How organisational climate and identity can overcome cultural barriers towards the willingness of knowledge sharing in a military organisation

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Master Thesis

How organisational climate and identity

can overcome cultural barriers towards

the willingness of knowledge sharing in a

military organisation

Executive Programme in Management Studies

Strategy Track (2016-2018)

Date of Submission:

29

th

_{June 2018}

Author:

F.C. (Ferry) Jong

Student number:

11203552

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Statement of originality

This document is written by student F.C. (Ferry) Jong 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.

F.C. (Ferry Jong)

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Abstract

This study aimed to explain how organisational identity and a changing organisational climate could overcome cultural barriers towards knowledge sharing in a military organisation.

Organisational culture has been recognised as a major barrier to knowledge management (De Long & Fahey, 2000). Overcoming these cultural barriers requires a climate of dependency and trusting relationships between community members (Buckman, 1998; Ali, Pascoe & Warne, 2002). The changing organisational climate between a home-stay and mission

environment within the military contributes to this research gap by deepen our understanding of the factors that increase and/or decrease members’ tendencies to engage in more

knowledge sharing behaviours. Because these behaviours are influenced by both personal motivations and contextual force (Yoo & Torrey, 2002) and organisational identity has been found to be a moderating factor by Kankanhalli et al (2005), it was included in this study.

A cross-sectional survey study was carried out and data was collected from 154 military employees within the Royal Netherlands Nav varying in rank, age, gender and educational level. The conceptual model was empirically tested by performing multiple hierarchical regression analyses. Results show that the lack of management support and the belief that sharing knowledge results in a loss of personal competitive advantage directly influence the willingness to share knowledge. Moreover, it was found that a home-stay climate interacts with the relationship between lack of management support and the willingness to share knowledge and organisational identity interacts with the relationship between the belief that sharing knowledge results in a loss of personal competitive advantage and the willingness to share knowledge.

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1. Introduction

As an extension of Barney’s (1986; 1991) resource-based view (RBV), Grant (1996)

introduced the knowledge-based view (KBV) of the firm. The internal focus on resources and capabilities of the firm would be a more stable basis for strategy formulation than the

traditional external focus. With the assumption that superior profitability is a consequence of resource and capability-based advantage rather than position and competitive advantages (Porter, 1979a, 1979b), he justified the integration of knowledge. It was identified as an organisational capability with the ability of repeatedly performing a productive task related to the capacity for creating value. Differences between organisations account for more variance in their performance than between industries (Rumelt, 1991). So, creating a competitive advantage should be focused on resources develop or made valuable inside the firm. The process and the difficulty of imitating these resources puts knowledge management in a preeminent position as a source of competitive advantage (Argote & Ingram, 2000). To obtain more profits, an organisation must capture and share knowledge in an effective way.

Knowledge management (KM) provides a framework to help creating, sharing and using that knowledge (Gan, Ryan & Gurirajan, 2006).

An increasing factor that has been recognised as a major barrier to knowledge management is organisational culture. De Long & Fahey (2000,) identified four ways in which culture influences the behaviours central to knowledge creation, sharing and use; “First, culture

shape assumptions about what knowledge is and which knowledge is worth managing.

Second, culture defines the relationship between individual and organisational knowledge,

determining who is expected to control specific knowledge, as well as who must share it and

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knowledge will be used in situations. Fourth, culture shapes the processes by which new

knowledge is created, legitimated, and distributed in organisations (De Long & Fahey, 2000, p. 113)”.

These four aspects of culture are most likely to influence knowledge-related behaviours. In a knowledge-sharing culture, people see it as natural to share ideas and insights it is natural to do. Prior research however shows that people have taught themselves to hoard knowledge over the years because it achieves power (Cantoni, Bello & Frigerio, 2001). Overcoming this cultural tendency to accomplish proactive knowledge sharing within an organisation requires a climate of continuity and trust (Buckman, 2000). Ali, Pascoe & Warne (2002) support the trusting relationship but claim that there is another factor which determines the success of knowledge sharing; the level of dependency between community members. This suggests that when the level of dependency increases by a changing organisational climate, it is likely that knowledge sharing increases between community members and cultural barriers towards knowledge sharing can be overcome.

Employees need to share what they know to make knowledge management work (Gupta & Govindarajan, 2000). In this perspective it is not the technology that makes knowledge management work, it is the culture and the environment that matter most (Gupta & Govindarajan, 2000; Mason & Pauleen, 2003; Spiegler, 2000). Dennis (1996) addresses organisational climate as a common phenomenon: the creation and influence of social

contexts in organisations. It refers to a contextual situation at a point in time and its link to the beliefs, feelings, and behaviours of organisational members. Thus, it is temporal and

subjective (Bock & Kim, 2002). Culture on the other hand, refers to an evolved context wherein specific situations are embedded. It is rooted in history, collectively held, and

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sufficiently complex to resist attempts at direct manipulation (Dennis, 1996). So, when the organisational climate changes to one that calls for a more trusting relationship and higher dependency level between community members it is likely to affect the willingness towards knowledge sharing and overcome cultural barriers towards it.

An organisation which constantly needs to adapt to changing climates and which can

contribute to this gap in the current knowledge management research is the military. Although their culture is rooted in history, the contextual situation i.e. organisational climate between a deployment (mission) and home-stay environment is totally different. This changing

organisational climate enhances the call for trusting relationships and increases the

dependency level between members. Therefore, it is expected that this change overrules the cultural influences of De Long & Fahey (2000) on knowledge sharing behaviour.

Looking at a military organisation, another factor must be considered. The military is well-known for their organisational identity. Prior inconsistent findings on rewards and incentives towards knowledge sharing suggest the possibility of moderators such as personality and contextual conditions (Wang & Noe, 2010). Organisational identity has been found as such a factor (Kankanhalli et al, 2005) and must therefore be taken into account of this study. Christensen (2007) also identified the lack of an identity as an important factor that have an impact on knowledge sharing. A common identity provides knowledge sharing in an easy way, as people from the same group use a same technical language, use common data and are interesting to reach the same aims. Building on this current state of literature, the research question for this study is;

“How can organisational climate and identity overcome cultural barriers towards the

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This study aims to explain the direct relationship of military culture towards the willingness of sharing knowledge and the (in)direct effect of organisational identity and organisational climate on this relationship.

A quantitative survey study within the Royal Netherlands Navy has been done to complement current research on knowledge sharing. This study contributes current knowledge

management research by informing entrepreneurs and their firms on the factors that affect the willingness to share knowledge. Consequently, this can improve knowledge management by informing managerial interventions that help design and re-design organisational mechanisms to support it (Fahrenkopf & Argote, 2015). By also looking at the psychological processes that underlie knowledge sharing within the organisation, a third contribution will complement current work in cognitive psychology at the individual level of analysis on knowledge sharing (Argote, Ingram, Levine & Moreland, 2000).

