“What is the relationship between personality traits of the Five-Factor Model and the process of sensing and seizing opportunities, and reconfiguration?”

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“What is the relationship between personality traits of the

Five-Factor Model and the process of sensing and seizing opportunities,

and reconfiguration?”

Student: Michel Büchner – 10278656 Final: 25-11-2013

Supervisor: Dr. Dipl. –Wirt. –Ing. S. Kortmann

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Abstract

Dynamic capabilities are being recognized as a source of sustained competitive advantage. However, there is critique in regard to this area of research. For instance that it lacks foundation and a clear definition of constructs. Without this, the dynamic capability view might remain a label without coherence.

Literature shows that dynamic capabilities can be built over time and consists of

microfoundations such as organizational structure and knowledge sharing mechanisms. It is being acknowledged that within this process, the individual plays a role. Study points out that personality traits impact the process of dynamic capability building. This study argues that the individual is an important microfoundation in order to build dynamic capabilities. To test this, empirical study has been done to the relationship between personality traits and dynamic capability building. The five-factor model has been used to explain personality.

Based on the results, there are signs that personality traits impacts the process. Openness to new experience is being identified as the most important positive driver and can be enforced or diluted by other traits, especially in the last stage. Agreeableness is being recognized as the most important negative driver. It is also explicated that gender and educational level have a relationship with dynamic capability building. The results provide contributions to both practice and theory, as well as avenues for future research.

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Acknowledgements

I would like to gratefully and sincerely thank Dr. Dipl. –Wirt. –Ing. S. Kortmann for his guidance and understanding. His constructive mentorship has led to new insights and ideas, and most important of all, motivation when needed. Every question was answered properly and feedback has been given in a serious manner and a coaching “kind of way”.

Also, I would like to thank Dr. A.H.B. de Hoogh for “keeping me sharp”, especially in regard to the quantitative part of this study.

My employer, Oxxio Nederland B.V. made it possible for me to do this study, which I am very thankful for. Above all, Jasper van Panhuis who took the initiative for arranging it. Furthermore, I would like to thank my wife Julia Driehuis for the support during the whole study in Master of Business Studies. She supported me every minute regardless the rush of her own study and work. At last I would like to thank my beautiful son, Tim Büchner, for the pleasant distraction after a day writing.

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1. Introduction

A critique on the resource based view is that it is based on a static market situation in a particular point of time and, this is being challenged in dynamic business environments (Eisenhardt & Martin, 2000). In reaction, the dynamic capability view has been developed. Dynamic capabilities are the drivers for sustaining competitive advantage in rapidly changing environments (Teece, 1997; Eisenhardt & Martin, 2000). For this study the definition of dynamic capabilities is understood as “the ability to integrate, build, and reconfigure internal and external competencies to address rapidly changing environments” (Teece, et al. 1997, p.516). These dynamic capabilities “enable business enterprises to create, deploy, and protect the intangible assets that support superior long-run business performance” (Teece, 2007, p.1319).

Several concepts have been developed for building dynamic capabilities and for this study Teece’s (2007) is leading. This concept consists of three stages. In the first stage opportunities need to be sensed in order to seize them in the second stage. The last and third stage is the reconfiguration phase in which the organization reconfigures and recombines assets and organizational structures.

These building blocks are based on microfoundations. Few general examples of

microfoundations are organizational processes, procedures and structures. Other research pointed out that also the individual plays a role in this process (Katkalo, et al. 2010; Hodgkinson & Healey, 2011; Rothaermel & Hess, 2007) . Hodgkinson and Healey (2011) point out that personality traits matters in the process of dynamic capability building and personality traits influence the way a person thinks and acts in specific manner (Wincent & Westenberg, 2005).

In order to get a better understanding of the relationship between personality traits and the process of dynamic capability building, the current study explicated the five-factor model (Costa & McCrae, 1992). This model has been developed over a few decades and classifies

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five main personality traits (McDougall 1932; Catell 1943, 1946, 1947, 1948;Borgotta 1964; Digman, 1990; Costa & McCrae, 1992; Bono & Judge, 2004). Costa and McCrae (1992) define the five factors as extraversion, agreeableness, conscientiousness, neuroticism and openness to new experience. These factors represent the basic dimensions of personality. A relationship between dynamic capability building and personality can be pointed out by various examples. For instance the personality trait of openness to a new experiences leads to innovative usage of IT applications, where neuroticism leads to the opposite. (Nov & Kuk, 2008). Another example is that anxiety might lead to less attention for new opportunities, and anxiety is an outcome of neuroticism (Hodgkinson & Healey, 2011; Digman, 1990).

The literature fragmentally shows a relationship between dynamic capability building and personality traits. However, little concrete research has been done to this relationship. According to Arend and Bromiley (2009), no explicit definition of dynamic capabilities has been developed so far and without more foundation the dynamic capability view will remain a label without coherence. Many concepts have been established and according to Arend and Bromiley (2009), the definition of what dynamic capabilities are, remain vague and unclear. Arend and Bromiley (2009) argue that the theory lacks of coherent foundation and that the practical implications are unclear. They describe four major problems with the dynamic capability view. First, it remains unclear what the added value is related to existing theories, second there is lack of coherent foundation, third, there is weak empirical support and at last, it is unclear what the practical implications are. In other words, there is a need for further research within the dynamic capabilities view (Teece, et al., 1997; Arend & Bromiley, 2009). In order to contribute to this field of research, the research questions as follows:

“What is the relationship between personality traits of the Five-Factor Model and the process of sensing and seizing opportunities, and reconfiguration?”

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The answer to the question will contribute to both practice and theory. This research will shed light on which traits affect the ability of dynamic capability building on individual level, which subsequently leads to an understanding for managers on which type of persons are needed per stage of dynamic capability building in order to sustain competitive advantage. From theoretical point of view this study contributes to further development of

microfoundations within the field of dynamic capability building.

2. Literature review

2.1 Development of dynamic capability view

According to Di Stefanio et al. (2009) in Helfat and Peteraf (2009), the three most influential definitions of dynamic capabilities are those from Teece (1997), Zollo and Winter (2002) and Eisenhardt and Martin, (2000). Eisenhardt and Martin, (2000, p.1107) state that “dynamic capabilities thus are the organizational and strategic routines by which firms achieve new resource configurations as markets, emerge, collide, split, evolve, and die”. In other words, it is the ability to alter resources in changing markets. Zollo and Winter (2002) see dynamic capabilities as a collective activity which is rooted in organizational learning in order to systematically generate and modify the operating routines of the organization.

According to Helfat and Peteraf (2009) the domain of dynamic capabilities is a broad and complex field of research. This has led to confusion and theoretical underpinnings and as Arend and Bromiley (2009) state, the dynamic capabilities view lacks coherent foundation. Despite the critics on the dynamic capability view, it has been a field of research for a few decades and as stated by Williamson (1999, p.1094) in Helfat and Peteraf (2009, p.92) “big ideas often take a long time to take on definition”.

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2.2 Building dynamic capabilities

The literature consist of various explications of dynamic capability building. For this study three types have been used to get more insight in the microfoundations of the process (Teece, 2007; Zollo & Winter; 2002; Cohen & Levinthal, 1990).

First the process in which internal knowledge and learning mechanisms drive dynamic

capability building. Zollo and Winter (2002) describe that dynamic capabilities are being built through experience accumulation then knowledge articulation and at last, knowledge

codification. Second, there is the theory of Cohen and Levinthal (1990) in which they state that external knowledge and the degree of absorptive capacity are main drivers. They describe that dynamic capabilities are being built through stages in which value of new external

knowledge is being recognized, then assimilated and at last, it is being applied to commercial ends.

The last type of process is the entrepreneurial version developed by Teece (2007). This entrepreneurial process also consists of three stages. For this study the entrepreneurial process is leading, since it is most recent. The theories of Zollo and Winter (2002) and Cohen & Levinthal (1991) are being used for better understanding of the role of the individual in sensing and seizing opportunities stages, and reconfiguration.

