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Productive Hybrid Intelligent Trusted The Influence of Microsoft Azure on Digital Maturity and Firm Performance Master Thesis | Information Management
Productive
Hybrid
Intelligent
Trusted
The Influence of Microsoft Azure on Digital
Maturity and Firm Performance Master Thesis | Information Management
The Influence of Microsoft Azure on Digital
Maturity and Firm Performance
Student Name: B. van Bennekom
Student number (SNR): 1258074
Application number (ANR): 783281
Telephone Number: (+31) 06-40382080
Email:
Thesis defence date:
January 14, 2019
Thesis Supervisor:
Second Supervisor:
Number of words:
Prof. Dr. X. (Carol) Ou
Prof. Dr. W.J.H. van Groenendaal
29.965
University: Tilburg University
Faculty:
Department:
Program:
External Company:
External Supervisors:
Tilburg School of Economic and Management
Department of Management
Master of Information Management
Microsoft Nederland
Jeffrey Vermeulen
Robbert Bakker
Management Summary
Over the last decade, the concept of digital maturity gained relevance. The primary reason for this trend
is that digital maturity improvements enhance firm performance. In addition, a substantial number of
firms have experienced pressures from customers and competitors to initiate their digital
transformation. Nonetheless, academic literature has primarily discussed brief decompositions of the
term or characteristics of digitally mature firms. Hence, to advance understanding with regard to the
concept of digital maturity, additional research is conducted. Accordingly, digital maturity is defined
as ‘[a] combination of technology-enabled initiatives and technology management that decide on an
organisation’s ability to digitally transform’. Meanwhile, the digital maturity model combines the
interrelated dimensions of digital intensity and transformation management intensity to determine a
firm’s maturity archetype.
Multiple research papers have highlighted the benefits of digital maturity improvements. However, they
often noted a variety of overlapping or contradicting aspects of firm performance. Therefore, the thesis
has consolidated all performance aspects that benefit from digital maturity enhancements into a set of
five firm performance aspects: products and services, internal processes, customers, partners and
competitors, and financials. Consequently, organisations are not confronted by a wide variety of aspects
that confuse rather than inspire them. Furthermore, this study has explored the connections between
digital maturity and the five factors and confirmed the positive influence on all factors except partner
and competitor collaboration.
Despite increasing acknowledgement of the relevance of digital maturity, a substantial number of
organisations have failed to enhance their maturity levels. Academic research states that a lack of
guidance and absence of best practices mainly induce this struggle. The academic literature has aimed
to guide firms along their digital journey by indicating the influencing factors of digital maturity.
Nonetheless, research studies have often suggested overlapping or contradictory factors, thereby
increasing the complexity of digital transformation. Therefore, this study has combined all factors into
a set of five overarching influencing factors: digital workforce, digital culture, digital capability, digital
leadership and digital vision. Companies should internally cultivate these factors to drive digital
maturity improvements. Moreover, the interview studies offer two additional findings that are pivotal
to the above-mentioned relationships. First, the creation of digital leadership stimulates the development
of the other four influencing factors as well. Second, significant digital maturity improvements are
achievable only when all five factors are present and aligned since the absence of one or more factors
hinders the impact of the remaining influencing factors.
Academic research also noted substantial maturity differences between industries. Industry-specific
factors, such as regulatory compliance, induce such discrepancies by moderating the connection
between the influencing factors and digital maturity. However, most information systems literature has
addressed only a narrow range of sectors and infrequently considered the effects of industry-specific
factors. Hence, the study has investigated the impact of institutional factors on the above-mentioned
relationship. Remarkably, the literature review proposes that this influence is negative, whereas the
interview studies indicate that it is dependent on an organisation’s attitude towards digital
transformation. Future research should thus consider whether institutional factors have a positive or
negative impact and investigate other industry-specific factors (e.g. economic and social and cultural)
that affect this relationship.
Finally, academic research reveals only the advantages of cloud computing for technological
development. Nevertheless, neither the impact of cloud technology on digital maturity nor the
connection between Microsoft Azure and digital maturity has received academic attention. Therefore,
this study has used internal documentation and empirical research to explore the latter relationship. Case
examples and the interview studies illustrate a positive influence of Microsoft Azure on the influencing
factors digital workforce, digital culture, digital capability and digital vision. Accordingly, Azure can
indirectly stimulate both the digital intensity and transformation management intensity dimensions. In
contrast, both sources of evidence reject the positive impact of Microsoft Azure on the creation of digital
leadership. In conclusion, the study argues that Microsoft Azure influences digital maturity and
consequently improves firm performance.
Table of Contents
1. Introduction ..................................................................................................................................... 1
1.1 Problem indication .................................................................................................................. 1
1.2 Problem statement ................................................................................................................... 3
1.3 Research question ................................................................................................................... 4
1.4 Research method ..................................................................................................................... 4
1.5 Research setting ...................................................................................................................... 5
1.5.1 Microsoft Nederland ....................................................................................................... 6
1.5.2 Microsoft Azure .............................................................................................................. 6
1.6 Relevance ................................................................................................................................ 7
1.6.1 Academic relevance ........................................................................................................ 7
1.6.2 Practical relevance .......................................................................................................... 8
1.7 Outline..................................................................................................................................... 8
2. Literature review ............................................................................................................................. 9
2.1 Research question 1: digital maturity ...................................................................................... 9
2.1.1 How to conceptualise digital maturity? ......................................................................... 10
2.1.2 Digital maturity concept ................................................................................................ 12
2.1.3 Digital maturity types.................................................................................................... 13
2.2 Research question 2: firm performance ................................................................................ 15
2.2.1 How does digital maturity impact firm performance .................................................... 16
2.2.2 Firm performance aspects ............................................................................................. 17
2.3 Research question 3: influencing factors .............................................................................. 20
2.3.1 What factors influence digital maturity? ....................................................................... 21
2.3.2 Consolidated influencing factors................................................................................... 22
2.4 Research question 4: industry-specific factors ...................................................................... 26
2.4.1 Which industry specific factors moderate the relationship between influencing factors
and digital maturity? ..................................................................................................................... 27
3. Microsoft Azure ............................................................................................................................ 30
3.1 Introduction to Microsoft Azure ........................................................................................... 30
3.2 Research question 5: Microsoft Azure .................................................................................. 31
3.2.1 How does Microsoft Azure impact the influencing factors and consequently influence
digital maturity? ............................................................................................................................ 32
3.3 Concluding remarks on literature .......................................................................................... 34
4. Research design ............................................................................................................................ 36
4.1 Research strategy .................................................................................................................. 36
4.2 Research context ................................................................................................................... 38
4.2.1 Microsoft Nederland ..................................................................................................... 38
4.2.2 Cloud & Artificial Intelligence department .................................................................. 38
4.3 Stage 1: define and design .................................................................................................... 39
4.3.1 Explore relationship ...................................................................................................... 39
4.3.2 Select interviews ........................................................................................................... 39
4.3.3 Data collection protocol design ..................................................................................... 43
4.3.4 Data analysis and conclusion ........................................................................................ 43
5. Results ........................................................................................................................................... 44
5.1 Stage 2: prepare, collect and analyse .................................................................................... 44
5.1.1 Interview Study A | Microsoft experts .......................................................................... 44
5.1.2 Interview Study B | Municipality .................................................................................. 50
5.2 Stage 3: analyse and conclude .............................................................................................. 53
5.2.1 Cross-interview analysis ............................................................................................... 54
5.2.2 Relationship modification ............................................................................................. 64
6. Conclusion .................................................................................................................................... 67
6.1 Key findings .......................................................................................................................... 67
6.2 Academic implications .......................................................................................................... 70
6.3 Practical implications ............................................................................................................ 71
7. Limitations and future research ..................................................................................................... 74
7.1 Research design .................................................................................................................... 74
7.2 Data collection ...................................................................................................................... 74
7.3 Data analysis ......................................................................................................................... 74
7.4 Conclusion ............................................................................................................................ 75
8. Bibliography ................................................................................................................................. 76
List of Figures and Tables
Figures Page
Figure 1. The conceptual framework 4
Figure 2. The research design 5
Figure 3. The digital maturity archetypes 15
Figure 4. The selection process of firm performance aspects 19
Figure 5. The consolidation process of influencing factors 24
Figure 6. Digital maturity breakdown across industries 28
Figure 7. The Microsoft Azure solutions 33
Figure 8. The effects of Microsoft Azure on digital transformation 34
Figure 9. The detailed conceptual model 36
Figure 10. The interview study methodology 39
Figure 11. The maturity archetypes of all case companies 58
Figure 12. The final conceptual model 70
Tables Page
Table 1. The literature on digital maturity 12
Table 2. The impact of digital maturity on firm performance 18
Table 3. The influencing factors of digital maturity 23
Table 4. The reviewed overarching influencing factors 24
Table 5. The institutional factors across industries 30
Table 6. The effects of Microsoft Azure on the influencing factors 35
Table 7. Description on the Microsoft Azure experts 42
Table 8. Description on the interview study companies 43
Table 9. Description on the interview study company experts 43
Table 10. Cross study analysis of the relationships 59
Table 11. The rationale for including or excluding relationships 69
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1. Introduction
This master thesis presents insight into the influencing and industry-specific factors that affect digital
maturity and firm performance. Firms are currently investing substantial capital in digital technologies,
such as those of a mobile, social media, cloud-based or analytical nature. These investments have often
yielded disappointing results, as firms have focused on incremental change instead of business
transformation (Westerman, Calméjane, Bonnet, Ferraris & McAfee, 2011). As a result, firms have
been unable to increase their digital maturity level and performance metrics. The objective of this
research paper is to complement the existing literature with regard to the influencing and industry-
specific factors that affect digital maturity and firm performance. More specifically, it studies the impact
of Microsoft Azure on these influencing factors and digital maturity.
The following chapter introduces the research topic and elaborates on the problem statement and
research question of this thesis. In addition, it defines the research method, research setting and
relevance of this paper. Finally, the outline section encompasses the structure and division of chapters
for the remainder of this research paper.
1.1 Problem indication
Over the last decade, information, communication and connectivity (ICT) technologies have improved
significantly and thus acquired new functionalities (Bharadwaj, El Sawy, Pavlou & Venkatraman,
2013). Such ICT technologies enable the creation, storage and usage of information as well as facilitate
communication between humans and electronic systems (El Kadiri, Grabot, Thoben, Hribernik,
Emmanouilidis, Von Cieminski & Kiritsis, 2016). Therefore, they shape the way that people and
organisations live, connect, consume and work (Licoppe & Smoreda, 2005). Through their
development, digital technologies have disrupted the traditional business landscape (Hansen & Siam
2015). To remain competitive, firms must not only apply these technologies but also rethink how they
operate (Andal-Ancion, Cartwright & Yip, 2003; Early, 2014). Over the years, organisations such as
Amazon and Google have successfully incorporated these digital technologies into their business
models. Meanwhile, firms such as Kodak and Polaroid Corporation have failed to initiate their digital
journeys and have consequently become outdated in their core business.
A substantial number of organisations have experienced pressure to change to meet customer demands
and remain competitive (Westerman et al., 2011). In an attempt to adapt, firms have often implemented
digital transformation initiatives that focus on technological solutions, such as those of a social, mobile,
analytical or cloud-based nature (Bharadwaj et al., 2013). However, firms that have aimed to digitally
transform have often lacked comprehensive signposts to guide them (Westerman, Tannou, Bonnet,
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Ferraris & McAfee, 2012). Traditional companies, which are older, larger and burdened with inflexible
legacies, have experienced even greater difficulties (Soule, Puram, Westerman & Bonnet, 2016).
Despite the importance of digital transformation, firms should shift their attention towards digital
maturity, as it can enhance their chance of adapting to an increasingly digital environment (Kane, 2017).
Digital transformation centres on the adoption of business processes and factors to compete effectively
in a digital world. In this context, the concept ‘transformation’ is complex, as it implies that firms
instantly become digitally adept. Nevertheless, firms should concentrate on responding to the
competitive environment in an agile way (Kane, Palmer, Nguyen-Phillips, Kiron & Buckley, 2017).
Since this goal is in line with digital maturity, the remainder of the paper studies this concept. Digital
maturity indicates how extensively firms have systematically adjusted to ongoing digital change (Kane
et al., 2017). The concept combines two distinct yet related dimensions, namely digital intensity and
transformation management intensity (Westerman et al., 2012). The first dimension is based on a firm’s
advanced digital capabilities in comparison to its competitors or relative to the rising expectations of
customers and employees. The latter reflects how a company envisions and manages its move into the
digital future. Together, these two dimensions determine the maturity level of an enterprise.
Fitzgerald, Kruschwitz, Bonnet and Welch (2014) have measured digital maturity through a survey
among 3,500 business executives, managers and analysts. They asked respondents to imagine an
organisation that was transformed by digital technologies and capabilities and subsequently rank their
own company in comparison to this ideal firm. Based on the results, three digital maturity groups were
created: ‘early’, ‘developing’ and ‘maturing’. Furthermore, the research paper has compared digitally
mature companies to their less mature peers and identified remarkable differences. For instance, firms
that were mature in the digital intensity dimension improved revenues through their existing assets.
Based on measures such as revenue per employee and fixed asset turnover, these firms outperformed
less mature firms by six percent. Moreover, organisations that were mature in transformation
management intensity were more profitable, as investments were aligned in a common direction.
Measures such as the earnings before interest and taxes (EBIT) margin and net profit margin indicate
that these firms are 9% more profitable. ‘Digital masters’ outperformed peers in both dimensions and
generated 9% more revenue and 26% more profit by comparison. Moreover, they achieved 12% higher
market valuations. Since every industry hosts ‘digital masters’ who are able to outperform less mature
competitors, firms across industries have been driven to advance their digital maturity level (Kane,
Palmer, Nguyen-Phillips, Kiron & Buckley, 2017).
Unfortunately, a significant number of firms possess neither the knowledge nor the skills to increase
their digital maturity (Westerman et al., 2012). Although consultancy-related studies have indicated the
relevance and potential of digital maturity, comprehensive academic literature on this concept is lacking
(Piccinini, Gregory & Kolbe, 2015). As a result, digital maturity has remained a ‘buzzword’ instead of
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a concrete, usable concept. In addition, various research papers have neglected to address the effects of
industry-specific factors on digital maturity, which highlights another gap in the literature. In
conclusion, academic research must focus on consolidating factors that affect digital maturity as well
as the industry-specific factors that moderate this relationship.
1.2 Problem statement
Adjusting to digital market environments and reaping the benefits of digital technologies to enhance
business operations are vital for every organisation. Moreover, various research papers have discussed
the benefits of digital maturity, such as improved firm performance (Iansiti & Lakhani, 2014). For
instance, firms with a mature digital intensity level employ technology that gather data in real time,
which allows them to create personalised customer offerings and increase revenue. Nevertheless, only
a small number of firms have made fundamental changes to enhance digital maturity (Kane et al., 2017).
According to research by the Massachusetts Institute of Technology (MIT) Center for Digital Business
and Capgemini Consulting, only 15 percent of respondents were digitally mature (Fitzgerald et al.,
2014). On the other hand, 65 percent of the companies were ranked as Beginners’ and thus possessed
low digital maturity.
Despite increasing acknowledgement of the importance of digital maturity, a substantial number of
firms have failed to enhance their maturity levels. This trend is visible within all sectors, as every
industry hosts Beginners (Andriole, 2017). A lack of guidance and absence of best practices have mainly
induced this struggle (Westerman et al., 2012). For instance, several research papers have not discussed
the journey to become digitally mature; they have only indicated that top management should initiate
and co-ordinate digital transformation (Kane, Palmer, Phillips, Kiron and Buckley, 2015). In contrast,
other studies have initiated a more relevant discourse, as their papers mention that firms should align
their culture, people, structure and tasks in order to drive digital transformation (Kane, Palmer, Phillips,
Kiron and Buckley, 2016; Westerman et al., 2012). Although the academic literature includes a wide
array of influencing factors, it does not provide a consolidated overview or practical guidance.
Therefore, it should be clarified which influencing factors affect digital maturity. At the same time,
cloud providers such as Microsoft and Amazon have stated that cloud computing positively impacts
digital maturity. Nevertheless, this relationship has not been validated from an academic standpoint. In
view of this, this master thesis studies the impact of cloud computing on influencing factors in order to
assess its effect on digital maturity. Since this research was conducted in co-operation with Microsoft,
it restricts cloud computing to the cloud solution Microsoft Azure. Lastly, academic research has not
differentiated between industries when elaborating on the factors that drive digital maturity.
Nonetheless, industry-specific factors, such as regulation, might impede the implementation of factors
that could drive digital maturity (Agarwal, Gao, DesRoches & Jha, 2010). Accordingly, this research
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mentions industry-specific factors that moderate this relationship and subsequently conducts a
comprehensive discussion of their impact. Figure 1 visualises the above-mentioned relationships.
Figure 1. The conceptual framework
1.3 Research question
In order to address the problem statement in Section 1.2, the following research question was
formulated.
How does Microsoft Azure impact digital maturity and consequently affect firm performance in
different industries?
To answer the main research question, multiple sub-questions are devised.
▪ Sub-question 1: How to conceptualise digital maturity?
▪ Sub-question 2: How does digital maturity impact firm performance?
▪ Sub-question 3: What factors influence digital maturity?
▪ Sub-question 4: Which industry-specific factors moderate the relationship between the
influencing factors and digital maturity?
▪ Sub-question 5: How does Microsoft Azure impact the influencing factors and consequently
influence digital maturity?
1.4 Research method
Research is conducted to fulfil an exploratory, descriptive or evaluative purpose (Saunders, Lewis &
Thornhill, 2009). The present research paper embodies an explorative design since it discusses the
impact of Microsoft Azure on digital maturity and firm performance, and these relationships have not
been studied extensively (Yin, 2003). To explore these effects, this study carried out behavioural
science research to examine theory that elaborates on human and organisational behaviour (Hevner,
March & Ram, 2008).
Behavioural science applies seven research strategies (Ayanso, Lertwachara & Vachon, 2011).
However, the implementation of an exploratory research design excludes certain strategies. By contrast,
a case study strategy is feasible, as it can yield empirical descriptions and theory (Dubois & Gadde,
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2002; Eisenhardt & Graebner, 2007). Nevertheless, case study research requires academics to study
diverse sources, such as interviews and observations. During this study, time and resource constraints
inhibited the consultation of an extensive range of sources, but academic literature as well as internal
and external interviews were analysed to explore the connections of interest. Thus, this thesis should be
considered an interview-based study instead of a case study. Figure 2 visualises this bilateral research
design.
Figure 2. The research design
This thesis starts with a literature review to gather the necessary contextualising information and
determine the current status of academic research on the relationships between Microsoft Azure,
influencing factors, industry-specific factors, digital maturity and firm performance. Subsequently, it
conducts various interview studies to explore these relationships in more detail. Cross-interview
analysis is thus possible and could inform the modification of the above-mentioned relationships.
Chapter 4 elaborates on these research stages.
1.5 Research setting
This master thesis is limited to the Information Management domain and focuses on the topic of digital
maturity. As Figure 1 illustrates, the study deliberates the relationships between the variables of
Microsoft Azure, influencing factors, industry-specific factors, digital maturity and firm performance.
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It explores these relationships from an economic and managerial standpoint and thereby excludes
technology-related content. The thesis was developed in co-operation with Microsoft Nederland and
studies the impact of Microsoft Azure on digital maturity and firm performance in the Netherlands.
Therefore, the upcoming sub-sections discuss Microsoft Nederland and its cloud solution to provide a
more detailed overview of the research setting of this thesis.
1.5.1 Microsoft Nederland
Microsoft Nederland is a subsidiary of the Microsoft Corporation that focuses on one mission: to ‘make
the Netherlands become an icon in the world for digital success’. To this end, they focus on three main
ambitions: facilitating more personal computing, building the intelligent cloud and reinventing
productivity. These ambitions translate into a variety of consumer and enterprise services which include
software development (e.g. Visual Studio), product development (e.g. Surface Pro), internet searches
(e.g. Bing), mixed reality (e.g. HoloLens) and cloud computing (e.g. Azure). These products and
services are offered to small and medium-sized enterprises (SMEs) (e.g. Fagron), international
corporations (e.g. ING) and government institutions (e.g. Hollands Kroon) across industries that range
from healthcare to financial services. By providing these services and products to a diversified set of
customers, Microsoft Nederland aims to achieve their mission.
This thesis was developed in collaboration with the Cloud & Artificial Intelligence department of
Microsoft. This department drives the sales and implementation of Microsoft Azure and other product
offerings, such as the Windows Server and SQL Server. As such, this department supports clients along
their digital journeys. However, because the department’s current product propositions are based mainly
on generic case examples, clients may be sceptical about the positive impact of, for instance, Microsoft
Azure. Thus, this research evaluates the impact of Microsoft Azure on digital maturity and firm
performance. With the resulting academic evidence, the Cloud & Artificial Intelligence department
could more effectively support future client offerings.
1.5.2 Microsoft Azure
Microsoft Azure is a cloud computing service for building, testing, deploying and managing
applications and services through a network of data centres. These applications and services focus on
several topics, such as databases (e.g. Azure SQL Database), Artificial Intelligence (AI) and machine
learning (e.g. Machine Learning Studio), analytics (e.g. Azure Databricks) and mobile services (e.g.
application service) to help organisations overcome their business challenges. Hence, Azure provides
firms with technological solutions of a social, mobile, and analytical nature that are capable of driving
digital maturity.
