MSc BA Strategic Innovation Management Thesis
Submitted for partial fulfillment of the requirements for a Master of Science in Strategic Innovation Management at the University of Groningen.
The copyright belongs to the author. The University of Groningen, Accenture and the author declare that any information provided by third parties, which these parties do not want to be made public, will be kept in confidence. Supervisor Dr. R.A. van der Eijk Co-assessor Dr. F. Noseleit Date June 20, 2016 Word Count 18.743 About the author
Abstract
Purpose – Innovation remains a difficult concept for SMEs, as many of them fail to
successfully bring new products or services to the market. The difficulty lies for a great deal in the ability to gain legitimacy. Firms need to manage their impression towards external evaluators to obtain the crucial resources they possess. This study tries to expose the interaction between the organizational elements and the evaluation given by an evaluator.
Design/methodology/approach – The study uses data obtained from a survey of 726
SMEs, of which 106 have proceeded to the jury assessment round. A logistic regression has been performed to check for initial effects of organizational elements on success. Afterwards, multiple linear regressions have been run to investigate whether the data of the firms’ elements could explain the scores given by the jury on six different criteria.
Findings – The outcomes indicate that it is difficult to explain all variance in the jury
scores by looking at the independent variables. It becomes clear that not all organizational elements show a direct significant relation with the six criteria. First of all, being affiliated with an incubator, investing more man days, working with more than three partners, investing more FTE, and starting multiple start-ups do not show any significant effect on the criteria. Combining variables, through interaction effects, have shown more promising results. Experience is a powerful factor when combined with a formal education, a diverse set of knowledge sources, and a large innovation budget. But also without experience, entrepreneurs who have a larger investment budget tend to do well on the assessment criteria. Teams that consist of both men and women do better on half of the criteria than men only teams, and pitching a product innovation is more successful when being assessed for pitch quality or the ability to answer questions. The key for entrepreneurs is to be aware of the complementarity of organizational elements.
Practical implications – It is most important for entrepreneurs to be aware that effective
management of organizational elements leads to more positive evaluations of evaluators. This will lead to a higher success rate in gaining legitimacy, which is necessary for gaining crucial resources on the pathway to success.
Originality/value – This paper shows the effect of organizational elements on the
evaluation of an evaluator. It does so by using unique quantitative data of the Accenture Innovation Awards 2014. Additionally, the uniqueness of the data allows for a direct connection between firm elements and jury criteria scores; investigating what elements lead to success when a firm is assessed by external evaluators.
Paper type – Research paper
Key words: Innovation, Legitimacy, Impression Management, Accenture Innovation
Awards, success-factors, organizational elements, SMEs
Acknowledgements
I would like to express my gratitude to my research supervisor Dr. Van der Eijk for supporting me throughout the process of writing this thesis, and to Dr. Florian Noseleit for providing additional statistical advice. The patient and thorough guidance was of great help to me to persist in delivering this paper. I would also like to offer my special thanks to my girlfriend Lizz Jansen for unconditional support, and my dear friend Wouter Nientker for helping me gain a better understanding of the statistical side of the research process. Last but not least, I want to thank my family for always supporting me.Executive Summary
Innovation has become one of the most important challenges that organizations have to face in todays business environment. However, while SMEs are well aware of the need to innovate, many of them fail to do so successfully. This struggle is well shown by the need to gain legitimacy in the market. This legitimacy is necessary to obtain crucial resources and approval from the market itself to be able to successfully implement a new product or service. Legitimacy is gained by successful impression management, and thus making it important to see what elements of the firm are being valued by the evaluating party. The Accenture Innovation Awards provides a real world situation: the competing SMEs need to gain legitimacy from the the awards’ jury to proceed to the finals. The purpose of this research paper is to answer the research question: “What elements of the
organization positively contribute to the judgment of an evaluator?”. Additionally, two
main sub research questions have been formulated to provide the paper with a clear structure.
This question will be answered by using data obtained by the Accenture Research Department. This data comes from a survey of 726 SMEs that participated in the Accenture Innovation Awards 2014. 106 SMEs proceeded to the jury selection round, and have thus been evaluated on six criteria: overall impression, impact, growth potential, concept innovativeness, quality of the pitch, and the ability to answer questions. This paper, based upon innovation literature, proposes four main hypotheses. According to this literature, human capital, research & development, organizational learning, and collaborations will all have a positive effect on the previously mentioned criteria. Most importantly, the results of the research show that these four factors do not fully explain the variance in the criteria scores. However, firms that invest a relatively high amount of money into the concept, that have more experience, pitch product innovations, and consist of men/women combination teams show more positive results on the criteria. A higher educational level or working with more knowledge partners, when looking at these variables in an exclusive view, seems to be detrimental to success in this analyses. However, when experience is combined with a higher educational level or more knowledge sources, the results show highly significant positive effects on the criteria. Entrepreneurs with more experience are abler to leverage their innovation budget, knowledge sources, and their education.
A major implication of this research is the fact that managers and entrepreneurs have to be aware of what elements are being valued by evaluators in order obtain crucial resources. Effective organizational management and impression management could improve the success rate of SMEs when confronted with an evaluator. This paper shows the influence these elements have on firm performance in evaluation situations. It also increases the awareness of the importance of gaining legitimacy when relying on innovation processes.
