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University-level mechanisms supportingthe creation of new companies: ananalysis of Italian academic spin-offsAnna Nosella a & Rosa Grimaldi ba Department of Industrial Engineering , DTG, University ofPadova , Str. la San Nicola 3, 36100, Vicenza, Italyb Department of Management , Rosa Grimaldi, CIEG, University ofBologna , Via Saragozza 8, 40123, Bologna, ItalyPublished online: 07 Jul 2009.
To cite this article: Anna Nosella & Rosa Grimaldi (2009) University-level mechanisms supportingthe creation of new companies: an analysis of Italian academic spin-offs, Technology Analysis &Strategic Management, 21:6, 679-698, DOI: 10.1080/09537320903052657
To link to this article: http://dx.doi.org/10.1080/09537320903052657
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Technology Analysis & Strategic ManagementVol. 21, No. 6, August 2009, 679–698
University-level mechanisms supporting thecreation of new companies: an analysis ofItalian academic spin-offs
Anna Nosellaa∗ and Rosa Grimaldib
aDTG, University of Padova, Department of Industrial Engineering, Str. la San Nicola 3, 36100, Vicenza, Italy;bRosa Grimaldi, CIEG, University of Bologna, Department of Management, Via Saragozza 8, 40123, Bologna, Italy
In this paper we address the role of university policies in the creation of academic spin-offs.We focus on university technology transfer units (UTTUs) in Italy and on the mechanismsthey have implemented to support academic entrepreneurship. We gathered data relating totheir strategies for technology transfer and to the mechanisms they had implemented to supportnew venture creation. Results show that the number of people dedicated to technology transferactivities, strong relationships that UTTUs have with external organisations involved in tech-nology transfer activities, and finally support services provided by universities and UTTUshave a significant influence in fostering the generation of new ventures.
Keywords: entrepreneurship; industry–academic relations; science and technology andinnovation policy studies; spin-off companies
1. Introduction
The important role that academic spin-offs play in favouring economic and technological growthhas been widely acknowledged (Birley 2002; Heirman and Clarysse 2004; Grimaldi and Sobrero2005). University spin-offs (Smilor 1990) or academic spin-offs (Nlemvo Ndonzuau, Pirnay, andSurlemont 2002) are firms, whose products or services are based on scientific/technical knowledgegenerated within a university setting (Samson and Gurdon 1993; Steffensen, Roger, and Speakman1999), where the founding members may (or may not) include the academic inventor.
Several studies have addressed the factors that can favour academic development of spin-offs,paying attention to both environmental aspects (such as market structure and technology regime),and university level characteristics (incentives created by universities, organisational supports,technology transfer offices (TTOs), etc.
Among these studies, only a few have focused on the role that networks created by universitieshave on the generation of spin-offs, thus leaving space for investigating further the role thatnetwork size and the strength of relationships – that university technology transfer units (UTTUs)establish with external partners – play in fostering the creation of new companies.
∗Corresponding author. Email: [email protected]
ISSN 0953-7325 print/ISSN 1465-3990 online© 2009 Taylor & FrancisDOI: 10.1080/09537320903052657http://www.informaworld.com
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Moreover, many of the existing studies have focused on the US context, where the academicspin-off phenomenon has been addressed for quite some time. European countries, where this issueis receiving increasing attention, have not been addressed by many studies. Yet, it is importantto assess the results of policies supporting academic start-ups in these countries, by taking intoaccount the peculiarities of the local contexts in order to develop tailored supportive policies (orto fine tune existing ones).
The aim of this paper is to provide an empirical investigation of the role that policies andstrategies, promoted by Italian UTTUs, have in favouring the creation of university spin-offs.These UTTUs include both formal TTOs – organisational units within universities specificallydedicated to technology transfer activities – and other groups of university employees, who takecare of technology transfer related activities, while belonging to research offices or administrativeoffices. In particular, we examined four different stocks of resources put in place by UTTUs inorder to favour the creation of new firms: the stock of technology transfer staff, the stock ofsocial resources, the stock of organisational services provided by the university units in charge oftechnology transfer, and finally other complementary services provided by universities.
We contacted Italian UTTUs and sent them a questionnaire aimed at investigating technologytransfer strategies and the mechanisms that they had implemented. Our final sample is made upof 37 observations.
Results show that the number of people dedicated to technology transfer activities, the strengthof relationships that UTTUs have with external organisations involved in technology transferactivities and finally the support services provided by universities and UTTUs have a significantinfluence in fostering the generation of new ventures from universities.
This paper makes two contributions to the burgeoning literature on technology transfer: firstwe explore the role of university relationships with external partners in fostering new venturecreation; second, we provide empirical evidence of the efficacy of policies supporting academicstart-ups in Italy, a country which, at the time of writing, has started investing in the creation ofconditions supporting academic entrepreneurship.
The paper is organised as follows. First, we discuss the importance of recent changes in theEuropean context and compare technology transfer policies implemented by European countriesto those of the USA; in the third section we analyse the literature on the factors influencingthe creation of university spin-offs in order to formulate the research hypotheses. In the fourthsection we present the methodology, describe the sample and the operationalisation of variables.In the last two sections, we present and discuss the results, and conclude by presenting the policyimplications that emerge from the research study and major issues for future research.
2. An overview of European and US university technology transfer policies
2.1. Entrepreneurial attitude at universities
Following the successful experience of US universities at the time of writing, many Europeanuniversities have been investing in the creation of conditions within their organisations to com-mercialise their research results successfully. Much emphasis has been given to achieving thisgoal and in many universities, TTOs have been created with the aim of promoting technologytransfer activities.