This study consists of five additional chapters. Next chapter will consist of an overview of relevant literature resulting in the hypotheses that are grounded in it. Chapter 3 describes the research methodology of the conducted survey. It includes a description of the population and sample, data collection method and measurement of the variables. Chapter 4 presents the results by descriptive statistics of the data and the statistical analyses being done to test the hypotheses. Chapter 5 presents the conclusions and discusses the significance of findings, including its relation to current literature, the contributions to science, the limitations of the study and recommendations for future research.

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2. Literature review

This chapter provides a detailed (theoretical) background for the conducted study about knowledge sharing. The first 2 paragraphs define the concept of knowledge and the willingness for sharing it. Paragraphs 3 to 5 presents an overview of relevant research

constructs that leads to the research hypotheses. Visualization of the conceptual model will be at the end of this chapter.

2.1 Knowledge

In order to answer the research question, it should be clear to what knowledge is, what types of knowledge there are, what the difference is between knowledge sharing and transferring and what we define as knowledge management. Knowledge comes from information and information comes from data. Davenport & Prusak (1998) viewed data as a set of facts and events. It is the base for information, because information can be determined as organised data (Jaspara, 2004). Knowledge is based on information and is situated in an individual’s mind. It represents experiences. Liyanage, Elhag, Ballal & Li (2009) claim that knowledge appears in the individual’s mind and is interpreted information by people. Wang & Noe (2010) define knowledge as information processed by individuals including ideas, facts, expertise, and judgements relevant for individual, team, and organisational performance.

Knowledge can be either explicit or tacit. Nonaka & Takeuchi (1995) describe tacit

knowledge as it exist in human mind and it is hard to capture and codify. As it is difficult to be codified, captured and represented as information which is stored the organisation, tacit knowledge (embedded in the human mind) brings more value to an organisation than explicit knowledge. This type of knowledge is based on common believes and understandings. To

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overcome transmission issues, organisations must provide an effective communication between participants in order to exchange this type of knowledge.

Knowledge transfer and knowledge sharing are terms that have been used in order to describe this exchange of knowledge, but they are different to each other. Knowledge sharing refers to the provision of task information and know-how to help others and to collaborate with others to solve problems, develop new ideas, or implement policies or procedures (Wang & Noe, 2010). Another definition of knowledge sharing (Paulin & Sunesson, 2012, p.83) is; “An

exchange of knowledge between two individuals: one who communicates knowledge and one

who assimilates it. In knowledge sharing, the focus is on human capital and the interaction of

individuals. Strictly speaking, knowledge can never be shared. Because it exists in a context;

the receiver interprets it in the light of his own background”

Knowledge sharing differs from knowledge transfer. Knowledge transfer involves both the sharing of knowledge by the source and the acquisition and application of knowledge by the recipient. It is a process of interaction. Paulin & Sunesson (2012, p. 83) define knowledge transfer as; “The focused, indirectional communication of knowledge between individuals,

groups or organisations such that the recipient of knowledge (a) has a cognitive

understanding, (b) has the ability to apply the knowledge, or (c) applies the knowledge”

The final concept to define is knowledge management. De Long & Fahey (2000, p. 115) claim that the purpose of knowledge management is; “to enhance organisational

performance by explicitly designing and implementing tools, processes, systems, structures,

and cultures to improve the creation, sharing, and use of all types of knowledge that are critical for decision making”. Cantoni & Frigerio (2001, p. 665) define knowledge

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within and across organisational boundaries, to produce and share new knowledge”. The

basic aim of knowledge management is to provide a framework for the capturing and sharing of knowledge within the organisation (Gan, Ryan & Gururajan, 2006).

2.2 Willingness to share knowledge

A major and repeatedly returning identified barrier for knowledge sharing and transfer is the motivation of the sender and receiver (Szulanski, 2000). Prior research of Davenport (1997) also argued that the sharing of knowledge is often unnatural. Gibbert & Krause (2002) claim that knowledge sharing is something that cannot be forced but can only be encouraged and facilitated. Fostering the motivation to share should precede, rather than just encouraging or mandating knowledge sharing. The attitude i.e. willingness towards knowledge sharing is defined by Ajzen & Fishbein (1980) as the degree of one’s positive feelings about sharing one’s knowledge. Positive attitudes towards knowledge sharing is crucial to knowledge management (Dignum & van Eijk, 2005).

The Theory of Reasoned Action (TRA) is adopted as the theoretical basis to explain how willingness affects knowledge sharing behaviour (Fishbein & Azjen, 1975). TRA assumes rationality of human beings and making systematic use of information available to them. A specified behaviour of a person is determined by his behavioural intention to perform the behaviour. The intention is jointly determined by a person’s attitude concerning the specified behaviour. In other words; positive attitudes towards knowledge sharing leads to a positive intention to share and ultimately to actual knowledge sharing behaviours (Bock & Kim, 2003). Knowledge sharing behaviour is assumed to be motivated and executed mainly at the individual level.

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Social exchange theories suggest that individuals evaluate the perceived ratio of benefits to costs and base their decisions on the expectation that it will lead to positive rewards (Blau, 1964). The willingness to share is a function of the benefits and costs analyses, but current research literature is unclear whether these benefits are externally or internally motivated. This reflects the distinction between agency and stewardship theory of management (Davis, Schoorman, Donaldson, 1997). Agency theory provides mostly financial incentive schemes to externally motivated employees in order to align the principal and agent interests. Researchers have criticized this perspective as being a simplification for mathematical modelling and an unrealistic human behaviour description (Jensen & Meckling, 1994). The stewardship perspective argues that the employee i.e. steward perceives greater utility in cooperative behaviour and can therefore still be considered rational. The motives between agents and principals are aligned. According to this theory, when life dependency is at stake, like in a mission climate, the benefits for sharing knowledge with team members would be expected to be of greater utility and of a higher order need (Maslow, 1970) than when this dependency factor is not at stake. The steward realizes that by working toward organisational, collective ends, personal needs are met (Davis, Schoorman & Donaldson, 1997). Therefore, it is likely that knowledge sharing within a military organisation in a home-stay climate will be less compared to knowledge sharing in a mission climate.

