemmas. In J. McGrath, J. Martin, & R. Kulka (Eds.), Judgement Calls for Research (pp. 69–102). Beverly Hills: Sage Publications.
McLaren, R. B. (1993). The dark side of creativity. Creativity Research Journal, 6(2), 137–144.
Merriam-Webster Inc. (2004). Merriam-Webster’s collegiate dictionary. Springfield, MA: Merriam-Webster.
Mertens, D. M. (1998). Research methods in education and psychology: Integrating diversity with quantitative & qualitative approaches. Thousand Oaks, CA: Sage Publications.
The unexpected implications of opening up innovation
120
Michelino, F., Caputo, M., Cammarano, A., & Lamberti, E. (2014). Inbound and Outbound Open Innovation: Organization and Performances. Journal of Technology Management & Innovation, 9(3), 65–82.
Minshall, T., Mortara, L., Elia, S., & Probert, D. (2008). Development of practitioner guidelines for partnerships between start-ups and large firms. Journal of Manufacturing Technology Management, 19(3), 391–406.
Mintzberg, H. (1979). The Structuring of Organizations: A Synthesis of the Research. Prentice Hall.
Miterev, M., Engwall, M., & Jerbrant, A. (2015). Exploring program management competences for various program types. International Journal of Project Management. doi:10.1016/j.ijproman.2015.07.006
Morais, R. (2010). Scientific Method. In A. Mills, G. Durepos, & W. E. (Eds.), Encyclopedia of Case Study Research (pp. 840–846). Thousand Oaks, CA: Sage Publications.
Morais, R., Martins, C., & Kansikas, J. (2009). Analysis of research ideas: Combining metaphors for research. In Proceedings of the XX ISPIM Conference: The Future of Innovation (p. 12). Vienna.
Mothe, C., & Thi, T. U. N. (2010). The link between non-technological innovations and technological innovation. European Journal of Innovation Management, 13(3), 313–332.
Muñoz-Gutierrez, R. (2014). Innovación a la Mexicana: Más alla de romper paradigmas. México City, Mexico: Penguin Random House.
Nascimento Souto, P. C. (2014). Innovating as sense-making conversations: enhancing the quality of conversations to potentiate knowledge creation and the communicative-access to experts’ tacit knowledge. International Journal of Innovation and Learning, 16(2), 113–150.
Nelson, R., & Winter, S. (1982). An evolutionary theory of economic change. Cambridge, MA: Harvard University Press.
Neyer, A. K., Bullinger, A. C., & Moeslein, K. M. (2009). Integrating inside and outside innovators: a sociotechnical systems perspective. R&D Management, 39(4), 410–419.
Nicolini, D., Gherardi, S., & Yanow, D. (2003). Knowing in organizations: A practice-based approach. New York, NY.: M.E. Sharpe, Inc.
Nitzsche, P., Wirtz, B. W., & Göttel, V. (2015). Innovation Success in the Context of Inbound Open Innovation. International Journal of Innovation Management, 1650025. doi:10.1142/S1363919616500250
Nordström, K. A., & Schlingmann, P. (2014). Urban express. Stockholm: Forum bokförlag. O’Reilly III, C. A., & Tushman, M. L. (2008). Ambidexterity as a dynamic capability:
resolving the innovator’s dilemma. Research in Organizational Behavior, 28, 185–206. OECD. (2005). Oslo Manual: Guidelines for collecting and interpreting innovation data.
(Organisation for Economic Co-operation and Development, Ed.) (3rd Editio.). Paris: OECD publishing.
References
121
OECD. (2008a). Empirical Measures of Open Innovation. In K. De Backer, M. Cervantes, & E. van de Velde (Eds.), Open Innovation in Global Networks (pp. 49–75). Paris: OECD Publishing.
OECD. (2008b). Sustainable manufacturing and eco-innovation: First steps in building a common analytical framework. Paris.
OECD. (2014). Measuring the Digital Economy: A new perspective. OECD publishing. OECD. (2015). Manufacturing or services?: That is not the Question. Oh, J., & Rhee, S. K. (2010). Influences of supplier capabilities and collaboration in new car
development on competitive advantage of carmakers. Management Decision, 48(5), 756 – 774.
Okasha, S. (2002). Philosophy of Science: A Very Short Introduction. Oxford, UK: Oxford University Press.
Ollila, S., & Yström, A. (2013). Anything goes? Characterizing open innovation collaboration in empirical research. In The 6th ISPIM Innovation Symposium – Innovation in the Asian Century (pp. 1–21).