This more ‘outward looking’ orientation on the part of universities has two main explanations(Pirnay, Surlemont, and Nlemvo 2003; Cesaroni et al. 2005; Chiesa and Piccaluga 2000). First,there has been increasing social pressure on universities to play a proactive part in supporting
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University-level Mechanisms Supporting the Creation of New Companies 681
regional economic development by local government. Economies aiming at developing a compar-ative advantage based on the enhancement and exploitation of the national knowledge base mustlook to foster university-based entrepreneurship as a central component of their strategy (O’Sheaet al. 2005). With the drive to generate knowledge based employment opportunities, policy makersare now placing a greater emphasis on the role of universities in the commercialisation of scientificand technological knowledge produced within research laboratories (O’Shea et al. 2005).
Second, there has been a decrease in public funding, which have stimulated many Europeanuniversities to find other sources of financing, some of them coming from the academic start-up.In fact, new sources of revenues are attached to the royalties of technologies licensed to academicstart-ups, to the possible sale of shares during different rounds of financing or IPOs, to researchcontracts coming from the start-up to support its growth, to the donations coming from alumniwhose ventures finally succeeded in the market. Such revenues can then be pooled at the centraladministration level to support additional research activities, hire research assistants, organise (andparticipate in) events, build and remodel laboratories, acquire new infrastructure, or be channelleddirectly to specific units, such as departments or research centres.
Another form of pay-off is the contribution of these activities to enhancing the attractiveness ofstudying in the university, thus increasing the opportunities of attracting smart people interestedin pursuing new ventures. This is true of talented researchers as well, who, in addition to thetraditional outcomes of research activities (publications and/or participation in conferences), aregiven the possibility of increasing their sources of revenues and capturing the rents to their rareand valuable intellectual property (Zucker, Darby, and Armstrong 1998).
Supporting academic start-ups may also contribute indirectly in strengthening a more generalset of opportunities of interaction with the industrial world (Guy and Quintas 1995; Friedman andSilberman 2003). Employment opportunities are enhanced, thus positively affecting placementservices.
2.2. Comparing Europe and the USA
Scholars have given different definitions of academic (university) spin-offs. In the USA, spin-offsbased on university licensed technologies are very frequent (Shane 2004). Therefore, it is possi-ble to have academic spin-offs that are founded by non-academic entrepreneurs, as far as a givenuniversity owned technology can be granted to a ‘surrogate’ entrepreneur (Franklin, Lockett, andWright 2001). O’Shea et al. (2005) define university spin-offs as new firms based on the transferof core technology from an academic institution, where the founding members may (or may not)include the academic inventor. In Europe, and particularly in Italy, there are very few companies-founded on the basis of technologies protected by university patents (Grimaldi and Grandi 2003).Notwithstanding the recent interest in university patenting (Baldini, Grimaldi, and Sobrero 2006),Italy does not have a long tradition of university patents, which reduces the number of companiescreated on the basis of university assigned technologies. In Europe, the most common type ofacademic spin-off is represented by companies based on a technological knowledge developedwithin academia and not formally covered by a university patent, which is transferred into thenew venture by academics themselves (Grimaldi and Grandi 2003). A broad definition applyingto the EU context may be the one provided by Mustar et al. (2006), according to which research-based spin-offs involve the creation of ventures based on the formal and informal transfer oftechnology or knowledge generated by public research organisations (Smilor 1990).
Our definition of academic spin-offs, as we will clarify in Section 4, includes companiesthat have been founded by a faculty member, staff member, or PhD student who transfer the
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technology developed within academia into their new companies. In the Italian context suchtransfer of knowledge is rarely protected by a university assigned patent.
The successful US models have been often imitated, regardless of the peculiarities of othercountries. US universities are much more autonomous and ever since they have been competitivein attracting brighter students, funding and in producing excellent knowledge. Traditionally, theyalso have better relations with industry, as for a long time there have been federal programmessupporting university–industry interactions. On top of that, there is a successful market for ven-ture capital which has promoted the creation and growth of important companies in high techindustries over the last 30 years, many of them spun off from universities. More generally, inter-actions among government, industry and research institutes are frequent and common. Togetherthese factors have created an environment which is particularly fertile for the creation of newventures.
Unlike US universities, in many European countries up until the recent past, academia wascharacterised by centralised systems where competition was scant, decisions were taken by thecentral government and few powers were transferred to single universities. Moreover, in manycases the poor industry–university relations that characterise several EU countries have made itdifficult for universities to generate entrepreneurial orientation. The rigidity of the labour marketoften represents an obstacle to new venture creation. Finally, in some EU countries, there are veryfew financing institutions and, more importantly, the venture capital market is still in its infancy.The result is that, in many European countries, research institutions have shown a limited capacityfor transferring their scientific and technological knowledge to industry (Jones-Evans et al. 1999),in particular, in relation to the process of spinning off new ventures (Callan 2001; O’Shea et al.2005). Moreover, it is widely recognised that local context specificities, characterising differentEuropean countries, make it difficult to harmonise technology transfer strategies and policies. Soeach nation has decided to follow a specific approach that reflects the particular characteristics ofits national innovation system (Freeman 1995).
In Italy, the weakness of the innovation system of research – as a result of the low share ofGPD that is devoted to R&D expenses and to the very limited participation of industry in financ-ing R&D activities – has negatively influenced the technology transfer activities carried out bypublic research institutions (Cesaroni et al. 2005). However, there have been important legislativechanges (Baldini, Grimaldi, and Sobrero 2006), which have been giving increasing autonomy touniversities and have started creating the conditions necessary for an effective commercialisationof research results through academic start-ups.
Overall, the technology transfer activities performed by different organisations in differentEuropean countries are beginning to produce considerable results, particularly in relation toresearch contracts and licensing. However, their influence on the creation of university spin-offs is still quite limited (O’Shea et al. 2005) and, therefore, more country level analyses arerequired for a deeper understanding of the factors that effectively support their creation andgrowth.