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For instance, Azure Databricks allows companies to extract, transform, load and analyse data in order
to provide comprehensive insights regarding business processes and customer experiences. Meanwhile,
Azure Web Apps presents a mobile solution by which firms can deploy and manage web applications
without managing their infrastructure. This option simplifies the implementation of mobile services in
business processes. Moreover, the Internet of Things (IoT) Hub Documentation connects, monitors and
controls billions of IoT assets, which improves connectivity over the cloud. This research paper reviews
all the capabilities of Azure and explores their potential to stimulate digital maturity and consequently
impact firm performance.
1.6 Relevance
This study was conducted to complement the academic literature on digital maturity. It adopts a
practical focus to ensure relevance for Microsoft Nederland as well as other companies. The upcoming
sub-sections further describe the academic and practical relevance of this research paper by deliberating
its implications for the academic world and business environment.
1.6.1 Academic relevance
Digital maturity has gained relevance over the last decade (Kane et al., 2017). Nevertheless, academic
research has primarily involved brief decompositions of the term or the characteristics of digitally
mature organisations (Westerman & Bonnet, 2015). To advance present understandings of the concept
of digital maturity, additional research is necessary (De Carolis, Macchi, Negri & Terzi, 2017). Multiple
research papers have highlighted the benefits of digital maturity (Iansiti et al., 2014); however, they
have often noted a variety of overlapping or contradictory aspects of firm performance (Tolboom,
2016). Therefore, this paper consolidates these factors to provide one comprehensive overview of the
impact of digital maturity on firm performance. The academic literature has also indicated a myriad of
influencing factors that impact digital maturity (Kane et al., 2017; Gill & Van Boskirk, 2016). Such
influencing factors are distributed among a large number of papers and regularly conflict, which
increases the complexity of digital transformation (Kane et al., 2017). Therefore, this paper also
consolidates these factors into five overarching influencing factors, which reveal the elements that
stimulate digital maturity as well as their impact on the dimensions of digital intensity and
transformation management intensity.
Most academic literature has employed a cross-industry perspective (Zhu et al., 2006). Accordingly,
research on industry-specific factors is absent (Chiasson & Davidson, 2005). Since this thesis studies
the impact of industry-specific factors, it extensively addresses this literature gap. Finally, academic
research has neglected the impact of cloud computing on digital maturity, so the connection between
Microsoft Azure and digital maturity has not received academic attention. Therefore, the present study
investigates this relationship as well to complement the academic literature.
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1.6.2 Practical relevance
Academic journals, such as MIT Sloan Review and Information System Research, have published
various articles on digital maturity. Although certain consulting firms, including Capgemini and
Accenture, have increased their service offerings with regard to this topic, executives have continued
to encounter significant challenges along their digital journeys (Piccinini et al., 2015). Therefore, the
present study discusses the conceptualisation of digital mature in more detail. Executives should be able
to assess their organisation’s digital maturity and subsequently plan their digital transformation. As
mentioned earlier, this research consolidates all firm performance aspects to determine the impact of
digital maturity improvements on firm performance. Organisations should realise how digital maturity
influences their firm performance and apply this knowledge to generate business value through digital
transformation. In addition, the present study consolidates and discusses the influencing factors of
digital maturity. The resulting insights can allow executives to avoid becoming distracted by the wide
array of options and instead concentrate on developing five comprehensive factors to advance in both
digital maturity dimensions. Accordingly, organisations can dedicate their resources to a small selection
of initiatives instead of exhausting their assets to pursue a wide variety of options.
This thesis also discusses the effects of industry-specific factors on the connection between the
influencing factors and digital maturity. With this knowledge, organisations can more clearly
understand the impact of industry-specific factors and consequently become more capable of driving
digital transformation while taking industry-specific factors into consideration. Moreover, since the
study validates the indirect impact of Microsoft Azure on digital maturity, it might motivate
organisations to adopt this cloud platform and enhance their digital maturity. Finally, Microsoft
Nederland can utilise the findings to strengthen their cloud propositions, which could not only generate
more sales but also provide enhanced support for the digital transformation of their clients.
1.7 Outline
This chapter has provided an introduction to the research topic. Next, Chapter 2 reviews the existing
knowledge base via an extensive literature study. To this end, it delineates the variables of influencing
factors, industry-specific factors, digital maturity and firm performance and subsequently discusses
their associated relationships. Chapter 3 focuses primarily on Microsoft Azure to determine its impact
on the influencing factors and digital maturity. Chapter 4 then discusses the research design to create
an overview of the data collection and analysis processes. Afterwards, Chapter 5 describes the results
of the analysis, and Chapter 6 presents the main conclusions of the master thesis on the basis of the
analyses in the previous chapter. Finally, Chapter 7 elaborates on the limitations of the study and
establishes recommendations for future research. A bibliography of all references as well as appendices
for additional information are available at the end of this paper.
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2. Literature review
This literature review elaborates on the relationship between the influencing factors, digital maturity
and firm performance. In addition, it discusses the influence of industry-specific factors on the impact
of influencing factors for digital maturity in order to consider industry differences. The existing
academic literature has indicated the importance of digital maturity by proposing a wide array of
definitions and digital maturity models. Nevertheless, it has not identified the most comprehensive
definition and maturity model for achieving construct clarity and conceptualising digital maturity
(Remane, Hanelt, Wiesboeck & Kolbe, 2017). Research has also been inconclusive with respect to the
factors that induce digital maturity and its effect on firm performance (Westerman et al., 2012;
Westerman, 2018). Lastly, existing research has emphasised cross-industry perspectives and therefore
excluded the effect of industry-specific factors (Agarwal et al., 2010).
The following sections address the above-mentioned topics. Thereby, they answer the first four research
questions. This extensive literature review consolidates and complements the academic literature on
digital maturity and can provide business executives with a more comprehensive understanding of this
topic.
2.1 Research question 1: digital maturity
In recent years, organisations in every sector have launched initiatives to explore new digital
technologies that involve mobile services, social media, the cloud and analytics (Matt, Hess & Benlian,
2015). Such initiatives have frequently involved the transformation of business operations, products,
services, organisational structures and management concepts (Mueller, Baer, & Weber, 2006), which
has resulted in alterations to existing business models and the creation of new ones (Bharadwaj et al.,
2013). This development is often referred to as ‘digital transformation’ (Fitzgerald et al., 2014).
According to Westerman et al. (2011), digital transformation refers to ‘the use of technology to radically
improve performance or reach of enterprises’ (p. 5). Hence, companies have implemented technologies,
such as analytics and social media, to alter customer relationships, internal processes and value
propositions. Kane et al. (2015) support this definition, as their study has framed digital transformation
as the ability to reimagine an organisation through digital means.
To account for the phenomenon of digital transformation, the academic literature has developed the
concept of digital maturity. Despite various equivalent terms, such as digital readiness and digital
dexterity, digital maturity is the predominant term in this master thesis (Jahn & Pfeiffer, 2014; Soule et
al., 2016). This study adopts the definition by Fitzgerald et al. (2014), who have described digital
maturity as ‘the digital initiatives undertaken, and the leadership capabilities implemented to drive
digital transformation’. Digital maturity is a key concept for further academic inquiry, as insights into
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digital progression permit a more profound understanding of this enduring phenomenon (Tilson,
Lyytinen & Sørensen, 2010). Construct clarity is needed to realise this knowledge-building potential
(Suddaby, 2010). The upcoming sub-sections comprehensively explain the definition of digital maturity
and its constituting parts to answer the first research sub-question of this thesis, ‘How to conceptualise
digital maturity?’ Subsequently, they elaborate on the selected concept and discuss digital maturity
archetypes.
2.1.1 How to conceptualise digital maturity?
In order to conceptualise digital maturity, construct clarity is imperative (Suddaby, 2010). The
definition of digital maturity was derived by examining various studies and choosing the most
convenient option. In addition, its constituting parts were selected by studying digital maturity models.
A maturity model reflects the progress of an object of interest towards a specific target state (Lahrmann,
Marx, Mettler, Winter & Wortmann, 2011). The concept refers to the degree of completion of a desired
transformation and can be applied to the context of a firm’s digital transformation (Remane et al., 2017).
The academic literature contains several digital maturity models that can support executives in
measuring their firm’s digital maturity. For instance, Valdez-de-Leon (2016) has developed a one-
dimensional digital maturity model that is based on six successive maturity stages: not started, initiating,
enabling, integrating, optimising and pioneering. Likewise, Lichtblau et al. (2015) have employed a
digital maturity model that focuses on six consecutive maturity phases and the six digital maturity
archetypes of outsider, beginner, intermediate, experienced, expert and top performer. Hence, digital
maturity models enrich the concept of digital maturity by clarifying its underlying items. As such, these
models can facilitate the conceptualisation process of digital maturity.
Since the literature review by Remane et al. (2017) is the most comprehensive analysis of digital
maturity models, it forms the foundation of this research. Their systematic literature review has
considered an initial set of 20 studies on digital maturity models. To account for recently published
articles, the study included additional sources, which resulted in a final data set of 25 studies. The
present study also reduced the data set by excluding sources that do not define digital maturity. On the
other hand, it did include more recent publications to enhance both its academic and practical relevance.
As Table 1 indicates, this filtering process yielded a data set of 14 studies.
11
Table 1. The literature on digital maturity
Reference Research strategy Definition of digital maturity Academic Digital maturity archetypes1 Archetype linearity2 Archetype dimensions3
Back & Berghaus
(2016)
Interview and survey Digital maturity provides insights into the level of digital transformation
within an organisation.4
Yes - - -
Catlin et al. (2015) Survey Digital maturity reveals a firm’s digital performance in today’s business
environment. 4
No Laggards, emerging leaders and
established leaders
Linear Digital quotient
Danaher (2018) Survey Digital maturity indicates the prevailing mentalities and behaviours with regard to digital.4
No Reactive, organised, digitised, connected and intelligent
Linear Digital maturity level
Fitzgerald et al.
(2014)
Survey A combination of technology-enabled initiatives and technology
management decide an organisation’s ability to digitally transform.4
Yes Beginners, conservatives, fashionistas
and differentiators
Non-linear Digital intensity and
transformation management
intensity
Gill & VanBoskirk
(2016)
Survey The digital capabilities of a firm to address cultural, organisational,
technical and insight challenges
Yes Sceptics, adopted, collaborators and
differentiators
Linear Digital maturity level
Kane et al. (2017) Interview and Survey
How organisations systematically prepare to adapt consistently to ongoing digital change
Yes Early, developing and differentiators Linear Digital maturity level
Lichtblau et al.
(2015)
Survey The assessment of an organisation’s readiness to progress towards
industry 4.0.4
No Outsider, beginner, intermediate,
experienced, expert and top performer
Linear Digital readiness
Schumacher, Erol &
Sihn (2016)
Case study Digital maturity indicates organisational and technological capabilities
and adequate strategies to develop them.
Yes - - -
Schreckling &
Steiger (2017)
Literature analysis The ability to leverage digital potential on an ongoing basis and integrate
it within an enterprise’s business model
Yes - - -
Soule et al. (2016) Interview and Survey A sustained ability to rapidly take advantage of emerging digital possibilities
Yes Early in transition, transition underway and digital dexterity threshold
Non-linear Digital dexterity and Digital capabilities
Uhl & Gollenia
(2016)
Literature analysis The assessment of a firm’s digitalisation approach with regard to their
culture, leadership and values4
Yes Initial, reactive, defined, managed and
excellence
Linear Digital maturity level
Valdez-de-Leon
(2016)
Interview A firm’s digitalisation focus that indicates its capability of driving digital
transformation throughout the organisation4
Yes - - -
Westerman et al.
(2011)
Interview A combination of digital intensity and transformation management
intensity that can drive digital transformation4
No
Beginners, conservatives, fashionistas
and digirati
Non-linear Digital intensity and
Transformation
management intensity
Zhu (2015) Literature analysis Digital maturity indicates whether organisations possess digital
capabilities to drive enterprise-wide performance.
Yes - - -
1 This column indicates which digital maturity stages each research paper adopts. 2 This column indicates the assumption of each research paper regarding how firms progress in their digital maturity. 3 This column indicates the opinion of each research paper on which digital maturity dimensions comprise digital maturity. 4 This research paper did not indicate a definition on digital maturity; therefore, a new definition was composed based on its content.
12
Digital maturity definition
Table 1 summarises various studies on digital maturity by noting two relevant items: their respective
definitions of digital maturity and associated digital maturity model. To determine the most
comprehensive definition, various selection criteria were adopted. First, the digital maturity definition
must only be accepted from an academic research paper; using another type of source would negatively
impact the validity of the literature review (Westerman et al., 2012). Second, digital maturity should
not only function as an assessment tool to measure digitalisation but also as a driving factor of digital
transformation (Fitzgerald et al., 2014). Lastly, the definition should denote the underlying items that
comprise digital maturity, as it indicates how digital maturity is measured. Based on these criteria, the
study applies the following definition of Fitzgerald et al. (2014): ‘A combination of technology-enabled
initiatives and technology management that decide on an organisation’s ability to digitally transform’.
Digital maturity model
Digital maturity models are beneficial to management practice because they assist managers in
determining the current position of a company and identifying potential areas for improvement.
However, such classifications often suffer from significant shortcomings (Remane et al., 2017). First,
several studies on digital maturity models are non-academic. Moreover, most research papers have not
mentioned any archetypes and focused on digital maturity scores, which reduces their practical
relevance to a business environment. Most importantly, many of these studies have proposed a linear
transformation path, which would indicate that all firms in various industries adhere to an identical
digital transformation journey. The validity of this concept is questionable, as extant empirical research
indicates that digital transformation is context-specific and follows an idiosyncratic path (Lucas & Goh,
2009; Agarwal, Johnson & Lucas, 2011; Karimi & Walter, 2015). Thus, a linear digital transformation
path generalises the digital journey and could lead to poor management decisions. To arrive at a maturity
model that is capable of conceptualising digital maturity, such shortcomings were converted into
selection criteria. The selection process yielded one research paper that conforms to these criteria:
Fitzgerald et al. (2014). As a result, this study adopts both the definition and digital maturity model of
Fitzgerald et al. (2014) to provide construct clarity and conceptualise digital maturity.
2.1.2 Digital maturity concept
Managers in every industry face an incomprehensible array of digital opportunities. Several rapidly
progressing start-ups, such as Pinterest, and a few large, high-tech firms, including Microsoft, have
managed to take advantage of these opportunities and subsequently generate a digital advantage.
However, many traditional firms are not able to capture the benefits of digital transformation, as they
involve inflexible legacies and a lack of signposts. Thus, they struggle to become digitally mature
(Westerman et al., 2011).
13
Digital maturity is a combination of technology-enabled initiatives and technology management that
determines an organisation’s ability to digitally transform (Fitzgerald et al., 2014). Moreover, it
indicates whether companies can adjust to ongoing change (Kane et al., 2017). Digital maturity depends
on two related dimensions: digital intensity and transformation management intensity (Westerman et
al., 2011; Westerman et al., 2012; Fitzgerald et al., 2014). Accordingly, firms should focus on these
dimensions to increase their digital maturity level and thereby drive digital transformation.
Digital intensity
Digital intensity concerns the implementation of technologically enabled initiatives (e.g. connected
products) that change how a firm operates (Westerman et al., 2012). These initiatives improve the
customer engagement and internal operations of a company. A firm’s digital intensity level measures
the maturity of their digital capabilities compared to competitors or relative to the rising expectations
of customers and employees (Westerman et al., 2011). As such, investments in cloud computing or
social media can advance a firm’s digital intensity level. Digital intensity also depends on the
connection among these digital capabilities. Therefore, investments should target digital capabilities
that can be combined, as they yield a more substantial lift in digital intensity. At the moment, firms in
all industries are investing in relevant digital initiatives, but such investments are often uncoordinated
and duplicative, which wastes resources (Fitzgerald et al., 2014).
Transformation management intensity
To mature in the second dimension of transformation management intensity, companies must develop
leadership capabilities that are vital to drive digital transformation. Transformation management
intensity involves four interrelated leadership capabilities: vision, governance, engagement and IT-
business relationships (Westerman et al., 2012). In this dimension, vision is crucial to shape a new
future, while governance and engagement guide the course, and IT-business relationships are developed
to facilitate technology-based changes. Through a combination of top-down leadership and bottom-up
innovation, these capabilities work together to promote ongoing digital transformation. However, many
firms lack one of these two items and are thereby hindered in their digitalisation (Kane et al., 2015).
2.1.3 Digital maturity types
The dimensions of digital intensity and transformation management intensity determine digital
maturity. Variation in maturity in these dimensions results in four digital maturity archetypes Beginners,
Fashionistas, Conservatives and Digirati (Westerman et al., 2012). Figure 3 details these archetypes.
14
Figure 3. The digital maturity archetypes (Westerman et al., 2012)
Beginners
Firms in the lower-left quadrant of Figure 3 are considered Beginners. These companies do not focus
on advanced digital capabilities but are mature in more traditional technologies, such as enterprise
resource planning (ERP) systems. Moreover, they are characterised by an immature digital culture, a
weak digital vision and a management team that is sceptical of the business value of advanced digital
technologies. Therefore, both their digital intensity and transformation management intensity are low.
Fashionistas
Fashionistas experiment with advanced digital features, such as social and mobile elements, cloud
technology and analytics. Nevertheless, digital technologies are often implemented without
consideration of synergies. With the addition of immature governance models, a lack of coordination
and a focus on non-aligned silo-structures, most of these technologies do not create business value
(Westerman et al., 2013). As such, fashionistas are motivated to drive digital change but lack effective
transformation management capabilities.
15
Conservatives
Conservatives are located in the bottom-right quadrant of Figure 3. These companies understand the
need for a unified vision, a corporate culture and strong digital governance to ensure an alignment of
digital investments across business silos. They also focus on attracting digital talent and building a
comprehensive digital strategy. Nevertheless, since their management teams are sceptical of the
business value of advanced digital technologies, this approach overlooks valuable opportunities to
increase digitalisation.
Digirati
Digirati truly understand how to drive digital transformation by combining strong governance,
engagement and an overarching digital vision with adequate investment in new digital opportunities.
With this strategy, a focus on vision and engagement fosters a digital culture that is capable of
envisioning and implementing changes. Moreover, investment in digital initiatives together with strong
governance models impart competitive advantage to Digirati. In view of these traits, such firms are
considered mature in both dimensions.
In conclusion, digital maturity encompasses a combination of technology-enabled initiatives and
technology management that determines an organisation’s ability to drive digital transformation. The
concept combines the interrelated dimensions of digital intensity and transformation management
intensity, which establish a firm’s digital maturity. Variance in maturity in these dimensions results in
the above-mentioned digital maturity archetypes. These insights address the first research question of
this thesis: ‘How to conceptualise digital maturity?’ The next section discusses the impact of digital
maturity on firm performance.
2.2 Research question 2: firm performance
As Section 2.1.1 has indicated, firms follow diverse routes to digital maturity (Westerman, 2018). For
instance, Asian Paints focused on governance, vision and engagement to unify their silo-focused
business. To this end, they financed investments in technology-enabled initiatives to transform internal
operations and customer engagement. Meanwhile, Nike reversed this process and started to build digital
intensity in silos. They additionally implemented transformation management capabilities to link these
silos and generate synergies.
The most prospective incentive for increasing digital maturity is a potential uplift in firm performance
(Iansiti & Lakhani, 2014). A research study by Capgemini Consulting and the MIT Center for Digital
Business supports this claim, as the studies reveal remarkable differences between mature companies
and their less mature counterparts. Moreover, Matt, Hess and Benlian (2015) have mentioned the
positive influence of digitalisation on sales, productivity, value creation and customer interaction, and
16
Zhu (2015) has suggested the existence of substantial financial performance differences between
‘digital masters’ and their less mature competitors. Table 2 provides an overview of these and other
studies that elaborate on the positive impact of digital maturity on firm performance. Such insights
confirm the positive relationship between these variables from an academic standpoint.
Nevertheless, the existing literature has not adequately consolidated the aspects of firm performance
that are influenced by digital maturity. For instance, Fitzgerald et al. (2014) have focused mainly on the
increase in financial performance, whereas Uhl and Gollenia (2013) have identified its positive impact
on customer centricity. Meanwhile, Li (2015) have indicated the effect of digitalisation on interface
improvements, which stimulates partners and competitor interactions. To clarify the relationship
between digital maturity and firm performance, the upcoming sub-sections discuss the performance
aspects that they positively influence and explains how digitalisation induces such effect. The resulting
insights answer the second research question of this master thesis: ‘How does digital maturity impact
firm performance?’
2.2.1 How does digital maturity impact firm performance
Section 2.1.1 has presented a literature review on digital maturity which resulted in a data set of 14
papers (see Table 1). Since this section addresses the effects of digital maturity, it also cites a substantial
amount of these studies. However, it includes other sources to improve the rigor and validity of the
review. To identify these sources, virtually equivalent terms, such as ‘digital readiness’, ‘digital
enterprise’ and ‘digital transformation’, were used as keywords to search across various databases (e.g.
World Cat and Google Scholar). Furthermore, these search results were extended via forwards and
backwards referencing (Webster & Watson, 2002). This process yielded a data set of 19 studies, which
Table 2 summarises.
Table 2. The impact of digital maturity on firm performance
Reference Research strategy Concept How does digital maturity impact firm performance?
Agarwal et al. (2010) Literature analysis Digital
transformation
Digital transformation can lead to lower costs, higher revenues and
improved productivity.
Andal-Ancion et al. (2003) Case study Digital maturity Increasing digital maturity level improves the personalisation of
products and services.
BCG (2018) Survey Digital maturity By taking the steps to become more digitally mature, a company can
boost their cost efficiency, time to market, product quality and market share.