Ollila, S., & Yström, A. (2016). An investigation into the roles of open innovation collaboration managers. R&D Management, n/a–n/a. doi:10.1111/radm.12197
Olsen, N. V. (2015). Design Thinking and food innovation. Trends in Food Science & Technology, 41(2), 182–187.
Ortt, J. R., & van der Duin, P. A. (2008). The evolution of innovation management towards contextual innovation. European Journal of Innovation Management, 11(4), 522–538.
Osborn, A. F. (1942). How to think up. New York, NY.: MacGraw-Hill. Osterwalder, A. (2004). The Business Model Ontology - A Proposition In A Design Science
Approach. University of Lausanne. Padilla-Meléndez, A., Del Aguila-Obra, A. R., & Lockett, N. (2013). Shifting sands: Regional
perspectives on the role of social capital in supporting open innovation through knowledge transfer and exchange with small and medium-sized enterprises. Nternational Small Business Journal, 31(3), 296–318.
Pallant, J. (2011). SPSS survival manual (4th ed.). Sydney: Allen & Unwin. Palmié, M., Zeschky, M., Winterhalter, S., Sauter, P. W., Haefner, N., & Gassmann, O. (2015).
Coordination mechanisms for international innovation in SMEs: effects on time-to-market and R&D task complexity as a moderator. Small Business Economics.
Parida, V., Johansson, C., & Larsson, T. C. (2009). Implementation of Open Innovation Practices in Swedish Manufacturing Industry. In International Conference on Engineering Design, ICED’09.
Parida, V., Larsson, T., Isaksson, 0., & Oghazi, P. (2011). Towards open innovation practices in aerospace industry: challenges and opportunities. In 3rd International Conference on Research into Design, ICoRD’11. Bangalore, India.
The unexpected implications of opening up innovation
122
Parida, V., Westerberg, M., & Frishammar, J. (2012). Inbound Open Innovation Activities in High-Tech SMEs: The Impact on Innovation Performance. Journal of Small Business Management, 50(2), 283–309.
Paskaleva, K. A. (2011). The smart city: A nexus for open innovation? Intelligent Buildings International, 3(3), 153–171.
Pavitt, K. (1984). Sectoral patterns of technical change: Towards a taxonomy and a theory. Research Policy, 13(6), 343–373.
Pavitt, K. (2004). Innovation Processes. In The Oxford Handbook of Innovation (p. 656). Oxford, UK: Oxford University Press.
Penrose, E. T. (1959). The Theory of the Growth of the Firm. Oxford: Blackwell. Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Broström, A., D’Este, P., … Sobrero, M.
(2013). Academic engagement and commercialisation: A review of the literature on university–industry relations. Research Policy, 42(2), 423–442. Retrieved from http://linkinghub.elsevier.com/retrieve/pii/S0048733312002235
Pink, D. H. (2009). Drive: The Surprising Truth About What Motivates Us. New York: Penguin Book Inc.
Pisano, G. P. (2015). You need an innovation strategy. Harvard Business Review, 93(6), 44–54.
Pisano, G. P., & Verganti, R. (2008). Which kind of collaboration is right for you? Harvard Business Review, 86(12), 78–86.
Podmetina, D., & Smirnova, M. (2013). R&D Cooperation with External Partners and Implementing Open Innovation. Journal of Innovation Management, 1(2), 103–124.
Pullen, A. J. J., Weerd-Nederhof, P. C., Goren, A. J., & Fisscher, O. A. M. (2012). Open Innovation in Practice: Goal Complementarity and Closed NPD Network to Explain Differences in Innovation Performance for SMEs in the Medical Devices Sector. Journal of Product Innovation Management, 29(6), 917–934.
Ragatz, G. L., Handfield, R. B., & Scannell, T. V. (1997). Success factors for integrating suppliers into new product development. Journal of Product Innovation Management, 14(3), 190–202.
Rahman, H., & Ramos, I. (2013). Challenges in Adopting Open Innovation Strategies in SMEs: An Exploratory Study in Portugal. Issues in Informing Science and Information Technology, 10, 431–448.
Ramirez-Portilla, A. (2015). Which one goes well with? Exploring the Link between Theoretical Perspectives and Research Contexts in Open Innovation Research. Procedia - Social and Behavioral Sciences, Forthcoming, 213, 1034–1039.
Ramirez-Portilla, A., Cagno, E., & Brown, T. (2014). Open Innovation Practices in SMEs: The case of the Mexican supercar VUHL. In The IV Symposium CONACyT fellows in Europe (p. 11). Strasbourg, France.
Ran, B. (2013). The Dark Side of Technological Innovation. Charlotte, NC: Information Age Publishing.
