Master Thesis
An exploratory qualitative research on open innovation adoption of SMEs:
A resource-based perspective
Submitted by Neha Kumari
B70280703/ S3600149 N.Sharma2@newcastle.ac.uk n.kumari@student.rug.nl
MSc Advanced International Business Management
Supervisors:
Newcastle University Business School – Dr. Karen Elliott University of Groningen – Dr. R.W. De Vries
August 16th 2019 Word Count – 14,842
1 Abstract
The key objective of this research is to explore the phenomenon of open innovation. The popularity of open innovation research is growing and the environmental forces and management practices that supports the process of open innovation has not been discussed much. As such this research aims to discuss the implications of strategy and the determinants of open innovation in the Dutch SME sector. The research conducted 6 in-depth interviews with senior employees working in the consulting, services and the manufacturing industry in the three cities – Groningen, Zwolle and Amsterdam. Later a model has been created that explains the adoption of OI principles and the determinants. The findings suggest that open innovation is the future of SME sector but the demands of the present time is a more flexible and positive attitude towards OI from the management side. Based on the findings and discussion the key propositions are presented that provides a ground for future empirical research.
Keywords: SMEs, Open innovation strategy, knowledge exploration (inbound open innovation), knowledge exploitation (outbound open innovation), resource-based view, open business model
2 Acknowledgements
First, I would like to thank my supervisors, Dr. Rudi de Vries and Dr. Karen Elliott for their constructive feedback, support, and guidance during the process of this research. I must acknowledge that they were truly honest with the feedback and patient enough to give a thorough review for my work from the starting. Second, I would like to thank my family for always believing in me and giving me the opportunity to pursue my dream of doing a Master’s course at the University of Newcastle and University of Groningen. Further, I am thankful for all the great people I met during my Master’s course. Lastly, I would like to thank all the inspiring employees who participated in this study.
3 Table of Contents
Abstract………...……….….1
Acknowledgement………..……….… 2
List of Figures………...…………4
List of tables……….….……...4
List of Abbreviations………..………..4
1. Introduction……….…….…5
2. Literature Review……….………….…….…..8
2.1 A review of open innovation………... ………....…………8
2.2 Challenges towards open innovation………....……….….15
2.3 Summary of the literature review and research Gap……….…20
3. Research Methodology………...………..…..……….…23
4. Findings………...40
5. Discussion and the grounded theory model………....………...56
6. Conclusion……….………..…...62
6.1 Managerial Implications……….…..………...63
6.2 Limitations and Future Research………..……….…………...64
References……….……..…..…..66
Appendix………...……..……74
Appendix 1: Coding Scheme………..……..….…...74
Appendix 2: Interview Guide……….…...….…...82
Appendix 3: Consent Form………....….………...….…....84
4 List of Figures
Figure 1: The Data Structure……….……….…………35 Figure 2: The grounded theory model……….……….……….…….61
List of Tables
Table 1: Demographic details of individual participants…………..……….…………28 Table 2: Ethical Issues………..….………....……….…….31
List of Abbreviations
SMEs Small and Medium Enterprises R&D Research and Development IP Intellectual Property
HR Human Resources
HRM Human Resource Management OI Open Innovation
OECD Organisation for Economic Cooperation and Development RBV Resource based view
NSH Not sold here NIH Not invented here
5 1. Introduction
Ever since it was first introduced by Chesbrough (2003), open innovation has been a topic of great interest. The most popular and widely used definition of open innovation states that:
‘Open innovation is the use of purposeful inflows and outflows of knowledge to accelerate internal innovation and expand the markets for external use of innovation’ (Chesbrough, Vanhaverbeke and West, 2006, p. 1). It is believed that open innovation practices enable firms to combine external and internal ideas, knowledge and technology and thus provide greater opportunities to technological collaboration (Lichtenthaler, 2011) and, hence, enhance their innovation capability and international competitiveness.
But, open innovation is easier said than done. The attitude of firms regarding this knowledge exchange is mostly negative (Lichtenthaler et al, 2010) that makes it hard to be realized. And in the majority of cases they still prefer in-house innovation than OI. Moreover, research so far is mostly limited to large firms with contradictory results and assumptions that may not be realized in every business environment – particularly the small and medium enterprises (Van de Vrande and Brunswicker, 2014; Van de Vrande et al., 2009; Lee et al, 2010).
SMEs, often characterised as firms with fewer than 250 employees and an annual turnover of less than 50 million euro (Kierzenkowski and Kastaneer, 2014) are considered as the backbone of an economy. They have specific characteristics that distinguish them from large corporations. They are generally independent, multi-tasking, cash-limited, based on personal relations and informality, highly personalized and local in their area (Perrini, Russo and Tencati, 2007). It is believed that they are one of the key actors in open innovation, but their context remains largely unexplored (Lee et al, 2010). Some studies show that SMEs are
6 performing better (van der Meer, 2007) while other reports show that SMEs are less open than large multinationals (Van de Vrande and Brunswicker, 2014; Van de Vrande et al., 2009) and are often sceptical about the financial gains of implementing open innovation. Although research has confirmed that SMEs are also adopting OI principles, a lot still needs to be explored because they have a specific nature and the existing findings on open innovation in large firms cannot be applied to them (Van de Vrande and Brunswicker, 2014; Van de Vrande et al., 2009). This highlights for an emphasis into SMEs in open innovation research.
