The Grit Effect on Individual Entrepreneurial
Orientation in Sticky Organizations
The effect of knowledge stickiness on individual entrepreneurial orientation,
mediated by grit, and affected by social identity
Executive Program in Management Studies – Strategy Track University of Amsterdam – Amsterdam Business School
Student: Mark Haasdijk
Student number: 11132256
Date of Submission: 28 March, 2018
1st Supervisor: Christopher Williams, PhD
Statement of Originality
This document is written by Mark Haasdyk who declares to take full responsibility for
the contents of this document. I declare that the text and the work presented in this
document is original and that no sources other than those mentioned in the text and its
references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of
completion of the work, not for the contents.
Date:
Table of Content
ABSTRACT ... 4 INTRODUCTION ... 5 LITERATURE REVIEW ... 9 ENTREPRENEURIAL ORIENTATION ... 9 KNOWLEDGE STICKINESS ... 14 GRIT ... 20 SOCIAL IDENTITY ... 21 THEORETICAL FRAMEWORK ... 23 METHOD ... 29 RESEARCH PROCESS ... 29 THE VARIABLES ... 34ANALYSIS OF DATA – DATA QUALITY AND ROBUSTNESS ... 41
RESULTS ... 43
CORRELATION ... 43
CONTROL VARIABLE EFFECTS ... 45
HYPOTHESIS 1:KNOWLEDGE STICKINESS HAS A NEGATIVE EFFECT ON IEO ... 45
HYPOTHESIS 2:"EFFECTS OF GRIT." ... 45
HYPOTHESIS 3&4:MODERATION OF SOCIAL IDENTITY? ... 49
DISCUSSION ... 53 MANAGERIAL IMPLICATIONS ... 56 LIMITATIONS ... 59 CONCLUSION ... 60 REFERENCES ... 61 APPENDICES ... 70
APPENDIX 1:GROUPS AND RESPONSE IN QUOTA SAMPLE ... 70
APPENDIX 2:IEO RELATED TO RANK (AS PART OF EXPERIENCE) ... 70
APPENDIX 3:TESTING OF CONTROL VARIABLES IN DIFFERENT MODELS, THROUGH REGRESSION ANALYSIS ... 71
Abstract
Cross-sectional inductive mixed-method research on individual entrepreneurial orientation and its antecedents and relevant factors, giving insights into the unique military organization of the Royal Netherlands Marine Corps and large organizations in general. The initial exploratory qualitative part of semi-structured interviews and literature research found knowledge stickiness to be an essential organizational factor. Furthermore, grit and social identity were found as substantial personal and behavioral factors of influence. These factors were put into a conceptual model, which was, in turn, tested quantitatively through received questionnaire data. The quantitative results show that there is no direct relation between knowledge stickiness and individual entrepreneurial orientation. Grit fully mediates the relation between knowledge stickiness and IEO, which means grit is required to act entrepreneurially in sticky environments. Knowledge stickiness has a negative effect on grit, followed by grit having a positive effect on IEO. The relation of grit and IEO can be positively affected (moderated) by high levels of social identity on the organizational level, social identity at lower levels in the organization do not affect this relation. The research finds the importance grit in the entrepreneurial context and ascertains the negative influence of knowledge stickiness in large organizations.
Keywords: Individual Entrepreneurial Orientation, Grit, Knowledge Stickiness, Transfer of Knowledge, Social Identity Theory, Military.
Introduction
"If there was a single question that obsessed 20th-century managers, from Frederick Taylor to Jack Welch, it was this: How do we get more out of our people? (Hamel, 2009)
Individuals working in large organizations might have brilliant ideas, see various opportunities and try to contribute to improving the organization. However, such large organizations seldom truly listen to those employees, rarely identify internal opportunities or cannot cope with the vast potential of knowledge and entrepreneurial intentions present in their workforce. How can we ensure that employees can contribute to their organization in an entrepreneurial way? To make sure that grass-roots initiatives reach the top and will be supported? However, it is fair to say that not every individual will act in such way. It is believed that certain personality traits or mindset is required to push initiatives through in large organizations. Attention is needed on the organizational ability to identify employees with the right mindset, to empower them to participate in or contribute to improving the organization. The combination of present but underused knowledge, entrepreneurial intentions, and a positive mindset should provide the right "ingredients" for organizations to start improving.
Any organization will try to find ways to improve, regardless of context and type, simply because it is a way of survival (cf. Burgelman, 1991). That does not mean that all organizations know how to. In the contemporary business environment, many large organizations are struggling to keep up and stay aligned with their environment. Innovation, disruptive technologies, lean and agile are buzz words but are not always clearly understood, properly executed or well-managed. To be able to do "something" about that status quo organizations often launch innovation campaigns and try to motivate personnel to do “something.” These intentions often hit internal barriers since most large organizations are structured entities with many internal processes and layers to keep control over efficiency, but mostly forgetting effectiveness. Although not every large organization is identical, the control type of
management is typical for large organizations and causes restrictions on the adaptiveness of such organizations (Miles et al., 1978). It implies that those organizations do not really grasp the ideas belonging to innovation, renewal, and entrepreneurship and tend to get stuck in their effort to start improving. Eric Ries, author, and founder of the "Lean Startup" way mentions that true innovation requires organizational change and most organizations are not truly interested in innovation, but create "innovation shows," which are excuses for true innovation since business will stay as usual (de Valk, 2018). Improving organizational performance by engaging and utilizing all knowledge and entrepreneurial potential that resides in the individuals of an organization could make a difference. How organizations can unleash and utilize this potential by making the best use of their personnel as the "most valuable" resource (cf. Grant, 1996; Teece et al., 1997) is one of the objectives of this exploratory research. This research provides a unique insight into a special military organization, namely the elite forces of the Royal Netherlands Marine Corps. In the Royal Netherlands Marine Corps (RNLMC) responsibility and accountability are decentralized and delegated to (very) low levels when conducting operations. Small units and teams are adaptive, remain flexible under various conditions and focus on mission achievement. These units and their unit leaders must be flexible, able to act proactively and take calculated risks to gain a military advantage in a hostile environment. This what Marines do, and what Marines are trained for. Regrettably, the flexibility, adaptiveness and proactive spirit are "lost" in the larger organization of the RNLMC and Ministry of Defence (MoD). These insights are shared by General Stanley McChrystal, a former US Special Forces Task Force commander in his book Team of Teams (2015). These observations have initiated the idea of doing in-depth research on the characteristics of the RNLMC, Marines and their entrepreneurial spirit. The characteristics of Marines are thought to be very similar to those of (individual) entrepreneurial orientation, consisting of innovativeness, proactiveness, and risk-taking (Bolton & Lane, 2012; Covin & Slevin, 1989), and could catch the essence of how the RNLMC organization should focus their efforts for improvement. The RNLMC should use what is considered to be engrained in Marines, and
utilize it more effectively for the benefits of the RNLMC. Therefore the research question is: what are relevant factors related to individual entrepreneurial orientation and how can we use these to ultimately improve organizational performance? The concept of individual entrepreneurial orientation (Bolton & Lane, 2012) could catch the essence of the entrepreneurial potential in large organizations. It is believed to contribute to organizational entrepreneurial orientation (Wiklund & Sheperd, 2011; Wales et al., 2011) which leads to improved organizational performance (Rauch et al., 2009).