References
123
Randhawa, K., Wilden, R., & Hohberger, J. (2014). Reviewing Open Innovation: Structure, Content and Future Research Avenues. In DRUID Society Conference 2014 (p. 37). Copenhagen.
Richardson, G. (1972). The organization of industry. The Journal, 82(327), 883–896. Riguelle, F., & Van Caillie, D. (2010). Toward a Taxonomy of Key Success Factors for SME ’
s in a Changing Environment: The case of the Luxury Industry. In The 12th IAMB Conference (p. 10).
Robertson, P., Smith, K., & Tunzelmann, N. von. (2009). Innovation in low- and medium-technology industries. Research Policy, 38, 441–446.
Robson, C. (2002). Real world research: a resource for social scientists and practitioner-researchers (2nd Ed.). Oxford: Blackwell.
Rogers, E. M. (1962). Diffusion of innovations. In Diffusion of innovations (1st ed.). New York, NY.: The Free Press.
Romijn, H., & Albu, M. (2002). Innovation, networking and proximity: lessons from small high technology firms in the UK. Regional Studies, 35(1), 81–86.
Rosell, D. T., & Lakemond, N. (2012). Collaborative innovation with suppliers – A conceptual model for characterizing supplier contributions to NPD. International Journal of Technology Intelligence and Planning, 8(2), 197–214.
Rothwell, R. (1992). Successful industrial innovation: critical factors for the 1990s. R&D Management, 22(3), 221–240.
Russo-Spena, T., & Mele, C. (2012). “Five Co-s” in innovating: a practice-based view. Journal of Service Management, 23(4), 523–553.
Sadeghi, M. E., & Sadabadi, A. A. (2015). Evaluating Science Parks Capacity to Create Competitive Advantages. International Journal of Innovation and Technology Management, 12(06), 1550031.
Salmelin, B. (Ed.). (2013). Open Innovation 2.0 Yearbook 2013. Luxemburg: Luxembourg Publication Office of the European Union.
Salmelin, B. (Ed.). (2015). Open Innovation 2.0 Yearbook 2015. Luxemburg: Luxembourg Publication Office of the European Union.
Salter, A., Wal, a T. Ter, Criscuolo, P., & Alexy, O. (2014). Open for Ideation: Individual-level Openness and Idea Generation in R&D. Journal of Product Innovation Management, In press, 17.
Santamaría, L., Nieto, M. J., & Barge-Gil, A. (2009). Beyond formal R&D : Taking advantage of other sources of innovation in low- and medium-technology industries. Research Policy, 38, 507–517.
Santonen, T., Kaivo-oja, J., & Suomala, J. (2007). Introduction to National Open Innovation System ( NOIS ) Paradigm: A Preliminary Concept for Interchange. Turku.
Sarstedt, M., Henseler, J., & Ringle, C. M. (2011). Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results. In Measurement and Research Methods in International Marketing (Vol. 22, pp. 195–218).
The unexpected implications of opening up innovation
124
Sassmannshausen, S. P., & Gladbach, S. (2011). How to Jump Start PhD Thesis in Entrepreneurship Research: A Practical Heuristic for PhD Instructors and Students. In Proceedings of the 8th AGSE International Entrepreneurship Research Exchange (pp. 1131–1145).
Saunders, M., Lewis, P., & Thornhill, A. (2003). Research Methods for Business students (3rd Ed.). Essex: Pearson Education Limited.
Schaffers, H., Komninos, N., Pallot, M., Trousse, B., Nilsson, M., & Oliveira, A. (2011). Smart Cities and the Future Internet: Towards Cooperation Frameworks for Open Innovation. In J. Domingue (Ed.), Future Internet Assembly (pp. 431–446). London, UK: Springer.
Schroll, A., & Mild, A. (2011). Open innovation modes and the role of internal R&D: An empirical study on open innovation adoption in Europe. European Journal of Innovation Management, 14(4), 475–495.
Schroll, A., & Mild, A. (2012). A critical review of empirical research on open innovation adoption. Journal Für Betriebswirtschaft, 62(2), 85–118.
Schumpeter, J. (1947). Capitalism, socialism and democracy. New York: Harper & Row. Seidel, J. V. (1998). Qualitative Data Analysis. Qualis Research. Retrieved from
http://www.scribd.com/doc/7129360/Seidel-1998-Qualitative-Data-Analysis Sierzchula, W., Bakker, S., Maat, K., & Wee, B. Van. (2015). Alliance Formation in the
Automobile Sector during an Era of Ferment. Creativity and Innovation Management, 24(1), 109–122.
Slowinski, G., & Sagal., M. W. (2010). Good practices in open innovation. Research-Technology Management, 53(5), 38–45.