Relevance to Dutch SMEs
In particular, the economic relevance of SMEs can be seen in the European nations. In the Netherlands alone, they represent over 99.7% of all enterprises close to the figure of 99.8% for the European Union (Kierzenkowski and Kastaneer, 2014). As such EU policymakers give huge importance to boosting their networks. The 2011 review of small business act (SBA), aimed at supporting European SMEs for open innovation and internationalisation, lead to great announcements for promoting new forms of collaboration between companies of the same or different regions (OECD et al, 2012). As such it can be said that these initiatives have been primarily focussed at strengthening the business networks of SMEs to encourage growth and open innovation.
However, meeting these flagship targets does not seem to be easy. Research shows that only a fraction of the total population of European SMEs including Netherlands are contributing to open innovation. Particularly, the context of the Netherlands calls for an attention. The macroeconomic situation of the country has been difficult in recent years. After the 2009 crisis Netherlands witnessed uncertainties in the macroeconomic environment (OECD, 2014). The worst consequences were for SMEs and the effects of the crisis are evident even now. Financial
7 restrictions and competences issues are still prevalent in the economy and in spite of being a highly developed knowledge-based economy Netherlands is struggling with the challenge of creating value from the knowledge. Moreover, the Netherlands ranks lower in international collaboration activities, with just 22% of the innovative Dutch firms collaborating with international partners (OECD, 2014) while the figures are 31% for France and 38% for Belgium. This presents an opportunity for researchers to examine the factors that influence this technological cooperation between SMEs and the external market in the Netherlands.
Therefore, this master’s thesis aims to explore the phenomenon of OI in the Dutch SMEs sector.
The purpose of the research is to explore the environmental factors prevalent in the Dutch SME market and the way they enable or hurt open innovation. The rest of the research is organised as follows - The next section provides a literature review on open innovation and its critics.
Based on it the research gap and the research questions are formulated. Next, the research methodology is discussed wherein, the research philosophy, research approach and the research method are stated. Later, based on the data analysis the findings are discussed. And the last sections give a brief about the limitations and perspective for future research and managerial implications.
8 2. Literature Review
Researchers should always begin their studies with prior guidance provided by some sort of orienting theoretical perspective (Locke, 2005). It is necessary to first discover relevant concepts for the purpose of theory building that can guide the creation and validation of constructs for theory generation (Gioia et al, 2012). Open innovation has a vast theoretical background and so it is first necessary to narrow down the concepts without reviewing the literature exhaustively. Not narrowing the concepts as a starting point of the research could be confusing and exhaustive for researchers and may lead to research failure. This research aims to explore the role of intermediaries for the successful implementation of open innovation in the Dutch SME sector. And the literature review is organised as follows: The first chapter describes the general overview of open innovation research. It describes the two dimensions of open innovation and its strategic implications. The second chapter discusses the criticizations of open innovation literature. Finally, drawing on the limitations and contradictions on the existing research the research gap would be developed.
2.1 A review of open innovation
Innovation is defined as the introduction of new and improved processes and products into the economy, subsequently a change in production resulting from a new or improved product, process, technique, or method (Johnston, 1966). Prior to the concept of industrialization and the need for knowledge sharing with the global market, industrial firms developed new technologies for their own products internally (Ahlstrom, 2010). Accordingly, most companies pursued relatively ‘closed’ innovation strategies with limiting interactions with the outside world. It is believed that successful innovation requires control and companies used to generate their own ideas, develop them, build them, market them and service them on their own (Vanhaverbeke and Chesbrough, 2014, p.56).
9 However, in recent decades the term ‘closed innovation’ is viewed as losing impact and a new terminology ‘open innovation’ (OI) is gaining popularity in the management and strategy literature (Chesbrough, 2003). Open innovation is embedded in the notion that the sources of knowledge for innovation are widely distributed in the economy (Chesbrough and Bogers, 2014) and that firms are increasing the acquisition and search for external technologies and knowledge through cross-border transactions. The rise in global competition, reduction in the life cycle of the product and the rising cost of research and development (R&D) are some factors that led to the evolution of the concept (Crema et al, 2014). The basic idea behind OI is that firms should look and operate beyond their boundaries and perform knowledge exploration and exploitation both inside and outside throughout the innovation process (Lichtenthaler, 2011). Particularly, the 21st century is more dynamic because of the rising globalisation and international technological collaboration, and the need for knowledge flows has been found surging more than ever. Thus, based on the assumption that valuable knowledge is widely distributed across the globe Chesbrough (2011) proposed two core types of OI namely, inbound and outbound.
Inbound open innovation or knowledge exploration refers to sourcing or acquiring knowledge or technology from outside the organisation instead of producing it on its own. It is an outside- in process where firms are more open for knowledge exploration (Lichtenthaler, 2011). On the contrary, outbound open innovation refers to the inside-out process where firms open up the innovation process to external knowledge exploitation. It is the less commonly recognized aspect where under-utilized ideas and technologies in the firm are allowed to go outside to be incorporated into others’ innovation processes. Lichtenthaler (2011) calls this as commercialization of technological knowledge. This dimension of open innovation aims at
10 earning profits by bringing ideas to market, selling intellectual property (IP), and multiplying technology by transferring ideas to the outside environment (Enkel et al, 2009).