According to Zollo & Winter (2002) dynamic capabilities are being built through learning mechanisms which encourage the use of internal knowledge. This process leads to an evolution of operating routines (Zollo & Winter, 2002). In more detail, the requirements for the firm is that known procedures must be properly executed while on the other hand, the firm should seek for desirable changes. Second, in order to articulate knowledge, a group of

individuals should figure out which elements of organizational tasks work and which do not. This type of collective learning finds place when individuals express their beliefs and

opinions and challenge each other’s viewpoints (Argyris and Schon, 1978; Duncan and Weiss, 1979 in Zollo & Winter 2002, p.341). Sharing individual experiences and comparing

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opinions lead to an improved understanding and are important when articulating knowledge. The last phase concerns knowledge codification. The focus in this phase is on codifying knowledge in for instance manuals, blue prints and other process specific tools.

Cohen and Levinthal (1990) focus on the application of external knowledge. They state that the ability to build dynamic capabilities depends on the degree of “absorptive capacity”, which means to what extent is the firm capable of absorbing and exploiting new knowledge. This can be broken down into three steps, namely, recognize value of new information, assimilate new information and apply new information into commercial ends.

Both theories from Zollo and Winter (2002) and Cohen and Levinthal (1990) are related to the knowledge based view of Grant (1996). As Grant (1996, p376) writes, “the essence of

organizational capability is the integration of specialized knowledge”.

Teece (2007) wrote that building dynamic capabilities can be disaggregated into three blocks, which obviously are related to the three steps as described by Zollo & Winter (2002) and Cohen & Levinthal (1996).

The first block is sensing opportunities, which is about scanning the environment and is a learning and interpretive activity. Sensing opportunities can be seen as an exploration process for new possibilities in which new knowledge is being developed and experiences are being accumulated (March, 1991; Zollo and Winter, 2002; Katkalo et al., 2010). The second block, seizing opportunities, is about the ability of the firm to address opportunities through, for instance, a new product or process. The third and last block involves the reconfiguration of processes and routines and the ability to manage threats like imitation. In this phase

recombination will be achieved and selected routines will be retained in order to stay evolutionary fit (Katkalo et al. 2010).

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11 Figure 1: Building dynamic capabilities

Authors Stage 1 Stage 2 Stage 3

Teece (2007) Sensing opportunities

“scanning, creation, learning, and interpretetitive activity” (p.1322) Seizing opportunities “address opportunities through new products, processes, or services” (p.1326) Reconfiguration “reconfigure and recombine assets and organizational structures” (p. 1335) Zollo & Winter

(2002) Experience accumulation “central learning process by which operating routines have traditionally been thought to develop” (p.341) Knowledge articulation “process through which implicit knowledge is articulated through collective discussions, debriefing sessions, and performance evaluation process” (p.341) Knowledge codification “supporting mechanism for the entire knowledge evolution process in changing currently available routines” (p.342)

Cohen & Levinthal (1990) “Recognize value of new, external information,… (p.128) …Assimilate it… (p.128) and apply it to commercial ends “ (p.128)

2.3 Microfoundations of sensing, seizing and reconfiguring

2.3.1 Sensing opportunities

The stage of sensing opportunities has its foundations in the literature of entrepreneurship and the knowledge based view of the firm (Hodgkinson & Healey, 2011). With this foundation Zollo and Winter (2002) identify two types of routines. The first one is the known and learned routine which is executed for the purpose of enhancing profit. The second one is the search routine which is focused on finding new ways to execute routines. Cognitive and creative abilities of individuals, and also skills of scanning and recognizing opportunities are needed in this explorative stage. He or she should be able to receive information through, for instance, a professional or private network and information systems. Also, individuals should be able to recognize the value of new information (Teece, 2007; Cohen & Levinthal, 1990). In this stage

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of the process, innovative and creative skills and behaviors are necessary; the individual should be able to see opportunities (Cunningham & Lischeron, 1991).

Sensing is comparable with exploration and underlying elements are captured in terms such as search, variation, risk taking, experimentation, play, flexibility, discovery and innovation (March, 1991; Katkalo et al., 2010; Cunningham & Lischeron, 1991). In order to identify opportunities both the local and distant environment should be scanned and explained. The exploring individual must figure out how to see particular events, market developments and also technological developments. As pointed out by March (1991) the individual plays a role in the process of exploration and relates with the individual capability of learning. Higher rates of learning lead to a faster equilibrium between exploration and exploitation. For the organization it is necessary to create a culture of openness that encourage debate (O'Reilly & Tushman, 2008). Furthermore, an optimal trade-off between the exploration and exploitation stage is needed; in a particular point of time, a firm should move from the sensing stage to the seizing stage in order to profit from opportunities (March, 1991; Teece, 2007; Masini et al., 2004).

2.3.2 Seizing opportunities

When opportunities have been explored, they need to be seized. This exploitative stage is characterized by such things as refinement, choice, production, efficiency, selection, implementation and execution (March, 1991; Katkalo et al., 2010). Furthermore this stage has decision making high on the agenda.

According to Teece (2007), this stage consists of four main necessities, mainly on

organizational level. First a firm should be able to make the right decisions in regard to the business model and be able to act in a timely manner (Teece, 2007; O’Reilly & Tushman, 2008). Examples of business model functions are the articulation of a value proposition, identifying a market segment and formulating a competitive strategy (Chesbrough, 2010, p355). Second, the boundaries of the firm should be set correctly. In other words, decisions

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have to be made about scope and integration. Third, when a firm has to deal with platforms and complementary assets, they should be managed correctly. At last there are dangers of bias, delusion, deception and hubris when seizing opportunities. Teece (2007) writes that errors in decision making are not uncommon, especially in large organizations.

It is obvious that in this stage the decision making process is high on the agenda. In stages where decisions have to be made, at least the best information needs to be available

(Finkelstein et al. 2009). To get a hold of the best information, it is suggested the firm needs knowledge that support the decision making process. For this, the individual gets an important role (Zollo & Winter, 2002). The critical requirement for exploiting knowledge is the ability to interpret a stream of information and the effectiveness of the communication. As stressed by Zollo and Winter (2002), collective discussions, debriefing sessions and performance evaluation processes are examples of driving mechanisms. It can be argued that the more diverse the stream of opportunities, the higher the need for interpretation and adaptability. As March (1991) describes, the degree of knowledge integration relies on the possibility of explicating knowledge in for instance manuals and blue prints.

2.3.3 Reconfiguration

This stage is characterized by activities like redeveloping established routines in order to stay evolutionary fit (Teece, 2007). The foundation of reconfiguration lies within the area of organizational structure (Hodgkinson & Healey, 2011). According to Hodgkinson and Healey (2011), the driver is the ability of top management to “coordinate and execute strategic renewal” (Hodgkinson & Healey, 2011, p.1502). Also Teece (2007, p28) states that “top management leadership skills are required to sustain dynamic capabilities”. For example, a microfoundation of reconfiguration is achieving decentralized decision making in order to react quickly on market changes. Furthermore the management of cospecialization is needed for successful commercialization (Teece, 1986). Second, microfoundations for

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2007). These are essential when integrating know-how and create incentive designs around learning creation and knowledge sharing. Grant (1986, p375) quotes that “the primary role of the firm […]is the integration of knowledge”.

There is a risk of shirking and free riding in this stage (Teece, 2007). Especially when rules and routines are being reconfigured the chance of shirking and free riding rises. As pointed out by Alchian and Demsetz (1972), rules and monitoring is needed in order to manage the chance of shirking and free riding.