3. Research hypotheses development
In this study we focus on the factors that explain university variation in the generation of aca-demic spin-offs. Different authors have already addressed the topic. Some of them, looking atexternal environment characteristics, have shown that different factors, including market struc-ture (Audretsch 1995), technology regime (Winter 1984; Shane 2001), infrastructure of the region
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University-level Mechanisms Supporting the Creation of New Companies 683
(Saxenian 1994), local context characteristics, presence of venture capital (Di Gregorio and Shane2003; Powers and McDougall 2005; Florida and Kenney 1988), presence of companies operatingin the same sectors, science parks and other investors, can influence the rate at which univer-sity spin-offs are created. Other studies have focused on academic personal-level characteristics.Authors belonging to this stream of research have shown that factors such as inventors’ careerexperiences (Levin and Stephan 1991), researchers’ motivations to become entrepreneurs (Shane2004), scientists’citation rate (Zucker, Darby, andArmstrong 1998), etc. can influence the decisionto start up new ventures.
In this paper we focus on the mechanisms that universities may implement within their organ-isations to encourage academics to found new ventures; we analyse whether some universityresources can predict the number of spin-offs generated. More specifically, drawing on the stud-ies investigating this topic, we analyse the effects of the stock of technology transfer staff, thestock of social resources, the stock of organisational services and, finally, other complementaryservices provided by universities on the generation of spin-offs.
According to a previous work of Lockett and Wright (2005), we modelled the different inputsand supports provided by the UTTUs, employing a resource-based view of the firm (Rumelt1984; Barney 1991) that considers resources as stocks and assets, putting the attention also on the‘productive services’ that different collections of resources – deployed together – can generate(Penrose 1959). The focus of this research study is then focused on the analysis of the resources(human, social and organisational) put in place by the UTTUs, in order to understand their rolein the creation of academic spin-offs.
3.1. The stock of technology transfer staff
Some authors (Clarysse et al. 2005; O’Shea et al. 2005; Lockett and Wright 2005) have highlightedthe importance of technology transfer staff (people in charge of technology transfer activities), asone of the factors that can influence cross-university variation in the rate of academic spin-offs. Infact, technology transfer staff carry out most of the activities that are supposed to support academicentrepreneurship such as establishing networks with external organisations, writing business plans,defining business ideas and stimulating entrepreneurial activities within universities (Siegel et al.2003b).
Moreover, technology transfer staff have an important role in the creation of an entrepreneurialculture within the university, taking time and effort to break down the barriers that in manycases exist between university scientists and the industrial world. The importance of technologytransfer staff is related to the ‘traditional non-commercial nature of some university environments’(Lockett and Wright 2005), that often makes it difficult to foster an entrepreneurial orientationwithin the academic world. For this reason, technology transfer officers can play a key role inthe recognition of commercial opportunities for the inventions developed by academic scientists(Lockett, Wright, and Franklin 2003). The number of people who are devoted to technologytransfer activities is likely to signal the magnitude of a university’s involvement in supporting thecreation of new companies.
Drawing on the contribution by Lockett and Wright (2005), we refer to the number of peoplewithin UTTUs, who are in charge of technology transfer activities, as the stock of technologytransfer staff.
On the basis of the arguments above, we hypothesise the following:
HP1: The greater the number of UTTU staff, the greater the number of academic spin-offs generated.
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3.2. The stock of social resources
Few empirical studies have investigated the role of innovation networks created by universitieswith the specific aim of enhancing the creation of academic spin-offs (Pérez Pérez and Sanchez2003; Grandi and Grimaldi 2005). Universities that are part of extended networks, includingdifferent organisations such as science parks, business angels, venture capitalists, agencies spe-cialised in technology transfer, are in a position to offer a set of different services and developexternal relationships supporting new venture creation (Vohora, Wright, and Lockett 2004; Lock-ett, Wright, and Franklin 2003; Siegel et al. 2003a). Social networks, as suggested by Powell(1990), are an important source for obtaining information and accessing resources. In many uni-versities, characterised by a scant entrepreneurial culture, it becomes fundamental to develop asolid network of external relationships with different actors such as institutional investors, firmsand consulting organisations. These networks can help new start-ups in the phases of ‘opportunityrecognition’ and ‘entrepreneurial commitment’ (Vohora, Wright, and Lockett 2004).
Aspiring would-be academic entrepreneurs can use their university networks in order to obtainsome resources for their companies’early development, thus increasing the companies’knowledgeand opportunities (Pérez Pérez and Sanchez 2003). Mustar (1998) shows that the most successfultypes of spin-off are represented by those companies that used partnerships and networks toaccess external resources and competencies. The study conducted by Nicolaou and Birley (2003)also maintains that the characteristics of spin-outs are influenced by ‘academic embeddedness in anetwork of exoinstitutional and endoinstitutional ties’. In particular, academic networks offer fourmain advantages: (1) they increase the entrepreneurs’ opportunity identification capabilities; (2)they facilitate access to resources; (3) they favour economies of time; and (4) they are a source ofstatus and referrals. Most of these external connections are inherited from the parent organisationsof academic start-ups.
Following the suggestion made by Degroof and Roberts (2004), we refer to the managerial andindustrial networks built up by UTTUs as social resources. Drawing on the contributions so fardescribed, we argue that the higher the level of social resources that UTTUs have (and thereforeoffer to their companies), the greater will be the number of academic spin-offs generated.
Therefore we hypothesise the following:
HP2: The higher the level of UTTU social resources, the greater the number of academic spin-offsgenerated.