Table of Content
ABSTRACT ... 3
ACKNOWLEDGEMENTS ... 4
EXECUTIVE SUMMARY ... 5
1. INTRODUCTION – THE IMPORTANCE OF INNOVATION ... 7
1.1 THE ROLE OF SMES IN INNOVATION ... 7
1.2 LEGITIMACY & IMPRESSION MANAGEMENT FOR SMES ... 8
1.3 SCOPE & DOMAIN: THE ACCENTURE INNOVATION AWARDS ... 9
1.4 PRACTICAL AND SCIENTIFIC RELEVANCE ... 10
1.5 RESEARCH QUESTION ... 11
1.6 RESEARCH PAPER OUTLINE ... 12
2. THEORETICAL FRAMEWORK ... 12
2.1 LEGITIMACY & IMPRESSION MANAGEMENT ... 12
2.2 IMPORTANCE OF LEGITIMACY & IMPRESSION MANAGEMENT ... 12
2.3 ORGANIZATIONAL ELEMENTS AFFECTING SME IMPRESSION ON AN EVALUATOR ... 14
2.3.1 Human Capital ... 15 2.3.2 Research & Development ... 16 2.3.3 Entrepreneurial Learning ... 17 2.3.4 Collaborating ... 18 2.3.5 Additional Moderating Effects of Variables ... 19 2.4 CONCEPTUAL MODEL ... 20
2.5 SPECIFYING SUB-RESEARCH QUESTIONS ... 21
3. RESEARCH METHODOLOGY ... 22
3.1 RESEARCH APPROACH ... 22
3.2 METHODOLOGY QUANTITATIVE ANALYSIS ... 22
3.2.1 Research approach ... 22 3.2.2 Data Content & Sample Description ... 23 3.2.3 Data collection Method ... 24 3.2.4 Data Analysis ... 26 3.2.5 Quality Criteria of Research ... 26 4. RESULTS ... 27 4.1 DESCRIPTIVE STATISTICS ... 27
4.2 RESULTS OF THE LOGISTIC REGRESSION ... 30
4.3 RESULTS OF THE MULTIPLE LINEAR REGRESSIONS ... 32
4.3.1 Factors influencing Overall Impression ... 32 4.3.2 Factors influencing Impact ... 32 4.3.3 Factors influencing Growth Potential ... 33 4.3.4 Factors influencing Concept Innovativeness ... 33 4.3.5 Factors influencing Quality of Pitch ... 33 4.3.6 Factors influencing the Ability to Answer Questions ... 34 4.4 TESTING THE HYPOTHESES ... 34 5. DISCUSSION ... 38 6. CONCLUSION ... 41 6.1 THEORETICAL IMPLICATIONS ... 42 6.2 MANAGERIAL IMPLICATIONS ... 42
6.3 LIMITATIONS & FUTURE RESEARCH ... 43
7. REFERENCES ... 44
8. APPENDICES ... 50
8.1 APPENDIX I. QUESTIONNAIRE ACCENTURE INNOVATION AWARDS ... 50
8.2 APPENDIX 2. VIF TABLES OF THE REGRESSIONS ... 54
1. Introduction – The Importance of Innovation
Innovation has become one the most important challenges that organizations have to face in todays business environment (Konsti-Laakso, Pikala & Kraus 2012; Clancy and Moschini, 2013; Omri, Ayadi-Frikha & Chaiby, 2014). This challenge has mostly been triggered by fast changing customer demands and behavior, the emergence of technological innovations, and the ongoing globalization of an ever more connected world (Radas & Bozic, 2012). Many organizational practitioners and academics nowadays agree that the problem lies in the increasing complexity of the environment – it is difficult for organizations to predict which path will lead to success (Radas & Bozic, 2012). In the past, this path used to be efficiency driven; but more recent organizational literature has increasingly shifted towards innovation as the key to success or failure (Bilton & Cummings, 2010; cited in Hotho & Champion, 2011).
While it is evident for both academics and organizations that innovation is a necessary component of business success, it seemingly remains difficult to innovate successfully. Many studies have shown how large organizations deal with innovation, but the relative lack of research in the small-and-medium-sized firm sector shows that this area has yet to be explored and thus there remains a gap in innovation management literature (Kenny & Reedy, 2006; Hotho & Champion, 2011). The issue here is that innovation is a classic ‘container definition’ – most know what it entails, but a clear definition is difficult to provide. Two widely accepted definitions address the differences between incremental and radical innovation: the first follows quickly upon the previous innovation and offers a small ‘incremental’ improvement, while the latter takes more development resources and provides a ‘radical’ new product or service to the market. The broader definition of innovation can be summarized as ‘’a process that starts with an idea, proceeds with development of invention, and results in the introduction of a new product or service’’ (Omri et al. 2014, p.5).
This research paper takes a quantitative perspective to analyze which elements of the organization enhance legitimacy through impression management, which in turn leads to innovation success amongst SMEs.
1.1 The Role of SMEs in Innovation
interesting when conducting research in the innovation field.
Much of the organizational literature is in consensus about the importance of SME innovation. It has become clear that the SME sector is a major driving force of innovation (Radas & Bosic 2012). Research has also shown that SMEs are key players in the innovation field when it comes to idea generation and entrepreneurial spirit. The latter is of crucial importance in bringing innovations to the market (Konsi-Laakso et al., 2012). ‘’One of the primary means through which SMEs are expected to accomplish this task is by
developing and commercializing innovations’’ (Radas & Bosic, 2009, p:438). This
management has to be investigated. Much of the research into impression management has been conducted at three levels of analysis: 1) the individual; 2) within the organization; 3) between the organization and its stakeholders (Parhankangas & Ehrlich, 2013). The extant of this literature has been focusing on personal influence, and various intra-organizational phenomena, such as feedback-seeking behavior (Morrison & Bies, 1991), whistle-blowing (Gundlach et al., 2003), successful leadership (Gardner & Avolio, 1998; Gardner & Cleavenger, 1998), and professional image construction (Roberts, 2005). This leaves out the important part of situations where the organization is dependent on external stakeholders; the third category described by Parhankangas & Ehrlich (2013). It means there has been devoted less attention to situations where “the organization’s
representatives have acted as gatekeepers for organization-specific information and sought to affect key stakeholders’ behaviors” (Bolino et al., 2008; Mohamed et al., 1999; Stanton et
al., 2004).
Because the evaluation of the jury is prone to subjectivity, the affiliation with impression management and legitimacy seeking is chosen for this research. The organizational elements are very likely to contribute to how the firm or entrepreneur is perceived by an evaluator. As such, the entrepreneur may enhance his or her success by effective organizational management. It is thus of importance to gain knowledge about which factors enhance success with evaluators. 1.3 Scope & Domain: The Accenture Innovation Awards It is clear that SMEs face an important challenge regarding innovation. It is not only difficult to generate new ideas, product and services, it is also challenging to bring these innovations to the market. This research paper is focusing on these challenges by looking at the Accenture Innovation Awards (AIA). This is the largest innovation award contest for SMEs in the Netherlands. This event originated in 2007. The awards are both a platform and a contest where Dutch firms can summit their innovation and show this to the public. The AIA is primarily about uniting, honoring, and stimulating innovation in the Netherlands. It does so by putting the focus on service, product, and business model innovation. The firm that stands out the most with its innovation will win the award. There are eleven categories in the awards that produce a final winner. Most of the participants of the AIA are SMEs, and many of them are start-ups. The innovations that make it to the jury round are 10 per category. The jury selects 5 per category that will move to the finals. The winner generally is the highest ranking innovation in this final jury round. This jury is a panel that consists of industry experts. These experts have a wide variety of backgrounds and may have different biases towards certain innovations or selection criteria.
innovation in SMEs remain vague (Hotho & Champion, 2011; Omri et al. 2014). Previous research has focused on the organizational organization by investigating the differences between innovative- and non-innovative SMEs, but there is still no exhaustive explanation of why some firms succeed while others do not (e.g. Hodgkinson & Healey, 2011; Forsman & Rantanen, 2011 cited in Konsti Laakso et al., 2012). When looking at the Accenture Innovation Awards it becomes evident that some internal factors contribute to innovation success. However, it becomes more interesting when the innovations flow through to the jury selection process. The jury selects the innovations on multiple criteria, and in these rounds it may very well be that the factors of organizational configuration influence their assessment in different ways. Previous research neglects the fact of legitimacy seeking and impression management towards the jury (the expert panel or evaluator in more general terms). The judgment of the jury can be dissected into six criteria that eventually make up the decision to proceed as a finalist or not.