So far, it seems top management is the key party in driving reconfiguration, however as noted by Augier and Teece (2009), one of the biggest challenges for top management is to transform identities and motivations of individuals within the firm. As clarified by Zollo and Winter (2002), in order to develop new routines, individuals are required to codify their

understandings for instance in written tools. It can be argued that microfoundations in this stage lie deeper than knowledge management on an organizational or midlevel management. Codifying knowledge in order to create new routines requires cognitive effort of the

individual (Zollo & Winter, 2002). Furthermore it is suggested that in a phase of reconfiguration with changing rules and routines, adaptive capacity of the individual is required in order to succeed. At last it is arguable that an intrinsic motivated person is more willing to reconfigure and lowers the chance of shirking and free riding.

2.3.4 Personality and sensing, seizing and reconfiguring

The framework of Teece (2007) rests, like most traditional dynamic capability formations, on the conception that the strategist is a cognitive miser. However developments in theory show that cognitive limits, biases and bounded rationality can undermine the entrepreneurial process of sensing, seizing and reconfiguration (Hodgkinson & Healey, 2011 p.1501). It is obvious that in all stages the individual plays a role and that organizational capabilities reside in its human resources capabilities (Katkalo et al., 2010). It is argued by Katkalo et al. (2010) that if valuable, rare, inimitable and non-substitutable resources are being managed by

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incompetent individuals, it might lead to little benefit and it is arguable that this impacts the chance of sustaining competitive advantage. Individuals might even replace R&D activities according to Rothaermel and Hess (2007). Also Hodgkinson and Healey (2011) point out that personality traits matters and “personal traits are dispositional characteristics, meaning that they are relatively enduring preferences on a person’s part for thinking or acting in a specific manner” (Epstein & O’Brian, 1985 in Wincent & Westenberg, 2005 p273). In other words, a trait of an individual influences the way he or she thinks and acts and this impacts the process of dynamic capability building. For instance, when new opportunities arise and the point of seizing is reached, knowledge needs to be explicated and integrated, and according to Aguier and Teece (2009) no IT system can fulfill the process of integrating knowledge.

The literature consists of various specific examples that indicates that personal traits

predispose individuals’ behavior in different ways when certain situations occur (Tatcher & Perrewé 2002, in Nov & Kuk, 2008, p.2851). For instance, research of Lit, Tan, Hock-Hai and Tan (2006) shows that personality traits of extraversion and openness to experience have a positive impact on the organizations’ innovative usages of IT (Nov & Kuk, 2008). In contrary, neuroticism has a negative effect.

Personality traits can be seen as an important microfoundation in the process of dynamic capability building and in order to gain more insight in personality traits, a comprehensive model has been used. This model is being developed over a few decades and exploits five basic personality traits: the Five-Factor Model (Costa & McCrae, 1992).

2.4 Personality traits of Five-Factor Model

Since the early thirties researchers began to investigate the taxonomy of personality (Digman, 1990). Eventually it was Borgotta (1964) who found five stable factors which emerged as the basis for further research (Digman, 1990). These factors were described as “assertiveness, likeability, emotionality, intelligence and responsibility. At last, Costa & McCrae (1992,

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p653) assigned the five factors as extraversion, agreeableness, conscientiousness, neuroticism and openness to new experience.

The first factor to be described is Eysenck’s (1947) extraversion versus introversion (Digman, 1990). Characteristics associated with this factor include social adaptability, assertiveness, exvia, social activity, sociability and ambition, power, activity, positive emotionally and interpersonal involvement (Digman, 1990). People who score high on extraversion in the NEO Personal Inventory, are seeking excitement and social attention (Costa & McCrae, 1992). They are described as assertive, active, talkative, upbeat, energetic and optimistic (Bono & Judge, 2004). These individuals are concerned with others’ interests (de Hoogh et al., 2005).

The second dimension is agreeableness. Traits subjective to this dimension are conformity, likeability, corteria, paranoid disposition, friendly compliance, love, sociability, level of socialization (Digman, 1990). When people score high in this dimension they are most likely to be cooperative, trusting, gentle and kind (Graziano & Eisenberg, 1997 in Bono & Judge, 2004).

The third dimension is conscientiousness. When a person scores high on this dimension he or she is willing to be achieving, dependable, task interested, has a strong superego, is an

introversive thinker, is prudent, is impulsive and has self-control (Digman, 1990). Individuals who score high on conscientiousness have a strong sense of direction and work hard to achieve goals (Costa & McCrae, 1992). However, these individuals also have the tendency to be cautious and thoughtful (de Hoogh et al., 2005).

The fourth dimension of the Big Five Factor Model is neuroticism. These individuals focus on emotional control, anxiety, affection and can focus on negative emotions (Digman, 1990). These persons have the tendency to be defensive, insecure and emotional (de Hoogh et al., 2005). This is associated with a lack of self-confidence and they may experience emotional distress (Bono & Judge, 2004).

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The last and fifth dimension is openness to experience. When an individual scores high on this dimension he or she most likely focuses on inquisition of intellect and culture (Digman, 1990). These people also have a critical attitude towards societal values (de Hoogh et al., 2005). At last, these individuals tend to be creative and insightful and tend to have a flexible attitude and engage in divergent thinking (Digman, 1990).

3. Theoretical framework

The relationship between the personal traits of the five-factor model and the person’s ability for dynamic capability building is being researched in this study. More specifically, it is theorized that there is a relationship between extraversion, agreeableness, conscientiousness, neuroticism and openness to new experience, and the person’s ability of sensing and seizing opportunities, and reconfiguration.

3.1 Extraversion

Extroversive persons show characteristics such as social activity, assertiveness and social adaptability. Since personal networks might lead to sensing new opportunities, it is arguable that the social character of the extroversive person affects the ability to sense opportunities. Furthermore these people are seeking for excitement. Underlying elements of sensing opportunities are for example play, experimentation and risk-taking (March, 1991). All factors are nominated to lead to excitement.

Also a study of Wang and Yang (2007) pointed out that extroversion has a positive effect on the intention to share knowledge. This trait is furthermore positively related to the speed of information-processing as concluded by Sočan and Bucik (1998). Since the individual should be able to gain knowledge through for instance a professional network in this stage, it is arguable that extraversion has a positive effect on the ability of sensing opportunities. Also the information should be processed, filtered and translated into an opportunity (Cunningham

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& Lischeron, 1991). Speed of information-processing is a driver in the process of sensing opportunities and as March (1991) stated, the higher the learning rate, the earlier the equilibrium between exploration and exploitation finds place.

It is suggested that the social and excitement-seeking characteristics of the extroversive person in combination with the ability to process information and the intention to share knowledge, especially impacts the ability to sense opportunities. This leads to the following hypothesis:

H1: Extraversion is positively related to sensing opportunities.

3.2 Agreeableness

People with a high level of agreeableness show traits of conformity, sociability, a level of socialization and cooperation (Digman, 1990; Graziano & Eisenberg, 1997 in Bono & Judge, 2004). Trust, straightforwardness and modesty are also facets which are at the top end of this scale (Costa, Crae, & Dye, 1991). As stated by Zhao and Seibert (2006), a person with this personality trait has cooperative values. It can be argued that this cooperative characteristics lead to better collective discussion, which is a microfoundation especially during the seizing stage (Zollo & Winter, 2002). On the other hand, the confirmative characteristic of the

agreeable person might lead to less outspoken opinions during these discussions. As stated by Zhao & Seibert (2006), people in an entrepreneurial role score lower on agreeableness. They conclude that agreeable people are less able to make difficult decisions and may suffer in less predictable environments. This might lead to a disadvantage for agreeable people during the stage of seizing opportunities where several decision have to be made. Based on the

arguments found in the literature, the following hypothesis is being defined:

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3.3 Conscientiousness

Conscientious persons are impulsive, task interested and motivated to achieve. (Digman, 1990). As stated by Costa et al. (1991) these persons are also capable and sensible. The deliberated earth of a conscientious person leads to thoughtfulness and planning.

It is suggested that especially in a stage of reconfiguration, a person who is willing to achieve and fulfill their tasks is more motivated to adapt. Also study of Le Pine et al. (2000) shows that the trait of conscientiousness positively effects the individual ability to adapt.