3.3. The stock of organisational services
Another important factor that helps to explain cross-university variation in the generation of aca-demic start-ups is represented by the organisational services that universities offer to support thecreation of new ventures. There are many different types of organisational services that can beoffered, such as mentoring and business advisory, business plan competition, technology oppor-tunity search, support in recruiting external resources, university-affiliated research/science park,intellectual property assessment and university-based incubator facilities/services. There are alsodifferent types of financial support that universities can offer to start-up companies, ranging fromaccess to venture capital, to business angels, advice on government commercialisation grants andequity in the university spin-offs.
Previous studies have highlighted the importance of these mechanisms. The results of theresearch conducted by Steffensen, Rogers, and Speakman (1999) confirm the positive role oforganisational support offered by TTOs in creating university spin-offs. In order to provide these
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University-level Mechanisms Supporting the Creation of New Companies 685
organisational services, the business experience of TTO managers is an important element (Siegelet al. 2003a); in fact both managerial and legal competences are needed to integrate the scientificknowledge of researchers who start new companies.
Sometimes academic inventors may lack business experience and management skills and thismay represent an obstacle in the generation of university spin-offs (Samson and Gurdon 1993;Radosevich 1995; Lockett, Wright, and Franklin 2003). Therefore, the organisational supportprovided by universities and through external relationships with the industrial world is key tofinding the resources and capabilities that are missing. As argued by Meyer (2003), the mostsuccessful start-ups are those that have used the facilities of science parks and incubators, andat the same time, have benefited from established business networks built by science parks orincubators. Even Smilor and Gill (1986) and Tornatzky and others (1996) highlight the importanceof university incubators in supporting new ventures. They have described the following mainadvantages related to the localisation of spin-offs within university incubators: access to libraryfacilities, contact with a creative environment, availability of different facilities and expertise, andaccess to student labour.
Most of the services mentioned above (e.g. business plan compilation, technology opportunitysearch) are provided through the UTTUs, whereas a few are given directly by universities them-selves (e.g. the university incubator, the academic spin-off regulation and the organisation of thebusiness plan competition). We call the former UTTU organisational resources, while we referto the latter as other complementary services provided by universities.
On the basis of the arguments presented above, we formulate the following two hypotheses:
HP3: The higher the level of UTTU organisational resources, the greater the number of academicspin-offs generated.
HP4: The higher the level of other support mechanisms offered by university, the greater the numberof academic spin-offs generated.
4. Methodology
4.1. The questionnaire
We gathered data about characteristics and policies put in place by Italian universities to supportnew venture creation. Data was collected through a questionnaire, that was drafted on the basisof the existing theoretical and empirical literature. The questionnaire contained four sections: thefirst one gathered some general information about the UTTUs (year of establishment, number ofpeople, experience and background of the staff, etc). The second section focused on the socialnetwork established by the UTTUs in terms of size and strength of ties with external organisations.We asked some questions about the number of organisations with which UTTUs had relationsand about their frequency of interaction. The third section was dedicated to the organisationalsupports provided by both universities and their UTTUs. We analysed in particular the presence ofuniversity level support mechanisms, such as university incubator, business plan competition andspin-off regulation. We also added some questions about the number of organisational servicesdirectly provided by UTTUs, like support on technology opportunity search, support on businessplan development, support on patent process and, finally, support in spotting funding sources.The last section gathered some information about academic spin-offs generated by universitymembers (year of establishment, industry, etc.). Detailed information about the items can befound in Appendix 1.
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For the development and selection of the items included in the different sections of the ques-tionnaire, we carefully analysed studies that followed a similar approach in order to derive a firstset of possible items; we also conducted some interviews with UTTU’s staff in order to integrateitems (and scales) emerged from the literature.
We used a small scale field test to assess whether questions were phrased in an ambigousmanner or not, and to find out if other relevant aspects could be included in the different partsof the questionnaire. More specifically we contacted three heads of UTTUs who provided veryhelpful insights with regard to the questionnaire’s completeness and clarity, as well as an evaluationof the time needed to complete it. No major inconsistencies emerged from this pre-test phase.
4.2. The sample
To obtain information relating to university technology transfer activities, we surveyed Italianuniversities. Out of the 78 Italian universities surveyed, which are the entire population, only 43universities carry out technology transfer activities; this information was gathered by analysinguniversity web sites and through telephone interviews with the chief administrative office ofeach university. This result is also confirmed by the fact that the ‘Italian Network per la Val-orizzazione della Ricerca Scientifica’ (Italian University Network for Research Exploitation)1
includes 41 universities.Therefore we sent out our questionnaire to the 43 universities representing the entire popula-
tion of Italian academic institutions carrying out technology transfer activities. In some of theseuniversities, there are TTOs dedicated to this task, while in other universities technology transferactivities are performed within other offices, such as the research office and the administrativeoffice. In both cases there are university employees specifically dedicated to technology transferactivities. However, in the former case a specific, ad hoc organisational unit is created, while inthe latter case these activities are performed within an organisational unit already existing. In theformer case, the questionnaire was sent to the head of the TTO, while in the latter it was sent tothe head of the office in charge of technology transfer activities.
Data collection started in November 2004 and ended in March 2005, with exactly 37 question-naires completed and returned, corresponding to a response rate of 86%. Given the high returnrate, we consider the sample representative of Italian universities performing technology transferactivities. Even considering the problems associated with a non-random sample, it should yield asound inference.
Table 1 shows that the universities surveyed are uniformly distributed in Northern and Cen-tral/Southern Italy. Out of the 37 universities analysed, 17 do not have a formal TTO. Morespecifically, among the 20 universities located in Central/Southern Italy, 13 have a formalisedTTO, while among the 17 located in Northern Italy, only seven have a dedicated TTO. Ananalysis relating to the year of establishment of UTTUs at each university shows a substantialdispersion between universities, ranging from 1989 to 2005.