Because knowledge sharing is the fundamental (means through which employees can

contribute to knowledge application, innovation and ultimately the competitive advantage of the organisation (Jackson, Chuang, Harden, Jiang, & Joseph, 2006), it allows organisations to exploit and capitalize on their knowledge-based resources. (Cabrera, & Cabrera, 2005,

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extent to which knowledge sharing occurs between employees (Cabrera & Cabrera, 2005; Gupta & Govindarajan 2000; Nonaka, 1994; Polanyi, 1966). In other words, knowledge sharing will be expected to meet less resistance on the battlefield because it is seen as enhancing both survival and performance of the individual and the team (Dalton, 2010).

2.3 Military Culture

Culture is defined as the shared values, beliefs and practices of the people in the organisation (Schien, 1993). It is embedded in the way people act, how they make sense of each other’s actions and what they expect of each other. It is rooted in the core values of the organisation and refers to an evolved context within which specific situations are embedded (Bock et al., 2005). Organisational culture is widely held to be a major barrier to creating and leveraging knowledge assets (De Long & Fahey, 2000). Benefits of new technology infrastructure are limited if long-standing organisational values and practices are not supportive of knowledge sharing. Understanding how culture affects the willingness of sharing knowledge helps to design strategies to either adapt to the culture or to reshape it to support the firm’s knowledge management objectives. Dalton (2010) claims that over control of knowledge transfer

initiatives by military command and control hierarchy results in a high probability of causing those initiatives to fail, because it clashes between the bottoms up nature of knowledge transfer and the top down nature of command and control. The overall expected hypothesis which I will specify further with three indicators (knowledge is power belief, position insecurity & lack of management support) in the next section is;

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2.3.1 Knowledge is power belief

In the introduction, De Long & Fahey (2000) accumulated four ways in which culture influences the behaviours central to knowledge creation, sharing and use. At first, it shapes assumptions about what knowledge is and which knowledge is worth managing. Kluge et al. (2001) identified the “knowledge is power” belief as one of two main barriers to develop a knowledge creating and sharing culture. This mindset places the values of knowledge to the individual above its value to the company. Employees see their own knowledge as part of their own competitive advantage (McLaughlin, Paton & Macbeth, 2008). McKinsey’s “Corporate Prisoner Dilemma” illustrates this point well, which is a modification of game theory’s prisoner dilemma:

Figure 1: “Corporate Prisoner Dilemma” by McKinsey’s

Although the ideal solution would be to share, if one decides to hoard knowledge whilst the other shares knowledge then the power balance is in favour of the one who hoards knowledge.

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Hoarding knowledge and looking guardedly at the knowledge offered by others are natural human tendencies (Davenport & Prusak, 1998). If sharing what employees know incurs personal risks and decrease power, the social norm governing how they should interact will not support knowledge sharing behaviours (De Long & Fahey, 2000).

East Asian organisational cultures show similarities with military culture as it has a highly bureaucratic and hierarchical structure, centralised decision-making and a strong family feeling. Goh Guan Gan, Ryan, Gururajan (2006) claim that there is a tendency in East Asian cultures to avoid taking responsibility for failure due to their organisation structure and the need for self-preservation. This phenomenon, Kiasu (afraid to lose)-ism results from the mentality that “knowledge is power” and job insecurities in addition to competition among members which lead to the hoarding of knowledge (Chaudry, 2005). Kiasu-ism is found to be an inhibitor for knowledge management and has a wide-ranging effect on organisational culture as it would impact on collaboration and mutual trust. Because of the similarities between the East Asian and military organisational culture it is expected that the “knowledge is power” belief is present in military culture and negatively related to the willingness of sharing knowledge.

Hypothesis 1a: Knowledge is power belief negatively influences the willingness to share knowledge

2.3.2 Position insecurity

As mentioned by Chaudry (2005) there is another factor which affects Kiasu-ism, namely job insecurities. Within the Dutch military it is not the job insecurity, but rather the position insecurity that is expected to have an effect. Every two to three years an employee changes

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from position (Ministerie van Defensie, 2018). The organisational goal behind this human resource (HR) policy is to maximize the experience and know-how of an employee about the different sides of the military. Although the HR policy enhances the knowledge held by an individual employee, it also generates individual competition and insecurity because of the dispersed locations of military bases in and the unknowing of future positions. Organisational culture that emphasizes individual competition may pose a barrier to knowledge sharing (Schepers & van den Berg, 2007; Wang, 2004; Willem & Scarbrough 2006). De Long & Fahey’s (2000) second way of culture influencing behaviours central to knowledge sharing is the defining relationship between organisational and individual knowledge, by determining who is expected to control specific knowledge. The military HR practice described above shows that it may be useful for employees to hoard knowledge in order to be most suitable for desired future positions.

Bock & Kim (2003) found that anticipated extrinsic rewards tend to discourage the formation of a positive attitude toward knowledge sharing. The assumption that people will do a better job if they are promised some sort of rewards i.e. future position undermines intrinsic motivation. Kohn (1993), on the other hand, claims that when employees compete for a limited number of incentives i.e. positions, they will very likely begin to see each other as competitors to their own success. With each employee who wins, there are many who feel they have lost. Therefore, it is expected that employees within the military perceive a certain level of position insecurity and this negatively influences the willingness to share knowledge.

Hypothesis 1b: Perceived position insecurity negatively influences the willingness to share knowledge

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2.3.3. Lack of management support

The third and fourth way for which culture influences behaviour central to knowledge sharing is the way it creates context for social interaction that determines how knowledge will be used and the processes by which new knowledge is created, legitimated and distributed in

organisations (De Long & Fahey, 2000). Management has a crucial role in the creation of the context for social interaction and determining the sharing norms, acceptability of discussing sensitive topics and perceived approachability of senior management. A supportive and interactive learning environment is the major factor in the success of both tacit and explicit knowledge sharing (Smith, 2001). Management support for knowledge sharing has been shown to be positively associated with employees’ perception of a knowledge sharing culture and willingness to share it (Connelly & Kelloway 2003; Lin, 2007). Lee et al. (2006) found that top management support affected both the quality and quantity of knowledge sharing and Wang & Noe (2010) claimed that management support is a good predictor of employee knowledge sharing.

King & Marks (2008) on the other hand, failed to find a significant effect for perceived organisational support after controlling for the ease of use and usefulness of knowledge management systems. Within the military, knowledge is not widely accessible to employees as many of it is classified and protected for usage. Constant et al (1994) found that firms actively limit knowledge sharing, because of the threats associated with industrial espionage.

A functionally segmented structure, like the military, likely inhibits knowledge sharing across functions and communities of practice (Tagliaventi & Mattarelli, 2006). Kim & Lee (2006) also suggests that knowledge sharing may be facilitated by having a less centralized

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sharing, organisations should create opportunities for employees to interact and employees’ rank and position within the organisational hierarchy should be de-emphasized (Wang & Noe, 2010). It is not usual in the military to openly speak against a high-ranking officer. The social norms for interaction in the military is not expected to support knowledge sharing. Dalton (2010) claims that over control of knowledge initiatives by military command & control will likely result in fail because the culture clashes between the bottoms up nature of knowledge transfer and the top down nature of command & control. Therefore, it is expected that

employees within the military perceive a lack of management support for knowledge sharing and consequently, this lack negatively influences the willingness for sharing knowledge.