An inductive approach is used to find which factors are relevant to individual entrepreneurial orientation in the RNLMC, following a grounded approach (Saunders et al., 2012; Strauss & Corbin, 1990). The research design is built on a mixed methodology to provide a more in-depth understanding (cf. Creswell et al., 2006). Data collection started with semi-structured interviews to explore on individual entrepreneurial orientation and mindset. The goal was to analyze what essential antecedents or factors are to establish a conceptual model for further quantitative research (Teddlie & Tashakkori, 2003). The most common organizational factor was found to be knowledge stickiness (Szulanski, 1996), which identifies and specifies the origins of knowledge barriers in the process of transferring knowledge (Argote & Ingram, 2000). Perseverance and a passion for long-term goals, known as grit, was identified as a personality trait that could provide an individual psychological factor of influence (Duckworth et al., 2007). In organizational behavior, social aspects affect processes. Social identity theory (Tajfel, 1978; Tajfel & Turner, 1979), which represents the individual's emotional connection (and related perceived value) to groups, provides the social context of organizational behavior. These variables are put into a conceptual model to test their relations statistically on individual entrepreneurial orientation.
In regard to (individual) entrepreneurial orientation, little research has been conducted on its relation to behavioral and psychological aspects, including grit and social identity (as suggested by Lumpkin & Dess, 1996; Lumpkin & Erdogan, 2004; Wiklund & Sheperd, 2003; Wales et al., 2013) and its relation with knowledge transfers (Argote & Fahrenkopf, 2016). Furthermore, internal research on
entrepreneurial orientation remains unexplored (Wales et al., 2013) and the public and nonprofit sectors are mostly not the scopes of research on EO (Morris et al., 2011).
Although the nature of the research is inductive and exploratory, the structure of this thesis is designed in a classical way since a large part of the research contains testing the conceptual model, including hypotheses testing, and discussing the outcome. The research is structured as follows. First, all relevant literature, containing the main variables as mentioned above, are explained, followed by the theoretical framework with hypotheses that were created after the initial qualitative part. The method section explains the way the research was designed and executed, including the qualitative method and results which have led to the conceptual model and the hypotheses. The results section only shows the quantitative outcome of the research. The discussion mentions the outcomes of the research and its relevance for literature. Managerial implications indicate relevance to some managerial areas. Limitations of the research are indicated, finally followed by the conclusion.
“being effective in today’s world is less a question of optimizing for a known (and relatively stable) set of variables than responsiveness to a constantly shifting environment. Adaptability,”
General Stanley McChrystal
Literature review
Entrepreneurial Orientation
Entrepreneurship is an essential feature of high-performing firms (Covin & Slevin, 1991). The intentions to create Corporate Entrepreneurship (CE) are self-evident and are found in companies where the strategic leaders in combination with their business culture generate a strong impetus to innovate, take risks, and aggressively pursue new venture opportunities (Dess & Lumpkin, 2005). The goals of Corporate Entrepreneurship are the creation and pursuit of new venture opportunities and strategic renewal (Guth & Ginsberg, 1990).
In the entrepreneurial context, corporate entrepreneurship explains the "what," and entrepreneurial orientation (EO) explains the “how,” meaning the entrepreneurial process; methods; practices; and decision-making styles to act entrepreneurially (Lumpkin & Dess, 1996). EO is thus a part of CE strategy, where EO is manifest within organizations as an organizational state or a quality through entrepreneurial processes and behavior (Ireland et al., 2009). EO should be viewed as an essential part of a unique, identifiable and entrepreneurial strategy, as manifested by organizations (Wales, 2016). In EO theory, entrepreneurship is regarded as more than simply a singular act or activity, such as the launching of new innovations (Covin & Lumpkin, 2011). It is an overall strategic posture! Interest in EO has been consistently growing since it is viewed as a central concept in entrepreneurship, where a cumulative body of knowledge is developing (Rauch et al., 2009). The reasons for this interest relate to the proposed relationship between EO and firm performance. Several studies have found that organizations, which demonstrate more (strategic) entrepreneurial orientation perform better (Wang, 2008). EO is an essential construct in the current context of increased competition, faster technological change and high need for economic growth (cf. Ferreira et al., 2016).
EO originated from the ideas of Miller (1983) who spoke about the determinants of entrepreneurship, Covin and Slevin (1989) called it the strategic posture of an organization which consists of the three dimensions (1) innovation, (2) proactiveness and (3) risk-taking. Lumpkin and Dess (1996) enlarged the EO construct to five dimensions by including autonomy and competitive aggressiveness. This dimensionality of EO has been the subject of considerable debate in the EO literature. Recent theorizing (Wales, 2016) suggests that the two predominant conceptualizations can co-exist in the literature with each approach providing unique insights. Covin and Wales (2012) assert that: "overall, one might say that the Lumpkin and Dess's (1996) conceptualization of EO is more domain focused – that is, it specifies where to look for EO, and the Miller (1983) conceptualization of EO is more phenomenon-focused – that is, it specifies what EO looks like." This research focuses more on the phenomenon of EO. Therefore, the conceptualization of Miller will be followed.
The dimensions of EO (Miller, 1983; Covin & Slevin, 1989) are explained briefly. First, Innovativeness refers to a firm's efforts to find new opportunities and novel solutions. Innovativeness reflects a firm's tendency to engage in and support new ideas, novelty, experimentation, and creative processes that may result in new products, services, or technological processes (Dess & Lumpkin, 2005). Innovation may come in many different forms and could have different "parents" (Baldwin & von Hippel, 2011) and can be quite challenging to manage (Dess & Lumpkin, 2005). Second, Risk-taking refers to a firm's willingness to seize a venture opportunity even though it does not know whether the venture will be successful. It is about making decisions and taking action without precise knowledge of probable outcomes. Some undertakings may also involve making substantial resource commitments in the process of venturing forward (Dess & Lumpkin, 2005). In his book Innovation and Entrepreneurship, Drucker (1985) argues that successful entrepreneurs are typically not risk takers, which is supported by Dess and Lumpkin (2005) stating that only carefully managed risk is likely to lead to competitive advantages. Third, Proactiveness is the tendency of an organization to anticipate future wants and needs and to pursue change ahead of the competition (Lumpkin & Dess, 1996), in
other words, it refers to a firm's efforts to seize new opportunities (Dess & Lumpkin, 2005). Individuals who practice proactiveness have their eye on the future in a search for new possibilities for growth and development (Dess & Lumpkin, 2005).