The purpose of this study is to analyze the factors that enable innovation success when SMEs are confronted with an evaluator. In other words, what do evaluators value in making their assessment and how entrepreneurs ensure they score well on these assessments? The organizational factors are analyzed to find out whether they have an effect on the judgment of an evaluator, which in this paper will be the jury of the Accenture Innovation Awards. This will be done by analyzing participants from these awards. The aim of the research is thus to research the effect of organizational characteristics on the jury evaluation in the AIA, which translates to the importance of impression management to obtain legitimacy by approval. The results can be translatable to other situations where an expert selection (evaluator) is in place. Here one can think about obtaining bank loans, finding venture capital, or convincing other parties in the market to collaborate. Important to note here is that this paper does not make a distinction between the performance of explorative and exploitative innovations in the AIA, nor does it explain differences between these firms in different industries or countries. Also, while the AIA is populated by many start-ups, the analysis does not take into account whether the firm is actually a start-up or a longer existing organization. 1.4 Practical and Scientific Relevance
the separate criteria. It may very well be that certain scores in these elements relate to skills or outcomes that are being valued by the jury, leading to success. Previous research has primarily focused on the elements and success rate, this paper dives one level deeper by taken the six criteria into account. It is since this year that the data from the jury tool of the AIA has become available, thus opening up new possibilities of research. The jury of the awards are all experts in the eleven given industries. This ensures an expert selection can be made from the contestants. This jury selection is key in awards like the AIA, but it plays a large role in many aspects of running a business. The two following examples can easily illustrate this. First, a firm that whishes to obtain a bank loan faces an expert selection as well; the banker has to decide whether the firm is eligible for funding. Secondly, finding partners to collaborate with is not an easy task. The firm has to position itself in such a way that external parties want to collaborate with it; a certain amount of trust or promise for success has to be transferred. These expert selections thus play a major role for success in both the awards and the market itself. This paper will shed light on this jury (evaluator) selection by analyzing how organizational elements influence the criteria. This will lead to a more complete picture of success, which is beneficial for every firm in the market that is competing for assets such as loans, partners, resources and market share. As such, the managerial interest in the results is profound, as it enables entrepreneurs and innovation managers to assess their firms a priori to the external evaluator assessment. The theoretical interest is large as well, as it shows how SMEs succeed in the market. This paper contributes quantitative results to the academic literature of innovation management. 1.5 Research Question It is clear that innovation is of crucial importance for any firm that is to succeed in the market. The relative lack of knowledge of innovation at SMEs is still evident, which makes it important to gain deeper insights of the process. It is not only useful to gain a better understanding about what factors drive innovation at SMEs, but also about how these firms manage gain legitimacy when faced with an expert selection – in this specific paper; the jury. The question to be answered by this research paper reads: “What elements of the organization positively contribute to the judgment of an evaluator?” To gain a better understanding of how SMEs perform in evaluations, two sub-research questions have been formed as follows:
The unit of analysis will be the organization, which means the research is at a micro level. More specifically, the focus will be on how elements of the firm contribute to the jury’s judgment in the AIA. The main research question has been translated into multiple hypotheses, which can be found in the literature section. 1.6 Research Paper Outline
This research paper is structured as follows: it first outlines the theoretical framework regarding innovation and impression management. Subsequently, it provides the research design. Thereafter, results of the data analysis are provided. Additionally, findings are discussed with respect to the importance of legitimacy seeking and impression management for SMEs, which is linked to existing literature. In the conclusion, implications, limitations and suggestions for future research are presented.
2. Theoretical Framework
Within this section, the concepts of innovation, legitimacy, and impression management are elaborated on by means of a literature review. First, legitimacy and impression management will be described as a basis to set a clear topic for this paper. Then the importance of obtaining legitimacy through impression management for innovation will be discussed in order to answer sub research question I. Secondly, the elements composing the organization that may influence the impression of the firm will be explored by focusing on previous research on these concepts. At the end of each subsection, the hypotheses are formulated. Finally, the research question will be further specified. 2.1 Legitimacy & Impression Management First it is important to specify the terminology that is at the base of this research paper. While impression management is prevalent in many different fields, research by Bolino & Turnley (1999), Bozeman & Kacmar (1997), Goffman (1959) offers a clear definition: “Impression management is a process through which people seek to influence the
image others have of them in order to attain a specific goal”. Other research in this field
is to present themselves in a favorable light to the outside world. Baron & Markman (2000) describe how impression management may prove to be very beneficial. First, the face-to-face interactions that the entrepreneurs have to face with many persons outside their firms are crucial for success. This effective interaction with customers and suppliers greatly affects their overall success. Secondly, effective impression management greatly affects the success of forming business alliances as well, which is crucial for innovation and new ventures (Baron & Markman, 2000). Cornelissen & Clarke (2010) make the connection between impression management and creating legitimacy for newly established firms. They describe their argument as “while social and cultural capital (as
based on reputation, social networks, awards and so on) are important in sustaining support, they emphasize the use of impression management techniques to align with the already existing configuration of the social context and what are perceived to be common, institutionalized understandings and norms of whether and how ventures are sensible, acceptable and legitimate” (adopted from: Cornelissen Clarke, 2010. Original from:
Aldrich and Fiol, 1994; Lounsbury and Glynn, 2001). Thus, making impression management an important factor in gaining legitimacy in the market or with an evaluator. Much of the literature has taken investors as a key example of how impression management is of importance in obtaining legitimacy. These investors have to be willing to engage with the newly created organization, which increases the need for a compelling account and story (Barry & Elmes, 1997; Cornelissen & Clarke, 2010; Lounsbury & Glynn, 2001; O’Connor, 2002). When looking at the investment world, early-stage investments often involve products or services that are unfinished and have not been tested for market demand (Murray & Marriott, 1998). The problem here lies in the fact that factual evidence is simply not there when it comes to checking the quality of the firm or the innovation. It becomes clear that it is difficult to assess these innovations, and in many cases the evaluator – in this research paper: the jury - has to deal with subjective claims made by the entrepreneurs (Maxwell, Jeffrey & Lévesque, 2011). This difficulty decreases when more reliable information about the market and/or reputation becomes available (Elsbach & Kramer, 2003).