Hypothesis 1c: Perceived lack of management support negatively influences the willingness to share knowledge

2.4 Organisational Identity

Prior research shows controversial results about the effect of rewards. Kankanhalli et al. (2005) found that organisational rewards, such as promotion, bonus and higher salary positively relates to the frequency of knowledge contributions especially when employees identify with the organisation. On the other hand, several studies found no relationship between extrinsic motivation and knowledge sharing attitudes and intentions (Kwok & Gao, 2005; Lin, 2007). The inconsistent findings on rewards and incentives towards knowledge sharing suggest the possibility of moderators such as personality and contextual conditions (Wang & Noe, 2010).

Kankanhalli et al (2005) already mentioned the moderation by organisational identity. Christensen (2007) supports this by identifying a lack of an identity as an important factor in

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the organisation, which has an impact on knowledge sharing. The military is well-known for their organisational identification. Surviving basic military training and earning your beret to become part of the military gives many employees an honoured and proud feeling. Many commercials and songs also represent this. Verbs like “brothers in arms”, “the few, the proud, the marines”, “honour, courage, commitment” are examples that stimulate this common identity. Organisational identity provides knowledge sharing in an easy way, as people from the same group use the same language, use common data and are interested to reach the same aims. In the research of Hwang & Kim (2007), they measured collectivism and found that one’s collectivism was positively related to the attitude of knowledge sharing as students used the group e-mail function in an online classroom management system to share knowledge. They found that this relation was fully mediated by their identification with the group.

Hansen (1999) limited the reach of organisational identity by finding that strong social identities and in-group favouritism may hamper knowledge sharing across groups. The effect depends to some extent on the width and the strength of the relationship between recipient and the source. Every military employee needs to pass basic military training. For this reason, the width and the strength of the identity within the military is expected to be across the whole organisations. Therefore, it is expected that the perceived level of organisational identity directly influences the willingness to share and indirectly moderates the negatively relationship between military culture and the willingness to share knowledge.

Hypothesis 2a: Perceived level of organisational identity positively influences the willingness to share knowledge

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Hypothesis 2b: Perceived organisational identity moderates (diminishes) the negative relationship between military culture (indicated by a knowledge is power belief, perceived level of position insecurity and perceived lack of management support) and the willingness to share knowledge

2.5 Organisational Climate

“To move from a culture that calls for the hoarding of knowledge in order to gain power and

move towards one that rewards the sharing of knowledge with an increase in power, we need

to create a climate that fosters long-lived, trusting relationships” (Buckman, 1998, p. 14-15).

Ali, Pascoe & Warne (2002) support the trusting relationship but claim that the success of knowledge sharing is also dependent on the level of dependency between employees. The military is unique in the way that it operates in multiple climates. The most prevalent

distinction can be made between a home-stay and mission climate. The dependency between employees in a mission climate is far greater than in a home stay climate. Organisational climate refers to a contextual situation at a point in time and is linked to the thoughts,

feelings, and behaviours of organisational members at that time (Dennis, 1996). It is temporal, just like a mission. Prior research shows that organisational climate affects individuals’

intention to share (Bock et al., 2005). With the variable of organisational climate this study can deepen our understanding of the factors that increase or decrease employees’ tendencies to engage in more knowledge sharing behaviours. These behaviours are assumed to be influenced by both personal motivations and contextual force (Yoo & Torrey, 2002).

Organisational climate has the power of renegotiating norms around knowledge distribution, ownership, and access to overcome cultural barriers (De Long & Fahey, 2000). The most severe challenge that organisations face with the goal to increase knowledge-sharing

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behaviours is to actually change people’s behaviours. Constant et al (1996), Huber (2001) & Orlikowski (1993) consider organisational climate as a critical driver of knowledge sharing. He et al. (2009) claim that the social ties, shared goals, and social trust have a combined effect on the knowledge sharing of employees as they are independent variables that represent the three dimensions of social capital (Chow & Chan, 2008). Prior research of Coleman (1988) and Bock et al (2005) identified organisational climate factors related to the institutional structures for which sociologist see that social action is governed by; collaboration (a climate by which people on a group actively assist one another in their task), trust (a trusting climate), and innovativeness (a climate that is tolerant of failure and within which information freely flows). Within a mission climate it is expected that these indicator variables of an

organisational climate are stronger than within in a home-stay climate.

Hypothesis 3a: The organisational climate of a home-stay environment, characterized by collaboration, trust and innovativeness does not moderate the relationship between military culture and the willingness to share knowledge

Hypothesis 3b: Organisational climate of a mission environment, characterized by collaboration, trust and innovativeness negatively moderates (diminishes) the negative relationship between military culture and the willingness to share knowledge

2.5.1 Perceived level of collaboration

Hurley & Hunt (1998) define collaboration as the degree to which people on a group actively assist one another in their task. A collaborative workplace influences knowledge management as it allows for increased levels of knowledge exchange, which is a prerequisite for

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teams by eliminating common barriers to knowledge exchange (Lee & Choi, 2003). In a mission climate, employees live and work at the same place. The ease of communication, survival and dependency factor is expected to have an increased impact on the perceived level of collaboration compared to a home-stay climate. Because collaboration tightens individual differences, it can help to shape a shared understanding about the environment through supportive and reflective communication (Fahey & Prusak, 1998) and consequently resulting in increased knowledge creation activities. Also, the dependency and survival factor of a mission climate results in a more group-based incentive to collaborate as pré-described in paragraph 2.2 with the stewardship theory of management. Prior studies have examined the influence of group-based incentives and found positive results on knowledge sharing compared to those that examined individual incentives (Quigley, Resluk, Locke, & Bartol, 2007; Taylor, 2006). This claim is supported by Ferrin & Dirks (2003) who found that a cooperative reward system positively affected information sharing between partners whereas a competitive system had the opposite effect. Collective responsibility senses lead employees to go to great lengths to avoid letting colleagues down, frequently offering help to each other, even if it burdens their own work (Majchrzak & Wang, 1996). In other words, the mission climate is expected overcome cultural barriers if employees in a group actively assist one another in their task with the sense of collective responsibility and group-based incentive.