It is to be noted that there has always been some sort of confusion with the two terms – closed and open innovation. In a review Trott and Hartmann (2009) argue that there has always been some sort of openness in the innovation and that Chesbrough has just restructured the concepts into a new dimension. Nevertheless, the degree of openness has surely surged in the present times with a change in the strategy of firms to innovate, a shift from in-house innovation to OI (Chesbrough, Vanhaverbeke and West, 2014). However, it is argued that research into this direction is still in its infant stages (Van de Vrande et al, 2009). For instance, the strategic implications of OI remains largely unexplored and mostly they have been studied for large firms (Crema et al, 2014). Therefore, the underlying study extends the OI literature by integrating it with the strategy literature.
2.1.1 Strategic implications of OI
For decades, literature on strategic management has generated theories that are popular among firms even today. Grant (1991, p.1) defines strategy as ‘the match an organisation makes between its internal resources and skills and the opportunities and risks created by its external environment’. Thus, highlighting the concept – resource-based view (RBV). The evolution of the RBV (Grant, 1991; Barney, 1991) is one of the great contributions in the strategic management literature. Whatever strategy a firm uses, it depends on its resource portfolio, strengths and weaknesses, as such the RBV approach can be considered as the backbone of strategy. Therefore, this research highlights the fundamentals of RBV before digging into the strategic choices of firms to implement OI.
11 Resource-based view
The RBV states that a firm’s internal resources and capabilities, that are rare and non-imitable, are the foundation of a long-term strategy for a competitive advantage (Grant, 1991). It underlines four basic assumptions as per the VRIO framework – value, rareness, imitability and organisation (Terziovski, 2010). Value refers to whether the resource provides a competitive advantage, rareness refers to whether competitors possess it, imitability refers to whether or not it is costly to imitate by competitors and organisation refers to whether the firm is organised to exploit the resources.
Resources here are inputs into the production process (Grant, 1991) such as the brands, tacit knowledge and competence of employees (Sveiby, 2001). Knowledge for instance is the personal skills of individuals in the economy that are valuable and difficult to be codified or imitated. Competence is broadly described as the ability to create value from the knowledge externally and internally (Sveiby, 2001). It is the mix of human knowledge, skills and aptitudes serving the enterprises productive purposes. However, whether a firm is able to exploit its resources and competencies depends on its capability to deliver added value at marketplace (Grant, 1991) – thus introducing the term organisational capability.
Capabilities are the organisation’s ability to use its resources to deliver added value in the marketplace, an organisations collective physical facilities and expertise of employees (Grant, 1991). It emphasizes how efficient the organisation is in deploying the tacit knowledge of its employees and at times in renewing and recreating its capabilities to meet the needs of changing environments. However, with changes in the global business environment and internationalisation, firms are now compelled to adapt and integrate with the external market.
This also requires their resources and capabilities to be adapting and evolving. It is this change
12 and adaptation that makes the resource-based view more dynamic – hence the term dynamic capabilities (Teece et al., 1997). Teece et al, (1997) describes dynamic capabilities as the firm's ability to integrate, build and reconfigure internal and external competencies to address rapidly changing environments. Thus, dynamic capabilities require interorganizational collaboration and co-creation to deliver added-value at marketplace and it provides an explanation of competitive heterogeneity between firms in the market. Overall, the resource-based view provides a robust approach to guide firms to formulate their strategy. Based on this the research presents an overview of the strategic choices that an SME can use to adopt OI principles.
Strategic choices for open innovation
Based on the above assumption’s literature has found two widely used strategic choices of firms - inside-out and outside-in.
Inside-out strategy (knowledge exploitation or outbound OI)
An example of a small firm that used the inside-out strategy is Shana Corp – a private Canadian software company (Miller et al, 2002). Over years Shana Corp developed its internal capabilities with the use of its vibrant innovation culture of product development and soon enough it started to share its growing knowledge with the clients who needed its abilities for their own innovations (ibid.). The managers identified what their firm was good at, developed it and later pursued those clients that would benefit from Shana’s growing capabilities (ibid.).
This way Shana Corp developed its dynamic capabilities. Thus, it can be concluded that an inside-out strategy is one that relies upon an internal orientation – inner strengths, resources and capabilities of the organisation. Firms with such a strategy try to build a vibrant innovation culture using their internal valuable resources and they also allow some of the ideas and
13 technologies to be used by other firms in their innovation processes (Chesbrough, 2011, p. 83- 84).
Similarly, firms may use the inside-out strategy to implement outbound OI. It can be implemented through three practices (Van de Vrande et al, 2009). The first is venturing.
Venturing refers to starting of new organisations drawing on internal knowledge and getting supported by the parent organisation in terms of finance, human capital, legal advice etc. Start- ups has gained huge popularity to describe young ventures. “A start-up is a company working to solve a problem where the solution is not obvious and success is not guaranteed” – Neil Blumenthal, cofounder and co-CEO of Warby Parker (Forbes, 2019). The second is outward licencing of intellectual property (IP). IP are the results of innovations that plays a crucial role in knowledge exploitation and firms out-license their IP to get more value of it (Gassmann, 2006). The third practice is to involve the non-R&D workers in the innovation process. While R&D has a long tradition of being involved in the in-house innovation, recent developments have witnessed the active integration of the non-R&D workers in the innovation process. The strategy of involving non-R&D employees basically entails leveraging the knowledge and initiatives of employees who are not involved in R&D, for example, by taking up suggestions, exempting them to implement ideas, or creating autonomous teams to realize innovations (Van de Vrande et al., 2009). This could be achieved by taking advantage of the knowledge gained by current employees on their job or possibly through their informal relationships with employees of other firms in the industry which is referred to as weak ties (De Vries, 1977).