EO in public (governmental) organizations
In a for-profit context, organizations have an incentive to act entrepreneurially (Morris et al., 2011), since it is based on supply and demand combined with a price mechanism (cf. Williamson (1979). Succesfully exploiting opportunities will disrupt existing markets and create a competitive advantage resulting into revenue. Nonprofit organizations, however, have different incentives, their mission is to provide some form of exchange that results in an increased social value (Mort et al., 2003). The public and nonprofit sectors rely on the same construct of EO (Morris et al., 2011; Mort et al., 2003), with differences in the utilization of these dimensions, given there is no economic interest. Morris et al. (2011) specified the dimensionality and the understanding of nonprofit EO, which incorporates: (1) social, mission-centric innovation, commercial innovation, and the unique case in which innovation includes both social and commercial aspects; (2) social, financial, and stakeholder-relevant risk; and (3) proactiveness relative to similar organizations in terms of social and commercial innovation as well as relative to stakeholder expectations. In perspective, Zahra (1993) already suggested that non-financial indicators of firm performance may be more telling and are potentially relevant at earlier stages of the entrepreneurial process (i.e., EO projects). Ultimately, a nonprofit organization needs to balance these different opportunities to meet the nonprofit’s various social, financial, and stakeholder objectives (Morris et al., 2011). Nonprofit EO considers not only the development of new products and services but also the means through which the organization can pursue social mission-related and commercial opportunities. Opportunities are valued by the perception of the organization itself, by the perception of stakeholders, and likely community support. The support for opportunities will partly determine which resources are acceptable to use (cf. Lumpkin at al., 2013). The importance of
nonprofit EO content and utilization should not be underestimated and provides relevant and essential factors for EO in general. It can play a critical role in all entrepreneurial activities, regardless of the financial context (for profit or nonprofit).
Individual EO
The roots of EO lie in the psychological approach to individuals that conduct entrepreneurial activities, i.e., the "entrepreneurs." Research on EO has predominantly focused on entrepreneurial behavior in small companies. It is relatively straightforward to examine the role of the entrepreneurs, who are mostly the owner and their focus on EO (such as Kraus et al., 2005; Wiklund & Shepherd, 2003; Rauch et al., 2009). In contrast, the scope of this research considers the roles of individuals in large organizations.1 In large organizations, with more complex structures and a broader portfolio,
individuals should act more entrepreneurially, since top management cannot oversee and monitor everything inside and outside of the organization. In this respect, it is not only about the individuals, but also about organizations being able to cope with and utilize such individuals by creating the ways and means to empower this entrepreneurial potential.
Individual Entrepreneurial Orientation (IEO) addresses the question: "What are the personal characteristics or attitudes a person possesses that might increase the propensity to engage in and be successful at entrepreneurial activities?" (Bolton & Lane, 2012; Lumpkin & Erdogan 2004). IEO is closely related to the construct of entrepreneurial intentions since innovativeness, risk-taking, and proactiveness correlate with entrepreneurial intentions (Bolton & Lane, 2012). Diverting from the organization level concept and reframing it to an individual level concept means that it is about
personality traits, attitudes, and their environment. Furthermore, entrepreneurial emotion plays a role at the individual level in the entrepreneurial process (Baron, 2008; Cardon et al., 2012) and will affect antecedents, choices, and consequences of the entrepreneurial process.
Covin and Slevin (1991) had already made clear that individuals in an organization could have a significant impact on the EO of an organization. As such, the manifestation of a firm's EO may be affected by its organizational members, their corporate location, job responsibilities, and business unit goals among other considerations. The benefits of entrepreneurial activity concerning promoting innovation, meeting consumer needs, job creation and stimulating economic growth have long been professed, but have arguably never been as relevant as in the current economic and competitive context as today (Ferreira, 2016). Understanding entrepreneurship and an individuals' predisposition for entrepreneurial activity is therefore of great importance for organizations in any business environment. Individuals are the ones who take the initiative, gather support and start "acting in anticipation of future demand" (Lumpkin and Dess, 2001) to contribute to the EO of an organization. Many entrepreneurial initiatives which come to shape EO may develop as a result of strategies emerging from lower levels below the top management team (Wales et al., 2011). Concurrently, EO may shape the behavior of organizational members (Wales, 2016), considering that EO will influence an individual's intention to experiment with new technologies, new products, new markets, or new processes. Arguably, the reciprocal relation of EO and IEO exists, should therefore always be considered and can be effectuated in both directions. In light of the reciprocal EO and IEO relation and considering EO in nonprofit organizations, the context of nonprofit EO is focused on creating a form of social value at the organizational level. This context might influence the individual level, but the scope of IEO will not differ in a non-profit setting from a for-profit setting since it is about the personal drive to engage in and be successful in entrepreneurial activities (Bolton & Lane, 2012) regardless of the organizational context since it is in the fundamental fibre of the person who chooses this path (Seshadri & Tripathy,
2006). Ferreira (2016) found that Individual Entrepreneurial Orientation (IEO) can impact positively on product development, job creation, and macro-level growth.
Knowledge Stickiness
Knowledge has been attributed to a form of power since the beginning of humanity. Philosophers such as Sir Francis Bacon (1597) and Thomas Hobbes (1651) elaborated on the notion that knowledge is power. Kogut and Zander (1992) explain that knowledge is the reason for why firms exist. They state that new ways of cooperating cannot be easily acquired, growth occurs by building on the social relationships that currently exist in a firm and the cumulative knowledge of the firm provides options to expand in new but uncertain markets in the future. They believe that the central competitive dimension of what firms know how to do is to create and transfer knowledge efficiently within an organizational context. The processing of knowledge, such as possession, creation or transferal in organizations is essential and should be seen as part of organizational processes or routines (Cyert & March, 1963; March & Simon, 1958; Nelson & Winter, 1982; Szulanski, 2000). Transferring knowledge within an organization is not easy (Szulanski, 1996; Argote & Ingram, 2000).
From the organizational perspective we can consider knowledge as an essential resource of the firm, and if that knowledge resides in specialized form among individuals, and organizational members, then the essence of organizational capability is the integration of individuals' specialized knowledge (Grant, 1996). However, it is not only about the transfer or integration of knowledge within firms, any organization that dynamically deals with a changing environment ought not only to process information efficiently but should also create information and knowledge (Nonaka, 1994).
Knowledge transfer is seen as a process in which an organization recreates and maintains a complex, causally ambiguous set of routines in a new setting (Szulanski, 2000). Stickiness connotes difficulty experienced in that process (Szulanski, 1996; von Hippel, 1994). Therefore, the mere possession of
potentially valuable knowledge somewhere within an organization does not necessarily mean that other parts of the organization benefit from that knowledge. Organizations do not necessarily know all that they know (Szulanski, 2000). The main reason for this unawareness is that the transfer of knowledge tends to be "sticky" or difficult to achieve rather than a fluid process (Szulanski, 1996; von Hippel, 1994). For some reason, the notion still exists that knowledge transfer is costless and instantaneous, although much research has shown otherwise (von Hippel, 1994; Szulanski, 1996; Argote et al., 2000). Szulanski (2000) even found that even when it is acknowledged as difficult, it is regarded an anomaly rather than a characteristic feature of the transfer.