It is argued that motivation of individuals is an important driver in this phase and research also pointed out that there is a relationship between free riding and personality (Nov & Kuk, 2008). Since conscientious people are willing to achieve, and as described by Zhao and

Seibert (2006), more dependable, it is indicated that they are more able to adapt. Therefore the following hypothesis is defined:

H3: Conscientiousness is positively related to the ability of reconfiguration

3.4 Neuroticism

Persons who score high on neuroticism are focused on affection and negative emotions (Digman, 1990). These people tend to be less self-confident and hostile (Zhao & Seibert, 2006). They are also described as anxious and vulnerable (Costa & McCrae, 1992). The sensing stage is being defined as explorative and has elements of risk taking and experimentation (March, 1991). It is suggested that anxiety leads to a lower ability of risk taking and thus a lower ability of sensing opportunities. These are being enforced by Hodgkinson and Healey (2011). They stressed that anxiety leads to less attention to new events and enforces the shield against new information that might lead to discomfort. This leads to the following hypothesis:

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3.5 Openness to new experience

People who are open to new experience are tend to seek new experiences and explore novel ideas. These people can be described as creative and innovative. This trait is also connected to intelligence (Zhao and Seibert, 2006). People with this trait also tend to have a flexible

attitude (Digman, 1990).

It is argued that especially in the phase of sensing opportunities these underlying elements match the experimentation and explorative characteristics of this stage since this type of persons are seeking for new ideas (Zhao & Seibert, 2006). Besides the explorative nature of this trait, Le Pine et al. (2000) show that the trait openness to experience positively affects the ability to adapt. This indicates that this type of person is also able to reconfigure since

adaptability is needed in this stage. These findings lead to two hypotheses:

H5a: Openness to new experiences is positively related to the ability of sensing opportunities H5b: Openness to new experiences is positively related to the ability of reconfiguration

Figure 2. Conceptual model

Ability to sense opportunities Ability to seize opportunties Ability to reconfigure Personality traits Extraversion, Agreeableness, Conscientiousness, Neuroticism, Openness to new Experience H1, H4, H5a H2 H3, H5b

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4. Methodology

4.1 Research design

For this empirical study hypotheses are tested through a quantitative research in which direct effects have been tested. The used technique composes a cross sectional survey in the form of an online questionnaire (Saunders & Lewis, 2012). The full questionnaire can be found in Appendix A.

This method of data collection is chosen due to its low cost and time effective character (Saunders & Lewis, 2012). Large groups of respondents can be reached without geographical dispersion and data entry can be automated. The disadvantages of lack of interaction with respondents and possibility to crash are accepted.

A self-administered Internet mediated questionnaire has been used for measuring the

independent, dependent and control variables. The selection of respondents has been executed through purposive and snowball sampling. The independent variables or predictor variables are the personality traits of the five-factor model and the dependent variables or outcome variables are sensing, seizing and reconfiguring.

4.2 Sample

The questionnaire has been distributed to 194 Dutch persons who were all employed and of which 173 persons were employed at a Dutch energy company. All persons received the questionnaire electronically and were being asked to distribute it within their own network as well. No reminders have been sent. From the 88 persons who started the questionnaire, 82 fully completed it. The response rate is being estimated at 47%.

59% of the respondents were males (n=49). Within this group most respondents were between 21 and 31 years old (42.8%). 22.4% was between 31 and 41 years, 24.4% between 41 and 51 years and at last 10.2% was between 51 and 61 years old. There is no report of male

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The modal class of organizational tenure among male respondents is 13 years or longer (42.9%). 8.2% had an organizational tenure of three years or shorter, 20.4% between four and seven years, 20.4% between seven and ten years, and 8.2% between ten years and thirteen years.

Most of the male respondents completed a master program at University (38.8%). 49% completed an educational program at university of applied sciences (MBO = 12.2% and HBO = 36.7%). 12.2% reported to have finished secondary or primary education.

41% of the respondents were females (n=34). Most female respondents were between 21 and 31 years old (50%). 29,4% was between 31 and 41 years, 11.7% between 41 and 51 years and at last 8.8% was between 51 and 61 years old. Also among the female respondents there is no report of age higher than 61.

The modal class of organizational tenure among female respondents is between four and seven years (29.4%). 11.7% had an organizational tenure of three years or shorter, 23.5% between seven and ten years, 11.7% between ten years and thirteen years, and 8.8% had a tenure higher than thirteen years.

The modal class of education among the female respondents also was university or higher (38.2%). 50% completed an educational program at university of applied sciences (MBO = 14.7% and HBO = 35.3%). 11.7% reported to have finished secondary or primary education. Taken all respondents together the modal class of age is between 21 and 31 (45.8%), second class is between 31 and 41 years with 25.3%, third class between 41 and 51 years (19.3%) and the maximum class between 51 and 61 (9.6%).

The modal class of organizational tenure is 13 years or longer and consisted of 34.9% of the respondents. Others were shorter than three years (9.6%), between four and seven years (24.1%), between seven and ten years (21.7%), and between ten and twelve years (9.6%).

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38.6% of the respondents reported a university degree or higher. 49.4% of the respondents have finished an educational program at university of applied science (MBO = 13.3% and HBO = 36.1%). 12% finished high school or primary education.

4.3 Measurement

4.3.1 Translation

The used items in the survey are derived from English studies. The respondents are Dutch persons and therefore the items have been translated to Dutch. This is done by translating the item into Dutch and then back translating them to English by a third person. A few corrections have been made in the final version.

4.3.2 Personality

To measure personality traits a 60-item NEO Five-Factor Inventory has been used. For each factor, twelve items were selected from the NEO Personality Inventory (Crae & Costa, 2003). The factors are measured using a five point Likert-scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Examples of items included are “I am no worrier” for neuroticism; “I like to have many people around me” for extraversion; “I do not like to waste my time with day dreaming” for openness to new experience; “I try to be gentle to everybody I meet” for agreeableness, and “I keep my things nice and clean” for conscientiousness.

4.3.3 Dynamic capability building

For measuring the process of sensing and seizing opportunities, and reconfiguration, six sets of items have been used, for each stage two sets. Some items were fully applicable for the questionnaire and some items have been transformed. An example is “We regularly apply technologies in new products” became “I regularly apply new methods in every day work”.

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Scanning the environment and recognizing the value of new information are factors that drives the ability to sense new opportunities (Teece, 2007; Cohen & Levinthal, 1990). In order to measure the scale of sensing the “environment exploration” (Cronbach’s α = .780) and “recognize” (Cronbach’s α = .960) scales have been used (Stumpf et al., 1983;

Lichtenthaler 2009). Those two consist of eleven items. Examples of items are “I thoroughly observe technological trends” and “to what extent have you behaved in the following ways over the last three months: initiated conversations with knowledgeable individuals in my career area” (Lichtenthaler, 2009; Stumpf et al., 1983). The items have been measured using a five point scale ranging from (1) little to (5) a great deal.

Seizing

This stage is characterized by decision making and the assimilation internal and external knowledge (Teece, 2007; Zollo & Winter, 2002; Cohen & Levinthal, 1990). In order to measure the scale of seizing opportunities, two sets of items have been used. The sets

“initiative” (Cronbach’s α = .820) and “assimilate” (Cronbach’s α = .810) consist of ten items in total (Berg & Velde, 2005; Lichtenthaler, 2009).

Examples of items are “How often do you make independent decisions about what you are going to do at work, that is, about the tasks or assignments you will perform?” and “I frequently acquire technologies from external sources” (Berg & Velde, 2005; Lichtenthaler, 2009). The items have been measured using a five point Likert scale ranging from (1) strongly disagree to (5) strongly agree.

Reconfigure

Application of knowledge and redeveloping routines are characterizing this stage (Teece, 2007; Cohen & Levinthal. 1990). In order to measure the scale reconfiguration, items from

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“transmute” (Cronbach’s α = .860) and “apply” (Cronbach’s α = .860) have been used (Lichtenthaler, 2009). In total, the sets consist of eight items.