Smith, G. F. (1998). Idea-Generation Techniques: A Formulary of Active Ingredients. The Journal of Creative Behavior, 32(2), 107–134.
Smith, H. L., Dickson, K., & Smith., S. (1991). There are two sides to every story’: Innovation and collaboration within networks of large and small firms. Research Policy, 20(5), 457–468.
Smith, K. (2004). Measuring Innovation. In J. Fagerberg, D. C. Mowery, & R. R. Nelson (Eds.), The Oxford Handbook of Innovation (p. 656). Oxford, UK: Oxford University Press.
Smith, M. J. (1984). Contingency rules theory, context, and compliance behaviors. Human Communication Research, 10(4), 489–512.
Spithoven, A. (2013). Open innovation practices and innovative performances: an international comparative perspective. International Journal of Technology Management, 62(1), 34.
Spithoven, A., Clarysse, B., & Knockaert, M. (2010). Building absorptive capacity to organize inbound open innovation in traditional industries. Technovation, 30(1), 130–141.
Spithoven, A., Vanhaverbeke, W. Roijakkers, N. (2012). Open innovation practices in SMEs and large enterprises. Small Business Economics, 41(3), 537–562.
References
125
Stefan, I., & Bengtsson, L. (2014). Appropriability mechanisms, openness and firm performance. In 1st World Open Innovation Conference (pp. 1–30). Napa, CA.
Storey, C., & Kahn, K. B. (2010). The Role of Knowledge Management Strategies and Task Knowledge in Stimulating Service Innovation. Journal of Service Research, 13(4), 397–410.
Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Grounded theory, procedures and techniques. (Sage, Ed.). Newbury Park, CA.
Suh, Y., & Kim, M.-S. (2012). Effects of SME collaboration on R&D in the service sector in open innovation. Nnovation: Management, Policy & Practice, 14(3), 349–362.
Tashakkori, A., & Teddlie, C. B. (2003). Handbook of Mixed Methods in Social and Behavioural Research. Thousand Oaks, CA: Sage Publications.
Teece, D. (2006). Foreword. In H. Chesbrough, W. Vanhaverbeke, & J. West (Eds.), Open innovation: Reseaching a new paradigm (p. 372). Oxford, UK: Oxford University Press.
Teece, D. J. (2007). Explicating Dynamic Capabilities: The Nature and Microfoundations of (Sustainable) Enterprise Performance. Strategic Management Journal, 28(13), 1319–1350.
Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.
Teirlinck, P., & Spithoven, A. (2013). Research collaboration and R&D outsourcing: Different R&D personnel requirements in SMEs. Technovation, 33(4/5), 142–153.
The Institute for Industrial Productivity. (2013). Industrial Efficiency Policy Database. Retrieved from http://iepd.iipnetwork.org
Theyel, N. (2013). Extending open innovation throughout the value chain by small and medium-sized manufacturers. International Small Business Journal, 31(3), 256–274.
Thurow, L. C. (1996). The future of capitalism: How today’s economic forces shape tomorrow's world. London: Nicholas Brealey.
Tidd, J. (2013). Open Innovation Research, Management and Practice. Hackensack, NJ: World Scientific.
Tidd, J. (2014). Introduction: Why We Need a Tighter Theory and More Critical Research on Open Innovation. In J. Tidd (Ed.), Open Innovation Research, Management and Practice. Hackensack, NJ: World Scientific.
Tidd, J., & Bessant, J. (2014). Managing innovation: integrating technological, market and organizational change (5th editio.). Chichester: John Wiley & Sons.
Tidd, J., Pavitt, K., & Bessant, J. (2001). Managing innovation. Chichester: Wiley. Tranekjer, T. L., & Knudsen, M. P. (2012). The (Unknown) Providers to Other Firms’ New
Product Development: What’s in it for Them? Journal of Product Innovation Management, 29(6), 986–999.
Tranekjer, T. L., & Søndergaard, H. A. (2013). Sources of innovation, their combinations and strengths – benefits at the NPD level. International Journal of Technology Management, 61(3/4), 205–236.
The unexpected implications of opening up innovation
126
Trianni, A., Cagno, E., & Worrell, E. (2013). Innovation and adoption of energy efficient technologies: An exploratory analysis of Italian primary metal manufacturing SMEs. Energy Policy, 61, 430–440.
Trott, P., & Hartmann, D. (2009). Why “Open Innovation” is old wine in new bottles. International Journal of Innovation Management, 13(4), 715–736.