2.5.2 Perceived level of trust

As mentioned earlier, the success of knowledge sharing is dependent on the level of trust and dependency between employees (Ali, Pascoe & Warne, 2002). The definition of trust most researchers agree on can be summarized as the willingness to be vulnerable based on positive expectations about the actions of others (Fukyama, 1995; Riegelsberger, Stasse & McCarthy,

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2003). A climate that emphasizes trust has been found to help alleviate the negative effect of perceived costs on sharing (Kankanhalli, Tan, & Wei, 2005). It serves to overcome the public good dilemma associated with knowledge sharing (Bock et al., 2005) and facilitates open and influential knowledge exchange (Abram et al., 2003; Lin, 2006; Nahapiet & Goshal, 1998; O’Dell & Grayson, 1999) When team relationships have a high level of mutual trust, members are more willing to engage in knowledge exchange (Mayer, Davis & Schoorman, 1995; Nahapiet & Goshal 1998; Shapiro, 1987). Although Robbins (1998) warns that trust take a long time to build and can easily be destroyed it is expected that the mission climate accelerates the need for perceived trust and that the high level of interaction, dependency factor influences this perceived level of trust amongst employees compared to a home-stay environment.

2.5.3 Perceived level of innovativeness

A climate that encourages new ideas and is focused on learning from failure was found to be positively related to effective knowledge sharing (Taylor & Wright, 2004). Innovativeness reflects the perception that change and creativity are actively encouraged and rewarded, that learning is emphasized, that information flows openly and that risk-taking is reasonable (Bock et al., 2005). When military employees are on a mission; they do not wear formal ranks on the battlefield, the hierarchical structure has been de-emphasized and the social context for

interaction is highly open. Prior research has shown that organisations with climates emphasizing on innovation are more likely to implement knowledge-management systems (Ruppel & Harrington, 2001). Although other research failed to find a significant relationship between knowledge sharing and a learning orientation, i.e. a climate focusing on learning and trying new approaches (Lee, Kim & Kim, 2006) for this study it is expected that the perceived

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level of innovativeness is higher between military employees in a mission climate compared to a home-stay climate.

A summary of the literature review and states hypotheses is illustrated in the conceptual model of this study;

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3. Data and Method

In this chapter the setup of the research is described. The 1st _{paragraph gives a description of}

the research and survey design. The 2nd paragraph describes the collection of data and the sampling technique. Paragraph 3 presents descriptive statistics of the collected data. The 4th paragraph contains the measurement of constructs and control variables. Paragraph 5

describes the reliability and validity and last, paragraph 6 describes the statistical strategy for analysing the collected data.

3.1 Research & Survey Design

The research philosophy for this research is positivism, because the emphasis lies on the prediction of outcomes, based on the conducted literature review and with the intention to manage these variables in the future. The roots of this philosophy lie in the law of cause and effect. Its structured methods are used to facilitate replication, resulting in generalizations (Saunders & Lewis, 2012). The approach fitting the study is deductive, because it involves the testing of theoretical hypotheses with the intention to explain a causal relationship between variables. Therefore, the research aim is explanatory in that the study wants to establish if there is a causal relationship between military culture and the willingness to share knowledge and its interaction with organisational identity and climate. With the attachments of

quantitative values to the variables they can be subjected to statistical tests in order to get a clear understanding about their relationship with each other. Quantitative survey-based

research taps into the features of an organization’s climate whereas qualitative research delves into the nature of an organisation’s culture (Bock et al., 2005).

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The intended structured collection of data from a sizeable population for this study requires a survey strategy in the form of a questionnaire. Using a survey allows for a large collection of data from a large amount of people in an effective manner and can generate findings that are representative for the whole population (Saunders & Lewis, 2012). The time horizon for this study is cross-sectional as it only looks at a particular phenomenon, the willingness to share knowledge, at a particular time. It is a snapshot of the current situation. With the intention to identify differences in the interacting effect between the organisational climate of a home-stay environment and a mission environment, two questionnaires were developed based on prior research constructs and pré-tested before formal data collection. To avoid missing responses and have more coding and distribution flexibility, the electronic questionnaire was preferred above a paper response method (Boyer et al., 2001). Qualtrics online survey platform was used to build two structured online questionnaires (Appendix A & B) with a few open and mostly closed questions. In order to save time for respondents to fill in the questionnaire and to increase the response rate a Likert-type scale was used (Jamieson, 2004). The use of a Likert scale provides ordinal data which is desirable for a several types of analysis (ANOVA, interaction, regression).

The respondents that I invited to participate are colleagues which I have worked with during my career in the Royal Netherlands Navy. I expected that the personalized tactics for e-mail survey would positively influence the response rate (Joinson, Woodley, & Reips, 2007). The distributed e-mail (Appendix C) began with information about the purpose of the survey and secondly an example was given of how to fill in the questionnaire. Since all the respondents are Dutch service members and the construct items are English, the questionnaire was translated from English to Dutch and vice versa to avoid idiosyncratic, syntax and

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grammatical errors (Hofstede, 1980; Adler, 1983). The questionnaire was pré-tested by five service members and small corrections were made on their feedback to improve the

understanding of the questions. In order to reassure the understanding of the purpose and fill in procedure of the questionnaire, the questionnaire itself contained general instructions, sub instruction per section and assurance of anonymous recording and processing of responses (Appendix A & B). Voluntarily and anonymity participation was guaranteed using an

untracked hyperlink. Respondents were unable to complete the questionnaire more than once, because it was blocked by set up configurations in the electronic questionnaire. This was done to secure validity and reliability of the survey. Two weeks after the initial e-mail, one follow-up e-mail (Appendix D) was sent in the third week to stimulate participation (Yu & Cooper, 1983). Besides the hyperlink to the survey, the follow-up e-mail also contained a QR-code to the survey. This QR-code could be scanned by a smartphone with a QR-scanner app.

Scanning the code would immediately direct the respondent to the online survey. Unfamiliar with the use of QR code and the feedback of a participant after the initial e-mail was sent, let me to include the code in the follow-up e-mail.

Several control variables were included in the research model to account for differences between respondents. The level of education, working experience, rank and age, were

included because Constant et al. (1994) found the employees with a higher level of education and longer work experience were more likely to share their experience and have a positive attitude towards knowledge sharing. Because the military is well-known for being a men’s world and there might be individual competition between military services, a gender and military service control variable was added. Gender will be used as a describing statistic to give insight in the distribution male/female. The final control variable that has been added to

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the research is mission experience. To answer the questions concerning a mission climate, service members need to have experience from prior deployments. This variable also controls for validity of the research.