In his seminal work, Szulanski (1996) found that there are three significant origins of stickiness: (1) lack of absorptive capacity of the recipient, (2) causal ambiguity, and an (3) arduous relationship between the source and the recipient. Interestingly these results contrast conventional wisdom or commonly "acknowledged" practice that attributes stickiness almost exclusively to motivational factors (Szulanski, 1996). Although Szulanski wrote the article 20 years ago, the typical perception at practitioners still exists that motivational factors are the true factors of influence, such as: jealousy, lack of incentives, lack of confidence, lack of buy-in, an inclination to re-invent the wheel, recipients' refusal to do as they are told, resistance to change, lack of commitment and not-invented-here syndrome. However, the statistical findings suggest that the origins of stickiness as knowledge barriers dominate motivation-related barriers. In other words, it is not up to individuals to reduce stickiness, but should be an organizational effort in improving its routines. When knowledge cannot be transferred efficiently, a gap will occur between what is known within an organization and what is put to use. This gap represents the potential of knowledge, which could be utilized once organizational routines can process the knowledge potential.
The context of knowledge transfer and its stickiness varies and can be viewed from many perspectives. It can be seen as a form of organizational learning (Levitt & March, 1988) or as an interaction between social units based on psychological and organizational research (Argote & Ingram, 2000). The social
units could be further defined as individuals, teams, organizations or populations (Bresman, 2010; Eple et al. 1991). One can look at the transfer of knowledge between organizations (such as Van Wijk et al., 2008; Ingram, 2002) or between units within organizations (Argote & Ingram, 2000). Argote and Ingram (2000) argued that knowledge transfer is an essential mechanism for increasing the performance of recipient units, and Argote et al. (2000) state that understanding how to facilitate knowledge transfer and minimize productivity loss can significantly improve organizational performance. Which is supported by later research (see Argote & Fahrenkopf, 2016). The focus in this research is on transferring knowledge within a single organization, and between individuals working in the same organization, who are working at different departments, units and in multiple locations.
Origins of Stickiness
The model of communication by Shannon and Weaver (1949) provided the basis for predicting the origins of knowledge stickiness. The model specifies the elements of a transfer: message, source, channel, recipient, and context. Szulanski (1996) framed those elements in four categories; (1) characteristics of the knowledge transferred (i.e., the message and channel), (2) the source, (3) the recipient and (4) the context in which the transfer takes place. The categories will be explained briefly in the following paragraphs.
Characteristics of the knowledge transferred
Since there is no clear-cut definition of "knowledge," it can be argued that all knowledge is somewhat causally ambiguous. Causal ambiguity can be viewed from a social perspective and a technical perspective. In knowledge management and with knowledge transfers parts of this knowledge will not be explicit nor tangible. The individual perception of transferable knowledge and its characteristics partly explains the ambiguity. Knowledge can be divided into tacit and explicit knowledge. Michael
Polyani (1958 and 1966) mentions the concept of tacit knowledge and his relatively simple explanation is "we can know more than we can tell." This philosophical explanation of tacit knowledge highlights that there are elements of knowledge which are not easy to transfer, replicate or imitate. Tacitness is something personal, an ability or skill to do something or to resolve a problem that is based, in part, in one's own experiences and learning (Grant, 2007). From a technical perspective, the transfer of knowledge consists of an exact or partial replication and connection of a specific set of social and technical resources. Knowledge transferal can thus be seen as the replication of a specific capability, process or routines (Winter, 1995). Lippman and Rumelt (1982) argued that difficulty in the replication of a capability is most likely to emanate from ambiguity about what the factors of production are and how they interact during production. When the precise reasons for success or failure in replicating a capability in a new setting cannot be determined even ex-post, causal ambiguity is present, and it is impossible to produce an unambiguous list of the factors of production, much less measure their marginal contribution (Rumelt, 1984). When regarding knowledge stickiness and the characteristics of the knowledge transferred, one should be aware that causal ambiguity will have a significant effect (Szulanksi, 1996).
Characteristics of the source of knowledge
Factors of the source were not significant in the findings of Szulanski (1996). Since this research is on the individual level, it is regarded as relevant. Furthermore, it is one category of the four possible categories of the origins of knowledge stickiness and should be included for completeness.
Although knowledge can be held collectively, knowledge transfers are usually executed by individuals. Even when executed as a representative of a collective, the source is usually an individual. Individual members are powerful mechanisms for transferring knowledge because they can transfer tacit as well as explicit knowledge (Argote & Ingram, 2000), and are more equipped to adapt knowledge than other
knowledge repositories, and adaptation is often required to move knowledge across contexts (Argote & Fahrenkopf, 2016).
Knowledge stickiness could exist or arise at the source. A knowledge source could be reluctant to share crucial knowledge for a lot of different reasons, such as fear of losing ownership, a position of privilege, superiority. It may resent not being adequately rewarded for sharing; or it may be unwilling to devote time and resources to support the transfer (Szulanski, 1996). Another reason for stickiness at the source is knowledge hiding, which is not simply the absence of knowledge sharing but, rather, involves an intentional attempt to withhold knowledge (Connelly et al., 2012). Connelly and Zweig (2015) studied the consequences of different types of knowledge hiding and fount that evasive hiding leads to the most negative consequences. Interestingly, the predictors of knowledge hiding include many of the same factors that predict knowledge sharing, such as the quality of a relationship between a source and recipient. Which can be compared to arduous relations, which is found to be a significant factor of knowledge stickiness. The characteristics of the source are an essential factor in knowledge transfers, namely it connotes the very start of a knowledge transfer process, also known as the initiation phase (Szulanski, 2000). The factor “lack of motivation” of the source (Szulanski, 1996) is therefore included in the research.
Characteristics of the recipient of knowledge
Motivation, absorptive capacity, and retentive capacity were stated relevant by Szulanski (1996) as characteristics of the recipient, but only absorptive capacity (ACAP) was found to be significant. When recipients are unable to exploit sources of knowledge, one can speak of a lack of absorptive capacity (Cohen & Levinthal, 1990, Zahra & George, 2002). ACAP is defined as a set of organizational routines and processes by which firms acquire, assimilate, transform and exploit knowledge (Zahra & George, 2002) or as Cohen and Levinthal (1990) define it, the firm's ability to value, assimilate and apply new
knowledge. Zahra & George (2002) separate ACAP into two stages, the first concerns "potential ACAP," external knowledge must be identified, acquired and further analyzed, processed and understood. The potential ACAP can be transformed into "realized ACAP" when new knowledge is utilized and implemented in routines and operationalized in an organization. The potential of valuable knowledge and knowledge sources must, therefore, be continuously assessed through organizational routines, to timely identify and process this potential through assimilation, transformation, and exploitation. Szulanski (1996) found that units high in ACAP were more likely to transfer best practices successfully than their counterparts with lower absorptive capacity. Knowledge stickiness can be a restrictive factor, when organizations, as recipients, have not adequately and efficiently internalized ACAP.