4.3. Definition and measurement of variables
4.3.1. Dependent variablesThe dependent variable counts the number of spin-off companies (SPINOFFS) generated from2003 to the beginning of 2005 at a given university. For each university, we considered onlythose companies founded after their university’s intervention in support of technology transferactivities. This means that, for each university, we include in the model only those companies
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Table 1. Localisation and age of UTTUs.
Localisation Age
Northern Central Southern ≤2 ≥3−≤5 ≥6−<11 ≥11Italy Italy Italy years years years years
Number of formal TTOs 7 6 7 7 10 2 1(18.91%) (16.21%) (18.91%) (19.44%) (27.78%) (5.56%) (11.11%)
Total number of UTTUs 17 13 7 12 18 2 4(45.94%) (35.13%) (18.91%) (33.33%) (50%) (5.56%) (11.11%)
No response 0 1
established after the creation of the UTTU, either in the form of an independent unit (TTO), oras groups of university employees, who are part of research or administrative offices.
In this research study, in line with previous studies (Samson and Gurdon 1993; Steffensen,Rogers, and Speakman 1999; Doutriaux 1987) and the considerations made in Section 2, wedefined a university spin-off as a company founded: by a faculty member, staff member, or PhDstudent, and on the basis of technological knowledge or scientific/technical know-how generatedin a university setting.
This definition fits the Italian context very well, where, unlike the USA, there are very fewspin-off companies founded on the basis of university assigned technologies.
4.3.2. Independent variablesAs for the stock of ‘social resources’ related to the external ties established by UTTUs, two dimen-sions were considered: size and strength of an UTTU’s ties. The first was measured counting thenumber of different external organisations with which UTTUs interact (NUMINT). The second,following the suggestion made by Grandi and Grimaldi (2005), was operationalised by measur-ing the frequency of interaction that UTTUs have with different external organisations (INT). Inorder to identify the list of external organisations, we first analysed the literature, then we askedtechnology transfer staff to describe the network of external organisations with which they used tointeract. Nine types of organisations were identified: science parks, incubators, technology trans-fer organisations, business angels, venture capitalists, banks, organisations that support spin-offs,other universities and other public institutions.2 Our variables measure the frequency and strengthof interaction that each UTTU had in 2003. According to our respondents, the network of externalagents with which they interact has not been changing from 2003 to the beginning of 2005 whichis the period that we looked at in our analysis.
The stock of ‘technology transfer staff’ (TTSTAFF), according to the literature (Lockett andWright 2005; O’Shea et al. 2005), was measured in terms of the number of full-time equiva-lent employees dedicated to technology transfer activities and working within each universityin 2003. This variable does not include staff working in separate science parks and incuba-tors. Part-time employees dedicated to technology transfer activities have been counted as 0.5full-time employees.
The stock of ‘organisational services provided by the university technology transfer unit’(SERV) was measured by counting the number of services that the UTTUs were offering in2003. We considered the following services: (1) support in identifying technology opportunities;
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(2) support in business plan development; (3) support along the patent process (disclosure, patentapplications, etc.); (4) support in finding sources of funding.
During our interviews we realised that, on average, there have been no major changes overour period of observation from 2003 to the beginning of 2005 in relation to the number and thetype of services UTTUs have been offering. Also, there have been no changes in the numberof employees.
The variable ‘other complementary services’ (UNISUPP) relates to other support mechanismsprovided by the university in order to help the generation of new ventures. It was measured bycounting the number of support mechanisms offered by universities to which UTTUs belong,such as: (1) availability of a university-affiliated incubator; (2) presence of a spin-off regulation;(3) presence of a business plan competition.
A complete list of services and support mechanisms provided by both the UTTUs and theiruniversities was identified through the analysis of the literature and by asking university staff todescribe the different support mechanisms that they offered. We included in our analysis onlythose spin-offs that were founded after the establishment of a given support mechanism at anyspecific university.
4.3.3. Control variablesWe controlled for the following effects: the number of patents (PAT), the geographical locationof university (REGION) and the presence of a formalised office dedicated to technology transferactivities (TTO).
The variable ‘patents’ (PAT) counts the total number of university-owned patents up until2004. It is reasonable to think that universities with more patents have a more ‘outward’ lookingattitude towards commercialising academic knowledge and this might influence their generationrate of spin-offs.
The variable ‘geographic location’ (REGION) was introduced taking into consideration thedifferences that exist between North and South Italian regions in terms of entrepreneurship,infrastructures, availability of venture capital and other supporting services provided by the localcontext. This choice was made following the suggestion given in the recent literature abouttechnology transfer that emphasises the important role that a beneficial environment plays infostering the generation of new firms (Grimaldi and Sobrero 2005; Clarysse et al. 2005; O’Sheaet al. 2005; Lockett and Wright 2005). In this research study, the variable ‘geographical location’is measured as a dummy variable, counting 1 if the university is located in northern Italy and 0 ifit is located in central or southern Italy.
The dummy variable ‘technology transfer office’ (TTO) was introduced in order to investigatewhether the presence of a formalised office dedicated to technology transfer activities plays a rolein favouring creation of new ventures. (Remember that only some universities have formalisedTTOs, whereas others have a group of people, who take care of technology transfer relatedactivities, while belonging to research offices or administrative offices).
Appendix Table A1 summarises all the variables described.
5. Analysis and empirical results
5.1. University technology transfer units
In order to briefly describe the profile and activities of UTTUs, we provide an analysis of themain characteristics of their employees, the typology of networks that they established and theservices offered.
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Table 2. Background of personnel in charge of technology transfer activities, based on the sizeof their UTTUs.