3.2 Data collection & Sampling Technique

A non-probability (quota) sample was used for the collection of primary data through the quantitative survey. Two questionnaires were developed based on various research literature and constructs together with two respondents lists. One for each questionnaire containing at least 50 non-commissioned officers (NCO’s) and 50 officers with an equal internal service distribution between the Navy and the Marines. This sampling technique of calculating quotas within the subgroups was chosen to increase the representativeness of collected data and because measures should be obtained from multiple types of respondents to avoid problems of common method bias (Argote, Fahrenkopf, 2016).

The population for this study is formed by military personnel of the Royal Netherlands Navy. In order to specify the factors relating to military culture and mission climate, a substantial number of service years is required. The sample will therefore only consist of

non-commissioned officers (NCO’s) from the rank of corporal and officers. Because of the career possibility for NCO’s to become an officer, the junior officer rank of lieutenant was included. The collection of representable data will be ensured by the inclusion of several control

variables that ensure mission and working experience. As of March 2018, the total population of the Royal Netherlands Navy consist of 7.510 military personnel1_{. From this 7.510, an}

estimated 4.000 men and women fall within the specified criteria for this study.

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A rough rule of thumb within pragmatic limit of respondents’ time availability claims that having a hundred respondents (N=100), represents a sample size that is adequate. N=200, would represent a sample size that is good, and a sample size of N=400+ is seen as great. The sufficiency of sample size for performing quantitative analysis is reached by the following criteria (Green, 1991);

- To test the overall model a, the following formula for determining a sufficient sample size should be used: 50 + k. K is the number of predictors.

- To test the individual predictors within the model, the following formula for determining a sufficient sample size should be used: 105 + k.

- The sample size should be at least 10 times larger than the number of variables being studied.

With the current conceptual model of one dependant variable (willingness to share

knowledge) and roughly seven independent variables (knowledge is power belief, position insecurity, lack of management support, organisational identity and 3 indicator variables to measure organisational climate) the sample size should be at least 80. This number also falls within the 50 + k formula, which resulted in 58 samples. In order to test individual predictors, the sample should be 105 + k which results in a required number of 113 samples.

The survey was carried out from April 23, 2018 until May 18, 2018. The initial e-mail (Appendix C) was sent to 313 respondents. 156 respondents were sent the hyperlink for the questionnaire containing questions about mission climate (Knowledge Sharing in a Military

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Organisation A) and 157 respondents were sent the hyperlink for the questionnaire containing questions about the home-stay climate (Knowledge Sharing in a Military Organisation B). The questions about willingness to share knowledge, military culture and organisational identity maintained the same in both questionnaires. The initial invitation resulted in 126 respondents equally divided over both questionnaires. A reminder (Appendix D) was sent on May 7th. Sending the reminder, with the possibility of also using a QR-code to fill in the survey, led to 48 additional respondents. 22 of those respondents made use of the QR-code to fill in the survey which represents 46% of the additional respondents. A total number (N) of 174 recorded responses were acquired. 18 responses were deleted for not completing the survey. These respondents only fill in the first 5 till 20 items and were deleted to increase reliability. An additional 2 responses were deleted for not having mission experience. These respondents filled in the questionnaire about mission climate without the required experience to give reliable judgement. Therefore, the total amount of respondents and recorded responses is (N) 154, almost equally divided over both questionnaires (80 by 74 responses). This leads to a response rate of 49,2%. According to the conceptual model and the sufficiency

requirements of Green (1991), this is enough to perform statistical quantitative analyses.

3.3 Descriptive statistics

The control variables that are claimed to have an impact on the positive attitude towards knowledge sharing is age, working experience and level of education. The higher the education is, the longer the working experience is and the older the age of employees is, the more likely it is that they will have positive attitudes towards knowledge sharing (Constant et al, 1994). Table 1 shows the descriptive statistics about the respondents work experience and age. The average age for respondents is 42 and the average working experience is nearly 22

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years. Table 2 shows the frequencies of education level within the survey sample. 98 respondents, which represents almost 64% of the total, have a relatively high level of education (HAVO, VWO, HBO, WO).

Table 1: Descriptive Statistics of Work Experience and Age

N Minimum Maximum Mean Std. Deviation Work Experience 154 5 38 21,58 9,009 Age 154 25 57 41,75 8,306 Valid N (listwise) 154

Table 2: Frequency statistics of Education level

Frequency Percent Valid Percent

Cumulative Percent Valid VMBO ₅ _3,2 _3,2 _3,2 MAVO 20 13,0 13,0 16,2 HAVO 12 7,8 7,8 24,0 VWO 8 5,2 5,2 29,2 MBO 31 20,1 20,1 49,4 HBO 36 23,4 23,4 72,7 WO 42 27,3 27,3 100,0 Total 154 100,0 100,0

The dispersion of respondents between military services are respectively stable (60% by 40% distributed), representing 92 Marines and 62 Navy responses. The dispersion between men and women is one to mention. Of the 154 respondents, there are 16 women (10%) and 138 men (90%). This dispersion is a representative sample of the Royal Navy. Of the 7.510 military personnel in the Navy by March 2018, 773 (10,3%) are women and 6.737 (89,7) are men2.

Table 3 represents the mission experience of respondents. Although there are 5 respondents with no mission experience, they all have sufficient years of working experience (minimum of

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5) to answer the questions about a home-stay climate. Two other responses of respondents with no mission experience were deleted, because they filled in the questionnaire about mission climate without the required experience.

Table 3: Frequency statistics of Mission Experience

Frequency Percent Valid Percent

Cumulative Percent Valid No 9 5,8 5,8 5,8 Yes, 1x 25 16,2 16,2 22,1 Yes, 2x 38 24,7 24,7 46,8 Yes, 3x 30 19,5 19,5 66,2 Yes, more than 3x 52 33,8 33,8 100,0 Total 154 100,0 100,0

3.4 Measurement of constructs

The used constructs for the questionnaires are introduced in this paragraph. All constructs were derived from previous validated constructs and marginally adopted to fit the

circumstances of this research.

The conceptual model contains 8 constructs: willingness to share knowledge, knowledge is power belief, position insecurity, lack of organisational support, organisational identity, perceived level of collaboration, perceived level of trust and perceived level of

innovativeness. All the constructs consisted of 3 to 7 items that were presented as statements throughout the questionnaires (Appendix A & B). Answering the questions was done by using a 7-point Likert-scale (Allen & Seaman, 2007, Brown 2011) ranging from 1= entirely agree, 2= agree, 3= somewhat agree, 4=neither agree nor disagree, 5=tend to disagree, 6= disagree, 7= entirely disagree. Preston & Colman (2000) & Lim (2008) claimed that high granularity (i.e. 7, 9 or 10 number of scale points) is more reliable and preferred by users. The larger spectrum of choices offers more independence to a respondent to pick the “exact” one rather

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than to pick the closest option (Dawes, 2008). Also, using a 7-point scale reveals more description about the motif and thus appeals practically to the “faculty of reason” of the respondents (Cox, 1980, Chang, 1994). Recent research concerning span of immediate memory supports this accuracy of response scale options around seven, as human mind has span of absolute judgement that can distinguish 7 categories at a time (Carifio & Perla, 2007). The inclusion of an undecided midpoint option was done to decrease the error in survey data. Respondents who do not have knowledge on the subject and do not have the midpoint option, would choose one side or the other, therefore increasing the survey data error (Converse, 1970). Because all the respondents speak and read Dutch as their native language, every item was translated in Dutch followed by a back-translation in English (Appendix D). The

questionnaires were pré-tested by 5 service members and commented on the questions and translations. Small corrections were made to prevent misinterpretations of the questions.