An example is “We regularly apply technologies in new products”. The items have been measured using a five point Liker scale ranging from (1) strongly disagree to (5) strongly agree.

Control variables

The results have been controlled by four control variables. Gender, age, organizational tenure and level of education. These variables were collected at the end of the questionnaire.

4.4 Statistical procedure and data reliability

Data have been collected through an online survey. The first completed survey has been filled in on the 1st of October. On the 11th of October, the survey has been closed. Qualtrics has been used to setup the survey and to collect data. Results were exported to a SPSS document and statistical analyses have been performed by SPSS version 22.

The first step was to recode the items which needed to be recoded. This was only necessary for the five scales of the five-factor model. Secondly the reliability of data has been improved if necessary by excluding, step by step, items from scales which showed a cronbach’s alpha below .700. Reliability statistics after exclusion for the independent variables are as follows: extraversion α = .817, agreeableness α = .773, conscientiousness α = .820, neuroticism α = .819, and openness to new experiences α = .749 (one item excluded: Q1). For the dependent variables no items have been excluded. The reliability statistics are as follows: Sensing α = .892, Seizing α = .874, and Reconfiguring α = .858.

Results of skewness statistics show normal skewness for all items (between -0.88 and 0.71). Kurtosis statistics show positive kurtosis for openness (1.35) and reconfiguration (1.54).

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Negative kurtosis is shown for gender (-1.91) and organizational tenure (-1.40). Other kurtosis statistics show normal kurtosis (between -0.74 and 0.70).

Linear regression analyses were undertaken to test the hypotheses. Alpha levels of 0.10, 0.05 and 0.01 have been used in statistical procedures.

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27 T ab le 1 : M ea n s, Stan d ar d d ev iatio n , Sk ewn ess , Ku rto sis , C o rr elatio n s an d R eliab ilit ies V a ria b le s M SD S k e w n e s s K u rt o s is 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 1. G e n d e r ( 1 = m , 2 = f) 1 .4 1 0 .4 9 0 .3 7 -1 .9 1 2. A g e 2 .9 3 1 .0 2 0 .7 1 -0 .7 4 -0 .1 2 0 3. O rg a n iz a tio n a l Te n u re 3 .3 6 1 .4 2 -0 .1 2 -1 .4 0 -0 .1 8 1 .6 9 3 * * 4. E d u c a tio n 4 .0 0 1 .0 4 -0 .8 8 -0 .0 6 -0 .0 2 1 -0 .2 1 2 -0 .1 6 1 5. O p e n n e s s 2 2 .3 3 4 .3 4 0 .3 2 1 .3 5 -0 .1 4 4 -0 .1 0 1 -0 .0 9 5 .3 3 2 * * α= .7 49 6. C o n s c ie n tio u s n e s s 3 7 .5 9 4 .7 9 -0 .4 5 -0 .0 1 0 .0 4 7 0 .1 1 8 0 .0 8 8 -0 .0 6 5 0 .0 5 2 α= .8 2 7. E xt ra v e rs io n 2 6 .9 9 4 .2 5 -0 .1 1 0 .4 4 -0 .1 2 4 -0 .1 0 7 0 .0 9 4 0 .1 9 2 .3 0 1 * * .2 6 5 * α= .8 17 8. A g re e a b le n e s s 2 5 .0 2 3 .7 1 -0 .0 1 -0 .1 2 -0 .0 1 8 .2 7 8 * .3 5 8 * * 0 .1 4 3 -0 .0 5 9 0 .1 5 0 .2 4 7 * α= .7 73 9. N e u ro tic is m 1 4 .0 0 3 .7 4 0 .4 7 -0 .3 4 0 .0 4 4 -0 .0 4 6 -.2 8 3 * -0 .0 1 4 -.3 1 1 * * -.4 2 7 * * -.4 1 5 * * -.2 4 9 * α= .8 19 10. S e n s in g 3 3 .6 3 7 .5 2 -0 .1 7 -0 .2 5 -.2 5 0 * -0 .0 9 7 0 .0 2 6 0 .1 5 4 .5 6 9 * * 0 .1 7 2 .3 9 6 * * -.2 3 3 * -.2 7 8 * α= .8 92 11. S e iz in g 3 2 .0 6 6 .2 7 -0 .5 0 0 .7 0 -0 .1 6 4 -0 .1 4 3 -0 .0 6 8 .2 5 4 * .5 4 2 * * 0 .1 6 0 .3 5 3 * * -0 .1 8 9 -0 .2 1 5 .7 7 9 * * α= .8 74 12. R e c o n fig u rin g 2 7 .8 5 4 .5 3 -0 .5 9 1 .5 4 -0 .1 0 9 -0 .0 8 2 -0 .0 3 8 0 .0 2 5 .4 1 5 * * .2 5 5 * .3 0 1 * * -.3 0 8 * * -0 .1 9 1 .7 2 4 * * .7 7 5 * * α= .8 58 N o te : N = 8 2 , R e lia b ili tie s a re re p o rt e d a lo n g th e d ia g o n a l * C o rr e la tio n is s ig n ifi c a n t a t t h e 0 .0 5 le v e l ( 2 -t a ile d ) * * C o rr e la tio n is s ig n ifi c a n t a t t h e 0 .0 1 le v e l ( 2 -t a ile d )

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5. Results

5.1 Correlation analysis

An overview of descriptive statistics, correlations and reliabilities is shown in table 1. As shown, extraversion is positively correlated with sensing (p < 0.01, r = 0.396), seizing (p < 0.01, r = 0.353), and reconfiguring (p < 0.01; r = 0.301). Furthermore, extraversion has a negative correlation with neuroticism (p < 0.01, r = -0.415) and a positive relationship with agreeableness (p < 0.05, r = -0.249).

Agreeableness is a negatively related to sensing opportunities (p < 0.05) and reconfiguration (p < 0.01). The strongest negative correlation can be found with reconfiguration (r = -0.308). The scale of agreeableness appears to be the most normal distributed with a skewness statistic of -0.01 and a kurtosis statistic of -0.12. Furthermore table 1 shows that agreeableness is positively related to organizational tenure (p < 0.01, r = 0.358) and with age (p < 0.05, r = 0.278).

As shown in table 1, conscientiousness only has a correlation with reconfiguration which is significant (p < 0.05, r = 0.255).

Neuroticism is only correlated with sensing opportunities (p < 0.05, r = -0.278). There is also a negative relationship between organizational tenure and neuroticism (p < 0.05, r = -0.283) The strongest correlation can be found with openness to new experiences. As given in table 1, openness to new experience is significant positively related with all stages. The strongest correlation can be found with sensing opportunities (p < 0.01, r = 0.569), secondly with seizing opportunities (p < 0.01, r = 0.542) and at last with reconfiguration (p < 0.01, r = 0.415).