Bughin, LaBerge & Mellbye
(2017)
Survey Digital maturity Digital winners outperform less digitised firms based in three
measures: revenue growth, EBIT growth and return on digital
investment.
Fitzgerald et al. (2014) Survey Digital maturity Digitally mature firms have a higher financial performance compared
to their less mature peers based on revenue creation, profitability and
market valuation.
Hägg & Sandhu (2017) Case study Digital maturity Digital maturity positively impacts financial performance through the use of digital technologies, such as social media, analytics and the
cloud.
Huang, Pan & Zuo (2012) Case study Digital maturity Digital maturity enables the virtualisation of work processes.
Therefore, employees can collaborate and share knowledge through
virtual platforms.
17
Jahn & Pfeiffer (2014) Case study Digital readiness The digital readiness of a firm influences the company’s success.
Therefore, digital maturity positively influences firm performance.
Kane et al. (2015) Interview and
survey
Digital
transformation
Digital maturity increases firm performance via improved customer
experiences, efficiency, innovation, decision making and business transformation.
Li (2015) Case study Digital
transformation
Digital transformation changes the eco-systems in which organisations
operate. As a result, new interfaces facilitate unprecedented
interactions between partners and competitors.
Neumeir, Wolf & Oesterle
(2017)
Literature analysis Digitalisation Digitalisation positively impacts five areas: customers, business
models, business processes, application systems and services, and
infrastructure.
Matt, Hess & Benlian (2015) Case study Digital transformation
The benefits of digitisation are manifold and include an increase in sales, productivity, value creation and customer interaction.
PWC (2016) Interview and
survey
Digital maturity By increasing digital maturity levels, firms will achieve revenue, cost
and efficiency gains.
Rishika, Kumar, Janakiraman &
Bezawada (2013)
Survey Digital
transformation
Because of digital transformation, the overall digital customer
experience is substantially improved.
Sia, Soh & Weill (2016) Case study Digitalisation Business digitalisation resulted in increased performance of DBS in
earnings, profit, share price and credit ratings.
Soule et al. (2016) Interview and
survey
Digital dexterity Combining digital dexterity and digital capabilities creates a digital
enterprise that is able to increase the enterprise’s performance.
Uhl & Gollenia (2016) Literature analysis Digital enterprise Companies should possess certain digital capabilities in order to
become a digital enterprise. These capabilities will result in customer
centricity, effective and knowledgeable workers, and operational
excellence.
Westerman et al. (2012) Survey Digital maturity Digital maturity drastically increases financial performance. More
digitally mature companies outperform their less mature peers in revenue generation, profitability and market valuation.
Zhu (2015) Literature analysis Digital maturity Digital masters achieve a significantly higher financial performance
compared to their less digitally mature competitors.
Table 2 encompasses a comprehensive literature review that confirms the positive impact of digital
maturity on firm performance. Since the academic literature lacks a consolidated overview of the
aspects of firm performance that are positively influenced by digital maturity, the table addresses a
knowledge gap. Moreover, it is also relevant from a practical standpoint, as firms must know how
investments in digital maturity affect their performance indicators.
2.2.2 Firm performance aspects
As Table 2 illustrates, various studies have described the effect of digital maturity on firm performance.
For instance, Matt et al. (2015) have reported that digital maturity improves sales, productivity, value
creation and interaction with customers. To summarise aspects of firm performance that are influenced
by digital maturity, a consolidation method needs to be developed. Tolboom (2016) has already
proposed that digital transformation influences seven organisational aspects: products and services,
customer segmentation, customer-organisation interaction, revenue models, internal processes,
partnerships, and resources and costs. Hence, these organisational aspects might function as overarching
factors of firm performance that are capable of consolidating the influence of digital maturity on firm
performance. However, this option is only valid if these organisational aspects can cover all the
influences of digital maturity on firm performance (see Table 2). Figure 4 demonstrates the selection
process to assess the feasibility of this option.
18
Figure 4. The selection process of firm performance aspects
Based on this process, five overarching firm performance aspects emerge: products and services,
internal processes, customers, partners and competitors, and financials. These aspects are capable of
representing all influences of digital maturity on firm performance. The sections below detail the
influence of digital maturity on each specific aspect.
Products and Services
Digital maturity substantially improves products and services (Li, 2015). The primary reason for this
effect is that digitalisation enables the creation of more personalised offerings which align with specific
customer preferences (Andal-Ancion et al., 2003). Moreover, firms can more quickly launch new
products and services, which significantly reduces their life cycle. As a result, products and services are
improved continuously (Fitzgerald et al., 2014). Lastly, digital devices and digital channels increase the
accessibility of products and services (Smith & McKeen, 2008). Digitally mature organisations are able
to harness the power of digital technology to align products and services with customer preferences,
improve them on a continuous basis and increase their accessibility (Hennig-Thurau et al., 2010). As a
result, they can refine their product and service offerings and thereby enhance firm performance.
Internal processes
Digital maturity also informs the internal processes of an organisation. Standardising internal processes
drives operational efficiency (Westerman et al., 2011). Thus, standardisation processes that implement
digital technologies are a top priority for many firms (Agarwal & Dhar, 2014). Digital technologies
such as analytics, robotics and augmented reality facilitate such standardisation (Bharadwaj et al.,
2013). For instance, DHL decided to equip all of their warehousing personnel with augmented reality
glasses, which standardised the order-picking process and improved productivity by 15%
(SupplyChain24/7, 2017). In addition, Inditex is implementing backroom robots to increase the
efficiency of their click-and-collect operations (Anderson, 2018). In such ways, digital maturity allows
for the implementation of advanced digital technologies that enhance internal processes.
19
Customers
Technologies such as analytics provide firms with an understanding of customer behaviour (Westerman
et al., 2011). Based on such insight, organisations can improve their market segmentation and
consequently extend offerings to each segment that more effectively fulfil customer needs (Dutta &
Biren, 2001). As a likely result, customers will be more willing to pay premiums for specific product
offerings (Li, 2015).
Digitally mature organisations also induce digital interactions with customers, which enhances
relationships between such organisations and their customers (Kurniawati, Shanks & Bekmamedova,
2013). For instance, social media and mobile marketing heightens customer awareness (Westerman et
al., 2011), which, in combination with other technologies, such as analytics, can improve and
personalise communication with customers. In addition, new interfaces allow customers to utilise a
wide array of distribution channels, which fosters omni-channel experiences (Verhoef, Kannan and
Inman, 2015). Thus, the integration of customer data and digital technologies can promote sales and
support organisational processes, which could in turn facilitate timelier and more accurate customer
service and thereby improve the digital customer experience (Kurniawati et al., 2013).
Partners and Competitors
Digital maturity also affects the eco-systems in which organisations operate (Li, 2015). Digital
technologies enable the creation of interfaces that are capable of facilitating new interactions with both
partners and competitors (Bharadwaj et al., 2013). Therefore, they intensify collaboration among
parties. For instance, the implementation of SAP Ariba can improve the buyer-supplier relationship
within supply chains by providing solutions to achieve more effective co-operation. Moreover, with
cloud-based technologies, such as Microsoft Azure, organisations can share data and digital services,
which permits even closer collaboration. Thus, digitally mature firms implement technologies that
construct end-to-end eco-systems that encourage collaboration among partners and competitors, which
can in turn improve firm performance.
Financials
Digital maturity significantly influences firm performance. Digitally mature firms improve product and
service offerings as well as their interactions with customers. Furthermore, with more accurate customer
insights, firms can segment markets and align offerings with customer preferences. Digital maturity can
also support the standardisation and integration of internal processes, which increases efficiency. Lastly,
the use of new interfaces and shared digital services promotes closer co-operation with partners and
competitors.
20
These aspects of firm performance influence the financials of an organisation. For example, enhanced
product and service offerings positively impact a firm’s revenues (Andal-Ancion et al., 2003), and more
fruitful interactions with customers, partners and competitors improve sales levels as well. Moreover,
digital maturity reduces costs since, for example, efficiency gains in internal processes mitigate
overhead costs (Huang et al., 2012). Moreover, collaboration and the sharing of knowledge through
virtual platforms reduces personnel costs (Nambisan, 2002). In this regard, research by Kane et al.
(2017) has confirmed that digitally mature firms outperform their less mature competitors in terms of
revenue, profit and market valuation, which implies that digital maturity increases financial
performance.
The previous sub-sections have indicated that digital maturity improves numerous facets of firm
performance. After consolidating such aspects, it is apparent that digitally mature organisations are able
to stimulate performance in four categories: products and services, internal processes, customers, and
partners and competitors. Such improvements can enhance an organisation’s financials in terms of
revenues, costs and profits. These insights address the second research question of this study: ‘How
does digital maturity impact firm performance?’ Therefore, it is relevant to elaborate on the influencing
factors of digital maturity to guide organisations in their digital journeys.
2.3 Research question 3: influencing factors
As Section 2.2.2 has illustrated, digital maturity positively influences five firm performance aspects:
products and services, internal processes, customers, partners and competitors, and financials. Thus,
organisations can benefit from a higher digital maturity level. Despite increasing evidence of the
advantages of digital maturity, many organisations still lack a digital focus (Andriole, 2017). In their
study, Fitzgerald et al. (2014) interviewed executives from 450 large companies to investigate their
digital maturity. Their results indicate that 65% of all interviewed companies were Beginners, whereas
only 15% were Digirati. Research by Kane et al. (2017) has reported similar results, as their survey
responses convey that 34% of companies belonged to the ‘early digital maturity’ grouping and 42%
were in the ‘developing digital maturity’ grouping, while only 24% comprised the ‘maturing digital
maturity’ grouping. Andriole (2017) has also observed this trend across industries, as every sector hosts
Beginners.
According to Westerman et al. (2012), this trend is induced by two factors: a lack of guidance and an
absence of best practices. Kane et al. (2015) have not elaborate on the digital journey. They only
mentioned several factors that might positively impact digital maturity. Kane et al. (2017) presented a
more fruitful discussion in advising companies to align their structure, people, culture and tasks to
become digitally mature. Sia et al. (2016) have more intensively addressed the topic by identifying the
following three factors that can increase digital maturity: cultivating leadership, developing agile and
21
scalable operations, and incubating and accelerating emerging digital innovations. Nonetheless,
academic literature has not provided a consolidated overview of the influencing factors of digital
maturity. Instead, studies have noted a variety of influences, which yields an inconclusive set of
influencing factors. Consequently, firms significantly lack practical guidance for driving digital
maturity. In view of this gap, the upcoming sections consolidate the influencing factors into a set of
overarching factors. The paper subsequently elaborates on such factors to answer the third research
question of this master thesis: ‘What factors influence digital maturity?’
2.3.1 What factors influence digital maturity?
Sections 2.1.1 and 2.2.1 have conducted literature reviews on the conceptualisation of digital maturity
and its impact on firm performance. Since this section elaborates on the influencing factors of digital
maturity, it recalls some of the same research. However, many studies have highlighted only the benefits
of digital maturity and only briefly decomposed the term. Therefore, this review incorporates
complementary studies that focus on the factors that induce digital maturity. Since the search term
‘digital maturity’ did not yield a sufficient number of sources, practically equivalent terms such as
‘digital transformation’, ‘digitalisation’ and ‘digital dexterity’ were also applied as keywords to search
relevant databases, including Google Scholar, World Cat, Infopedia (i.e. the Microsoft database) and
JSTOR. This process culminated in a data set of 15 studies, which Table 3 summarises.
Table 3. The influencing factors of digital maturity
Reference Research
strategy
Concept What factors influence digital maturity?
Agarwal et al. (2010) Literature analysis Digital
transformation
There are three major factors that influence healthcare information technology
(HIT) adoption and, thus, digital transformation: financial support from management, functionality and user willingness.
BCG (2018) Survey Digital maturity Research indicates three factors that positively influence digital maturity:
investments in digital technologies, digital experts and a digital culture.
Ehorus (2017) Survey Digital maturity Digital awareness, data analysis capabilities, digital leadership, technology
expenditures and a trained staff all positively impact digital maturity.
Fitzgerald et al. (2014) Survey Digital maturity Digital maturity is based on the factors of urgency, funding and support, vision,
governance, culture and digital leadership.
Gill & Van Boskirk (2016)
Survey Digital maturity Digital maturity can be determined by the maturity level of many factors. Overall, culture, technology, organisational alignment and insights on data influence digital
maturity.
Hägg & Sandhu (2017) Case study Digital maturity In order to increase their digital maturity level, firms should direct their attention
towards the factors of digital leadership, digital strategy and experimentation.
Kane et al. (2015) Interview and
survey
Digital
transformation
Digital maturity is driven by a clear digital strategy, top-down digital change, the
ability to close the skill gap and a culture that is conducive to digital
transformation.
Kane et al. (2017) Interview and
survey
Digital maturity Several key factors stimulate digital maturity: the development and organisation of
workforces based on collaboration, the cultivation of digitally minded cultures, the
scaling of small experiments to enterprise-wide initiatives, the attraction of talent
and secure leaders with a vision, digital capabilities and the digital strategy.
Matt et al. (2015) Case study Digital
transformation
Digital transformation should be governed by a digital strategy that serves as a
central concept to integrate the entire co-ordination, prioritisation and
implementation of digital transformations within firms.
Mettler & Pinto (2018) Interview and survey
Digital maturity Digital maturity is positively influenced by hardware and software, digital development of personnel, and digital operations and maintenance.
PWC (2016) Interview and
survey
Digital
transformation
Digital transformation is driven by a digital culture, leadership from the c-suite,
innovation, IT capabilities and the ability to attract, train and retain digital talent.
22
Sia, Soh & Weill
(2016)
Case study Digitalisation DBS bank advanced their digital transformation via three factors: cultivating
leadership, developing agile and scalable operations, and incubating and
accelerating emerging digital innovations.
Soule et al. (2016) Interview and survey
Digital dexterity Digital dexterity is encouraged by a digital mindset and three organisational dimensions: digital practices (e.g. digitised operations), a digital workforce and
digital resources (e.g. collaboration tools).
Westerman et al. (2011) Interview Digital maturity Firms are able to increase their digital maturity level when they develop a digital
vision, invest in digital transformation initiatives and lead change from the top.
Westerman et al. (2012) Survey Digital maturity Digital maturity is supported by a transformative vision, digital governance,
engagement and collaboration within the organisation, and IT-business
relationships.
Table 3 summarises the detailed literature review on the factors that impact digital maturity. Although
it specifies the influencing factors that have emerged from many papers, a comprehensive overview of
the overarching factors of digital maturity is absent. In view of this, all influencing factors should be
consolidated into a set of overarching factors. This process can complement the academic literature on
digital maturity and provide firms with practical guidance to influence this concept.
2.3.2 Consolidated influencing factors
Table 3 summarizes various papers, focused on the influencing factors of digital maturity. For example,
Agarwal et al. (2010) have mentioned the impact of financials, functionality and user willingness on
HIT adoption and, in turn, digital transformation. Meanwhile, Ehorus (2017) has studied the influencing
factors of digital maturity and identified several factors, such as data analysis capabilities, digital
leadership, technology investments and digital awareness. A comparison of these studies reveals that
the academic literature presents overlapping factors in different terms. For instance, the influencing
factors of ‘data analysis capabilities’ (Ehorus, 2017) and ‘IT capabilities’ (Mettler & Pinto, 2018) both
refer to the development of digital capabilities. Therefore, all of the influencing factors of digital
maturity in Table 3 must be combined into a set of consolidated factors. Figure 5 visualises this
consolidation process.
Figure 5. The consolidation process of influencing factors
The process started with developing a list of influencing factors on the basis of Table 3. Subsequently,
these factors were consolidated according to their definitions in their respective papers. Thereby,
virtually equivalent factors were merged. For instance, the factors of ‘digital experts’ (BCG, 2018), ‘the
ability to close the skill gap’ (Kane et al., 2015) and ‘digital workforce’ (Soule et al., 2016) were
23
combined into the overarching factor of ‘digital talent’. This process yielded five overarching
influencing factors: digital talent, digital culture, digital technology, digital leadership and digital vision.
To impart validity to this consolidation process, Microsoft experts and Tilburg University (TiU)
professors conducted reviews. Based on their feedback, two adaptions were made. First, the factor of
digital talent was replaced by the term ‘digital workforce’, as organisations need to not only attract
digital talent but also train their existing workforce. Second, ‘digital capability’ was substituted for
digital technology to offer a more inclusive consolidation of the influences in Table 3. Based on expert
opinions from practitioners and academics, five overarching influencing factors were adopted. Table 4
lists these factors and their descriptions, and Appendix I contains a more detailed overview of this
process in terms of the initial set of influencing factors, the consolidation process and the review
process.
Table 4. The reviewed overarching influencing factors
Overarching influencing
factor
Description of overarching factor
Digital workforce The degree to which an organisation’s workforce is capable of implementing digital technologies
Digital culture The degree to which an organisation’s culture embraces digital to prompt innovation and collaboration
Digital capability The degree to which an organisation possesses digital capabilities
Digital leadership The degree to which an organisation’s management supports and propagates digital change
Digital vision The degree to which an organisation’s vision focuses on strategies and governance that drive digital transformation
The upcoming sub-sections discuss the impact of these overarching factors on digital maturity. The
findings can inform more detailed guidelines for improving digital maturity.
Digital workforce
An organisation’s workforce substantially influences their digital journey. For instance, executives
often feel pressured by employees to change digitally (Westerman et al., 2011). On the other hand,
including digital talent in their workforce can increase a firm’s ability to digitally transform (Soule et
al., 2016). As mentioned, the consolidation of all workforce-related influencing factors highlighted the
overarching factor of digital workforce. Moreover, a summary of all associated definitions resulted in
the establishment of a primary definition of the digital workforce factor as ‘the degree to which an
organisation’s workforce is capable of implementing digital technologies’.
The ability to attract, train and retain digital talent impacts an organisation’s digital maturity (Kane et
al., 2017; PWC, 2017). Digital talent enables organisations to take advantage of technological
advancements, which promote collaboration and innovation (Ehorus, 2017). Moreover, training
existing employees to use digital technology further contributes to digital maturity (Mettler & Pinto,
2018). In view of these benefits, firms should attract digital talent and train existing employees in order
to cultivate a digital workforce that is capable of applying digital technology. With this achievement,
24
organisations could effectively implement technologically enabled initiatives and, hence, advance their
digital intensity dimension.
Digital culture
Digitally mature organisations recognise the value of collaboration and innovation, which support
systematic adaptation to change in terms of technology, vision and strategy (Kane et al., 2015; Kane et
al., 2017). Accordingly, collaboration and innovation positively impact digital maturity. Soule et al.
(2016) have stated that the use of digital encourages collaboration and innovation. Kane et al. (2017)
have similarly mentioned the critical impact of digital on collaborative behaviour. Such findings suggest
that organisations should stimulate the use of digital to drive collaboration and innovation and thereby
positively impact digital maturity. To this end, they must develop a digital culture (PWC, 2016). Based
on the consolidation process in the previous section, this study defines digital culture as ‘the degree to
which an organisation’s culture embraces digital to create innovation and collaboration”.
According to BCG (2018), all digital champions have adopted three factors: investment in digital
capabilities, the recruitment of digital experts and a digital culture. These factors seem logical given
that a digitally averse culture is unlikely to adopt digital technology. In this regard, Blumenthal and
Tavenner (2010) have indicated that electronic health record (EHR) technology was not implemented
in digitally unfriendly environments. Moreover, since a digital vision cannot flourish within a digitally
averse culture, organisations should develop a culture that embraces the use of digital. Nevertheless, if
digital is not implemented to foster collaboration and innovation, then its positive impact will likely be
limited to operational silos. In such a case, companies can only reach the digital maturity state of a
Fashionista. Therefore, culture should not only focus on the use of digital but also apply it to generate
innovation and collaboration within organisations, as this approach can position companies to
continuously adapt to changing technologies, strategies and visions. These insights illustrate that digital
culture impacts both the digital intensity and transformation management intensity dimensions.
Digital capability
A survey by Kane et al. (2017) has noted the positive effects of digital capabilities on the progression
of digital maturity. Specifically, the development of digital capabilities allows for a more seamless
digital journey. According to Westerman et al. (2014), digital capabilities concern three areas: customer
experience, operational processes and business models. For instance, data analytics capabilities permit
the implementation of technology-enabled initiatives, such as optimised pricing (Gill & VanBoskirk,
2016). In addition, go-to-market capabilities, including digital marketing, create possibilities for
personalisation (BCG, 2018). Meanwhile, cloud capabilities induce collaboration, which enhances
operational processes (Iyer & Henderson, 2010). Thus, digital capabilities positively impact the
implementation of technology-enabled initiatives, which in turn enhances customer engagement and
25
internal operations. All digital capabilities in combination determine the digital capability of an
organisation. Therefore, digital capability refers to ‘the degree to which an organisation possesses
digital capabilities’.
Nonetheless, firms do not simply develop digital capability (PWC, 2017). First, they must map which
capabilities they need to achieve a specific digital vision. Second, they should consider how to embed
these capabilities within a functional organisation. Lastly, firms should focus on so-called ‘capability-
generating practices’, such as digital assets and digital research and design (R&D) (Sandberg, 2014).
Following these steps, organisations should be able to acquire digital capabilities to carry out
technology-enabled initiatives. In this way, digital capability impacts the digital intensity dimension.
Digital leadership
According to Fitzgerald et al. (2014), support and funding from top management positively impact
digital maturity. Agarwal et al. (2010) have also noted that financial support that is focused on digital
advancement increases digital maturity. Top-down support additionally heightens the willingness of the
rest of the organisation to implement technology and adhere to an overarching digital vision (Hägg &
Sandhu, 2017). Executives should not only support digital change but also propagate the
implementation of digital. Accordingly, employees in digitally mature organisations are highly
confident in their leader’s digital fluency (Kane et al., 2015). This thesis refers to the combination of
these two factors as ‘digital leadership’, which can be defined as ‘the degree to which an organisation’s
management supports and propagates digital change’.