14 Outside in strategy (knowledge exploration or inbound OI)
Conversely, the firms that rely on the outside-in strategy start with an external market orientation and study customer trends in order to design their strategy – that can be acquisitions or building relationships with key partners and customers (Gianiodis et al., 2014). And, they make great use of external ideas and technologies in their own businesses (Chesbrough, 2011, p.83-84) It highlights the strategic importance of customers, suppliers and other stakeholders to improve the organisation’s dynamic capabilities and co-create value with external partners, thus emphasizing on external knowledge exploration.
There are different ways firms may use the outside-in strategy in the context of inbound open innovation or knowledge exploration. The first is through customer involvement (Van de Vrande et al., 2009). Users are not just passive adopters of innovations but they may rather develop their own innovations which producers can imitate (Von Hippel, 2005). Firms may benefit from their ideas and so they should provide tools for their proper integration. The second dimension is external networking. It involves both formal collaborative and informal networking activities. Networks allows firms to fill the knowledge gaps without spending enormous amounts of time and money to develop that knowledge internally. External participation is another important dimension to recover the innovations that were initially abandoned. As an example, enterprises may invest in start-ups to keep an eye on opportunities (Chesbrough, 2006).
Thus, overall the above two dimensions of open innovation seem to be proliferate and organisations are aware that they cannot manage all the competencies they require in-house (Gassmann, 2006). But research shows that OI is not easy to be managed and firms are often critical about the outcomes of open innovation (Van de Vrande et al., 2009). And, it still
15 remains unclear how SMEs manage their OI strategies. Therefore, the next chapter describes the critics towards OI adoption.
2.2 Challenges towards Open innovation
The previous chapter discussed the general review of open innovation and its strategic implications. But it gives a much wider generalisation about the concept. This part goes one step further by focussing on the challenges of OI and narrowing down the literature for SMEs in the Netherlands.
Employee Syndromes
Even though the two dimensions of open innovation discussed above look promising they are not easy to be managed and the reason is the attitude of employees. According to social psychology attitudes are a major factor in human interaction and decision making and they guide an individual’s thinking and information processing, thus their behaviour (Antons et al., 2017). However, studies suggest two of the most jeopardising individual-level attitudes of employees that hampers external knowledge transfer – “not-invented-here” (NIH) attitude and
“not-sold-here” (NSH) attitude. Lichtenthaler (2011) calls this as employee syndromes.
Employee syndrome is a term often viewed as a disease that describes the detrimental consequences of an overemphasis on internal knowledge (Katz and Allen, 1982; Lichtenthaler and Ernst, 2006). As reviewed by Lichtenthaler and Ernst (2006, p.369) the term ‘syndrome’
implies that the actions that are taken because of this disease is rather systematic and occurs frequently. Thus, the NIH and NSH are the major hampering factors for OI adoption.
The NIH syndrome (Katz and Allen, 1982) describes a negative attitude towards external knowledge exploration (inbound OI). This shows a decision-making bias that occurs during the
16 evaluation of knowledge from external organisational boundaries (Antons and Piller, 2015).
This attitude stems primarily from the tendency of employees to retain the monopoly of knowledge in their field (Katz and Allen, 1982). It also results from poor experience with knowledge transfer and poor incentive systems. And, it may cause severe harm to the organisation if the external knowledge is valuable in comparison to the internal solutions (Antons et al., 2017). Moreover, cultural differences are very common with external knowledge exploration (Dahlander and Gann, 2010).
Conversely, the NSH syndrome describes a negative attitude for external knowledge exploitation or outbound OI (Lichtenthaler et al., 2010). This attitude derives from the limitations and the fear of strengthening competitors, unsatisfactory incentive systems, limited experiences with external knowledge exploitation, inefficient market and poor competitive activity (ibid.). External knowledge exploitation always comes with the risks of revealing important information and ideas that are sensitive to a firm as such it may lead to market failures because inventors are reluctant to reveal their developments (Dahlander and Gann, 2010).
When an inventor is keen to license its information to a potential licensee, it is necessary to reveal some information to the potential customer. This ‘disclosure paradox’ implies that the potential licensee receives the information without paying for it and could act opportunistically and steal the idea (ibid.). Because of this opportunistic attitude companies start to refrain from external knowledge exploitation. Thus, not-sold-here tendencies also derive from risk-averse nature of employees. These attitudes result in the difficulties of firms to successfully manage the processes. Moreover, even if a firm sets up a particular management mechanism like a ‘new hiring policy’ (Lichtenthaler, 2011, p. 84) or new incentive systems, the results are not shown automatically.
17 These limitations and the attitudes of employees show why some firms still prefer in-house innovation over open innovation. And because of these attitudes the actual results of innovation are minimized. Even from a capability-based perspective the decision to transfer knowledge is a strategic choice as discussed in chapter 2.1, but the implementation is again affected by these attitudes (Lichtenthaler et al., 2010). A majority of the sample of firms studied so far have been reported to have faced these attitudes (ibid). Therefore, it is evident that external exploration and exploitation practices are both subjected to cultural and management challenges. In order to build a good relationship with customers, firms need to explore and import knowledge and also exploit knowledge that has already been accumulated (March, 1991), thus the trade-off between exploration and exploitation is crucial for innovation (Lichtenthaler, 2011). But so far research has not been able to clarify how the balance between exploration and exploitation can be achieved (He and Wong, 2004) and the type of management practices that firms should use to better adopt OI principles (Lichtenthaler, 2011). Therefore, the research presents the management challenges related to the OI principles.