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Table 2: Results of personality traits as predictor for sensing, seizing and reconfiguring

Variable B SE B β B SE B β B SE B β Step 1 Gender (m=1, f=2) -3.741 1.688 -.248** -2.171 1.412 -0.170 -1.096 1.060 -0.119 Age -1.375 1.112 -0.188 -0.854 0.938 -0.139 -0.466 0.704 -0.105 Organizational Tenure 0.668 0.820 0.125 0.151 0.681 0.034 0.045 0.511 0.014 Education 0.959 0.819 0.131 1.400 0.689 0.226** 0.010 0.517 0.002 Step 2 Gender (m=1, f=2) -1.934 1.448 -0.130 -1.989 1.386 -0.156 -0.650 0.955 -0.071 Age -0.685 0.976 -0.095 -0.705 0.921 -0.114 -0.566 0.626 -0.128 Organizational Tenure 0.440 0.764 0.083 0.512 0.689 0.114 0.120 0.454 0.037 Education -0.531 0.727 -0.074 1.727 0.694 0.279** -0.546 0.484 -0.123 Agreeableness -0.278 0.135 -0.241** Conscientiousness 0.197 0.084 0.240**

Openness to new experiences 0.638 0.138 0.512*** 0.329 0.085 0.423***

Neuroticism -0.028 0.131 -0.024 Extraversion 0.226 0.129 0.186 Step 3 Gender (m=1, f=2) -3.646 1.584 -0.241** -1.021 1.286 -0.080 -0.351 0.932 -0.039 Age -1.318 1.044 -0.181 -0.699 0.897 -0.113 0.307 0.639 0.070 Organizational Tenure 1.254 0.795 0.234 0.218 0.675 0.049 0.107 0.485 0.034 Education 1.564 0.787 0.213* 0.370 0.646 0.060 0.240 0.462 0.055 Agreeableness -0.460 0.155 -0.339*** -0.382 0.092 -0.470*** Conscientiousness 0.334 0.140 0.249** 0.139 0.130 0.121

Openness to new experiences 0.501 0.121 0.468***

Neuroticism 0.053 0.129 0.054 -0.121 0.082 -0.171 Extraversion 0.169 0.116 0.163 0.262 0.085 0.357*** R² Step 1 Step 2 Step 3 ΔR² Step 2 - Step 1 ΔR² Step 3 - Step 1 Note: N=82. * p < 0.1, ** p < 0.05, *** p < 0.01 0.2694 Seizing Sensing Reconfiguring 0.2506 0.3512 0.2906 0.0477 0.2294 0.3967 0.2383 0.2932 0.1348 0.1505 0.2484

Sensing Seizing Reconfiguring

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5.2 Direct and interaction effects

Table 2 consists of results of the OLS regression analyses. Multicollinearity has been tested with variance inflation factors (VIF) and tolerance levels. For the analyses as presented in table 2 the maximum VIF is 2.432. The minimum tolerance level is 0.411. Step 1 contains the control variables, step 2 includes the hypothesized effects and step 3 presents other

personality traits as predictor variable.

As shown in step 2, openness to new experience has a positive relationship with sensing opportunities (β = 0.512, p < 0.01) which is related to hypothesis 5a. No significant

relationships between neuroticism and extraversion, and sensing opportunities can be found in step 2. This leads to acceptance of H5a and rejection of H1 and H4 (ΔR² = 0.2932).

H3 is being accepted. There are signs that agreeableness has a negative effect on seizing opportunities as shown in step 2 (β = -0.241, p < 0.05), (ΔR² = 0.0477). Also H3 and H5b are being accepted. Conscientiousness has a positive relation with reconfiguration (β = 0.240. p < 0.05) as well as openness to new experience (β = 0.423, p < 0.01), (ΔR² = 0.2294).

Gender and educational level show significant relationships as well. Presented in table 2 and tested in step 1, female respondents tend to have a lower ability of sensing opportunities (β = -0.248, p < 0.05). Education has a significant positive relationship with seizing opportunities (β = 0.226, p < 0.05), this is being enforced in combination with agreeableness (β = 0.279, p < 0.05). These findings trigger for further research and gender differences are presented later in this report. Due to a lack of respondents per educational level, no further research has been done to this effect.

In step 3, other relationships than hypothesized are being presented. As can be found, besides openness to new experience, also agreeableness and conscientiousness show relationships with sensing opportunities. Agreeableness has a negative relationship with sensing

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opportunities (β = 0.249, p < 0.05). The ΔR² in this step is 0.1348, which is lower than ΔR² in step 2 (0.2932).

Contrary to agreeableness, openness to new experience is positively related with seizing opportunities (β = 0.468, p < 0.01). Other traits do not show any relationships in this stage. The ΔR² is 0.2484. This is higher than the ΔR² in step 2 (0.0477). Also in the reconfiguration stage, agreeableness has a negative relationship (β = -0.470. p < 0.01). Extraversion is

positively related to the reconfiguration stage (β = 0.357, p < 0.01). The ΔR² for step 3 compared to step 1 is 0.2694. The variance in step 3 is slightly higher than the ΔR² in step 2 (0.2294).

Agreeableness shows a negative relationship with sensing, seizing and reconfiguring where openness to new experience shows a positive relationship. Conscientiousness only seems to be related with the sensing and reconfiguring stage, and neuroticism does not show any relationship with the stages at all. Extraversion only has a positive relationship with the reconfiguration stage.

Table 3: Results of effects within dependent variables

Variable B SE B β B SE B β B SE B β Step 1 Gender (m=1, f=2) -3.741 1.688 -0.248** -2.171 1.412 -0.170 -1.096 1.060 -0.119 Age -1.375 1.112 -0.188 -0.854 0.938 -0.139 -0.466 0.704 -0.105 Organizational Tenure 0.668 0.820 0.125 0.151 0.681 0.034 0.045 0.511 0.014 Education 0.959 0.819 0.131 1.400 0.689 0.226** 0.010 0.517 0.002 Step 2 Gender (m=1, f=2) -1.943 1.059 -0.129 -0.175 0.825 -0.014 0.592 0.653 0.064 Age -0.611 0.691 -0.084 -0.071 0.529 -0.012 0.142 0.421 0.032 Organizational Tenure 0.516 0.506 0.096 -0.116 0.388 -0.025 -0.109 0.309 -0.033 Education 0.145 0.541 0.020 1.068 0.393 0.172*** -0.778 0.315 -0.174** Sensing 0.343 0.080 0.405*** 0.193 0.067 0.317*** Seizing 0.590 0.137 0.500*** 0.419 0.079 0.583*** Reconfiguring 0.525 0.183 0.320*** 0.661 0.125 0.475*** R² Step 1 Step 2 ΔR² Step 2 - Step 1 Note: N=82. * p < 0.1, ** p < 0.05, *** p < 0.01 0.6279 0.6485 0.5636 0.1035 0.1028 0.0212 0.6670 0.7307 0.6697

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Table 3 presents the effects between the stages of sensing, seizing and reconfiguring. In step 1 the control variables are tested. In step 2 the effects between the stages is tested. The analyses as presented in table 3 are also tested on multicollinearity. The highest VIF is 2.962 and the lowest tolerance is 0.338.

Sensing is positively related to seizing (β = 0.500. p < 0.01) and reconfiguring (β = -0.320. p < 0.01). The ΔR² is 0.5636. Seizing is positively related to sensing (β = 0.405, p < 0.01) and reconfiguring (β = 0.475, p < 0.01). The ΔR² in this stage is 0.6279. At last reconfiguring is positively related to sensing (β = 0.317, p < 0.01) and seizing (β = 0.583, p < 0.01). The ΔR² in this stage is 0.6485. As presented the relationships between the stages are strong with a maximum variance of (ΔR²) 0.6485 in the last stage. All relationships are significant with a p-value below 0.01.

The results show that openness to new experience has a positive relation with all stages and it is investigated which traits moderates this effect. The details of the results can be found in Appendix B. As shown, in the sensing and seizing stage, no significant interaction effects can be found. When zooming in to the reconfiguration stage, agreeableness and extraversion appear to be related with openness to new experience. Agreeableness enforces the relationship with openness to new experience during reconfiguration (β = 0.185 p < 0.1), the ΔR² is

0.0321. Extraversion weakens the positive relationship with openness to new experience (β = -0.199 p < 0.1). The ΔR² = 0.0289.