Characteristics of the context
An organizational context provides the formal structure, systems, sources of coordination and expertise, and behavior-framing attributes of the organization that should affect the number of attempts to transfer knowledge and the outcome of those attempts (such as Burgelman, 1983; Goshal & Bartlett, 1994). Szulanski (1996) did not find this relation to be significant. Another contextual perspective, related to the social and relational (interpersonal) aspects of knowledge transfer, was found significant (Szulanski, 1996). A transfer of knowledge, especially when the knowledge transferred has tacit components, may require numerous individual exchanges (Nonaka, 1994). The interaction of the source and the recipient, therefore, has an impact on the effectiveness of knowledge transfers and its outcomes (cf. Argote & Ingram, 2000). An arduous (i.e., laborious and distant) relationship might create additional hardship in the transfer (Szulanski, 1996). Such characteristics of the context can be a reason for knowledge stickiness when relations are difficult between the source and recipient.
Grit
In achieving goals, personality traits can influence success. Personality traits are usually described by the Big Five personality traits (Extraversion, Emotional Stability, Agreeableness, Conscientiousness, and Openness to Experience) represented in the Five Factor Model (McCrae & John, 1992). Personality traits are the relatively enduring patterns of thoughts, feelings, and behaviors that reflect the tendency to respond in specific ways under certain circumstances (Roberts, 2009). Research on personality and behavior has a long history. Based on the insights of William James (1907) researchers were encouraged to address two broad problems: First, what are the types of human abilities and, second, by what different means do individuals unleash these abilities? The first part has been investigated thoroughly over last century; the second, however, has received little attention (Duckworth et al., 2007). The notion that sustained effort and focused interests are distinct from talent but equally vital to success have been discussed in the psychological literature for well over a century (Eskreis-Winkler et al., 2014). We know comparatively little about why, as James (1907) put it, most individuals make use of only a small part of their “resources,” whereas a few exceptional individuals push themselves to their limits (Duckworth et al., 2007) in utilizing their focus and sustained effort more effectively. What explains the variance in this utilization and achievement between individuals? Is it about talent, physical strength, mental hardship or other factors? Grit could be one of the answers. It is defined as perseverance and passion for long-term goals and entails working strenuously toward challenges, maintaining effort and interest despite failure, adversity, and plateaus in progress (Duckworth et al., 2007). As a personality trait, grit will affect the individual tendency to succeed. To illustrate, grit accounted for more variance in outcomes than commonly observed for Big Five Conscientiousness. (Duckworth et al., 2007), which is shown to be a significant trait for entrepreneurs (Zhao & Seibert, 2006).
Up to now, research on grit has been predominantly executed in educational or learning environments (Duckworth et al., 2007; Duckworth et al., 2009; Duckworth et al., 2011). It was found in several
studies that individual differences in grit accounted for significant incremental variance in success outcomes over and beyond that explained by IQ (Duckworth et., 2007). It shows that perseverance is at least as crucial as intelligence. The most critical inherent differences may be ones of temperament rather than of intellect as such. One outcome showed that grit more strongly predicts cadet retention at the Military Academy of West Point (USA) than does an SAT score, high school rank, or self-control (Duckworth et al., 2007). Eskreis et al. (2014) found an association between grit and retention in a range of life contexts, such as job retention, drop-out of military special forces selection, and marriage. The findings of earlier research to grit (Duckworth et al., 2007; Eskreis-Winkler et al., 2014) are consistent with other research showing that personality traits have small or small-to-medium sized predictive validity over and above individual difference variables and demographic predictors of life outcomes (Roberts et al., 2007). Indicating that grit can be used in other contexts than educational environments. The achievement of goals at educational institutions are clear-cut since the effect of grit can be measured in retention, receiving grades and diplomas. In an entrepreneurial context, the achievement of goals is less specific or tangible and will be more difficult to measure. As shown in earlier research, grit will affect the individual tendency to succeed. The association of grit and entrepreneurship could be considered straightforward. Perseverance and a passion for long-term goals can be seen as requirements for effectively thinking and doing in an entrepreneurial context.
Social Identity
Since the publications of social identity theory (Tajfel, 1978; Tajfel & Turner, 1979) and later the theoretical expansion of self-categorization (Turner, Hogg, Oakes, Reicher, & Wetherell, 1987) these concepts have steadily and increasingly impacted the field of psychology (Postmes & Branscombe, 2010). Tajfel (1978) famously defined social identity as “that part of an individual’s self-concept which derives from his knowledge of his membership of a social group (or groups) together with the
groups has serious implications for their experience and behavior (see; Tajfel & Turner, 1979; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987). Social identity and identification are now considered as “root constructs” in organizational phenomena (Albert et al., 2000). Whether this is related to an organization, group or person, each “actor” needs at least an answer to the question "who are we?" or "who am I?" to interact effectively with other actors. Similarly, other actors need at least an answer to a preliminary question “who are they?” for effective interaction. Thus, identities situate the organization, group, and person (Albert et al., 2000) since they cannot act meaningfully without a situated sense of who they are and who their fellow actors are (Ashforth, 2016).
A key conceptual advancement of social identity theory is the notion that individuals categorize themselves into specific social identities, so-called in-groups as opposed to out-groups (Tajfel & Turner, 1986), resulting in the tendency to behave as a collective (group), as opposed to an (independent) individual. Being part of an organization implies multiple group memberships: membership in the organization as a whole, in one's department, in one's team or work unit, and so forth (Knippenberg, 2000). Individuals will identify in different ways with different groups. Especially in larger organizations, this is of importance, because there will likely be individual differences in the strength of their ties with different groups. However, not all groups are equally influential. The individuals' level of identification with in-groups determines the degree to which their membership is psychologically affecting and socially consequential (Ellemers, Spears, & Doosje, 1999). It has made in-group identification a near indispensable construct in understanding intra- and intergroup dynamics (Leach et al., 2008). Empirical work has overwhelmingly focused on the organization as the target of identification compared to groups, teams, and subunits (Miscenko & Day, 2016). However, as in most social domains, life in organizations is experienced locally. The tasks one performs, the coworkers one interacts with, the manager that directs traffic, and the physical setting where one spends the bulk of one's time tend to be bound to a particular niche of the organization (Ashfort, 2016). For these reasons,
measuring the strength of the social identity will be on the unit level and the RNLMC organizational level to compare results from both perspectives.
Theoretical framework
An attempt is made to research how individual entrepreneurial actions and intentions are related to organizational (knowledge) routines and whether specific personal characteristics and the social context of an organization will affect this relation to deepen the understanding of organizational behavior. Specifically, the focus of this research is on IEO and its relation with difficulties in knowledge transfers, known as knowledge stickiness. It is believed that this relation is affected by the grit and by the social identity and identification to elements of the organization.