Managerial Challenges
The second critics applies to the managerial challenges or the paradox of openness (Larsen and Salter, 2014). As stated by the authors this paradox evolves because ‘the creation of innovations often requires openness, but the commercialization of innovations requires protection’
(Laursen & Salter, 2014, p.867). Accordingly, opening up and capturing value from this approach is challenging and requires a considerable managerial attention. It is this paradox which explains why firms prefer exploration over exploitation. Because the latter entails more risks and uncertainties. This paradox can also be seen from the OI practices of Dutch SMEs.
18 Van de Vrande et al., (2009) organised a study on Dutch SMEs and found that they are increasingly getting involved in both – technology exploration and exploitation, although, exploitation activities are pursued by less than 30% of their sample, whereas exploration ones are adopted by more than 90%. Among the barriers recognised from the sample are – resources, time, marketing, culture and administrative. But research needs to highlight how these barriers can be overcome. Moreover, the article could not specify how large and small firms interact for open innovation (Van de Vrande et al., 2009, p.436). Although large firms and small firms manage open innovation differently, there are occasions where they share a common platform as partners. As such it is important to focus on the management implications of these practices (ibid).
van der Meer (2007) as well-found significant differences in open innovation practices of firms.
He organised a survey on open innovation strategy in Dutch companies and found that the collaboration between innovative larger companies is different from the collaboration between SMEs (p.200). He describes Dutch firms as reluctant to take part in the exploitation activities with only 54% highly innovative companies using them vs. 74% adopting exploration practices. This shows that the Dutch market is more inbound (exploration-intensive) than outbound (exploitation-intensive). Overall these findings suggest that Dutch SMEs are more naturally suited to engage in open innovation than larger companies, but it needs to be studied how the transaction can be facilitated. Thus, the managerial challenges still remain intact.
Another challenge for managers is the applicability of RBV. Applying the RBV approach for OI strategies in SMEs is critical. RBV itself is prone to critics that calls for further clarifications of the theory (Kraaijenbrink et al., 2010). For instance, Connor (2002) argues that the RBV applies only to large firms with significant market powers and the smaller firms fall beyond the
19 bounds of RBV. As such RBV may not be applicable under unpredictable environments, in which new technologies emerge and the value of resources change drastically. This may be problematic for SMEs. It has been long argued that SMEs need to improve their organisational capabilities and organisational structure to become more efficient (Bessant and Tidd, 2007).
And that they don’t have the leverage of these resources and capabilities that large firms can easily manage. According to Nooteboom (1994) a major problem within SMEs is that their characteristics - small scale, lack of functional expertise and limitations in investment capital and resources often hamper the identification and leverage of resources needed to yield new opportunities. Thus, it still remains unclear how SMEs manage their resources and open innovation strategy. Therefore, this research aims to discuss the management practices that can overcome these challenges.
Challenge of business model
The last critic is related to the challenge of a business model. Vanhaverbeke and Chesbrough (2014) addressed the role of business models in the context of OI. ‘A business model is a framework to link ideas and technologies to valuable economic outcomes’ (Vanhaverbeke and Chesbrough, 2014, p.52). In their review they describe two extremes of business models – open business model and closed business model. The traditional stand-alone business models have the idea of closed innovation where most of the innovation is carried out in-house like internal R&D. But, with rising competition and mobility, firms are seen using a more open business models that are more networked and create value by leveraging external ideas into the process (Vanhaverbeke and Chesbrough, 2014). Open business model not only reduces the cost of innovation by the division of labour but also generates extra revenues through spin-off activities (ibid.). Especially, for the SMEs the adoption of OI is inextricably linked with the
20 open business model of the firm and the efficiency with which they build networks with external partners (Chesbrough, Vanhaverbeke and West, 2014).
However, research shows that there is a significant positive correlation between company size and network cooperation intensity (Carlsson et al, 2011). Moreover, the cultural, cognitive, organisational and institutional differences between collaboration partners have been recognised as the main barriers to the successful adoption of open innovation practices in SMEs (Van de Vrande et al., 2009). As such it is believed that SMEs do not enjoy the benefits of networking that large firms generally do. Particularly, for the Dutch economy, an increasing number of self-employed and part-time workers on temporary contracts (OECD, 2014; OECD, 2018; Baker and Gielens, 2018) raises the question of whether SMEs enjoy a robust long-term business network. Thus, the business model of SMEs is often challenging because of their weak networks and poor resource portfolio. This highlights for an emphasis into the business model of SMEs. The importance of different kinds of network and the internal dimensions of managing open innovation in the SME needs to be explored (Chesbrough, Vanhaverbeke and West, 2014). Therefore, getting an idea about the networks and the institutional supports (government and universities) is another motive of this research.
2.3 Summary of the literature review and research gap
Overall, the central premise of the literature review and the critics is that open innovation in SMEs is subjected to critical acclaim and broad claims that still needs to be validated. The strategy-open innovation construct for SMEs needs to be explored (Van de Vrande et al., 2009;
Crema et al., 2014) and the management processes and attitudes of employees that influence the collaboration between partners also needs to be discussed (Lichtenthaler et al, 2010).
21 Although the two syndromes discussed above are considered as bottlenecks in the context of OI, there are ways to legitimize and facilitate the internal adoption of OI principles. For instance, in a review Burcharth et al., (2014) demonstrated that training and competence building programs for employees can reduce the negative effects of the employee syndromes for OI. And this can be achieved through better management practices. Yet, research on employee syndromes have been mostly superficial and lacks substantial managerial implications (Antons et al, 2017; Lichtenthaler, 2011). Therefore, the research aims to explore the management practices and other determinants that eases the knowledge flows for open innovation in the Dutch SMEs.