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33 T ab le 5 : Me an s, Stan d ar d d ev iatio n s, Sk e wn ess , Ku rto sis C o rr elatio n s an d R eliab ilit ies o f th e m ale resp o n d en ts T ab le 4 : Me an s, Stan d ar d d ev iatio n s, Sk e wn ess , Ku rto sis C o rr elatio n s an d R eliab ilit ies o f th e fem ale resp o n d en ts V a ria b le s M SD S k e w n e s s K u rt o s is 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 1. G e n d e r m a le 1 .0 0 0 .0 0 0 .0 0 0 .0 0 2. A g e 3 .0 4 1 .0 6 0 .4 8 -1 .1 2 3. O rg a n iz a tio n a l Te n u re 3 .5 7 1 .4 3 -0 .3 7 -1 .3 2 .6 5 8 * * 4. E d u c a tio n 4 .0 4 1 .0 4 -1 .0 5 0 .5 5 -.3 3 6 * -0 .2 2 2 5. O p e n n e s s 3 3 .0 4 5 .2 1 0 .0 2 -0 .3 1 -.2 9 5 * -.4 0 7 * * .3 9 2 * * α= .8 57 6. C o n s c ie n tio u s n e s s 4 5 .1 5 6 .4 6 -0 .2 7 -0 .3 9 0 .1 5 1 0 .0 6 8 -0 .0 1 4 .3 0 9 * α= .7 94 7. E xt ra v e rs io n 4 2 .3 4 6 .0 3 0 .1 5 0 .0 1 -0 .1 8 2 -0 .0 0 3 0 .1 9 2 0 .1 2 9 .4 3 6 * * α= .7 07 8. A g re e a b le n e s s 3 9 .5 5 4 .5 9 -0 .1 8 -0 .2 5 0 .1 5 6 0 .2 4 3 0 .2 2 7 -0 .0 9 8 0 .0 9 2 0 .1 3 8 α= .7 06 9. N e u ro tic is m 2 7 .8 5 6 .8 5 0 .8 9 1 .1 5 0 .0 8 4 -0 .1 1 0 -0 .1 2 7 -.3 4 3 * -.4 8 0 * * -.4 8 0 * * -0 .0 8 0 α= .8 65 10. S e n s in g 3 5 .0 7 7 .3 9 -0 .0 6 -0 .5 2 -0 .2 4 4 -0 .0 6 7 0 .1 2 1 .4 7 6 * * .3 9 8 * * .4 4 9 * * -0 .1 5 8 -.4 3 0 * * α= .8 78 11. S e iz in g 3 2 .9 8 6 .2 7 -0 .2 1 -0 .4 9 -0 .2 1 2 -0 .1 0 1 0 .2 7 7 .4 4 4 * * .3 8 6 * * .3 8 1 * * -0 .1 4 0 -.3 2 7 * .7 7 3 * * α= .8 67 12. R e c o n fig u rin g 2 8 .3 0 4 .4 4 0 .0 9 0 .3 6 -0 .0 6 3 -0 .0 2 1 -0 .0 0 7 0 .2 1 4 .4 3 9 * * .2 9 3 * -0 .1 9 6 -.2 9 8 * .6 7 8 * * .7 7 2 * * α= .8 38 N o te : N = 4 8 , R e lia b ili tie s a re re p o rt e d a lo n g th e d ia g o n a l * C o rr e la tio n is s ig n ifi c a n t a t t h e 0 .0 5 le v e l ( 2 -t a ile d ) * * C o rr e la tio n is s ig n ifi c a n t a t t h e 0 .0 1 le v e l ( 2 -t a ile d ) V a ria b le s M SD S k e w n e s s K u rt o s is 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 1. G e n d e r f e m a le 2 .0 0 0 .0 0 0 .0 0 0 .0 0 2. A g e 2 .7 9 0 .9 8 1 .0 6 0 .1 4 3. O rg a n iz a tio n a l Te n u re 3 .0 6 1 .3 7 0 .1 9 -1 .2 1 .7 3 3 * * 4. E d u c a tio n 4 .0 0 1 .0 2 -0 .7 4 -0 .4 9 -0 .0 3 1 -0 .0 8 7 5. O p e n n e s s 3 5 .3 2 6 .5 1 -1 .4 3 3 .3 0 0 .1 2 5 0 .2 0 5 0 .2 8 9 α= .8 29 6. C o n s c ie n tio u s n e s s 4 5 .6 8 4 .1 0 0 .2 5 1 .0 6 0 .0 6 6 0 .1 7 1 -0 .1 8 2 -0 .2 3 1 α= .8 53 7. E xt ra v e rs io n 4 0 .7 9 6 .4 0 -0 .7 9 0 .8 4 -0 .0 4 4 0 .1 7 8 0 .1 8 9 .5 3 1 * * -0 .0 4 8 α= .8 17 8. A g re e a b le n e s s 4 2 .6 8 6 .4 4 -0 .3 9 0 .5 9 .4 4 1 * * .4 8 0 * * 0 .0 4 2 0 .0 0 6 0 .1 6 8 0 .2 9 4 α= .7 73 9. N e u ro tic is m 2 8 .4 1 5 .7 7 -0 .7 5 -0 .8 3 -0 .2 5 8 -.5 7 0 * * 0 .1 7 6 -0 .3 0 5 -0 .3 1 6 -0 .3 1 5 -.3 4 3 * α= .7 57 10. S e n s in g 3 1 .2 9 7 .2 2 -0 .3 3 -0 .0 5 0 .0 3 0 0 .0 3 2 0 .2 0 7 .6 8 6 * * -0 .2 5 8 0 .2 9 4 -.3 8 2 * -0 .0 3 2 α= .8 53 11. S e iz in g 3 0 .8 8 6 .3 3 -1 .0 0 1 .9 3 -0 .0 9 7 -0 .1 0 1 0 .2 2 2 .6 3 0 * * -0 .2 8 7 0 .2 8 7 -0 .3 0 6 -0 .0 2 4 .7 7 5 * * α= .8 78 12. R e c o n fig u rin g 2 7 .2 9 4 .7 1 -1 .1 0 2 .4 5 -0 .1 4 4 -0 .1 1 1 0 .0 6 3 .6 4 3 * * -0 .0 8 1 0 .2 9 7 -.4 6 4 * * -0 .0 1 9 .7 9 0 * * .7 7 2 * * α= .8 87 N o te : N = 3 4 , R e lia b ili tie s a re re p o rt e d a lo n g th e d ia g o n a l * C o rr e la tio n is s ig n ifi c a n t a t t h e 0 .0 5 le v e l ( 2 -t a ile d ) * * C o rr e la tio n is s ig n ifi c a n t a t t h e 0 .0 1 le v e l ( 2 -t a ile d )

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5.4 Gender differences

5.4.1 Correlation analysis

As presented earlier, it is likely that there is a relationship between gender and sensing, seizing and reconfiguring. Table 4 contains descriptive statistics for the female respondents and table 5 for the male respondents.

Men show a negative correlation between age and openness to new experience (p < 0.05; r = -0.295), organizational tenure and openness to new experience (p < 0.01; r = -0.407), and a positive correlation between educational level and openness to new experience (p < 0.01; r = 0.392). Women do not show any correlation between those variables. However, women show a positive correlation between age and openness to new experience (p < 0.01; r = 0.441), and organizational tenure and openness to new experience (p < 0.01; r = 0.480).

Neuroticism is negatively correlated with organization tenure among female respondents (p < 0.01; r = -0.570). This correlation is not significant among male respondents.

Differences can also been found among predictor variables and more significant correlations can be found in the male group. Where conscientiousness and openness to new experience are positively correlated among men (p < 0.05; r = 0.309), openness to new experience is

positively correlated with extraversion among women (p < 0.01; r = 0.531). Neuroticism is only negatively correlated with openness to new experience among men (p < 0.05; r = 0.343). Conscientiousness is positively correlated with extraversion among men (p < 0.01; r = 0.436). Women do not show this correlation. At last, neuroticism also has a negative correlation with conscientiousness and extraversion among men (both p < 0.01; r = -0.490).

Also differences can be found among correlations between predictor variables and outcome variables. Openness to new experience is positively correlated with reconfiguration in the female group (p < 0.01; r = 0.643), man only show positive correlations with sensing and seizing in regard to this predictor. Conscientiousness has strong correlations with the three

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stages among men, within the female group, no significant correlation can be found in neither of the three stages. This is the same for extraversion and neuroticism. At last agreeableness is negatively correlated with sensing (p < 0.05; r = -0.382) and reconfiguring (p < 0.05; r = 0.464), men do not show this correlation.