Number of UTTUs having personnel with:
Total number No technical Managerial Technical Both technicalof personnel or managerial background background and managerialwithin UTTUs background only only background
1–2 employees 9 (25%) 8 (22.22%) 5 (13.89%) 2 (5.56%)3–5 employees 2 (5.56%) 4 (11.11%) 0 (0%) 4 (11.11%)≥5 employees 0 (0%) 0 (0%) 0 (0%) 2 (5.56%)Total 11 (30.56%) 12 (33.33%) 5 (13.89%) 8 (22.22%)No response 1
Table 2 shows the profile of the employees in charge of technology transfer activities, basedon the size of the UTTUs to which they belong: it is interesting to highlight that there are 11universities where the employees have a humanistic background, while in the other universitiesthere are more employees with managerial background rather than technical background. Table 2also shows that more than half of the universities surveyed have less than three employees inthe UTTU.
Table 3 illustrates that UTTU personnel do not have much experience in technology trans-fer activities (number of years), confirming the recent involvement of Italian institutions in theexploitation and valorisation of research results.
Table 4 shows that 37% of all universities located in southern and central Italy operate ina context which is not supportive to entrepreneurship (unsupportive local context),3 where thesupport mechanisms available to any new start-ups are quite limited; in comparison, only 16.6%of all the universities located in the north are located in a weak entrepreneurial context, with scantinfrastructures supporting technology transfer (see Table 4).
5.2. Characterisation of university spin-offs
The 37 universities in our sample generated 144 spin-offs, with a mean of 3.89 spin-offs peruniversity, with a substantial dispersion between the universities in terms of the number of spin-offs created. Approximately 35% of the universities surveyed generated no spin-offs. The peakyear for the highest number of academic spin-offs was 2004. There were a limited number of
Table 3. Average experience of UTTUs’ personnel.
AverageTotal number experience ofof personnel the employeeswithin UTTUs (years) s.d.
1–2 employees 3.675 2.5423–5 employees 3.065 1.806≥5 employees 5.61 4.198No response 7
Note: s.d. = standard deviation.
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Table 4. Number of UTTUs and local context.
Local context
Localisation in Italy Not supportive Supportive
Number of UTTUs in northern Italy 3 (8.1%) 15 (40.5%)Number of UTTUs in central/southern Italy 7 (18.9%) 12 (32.5%)
spin-offs in 2005 and this is probably due to the fact that our data collection closed before the endof 2005.
Most of the spin-offs generated are in the ICT and software industry, followed by electronicsand traditional sectors (automation, mechanics and energy); few spin-offs have been generated inthe health care industry, probably due to the high and risky investments required for developingnew drugs. Much attention has been recently given to the biotechnology sector, as confirmed bythe significant number of spin-offs in this industry.
A significant portion of companies provides only services, but the number of firms that offerboth products and services is quite high. A synthesis of these figures is presented in Table 5.
5.3. Regression analysis
In order to test the hypotheses discussed in Section 3, we conducted a regression analysis. Weconsidered log-linear models (Agresti 2002), both Poisson and negative binomial distributions.
Table 5. Year of establishment, type of industry and type of business of academic spin-offs.
Year of establishment <2000 13 9.42%2000 10 7.25%2001 12 8.7%2002 9 6.52%2003 26 18.84%2004 50 36.23%2005 18 13.04%Total 138 100%No response 6
Type of industry Biotech 16 11.43%ICT & software 38 27.14%Health care 8 5.71%Electronics 25 17.86%Chemistry 6 4.29%Traditional sectors 24 17.14%Environment/food 14 10%Managerial consulting 9 6.43%Total 140 100%No response 4
Type of business Products 32 23.19%Services 58 42.03%Products and services 48 34.78%Total 138 100%No response 6
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We found that the Akaike information criterion (Akaike 1973) is smaller for the Poisson log-linearmodels, which we chose for our analysis.
Descriptive statistics and correlation matrix of the dependent, control and independent variablesare presented in Tables 6 and 7.
We ran bivariate correlation analysis to detect the interrelationships among the independent,control and dependent variables. The analysis shows that most of the variables are unrelatedand when there are correlations between variables, these correlations are below the thresholdcommonly used to detect multicollinearity problems (Berry and Feldam 1985).
Table 8 shows the results of regression analysis.Results support Hypothesis 1 relating to the effect of technology transfer staff stock on the
generation of academic spin-offs; the coefficient associated with the variable ‘technology transferemployees’ (TTSTAFF) is positive and statistically significant (p < 0.01). Hypothesis 2, relatingto the role of social networks established by UTTUs with external organisations, is supported onlyfor one variable relating to the strength of the ties (p < 0.01). The other variable (NUMINT),measuring the size of the network, is not significant. Our results also support Hypothesis 3concerning the role of the services provided by UTTUs (SERV) in favouring the generation of start-ups (p < 0.05). Finally, even Hypothesis 4 about the role of support mechanisms (UNISUPP)provided by universities themselves (such as incubator, spin-off regulation and business plan
Table 6. Descriptive statistics for independent, control and dependent variables.
StandardVariables Mean deviation Median Minimum Maximum
TTSTAFF 2.6 2.137 2 1 10INT 2.57 0.619 2.666 1.33 4.5NUMINT 5.513 2.231 5 0 9SERV 3.594 0.831 3 0 4UNISUPP 1.375 1.039 1 0 3SPINOFFSa 2.54 3.042 2 0 13PAT 17 24.132 7 0 104
aThe mean reported for spin-offs in Table 6 does not coincide with the mean reported at the beginningof Section 5.2. This is due to the fact that for the dependent variable we only included those spin-offsfounded after the constitution of the UTTOs.
Table 7. Correlation matrix.