The research considers the gap in two areas – strategic implications of open innovation in the Dutch SMEs sector and the environmental factors (barriers and enablers) that influences open innovation principles. Hence, acknowledging the work and suggestions of scholars (Lichtenthaler et al, 2010; Chesbrough, Vanhaverbeke and West, 2014; Antons et al., 2017) for further research on open innovation literature this research aims to answer the following main questions:
Q1: What are the determinants (enablers and barriers) of open innovation in the Dutch SMEs?
Q1a: What are the effects of management tools on the adoption of OI principles?
Q2: Who are the intermediaries of the open business model of the Dutch SMEs?
The research contributes to the exploratory SME literature by exploring the determinants of open innovation strategy in SMEs. First, the study aims to explore whether the Dutch small and medium enterprises follow inside-out or outside in strategy for open innovation, thereby linking the open innovation literature to strategy. Second, the research aims to link open
22 innovation literature to business model research. The research explores the components and the management culture of the business models that facilitates open innovation. The intermediaries involved in the open innovation process and the business model would give a good review of the inter-organisational networks that facilitates or hinders open innovation in the SME market.
23 3. Research Methodology
This section represents the methodology or the blueprint that governs this research and the underlying assumptions. The motive of this section to describe the setting in which the research is conducted and the methods used to do the study. The chapters below are organised as follows – first the research underlying assumptions are explained followed by the research approach.
Next, the research method is described and data collection and sample profile are explained.
Later the data analysis and the research quality are described.
Research Philosophy
The three philosophical perspectives that a researcher can follow are: positivist, interpretive and critical perspectives (D.lapan et.al, 2011, p.6-8). Positivist philosophy is most suited when the study involves testing of one or more hypotheses while, interpretivist philosophy is most suited when the researcher wants to explore a topic in general rather than testing or validating an existing model. The critical perspective is relatively new and not much in practice. This research does not intend to test or confirm any existing model but to explore an emerging phenomenon. Therefore, the study uses the interpretivist philosophy and the axiology paradigm as a way of thinking.
Axiology is the branch of philosophy that explores the nature of ethics (D.Lapan et al., 2011, p.22). The assumptions underlying this paradigm is that reality is socially constructed and can be best achieved through social constructions such as language, consciousness, shared meanings and instruments. It assumes that people are the ‘knowledgeable agents’ in organisations who know what they are trying to do and who can explain their thoughts and actions (Gioia et al., 2012). Netherlands is a culturally diverse nation with numerous
24 international students and expats studying and working. And in my view, a good sample for the study has to be culturally diverse to understand the social and ethical perspective. Therefore, the research aims to explore the subjective views of the employees of the small and medium firms who work in a culturally diverse innovative business environment and to understand every minute details about them including their culture, expertise and management skills. The research ensured to explore the attitudes of the employees towards external cooperation. In doing so it was possible to understand the realities of the business world of SMEs and how they interpret the process of open innovation.
Research Approach
Unlike the classical deductive approach in which a phenomenon is narrowed down to a specific set of hypotheses that are then tested by collecting empirical data (Adams et al, 2014), this study followed an inductive approach in which the researcher begins by collecting data and comes to a generalisation about it. Inductive reasoning is more open-ended and exploratory where the main purpose is theory building whereas deductive reasoning is narrower where the purpose is to test or confirm the hypotheses (ibid.). Hence, the focus was not on the cause- effect link like in deductive research or on finding the best or more likely explanations like in an abductive approach (Saunders et al., 2012). But to explore the reality of the small and medium enterprises including the attitudes of their employees and their subjective views about open innovation. Thus, to better understand the nature of the problem and leave room for alternative explanations of what is going on. To sum up, this research uses the interpretivist philosophy and inductive approach. The paragraphs below would address the methodological choices and the data collection and sample profile.
25 Research Strategy
In order to understand employees subjective views and experiences with the process of open innovation, this study uses exploratory qualitative research (D.Lapan et.al, 2011; Adams et al., 2014). Qualitative research refers to research that produces descriptive data, people’s own written or spoken words and observable behaviour. It is best suited for a research that explores a wider open-ended question, ‘who’ ‘what’ and ‘why’, rather than exploring or testing numerical data through complex scientific methods (D. Lapan et al., 2011, p.6). Especially the question word “what” underlines the qualitative aim of developing an initial understanding of subject instead of quantifying data and seeking generalizable results (D.Lapan et al., 2011, p.6).
The reason for choosing an exploratory qualitative research is to examine a complex phenomenon using naturally occurring data (Silverman, 2014) and to overcome the limits of borrowed theories and quantitative empiricism. Also, because the research subject has so far only been approached by few scholars, who explicitly call for more work on the subject matter (Lichtenthaler, 2011; Crema et al, 2014). Thus, the study aims to focus on a limited sample which could then be analysed with grounded theory approach proposed as described in the later section. Moreover, the study employs a combination of primary and secondary data sources to explore the phenomenon of OI.
Data Collection Primary data
Saunders et al., (2012) suggest a minimum sample size of 5-25 participants for interviews.