It is most beneficial for the firm if the evaluator or jury gains a positive image, thus making it important to gain a better understanding of impression management for SMEs. The process of managing impressions is divided in two conflicting pressures on entrepreneurs. Entrepreneurs know that evaluators, in this case still the investors, will have certain criteria to assess when making a decision (MacMillan et al., 1985; Mason & Stark, 2004; Sudek, 2007). Research by MacMillan et al. (1985), Mason & Stark (2004), & Sudek (2007) provides many of the criteria that are also being used by jury of the Accenture Innovation Awards: market growth potential, product quality, innovativeness, and expertise of the entrepreneurial team. It is because of this knowledge of the criteria in place that entrepreneurs may feel tempted to promote their firm or innovation in an excessive manner. This is being done by “overstating his/her expectations of the future
performance of the firm, the distinctiveness of its business model, the speed of product development, or the competence of the entrepreneurial team” (MacMillan et al., 1985;
too modest or even too revealing of his/her weaknesses, the evaluator may conclude with a negative assessment. In many cases it is better to exceed expectations than completely fail to deliver. This is because failure will result in a worse position towards the evaluator, and may prevent the firm from succeeding (Cable & Shane, 1997; Heide & Miner, 1992; Maxwell & Levesque, 2001).
Most of the literature found on the topic shows that impression management becomes more visible when individuals and firms interact with a powerful audience, especially when they need to gain their support, approval or positive assessment (e.g., Carter, 2006; Gardner & Martinko, 1988; Judge & Bretz, 1994; Rindova & Fombrun, 1999; Schlenker, 1980). It becomes particularly important when that audience or evaluator has a difficult job due to uncertainty or ambiguity about the entrepreneurs’ claims (Bansal & Kistruck, 2006). As has been described earlier; impression management is crucial for young firms and start-ups. These firms remain for a large amount dependent on external parties to obtain the direly needed resources to succeed (MacMillan & Subba Narasimha, 1987; Wright, 1998). The previously conducted research thus stresses the importance of impression management for innovation success. The AIA provides a unique opportunity to look into such a previously described situation; as the jury of the event is a powerful audience. But what makes firms successful in managing their image towards a certain set of jury criteria? Many organizational elements that are measured by the AIA survey could be affecting this impression of the firm towards the evaluator. Successfully managing the impression of the organization is expected to be related to the elements described in the following subsection. Important to note here is that this paper does not make a distinction between the performance of explorative and exploitative innovations in the AIA, nor does it explain differences between start-ups in different industries or countries. 2.3 Organizational Elements affecting SME Impression on an Evaluator
their presumed effect on the scores on the jury criteria, which in their turn affect successfulness of the SME. The elements are combined into factors, which in turn have been operationalized in a following section (3.2.3 Data collection method). The jury criteria (dependent variables) that are influenced by the factors are summarized in the following table 1.
Table 1: Jury Criteria (dependent variables) of the AIA explained
Jury Criteria Definition References
Overall Impression The entrepreneur is knowledgeable and
conducts him or herself professionally and is confidence inspiring. Would you be willing to invest in him or her?
Accenture AIA
Impact The concept holds the potential to have
significant economic and societal impact (changes the way we do business, changes the way we live, creates significant additional value, generates positive societal and/or environmental outcomes).
Accenture AIA
Growth Potential The ability of the concept to grow in the relevant markets in the future and generate larger profits.
Accenture AIA
Concept Innovativeness The concept is innovative in the sense that it is novel (a new idea, product, process, or service). Is the concept new to the market / new to the world?
Accenture AIA
Quality of Pitch The pitch is clear, engaging, generates
enthusiasm, and is to the point.
Accenture AIA Ability to Answer Questions The entrepreneur is able to answer
experience in the industry, or enjoy a higher education level, are found to generate more innovative ideas for new products, services, or processes (Suanders & Gray, 2014). Additionally, past professional activities and training lead to a more diverse skillset and extended knowledge pool to discover opportunities (Unger et al., 2011). Additionally, entrepreneurs who have prior entrepreneurial experience are more likely to exploit new opportunities because of their increased organizational learning, which reduces opportunity costs (Carroll & Mosakowski, 1987). Additionally, historical success of the entrepreneur is a key success factor in obtaining legitimacy (Rao, Chandy, & Prabhu, 2008). Entrepreneurs who have founded multiple start-ups already have this historical legitimacy compared to new entrepreneurs. These findings lead to the presumption that a higher score on the factor of human capital will result in innovations that have a higher concept innovativeness, and have a higher impact rating. Also, a higher degree of entrepreneurial knowledge leads to a better planning strategy, and enables the firm to successfully commercialize the innovation (Baum, Locke, & Smith, 2011). This (in-)directly affects the growth potential of the product or service. Research by Baron & Mark (2000) results in the statement that the social competence of entrepreneurs is key for success. While some entrepreneurs are naturally socially strong, this competence is further developed during their professional career. Thus implicating that the factor
(Makri, Hitt, & Lane, 2010). It is clear that R&D is heavily influencing the firm’s innovative capabilities and eventual success. Therefore, it is expected that higher investments in R&D will ensure the firm is more capable to develop innovations that score higher on the jury criteria. It will lead to: i) innovations with more impact; ii) innovations that show more growth potential; iii) concepts that are more innovative. In short, it is expected that R&D factors have a positive effect on Overall Impression, Impact, Growth Potential, and Concept Innovativeness. H2a: Total amount of investment has a positive effect on Overall Impression, Impact, Growth Potential, Concept Innovativeness H2b: Total amount of man-days has a positive effect on Overall Impression, Impact, Growth Potential, Concept Innovativeness H2c: Number of FTE has a positive effect on Overall Impression, Impact, Growth Potential, Concept Innovativeness Research & Development is measured by the independent variables: Total Investment, Man-days, FTE. These will be elaborated on in section 3.2.3. 2.3.3 Entrepreneurial Learning Entrepreneurial learning is closely connecting with R&D, as it is crucial for firms to recognize new knowledge, assimilate it, and transform it into commercially viable products or services (Cohen & Levinthal, 1990). This process is still a popular research topic and of ongoing interest for SMEs because of the importance it holds for innovative capabilities (Hopp & Stephan, 2015). It is defined as “the commitment to learn, to be open-minded, and stimulate interorganizational knowledge sharing” (Adopted from Keskin, 2006). This factor stresses the importance of collaborative activities for the discovery and
execution of new ideas. ‘’Entrepreneurial learning orientation fosters a set of knowledge-questioning and knowledge-enhancing values that leverage the adaptive behaviors provided by market-orientation to a higher-order learning that leads to the development of breakthrough products, services, and technologies, and the exploration of new markets’’
(cited in Keskin, 2006, p.399). Much of the innovation literature agrees that learning from the external environment to gain new knowledge is highly beneficial for organizations and it has been recognized as a crucial skill for success (Wren, Sounder & Berkowitz, 2000). Zeng, Xie & Tam (2010) add that entrepreneurial learning is all about knowledge accumulation, and that innovation success is depended on the capabilities of the firm to transform this knowledge. Therefore, it leads to the assumption that when firms use more or more important external knowledge sources, they assimilate more and more diverse knowledge, which in turn results in innovations that will have more impact, show more growth potential, and are more innovative compared to competitors. In short, it is expected that Entrepreneurial Learning factors have a positive effect on Overall Impression, Impact, Growth Potential, and Concept Innovativeness.