Tushman, M., Lakhani, K. R., & Lifshitz-Assaf, H. (2012). Open Innovation and Organization Design. Journal of Organization Design, 1(1), 24–27.
UNIDO. (2010). Global Industrial Energy Efficiency Benchmarking: An Energy Policy Tool. Vienna.
Utterback, J. M. (1994). Mastering the Dynamics of Product Innovation: How Companies Can Seize Opportunities in the Face of Technological Change (Vol. 44). Boston, MA: Harvard Business School Press.
Vallistu, J. (2013). The Digitized Manufacturing – A Revolution Waiting to Happen. Oslo. van Beers, C., Kleinknecht, A., Ortt, R., & Verburg, R. (2008). Determinants of innovative
behaviour: a firm’s internal practices and its external environment. New York, NY.: Palgrave Macmillan.
Van de Ven, A., Polley, D., Garud, R., & Venkataraman, S. (1999). The innovation journey. Oxford, UK: Oxford University Press.
van de Vrande, V., de Jong, J. P. J., Vanhaverbeke, W., & de Rochemont, M. (2009). Open innovation in SMEs: Trends, motives and management challenges. Technovation, 29(6-7), 423–437.
van de Vrande, V., Vanhaverbeke, W., & Gassmann, O. (2010). Broadening the scope of open innovation: past research, current state and future directions. International Journal of Technology Management, 52(3/4), 221–235.
van der Meer, H. (2007). Open Innovation; The Dutch Treat: Challenges in Thinking in Business Models. Creativity and Innovation Management, 16(2), 192–202.
VanGundy, A. B. (1992). Idea power: Techniques & resources to unleash the creativity in your organization. New York, NY.: American Management Association.
Vanhaverbeke, W. (2006). The Interorganizational Context of Open Innovation. In H. W. Chesbrough, W. Vanhaverbeke, & J. West (Eds.), Open innovation : researching a new paradigm. Oxford: Oxford University Press.
Vanhaverbeke, W., & Cloodt, M. (2006). Open Innovation in Value Networks. In H. W. Chesbrough, W. Vanhaverbeke, & J. West (Eds.), Open innovation: Researching a new paradigm. Oxford: Oxford University Press.
Vanhaverbeke, W., & Cloodt, M. (2014). Theories of the firm and open innovation. In H. Chesbrough, W. Vanhaverbeke, & J. West (Eds.), New Frontiers in Open Innovation (pp. 256–278). Oxford, UK: Oxford University Press.
Vanhaverbeke, W., Vermeersch, I., & Zutter, S. De. (2012). Open Innovation in SMEs: How can small companies and start-ups benefit from open innovation strategies? Flanders, Belgium.
References
127
Verheugen, G. (2003). The new SME definition: User guide and model declaration. Official Journal of the European Union, 51.
Vij, S., & Bedi, H. S. (2015). Effect of organisational and environmental factors on innovativeness and business performance relationship. International Journal of Innovation Management, 20(3), 1650037.
von Hippel, E. (1986). Lead users: a source of novel product concepts. Management Science, 32(7), 791–805.
von Hippel, E. (2005). Democratizing Innovation. London: The MIT Press. von Saucken, C., Gürtler, M., Schneider, M., & Lindemann, U. (2015). A method model for
distinguishing and selecting open innovation methods. In Proceedings of the 20th International Conference on Engineering Design (ICED15), (p. 10). Milan, Italy.
Vroom, V. H., & Yetton, P. W. (1973). Leadership and decision-making. Pittsburgh: University of Pittsburgh Press.
Weill, P., & Olson, M. H. (1989). An Assessment of the Contingency Theory of Management Information Systems. Journal of Management Information Systems, 6(1), 59–85.
Wen, J., & Kobayashi, S. (2001). Exploring collaborative R&D network: some new evidence in Japan. Research Policy, 30(8), 1309–1319.
Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), 171–180.
West, A. (2002). Innovation Strategy. Madrid: Fundación Cotec para la Innovación Tecnológica.
West, J., & Bogers, M. (2013). Leveraging External Sources of Innovation: A Review of Research on Open Innovation. Journal of Product Innovation Management, 31(4), 1–18.
West, J., & Gallagher, S. (2006). Challenges of Open Innovation: The Paradox of Firm Investment in Open Source Software. R&D Management, 36(3), 319–331.
West, J., & Lakhani, K. R. (2008). Getting Clear About Communities in Open Innovation. Industry & Innovation, 15(2), 223–231.
West, J., Salter, A., Vanhaverbeke, W., & Chesbrough, H. (2014). Open innovation: The next decade. Research Policy, 43(5), 805–811.