Hence, the research conducted 6 in-depth semi-structured interviews each lasting for 30 to 60 minutes. The interviews were audio recorded and transcribed. Non-probability sampling was used for the data collection. In non-probability sampling the probability of selecting population
26 elements is unknown and is best suited for time and cost benefits (Adams et.al, 2014). A combination of convenience sampling and snowball sampling was used for exploratory research because of the time constraints. Convenience sampling is a type of non-probability sampling where members of the target population that meet certain criteria like easy accessibility, geographical proximity, availability at a given time, or the willingness to participate are included to participate in a study. And snowball sampling is a simple way in which participants are best located through referral networks (ibid.).
The participants had to have an experience working for an SME at least once in their career.
The research ensured that the size of the firm fits in the category of a SME considering the following restrictions - Firm size: small firms (n < 50 employees), medium-sized firms (51 <
n < 250 employees) (Ranga et al, 2008). This was the first condition to be met for shortlisting.
Second, the participants had to have experience in either of the following sectors: Consulting and HR, Services and Manufacturing. The reason being that most of the earlier research has focused on one industry like manufacturing (Carree and Thurik, 1998). Therefore, having a diverse setting would allow for more robust inferences.
An interview guide with eleven, mostly open-ended and non-directive questions were used that helped the interviewer to express his/her thoughts freely and to maintain consistency across interviews, while leaving space for follow-up questions (see appendix 2). This data collection method allows the conversation to follow the interviewees’ individual responses and provides the opportunity for identifying new perspectives of the topic. The respondents’ freedom to express their feelings and beliefs in their own words can generate a greater depth of insight, such as the discovery of new themes. This represents a valuable aspect of qualitative research.
Individual interviews
27 I used my LinkedIn network to identify the participants and I tried to contact them by posting a message on their mailbox describing the purpose of study. However, it was difficult to identify who were willing to participate. Particularly, most of the female employees who were contacted did not respond. I personally visited Zwolle and Amsterdam to conduct two interviews, but it was difficult to find the remaining participants. At last, after contacting over 18 employees through LinkedIn, phone calls and emails 6 employees were selected for the individual interviews. The table below gives their demographic details. For P1, P2 and P5 the interviews were face-to-face. And for the remaining participants telephonic interviews were conducted.
Participa nt- ID
Role Gende
r
Industry Size of the firm
Age Years of experienc e
Nationality
P1 Consultant M Human
Resources and
Consultancy
< 250 31 4 Dutch
P2 Consultant M Services < 250 27 3-4 Indian
P3 Consultant M Services < 250 25 3-4 Indian
28
P4 Interim
Manager, Organisatio n Advisor, Entrepreneu r
M Food, Pump, Machine building, Manufacturin g
< 250 65 40+ Dutch
P5 IT head,
Entrepreneu r
M Services, Digital entrepreneur
<50 Exact age not know n
18+ Dutch
P6 Service
Manager
M Services <50 Exact
age not know n
9+ Dutch
Table 1: Demographic details of individual participants
29 Secondary data
One of the limitations about the primary source in this research is a small sample size. To compensate for this limitation and to draw better comparisons and validations, the research also used secondary data. Secondary data is often used to validate and compare the primary data (Adams et al., 2014) and to draw important themes that would not have been otherwise found.
Therefore, the research used academic literature and the latest OECD reports related to SMEs in the Netherlands, between years 2010-2019. The academic literature and the OECD reports are available at the online library of the University of Groningen and referenced later. The E- journals and SmartCat search engines available at the university library provided a scope for sufficient literature review needed for the study. Moreover, the Google search engine was also used to find relevant published articles on open innovation. The next chapter will describe the sample profile and the way the interviews were organised.
Sample profile
Prior to beginning the data collection, it was important to identify if the participants worked for SMEs at least once in their working career. It is noteworthy that some of the participants selected had experience with both multinationals and small firms but the research ensured to clarify whether they worked for SMEs before. This was robust for the research because they could draw on key differences between multinationals and small and medium enterprises. To ensure credibility and more robust participation, I treated them as knowledgeable experts and ensured that there were some follow up questions from their side.
All the 6 participants (see table 1 for demographic details) were employees in the Netherlands and all the interviews took place in the three cities – Groningen, Zwolle and Amsterdam. All
30 the participants confirmed to have worked in a small to medium firm (< 250 employees). In addition, 4 participants also confirmed to have owned a small business.
Maintaining gender balance was not possible in this research as all the female employees who were contacted were short of time and could not commit. Therefore, the interviews were conducted with male employees. To ensure variations in experiences, I tried to have a good mix of young and experienced professionals.
The first interview took place at Zwolle with the consultant at a HR and consultancy firm.
Furthermore, three individual participants from Amsterdam had some relevant experience in the services industry. Another interview took place with the head of the Dutch Business Partners and he was the most informative even though he had more experience with closed innovation. He was informative about the critical issues or barriers with open innovation.
The last interview took place in Groningen. This participant worked in a small agency having less than 10 employees and he also worked for multinationals. This participant has over 18+
years of total experience in which working with SMEs is the major expertise as described by him. Therefore, I focused only on the details specific to the small and medium firms. Prior to inviting them for the face-to-face or telephonic interviews I ensured that the ethical considerations are not undermined in this research.
Ethical Considerations
In order to avoid any ethical issues, the conduct of research was guided by the six key principles of the ESRC Framework for Research Ethics (Economic and Social Research Council, 2015).
Table 2 shows the six principles and what was followed throughout the research to mitigate the key ethical issues.
31 ESRC Principle Measures for an ethical research conduct Maximize benefit for individuals and society
and minimize risk and harm
To minimize the risk and harm the interview data and quotes were used in a way that could not reveal the identity of the interviewees.