Impact, Growth Potential, Concept Innovativeness
Entrepreneurial Learning is measured by the independent variable: Importance of Knowledge Sources. This variable will be elaborated on in section 3.2.3.
2.3.4 Collaborating
As has been mentioned in entrepreneurial learning; knowledge sharing is of crucial importance for innovation success. While that factor was about knowledge sources, the factor collaborating is about the sharing of resources between different parties. It is defined as the purposive horizontal and vertical inflows and outflows of knowledge and resources to others to enhance innovation (adopted from Chesbrough, Vanhaverbeke & West, 2006). The importance of collaboration for SMEs can best be explained by comparing them to larger organizations; these larger firms are better equipped internally when it comes to relevant resources, knowledge or other specialized assets (Teece, 1986). Therefore, innovation success in SMEs is more dependent on the ability to utilize external resources than trying to build expensive assets in house. Crema et al. (2015) adds that SMEs are increasingly trying to obtain resources or knowledge from external parties, such as customers, suppliers, research institutions, etc., to become more successful in innovation. Open innovation is no longer being considered a unique proposition, but is necessary to gain access to a wider pool of ideas or resources than would be available inside the own organization (Chesbrough, 2003). This allows firms to combine existing knowledge with new know-how from others. Other research by Laursen & Salter (2014) acknowledges that connected firms or actors working together in iterative trial and error processes are abler to successfully commercialize products and services. The concept of open innovation is an ongoing trend in modern literature, and interorganizational collaboration for innovation is an increasingly dominant approach for firms (Vanhavereke, van der Vrande, & Chesbrough, 2008). This tactic seems to be highly beneficial for SMEs, as it provides them with the opportunity to gain information that would have otherwise remained hidden for them (Almirall & Casadesus-Masanell, 2010). It is clear that collaborating with other parties in the market is crucial for organizations to succeed in innovative activities, and literature suggests that this holds true especially for SMEs. Firms that collaborate will be more likely to discover new- or even better ideas for services or products and learn more on how to execute/manage the innovation process. This leads to the assumption that firms scoring high on collaboration variables will demonstrate innovations that have more impact, a higher growth potential, and that are simply more innovative than firms that do not collaborate. In short, it is expected that Collaboration factors have a positive effect on Overall Impression, Impact, Growth Potential, and Concept Innovativeness. Being affiliated with an incubator is also predicted to have a positive impact on the Quality of the Pitch and the Ability to Answer Questions.
and Ability to Answer Questions H5c: More experience increases the positive effect of having more knowledge sources on Overall Impression, Impact, Growth Potential, Concept Innovativeness H5d: A higher innovation budget increases the positive effect of having more knowledge sources on Overall Impression, Impact, Growth Potential, Concept Innovativeness Table 2: Overview of the elements of the organization (independent variables) with their influence on the judgment of an evaluator Factors – elements of the organization Influencing Criteria Definition – of the elements composing the organization Example of studies on these elements 1.Human Capital Overall Impression, Impact, Growth Potential, Concept Innovativeness, Quality of Pitch, Ability to Answer Questions Skills and knowledge that individuals acquire through investments in schooling, on the-job training and other types of experience Unger et al. (2011), Suanders et al. (2014), Omri et al. (2014), Baum et al. (2011) 2.Research &
Development Overall Impression, Impact, Growth Potential, Concept Innovativeness The resource commitment towards innovation Cooper et al. (2007), Oxley et al. (2004), Cohen et al. (1990) 3.Entrepreneurial
Learning Overall Impression, Impact, Growth Potential, Concept Innovativeness The commitment to learn, to be open- minded and stimulate interorganizational knowledge sharing Keskin (2006), Farrel (2000), Wren et al. (2000) 4.Collaborating Overall Impression, Impact, Growth Potential, Concept Innovativeness The use of purposive inflows and outflows of resources to others/partners for innovative activities Chesbrough et al. (2006), Laursen et al. (2013), Teece (1986), Crema, et al. (2015) 5. Interaction
Effects Overall Impression, Impact, Growth Potential, Concept Innovativeness, Quality of Pitch, Ability to Answer Questions The combination of organizational elements Robinson & Sexton (1994), Stuart & Abetti (1990), Caloghirou et al. (2004) * These elements will be referred to as predefined factors and are derived from previous research on the innovation processes in section 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.3.5 2.4 Conceptual Model The previously described hypotheses are synthesized into a comprehensive model (Figure 1) that shows the relations between the factors and the evaluator criteria. As described, the proposed relations between the elements of the organizations have a positive influence on the criteria. Additionally, four moderating effects have been described. All the depicted relations are predicted to be positive.
Figure 1. Conceptual Model – Note that all depicted relations between factors and criteria are predicted to be positive, according to the literature and hypotheses 1-4. The moderating hypotheses 5a,b,c,d indicate an increase in effect due to more experience and a higher investment budget.
2.5 Specifying Sub-Research Questions
II.I How does human capital influence overall impression, impact, growth potential, concept innovativeness, quality of pitch, and the ability to answer questions? II.II How does research & development influence overall impression, impact, growth potential, and concept innovativeness? II.III How does entrepreneurial learning influence overall impression, impact, growth potential, and concept innovativeness? II.IV How does collaboration influence overall impression, impact, growth potential, and concept innovativeness?
II.V How does the combination of factors influence influence overall impression, impact, growth potential, concept innovativeness, quality of pitch, and the ability to answer questions?
3. Research Methodology
This section starts with explaining the overall research approach. Secondly, the analysis technique, the sample description, data content, data collection method and data analysis are explained.
3.1 Research Approach
This paper is investigating the relationship between the elements of the organization and the jury’s judgment in the awards. In order to research this relationship between the elements and an evaluator, this paper applies a theory testing method according to the empirical cycle by Van Aken, Berends et al. (2012). The research design is focusing on the latter part of the cycle; the theory testing part. This will be done by deducting hypotheses, testing them, and evaluating the results. This particular method is being applied because literature on innovation in SMEs is relatively recent beginning to develop. While many aspects of this topic have not been addressed yet in current academic literature (Creme, Verbano & Venturini, 2015), the existing literature is sufficient to establish hypotheses. By analyzing the elements of the AIA finalists of 2014, this research will test theory that can enrich the current literature with new insights and especially open new doors for future research.