One of the differences between ‘digital leaders’ and ‘digital laggards’ is a digital leadership orientation
(Kane et al., 2015). A survey by Kane et al. (2017) has confirmed that 14% of all respondents regarded
digital leadership as the most pivotal factor of digital success. Digital leadership fosters leadership
capabilities that are necessary to drive digital transformation (Westerman et al., 2011; Westerman et al.,
2012). As such, digital leaders effectively engage employees by supporting and propagating digital
change. Digital leadership can also build IT-business relationships, which further stimulate technology-
based change. These effects illustrate that digital leadership has a beneficial impact on the
transformation management intensity dimension.
Digital vision
A survey by Westerman et al. (2011) has indicated that digitally mature companies have a strong
overarching digital vision. Thus, organisations must develop, evolve and communicate their digital
vision in order to drive digital transformation. Early communication with regard to a digital vision
prompts change and reduces organisational resistance (Westerman et al., 2012). The academic literature
has also reported a positive impact of digital strategy on digital maturity. For example, Kane et al.
26
(2015) have found that only 15% of digitally immature organisations developed a clear and coherent
digital strategy. In contrast, this figure was 80% among digitally maturing companies. Governance also
influences the digital journey of an organisation, as it manages and fosters digital advancement
(Westerman et al., 2012; Fitzgerald et al., 2014). Nevertheless, since digital vision is the major
determinant of a strategy and governance that pursue digital transformation (Gill & VanBoskirk, 2016;
Kane et al., 2017), this thesis defines digital vision as ‘the degree to which an organisation’s vision
focuses on strategy and governance that drives digital transformation’.
A strong digital vision frames future differences in the company (Kane et al., 2015). In this way, it
clarifies for employees which former assumptions will be no longer valid. In the long term, such effect
might not only counter activities that endanger an organisation’s digital journey but also energise
personnel to generate change themselves (Westerman et al., 2012). This highlights the difference
between Conservatives, who employ a vision to mitigate digitally averse behaviour, and Digirati, who
inspire employees to drive digital change. Thus, a digital vision supports the development of leadership
capabilities, such as governance and engagement, which suggests that it positively impacts the
transformation management intensity dimension.
The academic literature has identified a wide range of factors that can advance digital maturity.
However, these factors are distributed across a myriad of articles and often overlap in their descriptions.
Since a comprehensive set of overarching influencing factors is absent, all factors were consolidated
into the following five overarching influencing factors which stimulate digital maturity: digital
workforce, digital culture, digital capability, digital leadership and digital vision. Organisations should
internally cultivate these factors to drive digital transformation. This insight addresses the third research
question of this thesis: ‘What factors influence digital maturity?’ The upcoming section discusses
industry-specific factors, such as regulation, as they might moderate the relationship between the
influencing factors and digital maturity.
2.4 Research question 4: industry-specific factors
Fitzgerald et al. (2014) have indicated that a significant number of firms are not digitally mature. Their
study has developed four maturity archetypes for ranking firms by digital maturity level. Beginners
have the lowest digital maturity level, whereas Digirati are digitally mature. Survey responses reveal
that 65% of all companies belonged to the Beginner archetype, whereas only 15% were considered
Digirati. Andriole (2017) has further observed this trend across industries. Nevertheless, as Figure 6
illustrates, there are substantial digital maturity differences between industries. Within the high-
technology sector, 38% of all companies were Digirati, while only 17% percent were Beginners. By
comparison, the pharmaceutical industry is less digitally mature; within this sector, only 7% of all
companies are Digirati, and 33% are Beginners.
27
Figure 6. Digital maturity breakdown across industries (Westerman et al., 2012)
According to Kane et al. (2015), industries that were founded on technology include the most digitally
mature organisations. Specifically, the IT, telecom and entertainment sectors ranked among the most
mature industries, whereas the performance of construction, public and manufacturing sectors was
below average.
Agarwal et al. (2010) have noted that industry-specific factors, such as regulation, induce such maturity
differences. For instance, the heavy regulation of developments in EHR and payment systems
occasionally prevents their adoption (Blumenthal & Tavenner, 2010; Menon & Lee, 2000). The
financial services industry is also impacted, as compliance, confidentiality and security concerns deter
organisations from driving digital transformation (Singh & Hess, 2017). Incumbent banks are the most
affected sector, whereas the fintech industry has managed to negate these negative influences (Cuesta,
Ruesta, Tuesta & Urbiola, 2015). These insights demonstrate that industry-specific factors substantially
moderate the relationship between influencing factors and digital maturity.
Most of the academic research has not differentiated between industries (Zhu, Dong, Xu & Kramer,
2006). This lack of differentiation is evident from the narrow range of sectors that are studied in
Information System (IS) research as well as the infrequent consideration of industry-specific effects
(Chiasson & Davidson, 2005). As a result, organisations do not understand the effects of industry-
specific factors on the relationship between influencing factors and digital maturity. The upcoming
section discusses these factors and identifies the industries they impact to answer the fourth research
question: ‘Which industry-specific factors moderate the relationship between the influencing factors
and digital maturity?’
2.4.1 Which industry specific factors moderate the relationship between influencing
factors and digital maturity?
The previous sections have elaborated on the conceptualisation of digital maturity, its impact on firm
performance and the influencing factors that positively affect this phenomenon. These sections have
28
regularly cited academic literature with an emphasis on cross-industry perspectives and thus excluded
attention to the impact of industry-specific factors. Chiasson and Davidson (2005) have stated that IS
research has rarely considered industry perspectives despite their significant influence on IS activities.
In view of this, it is relevant to identify industry-specific factors that may partly determine the impact
of influencing factors on digital maturity.
According to Crowston and Myers (2004), there are three perspectives on industry-specific factors:
economic, institutional, and social and cultural. The institutional perspective considers the regulatory
framework that governs an industry (Chiasson and Davidson, 2005). The implementation of the General
Data Protection Regulation (GDPR) in Europe has significantly heightened the importance of the
institutional perspective. The regulation limits the use of various technologies (e.g. beacons), thereby
hindering the implementation of technology-enabled initiatives and negatively affecting digital
maturity. Therefore, the remainder of this section analyses the impact of institutional factors. Research
has indicated that institutional influences can be consolidated by focusing on the factor of ‘regulatory
compliance’, as it comprises sub-factors that include data security and privacy (Vliem, 2018).
Accordingly, this section discusses the influence of regulatory compliance on various industries. To
this end, concepts that include digital maturity as well as industry-related terms, such as healthcare,
were applied as keywords to search relevant databases (e.g. World Cat, Google Scholar). This search
yielded a data set of 16 studies, which Table 5 summarises.
Table 5. The institutional factors across industries
Reference Research strategy Industry Which industry-specific factors moderate the relationship between the influencing
factors and digital maturity?
Agarwal et al.
(2010)
Literature analysis Healthcare Regulatory compliance regarding data privacy and security hindered HIT adoption. As a
result, digital transformation was substantially limited within the healthcare sector.
Cortet, Rijks &
Nijland (2016)
Literature analysis Banking Credit institutions are subject to high regulatory requirements, which forces them to
optimise for regulatory compliance, security and resilience instead of agility and innovation.
Eling & Lehmann
(2018).
Literature analysis Insurance Regulation and security concerns impede the digitalisation of existing insurance firms
and prevent new firms from entering and disrupting this industry.
Goldschmidt
(2005)
Literature analysis Healthcare The adoption of EHR is negatively influenced by security, privacy and confidentiality
concerns as well as regulatory compliance.
Gruber &
Verboven (2001)
Mathematical
model
Telecom Regulatory decisions regarding spectrum licensing, competition and technical standards
reduce the adoption of mobile services, which impedes digital maturity in business environments.
Hausman, Pakes &
Rosston (1997)
Literature analysis Telecom Regulation negatively affects the introduction of new telecommunication services,
thereby impeding digitalisation and reducing the overall welfare gain.
Laursen & Salter
(2006)
Survey Manufacturing Innovation and digitalisation within the manufacturing industry is negatively impacted
by environmental, health, technical and safety regulations.
Lerer & Piper
(2003)
Literature analysis Pharmaceutical Regulation of e-health safety and health information systems is problematic and obstructs
developments in the pharmaceutical sector.
McDaniel & McLaughlin (2009)
Interview and survey
Utilities Despite the social and technological benefits of digital technology (e.g. smart grids), several security and privacy concerns have emerged that problematise their
implementation.
Murdoch & Detsky
(2013)
Literature analysis Healthcare The adoption of big data within healthcare will induce considerable privacy concerns. As
such, further developments will be restrained, which would negatively impact
digitalisation.
Nuechterlein &
Weiser (2007)
Literature analysis Telecom Regulatory compliance regarding competition prevents disruptors from entering. As a
result, digital developments will be slowed, which will negatively influence
digitalisation.
29
Sia, Soh & Weill
(2016)
Case study Banking Digital transformation within the financial services industry is negatively impacted by
regulatory compliance and data security concerns.
Sing & Hess (2017) Case study Banking The banking sector needs to comply with regulatory influences regarding confidentiality
and security, which harms the digital transformation of incumbent banks.
Westerman et al.
(2012)
Survey Pharmaceutical
insurance
Companies that operate within these industries focus on innovation with new
technologies. Nevertheless, many firms are limited by regulatory concerns.
Westerman, Bonnet
& McAfee (2014)
Survey Insurance Many insurance companies have been slow to adopt digital innovations in view of
regulatory challenges within the business environment.
Zhu et al. (2006) Survey Manufacturing
CPG
Data security may deter e-business diffusion and thus impede digitalisation. As a result,
companies could become reluctant to participate in online business.
Table 5 provides a comprehensive literature review on the effects of institutional factors. For instance,
Goldschmidt (2005) has mentioned that data security and privacy regulations negatively impacted the
healthcare sector, which in turn stalled developments in EHR and other technological advancements,
thereby impeding digital maturity. Meanwhile, Nuechterlein and Weiser (2007) have stated that
regulation protects existing telecom companies from new entrants; however, this barrier only hinders
digital development, which prevents this sector from achieving digital maturity. Thus, institutional
factors negatively impact the effect of influencing factors on digital maturity, though the academic
literature has not discussed the extent to which these factors affect the above-mentioned relationship.
Therefore, the same institutional factor might have a heavier impact on the healthcare sector than on
the banking industry. Research has also neglected the impacts of the institutional perspective in
comparison to those of the economic and social and cultural perspectives. Therefore, future research
must address these topics. As such, it is not possible to provide a comprehensive answer to the fourth
research question: ‘Which industry-specific factors moderate the relationship between the influencing
factors and digital maturity?’
30
3. Microsoft Azure
The master thesis studies the effect of technology on digital maturity improvement and consequently
firm performance enhancement. Therefore, this chapter elaborates on Microsoft Azure to contextualise
this cloud solution and its potential impact on digital maturity and firm performance. The first section
describes the characteristics of the cloud platform and a variety of solutions. It then deliberates the effect
of Microsoft Azure on the five influencing factors in order to consider its indirect impact on digital
maturity. Accordingly, this discussion answers the last research question of this master thesis.
Consequently, preliminary conclusions about the relationships between Microsoft Azure, influencing
factors, institutional factors, digital maturity and firm performance are created. Such findings offer a
basis of knowledge on which the qualitative research can build.
3.1 Introduction to Microsoft Azure
Microsoft Azure is the overarching platform of Microsoft’s cloud computing services and includes a
wide variety of solutions on which cloud computing is founded. With this programme, both
organisations and individuals can build, test, deploy and manage applications and services through a
network of data centres.
Azure is a productive, hybrid, intelligent and trusted cloud that is able to outperform many competitors
(e.g. Azure Web Services and Google Cloud). This cloud platform enables organisations to quickly
convert ideas into solutions, as it facilitates the development of applications and services with almost
any programming language (e.g. Java or NET). In combination with integrated tooling, unified data
management and a broad array of solutions, Microsoft Azure delivers unparalleled development
productivity. Consequently, it can substantially decrease the time-to-market of products, services and
applications, thereby granting organisations a first-mover advantage. Second, Azure is a hybrid cloud
that reduces complexity and risks when on-premise and cloud environments co-operate. Therefore,
organisations can consistently develop and deploy applications, seamlessly manage data, and deliver
integrated security and management across on-premise data centres and the public cloud. Third, Azure
is an intelligent cloud platform because it employs a comprehensive set of services and infrastructures
to build AI-powered experiences. As a result, data sources can be combined with AI services (e.g. Azure
Cognitive Services) to enable new possibilities for human-like intelligence. Finally, Microsoft
established security and privacy requirements for Azure to create a trusted and secure cloud
environment. Consequently, it complies with a significant number of international (e.g. GDPR),
industry-specific (e.g. ISO 27001) and domestic regulations (UK G-Cloud). In addition, third-party
audits validate the adherence of Azure to the stringent controls that these standards mandate.
31
Microsoft Azure also provides numerous and diverse solutions for areas such as customer facing apps,
internal business apps, the IoT and business analytics. Figure 7 visualises the dominant service areas
of Azure as well as several solutions within these areas.
Figure 7. The Microsoft Azure solutions
Organisations can implement and combine these solutions to support their business processes. For
example, Maersk combined solutions regarding the IoT, data warehousing and business intelligence to
gather data and generate insights in real time. As a result, they predicted the maintenance needs of
transportation vehicles and thereby reduced the chance of downtime. Moreover, HP adopted machine
learning and data warehousing solutions to meaningfully interpret customer data. Consequently, they
established a virtual agent that is capable of answering simple customer questions. In conclusion,
Microsoft Azure offers a productive, hybrid, intelligent and secure cloud environment in which
organisations can innovate with advanced digital solutions. These solutions can be implemented and
connected to support the digitalisation of business processes, thereby driving digital transformation.
3.2 Research question 5: Microsoft Azure
According to Microsoft, digital transformation impacts four organisational aspects: employees,
customers, operations and products. For instance, the implementation of Microsoft Teams can empower
employees to co-operate and innovate on projects, while customer engagement can benefit from Power
BI, as it enables organisations to derive valuable insights from customer data. Figure 8 illustrates the
pivotal role of Microsoft Azure within this transformational process.
32
Figure 8. The effects of Microsoft Azure on digital transformation
Microsoft Azure includes solutions such as Azure DevOps and Microsoft Teams to fuel collaboration
and innovation. Its governance mechanism, Azure Active Directory, also drives co-operation while
mitigating risks, such as data leaks. In this way, the cloud solution empowers employees by providing
collaborative and inclusive solutions. It also enables organisations to foster stronger customer
engagement. For instance, data warehousing and data analytics solutions can rapidly aggregate and
analyse customer data, which yields insights for targeting customers in a more personalised manner.
Moreover, these capabilities optimise internal operations, as in the case of Maersk’s adoption of Azure
solutions to enable predictive maintenance. Lastly, Microsoft Azure improves the speed of product and
service development and refinement. For example, Azure Data Bricks shortens feedback loops on
products and services, which drives continuous improvements. Azure also allows developers to create
and scale applications within days. In comparison, on-premise data centres require weeks to produce
similar applications, as they must procure and connect hardware and software before conducting any
development activities. Since this thesis focuses on the relationship between Microsoft Azure and
digital maturity, the upcoming subsection assesses the impact of Azure on the five influencing factors
of digital maturity. This discussion answers the fifth and final research question of this master thesis:
‘How does Microsoft Azure impact the influencing factors and consequently influence digital maturity?’
3.2.1 How does Microsoft Azure impact the influencing factors and consequently
influence digital maturity?
The academic literature has not studied the relationship between Microsoft Azure and digital maturity.
Therefore, data concerning this connection was sourced from Infopedia, the internal database of
Microsoft. To this end, concepts such as ‘workforce’, ‘culture’, ‘capability’, ‘leadership’ and ‘vision’
were applied as keywords to search for relevant case examples regarding the above-mentioned
relationship. This process generated a data set of 15 case examples, which Table 6 summarises.
33
Table 6. The effects of Microsoft Azure on the influencing factors
Case
example
Industry The influence of Microsoft Azure on digital maturity Digital
workforce
Digital
culture
Digital
capability
Digital
leadership
Digital
vision
Asos Retail Asos transformed its platform from a monolithic, on-premise
system to a microservices platform that runs on Azure and
subsequently accelerated the development of mobile apps and
features.
x
Carlsberg CPG Carlsberg adopted Microsoft Azure to combine the IoT, Data
Bricks and Power BI. As a result, they developed new digital
capabilities in terms of data analytics. Moreover, Azure
stimulated an innovative and collaborative environment
throughout the firm.
x x
Carmax Automotive The implementation of Azure DevOps cultivated an innovative
and collaborative culture for designing more efficient and automated business processes.
x x
Clear Bank Financial
services
Microsoft Azure enabled the implementation of application
programming interfaces (APIs) for swift application
development. As such, Clear Bank could create and combine
digital technologies on an ongoing basis.
x
Coca-Cola CPG Microsoft Azure enabled collaboration and innovation among
developers. As a result, they were able to combine technologies
(e.g. Visual Studio and Slack) to obtain new digital marketing capabilities.
x x
Daimler Manufacturing Azure IoT Hub enabled Daimler to collect, store and analyse data
that derived from vehicles on the road. Consequently, predictive
maintenance activities were possible, which reduced the
downtime of trucks.
x
Dixons
Carphone
Retail Dixons Carphone implemented Azure to empower employees to
use AI. Such employees were able to provide a personalised
customer journey and improve in-store experiences.
x x
Dun &
Bradstreet
Data &
Insights
Dun & Brandstreet implemented solutions such as Github to
encourage a collaborative and innovative culture among
developers.
x
Emaar group Real estate The implementation of Azure enabled the Emaar Group to
communicate and advance its digital vision across the entire
organisation.
x
John Hopkins
Healthcare Azure facilitated the implementation of real-time and data-driven intelligence within healthcare. Consequently, healthcare
employees could deliver more sophisticated care to patients.
x x
Maersk Cargo Azure enabled the combination of digital technologies, such as AI
and analytics, to create digital capabilities. Moreover, Azure
Active Directory supported a collaborative and innovative
environment.
x x
Presence
health
Healthcare Azure Multi-factor Authentication offered a secure and mobile-
based solution by which employees could access data and subsequently provide care to patients at home.
x x
Sandvik Manufacturing Azure solutions regarding machine learning and IoT yielded data
analytics capabilities that allowed Sandvik to implement
predictive maintenance within their business processes.
x
Taibah
university
Education Azure DevOps fostered a collaborative and innovative culture in
which developers were able to continuously produce and combine
digital technologies to support digital capability.
x x
QwikVisit Healthcare With Azure, healthcare employees could implement data
analytics and use the data to provide telemedicine to patients,
which increased resource utilisation and patient satisfaction.
x x
Table 6 summarises several case examples that indicate the positive influence of Microsoft Azure on
digital maturity. For instance, Asos transformed its monolithic, on-premise system to a microservices
platform that runs on Azure. This change accelerated the creation of applications and features and, in
turn, the development of digital marketing capabilities. Moreover, Dixons Carphone adopted Azure to
drive the adoption of AI solutions by personnel. Since these Software as a Service (SaaS) and Platform
as a Service (PaaS) solutions were preconfigured, employees only needed to connect them to data
34
sources before generating deep customer insights. The implementation of Azure DevOps at Taibah
University enabled the emergence of a digital culture by stimulating developers to create and combine
digital technologies to enhance digital capability. In addition, Sandvik adopted machine learning and
IoT solutions to continuously monitor manufacturing devices. As a result, data was collected,
aggregated and analysed to predict maintenance needs and subsequently prevent malfunctions in
production processes. In conclusion, Microsoft Azure drives the development of a digital workforce,
digital culture and digital capability. However, the impact of Azure on the creation of a digital vision is
negligible, and the connection between Azure and digital leadership is not mentioned. These insights
answer the fifth research question of this study: ‘How does Microsoft Azure impact the influencing
factors and consequently influence digital maturity?’ Nevertheless, these relationships are based on
internal documentation, so additional research must be conducted to validate and possibly adjust these
connections.
3.3 Concluding remarks on literature
Chapters 2 and 3 have elaborated on all of the research questions as noted in Section 1.3. Thereby, they
have generated more insight into the variables of study and their associated relationships. The findings
are visualised in Figure 9 and discussed in more detail below.
Figure 9. The detailed conceptual model
First, academic sources have clearly conceptualised digital maturity differently. Accordingly, multiple
definitions and digital maturity models exist in parallel. This thesis conceptualises digital maturity
according to the study of Fitzgerald et al. (2014), as this academic source incorporates digital maturity
archetypes and a non-linear transformation path. Digital maturity can be measured by two interrelated
35
dimensions: digital intensity and transformation management intensity. Maturity differences along
these dimensions determine four maturity archetypes: Beginners, Fashionistas, Conservatives or
Digirati. Second, academic literature has mentioned that digitally mature organisations are able to
improve firm performance in five categories: products and services, internal processes, customers,
partners and competitors, and financials. As a result, organisations might be motivated to initiate their
digital transformation. To support companies along their digital journey, all influencing factors of
digital maturity were consolidated and discussed. Based on the findings, this thesis identifies five
pivotal factors that enhance digital maturity and studies how Microsoft Azure impacts them. Internal
case examples illustrate that Azure contributes to a digital workforce, culture, capability and vision.