By analysing the data, the research tried to find out the importance of channels and intermediaries for idea generation, knowledge exploration, retention and exploitation
Right and Dignity of individuals should be respected
To ensure that the participants are not offended, direct personal questions were avoided, like about the family members.
Participation was properly informed All the participants were informed that they need to sign a consent form prior to the interview and that the interview would be recorded. It was up to them if they wanted to withdraw. Hopefully, they all signed the consent forms before the interview.
Research should be conducted with integrity and transparency
To maintain the integrity, all participants were asked if they wanted to have a copy of the transcripts or the recording. But, no one actually wanted it as the consent form was sufficient.
Lines of responsibility and accountability should be clearly defined
The information sheet handed out contained specific details on how the data will be used and about the responsibility of the researcher Independence of research should be
maintained
The research was an independent project without any influence from third parties.
Table 2: Ethical issues
Data analysis
Data analysis of interviews
In line with the study’s interpretivist philosophy and exploratory nature, this study adopted the Gioia approach of grounded theory (Gioia et al., 2012, p.20) to analyse the interview transcripts. This method was chosen because it offers a more systematic theory-building
32 approach and is designed to bring qualitative rigor to inductive theorizing and developing new concepts.
According to this approach “qualitative rigor” is enhanced by organising the qualitative data into the 1st- and 2nd- order categories. In the 1st order analysis there is little attempt to distil categories that may later emerge from the data (ibid.). Rather it lists all the categories that can be possible from the interview. The 2nd order analysis is the phase that seeks for a pattern in the initial codes and in which the researcher considers himself/herself as “knowledgeable agent” (ibid.). Eventually the categories are reduced to a more manageable number. Finally, it is investigated if the 2nd order themes can be distilled further into “aggregate dimensions”
(ibid.). This is transformed into the data structure that finally leads to the grounded theory model after reviewing and comparing it with relevant literature to recognise possible emerging themes and structures. Thus, keeping track of this approach the qualitative data was analysed in three stages also guided by the principle of thematic analysis to identify themes or pattern in the data (Braun and Clarke, 2006) that can address the research questions.
As a very first step, existing literature was reviewed making notes of the themes that emerged out of it. The focus was to summarize what was already known. This served as an initial framework for the analysis. The first stage was for generating the initial codes (1st order categories). After each interview transcription initial codes were generated and it was ensured that the initial codes are relevant to the research questions. Examples of initial codes are –
“whereas smaller companies…you are much more agile…flexible and you can just quickly move”. Thus, this initial code is relevant to the research question in two ways. First, it explicitly relates to SMEs and second, it relates to the type of management in SMEs. Both the concepts are relevant to the research questions. Next, guided by the principle of thematic analysis, these
33 initial codes were compared and analysed to generate semantic and latent themes. Semantic theme carries the explicit or surface meanings of the data whereas a latent theme looks for the underlying meaning or conceptualization of the semantic content of the data (Braun and Clarke, 2006). These themes were then grouped into relevant 2nd order themes to answer the research questions. During this process it was important to pay special attention to emerging new concepts from the participants. It was ensured that the 2nd order themes are properly defined using phrases to give meaning to them.
For example, the initial code “whereas smaller companies…you are much more agile…flexible and you can just quickly move” was coded as “Agile management culture” (see Figure 1, Appendix 1). Next, I tried to compare the initial codes to find if there are any repetitions or pattern. For example, the quote “Countries in Europe start with a Dutch start-up or buy a Dutch start-up because it is flexible, it is quick” matched with the initial coding “Agile Management Culture”. Hence, “Agile Management Culture” is the 2nd order theme coded as per the repetition in the responses. Finally using this strategy 8 more theory and researcher centric 2nd order themes were generated. These themes were then used to construct the grounded theory model as presented in the discussion section later.
In the third stage of analysis, the 8 major themes were assembled into 3 aggregate dimensions, which captured the overarching concepts relevant to the open innovation strategy of SMEs (Figure 1). Next, to make the analysis stronger and more trustworthy it was supplemented and compared with secondary data.
Data analysis of secondary reports
34 The secondary reports were analysed to gather more information about Dutch SMEs innovative performance and the key barriers they face. As stated earlier, these reports are used as a supplement to strengthen the analysis of the primary data and make better comparisons. As a first step of the analysis, the 2nd order themes from the primary data analysis were used to find supporting or contradictory points in the secondary reports. For example, the 2nd order theme
“Duality of labour force” was found as “This divide (or duality) should be reduced” (OECD, 2014). Thus, using the secondary and primary data a better picture could be drawn. However, one extra 2nd order theme “Gender Inequality” was found from the OECD statistics (Baker and Gielens, 2018; OECD, 2018). It was on the basis of my own observation and subjective view and also because it was closely associated to the research questions. Finally, after the data analysis (Primary and secondary) the below data structure with 9 relevant 2nd order themes were finalised.
35
1.Barriers[..]Time, cost and resources 2.the time and the effort that we put in is also less because we need money 3. No budget resources
4. limited role of venture capital in risk financing
1.More part-time women workers 2. less expertise and knowledge than men
(Baker and Gielens, 2018) This divide (or duality) should be reduced” (OECD, 2014)
1.not enough background 2.less experience you have less knowledge
Duality of labour force
Lack of resources
Gender inequality
Less Experience
Barriers of OI 1st Order Categories 2nd Order Themes Aggregate Dimensions
Figure 1: The Data Structure