1 2 3 4 5 6 7 8 9
1. NUMINT 1 0.234 0.141 0.347∗ 0.073 0.305 0.342∗ −0.188 0.2202. INT 1 0.382∗ 0.363∗ −0.254 0.251 0.129 −0.292 0.1203. TTSTAFF 1 0.518∗∗ 0.355∗ 0.405∗ 0.249 0.166 0.2244. SERV 1 0.134 0.234 0.360∗ −0.099 0.428∗∗5. UNISUPP 1 0.260 −0.040 −0.244 −0.1096. PAT 1 0.190 0.122 0.481∗∗7. REGION 1 0.120 0.3058. TTO 1 0.347∗9. SPIN OFF 1
∗Correlation is significant at the 0.05 level (2-tailed); ∗∗Correlation is significant at the 0.01 level (2-tailed).
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Table 8. Regression results
Independent variables Model
TTSTAFF 0.135 (0.063)∗∗INT 1.280 (0.566)∗∗NUMINT −0.309 (0.158)SERV 0.627 (0.329)∗UNISUPP 0.411 (0.157)∗∗∗REGION 0.947 (0.420)∗∗PAT 0.007 (0.007)TTO −0.364 (0.347)CONSTANT −4.371 (1.833)AIC 100.98
Notes: Standard errors in parentheses.∗Correlation is significant at the 0.05 level;∗∗Correlation is significant at the 0.01 level;∗∗∗Correlation is significant at the 0.001 level.
competition) in fostering the creation of new ventures is confirmed. The coefficient of the variableassociated with university support is positively and statistically significant (p < 0.001).
We controlled for the effect of three control variables: the geographical location of univer-sity (REGION), the number of patents (PAT) and the presence of a TTO. Results show thatlocalisation of university is statistically significant (p < 0.01), thus affecting the generation ofacademic spin-offs.
6. Discussion
6.1. Contribution to theory
This research study draws attention to factors that can explain cross university variation in spin-offgeneration. We focus on the contribution of UTTUs and, more generally, of university policies insupport of the creation of new academic spin-offs.
Most of the studies are based on the US context and focus only on new firms established toexploit university assigned technologies, and do not extend their analyses to start-up activitywhich is not designed to exploit university assigned intellectual property (Di Gregorio and Shane2003). Although most of the academic spin-offs in Europe are not based on university assignedtechnologies, their study deserves further attention.
The novelty of the study stems from its focus on the Italian context, where, only over the lastfew years, universities have started investing and creating mechanisms to favour the exploitationof academic scientific knowledge through the creation of new companies. Some characteristicsof the Italian context (scant university–industry relations, absence of venture capital market,labour market rigidity, etc.) are common to other European countries and therefore the resultsthat we present about the Italian experience can contribute to enhancing our understanding of thisphenomenon also in other European contexts.
Our results support existing contributions that have shown the important role that technol-ogy transfer staff play in favouring the creation of new firms (O’Shea et al. 2005; Lockett andWright 2005). The availability within universities of personnel dedicated specifically to support-ing technology transfer activities is important as far as it signals a university’s commitment to
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invest seriously in this important area. All the universities that we investigated, even those that donot have formal TTOs, have devoted part of their budget to cover technology transfer personnelexpenses. In fact results of the study show that the presence of a formal TTO does not have asignificant impact in the number of spin-offs generated. In other words the creation of ad hocorganisational units specifically devoted to technology transfer activities is not significant for thegeneration of spin-offs, while staff commitment towards technology transfer policies plays a moreimportant role.
Concerning the stock of organisational resources, we have distinguished between the servicesprovided by UTTUs and those offered by universities themselves, such as business plan compe-tition, university incubator and spin-off regulation. Both of them positively affect the number ofacademic start-ups generated by each university. These support mechanisms are an incentive for‘aspiring academic entrepreneurs’, as far as they can provide the support that is required in theinitial stages of a new venture creation. This is particularly true for those complementary resourcesthat scientists often lack – like managerial competencies – and that can be provided, at least par-tially, by these UTTUs. With regard to this, our results support the findings of previous studies.Smilor and Gill (1986) and Tornatzky et al. (1996) highlight the importance of university incuba-tors in fostering the generation of new academic ventures, and Steffensen, Rogers, and Speakman(1999) and Davenport, Carr, and Bibby (2002) maintain that the success of spin-off companies isrelated to the degree of support (e.g. laboratory facilities, access to research equipment) that theyreceive from the universities.
In relation to social capital, we found that the size of social network does not impact new firmcreation. Even if most of the literature (Pérez Pérez and Sanchez 2003; Siegel et al. 2003a,b) showsthe importance of social networks in fostering the creation and development of new ventures, theresults of this study do not support this evidence. This might be due to specificities of the Italiancontext. First among the external entities, which might be key for supporting academic start-ups,there are no venture capitalists and no business angels. More generally, frequency of interactionsbetween universities and industrial partners is very limited.
More importantly, the fact that the size of external networks is not relevant might signal thatmany external organisations (science parks, business incubators, technology transfer agencies)offer the same type of services provided by UTTUs themselves, and this does not provide addi-tional value to academic start-ups. Recently, following EU and national directions, there hasbeen a proliferation of actors/agencies in the local context offering similar services to aspiringacademic and non-academic entrepreneurs. This situation might be a problem for both universi-ties and external organisations, because it apparently signals that there is an overlap of supportmechanisms (which is not desirable from the point of view of public expense) and a replica-tion by universities of support mechanisms, which do not appear to be useful in supportingacademic start-ups. Degroof and Roberts (2004) argue that the extent of university interventionshould be based on the specificities of the local context and should not replicate the mech-anisms that are already at place. Only in the case where the frequency of interaction withexternal partners is high, does the social network become relevant for the creation of academicspin offs, thus suggesting that stable and continuous relationships provide value to would-beentrepreneurs.
6.2. Managerial and policy implications
In line with the previous literature (Chiesa and Piccaluga 2000) which has provided evidence onthe Italian context, the important role of parent universities in supporting the start-up of new firms
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seems to be confirmed by our research results, showing that the generation of academic start-upsis positively affected by university intervention.