However, it has no identified effect on digital leadership; in fact, this influencing factor appears to drive
the implementation of Azure rather than vice versa. Finally, the thesis has discussed the effect of
institutional factors on the connection between the influencing factors and digital maturity. However,
the dependency of institutional factors on other industry-specific factors (e.g. social and cultural)
inhibited a comprehensive conclusion.
36
4. Research design
The upcoming sections describe and explain the empirical part of this master thesis, including the
research strategy and context of this study. They then deliberate the methodology of Yin (2003) and
describe its implementation within this paper. Hence, this chapter elaborates on the research design that
was employed to study the relationships between Microsoft Azure, influencing factors, institutional
factors, digital maturity and firm performance.
4.1 Research strategy
According to Saunders et al. (2009), research is designed to fulfil an exploratory, descriptive or
explanatory purpose. An exploratory study aims to develop new insights and assess phenomena in a
different light (Robson, 2002). It is particularly useful to gain insight into a specific problem or
phenomenon. Descriptive studies strive to develop an accurate profile of persons, events or situations
and are thus an extension of exploratory research. Furthermore, explanatory research seeks to establish
causal relationships between variables by studying different situations or problems. This master thesis
has an exploratory purpose given that the effect of Microsoft Azure on digital maturity and firm
performance has not been studied extensively (Yin, 2003). Consequently, this study can offer an
understanding of this connection and thereby provide a foundation for future research (Yin, 2014).
Most research in the IS discipline is characterised by two paradigms: design science and behavioural
science (Hevner et al., 2008). Design science research aims to extend the borders of human and
organisational capabilities by developing innovative artefacts. Meanwhile, behavioural science
generates and validates theories that deliberate human or organisational behaviour. This thesis focuses
on the behavioural science paradigm to explore the relationships between Microsoft Azure, influencing
factors, institutional factors, digital maturity and firm performance.
According to the academic literature, behavioural science applies seven research strategies: case study,
field study, laboratory experiment, library research, literature analysis, mathematical model and survey
(Ayanso et al., 2011). Since this thesis adopts an exploratory research design, the implementation of a
case study strategy is a reasonable option. Case study research enables scholars to adopt multiple
research methods and study relationships in real-life business settings (Zainal, 2007; Yin, 2014; Dubois
& Gadde, 2002). Still, to satisfy the requirements of case study research, academics need to examine an
extensive range of sources, such as documents, artefacts, interviews and observations (Yin, 1994).
Because of time and resource constraints, the sources of this study are limited to internal and external
interviews, which characterises the master thesis as an interview study instead of a case study. Since
time constraints also inhibited data collection at several points in time, this research paper is not a
37
longitudinal study (Zainal, 2007). Nevertheless, it involved collection and analysis of interview data
from multiple organisations and thus employs a cross-sectional research design (Mann, 2003).
This research implements a modified version of the research methodology of Yin (2003). Specifically,
interview studies were conducted instead of case studies as in the original method, and interviews were
not complemented by other sources of evidence. This methodology implements multiple interview
studies since their evidence is more persuasive than that of single interview studies (Yin, 2003).
Moreover, multiple interview study analysis enables researchers to answer ‘how’, ‘why’ and ‘what’
questions (Yin, 2003). Since this thesis considers a mix of ‘how’ and ‘what’ questions, a multiple
interview study is appropriate. The methodology of Yin (2003) follows the distinct research flow in
Figure 10 to guide academics through the data collection and analysis process.
Figure 10. The interview study methodology (Yin, 2003)
This study entails three research stages: ‘define and design’; ‘prepare, collect and analyse’; and ‘analyse
and conclude’. Chapter 2 and 3 have detailed the ‘define and design’ stage by exploring the relationships
of interest. The present chapter also addresses the first research stage by outlining the research design
of the study. Chapter 5 tackles the second and third stages by collecting and analysing data from
interview studies to subsequently establish cross-interview conclusions. This approach could validate
and possibly inform modifications to the relationship between Microsoft Azure, influencing factors,
institutional factors, digital maturity and firm performance. Nevertheless, before implementing the
38
methodology of Yin (2003), the upcoming section describes the research context of this thesis to clarify
the scope of the study.
4.2 Research context
The scope of this master thesis is limited to the Information Management domain, as the research
interest is economic and managerial topics. As such, the paper deliberates all variables and their
associated relationships within these boundaries. The upcoming chapter explores these connections via
multiple interviews with Microsoft Azure experts and clients, thereby significantly narrowing the scope
of this research. To provide a comprehensive understanding of the research setting, the following
sections also describe Microsoft Nederland and the Cloud & Artificial Intelligence department in more
detail.
4.2.1 Microsoft Nederland
As Section 1.5.1 has indicated, Microsoft Nederland states one mission: to ‘make the Netherlands
become an icon in the world for digital success’. Since Microsoft Azure is a pivotal factor in achieving
this mission, Microsoft Nederland aims to increase the adoption of Azure across a wide range of
industries and organisations that include commercial (e.g. financial services) as well public (e.g. water
authorities) sectors. Thus, they are targeting both corporates and SMEs. Instead of considering Azure
to be a substitute for on-premise data centres, potential clients should also recognise its tremendous
potential for applications such as machine learning and AI. To encourage this, Microsoft Nederland
advocates for a transition from simple workloads (e.g. compute and networking) to more advanced
workloads (e.g. analytics and enterprise integration), as the latter are more likely to improve digital
maturity. The Cloud & Artificial Intelligence department is responsible for achieving the above-
mentioned targets.
4.2.2 Cloud & Artificial Intelligence department
The Cloud & Artificial Intelligence department is tasked with driving the sales of Microsoft Azure.
Therefore, the department co-operates with technical sales professionals as well as sales solution
specialists to increase the adoption of Azure and support those clients along their digital journeys.
Nevertheless, many clients are hesitant to adopt Microsoft Azure since no extensive research has
supported the positive impact of Azure on digital maturity. To address this hesitance, this master thesis
explores the relationship between Microsoft Azure, digital maturity and firm performance. The Cloud
& Artificial Intelligence department supported this research process with two efforts. First, the
department manager motivated internal personnel and external clients to take part in the interview
studies. Second, multiple employees provided relevant information about Microsoft Azure to clarify the
characteristics of this cloud solution.
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4.3 Stage 1: define and design
The ‘define and design’ stage involves three separate processes: theory development, case selection and
data collection protocol design (Yin, 2013). However, because of the exploratory nature of this study,
it modified the methodology of Yin (2003). Thereby, the phases ‘develop theory’ and ‘modify theory’
were replaced with the phases ‘explore relationship’ and ‘modify relationship’. In addition, multiple
other phases were adapted to suit the methodology’s focus on interview studies instead of case studies.
For example, the phase ‘select cases’ was replaced by the phase ‘select interviews’. The upcoming
sections detail these phases as well as the data analysis method for developing conclusions.
4.3.1 Explore relationship
The first step in the ‘define and design’ phase explores and develops a relationship (Yin, 2003). For this
step, the present study performed a literature review on the relationships between Microsoft Azure,
influencing factors, institutional factors, digital maturity and firm performance. Various articles were
studied to answer the five research questions and subsequently develop a framework that
comprehensively illustrates the above-mentioned connections.
The data for this literature review derived from relevant databases, such as Google Scholar, JSTOR,
Infopedia (i.e. Microsoft database) and World Cat. Initial search results were extended via forward and
backward referencing (Webster & Watson, 2002). While searching for literature, various keywords
were used for concepts such as ‘digital maturity’ and ‘firm performance’, as the academic literature has
referred to these concepts in an inconsistent manner and employed other terms, including ‘digital
transformation’ and ‘financial performance’. Nevertheless, the definition of every article was checked
before applying the source within the literature review.
4.3.2 Select interviews
After completing the literature review, various interview options were selected to explore the
relationships. To conduct comprehensive interview studies, data were collected via internal expert
interviews as well as external client interviews. This method establishes data triangulation, as it uses
two sources of evidence to investigate the effects of Microsoft Azure (Eisenhardt, 1989). Such
triangulation increased both the case quality and construct validity (Yin, 2003).
Expert interviews
Microsoft experts were selected based on their experience with Microsoft Azure, which implies that
experts were required to understand its impact in real-world business settings (Eisenhardt, 1989).
Technological experts were mostly excluded, as their expertise exceeded the scope of this thesis.
Consequently, interviews were mostly conducted with solution sales professionals, cloud solution
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architects and cloud solution specialists, as these employees were able to explain the impact of Azure
without deliberating its technological architecture in detail. Azure focuses on two domains: (1)
infrastructure and security and (2) data and AI. Experts from both domains and different industries were
interviewed to provide a complete overview of the effects of Microsoft Azure and to meet the
exploratory purpose of the research, respectively. Consideration of multiple industries also highlighted
the influence of institutional factors. Table 7 lists all of the Microsoft Azure experts and their associated
demographics.
Table 7. Description on the Microsoft Azure experts
Study Code Business role Azure domain Industry Interview date
Study A A1 Principal cloud consultant Infrastructure & security Public sector 22-10-2018
Study A A2 Cloud solution architect Data & AI Cross-industry 24-10-2018
Study A A3 Cloud solution architect Data & AI Cross-industry 24-10-2018
Study A A4 Cloud solution specialist Data & AI Telecommunication 25-10-2018
Study A A5 Solution sales professional Infrastructure & security Public sector 25-10-2018
Study A A6 Technical solution professional Infrastructure & security Cross-industry 29-10-2018
Study A A7 Cloud solution architect Data & AI Cross-industry 30-10-2018
Study A A8 Cloud solution architect Data & AI Cross-industry 31-10-2018
There are generally three types of interviews: unstructured, semi-structured and structured (Corbin,
Strauss & Strauss, 2014). For the expert and client interviews, a semi-structured approach was adopted.
This approach ensures coverage of all correct materials while also offering the freedom to explore a
topic in more detail (Harrell & Bradley, 2009). These interviews contained only open questions to grant
interviewees the opportunity to answer without any restrictions and elaborate on their beliefs and
experiences (DeMarrais & Lapan, 2004). Given the exploratory purpose of this study, open questions
offer a strong basis for extending knowledge of the impact of Microsoft Azure.
Client interviews
To cross-check expert interview conclusions, interviews were conducted with employees of clients of
Microsoft. As such, the organisations are in accordance with the target population of the study
(Eisenhardt, 1989). This implies that the selected companies implemented Microsoft Azure to support
digital maturity and firm performance. Since this research is explorative in nature, it considers
companies from multiple industries and of varying sizes. However, due to time and resource constraints,
it was not possible to conduct interview studies within all industries. Hence, companies were selected
based on their presence within one of the following key industries of Microsoft Enterprises: the public
sector, financial services, utilities, manufacturing or healthcare. Given the significance of organisational
size, both SMEs and corporations were included. The sampling process also took digital maturity into
account to include diverse perspectives. Table 8 specifies the selected companies and their
accompanying demographics.
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Table 8. Description on the interview study companies
Study Revenue per year (Euros) Number of employees International focus Digital maturity5 Industry
Study B N/A 500 No Beginner Public sector
Study C 450 million 1,900 No Conservative Public sector
Study D 12.1 billion 15,000 Yes Beginner Financial services
Study E 9.2 billion 19,950 Yes Beginner - Conservative Financial services
Study F N/A 230 Yes Fashionista - Digirati Utilities
Study G 3.3 billion 7,000 Yes Fashionista Utilities
Study H 436.9 million 2,050 Yes Digirati Manufacturing
Study I 68.3 million 1,500 No Fashionista Healthcare
Within the organisations, employees were identified according to their ability to provide valuable
insight on the impact of Microsoft Azure. Since time and resource constraints restricted interviews to
one employee per company, participants were selected only if they fully understood the capabilities of
Microsoft Azure and its implications for their organisation’s digital maturity and firm performance.
Table 9 contains the demographics of each employee and his or her position within the organisation. It
also briefly describes all external interviewees.
Table 9. Description on the interview study company experts
Study Code Business role Years in current role Previous experience with Microsoft Azure Interview date
Study B B1 Manager information and automation 1.5 years Before this role, the interviewee worked with
Azure on a daily basis as a data scientist. 20-11-2018
Study C C1 IT manager cloud 1 year Before this role, the interviewee used Azure
on a conceptual level as a domain architect. 26-11-2018
Study D D1 Data scientist 2.5 years Before this function, the interviewee did not implement Azure but used similar platforms.
28-11-2018
Study E E1 Lead IT development and cloud 4 years Before this role, the respondent did not work
with Azure but used on-premise data centres. 21-11-2018
Study F F1 Chief information officer 2 years Before this function, the interviewee worked
with Azure on a practical basis as a manager. 21-11-2018
Study G G1 Domain architect customer operations 0.5 years
Before this position, the respondent used
Azure on a conceptual basis as an IT architect.
23-11-2018
Study H H1 Digital transformation officer 2 years Before this role, the interviewee worked with
Azure on conceptual and practical levels. 19-11-2018
Study I I1 Manager information and automation 2 years
Before this function, the respondent worked
with Azure on a conceptual basis as a
manager.
23-11-2018
Interviewee B1
Respondent B1 fulfils the position of information and automation manager within a public sector
organisation that was one of the first governmental institutions to adopt Microsoft Azure for data storage
as well as more advanced solutions. The interviewee is responsible for the development and
implementation of the cloud strategy and thus provided useful knowledge of the impact of Microsoft
Azure.
5 These digital maturity archetypes are based on self-ratings by external interviewees.
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Interviewee C1
Interview study C involves an interview with the IT manager cloud of a governmental institution. The
organisation is a precursor of cloud computing within the public sector and implements Azure to collect
data and insight regarding business processes. Interviewee C1 supports the board of directors in
developing the digital strategy and is directly responsible for the cloud strategy.
Interviewee D1
Respondent D1 is a data scientist who is employed by a financial services company. The organisation
implements Azure for isolated digital initiatives, as they still need to transfer many IT assets to the
cloud. Therefore, their cloud maturity is relatively low. Interviewee D1 works with Azure on a daily
basis and shapes the cloud strategy of his business unit as well.
Interviewee E1
Study E concerns an interview with the lead IT development and cloud platforms of a financial services
organisation. The company already transitioned a substantial number of IT asset to Microsoft Azure to
improve alignment of technology and business processes. The main responsibility of interviewee E1 is
to design the cloud strategy for all business units.
Interviewee F1
Respondent F1 is the chief information officer of a utilities company. The organisation implements
Microsoft Azure to support their charging infrastructure and generate deep insights regarding business
processes. Interviewee F1 defines the digital vision and strategy of the entire organisation.
Interviewee G1
Interview study G encompasses one interview with the domain architect customer operations of a
utilities company. The firm uses Microsoft Azure for storage and computing workloads but seeks to
deploy more advanced services in the future. Respondent G1 determines the digital strategy for his
business domain and supports digital transformation across the entire group.
Interviewee H1
Respondent H1 is the digital transformation officer of a pharmaceutical compounding company. The
organisation implements Microsoft Azure to adopt advanced digital solutions which enable
personalised medication. As the digital transformation officer, Respondent H1 drives digitalisation
within the company.
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Interviewee I1
Interviewee I1 holds the position of information and automation manager within a healthcare
organisation. The company is a frontrunner in cloud use within the healthcare sector and implements
Azure to collect and manage data to support employees during care treatments. Respondent I1 manages
the entire IT department and thus leads digital transformation within the firm.
4.3.3 Data collection protocol design
According to Yin (2003), the development of a data collection protocol is essential to a multiple
interview study. This protocol not only increases the reliability of an interview study but also guides
researchers through the data collection process (Tellis, 1997). For this master thesis, a data collection
protocol was designed according to the method of Yin (2003). Appendix II contains this protocol,
including the data collection procedures, an outline of the interview study report and the interview
questions. To improve the data collection protocol, proxy interviews were conducted prior to the
internal expert interviews and external client interviews. The proxy interviews identified and resolved
flaws in the data collection procedure, thereby refining the data collection process. They additionally
helped to ask the right questions during the actual interviews and thus improved the reliability of the
research. Appendix III includes these proxy interviews, which eventually informed the final data
collection protocol.
4.3.4 Data analysis and conclusion
The theoretical context of the effects of Microsoft Azure on digital maturity and firm performance led
the interview study analysis, as the studies aim to explore these effects and potentially discover
additional influences. To perform these studies, cross-interview analysis was employed. This technique
checks whether interviewees also mention the effects that are identified in the literature. Additionally,
individual interview studies were analysed to detect effects that academic research has not noted.
Discovering additional effects during the interviews could validate whether other interview studies have
mentioned them as well. As Figure 10 illustrates, this process yields cross-interview conclusions, which
can subsequently be used to modify the initial relationship that was developed in the ‘define and design’
stage.
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5. Results
This chapter analyses the data per interview study and subsequently summarises them in the cross-
interview analysis section. To this end, it more thoroughly explores the theoretical relationships that
emerged in the ‘define and design’ stage. The findings from the interview study research validate and
possibly extend the academic literature.
5.1 Stage 2: prepare, collect and analyse
This section describes only interview studies A and B, as the magnitude of all individual studies
decreases the readability of this thesis. Appendix IV contains interview study C through I, which use the
same structure as the studies A and B. The individual interview studies provide a detailed description
of the industry focus, organisational structure and digital maturity of each specific company.
Nonetheless, as interview study A contains only internal expert interviews, it lacks company-specific
information. Stage 2 also includes key findings regarding the relationships of interest. Ultimately, the
paper answers all of the research questions from an empirical standpoint. However, the first research
question is not discussed, as the conceptualization of Fitzgerald et al. (2014) is validated by all
interviewees. Therefore, its concepts are only included while answering the other research questions.
First, the influence of digital maturity on firm performance is discussed. Second, the effect of the
influencing factors on digital maturity is studied. Third, the impact of industry-specific factors on the
connection between the influencing factors and digital maturity is elaborated on. Finally, the influence
of Microsoft Azure on the five influencing factors is discussed. Appendix V provides the full interview
transcriptions.
5.1.1 Interview Study A | Microsoft experts
Key findings
Research question 2: How does digital maturity impact firm performance?
According to the interviewees, digital maturity positively impacts various aspects of firm performance.
Respondent A1 mentioned that digital maturity influences the time-to-market of products and services.
Thus, digital transformation improves the rate at which products and services are developed, produced
and updated. Respondent A2 supported a financial institution in creating mobile applications, which
increased the quality of banking services in the front-end of the organisation. However, since the
organisation disregarded the replacement of legacy IT, continuous service improvement was not viable.
Interviewee A4 worked with a more digitally mature firm which develops auditing software. This
company not only creates new services but also continuously advances them. Hence, it released
software more often and takes customer feedback into account. In other words, the firm performance
aspect of the products and services is dependent on the digital maturity level of an organisation.
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According to interviewee A4, digital maturity also increases the efficiency of internal processes. For
example, initiatives such as robotic process automation can heighten workforce productivity, thereby
improving process efficiency. Respondent A3 was active in two transportation companies, of which
one was Digirati and the other Beginner. The digitally mature organisation applied more advanced
order-picking methods, such as Google Glass, which reduced order-picking failures by employees and
in turn increased operational efficiency. Respondent A5 mentioned that the implementation of
HoloLens solutions at a public transportation company enhanced the efficiency of maintenance
processes, as experts could support multiple engineers during maintenance activities without being
physically present. Hence, digital maturity positively influences the efficiency of internal processes.
By employing digital technology, firms can also gather information about current and potential
customers. Respondent A5 worked with several e-commerce retailers and noticed that even short
website visits yielded sufficient data to develop customer profiles and subsequently target customers in
a more personalised manner. Through such targeting, organisations can more successfully fulfil
customer needs and cultivate stronger engagements. Besides web interaction, loyalty programs can also
be implemented in order to gather data and push more personalised offerings towards customers.
Respondent A7 worked with a retailer that employed such a loyalty program. The solution gathered
data during every purchase and automatically converted this information into personalised offerings.
Consequently, customers received discounts on the same or related products and would be more likely
to return to the retailer in the future.
Organisations that heavily employ technology can also simplify and improve interactions with other
companies. Respondent A8 indicated that e-commerce platforms use forecasting to update suppliers
about future demand so that they are able to uphold their guarantee of one-day delivery. Furthermore,
respondent A7 mentioned that digitally mature companies can use technology to develop end-to-end
ecosystems, which streamlines collaboration across organisational boundaries. However, interviewee
A8 mentioned that this was only viable when partners embodied the same digital maturity; otherwise,
technology could not influence co-operation, as it could not be implemented. Moreover, co-operation
depends not only on the availability of digital technology but also, according to respondent A2, on a
result of added value for all parties. Hence, digital maturity enables easier, superior collaboration but
does not ensure a positive influence on this aspect.
Finally, the four above-mentioned performance aspects raise the financial position of an organisation.
For instance, improved products and services increase sales, whereas more efficient processes induce
cost savings. Nevertheless, interviewee A1 disproved this relationship in the short term, as firms must
invest in digital technology and transform their entire organisation. Moreover, respondent A2
mentioned financial performance differences with regard to firm size, as the flexible nature of small
enterprises renders them more likely to improve their financials. In contrast, corporates are likely to
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encounter more challenges due to, for instance, legacy IT. As such, their digital transformation requires
more resources. Nevertheless, all interviewees agreed on a positive impact of digital maturity on the
four firm performance aspects and its subsequent influence on an organisation’s long-term financials.
In conclusion, interview study A supports a positive relationship between digital maturity and an
organisation’s products and services, as an uplift in digital maturity enhanced both their quality and
time to market. Moreover, the interviewees stated that digital maturity adds efficiency to internal
processes, and digital transformation enables companies to target customers more effectively, thereby
increasing customer engagement. The academic literature has also stated a positive impact of digital
maturity on partner and competitor collaboration; however, interview study A supports this connection
only without substantial maturity differences between organisations, as technology would otherwise
hinder collaboration. Finally, the respondents also supported an indirect relationship of digital maturity
on financial performance given that efficiency improvements in internal processes would, for instance,
reduce costs. These findings address the second research question of this master thesis: ‘How does
digital maturity impact firm performance?’