EO leads to improved performance (Rauch et al., 2009). Because of the reciprocal relation of EO and IEO, it can be argued that high levels of IEO will be beneficial to organizations and will therefore indirectly lead to improvements in performance. Organizational routines should, however, enable the underlying individual entrepreneurial intentions to be successful. A part of these routines are knowledge-based and are required for identifying the opportunities needed for entrepreneurial activity. One of the origins of entrepreneurship is the knowledge context, combined with routines, resources and the evolution of the business environment (Agarwal & Shah, 2014). Argote and Fahrenkopf (2016) have suggested that the study of knowledge transfer needs to expand to new problem domains such as entrepreneurship. It is their view in applying the understanding of knowledge transfer to advance the analysis of other phenomena, including organizational form, entrepreneurship, innovation and strategic management. Since knowledge transfer is part of the routines of organizations, it is indirectly about how an organization manages these routines. Knowledge should, therefore, be easy to access, easy to share and should be exploited in effective and appropriate ways in an organization. Otherwise,
entrepreneurial activity will be limited and will not be undertaken efficiently. In the process of knowledge sharing Szulanski (1996) found there is a strong correlation (R=0,87) between the process stages (initiation, implementation, ramp up & integration) and origins of stickiness (knowledge, source, recipient, context). In other words, there is a linear relation between the origins of knowledge stickiness and the process stages of knowledge transfer. High levels of knowledge stickiness are believed to hamper and restrict IEO, and on the contrary fluid knowledge transfers will be beneficial for IEO and performance. However, knowledge transfer does not automatically occur (Argote & Miron-Spektor, 2011). The central competitive dimension of what firms should know how to do is to create and transfer knowledge efficiently within an organizational context (Kogut & Zander, 1992). It is the organization that needs to organize itself to mitigate knowledge stickiness effectively.
Knowledge is required to discover and exploit new opportunities (Wiklund & Sheperd, 2003). Given that the primary focus of management research involves distinguishing between effective and ineffective management practices (Dess & Lumpkin, 2005), it is about how an organization can be effective in transferring knowledge to ensure success in performance. Not being effective in transferring knowledge will have consequences for the performance of organizations, including its antecedents such as (I)EO. When knowledge cannot adequately be transferred, a gap will occur between what is known within an organization and what is actually put to use (Szulanski, 1996). Hypothesis 1: Knowledge stickiness has a negative effect on IEO
From an explorative perspective, the effect of grit will be investigated. The effect of grit in an entrepreneurial context has not been examined before in literature. The type of effect is to be tested since no prior data exists. The consideration of a third variable may appear simple, but three-variable constructs can be very complicated (MacKinnon et al., 2007). There is a reason to believe that grit will have a positive impact on the relation of knowledge stickiness and IEO. Whether as a mediator, which
is a variable that is in a causal sequence between two variables or as a moderator which is not part of a causal sequence between the two variables (MacKinnon et al., 2007). First, it will be determined whether there is a direct effect on the dependent variable, IEO. Followed by testing for mediation effect and moderation effect.
Wiklund and Sheperd (2003) note that knowledge-based resources have an essential role in EO. These knowledge-based resources mostly consist of the personnel in an organization. The presence of positive personality traits will likely generate positive results. Grit, which contributes to long-term goals and perseverance (Duckworth et al., 2007), is considered to have a positive effect on proactiveness, innovativeness, and risk-taking at the individual level (cf. Bolton & Lane, 2012). Therefore, a positive association with IEO is foreseen and a direct effect positive effect of grit on IEO is anticipated.
Hypothesis 2a: Grit positively influences IEO.
It is possible that (a part of) the effect of knowledge stickiness on IEO goes through grit, meaning that grit is (partly) mediating the effect of knowledge stickiness on IEO. Mediation is one way that can explain the process or mechanism by which one variable affects another (MacKinnon et al., 2007) and it will be investigated statistically (cf. Fiske et al., 1982) Intuitively, it seems that high levels of knowledge stickiness imply almost the opposite of high levels of IEO. However, it could be that grit is the variable that explains the mechanism of how knowledge stickiness affects IEO, following "attitudes cause intentions, which then cause behavior" (Fishbein & Ajzen, 1975) and can be seen as a chain of relations (Baron & Kenny, 1986). This assumes that knowledge stickiness will affect grit negatively, meaning high levels of stickiness will likely result in low grittiness. The second step in mediation is the effect of grit on IEO, which has been discussed at hypothesis 2a. The total effect is expected to be negative, due to the negative anticipated relation of knowledge stickiness on IEO and
grit. It is believed that people with high grittiness will be able to act entrepreneurially, even when knowledge stickiness exists.
Hypothesis 2b: Knowledge stickiness has an indirect negative effect on IEO, through Grit.
Another probability is that grit moderates the effect of knowledge stickiness on IEO. Grit will most likely positively influence this effect since it is believed that perseverance and a passion for long-term goals contribute to an IEO perspective. High levels of grittiness will probably be effective against and could overcome the knowledge barriers of causal ambiguity, ACAP and arduous relations. Therefore, the negative association between knowledge stickiness will likely be lessened by grit.
Hypothesis 2c: Grit will lessen the negative effect of knowledge stickiness on IEO.
Lumpkin and Dess (1996) have called for additional research to provide insight into areas such as the relationship between EO and culture, and how complex social processes may be associated with EO. Argote and Fahrenkopf (2016) have further argued that more research is needed to identify conditions that facilitate or impede the transfer of knowledge in the various repositories across social units. Therefore, social processes and structures provide relevant research approaches concerning IEO and knowledge transfer. Kane et al. (2005) hypothesized and found that sharing a social identity led group members to be open to the ideas of members from other groups to adopt those ideas that were likely to improve performance. Notably, social identity is not a unidimensional construct but typically consists of many different yet interconnected sub-identities (Mischenko & Day, 2015). It is believed that when the RNLMC, as the organizational level actor, is seen as the group with the strongest social identity, then knowledge will be transferred more efficiently compared to when social identity is stronger at a lower unit or department level in the RNLMC. Most marines will likely have the strongest tie with the RNLMC at the organizational level since units or departments are often seen as a temporary
social unit because the regular job-rotation period usually is two years. This transient nature of jobs will lead to a stronger social identity at the organizational level because this tie is lasting. This shared superordinate identity promotes effective communication and knowledge transfer (Argote & Fahrenkopf, 2016). The starting assumption is that social identification reflects the relationship of an individual with a group, not with other group members (Postmes et al., 2013).
Hypothesis 3: Social identity at the RNLMC level will have a more positive effect than social identity at the lower unit or departmental levels.
A strong social identity will likely lessen the negative effect of knowledge stickiness on IEO. Furthermore, social identity is believed to have a direct positive impact on IEO. When higher levels of identification at the organizational level are perceived, intentions to improve the organization and act entrepreneurially for that organization are more likely to occur. It is therefore believed that when social identity enables effective communication and knowledge transfer (cf. Argote & Fahrenkopf, 2016), knowledge stickiness would be reduced. Then, arduous relations (Szulanski, 1996) would be less of an issue, and causal ambiguity could be reduced since there should be a higher common understanding of diverse practices and procedures. Indicating that a certain amount of tacit knowledge will be transferred. Kogut and Zander (1992) support this view, when stating that "in group and collectively held knowledge tacitness could be seen from another perspective, where such collectivity is seen as highly beneficial for an organization. Social relationships are required to transfer and (re)combine knowledge and make organizations grow." Aiming for growth clearly follows an entrepreneurial spirit.
Hypothesis 4a: A strong social identity will have a positive effect on the association of knowledge stickiness on IEO.