In order to to gain a high quality research, a quantitative approach is chosen where a multiple regression analysis is performed to asses the relationship between the previously described factors and the jury criteria.
3.2 Methodology Quantitative Analysis
3.2.1 Research approach
ability to be analyzed in a statistical manner (Wyse, 2012). This paper analyzes the collected data by using the ordinary least squares technique; multiple linear regression. The conceptual model created for the analyses has multiple explanatory or independent variables and one depended variable, which makes this technique appropriate. The formula of the linear regression: Y = b0 + b1X1 + b2X2 + ... + bp Xp Where Y is the dependent variable, X shows all the predictor variables. The b indicates the Beta values or the regression coefficients (Field, 2009). 3.2.2 Data Content & Sample Description
* Percentage of the total number of participants ** Percentage of the total number of finalists *** List wise deletion of observations was used
3.2.3 Data collection Method In line with Bacharach’s (1989) statement, each variable used in this empirical part of the study must be defined in terms of measurement. Therefore, all variables will be described in the following section. Most of the elements of the organization are operationalized based upon the before mentioned Community Innovation Survey (CIS4), organized by Eurostat. Innovation success and the element of human capital are based upon innovation literature and are further operationalized by the Accenture Research department. Additionally, table 3 provides an overall summery including supplementary information about each variable included. Note that these variables have been selected from the available survey data. Due to the limited sample size, some variables have been simplified or transformed. Control Variables – Three control variables have been chosen for this research. Firm Size shows how many people work at the organization. Larger firms may employ a wide variety of creative people. Gender shows whether the entrepreneur(s) is male or female, or have a combination team. This one is chosen to check for gender differences. Product Innovation indicates whether it is a product or service innovation. This variable will check whether there are any differences between pitching a service or product innovation.
Innovation Success – in order to determine the successfulness of the innovation,
the status of the participants in the competition was used: accepted to participate in the finale or not. Two values were attributed to this variable, 0 for not being accepted to the finale and 1 for being accepted as a finalist. A total of 38 (60,3% of the qualitative research sample) registrations have been assigned value 1, and the rest of the 25 (39,7%) registrations was assigned with the value 0. All registrations approved in the finals are screened on equal criteria by the jury, formed by markets and industry experts in which the SMES are active, enforcing the quality of this variable. The jury took the following criteria into consideration when assessing the finalists: overall impression, impact, growth potential, innovativeness, quality of the entrepreneur’s pitch and the entrepreneur’s ability to answer questions properly. Note that the competition status was not a question in the questionnaire which was answered by the respondents as the rest of the variables. Rather it was the outcome of the AIA 2014 competition.
Collaboration – For collecting data about the collaboration, respondents were
asked to whether they were affiliated with an incubator (0=no, 1=yes). Next, respondents were asked if they collaborated with different parties. Due to data restrictions, this
variable has been transformed into a dummy variable: three or more partners (0=no, 1=yes).
R&D Expenditures and Activities – Additionally, in order to collect data about
the R&D expenditures and activities, the respondents were asked about their total investment in R&D by using a 5-point Likert Scale (0-10.000=1, 10.000-100.000=2, 100.000-1.000.000=3, 1.000.000-10.000.000=4, 10.000.000 or more=5). This variable is measured with a Likert scale to avoid outliers and loss of data events. Next, the respondents were asked about the investment in terms of man days by using a 5-point Likert Scale (0-100=1, 100-1000=2, 1000-10000=3, 10000 or more=4) and FTE (0-20=1, 20-40=2, 40-60=3, 60-80=4, 80-100=5).
Human Capital – The human capital of the respondents was investigated by
asking about their experience in the industry of their SME (No=1, less than 3 years=2, 3-10 years=3, 10 years or more=4) and the experience they have with founding start-ups (No=1, 1 startup=2, 2 startups=3, 3 startups=4, 4 startups=5, 5 startups or more=6). Both variables are measured by a Likert scale.
Entrepreneurial Learning – Lastly, in order to gather data about the
entrepreneurial learning, respondents were asked about their knowledge sources with different parties on a 4-points Liker Scale (very important=1, important=2, somewhat important=3, not used=4). This variable has been translated into a dummy variable due to the sample size restrictions as well. The mean of the importance rating of all knowledge sources has been calculated. This mean shows the relative importance of all used knowledge sources. A higher mean implicates that the firm has used more knowledge sources that are deemed of importance for success. Table 3: Operationalized variables overview Variable -Measured in the qualitative phase- Operationalization -defining the measurement of the element incl. question nr in Questionnaire- Data type -of operationalization per element- Level of measurement -measurement scale per variable- Reference- source of information -
Control Firm Size (nr.10) 4-point Likert scale
(0-5=1, 6-20=2, 21-50=3, 51+=4) Interval Accenture Research Department Gender (nr.11) Binary (0=female/combina tion, 1=male) Nominal Accenture Research Department Product Innovation (nr.12) Binary (0=service, 1=product) Nominal Accenture Research Department Innovation
success Competition status (nr. 19) Binary (0=non-finalist, 1=finalist) Nominal Accenture Research Department Collaboration Affiliated with an Incubator (nr.1) Binary (0=no, 1=yes) Nominal Eurostat (CIS4) More than three
R&D Expenditures and Activities Total investment R&D (nr. 2) 5-point Likert scale (0-10.000=1, 10.000.000 or more=5) Interval Eurostat (CIS4)
Investment in man-days (nr.3) 4-point Likert scale (0-100=1, 10000 or more=4) Interval Eurostat (CIS4) Investment in FTE (nr.4) 5-point Likert scale (0-20=1, 80-100=5). Interval Eurostat (CIS4) Human Capital Highest Educational
Level (nr.7) 6-point Likert scale (1=Elementary, 2= Secondary, 3=MBO, 4=HBO, 5=University, 6=PHD) Interval Suanders & Gray (2014); Accenture Research Department Experience in
industry (nr.8) Likert scale (No=1, 10 years or more=4) Interval Suanders & Gray (2014); Accenture Research Department Experience with founding start-ups (nr.9) Likert scale (No=1, 5 startups or more=6) Interval Suanders & Gray (2014); Accenture Research Department Entrepreneur
ial Learning Mean of used knowledge sources (nr.5) Likert scale (very important=1, not used=4). Interval Eurostat (CIS4) 3.2.4 Data Analysis
The four previously described factors have been operationalized into 9 independent variables. The literature has described their expected relation with the dependent variables (jury criteria and success). In order to evaluate whether these organizational elements truly have an effect on the given jury scores, multiple linear regression analyses have been performed in SPSS. This allows seeing the intensity of the effects of these elements on the different criteria. Before these multiple linear regressions are performed, a logistic regression will be executed to check which elements contribute to a firm’s success in the AIA. This allows to see a preliminary view of what influences success, before going more in depth with assessing the criteria. The regressions have been tested for the necessary assumptions in order to guarantee usable results. The results are described in section 4.1. 3.2.5 Quality Criteria of Research
experience in the industry (mean=3.33). The education level is generally high among the firms with a mean of 4.75, which translates to ‘HBO’ or higher. More than half of the participants have collaborated with more than three partners in the innovation process (mean=0.62) and less than half are connected with an incubator (mean=0.35).