For measuring the dependent variable, the willingness to share knowledge, the 5 items of Bock, Lee & Zmud (2005) were used. Their research showed a high composite reliability (0.918) and Cronbach Alpha (0.832). Their study aimed to develop an integrative

understanding of the factors supporting or inhibiting individuals’ knowledge sharing

intentions. They adopted the theory of reasoned action (TRA) as their theoretical framework.

Based on the literature review in the previous chapter, 3 indicators were identified for measuring the independent variable of military culture. To measure the construct of

knowledge is power belief, the 5 greed items of Lu et al (2006) were adopted. Although the

effects of greed are well known within the literature (Brewer & Kramer, 1986; Komorita & Parks, 1994) a scale wasn’t identified and therefore a five-item greed scale was developed for

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knowledge sharing. Their research in China showed a Cronbach Alpha of 0.81 and greed was found an individual factor that reduces knowledge sharing.

Position insecurity was measured by adopting the 7 items of Hellgren et al (1999) and

changing the word “job” for “position”. The items relate to the quantitative and qualitative dimensions of perceived loss of continuity in a job situation. Quantitative job insecurity (item 1-3) referred to concerns about the future existence of the present job and the qualitative job insecurity (item 4-7) referred to the perceived threats of impaired quality in the employment relationship. The internal consistency reliability was satisfactory for both quantitative (Cronbach Alpha 0.75) and qualitative job insecurity (Cronbach Alpha = 0.79).

Organisational support was measured by adopting the items of Lin (2006). This study was

conducted in Taiwan and aimed to develop a research model examining how organisational support influences the intention to facilitate knowledge sharing. Confirmatory factor analysis was done to examine the validity of the measurement model.

To measure the interacting variable of organisational identification the 5 items of Fombelle et al. (2012) were used. Their research showed that that customer perception of identity synergy positively relates to identification with an organisation. Organisational identification was defined as a specific form of social identity in which a person’s identity is defined in terms of membership in an organisation. Their research showed a Cronbach Alpha of 0.91

The conceptual model of this research contains a second-order interacting variable

(Organisational Climate). This second-order construct is created by using the factor scores for the first-order constructs (Chin et al., 2003; Wold, 1989). Given that the focus of this study lies with quantitatively assessing individuals’ perceptions of their organisational context, I

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follow Dennis’s (1996) ideas as referred to salient institutional structures as organisational climate. Three organisational climate dimensions were used as indicators (Chin & Gopal, 1995) to create the superordinate organisational climate construct. Two out of the three indicators were adopted from Bock, Lee & Zmud (2005). These are the 4 items construct of

collaboration and 3 items construct of innovativeness. The two organisational climate

indicators were believed and found to influence individuals’ knowledge sharing intention. Their constructs showed a composite reliability of 0.898 and 0.874 and a Cronbach Alpha of 0.829 and 0.836. The 3rd indicator construct of trust consists of 7 items that were adopted from Lu et al. (2006). The trust construct in this research focusses primarily on confidence in the ability of others and faith in their positive intention. The items were adopted from prior research of Cook & Wall (1980) and demonstrated a Cronbach Alpha of 0.84.

3.5 Reliability & Validity

To ensure the internal reliability of items from individual constructs, Cronbach’s Alpha (CA) analyses were performed. Cronbach’s Alpha represents the estimator of the internal

consistency of items within the construct. The test verifies whether all the items per construct contribute to its measurement and shows whether an item should be removed to improve internal consistency. A threshold of 0,7 assures sufficient internal reliability (Carmines & Zeller, 1979; Nunnally & Bernstein, 1994). Rule of thum for justifying the remove of an item within the construct is when the internal reliability is below 0,7 or the corrected-item

correlation is below 0,3 The internal-correlation of items indicate whether the score of items correlate with the total score of the scale.

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The initial reliability analysis of the knowledge is power construct resulted in a CA of 0,55. Item 1 showed little correlation (<0,3) with the other items. Looking at the descriptive

statistics in table 4, item 1 is normally distributed (skewness and kurtosis is between -1 and 1) and shows a substantially different mean compared to all the other items.

Item 1 specifically questions the knowledge is power belief. Interpreting table 4, the belief is present, but it is not enough to hoard knowledge. Item 1 was removed from the construct but used for further statistical analysis as an individual construct “Knowledge is power belief”. The remaining construct of 4 items is labelled as; “Sharing Knowledge as a loss of personal Competitive Advantage belief”. The secondary reliability analysis of the remaining 4 items showed a CA of 0,597. Item 3 showed insufficient correlation with a score of 0,257. Removal of item 3 resulted in an increase in reliability up to 0,631. The remaining items showed sufficient correlation and no further reliability improvements could be made. Although the construct showed insufficient reliability (<0,7 (Chin, 1998)), it was taken for granted for further analyses.

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The reliability analysis of the position insecurity construct showed a CA of 0,32. None of the internal items showed sufficient correlation. Table 5 shows the descriptive statistics of the construct.

Interpretation of table 4 shows that item 1 and 4 appear to be related as they show similar means and the questions concern leaving the current position. The score is below average (4) which indicates that employees don’t mind leaving their current job position. On the other hand, item 2 and 5 show a score above average and concern future career opportunities and a stimulating job content in the near future. These results indicate that employees feel insecure about their future position. For this reason, the construct should be split up between a

construct of “Current Position Insecurity” and “Future Position Insecurity”. Item 3 shows a score near average and was removed from the construct. Item 5 questions the belief of personal use for the organisation and is interpreted as unrelated to position insecurity. The same accounts for item 7 as the military (public organisation) has standardized wages and the score is slightly below average. A 2nd and 3rd reliability analysis was conducted on the

constructs of “Current position insecurity”, which showed a CA of 0,58 with the items internally correlated, and “Future position insecurity”, which showed a CA of 0,71.