When grit is combined with a strong social identity, it is believed that this will create a strong positive interaction (cf Albert et al., 2000). Argote and Fahrenkopf (2016) mention that psychological factors play important roles in knowledge transfer across social units and other factors come into play such as social networks. The strength of that social network is dependent on the level of social identity. Hypothesis 4b: A strong social identity will have a positive effect on the association of grit on IEO
As a simplified overview, figure 1 shows the conceptual model, including all possible relations, and corresponding hypothesis. Knowledge Stickiness IEO Grit SID H1 H2b H4a H4b H2a H2c H3 (+) (+) (+) (+) (-) (-)
Method
The population for this research is the Royal Netherlands Marine Corps (RNLMC). The RNLMC is part of the Royal Netherlands Navy, and historically provide their land(ing) force "Qua Patet Orbis" (as wide the world extends), thus mostly projected from the sea. Marines are light infantry soldiers and provide special operations (capable) units, who are specialized in amphibious operations; initial entry operations; and military operations in extreme environments, i.e., in the desert, mountains, arctic and jungle. Every Marine goes through arduous training before being part of this elite unit. The actual strength is estimated on 1900 persons, based on an anonymized copy of the personnel file of the
RNLMC units.2
Research process
Access to sources of data in the RNLMC was not an issue since it was internal research. The research was designed following a sequential mixed method approach, with exploratory interviews followed by a web-based survey (cf. Tashakkori & Creswell, 2007) to collect relevant data. The overall purpose and central premise of mixed methods studies in business fields is that the use of quantitative and qualitative approaches in combination provides a better understanding of research problems and complex phenomena than either approach alone (Creswell & Plano Clark, 2007), and can enhance and extend the logic of qualitative explanations about the social world (Creswell et al., 2006).
Qualitative data collection preceded quantitative data collection to provide the input for the conceptual model and survey instrument (Teddlie & Tashakkori, 2003). The intention was first to explore the RNLMC context and (I)EO related factors for the identification and choice of adequate and valid variables to incorporate into the questionnaire. This mixed-methodology enhances validity, and it
combines results to develop broader and more in-depth interpretations (Cf. Green et al., 1989), and is more likely to yield richer and more appropriate findings (Molina-Azorin et al., 2012).
Qualitative part
The qualitative part was set-up as an inductive pilot study to enhance the research design and to decide on what type of further research was most appropriate (Teijlingen & Hundley, 2001; Saunders et al., 2012). The researcher is in active service in the RNLMC since 2000 and has good awareness on the RNLMC organizational history (Miller & Friessen, 1984) by years of observations, interviews, discussions, experience and internal reports. This context led to the initial idea of exploring (I)EO in the RNLMC. The research started with the presumption that EO is found to contribute to the performance of organizations (Rauch et al., 2009) and observations that the knowledge residing in the personnel of the RNLMC is not utilized effectively for innovation and renewal. Both factors were discussed in hour-long semi-structured interviews with three top managers, using existing contacts. The interviews were audio-recorded and transcribed before qualitative data analysis. Although only three interviews were conducted, some saturation of responses was clear. The interviews were coded by the theory method of Charmaz (2006). First, initial coding was conducted, and labels were given to aspects of IEO, mindset and other organizational factors. This categorization helped to identify significant concepts and themes to develop a narrower focus during this process. Second, focused coding (Charmaz, 2006) in combination with further literature research followed in reanalyzing the data to gain further insights and trying to link these to academic concepts to establish a grounded theory. “Stickiness” was found to be the most common and recurring factor. The origins of this stickiness varied in the answers, it was due to "bureaucracy, centralization of processes, risk aversion or organizational culture." It was apparent that stickiness created barriers. This notion was further explored in academic literature and considered in combination with the underutilized knowledge potential, and related transfers of knowledge to “knowledge stickiness” which represents
organizational routines and processes (Szulanski, 1996). The interviews were also about mindset and the spirit of Marines, with their "can do" attitude and stamina to fulfill any given mission. Routines are always affected by personalities and organizational culture. Grit was found in the literature (Duckworth et al., 2007) as a factor that is very related to the spirit of the RNLMC with their core values: Strength, Unity, and Dedication. Duckworth (2016) mentions the equation “skill x effort = achievement,” which can be regarded as part of the mindset on how the RNLMC operates. Perseverance is commonly seen as essential and required in successfully achieving missions, which is related to dedication and strength. Unity is considered another "strength" in the RNLMC since most activity is done in units. It implies interdependence on their fellow Marines at any given moment in their work in achieving their missions. Unity is considered related to social identity (Tajfel, 1978) and is regarded as a critical value within the RNLMC. This identity and inherent identification as a Marine with the RNLMC are never lost, nor forgotten. Once you become a Marine, you stay a Marine. There are no ex-Marines! The results of the interviews and further research in literature have led to the design of the conceptual model (see Figure 1), and its hypotheses, that initiated the quantitative phase of the research (cf. Tashakkori & Teddlie, 1998).
Quantitative part
Sampling
Due to limited time and restricted access to detailed personnel files, it was not possible to build a complete probability sampling frame. Therefore, a non-probability sampling method was chosen. The strategy for sampling was built on the quota sampling method, which is quicker than probability sampling and makes research on smaller subgroups possible (Saunders et al., 2012). Quota sampling is a type of stratified sampling in which selection of cases within strata is entirely non-random (Barnett, 2002) but presents reasonable to high representation of the population (Saunders et al., 2012). The sampling method was used to create sufficient data in total, but also per subpopulation, to be able to
conduct further analysis. Indirectly and through management, every person in the RNLMC operational units was invited to participate in the research and given the means to do so.
Groups were based on individual specialization, thinking specialization could differ in affecting grit and IEO. Units may sound more logical, but in the RNLMC context with the temporary nature of jobs, specialization is more logical since it is permanent and provides a clear distinction between groups. Especially considering the differences in nature, effort, and duration in becoming a specialist (see Appendix 1 for types of specializations and response rates). The requirement for each group was set at 30 persons, following Central Limit Theorum, which was mostly achieved during the research. Two groups needed a reminder to ensure sufficient respondents. Only Recce, Amphibious, and Sports are specializations that are underrepresented. It is not an issue for sports (instructors) as a general specialization, but is a pity for the amphibious specialists, as a niche capacity, since the number of respondents provided too little input for being representative. Recce did not provide sufficient response, but there is similarity in comparison to SOF.
The questionnaire
The questionnaire was designed following the outcome of the qualitative part. Easy to comprehend and limited in the amount of time needed to complete were factors influencing the composition of the questionnaire. (cf Galesic & Bosnjak, 2009). Initially designed with the original (untranslated) constructs, but when pretesting the questionnaire (Presser et al., 2004), it became apparent that the required level of English (reading and understanding) was not sufficient to release the questionnaire. Therefore, the questionnaire was translated into Dutch and being tested by back-translation (Brislin, 1986) using two other persons.
The questionnaire was sent via MoD intranet email to the author, with all line managers and unit commanders in BCC, who were asked to distribute the questionnaire to their personnel. All per the ethical principles in research (Saunders et al., 2012) such as the protection of participants (i.e., privacy
and respect for others), and under the Academy of Management Code of Ethics (2016). The email briefly explained the aim and content of the research and provided some explanation on how to participate. Two options were presented to get access to the questionnaire. One was an internet link, and the other was a QR code which could be scanned via mobile phone to access to the online and mobile-friendly questionnaire. To promote participation, sharing via "Whatsapp" groups and printing the QR code to provide access to large numbers in short amount of time was suggested.