Table 4: Descriptive Statistics and Correlation Matrix
Variable N Min Max Mean Std. Dev. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
4.2 Results of the Logistic Regression
Table 5 presents the results of the logistic regression checking for success factors among the organizational elements. Every model was statistically significant, and improved with the addition of the independent variables in model 2, and the interaction variables in model 3. Model 3 provided the best results (χ2= 39.511, p<.001) and correctly classified 85.5% of cases. The model explained 63.2% (Nagelkerke R2) of the variance in becoming successful (proceeding as finalist). Entrepreneurs pitching a product innovation were 3.7 times more likely to gain success. Having a higher education hampered the chance for success. While having multiple knowledge sources and more years of experience does not show a direct effect on success, the interaction effect of these two variables indicates that they do contribute in a positive way when combined. The multiple linear regressions should explain more in-depth on how the organizational elements affect the jury criteria that lead to success.
Table 5: Logistic Regression on Innovation Award Success
Kolom1 Success Success2 Success3
Model 1 Model 2 Model 3
4.3 Results of the Multiple Linear Regressions
Table 7 presents the results of the multiple linear regressions performed to check the effects of the variables on the six jury criteria. First the regressions were run with the control variables Firm Size, Gender, and Product Innovation. Afterwards the independent variables were added for a second run to check whether the model improved its predictive power. A third run was performed to check for the proposed interaction effects. This section of the paper just describes the results that have been found, the following discussion section (chapter 5) will elaborate on these findings.
4.3.1 Factors influencing Overall Impression
of 1.682. Model 3 shows two significant interaction effects. The R values do slightly increase, including the adjusted R2, which means the model does a better job than model 2 in explaining the variance in Impact.
4.3.3 Factors influencing Growth Potential
F value of model is 2.557 with p<.05. The VIF values lie between 1 and 2, and the Durbin-Watson test shows a result of 2.242. Model 3 has a lower adjusted R2 value (.123) and is thus considered less effective in explaining the variance as model 2.
4.3.6 Factors influencing the Ability to Answer Questions
This analyses performs differently than the previous five. Model 1, without the independent variables, actually does a better job explaining the variance in the ‘answering questions’ scores. It shows a significant F (F=2.959, p<.05) and the following R values: R=.340, R2=.115, and Adj. R2=.076. It indicates a negative significant relation between being a male entrepreneur and the ability to answer questions (b=-.262, p<.10) and a positive effect by having to defend a product innovation (b=.329, p<.05). Model 2 shows an F statistic of only 1.679 with a significance level of p>.10. R=.397, R2=.157, and Adj. R2=-.064. The first model seems to explain the variance in a better way than the second model, showing that not the independent variables lead to better scores, but the control variables. Model 3 also has a lower adjusted R2 value (.062) and is thus considered less effective in explaining the variance as model 1 and 2.
The first four discussed criteria show an increase in the adjusted R squared value in model 3, which does not only prove these models have theoretical significance, but also provide economic value for entrepreneurs. 4.4 Testing the Hypotheses
By analyzing the previously stated results, the hypotheses can be accepted, partly accepted, not assessable, or not accepted. For a summary of the results, please see Table 6. First of all, hypothesis 1a is not accepted. The level of education of the entrepreneur even has a negative effect on four criteria. Hypothesis 1b is partially accepted; experience does only slightly positively effect the score on Growth Potential. The amount of start ups started has no significant effect on any criteria, leading to the non assessment of hypothesis 1c.
Secondly, hypothesis 2a is measured by TotalInvestment. This variable shows a positive effect on impact, growth potential, and innovativeness, therefore partially accepting the hypothesis. The number of Man-days and FTE showed no significant effect on the criteria, and hypothesis 2b and 2c thus cannot be assessed. Thirdly, the importance and amount of knowledge sources (MeanKSources) used in the process even has a negative effect on the scores of Overall Impression and Growth Potential. No significant effect has been noticed on the other two variables, therefore not accepting hypothesis 3. Entrepreneurial Learning does not have a positive effect on the jury criteria following from this analysis. Additionally, being affiliated with an incubator or working with more than three partners does not necessarily lead to better jury scores. As both these variables had no significant effect on the criteria, hypothesis 4a and 4b cannot be assessed.
power on some of the other independent variables, as suggested by the literature. Hypothesis 5a, b and c are partially accepted, while 5d is not.
Table 6: Hypotheses Status
However, while not all hypotheses show the expected results, the addition of the interaction variables have presented some interesting findings. It seems that many variables in itself do not have a direct influence on the criteria scores. The combination of factors, however, is leading to better results for entrepreneurs competing for high evaluation scores. The following section of this paper will discuss these findings in more detail.