Overall, our results show that universities, through specific support mechanisms, may havean important role in overcoming some types of market failure, thus facilitating the creation ofnew companies.
Context institutions and social relationships are areas for public policy intervention in termsof creating a supportive and positive environment for entrepreneurship. More generally, publicpolicies should leverage on the presence of local research institutions, increase the availabilityof venture capital, encourage a culture of risk taking and create strong local informational andbusiness development networks. More importantly university initiatives should take into accountthe characteristics of the local context in which they are settled in order to create effective mech-anisms and to avoid replication of support tools already at place. In this regard, our results showthat universities located in the north and more industrialised part of Italy are more likely to gen-erate spin-offs, confirming the importance of a fertile local context to enhance the creation ofnew companies.
Of course, universities cannot go it alone in the process of complementing the support mecha-nisms already in place in the local context. Most of the problems that academic start-ups face arisefrom institutional market inefficiencies (labour mobility, scant public-industry relations, fundingreduction for public research), which need to be addressed by local governments (Friedman andSilberman 2003).
With regard to social network, our results also suggest that it is important for UTTUs to havestrong and stable relationships with external partners. Therefore, it would be desirable for UTTUs’managers to put effort into the creation of high quality relations with a few, selected and relevantexternal partners, more than establishing weak relations with too many partners.
6.3. Limitations and further research
Among the limitations of this study there is the number of observations of our sample. However,in this specific case, even a relatively small sample makes us confident about the stability ofour results. Our sample accounts for more than 2/3 of the entire population of Italian UTTUs,which, even considering the problems associated with a non-random sample, should yield asound inference.
Another limitation of this analysis is represented by the fact that we did not control for thedisciplinary profile of the university. We are aware that, at least in the USA, the presence of amedical school is particularly relevant in explaining the overall increasing trend in universities’technology transfer activities (Mowery, Sampat, and Ziedonis 2001). Also, we did not considerthe size of universities in our controls. Further research should be devoted to investigating theeffect of universities’ characteristics on spin-off creation.
Our study suffers from the shortcomings of analyses based on self-reported data. Future researchcould be directed at collecting more quantitative/objective indicators.
As for the generalisability of our results, we believe our study to be particularly relevant forthose countries that recently became involved in the creation of mechanisms supporting thecommercialisation of research results, that do not have a consolidated system for supportingtechnology transfer and, more generally, university–industry technology transfer.
Finally, an interesting extension of this study would be to investigate the extent to whichacademic founders appreciate the support mechanisms available in the process of starting uptheir companies. An analysis at micro level of academics’ perceptions of incentives and obstacles
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encountered in their new venture creation process would provide further insights into the realeffectiveness of public intervention.
Notes on contributors
Anna Nosella is an assistant professor in management and strategy at Padua University. Her current research interestsinclude innovation and entrepreneurial networks, innovation management, new venture creation and collaborative FIRBresearch project on knowledge management in SMEs.
Rosa Grimaldi is associate professor of technology and innovation management at the Department of Management of theUniversity of Bologna. Her research interests are entrepreneurship, academic spin-offs and the management of innovation.She is the author of several international publications on these topics.
Notes
1. The university network for research valorisation that was established in 2002 involves Italian universities that performtechnology transfer activities. This network was created with the specific aim of sharing experiences about thevalorisation of university scientific/technical knowledge.
2. Science parks have been considered as external organisations because in Italy they are organisational structuresautonomous and external to universities. Also incubators have been considered external organisations for the samereasons. Universities usually own shares (not a majority) in both types of institutions.
3. The variable local context relates to availability in the local context, in which companies operate, of externalorganisations that support entrepreneurships. It is a dummy variable, which is:1 – if in the regions there are more than four of the following organisations: science parks, incubators, TT organisa-tions, business angels, venture capitalists, organisations that support spin-offs and other universities (supportive localcontext)0 – otherwise (unsupportive local context).
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Appendix
Table A1. Meaning and measurement of variables.
Category Variables Measurement
Independent variablesSocial resources NUMINT The variable counts the number of the following organisations
which TT personnel interact with: science parks,incubators, TT organisations, business angels, venturecapitalists, banks, organisations that support spin-offs,other universities and other public institutions.The variableranges from 0 to 9
INT The variable relates to the frequency of interactions thatTT personnel have with: science parks, incubators, TTorganisations, business angels, venture capitalists, banks,organisations that support spin-offs, other universities andother public institutions
Items relating to the frequency of interaction with thesedifferent organisations have been collapsed into onesingle variable through the arithmetic averaging of theanswers. Answers have been given on a 1 (no frequencyof interaction) to 5 (very high frequency of interaction)likert scale
Technology transfer staff TTSTAFF The variable counts the number of full-time employees(working inside the university) involved in technologytransfer activities
Part-time employees were counted as 0.5 full-time employees
Organisational resources SERV The variable counts the number of the following servicesprovided by UTTUs: (1) support on technology opportunitysearch; (2) support on business plan development; (3)support on patent process; (4) support in finding fundingsources. The variable ranges from 0 to 4
UNISUPP The variable counts the number of the following servicesprovided by the university: (1) presence of universityaffiliated incubator; (2) presence of a spin-off regulation;(3) presence of a business plan competition The variableranges from 0 to 3
Control variablesPatents PAT The variable counts the number of university patents up
until 2004
Geographical location REGION The variable relates to geographical location of universityIt is a dummy variable, which is:1 – if university belongs to northern regions0 – if university belongs to central and southern regions
Technology transfer office TTO The variable relates to the presence of a formalised officededicated to technology transfer activities
It is a dummy variable, which is:1 – if there is a TTO0 – if there is not a TTO
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