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The lack of management support construct showed an initial CA of 0,69. Item 5 showed insufficient correlation with the scale (0,271) and removal increased CA to a consistent level of 0,71. After removal of item 5, a secondary reliability analysis was performed and showed that item 4 was slightly uncorrelated (0,291) and the removal showed an increase of CA >0,05. The removal of item 4 resulted in a third reliability analysis with a CA of 0,76.

Table 6 presents the descriptive statistics of item 4 and 5. Interpretation of these items show that employees experience no reward system for knowledge sharing (mean 2,53) which indicates a lack of management support, but they do make use of knowledge networks in order to communicate with colleagues (mean 5,08), which indicates management support.

The construct of willingness to share knowledge showed a CA of 0,70. Although sufficient, item 1 (“Mijn kennisdeling met collega’s is goed”) presented a corrected item-total

correlation of 0,293 which is below <0,3 and was therefore removed from the construct. The secondary reliability analysis showed a CA of 0,72. The definition and interpretation of what “good” knowledge sharing is might have caused this inconsistency.

The trust construct in a mission climate presented an initial CA of 0,62 with item 3

(“Wanneer ik op missie ben is het goed overweg kunnen met de meeste collega’s op de lange termijn belangrijk voor mijn verdere carriere ontwikkeling”) insufficiently correlated (0,197). Removal showed an increased CA of 0,66. Item 1 (“Wanneer ik op missie ben geloof ik dat ik

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de hulp die ik geef aan collega’s in de toekomst terug kan verwachten”) presented a corrected item-total correlation score of 0,268 in the secondary reliability analysis and was also

removed from the construct. A third reliability analysis showed a CA of 0,66. Although all the items were correlated, the removal of item 7 (“Wanneer ik op missie ben zijn de meeste conflicten tussen collega’s in de organisatie eerder werk gerelateerd dan persoonlijke conflicten”) resulted in an increase of CA to 0,69. Because the threshold level of 0,7 hasn’t been reached, the item was removed. A fourth reliability analysis showed that the removal of item 2 (“Wanneer ik op missie ben voelen mijn collega’s als persoonlijke vrienden”) an increase of CA to a sufficient level of 0,74. Table 7 shows the descriptive statistics of the removed construct items. All the items present a positive score (> 4) towards trust in a mission climate. Item 3 and 1 are more concerned about the future trusting relationship with employees than the current one in a mission climate hiwch is temporal. Removal of the items seems therefore logical. Item 7 and 2 are more related to how employees interpreted conflicts between each other and how they see each other, than the actual trust they have in each other. Removal of the items might be explained by this reasoning.

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Innovation in a mission climate showed an initial CA of 0,70. All the items showed enough correlation, but the removal of item 2 (“Wanneer ik op missie ben hecht mijn organisatie veel waarde aan het nemen van risico’s, ook als dit niet direct tot succes leidt”) could increase CA to 0,77. Because the increase is >0,05, the item was removed from the construct. Interpreting the item is seems logical that in a mission climate, where life dependency is at stake, there is a lower acceptability level of taking risks. The descriptive statistics of the removed item in table 8 supports this as the item shows a rather average score of 3,89

The final construct that showed inconsistency in the reliability analysis is the trust construct in a home-stay climate. Reliability analysis showed a CA of 0,75, but item 7 (“Wanneer ik niet operationeel geplaatst ben zijn de meeste conflicten tussen collega’s in de organisatie eerder werk gerelateerd dan persoonlijke conflicten”) was insufficiently correlated with a corrected total-item correlation score of 0,066. Removal of the item increased CA to a level of 0,79.

The external validity of the research is sufficient, byt not very high as the number of

respondents is 154. The sample is between adequate (N=100) and good (N=200) for statistical analysis (Green, 1991). By using validated existing scales construct validity has been taken into account and likely to be high within this research. The internal validity of the research is increased with the inclusion of control variables.

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3.6 Data analysis and method

The data from the recorded responses (N=154) was imported in the Statistical Software Package for Social Sciences (IBM SPSS v. 24) and prepared for statistical analyses. First, nine reversed items were recoded. One item from the construct of willingness to share knowledge (“Mijn kennisdeling met collega’s is nadelig voor mij”), three items from the construct of position insecurity (“Mijn toekomstige carriere kansen in deze organisatie zijn gunstig”, “De organisatie kan mij van een stimulerende functie-inhoud voorzien in de nabije toekomst”, “Mijn salarisontwikkeling binnen deze organisatie is veelbelovend”), all the five items of management support, because it measured management support and not the lack of it and finally one item(s) within the construct(s) of willingness to share knowledge in a

mission/home-stay climate (“wanneer ik op missie ben is kennisdeling met collega’s nadelig voor mij / wanneer ik niet-operationeel geplaatst ben is kennisdeling met collega’s nadelig voor mij”). These items were included to avoid the risk of acquiescence response bias (Toner, 1987). Acquiescence bias refers to the respondents’ tendency to agree with statements rather than disagree. When the responses are distorted by this bias, the chances of type II error (missing an existing significant effect) increase (Podsakoff, MacKenzie, Lee & Podsakoff, 2003).

Secondly, the Cronbach Alpha’s were calculated for the variables in the model. A Cronbach’s Alpha score of >0,7 indicates a high level of internal consistency which enables the merger of items to one scale. The 3rd_{step in preparing the data for analysis was the creation of these one}

scale items with the function “compute variable” within SPSS. 4th, a correlation test was executed to check for correlation between variables. The following subdivision is used within this research: A weak positive relationship represent a score of r = <0,4. A moderately

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positive relationship is applied with scores between r = 0,4 and r = 0,7. A strong positive relationship reflects a score of r = >0,7.

In order to gain insight in the extent that the willingness to share knowledge (dependent variable) is explained by the predictor (independent) variables, multiple regression analyses were conducted at the final 5th step. These regression analyses tested the hypothesized direct and indirect relationships of the conceptual model. Testing the direct relationships required two steps. First, the control variables were inserted to control for rank, work experience, age, education level, service and gender. Second, the hypothesized antecedents were independently included to test for isolated direct effects. Multiple hierarchical regression analyses allow for effect testing of hypotheses and simultaneously for controlling other independent variables within the model (Cohen et al, 2013). The hypothesized moderators (indirect relationships) of organisational identity and organisational climate were tested by entry of one moderator per multiple hierarchical regression once the direct effect has been confirmed. This method measures the increased difference in explained variance of the willingness to share

knowledge. These bootstrapped multiple hierarchical regressions were executed by the using the PROCESS-marco volume 3 for SPSS from Hayes (2018).

How organisational climate and identity can overcome cultural barriers towards the willingness of knowledge sharing in a military organisation

Master Thesis