Hypotheses Status Summary
H1a: Education Level has a positive effect on Overall Impression, Impact, Growth Potential, Concept
Innovativeness, Quality of the Pitch and the Ability to Answer Questions Not Accepted
Education has a significant negative effect
H1b: Experience in the industry has a positive effect on Overall Impression, Impact, Growth Potential,
Concept Innovativeness, Quality of the Pitch and the Ability to Answer Questions Partially Accepted
Experience significantly positively affects Growth Potential
H1c: Number of start-ups started has a positive effect on Overall Impression, Impact, Growth Potential,
Concept Innovativeness, Quality of the Pitch and the Ability to Answer Questions Cannot be Assessed No significant effect on criteria
H2a: Total amount of investment has a positive effect on Overall Impression, Impact, Growth Potential,
Concept Innovativeness Partially Accepted
Significant positive effect on Impact and Concept Innovativeness
H2b: Total amount of man-days has a positive effect on Overall Impression, Impact, Growth Potential,
Concept Innovativeness Cannot be Assessed No significant effect on criteria
H2c: Number of FTE has a positive effect on Overall Impression, Impact, Growth Potential, Concept
Innovativeness Cannot be Assessed No significant effect on criteria
H3a: The importance of knowledge sources has a positive effect on Overall Impression, Impact, Growth Potential, Concept Innovativeness Not Accepted Significant negative effect on Overall Impression and Growth Potential H4a: Being affiliated with an incubator has a positive effect on Overall Impression, Impact, Growth Potential,
Concept Innovativeness Cannot be Assessed No significant effect on criteria
H4b: Having more than three partners has a positive effect on Overall Impression, Impact, Growth Potential,
Concept Innovativeness Cannot be Assessed
Significant positive effect on Growth Potential
H5a: More experience increases the positive effect of having a higher investment budget on Overall
Impression, Impact, Growth Potential, Concept Innovativeness Partially Accepted
Significant positive effect on Overall Impression
H5b: More experience increases the positive effect of having a higher level of education on Overall
Impression, Impact, Growth Potential, Concept Innovativeness, Quality of the Pitch, and Ability to Answer Questions
Partially Accepted
Significant positive effect on Overall Impression, Impact, and Concept Innovativeness
H5c:More experience increases the positive effect of having more knowledge sources on Overall Impression,
Impact, Growth Potential, Concept Innovativeness Partially Accepted
Significant positive effect on Impact
H5d:A higher innovation budget increases the positive effect of having more knowledge sources on Overall
Impression, Impact, Growth Potential, Concept Innovativeness Not Accepted
Table 7: Multiple Linear Regression on the six dependent variables (the table continues on the next page)
Kolom1 Overall Impression Overall Impression2 Overall Impression3 Impact Impact2 Impact3 Growth Potential Growth Potential2 Growth Potential3
Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Model 1 Model 2 Model 3
Kolom1 Concept Innovativeness Concept Innovativeness2 Concept Innovativeness3 Quality of Pitch Quality of Pitch2 Quality of Pitch3 Answering Questions Answering Questions2 Answering Questions3
Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Model 1 Model 2 Model 3
5. Discussion
The results of the multiple regression analyses will be interpreted and discussed here according to the literature. This paper adds knowledge to both the literature on legitimacy seeking and impression management and the literature on innovation success. Looking at the regression table (table 6) already shows that many variables did not have any significant effect on the jury criteria. Whilst this is unexpected, it may be explained by the limited sample size or the subjective judgment of the jury. However, the found interaction effects provide an additional and more interesting explanation; the combination of elements does increase the scores on the criteria. Important to note is that the jury’s personal characteristics lie outside this research’s scope.
experience in the industry are found to generate more innovative ideas for new products, services, or processes (Suanders & Gray, 2014). Hypothesis 1b in itself is thus not accepted, but the combination of experience with the other variables has shown great effects on the evaluation scores, creating new insights for entrepreneurs in how to succeed. It remains important to state that the amount of start-ups started does not seem to influence the scores on the jury criteria at all in this research, leaving hypothesis 1c unassessed. This is opposite of what Unger et al. (2011) describes: the ability to learn from new venture creation enhances success. It could be that having started a start-up before leads to better results, but that the second, third or even sixth one do not add more relevant experience.
evaluator. Research by Rosenbusch, Brinckmann & Bausch (2011) has also challenged network and social capital literature by providing empirical evidence that external collaborations have no significant effect on performance, or are even detrimental to performance for small firms. However, these statements are not exhaustive, and again it proves to be important to assess the nature of the relations found in this analysis. The two-way interaction of these knowledge sources with an increased experience leads to strong, significant, positive effects on the overall impression, impact, and growth potential of the concept. These findings indicate that having or using multiple knowledge sources does not necessarily increase the success rate on an evaluator’s assessment criteria. Only when the entrepreneur has an increased level of experience he or she is able to leverage these knowledge sources to a greater extent. Absorbing knowledge proves to be one of the key success factors for entrepreneurs that want to leave a great impression on an evaluator assessing for these criteria.
Hypothesis 4a, being connected to an incubator, shows no significant results, and cannot be assessed accordingly. This is a surprising result, as the literature shows that incubator managers play a significant role in helping incubates achieve success. They do this by creating partnerships and fostering the entrepreneurial spirit (Shepard, J.M., 2014). As such, firms affiliated with an incubator are presumed to have a predisposition towards higher scores because of their increased collaborative- and learning efforts. This finding is interesting in itself; it questions, although to a small extent, the validity of business incubators. Finally, hypothesis 4b implies that working together with multiple other organizations would improve innovation performance and the scores on the jury criteria. The analysis has shown no significant effects on the tested criteria. The extent to which this factor has been measured and used for this analysis may not have been satisfactory. Most literature indicates that collaboration allows for the discovery of technical and market information, that would otherwise be difficult to achieve (Malairaja & Zawdie, 2008; Almirall et al. 2010). However, an explanation for the lack of evidence on the other three criteria may be provided by Groen, Kraaijenbrink, Lowin & Van Rossum (2012). Their research shows that it is difficult to capture value from new knowledge, and that many firms who are connected, are connected through weak ties. These ties facilitate the transfer of simple and codified knowledge, but not so much the exchange of more complex or tacit knowledge. This research’s scope has not allowed for taking into account the exact details of the composition of collaboration partners, but the results may be explained if most firms utilized many but weak relations with their partner firms. Future research could delve deeper into the collaborative effort in increasing evaluator assessment scores. Again, it may also be explained by the necessary data transformation that has been performed due to sample size restrictions. More importantly, the research by Rosenbusch et al. (1987) provides empirical evidence that external collaborations have no significant effect on performance, or are even detrimental to performance for small firms. Hypothesis 4b has thus been unassessed due to the lack of significant variables.
To conclude, the findings of these analyses, including the interaction effects, are not necessarily exhaustive, and many other (interaction-) variables could be taken into account with an expanded dataset. However, they do provide clear indicators of how firms succeed in the evaluation process.
6. Conclusion
Most of the empirical literature has been focusing on the direct connection between organizational elements and success, but this research has added another level of analysis. This has been done by looking into the evaluators judgment in the Accenture Innovation Awards. Previous research acknowledges that innovation stems from the capabilities and creativity of the firm and its employees (Hotho & Champion, 2011; Omri et al. 2014) and that effective impression management greatly affects the success of forming business alliances as well, which is crucial for innovation and new ventures (Baron & Markman, 2000). The jury of the AIA represents a powerful audience, or an evaluator, that assesses the firms. It is highly important for firms to get high scores on the jury criteria. In this case to be successful in the awards, but it can be applied in a more general way. As has been described earlier; impression management is crucial for young firms and start-ups. These firms remain for a large amount dependent on external parties to obtain the direly needed resources to succeed (MacMillan & Subba Narasimha, 1987; Wright, 1998). The analyses of the data and afterwards the results of the regressions ensure that this paper explains something about the effects of the organizational elements that influence the jury criteria. The research question of this paper reads: “What elements of
the organization positively contribute to the judgment of an evaluator?”. As a result, it