West, J., Vanhaverbeke, W., & Chesbrough, H. (2006). Open Innovation: A research agenda. In H. W. Chesbrough, W. Vanhaverbeke, & W. West (Eds.), Open Innovation, Researching a New Paradigm (pp. 285–307). New York, NY.: Oxford University Press.
Wiio, I. (1978). Contingencies of organizational communication: Studies in organization and organizational communication. Helsinki: Helsinki School of Economics.
Wikhamn, B. R., & Wikhamn, W. (2013). Structuring of the Open Innovation Field. Journal of Technology Management & Innovation, 8(3), 173–185.
Woodward, J. (1958). Management and technology. Indianapolis, Indiana: H. M. Stationery Off.
Wu, Y. (2006). The study on the management theory of intellectual property right on the basis of the open innovation. Studies in Science of Science, 2, 1–26.
The unexpected implications of opening up innovation
128
Wyckoff, A., & Koreen, M. (2010). Making the Most of Open Innovation in Post-Crisis Era. Economy, Culture & History Japan Spotlight, 29(1), 6–9.
Xiaobao, P., Wei, S., & Yuzhen, D. (2013). Framework of open innovation in SMEs in an emerging economy: firm characteristics, network openness, and network information. International Journal of Technology Management, 62(2/3/4), 223–250.
Yan, T., Azadegan, A., & Oke, A. (2014). A Knowledge Management View of Open Innovation Strategies. Academy of Management Proceedings, 2014(1), 11001.
Yin, R. K. (1994). Case Study Research: Design and Methods (4th Editio.). Thousand Oaks, CA: Sage Publications.
Yun, J., Won, D. K., Hwang, B. Y., Jung, W., & Kim, D.-H. (2013). Exploration of the Effects of Open Innovation Policies on National Innovation Systems through System Dynamics Simulation. In The 31st International Conference of the System Dynamics Society (p. 24). Cambridge, Massachusetts.
Yurdusev, A. N. (1993). “Level of Analysis” and “Unit of analysis”: A Case for Distinction. Journal of International Studies, 22(1), 77–88.
Zapata, C., & Nieuwenhuis, P. (2010). Exploring innovation in the automotive industry: new technologies for cleaner cars. Journal of Cleaner Production, 18(1), 14–20.
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Appendixes
Appendix A – Interview guide for case study of OI projects in the food industry
Introductory information: We are conducting a study to explore the practices that firms use to integrate with other organizations during collaborative innovation projects. The interview will take approximately one hour, and it will have a semi-structure interview format. This means, that you can feel free to elaborate on your answers and also that new questions may arise during the interview. Also, is it okay if we could record this interview? Section A. Innovation in general
1. What are your name, current position, and time working for this organization? 2. What is your experience working with innovation in general? 3. What is your experience working with projects of more open or collaborative
innovation within the organization? 4. Could you please tell us first something about the innovation process in your
organization? How does it take place? 5. How is the interaction between the persons, teams, and stakeholders involved during
the innovation process?
Section B. Integration practices during innovation
6. What are the integration practices more visible in your organization during the innovation process? Please consider as integrations practices the habitual use of specific tools, structures, systems, methods, procedures or techniques allowing better integration with internal and external stakeholders.
7. Do you perceive some integration practices during the innovation process as generic? In other words, could they be used in any type of innovation project?
8. Do you believe the use of appropriate integration practices during innovation projects varies on something? For example, type of actor or innovation?
9. Do you believe there is a difference between the integration practices used inside your organization and the ones used with external actors? Is there a clear and remarked difference? For example, formal or informal.
10. Do you use external agencies as mediators between your organization and the outside innovators?
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Section C. Integration practices during collaborative innovation
11. According to you, what are the integration practices more efficient and effective used during a collaborative innovation project inside the organization (E.g. between different departments)?
12. According to you, what are the integration practices more efficient and effective used during a collaborative innovation project with external actors? (E.g. with other actors such as universities, suppliers, costumers, etc.)
13. Do you think level uncertainty and ambiguousness are among the most relevant factors affecting the decision on which integration practices to use?
14. What are some of the downsides or pitfalls that integration practices in the innovation process can present? For example costs, time consuming, investment.
15. Do you have any recommendations to improve and manage the integration during the innovation process either with internal or external actors?
Section D. Open Innovation practices in general
16. What about Open Innovation, are you aware of this term? (If s/he has not mentioned the term during the interview)
17. Would you be able to define Open Innovation in few words? 18. How often does your organization practice opening the innovation process? 19. Based on the definition of Open Innovation that I just mentioned you, would you say
your organization is currently practicing Open Innovation? 20. Do you believe your organization has adopted more specific practices or initiatives to
enhance open and collaborative innovation in the last five years? 21. If yes, could you please provide some examples? If no, do you know why or could you
provide your opinion on why not?