Research question 3: What factors influence digital maturity?
Respondent A8 mentioned that a digital workforce is vital to achieving digital maturity, as its absence
impedes digital transformation. For instance, a financial services client of this interviewee lacked a
digital workforce, which hindered the execution of the digital strategy. Thus, a digital workforce is a
hygiene factor of driving digital maturity. Interviewee A4 supported this statement in sharing that one
of his telecommunication clients restricted innovation with advanced technologies. As a result,
employees were able to work with complex ERP systems but severely lacked cloud computing skills.
As a result, the digital workforce could not implement digital initiatives, which precluded benefit to the
digital intensity dimension. According to respondent A7, firms try to close this skill gap by hiring digital
natives who are capable of implementing advanced digital technologies. Nevertheless, organisations
should also train existing employees, as they are more experienced in managing current business
processes. Interview study A thus reflects the positive impact of a digital workforce on digital maturity
but reveals multiple examples in which organisations struggled to develop this influencing factor.
Respondent A1 mentioned that firms should also create a digital culture since it drives the adoption of
digital technology and thus stimulates co-operation and innovation. Consequently, employees are
motivated to experiment with new technologies and share them throughout the organisation. Therefore,
the creation of a digital culture positively impacts the digital intensity and transformation management
intensity dimensions. Lacking a digital culture will substantially hinder a firm’s digital transformation.
For instance, respondent A7 experienced several situations in which employees resisted digital change
because they were focused on day-to-day business processes and their associated financial targets. As
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a result, only isolated business units implemented digital initiatives. In this case, the digital intensity
dimension was slightly impacted, but the transformation management intensity was not affected.
According to interviewee A2, personnel also refused to adopt digital technology out of fear of losing
their occupation. To remove these barriers to a digital culture, management should hire digital natives
while also motivating their existing workforce. Respondent A6 mentioned that Microsoft also adopted
this tactic during their transformation. Thereby, they developed a digitally minded environment that
focused on collaboration and innovation.
According to interviewee A1, organisations should also pursue digital capability, as it impacts the
digital intensity dimension. Respondent A2 supported this statement by citing his involvement in the
creation of digital capability for a utility company. Data warehousing and business intelligence solutions
were connected to build data analysis capabilities. As a result, the firm was positioned to personalise
offerings, which improved customer engagement. Interviewee A4 also identified the connection
between digital capability and digital maturity. One of his clients was active in the audit and assurance
sector, so this company possessed significant amounts of client data. To derive additional insights from
this data, Microsoft supported this organisation in the development of data analysis capabilities, with
which they then provided additional services next to their traditional auditing activities. Nevertheless,
respondent A8 mentioned that the digital capability of a firm must continuously improve, as digital
technology also advances. Hence, digital capability increases the digital intensity dimension provided
it constantly evolves alongside technological developments.
Digital leadership is also crucial during a digital transformation process. Respondent A6 indicated that
executives must define a digital vision that is underpinned by a digital workforce, culture, and
capability. Thus, management should plan and orchestrate digital transformation. Interviewee A4
agreed with this statement and noted that the digital journey of one of his clients was heavily dependent
on management support. Since the organisation focused on public transportation and implemented
outdated technologies in an isolated fashion, the IT department managed a vast application landscape
that was dispersed across several business units. Moreover, most employees were not interested in
digital change, as it would disrupt their daily business activities. Therefore, once this organisation
initiated digital transformation, both human and technological obstacles arose. To remove these
complications, respondent A4 motivated the leadership team to support and propagate digital change
throughout the entire organisation by creating a top-down vision and encouraging bottom-up initiatives.
Consequently, digital leadership acquired leadership capabilities (e.g. vision and engagement) to drive
the transformation management intensity dimension. In contrast, a lack of digital leadership hinders
digital transformation, as neither human nor technological difficulties can be easily overcome, and a
digitally averse leadership team can also incite the above-mentioned difficulties. For example,
respondent A4 experienced a situation in which the executives of a telecommunication company did
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not support the creation of a digital vision and obstructed any form of funding for advanced technology,
such as cloud computing. Hence, the absence of digital leadership negatively impacted digital maturity.
To summarise, interview study A evidences positive relationships between the five influencing factors
and digital maturity. Nevertheless, the interviewees stated that the individual factors do not substantially
improve digital maturity, as the absence of one or multiple influencing factors prevents digital
transformation. In view of this, organisations should develop and align all five factors to significantly
impact digital maturity. In addition, the influencing factor of digital leadership was considered the most
pivotal factor, as it directly affects the other four influencing factors via top-down leadership. These
insights address the third research question: ‘What factors influence digital maturity?’
Research question 4: Which industry-specific factors moderate the relationship between the influencing
factors and digital maturity?
According to respondent A1, institutional factors focus on data privacy and data security and deter
organisations, especially those in the financial services, public sector and healthcare industry, from
implementing advanced digital technologies. Nonetheless, Microsoft aims to develop technologies that
are already compliant with regulation. For instance, Microsoft Azure is certified, which signals its
regulatory compliance and suggests that organisations can conform more easily when adopting Azure
in comparison to on-premise data centres. Still, many firms refer to regulation as an argument to resist
digital change. For instance, interviewee A4 experienced several situations in which telecommunication
companies argued against certain transformations because they would increase the complexity of
compliance processes. According to respondent A5, employees in public sector institutions also use
regulatory arguments to avoid transformation. These tendencies evidence that institutional factors, such
as data security, might hinder digitalisation.
Interviewee A7 explained that various digital technologies are already compliant, which can be cited to
repel any regulatory-based objections to digital transformation. Compliance is one of the main drivers
of digital change given that digital technology often facilitates compliance by organisations. Therefore,
institutional factors can both positively and negatively impact the relationship between the influencing
factors and digital maturity, and the organisational attitude towards digital change determines whether
the effect is positive or negative. This conclusion answers the fourth research question of this study:
‘Which industry-specific factors moderate the relationship between the influencing factors and digital
maturity?’
Research question 5: How does Microsoft Azure impact the influencing factors and consequently
influence digital maturity?
Respondent A1 indicated that Microsoft Azure enables employees to implement advanced technologies.
For instance, it offers and supports back-end functionalities that facilitate the development and usage
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of AI solutions. Respondent A5 agreed and recounted various situations in which personnel built
advanced solutions without support from the IT department. Thus, this solution reduced barriers for
digitally immature employees in implementing advanced technologies and allowed personnel to enact
digitally enabled initiatives, such as predictive maintenance. Therefore, Microsoft Azure can indirectly
impact the digital intensity dimension of digital maturity, although interviewee A8 mentioned that IT
departments can develop advanced technologies, such as machine learning, without Azure. Still, this
cloud platform improves the speed and ease of producing and implementing technologies. Since
Microsoft Azure also increases the technological comfort zone of employees, it drives the cultivation
of a digital workforce as well.
Microsoft Azure also enables the formation of a digital culture. According to respondent A7, the cloud
solution spans across organisational silos, thereby connecting isolated business units. Moreover, Azure
implements a governance mechanism that removes obstacles of innovation and collaboration while
guaranteeing security. Respondent A8 also mentioned that Azure reduces the risk of innovation; for
instance, employees can build and test new solutions without committing extensive resources. In
addition, Azure supports various solutions that allow for co-operation. For instance, with Azure
DevOps, developers can write programming code in parallel and provide mutual support in the process.
The characteristics and solutions of Azure thus drive the creation of a collaborative and innovative
culture. Consequently, personnel are more likely to develop and implement digital initiatives that are
aligned with the digital vision. In this way, Azure advances the digital intensity and transformation
management intensity of digital maturity.
The interviewees further asserted that Microsoft Azure drives the development of digital capability.
According to respondent A6, the relationship results from two elements. First, Microsoft Azure includes
a large variety of solutions that can be implemented instantly. Accordingly, employees can apply
solutions without needing to focus on the development process. Interviewee A1 reinforced this
statement by sharing that a client could quickly implement IoT solutions with Azure IoT Hub. Second,
solutions on this cloud platform use the same network protocol, which simplifies communication
between technologies. As a result, personnel can connect technologies more easily to enhance digital
capabilities. Respondent A4 experienced a similar situation with a telecommunication client. The
organisation initially struggled to connect databases and technologies, as these solutions required an
integration layer to communicate. By adopting Microsoft Azure, they achieved swifter and more
convenient digital capability development. Such advancement yielded digital initiatives, such as
personalised marketing, which indirectly stimulated the digital intensity dimension.
Interview study A does not support the connection between Microsoft Azure and the creation of digital
leadership. Instead, respondent A2 mentioned that executives develop a digital mindset in order to meet
or surpass competitors. For instance, one of his clients initiated digital transformation to react to the
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market entry of new competitors. These competitors had already digitised their business processes and
could thus outperform the client in service delivery. Since their emergence resulted in the client’s loss
of market share, executives were motivated to drive digital change. Interviewee A3 also supported a
fintech firm that disrupted the payment sector with digital business propositions, which their leadership
team created to outperform incumbent banks. Thus, digital developments, do not stimulate the digital
awareness of management teams; rather, they provide tools to incite digital change within a firm.
Finally, the respondents disagreed about the impact of Azure on the creation of a digital vision.
Respondent A1 believed that Microsoft Azure stimulates the creation of a digital vision because its
technological possibilities inspire organisations to consider the role of technology in their business
models. For instance, the CEO of a global oil company was triggered by the possible impact of Azure
on the organisation’s business processes. Therefore, he motivated the board of directors to develop a
digital vision that is based on the projected possibilities of the cloud platform. Respondent A8 supported
this relationship, as Azure illustrated the future IT landscape for multiple clients. This image informed
their subsequent development of a digital vision to guide the digital transformation of the company. In
this way, Microsoft Azure indirectly supported the transformation management intensity dimension.
However, the other interviewees rejected the above-mentioned connection, as they considered its
argumentation to be far-fetched. Instead, they stated that an organisation’s management team primarily
drives the formation of a digital vision. Microsoft Azure provides the technologies to achieve such
vision, but it does not determine the digital journey of a firm.
In conclusion, interview study A supports the positive impact of Microsoft Azure on three influencing
factors: digital workforce, digital culture and digital capability. Therefore, Azure indirectly stimulates
both the digital intensity and transformation management intensity dimensions. Moreover, the
interviewees shared that digital leadership derives not from Microsoft Azure but from market
developments, such as the market entry of new competitors. Lastly, only two respondents identified a
positive contribution of Azure to the development of a digital vision, while the other interviewees
explained that digital leadership predominantly drives this process. In view of the findings, interview
study A does not support this connection, which addresses the fifth and final research question: ‘How
does Microsoft Azure impact the influencing factors and consequently influence digital maturity?’
5.1.2 Interview Study B | Municipality
Case description
Industry focus
Company B is one of the largest municipalities in the Netherlands. The non-profit organisation focuses
on service delivery to its citizens and generates revenue via taxation and central government subsidies.
The company employs around 500 people who are active in variety of sub-organisations.
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Organisational structure
This municipality consists of two separate bodies. The city council concentrates on the political items
and thus determines all major decisions. Moreover, the governmental body manages this organisation
on a daily basis and is led by two directors, one of whom is indirectly responsible for the IT department.
Respondent B1 reports to this director and manages the IT department.
Digital maturity
Respondent B1 stated that organisation B is slowly progressing from the Beginner phase to the
Fashionista phase. The organisation adopted several advanced technologies, including Azure, but did
so mainly in small pilot implementations. Leadership capabilities with regard to a digital strategy,
governance and engagement are also absent. Thus, management desires transformation but situates
responsibility for it in lower levels of the organisation. As a result, digital change is initiated from the
bottom up and lacks guidance and support to impact the entire enterprise and significantly drive digital
transformation.
Key findings
Research question 2: How does digital maturity impact firm performance?
Interview study B supports the relationship between digital maturity and all aspects of firm
performance. For example, the implementation of Microsoft Azure enabled company B to map its
application landscape. Personnel understood where data resided and how they could be aggregated to
support internal processes, and they could thus make well-informed decisions on childhood support
(Jeugdzorg) processes. Furthermore, digital maturity enhanced the quality of products and services, as
process improvements permitted swift service delivery to inhabitants. The implementation of Office
365 also allowed employees to answer customer questions effectively, as they could easily access
specific data sources without browsing the entire database. Improved products and services and more
efficient internal processes also heightened customer engagement since inhabitants were more satisfied.
Respondent B1 also stated that the implementation of Microsoft Teams impacted internal and external
collaboration by allowing employees and organisations to share data and work on projects in parallel.
Therefore, study B also supports the relationship between digital maturity and improved partner and
competitor co-operation. Finally, interviewee B1 indicated that an uplift in these four performance
aspects increased financial performance. For instance, internal process improvements concerning
childhood support (Jeugdzorg) enabled personnel to make more rational decisions regarding
expenditures and thereby lowered costs. In conclusion, interview study B mentioned a positive impact,
whether direct or indirect, of digital maturity on all aspects of firm performance. These insights address
the second research question of this master thesis: ‘How does digital maturity impact firm
performance?’
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Research question 3: What factors influence digital maturity?
According to respondent B1, organisations can enhance their digital maturity by creating a digital
workforce, culture, capability, leadership and vision. However, since company B is a Beginner in terms
of digital maturity, it often lacks these influencing factors, which consequently hinders the digital
journey of the organisation. For example, multiple employees are unable to work with simple or
advanced digital technologies. Interviewee B1 also explained that a digitally averse culture impeded
digital transformation, as approximately 50% of the organisation resisted digital change. Therefore,
company B lacks both a digital workforce and digital culture, and digitally enabled initiatives that are
developed by the IT department are not implemented throughout the entire organisation. However,
company B has managed to connect technologies and create digital capabilities. For instance, the IT
department connected Azure IoT Hub, Azure Data Bricks and Power BI to clarify the infrastructure
status within the municipality. This action prompted new digitally enabled initiatives for predictive
maintenance, which improved the digital intensity dimension. Nevertheless, this uplift was marginal,
as the implementation of these digital initiatives was often disregarded because of the absence of a
digital workforce and culture. According to respondent B1, executives supported digital transformation
by funding bottom-up digital experiments but practiced no top-down leadership, as the responsibility
for orchestrating digital change was assigned to the lower levels of the organisation. Since company B
had no digital vision or digital strategy, their employees did not understand how to drive digital
transformation on a daily basis, which resulted in the emergence of contradictory initiatives throughout
the organisation. In conclusion, company B is digitally immature given their lack of a digital workforce,
culture, leadership and vision. Interviewee B1 proposed that the company must develop these factors in
the future to stimulate both digital maturity dimensions. In view of these insights, interview study B
evidently supports the five influencing factors of digital maturity, which answers the third research
question: ‘What factors influence digital maturity?’
Research question 4: Which industry-specific factors moderate the relationship between the influencing
factors and digital maturity?
Interview study B established that industry-specific factors, such as regulation, obstruct digital
transformation. Respondent B1 mentioned that two aspects induce this effect. First, regulations are not
transparent since they can be interpreted in multiple ways. As a result, the legal and IT departments of
company B often disagreed about the implementation of digital technology, and executives had to
intervene to resolve conflicts before the technology could be adopted. Second, the ambiguity of
regulatory influences strengthens the position of employees who resist digital change. Consequently,
digital initiatives were often postponed or terminated, as organisation B did not want to risk fines for
non-compliance. In conclusion, respondent B1 supported the negative influence of industry-specific
factors on the relationship between the influencing factors and digital maturity, which addresses the
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fourth research question: ‘Which industry-specific factors moderate the relationship between the
influencing factors and digital maturity?’
Research question 5: How does Microsoft Azure impact the influencing factors and consequently
influence digital maturity?
Study B illustrated the positive impact of Microsoft Azure on four influencing factors. First, Azure
stimulated the creation of a digital workforce by enabling employees to implement advanced
technologies in a more convenient and swift manner. Respondent B1 explained that this effect
originated from Azure’s focus on PaaS and SaaS solutions. Accordingly, personnel could implement
technologies, such as machine learning, without a full understanding of their development and
management of back-end processes. Personnel subsequently initiated multiple pilot runs of digital
initiatives, and company B consequently formulated predictive maintenance solutions that improved
their digital intensity. Second, Microsoft Azure contributed to the cultivation of an innovative and
collaborative environment. According to interviewee B1, Azure Active Directory primarily induced this
effect, as this governance mechanism removed restrictions on collaboration and experimentation.
Consequently, employees started to innovate with new technologies, which yielded new digital
initiatives. The creation of a more collaborative environment also positively influenced transformation
management intensity by generating engagement and IT-business relationships. Nevertheless, since
company B implemented Azure on a small scale, the effects are negligible. Third, Microsoft Azure
facilitates digital capability because its solutions are easy to implement and connect. According to
interviewee B1, these characteristics enabled the IT department to swiftly adopt and connect
technologies, thereby imparting digital analyses capabilities, such as predictive maintenance. Finally,
Azure initiated digital leadership, as the executives of company B were inspired by the possibilities of
the cloud platform. Therefore, management noticed the relevance of digital change and started to fund
bottom-up initiatives, which established leadership capabilities, such as IT-business relationships, that
slightly improved transformation management intensity. Nevertheless, because of the limited scale of
the platform’s implementation, its influence on the digital maturity of company B was not substantial.
In conclusion, interview study B reflects a positive impact of Microsoft Azure on the creation of a
digital workforce, culture, capability and leadership, which answers the fifth research question: ‘How
does Microsoft Azure impact the influencing factors and consequently influence digital maturity?’
5.2 Stage 3: analyse and conclude
The upcoming sections establish cross-interview conclusions on the basis of the previously deliberated
interview studies. Thus, they consolidate the individual interview study conclusions into one
comprehensive overview. In addition, the following sections compare these conclusions to the literature
findings that Chapters 2 and 3 discuss, and they validate and possibly modify the relationships in Figure
9.
54
5.2.1 Cross-interview analysis
Section 5.1 and Appendix IV contain individual analyses of the nine interview studies. These analyses
offer insight into the relationships that were studied. The analyses revealed that the outcomes of the
studies were partly dependent on the respective organisation’s digital maturity. Therefore, to further
contextualise the cross-interview analyses, Figure 11 visualises the maturity archetypes of all
companies. These archetypes were initially based on ratings from the external interviewees; however,
since multiple ratings did not align with the interview analyses, adaptions were made. For instance,
interviewee D1 considered company D to be positioned in the Conservative space despite the
organisation’s lack of a digital strategy, engagement and IT-business relationships. Such adaptations
slightly altered the positioning of certain companies.
Figure 11. The maturity archetypes of all companies
Table 10 summarises the individual interview conclusions for all relationships. It indicates whether the
interview studies agree with a specific relationship or not. Moreover, if additional connections were
noted during the interview studies, they are included as well. These relationships are encompassed
within the ‘Study only’ column and denoted by the ● symbol. The rest of this section synthesises the
interview conclusions per research topic (e.g. firm performance and influencing factors). It
subsequently compares these findings to the answers in the literature to validate whether the interview
study research supports connections that have emerged in previous academic work. Such comparison
also detects relationships in the academic literature that did not arise in the interview studies, and vice
versa. The findings are ultimately implemented to validate and possibly adjust the relationships that
were identified in the ‘define and design’ stage.
55
Table 10. Cross study analysis of the relationships
Topic Relationships Study A
Microsoft
Study B
Public sector
Study C
Public sector
Study D
Financial services
Study E
Financial services
Study F
Utilities
Study G
Utilities
Study H
Manufacturing
Study I
Healthcare
Study
only
Fir
m p
erfo
rma
nce
Digital maturity positively impacts a firm’s products and services. | Firm Performance 1
(FP1)6 x7 x x x x x x x x
Digital maturity positively impacts a firm’s internal processes. | Firm Performance 2 (FP2) x x x x x x x x x
Digital maturity positively impacts a firm’s customer engagement. | Firm Performance 3
(FP3) x x x x x x x x x
Digital maturity positively impacts a firm’s partner and competitor co-operation. | Firm Performance 4 (FP4)
x x x x x
Digital maturity improves co-operation if significant maturity differences between parties
are absent. | Firm Performance 5 (FP5) x x x x ●
Digital maturity positively impacts a firm’s financials. | Firm Performance 6 (FP6) x x x x x x x x x
Infl
uen
cin
g f
act
ors
Digital workforce positively influences a firm’s digital maturity. | Influencing Factors 1
(IF1) x x x x x x x x x
Digital culture positively influences a firm’s digital maturity. | Influencing Factors 2 (IF2) x x x x x x x x x
Digital capability positively influences a firm’s digital maturity. | Influencing Factors 3
(IF3) x x x x x x x x x
Digital leadership positively influences a firm’s digital maturity. | Influencing Factors 4
(IF4) x x x x x x x x x
Digital leadership positively impacts a firm’s digital workforce, culture, capability and
vision. | Influencing Factors 5 (IF5) x x x x ●
Digital vision positively influences a firm’s digital maturity. | Influencing Factors 6 (IF6) x x x x x x x x x
Digital maturity is only influenced substantially if all five influencing factors are present and aligned. | Influencing Factors 7 (IF7)
x x x x x x ●
Inst
ituti
ona
l
fact
ors
Institutional factors negatively influence the connection between the influencing factors
and digital maturity. | Institutional Factors 1 (ISF1) x x x x x x x
Institutional factors positively influence the connection between the influencing factors
and digital maturity. | Institutional Factors 2 (ISF2) x x x x x ●
Mic
roso
ft A
zure
Microsoft Azure enables the creation of a digital workforce. | Microsoft Azure 1 (MA1) x x x x x x x x x
Microsoft Azure enables the creation of a digital culture. | Microsoft Azure 2 (MA2) x x x x x x x x x
Microsoft Azure enables the creation of digital capability. | Microsoft Azure 3 (MA3) x x x x x x x x x
Microsoft Azure enables the creation of digital leadership. | Microsoft Azure 4 (MA4) x x x ●
Microsoft Azure enables the creation of digital vision. | Microsoft Azure 5 (MA5) x x x x x
6 These codes were implemented to connect Table 10 with the cross-interview analysis below.
7 The x symbol indicates that an interview study agrees with a certain relationship; otherwise, the cell is blank.
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Research question 2: How does digital maturity impact firm performance?