After two weeks, the response of two units with specialists was meager, and their line managers were contacted a second time which led to sufficient response from only one of those units. The questionnaire was available from the initial email on 16 November until Christmas 2017.
Data collection
A total of 332 persons responded to the survey, resulting in a response rate of 17,5% (on the estimated population of 1900 persons). The response rate is calculated on the assumption that all line managers and unit commanders passed on the information to their colleagues and subordinates. The QR code was used by 41% of the respondents, leaving 49% using the link. When cleaning for missing data, it became clear that 75 respondents did not finish their questionnaire. Listwise deletion gave 257 useable responses for analysis. No alternative method (such as Meyers, 2011) was used for handling missing data since the number of responses suffices for further analysis, the margin of error is 5.69% at a 95% confidence interval. In regard to non-completion, 9.6% stopped after entering their personal information, 1.6% stopped after the first data collection part (IEO), another 1.5% stopped after the following part (grit) and only .6% stopped just before the last part, leaving 77.4% (N = 257) of the total responses completed. All ranks were represented in not completing the questionnaire. However, a significant association between rank and finishing the questionnaire was found, c2(9) = 24.622, p =
.003. There are differences in the response rate of Marines, NCOs, and officers. The effect size is moderate (f = .272, approximate p = .003). In finishing the questionnaire, 62.5% of the enlisted
Marines; 75-80% of NCOs and 90% of the officers were successful. It could be that the level of personal experience with the topics influenced the determination to complete the questionnaire.
The variables
The main variables were checked for normality and analyzed for reliability using Cronbach's alpha, with a minimum of .7 following Nunnally and Bernstein’s (1994) standard for scale development. Various statistical tests were executed to analyze the questionnaire data in SPSS. Detailed statistical information on the variables is presented in the next paragraphs, starting with the dependent variable (IEO), followed by the independent variable (knowledge stickiness), grit as an "affecting variable," the moderating variable of social identity and finally the control variables. Descriptives of all variables can be viewed in table 1.
Table 1: Descriptives of main variables
Type Variable Mean SD Cronbach's Skewness Kurtosis
DV IEO 4.046 .482 .786 -.968 3.486
IV Knowledge Stickiness .000 .409 .839 .138 1.135
Mod/ Med Grit 3.717 .421 .728 -.214 -.341
Mod SID RNLMC 5.890 1.384 NA -1.718 2.565
Mod SID unit 5.470 1.559 NA -1.315 .952
CV Unit -- -- -- .315 -1.563 CV Years in service 13.910 10.222 NA .653 -.513 CV Rank 4.160 2.507 NA .238 -1.227 CV Specialization -- -- NA -.814 -.825 CV Deployed on Operations 3.110 1.416 NA -.003 -1.326 CV Education level -- -- NA .521 -.783
Dependent variable: Individual Entrepreneurial Orientation
Bolton and Lane (2012) created the measurement of IEO on a ten-item, five-point Likert, scale ranging from strongly disagree to strongly agree. Reliability of the construct is good, with Cronbach's Alpha of .786. All items have good correlation with the total score of the scale (all above .30). Deletion of
items does not improve the reliability of the scale. A Normality check was conducted and resulted in an expected and "normal" distribution, however, centered on the mean of 4.04 (SD = .482). Distribution does not show actual skewness, although this would be expected with a score of -.968. The results show kurtosis (3.49), since the majority has scored very high on IEO (median = 4.1) . An explanation is that Marines are trained to take risks, try new things and be proactive in their work. An exploratory factor analysis was conducted to see whether the original dimensions (Bolton & Lane, 2012) differ from the findings of this research. The Kaiser-Meyer-Olkin (KMO) measure verified the sampling adequacy for the analysis (KMO = .819). Bartlett's test of sphericity is significant (p < 0,001) indicating that the items are unrelated and multiple factors exist. The analysis shows two components with an eigenvalue over Kaiser's criterion of 1 and in combination explain 47,18% of the variance. A third factor has an eigenvalue of .938. Although not up to the standard of Kaiser (1960), other researchers such as Jollife (1972, 1986) have argued that Kaiser's criterion is too strict and suggested that .7 could be a threshold. To be able to check alignment with the original three dimensions, the threshold was lowered to .9. Three factors derived from this factor analysis with 56.57% of the variance explained. The three factors were rotated with a Varimax method with Kaiser Normalization. The outcome represented the IEO scale by Bolton & Lane (2012).
Independent variable: Knowledge Stickiness
Knowledge Stickiness factors (Szulanski, 1996) are measured with different scales. Lack of motivation is measured on a 14 item binary scale (yes-no), absorptive capacity (9 items) and causal ambiguity (6 items) are measured on a five-point Likert scale (Yes!/ yes, but/ no opinion/ no, not really/ No!) and arduous relations is measured on a three-item, four-point Likert, scale (very easy, fairly easy, fairly demanding, very demanding). To be able to analyze and test the data it was required to normalize the items by creating z-scores.
The original scales required context to specify this research on knowledge stickiness. The "practice," the "source" and "recipient" needed to be entered (Szualnski, 1996). Innovation was used as the practice since it is the scope of the research and often preached but rarely effectuated. There is a vast potential for innovative and entrepreneurial ideas at the individual level, but this knowledge and ideas are not often used by, available for or accessible to the organization. Each Marine (respondent) is considered a source and the recipient was the RNLMC organization.
Reliability of the normalized knowledge stickiness is excellent, with a Cronbach's Alpha of .839. Exploratory factor analysis showed that the Kaiser-Meyer-Olkin measure verified the sampling adequacy for the analysis (KMO = .850) and Bartlett’s test of sphericity is significant (p < 0,001) indicating that the items are unrelated and multiple factors exist. The analysis shows seven components with eigenvalues over Kaiser's Criterion of 1 and in combination explained 58.47% of the variance. The factors were rotated by a Varimax method with Kaiser Normalization. Examination of the scree plot shows a point of inflection after the second factor, although eigenvalues at that point are still around 2. Field (2013) indicates that all factors right of the point of inflection should not be included and, in this case, only two factors should be retained. A second factor analysis is run, with a maximum of 2 factors, which shows a loss of information in the commonalities. Fewer factors obviously mean less of the variance explained, only 36.18% with 2 factors. Therefore, it is decided that all seven factors with an eigenvalue over 1 will be retained, following Kaiser's belief that all factors should be retained when they are above 1 (Kaiser, 1960). When regarding the content, the variance explained by the seven factors show great similarities with the original variables of Szulanski (1996) but have a slightly different scope. The original variable of "Lack of Motivation" is now represented in 3 factors, so-called; self-performance; organizational operationalization of innovation and; training/education support. The variable of "Causal Ambiguity" only retained 1 item that was actually about causal ambiguity, the other items of the variable were represented by so-called "Innovation standard operating procedures" (SOP). This change is not a big one considering that SOPs normally give clarity, for