Interview Control:
Date of the interview:
Place of the interview:
Duration of the interview:
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Appendix B – Interview guide for pilot case studies of small and medium-sized manufacturers of supercars
Purpose: The purpose of this interview guide is twofold. First, the interview guide was designed to collect qualitative data from experts and practitioners of the innovation process in your organization. Second, it was designed to ensure that the main questions are uniformly administered to all the interviewees while providing in advance the type of questions that the interview will cover. Confidentiality clause: The collected data and information will be used only for the purpose of scientific research and treated as confidential. The name of the organization and the interviewees will not be disclosed unless their formal consents. Nevertheless, the analysis and results of this research will be used in academic publications such as a doctoral thesis, academic conferences, and scientific journals. The results will be shared with the firm and interviewees upon completion. Interview questionnaire: This interview questionnaire has 25 questions distributed in 5 sections. The 1st section includes the firm and interviewee´s profile. The 2nd section asks for general information about how the firm manages innovation when designing and manufacturing. Section 3 and 4 include more specific information about the innovation process. Section 5 includes questions about the purpose of this study. Section A. Interviewee and Firm Profile
Interviewee Profile Name of Interviewee
Position
Main duties
Experience (incl. years)
Firm Profile Name of the firm
Annual revenues
Number of employees
Main products/services
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Section B. General management of innovation
1. Based on the core business of the firm, in which type of industry do you consider this firm fits better? E.g. automotive, design, engineering, leisure.
2. Do you think the way of designing and innovating in the automotive industry will radically change in the future or will remain more or less the same?
3. What is your current strategy to manage innovation within your firm? 4. Does innovation results are usually restricted to the boundaries of your firm? 5. Where does innovation usually start inside your firm? For example, from a person,
from an area, from a division, etc. Section C. Outside-in innovation
6. What are other sources of innovation for your firm? 7. Have your firm used as external sources of innovation any of these? If yes, could you
8. Do you believe your firm has gained any type of knowledge through the
integration/cooperation with any of the entities mentioned before? 9. Do you believe your firm has gained INNOVATION knowledge through the
integration/cooperation with any of the entities mentioned before? 10. Does your firm practice any of these strategies? If yes, provide examples.
Alliances / Partnerships Trend and technology Scouting Purchase of technical services Common research laboratory Supplier involvement Online portal for entering ideas Venture investing Online market place Outsourcing services Product exhibition by other firms Licensing-in Venture Capital Announcement of competitions Reverse engineering Learning Journeys Others:
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11. How much does your firm spends on Innovation/R&D per year? (Not only money but
also using other resources) 12. Do you believe it should spend more, less, or use the same amount of resources? 13. Do you think the role of the people in charge of innovating in your firm will need new
competences? For example, better expertise to assess external technologies. Section D. Inside-out innovation
14. Do you commercialize unused innovation (technology) developed in your firm? If
answer is “yes”, could you provide an example? 15. Have your firm being involved with any of these external paths for innovation to
outside their current business? If yes, provide examples.
Competitors Universities Joint Ventures Same industry but other markets Research Centres Suppliers / Subcontractors Other industries Others…
16. If answer is “no”, why is this? Do you believe doing this in your industry is risky or not
profitable? 17. What are the restrictions for transferring innovation, design or technology outside your
firm? 18. Does your firm practice any of these strategies? If yes, provide examples.
Licensing-out Patent sale Alliances Selling other intellectual property Joint Venture Grant-back license Supply of technical services Reciprocal license agreements Consulting Bring ideas to market Personnel exchange Transferring ideas to other places Spin-offs Others:
19. How much does your firm profit on Innovation/R&D per year? (Not only money but
also obtaining other resources) 20. Do you believe is possible for your firm to benefit further by exploiting (more) its
patents, designs or technology?
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Section E. Open Innovation awareness
21. Have you heard before about the concept of Open Innovation and what it involves? 22. If yes, do you think it is applicable to the automotive industry? 23. Do you think it is applicable in your firm? 24. Do you think open innovation practices (like some previously mention during the
interview) could be adopted by carmakers other than large OEMs? If not, why? 25. If your firm could use more open innovation practices (in any degree) would you be
interested or in favour of doing this? Acknowledgement and follow up
• Thank you for your valuable time and for the information provided. Your help is very much appreciated to support academic research projects.
• When we conclude this research project a summary of the results will be provided to you so you can share it with your organization.
• Finally, do you mind if we contact you again in case we need further explanations for some questions?