All interviewees agreed that digital maturity positively impacts an organisation’s products and services
(FP1). Interview study A mentioned that digitally mature organisations can improve the time to market
of products and services, as technology increases the rate of their development, production and
enhancement. For instance, company H implemented applications such as OneDrive and SharePoint to
improve collaboration across organisational silos. As a result, they could design, manufacture and
release products within weeks instead of months. Moreover, digital maturity improves the quality of
products and services. For example, company F combined IoT and machine learning technology to
notify drivers of charging points that are likely to remain unoccupied. Accordingly, drivers could
configure their routes based on real-time information. Multiple academic studies have demonstrated the
benefits of digital maturity for the quality and time to market of products and services (Andal-Ancion
et al., 2003; Neumeir et al., 2017). Therefore, two sources of evidence validate this relationship.
The respondents also supported a positive influence of digital maturity on internal processes (FP2).
Study C indicated that an uplift in digital maturity increased the efficiency of internal processes. The
organisation adopted Maximo, an asset management platform, to aggregate data regarding its water
management facilities (e.g. water-pumping stations). Predictive models employed this data to anticipate
maintenance needs, thereby reducing the downtime of assets. Moreover, within company D, the
implementation of optical character recognition (OCR) automated the digitalisation process of internal
documentation, which led to an 80% to 90% reduction in the time that they spent on this process.
Company E also adopted technologies to automate back-end processes for mortgage requests. As such,
they automatically analysed customer data to validate the adherence of mortgage requests to regulatory
standards. The efficiency of this process consequently improved substantially. Previous research papers
have supported the above-mentioned relationship as well (Kane et al., 2015; Uhl & Gollenia, 2016).
Therefore, both academic literature and empirical research confirm this connection.
All interview studies also highlighted the positive relationship between digital maturity and customer
engagement (FP3). Studies A, D and G suggested that digital maturity directly impacts customer
engagement, as technology enabled more personalised customer targeting. For instance, company D
combined customer data with machine learning to delineate more sophisticated customer segments. As
a result, their marketing efforts targeted specific customers instead of large segments, thereby providing
them with a more customised experience. The other studies considered this relationship to be indirect
given that enhanced products, services and processes automatically generate customer engagement. For
example, respondent E1 remarked that improvements to their online banking platform heightened
customer satisfaction, as additional services improved their digital banking experience. Academic
literature has evidenced both a direct (Rishika et al., 2013) and indirect (Matt el al., 2015) relationship
57
between digital maturity and customer engagement. Thus, both the literature and the interview study
research verify this link.
Interview studies B, D, E, G and I reflect the connection between digital maturity and superior
collaboration with partners and competitors (FP4). These studies state that technology stimulates
communication and co-operation between parties. For example, company D implemented digital portals
to provide insight to intermediaries who are responsible for direct client contact. Consequently, the
organisations could more effectively target customers. In addition, respondent E1 mentioned that the
creation of an API ecosystem enabled company E to collaborate with third parties on software
development and, as a result, publish their own software and use applications by other providers for
their own business processes. As noted earlier, the literature has accepted the positive effect of digital
maturity on partner and competitor collaboration (Li, 2015; Huang et al., 2012).
The other interview studies supported the above-mentioned relationship only in the absence of
significant maturity differences between parties (FP5). According to Respondent F1, such differences
between company F and another organisation hindered co-operation, as the partner implemented
outdated back-end systems that could not easily communicate with the Azure web services of company
F. Company H experienced a similar situation, as maturity disparities forced the organisation to adapt
to the technology of its partners. These adaptions led to disorganised warehousing processes, as these
were dependent on certain warehousing technologies. Since other research papers have not mentioned
this connection, further examination might complement the academic literature in the future.
Finally, all interview studies illustrated that digital maturity can indirectly improve an organisation’s
financial performance in terms of the four above-mentioned firm performance aspects (FP6). For
example, company H implemented HoloLens technology in their manufacturing processes, which
decreased the rejection rate of certain medications by 50% and, thereby, the cost of these goods.
Moreover, the adoption of chatbots, speech recognition and co-browsing in call centre operations
allowed company G to reduce employee costs. The academic literature has also confirmed this indirect
relationship (Agarwal et al., 2010; Bughin et al., 2017).
Nevertheless, digital maturity advancements do not improve financial performance in the short term, as
companies must first invest substantial resources in digital technology and the transformation of the
organisation. Interview study A revealed that this process requires even more effort in corporations,
whose inflexible nature poses additional challenges. Soule et al. (2016) have reinforced this statement
in their research paper which indicates that older and larger companies that are burdened with inflexible
legacies experience more substantial difficulties during their digital journeys. Furthermore, the digital
maturity of an organisation affects the ability of digital initiatives to save on costs or improve revenue
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(Fitzgerald et al., 2014). The interview studies yielded the same results, as company H, a Digirati, was
the only organisation to derive revenue improvements from digital initiatives.
The preceding sections have addressed the second research question of this master thesis: ‘How does
digital maturity impact firm performance?’ The academic literature as well as interview study research
demonstrate a positive impact of digital maturity on the firm performance aspects of products and
services, internal processes, customer engagement and financial performance. However, only the
literature has mentioned a positive influence of digital maturity on partner and competitor collaboration,
as multiple interview studies indicate that maturity differences between parties inhibit this relationship.
In view of this, future research should examine this connection.
Research question 3: What factors influence digital maturity?
All interview studies identify a positive relationship between a digital workforce and digital maturity
(IF1). In fact, respondent A8 stated that the absence of a digital workforce impeded the implementation
of digitally enabled initiatives throughout the enterprise. In such a case, the organisation cannot improve
their digital intensity. Company F experienced a similar scenario, as several employees were not able
to integrate technologies that were developed by the IT department. As a result, they often disregarded
digital initiatives and thereby precluded digital intensity improvements. Since the lack of a digital
workforce acts as a ‘bottleneck’ in digital transformation, organisations try to close the skill gap by
hiring digital natives as well as training existing employees. The academic literature has also supported
a positive impact of a digital workforce on digital maturity (Ehorus, 2017; Mettler & Pinto, 2018; PWC,
2016). Therefore, two sources of evidence verify the above-mentioned connection.
The interview studies also reveal that a digital culture stimulates the digital maturity of an organisation
by motivating innovation and collaboration (IF2). For example, the Cloud-based Services (CBS)
department of company E continuously innovated with Azure technology to create digital analyses
capabilities. With such capabilities, they developed digitally enabled personalisation initiatives that
stimulated the digital intensity dimension. Nevertheless, business-oriented departments often refused to
surrender their traditional ways of working and thus disregarded these initiatives. Middle management
in particular abused their executive power to hinder the implementation of these initiatives.
Consequently, digital transformation was limited to isolated business units. Company F experienced a
similar situation, as digitally averse executives managed certain business units and did not motivate
their employees to embrace digital change. Hence, the absence of a digital culture impeded digitalisation
in companies E and F. Meanwhile, company C stimulated innovation and collaboration via ambassador
programs, lectures and inspiration sessions, which cultivated a digital culture in which digital initiatives
were not only developed but also shared across organisational silos. Such effects heightened both the
digital intensity and transformation management intensity dimensions of the organisation. The
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academic literature has also noted the positive relationship between a digital culture and digital maturity
(Agarwal et al., 2010; Gill & Van Boskirk, 2016). Therefore, according to the academic literature and
empirical research, digital culture is an influencing factor of digital maturity.
All interview studies highlighted the positive impact of digital capability on digital maturity (IF3). The
interviewees stated that organisations should connect technologies because digital capability drives the
digital intensity dimension. For example, company D connected data warehouses with machine learning
technologies to acquire data analysis capabilities for targeting customers with more personalised
content. In organisation B, the IT department connected Azure IoT Hub, Azure Data Bricks and Power
BI to derive insights regarding the infrastructure status within the municipality. Such knowledge
informed predictive maintenance techniques, which prevent substantial damage to infrastructure.
Nevertheless, the creation of digital capability can be complex given that legacy technologies are not
easily connected. For instance, company G implemented duplicative and non-compatible applications
within business processes, which significantly obstructed the development of digital capabilities. Since
such capabilities encourage digitally enabled initiatives, organisations are motivated to replace their
legacy applications with platforms such as Microsoft Azure. The academic literature has also stated that
digital capability advancements positively impact digital maturity (Sia et al., 2016; Hägg & Sandhu,
2017; BCG, 2018). Therefore, both the literature and the interview study research validate the above-
mentioned relationship.
According to all interviewees, digital leadership is an influencing factor of digital maturity (IF4).
Executives are positioned to plan and orchestrate digital transformation, as their executive power
enables top-down digital change. For example, the chief digital officer and chief information officer of
company C supported and propagated digital transformation across the organisation. To this end, they
aligned digital initiatives, engaged stakeholders and removed technical and human obstacles. Hence,
digital leadership enabled the establishment of a vision, engagement and IT-business relationships,
which contributed to the transformation management intensity dimension. Respondent D1 also
referenced the above-mentioned connection, as he observed that an absence of digital leadership inhibits
digital change. Company D was managed by a board of directors that funded only bottom-up initiatives
and provided no top-down guidance. Thus, executives did not develop a digital vision, governance,
engagement or IT-business relationships, and digital transformation was limited to isolated initiatives
within a small number of business units. To avoid this outcome, companies should incorporate digital
leadership to drive digital change across the entire enterprise. Most of the academic research in Table
3 has also supported the positive influence of digital leadership on digital maturity (Fitzgerald et al.,
2014; Kane et al., 2015; Westerman et al., 2011).
According to the interview studies A, F, G and H, digital leadership also positively impacts the
development of a digital workforce, culture, capability and vision (IF5). As noted, executives are
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positioned to drive top-down digital change by supporting initiatives that aim to enhance the other four
influencing factors. For example, respondent A4 stated that the digital mindset of c-level executives
stimulated digital analysis capabilities, as they provided funding and managed the transition from old
legacy systems to Microsoft Azure. Moreover, the leadership team of company H established a digital
vision and strategy to guide the organisation along their digital journey. In addition, the executives
supported initiatives, such as a ‘digital hero’ program, to encourage a digital mindset throughout the
organisation. Nevertheless, since the literature has not identified this connection, future research should
consider its validity.
All interviewees also argued that a digital vision positively impacts digital maturity because it indicates
an organisation’s intended position in the future and clarifies how digital initiatives will support this
transition (IF6). Thus, a digital vision specifies how the development of a digital workforce, culture and
capability drives digital transformation. Interview study A similarly remarked on the importance of a
digital strategy to obtain the above-mentioned influencing factors. For instance, the vision of company
C proposed that a digital culture could stimulate organisation-wide change, while their digital strategy
provided concrete examples of cultivating such a culture. Accordingly, the company launched
initiatives such as an ambassador program and digital ‘boot camps’. Academic research has also noted
the positive impact of both influencing factors on digital maturity (Kane et al., 2017; Matt et al., 2015).
Therefore, both the literature and empirical research highlight the importance of both factors.
Finally, interview studies A, E, F, G, H and I indicated that organisations can only motivate significant
improvements in digital maturity if they possess and have aligned the five influencing factors (IF7).
The main reason for this criterion is the severe obstruction to digital transformation that is due to the
absence of one or multiple influencing factors. For instance, company E lacked a digital workforce as
well as a digital culture. Accordingly, lower levels of the organisation disregarded digital initiatives
despite the presence of digital leadership, vision and capability. Moreover, company H was digitally
mature in the transformation management intensity dimension, but legacy IT halted various initiatives.
Interview study A also illustrated that the influencing factors must be aligned to ensure a seamless
digital journey. For example, when developing digital capability, companies should consider the digital
skillsets of employees; otherwise, discrepancies between skillsets and technological possibilities could
discourage personnel from adopting new technologies. The academic literature has not explicitly
mentioned this relationship, as it contains no consolidated set of overarching factors in the first place.
Therefore, future research should compose a comprehensive overview prior to validating the above-
mentioned relationship.
The preceding sections have elaborated on the third research question of this study: ‘What factors
influence digital maturity?’ According to the academic literature and empirical research, the influencing
factors of digital workforce, digital culture, digital capability, digital leadership and digital vision
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positively impact digital maturity. Furthermore, the interview study research identified two additional
relationships. First, the influencing factor of digital leadership drives the creation of the other
influencing factors. Second, alignment of the five influencing factors is imperative to significantly
improve digital maturity. Since the literature has not mentioned these links, future research should
further investigate their existence.
Research question 4: Which industry-specific factors moderate the relationship between the influencing
factors and digital maturity?
Interview studies A, B, D, E, G, H and I support a negative impact of institutional factors on the
relationship between the influencing factors and digital maturity (ISF1). Two elements induce this
effect. First, respondent B1 stated that regulations such as the GDPR are not transparent, as they have
several possible interpretations. Therefore, digital initiatives are often postponed to first consult
additional experts. As such, institutional factors substantially slow digital transformation. Second, the
ambiguity of regulation encourages digital aversion among employees. For instance, company E set up
a cloud approval board to individually authorise each cloud initiative despite the implementation of
Azure Active Directory. Multiple stakeholders were conscious proponents of this redundant governance
mechanism, which hindered digital transformation. The academic literature also supports above-
mentioned connection, as multiple studies have confirmed the negative influence of institutional factors
on the connection between the influencing factors and digital maturity (Cortet et al., 2016; Goldschmidt,
2005).
In contrast, interview studies A, C, F, H and I suggest that the above-mentioned relationship can also
be positive (ISF2). For instance, the dispersion of customer data across several databases renders
compliance with the GDPR more difficult in comparison to adopting the cloud and using one integrated
interface. In addition, interviewee F1 mentioned that the adoption of Microsoft Azure enabled company
F to comply more easily with ISO 27001. Microsoft Azure Security Services ensure compliance by
default, thereby replacing the tedious processes of manually implementing a wide array of procedures
and governance mechanisms. Thus, digital transformation facilitates company compliance, and
intensified regulatory influences can also induce a positive effect on the above-mentioned relationship.
Nevertheless, as academic research has not mentioned this influence, it warrants additional research.
Table 10 also indicates that studies A, H and I supported both relationships (ISF1/ISF2). Study H
revealed that certain companies struggle to comply with regulation because of its interpretability.
Therefore, the ambiguity of regulation deters organisations from digital transformation because it might
increase the complexity of compliance processes. Nonetheless, interviewee H1 argued that regulatory
compliance does not necessarily hinder digital transformation, as technological solutions can be
designed to comply by default. These results suggest that the impact of institutional factors is subject
to the organisational attitude towards digital change and can thus be positive as well as negative.
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In conclusion, the academic literature and interview study research both evidence that institutional
factors impact the relationship between the influencing factors and digital maturity. While academic
research has considered this impact to be negative, the empirical study reflects that its influence is
dependent on the organisational attitude towards digital change. This conclusion addresses the fourth
research question, ‘Which industry-specific factors moderate the relationship between the influencing
factors and digital maturity?’ based on an in-depth exploration of the factors of interest.
Research question 5: How does Microsoft Azure impact the influencing factors and consequently
influence digital maturity?
All interview studies support a positive impact of Microsoft Azure on the creation of a digital workforce,
as the platform enables employees to adopt and implement technologies that would otherwise exceed
their technological comfort zone (MA1). Furthermore, technologies can be implemented more easily
and rapidly through Azure’s SaaS and PaaS solutions, which only require modification to align with
business processes. In comparison, when similar solutions are developed in on-premise environments,
personnel must understand back-end processes for networking and storage. Moreover, additional time
is expended on software and hardware procurement prior to any development activities. For instance,
IT personnel in company F were able to formulate machine learning solutions with more ease and speed,
while business-oriented personnel conducted complex analyses via business intelligence and
virtualisation solutions without IT assistance. In conclusion, Microsoft Azure enables employees to
more easily and rapidly adopt advanced digital technology without requiring extensive technological
knowledge. In this way, it drives digitally enabled initiatives and thereby indirectly stimulates the digital
intensity dimension. Internal case examples also support this relationship, as Dixons Carphone and
Maersk used Microsoft Azure to foster a digital workforce that is capable of implementing advanced
technology.
The interviewees also mentioned the positive influence of Azure on the creation of a digital culture that
is focused on collaboration and innovation (MA2). This effect derives from two elements. First,
Microsoft Azure presents multiple solutions, such as Azure DevOps and GitHub that encourage co-
operation and experimentation. Company C implemented these solutions to improve software
development processes by allowing developers to collaborate in parallel and use open-source software
from other providers. Second, the characteristics of this cloud platform contribute to a digital culture.
Azure Active Directory, the platform’s governance mechanism, provides automatic and enhanced
security, access management, scalability and reliability for connecting users. Respondent I1 believed
that this governance mechanism simplified governance processes, as the IT department did not have to
individually address the authorisation of employees. Instead, Azure Active Directory enabled this
department to designate specific business roles that warranted different authorisations and were
applicable to the entire workforce. This action improved the transparency of governance processes,
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thereby enabling the IT department to remove redundant restrictions on internal co-operation and data
sharing. Moreover, Azure reduces the risks of innovation. Interviewee E1 indicated that its pay-per-use
model and the ability to easily and swiftly generate solutions reduced barriers to experimentation, since
employees could adopt and implement technologies without committing extensive resources. In
conclusion, Microsoft Azure supports an innovative and collaborative culture. Therefore, the cloud
solution facilitates engagement and IT-business relationships and drives the development and
implementation of digitally enabled initiatives throughout the entire firm. Therefore, Azure indirectly
stimulates both the digital intensity and transformation management intensity dimensions. Chapter 3
has also demonstrated this relationship through the case examples of Carlsberg, Coca-Cola and Taibah
University, which indicate a positive impact of Azure on the formation of a digital culture.
All interviewees confirmed the positive connection between Microsoft Azure and gains in digital
capability by explaining that the platform helps organisations connect technology (MA3). The main
reasoning behind this explanation is that data and technology reside on the same platform instead of
across separate business units. Furthermore, Azure’s technologies and databases use standard protocols
that simplify communication processes. Consequently, they can be easily connected without manual
development of integration layers. As noted, the adoption of technologies is facilitated by the SaaS and
PaaS solutions of Azure, which only require personnel to modify their specifications prior to their
implementation. As a result, technologies do not need to be developed from scratch before they can be
combined into digital capabilities. Hence, the above-mentioned aspects increase the speed and ease of
acquiring digital capability, which supports digitally enabled initiatives and thereby drives digital
intensity. Internal documentation also supports this connection, as most of the case examples in Table
6 illustrate the positive impact of Azure on capability development.
Interview studies B, D and H support the positive relationship between Azure and the creation of digital
leadership (MA4). Respondent B1 mentioned that the opportunities of Microsoft Azure triggered
executives to consider the role of technology within business processes. Consequently, they realised the
relevance of digitalisation and subsequently supported digital initiatives. Respondent D1 also stated that
executives in company D generated digital awareness after noting the positive impact of Azure on
multiple business processes and thereafter offered substantially more management support for digital
change.
The other interview studies did not agree with the above-mentioned relationship, as the respondents
believed that external influences affect the cultivation of digital leadership. In study A, executives
developed a digital mindset to meet or surpass competitors. Respondent E1 similarly reported that
management stimulated digital change to avert threats from FinTech’s (e.g. PayPal) and competitors
(e.g. ING). Moreover, the leadership team of company I initiated digital change to anticipate
demographic changes concerning the ageing of the population. Respondent I1 indicated that Microsoft
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Azure supported management in driving digital change through its positive impact on the development
of a digital workforce, culture and capability. Chapter 3 has rejected the positive impact of Microsoft
Azure on the creation of digital leadership given that no internal case examples highlighted this
connection.
Finally, studies D, E, F, H and I evidenced the positive impact of Microsoft Azure on formulating a
digital vision (MA5). According to respondent D1, the cloud platform supported executives in
developing a digital vision by illustrating the conceivable implementation of technology in business
processes. Microsoft Azure induced the same effect in company E, which stimulated executives to
consider the role of advanced technologies in banking processes. This cloud solution therefore
stimulates the transformation management intensity dimension by fostering the leadership capability of
vision. Internal documentation marginally suggests this connection, as only one case example reported
a positive impact of Microsoft Azure on the creation of a digital vision.
In contrast, interview studies A, B, C and G did not evidence a pivotal impact of Azure on generating a
digital vision. For example, interviewee G1 stated that the executive team constructed a digital vision
according to external developments in the pharmaceutical industry. Microsoft Azure contributed to this
vision only by specifying which technologies should be implemented. Thus, Azure can provide an
organisation with the technology to realise a digital vision.
To summarise, the internal literature and interview study research support a positive impact of
Microsoft Azure on the influencing factors of digital workforce, digital culture and digital capability.
However, both the academic and empirical research have rejected the connection between Azure and
the creation of digital leadership since external aspects, such as the market entry of new competitors,
can impact this influencing factor. Lastly, both sources only slightly evidenced a positive effect of Azure
on the development of a digital vision; nevertheless, because of the exploratory nature of this study, it
considers this relationship. Future research should further explore this connection to confirm its
existence. These conclusions answer the fifth research question of this master thesis: ‘How does
Microsoft Azure impact the influencing factors and consequently influence digital maturity?’
5.2.2 Relationship modification
Table 10 indicates that all relationships that were noted in the literature also emerged in the interview
study research. The interviewees also mentioned five additional connections regarding the research
topics. However, the number of validations per relationship differs substantially. For example, all
interviewees highlighted the connection between digital maturity and internal processes (FP2), whereas
the connection between Microsoft Azure and digital leadership (MA4) only arose in three of the studies.
Thus, the first relationship is more likely to be valid compared to the latter. Hence, the number of
validations per relationship determines its inclusion in the conceptual model. Since this thesis is
65
explorative in nature, the criteria for adopting a certain relationship are relatively low. Future research
should analyse these connections as well to verify their existence. Table 11 lists the criteria for including
or excluding a certain connection.
Table 11. The criteria for including or excluding relationships
What are the different scenarios? Include in model Exclude from model
Relationship is supported by literature and at least four case studies. x
Relationship is supported by literature and less than four case studies. x
Relationship is supported by interview study research and confirmed by at least three other
studies. x
Relationship is supported by interview study research and confirmed by less than three other
studies. x
By applying the criteria in Table 11, one connection was excluded, while four additional relationships
were incorporated into the conceptual model. Interview studies B, D and H reflect a positive relationship
between Microsoft Azure and digital leadership (MA4), but the literature has not mentioned this
connection. Therefore, it is debatable and excluded from the conceptual model. The four additional
relationships (FP5, IF5, IF7 and ISF2) are absent from the academic literature but supported by at least
four interview studies. In view of this, the final conceptual model includes these connections, as
visualised in Figure 12.
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Figure 12. The final conceptual model
Figure 12 depicts the final conceptual model of this master thesis, which is based on literature as well as interview study research. The model not only contains
all of the connections that were studied but also indicates which additional relationships it includes (underlined) and excludes (bold) based on the criteria of
Table 11.
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6. Conclusion
This thesis has elaborated on the relationship between Microsoft Azure, digital maturity and firm
performance. Moreover, it has discussed the influence of institutional factors on this connection. The
preceding chapters have analysed these relationships from an academic standpoint and subsequently
validated the findings via interview study research. This chapter applies the findings to answer all of
the research questions and concludes by specifying the academic and practical contributions of this
study.
6.1 Key findings
Research question 1: How to conceptualise digital maturity?
Digital maturity can be conceptualised by combining two elements: a definition and a maturity model
(Suddaby, 2010). The academic literature has only provided concise decompositions of the concept and
described characteristics of digitally mature companies (Westerman & Bonnet, 2015). Thus, the present
study consolidated multiple definitions of digital maturity and several maturity models into one
comprehensive overview. Subsequently, it applied various criteria to select the most appropriate
conceptualisation. For instance, a digital maturity definition was adopted only from academic research,
as the use of another source would negatively impact the literature review (Westerman et al., 2012).
Moreover, digital maturity models were only considered if they propose an idiosyncratic transformation
path (Lucas & Goh, 2009; Agarwal et al., 2011; Karimi & Walter, 2015). By employing these criteria,
the definition and maturity model of Fitzgerald et al. (2014) were selected to conceptualise digital
maturity. On this basis, digital maturity was defined as ‘[a] combination of technology-enabled
initiatives and technology management that decide on an organisation’s ability to digitally transform’.
Meanwhile, the maturity model dually considers the dimensions of digital intensity and transformation
management intensity to determine an organisation’s maturity archetype.
Research question 2: How does digital maturity impact firm performance?
Organisations are motivated to pursue digital maturity because it heightens firm performance (Iansiti &
Lakhani, 2014). Multiple studies have highlighted significant performance differences between
digitally mature companies and their less mature competitors (Westerman et al., 2012; Fitzgerald et al.,
2014). However, the academic literature has not composed a consolidated overview of the performance
aspects that benefit from digital maturity (Tolboom, 2016). Therefore, this study consolidated such
aspects into an overarching set of five firm performance factors: products and services, internal
processes, customers, partners and competitors, and financials. The literature review indicates that
digital maturity positively impacts firm performance by enhancing products and services, internal
processes, customer engagement, partner and competitor collaboration, and financial performance. The
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interview study research evidences a positive effect of digital maturity on all performance aspects but
partner and competitor collaboration, which multiple respondents claimed is inhibited by differences in
digital maturity between organisations.
Research question 3: What factors influence digital maturity?
As noted, organisations can substantially benefit from improving their digital maturity (Iansiti &
Lakhani, 2014; Westerman et al., 2012). Nevertheless, numerous firms have not initiated a digital
transformation (Andriole, 2017; Kane et al., 2017). Academic research has concluded that a lack of
guidance and the absence of best practices induce this trend (Westerman et al., 2012). In this regard,
there is also no consolidated overview of the influencing factors of digital maturity. Therefore, the
present study combined all factors into an overarching set of five influencing factors: digital workforce,
digital culture, digital capability, digital leadership and digital vision. The literature study thus states
that the development of these factors contributes to both digital maturity dimensions, which is further
supported by empirical research. Moreover, the interview studies identified two additional
relationships: first, the creation of digital leadership stimulates development of the other four
influencing factors as well; second, substantial digital maturity improvements are achievable only when
all five influencing factors are present and aligned, as the absence of one or more factors would hinder
the advantages of the remaining influencing factors for digital maturity.
Research question 4: Which industry-specific factors moderate the relationship between the influencing
factors and digital maturity?
According to the academic literature, many firms are not digitally mature (Fitzgerald et al., 2014; Kane
et al., 2015). Numerous research papers have claimed that this trend is industry wide, as all sectors host
Beginners (Andriole, 2017). However, substantial maturity differences between industries disprove this
statement (Westerman et al., 2012). Industry-specific factors, such as regulation, induce such
discrepancies by impacting the relationship between the influencing factors and digital maturity
(Agarwal et al., 2010). Research has mentioned three types of industry-specific factors: economic,
institutional, and social and cultural (Crowston & Myers, 2004). Since the importance of institutional
factors has increased substantially over the last years, this study has focused on the institutional
perspective. The academic literature has indicated that institutional factors negatively moderate the
above-mentioned relationship by significantly discouraging technology-enabled initiatives
(Goldschmidt, 2005; Lerer & Piper, 2003; Sia et al., 2016). For instance, regulatory influences were
obstacles to the adoption of HIT systems by healthcare organisations (Agarwal et al., 2010). Moreover,
regulatory requirements force credit institutions to optimise for regulatory compliance, security and
resilience instead of agility and innovation (Cortet et al., 2016). In contrast, the interview study research
implies that the impact of institutional factors depends primarily on the organisational attitude towards
digital change, which evidences that the above-mentioned connection can be positively and negatively
69
influenced. Additional research is necessary to assess the positive or negative nature of the effect of
institutional factors. Moreover, the economic and social and cultural perspectives of industry-specific
factors warrant further attention to comprehensively answer the fourth research question.
Research question 5: How does Microsoft Azure impact the influencing factors and consequently
influence digital maturity?
The academic literature has not addressed the relationship between Microsoft Azure, the influencing
factors and digital maturity. Therefore, this study has used internal documentation and empirical
research to explore this connection. Case examples illustrated a positive influence of Microsoft Azure
on the influencing factors of digital workforce, digital culture and digital capability. As such, Azure can
indirectly stimulate the digital intensity and transformation management intensity dimensions. For
instance, Carlsberg implemented this cloud platform to develop a collaborative and innovative culture;
consequently, they carried out co-operative digital initiatives throughout the enterprise. Meanwhile,
Johns Hopkins adopted Microsoft Azure to advance digital capabilities for implementing data-driven
intelligence within business processes. As a result, employees became capable of providing more
sophisticated care to patients. The interview study research also supports these connections, as all
respondents cited a positive impact of this cloud platform on the creation of a digital workforce, culture
and capability.
Both sources of evidence also suggest a positive connection between Microsoft Azure and digital vision.
However, support was less conclusive, as only one internal case example and five interviewees
confirmed this link. Finally, both internal documentation and empirical research rejected the positive
impact of Azure on the creation of digital leadership for two reasons: none of the case examples
mentioned this relationship, and respondents considered external aspects to influence this factor instead.
Main research question: How does Microsoft Azure impact digital maturity and consequently affect
firm performance in different industries?
The findings of this study successfully address the main research question of the master thesis. Internal
documentation and the interview study research support a positive relationship between Microsoft
Azure and development of the influencing factors of digital workforce, digital culture, digital capability
and digital vision. Since these influencing factors in turn stimulate the digital intensity and
transformation management intensity dimensions, Azure indirectly enhances digital maturity.
Moreover, the academic literature and empirical research confirm that an uplift in digital maturity
improves an organisation’s products and services, internal processes, customer engagement and
financial performance. Therefore, Microsoft Azure positively influences digital maturity and, as a
result, firm performance. In addition, since the cloud platform is designed to comply by default, the
influence of institutional factors on the above-mentioned connection is marginal, and the impact of
70
Microsoft Azure on digital maturity and firm performance does not substantially fluctuate across
industries. However, since this study does not deliberate the impact of economic or social and cultural
industry-specific factors, their influence on the above-mentioned relationship warrants attention in
future research to examine potential discrepancies across industries.
6.2 Academic implications
This master thesis complements academic research in multiple ways. First, it expands on the concept
of digital maturity by consolidating several definitions and maturity models (Subbady, 2010).
Consequently, it extends the existing knowledge base with insight into digital maturity and its
underlying items (Westerman & Bonnet, 2015).
Second, the study has consolidated all performance aspects that benefit from digital maturity
improvements into a set of five firm performance factors. With this approach, organisations are not
confronted with a host of aspects that confuse rather than inspire them (Tolboom, 2016; Kane et al.,
2017). Moreover, the study has explored the connections between digital maturity and the five factors
in more detail and imparted a deep understanding of the impact of digital maturity on firm performance.
In this regard, the positive relationship between digital maturity and partner and competitor
collaboration was evidently conditional, as it accepts no digital maturity differences.
Third, this study provides more insight into the factors that impact digital maturity. The academic
literature has aimed to guide organisations along their digital journey by indicating the influencing
factors of digital maturity (Kane et al., 2015; Fitzgerald et al., 2014; Hägg & Sandhu, 2017). However,
research papers have often proposed overlapping or contradictory factors, which has increased the
complexity of digital transformation (Kane et al., 2017). Therefore, this study has combined all factors
into a set of five overarching influencing factors. Moreover, it has discussed the relationships between
these factors and digital maturity. Thereby, it complements the existing academic research in two ways.
First, it composes a comprehensive set of factors based on all of the influencing factors that have been
mentioned in numerous papers. Second, by extensively examining the individual connections, the
research highlights how these factors influenced digital maturity and in which dimensions. The
interview study research offers two additional findings that are pivotal to the relationships between the
influencing factors and digital maturity. Despite their significant impact on the above-mentioned
relationships, academic studies have not mentioned them, so the present study contributes such a
discussion to the academic literature as well.
Fourth, this master thesis explores the impact of industry-specific factors, whereas most academic
research has not differentiated between industries (Zhu et al., 2006). The IS literature has addressed a
narrow range of sectors and infrequently considered industry-specific effects (Chiasson & Davidson,
2005). Since these factors significantly influence IS topics, the present study has investigated their
71
impact on the relationship between the influencing factors and digital maturity. Nevertheless, time and
resource constraints limited the scope of this thesis to the institutional perspective. Accordingly, it has
only explored the impact of institutional factors on the above-mentioned relationship. Remarkably, the
literature review suggests that this impact is negative, whereas the interview study research indicates
that it is dependent on an organisation’s attitude towards digital transformation. These findings
contribute to the academic literature. Nevertheless, future research should consider whether institutional
factors have a positive or negative impact and investigate other industry-specific factors that affect this
relationship.
Finally, this research contributes an analysis of the relationship between Microsoft Azure and digital
maturity. Academic research has revealed the advantages of cloud computing for technological
development (Bharadwaj et al., 2013; Antonopoulos & Gillam, 2010). Nevertheless, neither the
influence of cloud technology on digital maturity nor the relationship between Microsoft Azure and
digital maturity have received academic attention. Therefore, the positive connections between Azure
and the creation of a digital workforce, digital culture, digital capability and digital vision contribute to
the academic literature by confirming the indirect relationship between this cloud platform and digital
maturity improvements.
6.3 Practical implications
Over the last decade, the concept of digital maturity has increased in importance (Kane et al., 2017).
For example, journals such as Information System Research and MIT Sloan Review have published
multiple articles on the topic. Moreover, consulting firms such as Deloitte and Capgemini have adapted
their service offerings to provide more guidance in their clients’ digital journeys. Despite these efforts,
executives have encountered various obstacles to their digital transformation (Westerman et al., 2011;
Piccinini et al., 2015). Therefore, this study provides practical insights on the concept of digital
maturity.
Interview companies
First, the research has discussed the conceptualisation of digital maturity to present executives with a
more deliberate understanding of the topic and its underlying items. It is crucial for organisations to
comprehend the digital maturity dimensions and how they are affected. Moreover, management teams
can use such knowledge to assess their own digital maturity and map their future digital transformation.
Thereby, executives can transform their organisations and consequently induce digital maturity
improvements.
Second, this thesis clarifies the impact of digital maturity on firm performance. Therefore, the research
provides a more consolidated overview of the firm performance aspects that benefit from digital
72
maturity enhancements. With this knowledge, executives can conceptualise how digital maturity drives
specific firm performance aspects. Consequently, organisations can more accurately quantify the impact
of digital maturity improvements and, as a result, easily justify investments in digital transformation
initiatives. As such, this paper enables executives to make more well-informed investment decisions
about digitalisation.
Third, the study has consolidated and extensively discussed the influencing factors of digital maturity,
thereby identifying five influencing factors that stimulate either one or two dimensions of digital
maturity. This simplification avoids confusing organisations with a wide array of digital transformation
options. Rather, they can focus their efforts on building the five comprehensive factors to advance both
digital maturity dimensions. In terms of financial resources, companies can also allocate their
investments to specific initiatives instead of wasting assets on an excessive number of projects.
Moreover, this study indicates that companies should develop and align all influencing factors, as the
absence of one or more of them inhibits digital maturity. As such, firms can assess whether any factors
are lacking and the effects on their digital journey. In addition, since this study highlights digital
leadership as the most pivotal factor of digital maturity, companies can stimulate their executives to
support and propagate digital change.
Fourth, the study has investigated the impact of industry-specific factors on the relationship between
the influencing factors and digital maturity. As noted, academic research on industry-specific factors is
minimal (Zhu et al., 2006; Chiasson & Davidson, 2005). Consequently, organisations cannot understand
their impact on digital transformation. Such ignorance imposes two negative effects. First, industry-
specific factors, such as regulation, can deter companies from initiating their digital transformation
(Agarwal et al., 2010; Murdoch & Detsky, 2013). Second, firms that do not consider these factors when
initiating digital transformation might be halted by regulators for their non-compliance (Mettler &
Pinto, 2018; Sia et al., 2016; Sing & Hess, 2017). Therefore, the discussion of industry-specific factors
offers insight for firms in various sectors that can enable them to drive digital transformation while
taking industry-specific factors into account. As such, companies can induce digital maturity
improvements while implementing compliant technologies within their business processes.
Furthermore, the insights of this study evidence that industry-specific factors can positively and
negatively influence the above-mentioned connection. This information can reconcile proponents and
opponents of digital change, thereby resolving stand-offs between organisational departments.
Nevertheless, as this study explores the impact of institutional factors only, additional research is needed
to determine the influence of economic as well as social and cultural factors.
Finally, this study indicates a positive impact of Microsoft Azure on the creation of a digital workforce,
digital culture, digital capability and digital vision. Accordingly, it might motivate organisations to
implement Azure and consequently stimulate their digital maturity via the development of the five
73
influencing factors. In addition, the findings of this research paper can highlight useful business cases
to advance the adoption of Azure. Consequently, employees and executives can more easily justify
investments in this cloud solution. As such, the thesis advocates for a shift from on-premise data centres
to cloud computing, and more specifically, Microsoft Azure.
Microsoft Nederland
The present study has noted a positive effect of the five influencing factors on digital maturity
improvements. Microsoft Nederland can utilise these findings to create new product and service
offerings that improve the guidance of customers along their digital journeys. For example, ‘modern
workplace’ solutions (e.g. Office 365) can focus more on co-operation and innovation, thereby
stimulating the development of a digital culture. In addition, advancements in ‘business application’
technologies (e.g. Dynamics) might reduce organisational silo’s regarding data and applications and
consequently drive the creation of digital capability. Moreover, Microsoft Nederland can provide
additional services that focus on the creation of the influencing factors as well. For instance, Microsoft
Consulting Services might be able to train a client’s workforce to use digital technologies, such as
Power BI, and consequently develop a digital workforce. Accordingly, Microsoft Nederland can adapt
their client offerings to the five influencing factors of digital maturity to more comprehensively assist
clients along their digital transformation journey. Nevertheless, the offerings must focus on all
influencing factors of digital maturity, as substantial maturity improvements are achievable only when
all five influencing factors are present and aligned.
As noted, this thesis supports the positive connection between Microsoft Azure and the development of
the digital workforce, digital culture, digital capability and digital vision. Microsoft Nederland can use
this knowledge to strengthen cloud propositions to current and potential customers. Such insight induces
two effects. First, existing clients might not only consider Microsoft Azure as a substitute for on-premise
data centres, but also recognize its potential for applications such as machine learning and IoT.
Accordingly, customers can be motivated to transition from simple workloads (e.g. computing) to more
advanced workloads (e.g. analytics) that consequently drive digital maturity improvements. Second,
potential clients are provided with academic research that addresses their hesitance to adopt Microsoft
Azure. As such, they are encouraged to implement this cloud solution that will subsequently assist them
along their digital journeys. In conclusion, the insights of this research could generate more sales and
equip Microsoft Nederland to more effectively support the digital journeys of their clients.
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7. Limitations and future research
The conclusions of this study warrant careful interpretation given that time and resource constraints
imposed multiple limitations. This chapter describes these limitations in terms of four research areas:
the research design, data collection, data analyses and conclusion. Moreover, it proposes
recommendations for future research which derive from the limitations.
7.1 Research design
The research design of this thesis did not specify a time period for conducting the interview study
research, which obscures potential temporal differences between data collection and data analyses. In
view of this, academics might question the credibility of all previously deliberated conclusions.
Furthermore, this study does not entail a longitudinal research design, as data collection occurred at one
specific point in time. Accordingly, it has not considered outcome deviations in the interview analyses
that originate from digital maturity changes. Moreover, the researcher spent time at client sites only
while conducting interviews, which precluded an intimate understanding of the research setting. Hence,
future research should focus on longitudinal studies to examine the impact of digital maturity changes
on the relationships of interest. Additionally, given that certain interviewees adapted their answers once
the researcher ensured full anonymity, future research should dedicate more time to visiting client sites
to take account of the impact of the research setting on the answers of participants.
7.2 Data collection
Throughout the data collection process, criteria for excluding interview studies were not specified, as
the initial number of sources was relatively low. Therefore, this thesis encompasses one interview study
that does not complement the academic literature or practical knowledge. Furthermore, the reliability
of the above-mentioned sources was not assessed. Therefore, respondents may have provided false
information during the interviews. Direct or participatory observations were also omitted due to time
and resource constraints. As a result, the conclusions are based solely on internal and external
interviews, which limits their validity. Time constraints further prevented the researcher from collecting
a mix of qualitative and quantitative data, so methodological triangulation was not possible. Future
studies should establish criteria for excluding data sources. Moreover, they must consult a more
extensive range of sources (e.g. observations) to improve the validity of the results. Finally, they should
implement quantitative methodologies to confirm and reinforce the outcomes of qualitative measures.
7.3 Data analysis
The data analysis process also entailed various limitations. First, since interviewees indicated their
opinions regarding only the relationships that were studied, the research involved no inter-rater
75
reliability tests. Consequently, the study does not reveal the degree to which respondents supported a
given connection. Furthermore, direct quotations from interviewees were not incorporated in any
interview study, as the interviews were conducted in Dutch. Thus, quotations would first require
translation, which could risk the introduction of bias. Hence, considering the above-mentioned
limitations, future studies should include information regarding the sentiment of respondents towards
relationships. Such insights could indicate the degree of support for connections. Finally, these studies
should integrate interviewee quotations to convey a more animated storyline within the analysis section.
7.4 Conclusion
The conclusions in this thesis are not generalisable across all industries. Rather, this study concerns
only the public, financial services, utilities, manufacturing and healthcare sectors and neglects other key
industries, such as telecom and retail. Furthermore, the research has not addressed these five industries
in immense detail, as industry-specific factors are not the focus of this study. As a result, findings on
this topic are limited to the effects of institutional factors, such as regulation. Digital maturity presents
a broad and constantly changing field of study; however, time and resource constraints impeded
research from a variety of perspectives. Interviews were thus conducted with personnel in IT or
management roles, which excluded more diverse perspectives. Based on these limitations, future studies
should focus on additional industries to establish conclusions that are generalisable across sectors. In
addition, they must elaborate on specific industries with respect to the relationships of interest to
construct a more comprehensive overview of the effects of industry-specific factors per sector. Finally,
additional perspectives warrant investigation to produce new insights regarding the connections that
have been studied.
76
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