Interview Control:
Date of the interview:
Place of the interview:
Duration of the interview:
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Appendix C – Questionnaire for case studies of small and medium-sized foundries
Questionnaire: Innovation and Energy Efficiency
Summary: The purpose of this questionnaire is to evaluate the relationship between some specific innovation practices and the energy efficiency level that foundries in Italy could achieve. The questionnaire is divided in 4 main sections and it should be answered in approximately 40 minutes. The researchers that are talking with you will support recording your responses. Thank you for your support.
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Section A. Energy efficiency level Section B. Adoption of energy efficiency technologies
Depending on the following questions please answer with either “Yes” or “No”, or indicating one the three options provided.
I) For the production of Steel
137
II) For the production of Aluminium
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III) For the production of Cast Iron
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Section C. Perception Of Barriers To Energy Efficiency
Depending on the following questions, please answer with either “Yes” or “No”, or by using the following 4 points Likert scale where:
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Section D. Adoption Of Innovation Practices
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Appendix D – Questionnaire for survey of small and medium-sized manufacturers of supercars
Which practices does your company use to innovate? A global survey of small and medium manufacturers of one-of-a-kind vehicles
We would like to invite your company to participate in a survey about the practices used to manage innovation by firms designing and manufacturing one-of-a-kind vehicles. These include vehicles with a great level of design, craftsmanship, performance, innovation or technology. The questionnaire has been carefully designed and should take around 10 minutes to complete. All information provided will be treated as strictly confidential and results will be reported in aggregate only for the entire survey sample. We will be collecting responses until the 17th of May and a couple of weeks later all participants will receive a free summary of the survey results. This survey is addressed to company owners, top management, and key employees involved with the innovation process within the company.
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Section 1. Innovation practices and firm performance 1.1 INTERNAL R&D Q1. What was the total annual revenue for your company during 2014 (in USD)? . Less than $500,000 . Between $500,000 and 2 million . Between $2 and $6 million . Between $6 and $10 million . More than $10 million Q2. Please indicate your annual expenditure in internal R&D as a percentage of your annual revenue.
Q3. Please indicate your agreement with each of the following statements with respect to your firm’s internal R&D practices:
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1.2 OPEN INNOVATION PRACTICES
*Q4. Please indicate your agreement with each of the following statements with respect to other innovation practices within your firm:
Examples of external partners include customers, competitors, research institutes, consultants, suppliers, government, or universities, amongst other stakeholders.
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*Q5. Please indicate the extent to which your firm has used the following stakeholders as collaboration partners for innovation activities: *Q6. In contrast, now please indicate the extent to which your firm has used the same stakeholders as external paths to commercialize and profit from innovations created inside your firm:
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1.3 OPEN INNOVATION MODELS *Q7. Please indicate your agreement with the following: “We collaborate with our partners while they provide us with the following:
*Q8. Please indicate the extent to which your firm has collaborated with external partners in the following phases of the innovation process over the last 5 years:
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Section 2. Other factors in the firm
2.1 MARKET AND TECHNOLOGY TURBULENCE *Q9. Please indicate your agreement with each of the following statements with respect to your firm’s technology and market environment:
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2.2 ENTREPRENEURIAL ORIENTATION
*Q10. Please indicate your agreement with each of the following statements with respect to your firm’s strategy:
2.3 ABSORPTIVE CAPACITY
*Q11. Please indicate to what extent the following statements fit your firm’s capacity to search for information, communicate, process and exploit knowledge:
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Section 3. Performance in the firm 3.1 INOVATIVENESS (PERFORMANCE)
*Q12. Please indicate how well your innovation practices have influenced the following objectives over the last 3 years:
1.2 ENVIRONMENTAL AND SOCIAL PERFORMANCE
*Q13. Please indicate how well your innovation practices have influenced the next aspects of your firm’s performance:
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3.3 ECONOMIC PERFORMANCE *Q14. Please estimate your firm’s economic performance:
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Section 4. General information Q15. Which of the following roles best suits your job position?
• Owner of the company • General Director • Head of R&D • Head of Engineering • Other ____________
*Q16. In which country is your company located? If your company has locations in several countries, please write where is the main facility.
*Q17. What is the number of employees in your company (including full and part-time)?
• Less than 10 • Between 10 and 50 • Between 50 and 250 • More than 250
*Q18. In which year was your company founded?
Q19. Please indicate the industry or sector to which you believe your company belongs. You can choose one or more options.
• Automotive • Motorsport • Luxury • Manufacturing other • Other ____________
Q20. How would you classify the vehicles your company designs and manufactures? You can choose one or more options.