The biggest differences can be found in the correlations between the predictor variables and outcome variables. Openness to new experience has a stronger relationship with outcome variables among female and conscientiousness, extraversion and neuroticism show stronger correlations with outcome variables among men.

In the female group the skewness and kurtosis statistics also show bigger variances in

comparison with the male group. The biggest difference is seen in the kurtosis of openness to new experience (male: -0.31, female: 3.30).

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Table 6: Results of personality traits among female respondents as predictor for sensing, seizing and reconfiguring Variable B SE B β B SE B β B SE B β Step 1 Age -0.003 1.940 0.000 -0.428 1.689 -0.066 -0.678 1.280 -0.141 Organizational Tenure 0.267 1.390 0.051 -0.153 1.210 -0.033 -0.008 0.917 -0.002 Education 1.502 1.276 0.211 1.352 1.110 0.217 0.273 0.842 0.059 Step 2 Age -0.166 1.601 -0.022 0.013 1.644 0.002 -0.321 0.936 -0.067 Organizational Tenure 0.086 1.322 0.016 0.430 1.208 0.093 -0.881 0.698 -0.256 Education -0.292 1.070 -0.041 1.528 1.073 0.245 -0.765 0.647 -0.165 Agreeableness -0.356 0.194 -0.362* Conscientiousness 0.135 0.161 0.117

Openness to new experiences 0.874 0.192 0.792*** 0.564 0.105 0.779***

Neuroticism 0.234 0.233 0.185 Extraversion -0.073 0.195 -0.064 Step 3 Age 0.575 1.740 0.078 -0.225 1.471 -0.034 1.087 1.072 0.232 Organizational Tenure 1.470 1.283 0.279 -0.617 1.214 -0.131 -0.095 0.870 -0.028 Education 1.582 1.149 0.222 0.042 0.983 0.007 0.164 0.675 0.037 Agreeableness -0.592 0.206 -0.528*** -0.503 0.122 -0.716*** Conscientiousness -0.320 0.290 -0.181 -0.289 0.288 -0.179

Openness to new experiences 0.615 0.192 0.641***

Neuroticism -0.031 0.236 -0.028 -0.110 0.150 -0.140 Extraversion -0.050 0.179 -0.051 0.335 0.118 0.471*** R² Step 1 Step 2 Step 3 ΔR² Step 2 - Step 1 ΔR² Step 3 - Step 1 Note: N=34. * p < 0.1, ** p < 0.05, *** p < 0.01 0.4307

0.0452 0.0578 0.0243

0.5082 0.1558 0.5193

0.3056 0.4729 0.4550

0.4629 0.0980 0.4950

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Table 7: Results of personality traits among male respondents as predictor for sensing, seizing and reconfiguring

Variable B SE B β B SE B β B SE B β Step 1 Age -2.307 1.407 -0.332 -1.060 1.177 -0.180 -0.406 0.874 -0.097 Organizational Tenure 0.836 1.039 0.157 0.302 0.847 0.069 0.112 0.629 0.036 Education 0.315 1.110 0.044 1.393 0.927 0.231 -0.137 0.688 -0.032 Step 2 Age -1.630 1.196 -0.239 -0.937 1.168 -0.159 -0.794 0.802 -0.190 Organizational Tenure 1.327 0.992 0.257 0.534 0.856 0.122 0.297 0.603 0.095 Education -1.397 0.969 -0.201 1.795 0.963 0.298* -0.347 0.668 -0.081 Agreeableness -0.290 0.212 -0.213 Conscientiousness 0.297 0.104 0.431***

Openness to new experiences 0.735 0.226 0.538*** 0.081 0.149 0.095

Neuroticism -0.081 0.167 -0.077 Extraversion 0.359 0.175 0.291* Step 3 Age -2.804 1.258 -0.403** -1.268 1.173 -0.214 0.018 0.861 0.004 Organizational Tenure 1.245 0.943 0.234 0.844 0.881 0.193 0.094 0.634 0.030 Education 0.657 1.027 0.093 0.520 0.908 0.086 0.025 0.690 0.006 Agreeableness -0.345 0.228 -0.216 -0.258 0.152 -0.267* Conscientiousness 0.526 0.151 0.464*** 0.229 0.167 0.236

Openness to new experiences 0.414 0.211 0.346*

Neuroticism 0.050 0.162 0.054 -0.120 0.109 -0.184 Extraversion 0.221 0.173 0.208 0.208 0.127 0.274 R² Step 1 Step 2 Step 3 ΔR² Step 2 - Step 1 ΔR² Step 3 - Step 1 Note: N=48. * p < 0.1, ** p < 0.05, *** p < 0.01 0.2370 0.2529 0.1902 0.3128 0.3481 0.1958 0.3521 0.0385 0.2147 0.0952 0.0056 0.4278 0.1337 0.2203 0.0757

Reconfiguring

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5.4.2 Direct effects

Table 6 shows the direct effects among women and table 7 shows the direct effects among men. The same analyses have been done as presented in table 2 for the whole group. For these groups also multicollinearity has been tested. The maximum VIF is 3.166, the lowest

tolerance is 0.316.

No differences can be found in relationships among control variables in step 1. Step 2 shows three differences in regard to significant relationships. Extraversion has a positive relationship with sensing opportunities among men (β = 0.291, p < 0.05), but no significant relation is shown among women. Where conscientiousness is a positively related to reconfiguration among men (β = 0.431, p < 0.01), it is openness to new experiences that has a positive relationship with reconfiguration among women (β = 0.779, p < 0.01).

In step 3, other personality traits are being tested. Five differences occur in these analyses. Agreeableness does not show a significant relationship among men. Among the female group there is a significant negative relation with sensing (β = -0.528, p < 0.01) and reconfiguring (β = -0.716, p < 0.01). The same happens for extraversion and seizing opportunities (β = 0.641, p < 0.01), and extraversion and reconfiguration (β = 0.471, p < 0.01). At last conscientiousness show a significant positive relationship with the seizing stage among the male respondents (β = 0.464, p < 0.01) and no significant relationship among the female group.

Variance of personality traits in relation to the three stages is stronger in the female group. The biggest delta’s can be found in the reconfiguring stage. ΔR² step 2 – step 1 is 0.4950 among women and 0.2147 among men. ΔR² step 3 – step 1 is 0.4307 in the female group and 0.1902 in the male group.

Table 11 presents dependent variable effects in the female group, table 12 for the male group. Four differences in significant relationships can be found. In the female group, all stages have a relationship with each other. In the male group there are two exceptions. Sensing ability does not relate to the ability to reconfigure and vice versa. Among the male respondents,

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education impacts the ability to seize (β = 0.229, p < 0.01) and the ability to reconfigure (β = -0.210. p < 0.05). This effect is not significant in the female group.

Table 11: Results of effects in dependent variables among female respondents

Table 12: Results of effects in dependent variables among male respondents

Variable B SE B β B SE B β B SE B β Step 1 Age -0.003 1.940 0.000 -0.428 1.689 -0.066 -0.678 1.280 -0.141 Organizational Tenure 0.267 1.390 0.051 -0.153 1.210 -0.033 -0.008 0.917 -0.002 Education 1.502 1.276 0.211 1.352 1.110 0.217 0.273 0.842 0.059 Step 2 Age 0.719 1.092 0.097 -0.033 1.027 -0.005 -0.555 0.711 -0.115 Organizational Tenure 0.337 0.778 0.064 -0.245 0.728 -0.053 -0.056 0.510 -0.016 Education 0.722 0.742 0.101 0.649 0.694 0.104 -0.627 0.479 -0.135 Sensing 0.362 0.163 0.413** 0.343 0.105 0.525*** Seizing 0.415 0.187 0.364** 0.285 0.121 0.382** Reconfiguring 0.802 0.246 0.524*** 0.581 0.247 0.433** R² Step 1 Step 2 ΔR² Step 2 - Step 1 Note: N=34. * p < 0.1, ** p < 0.05, *** p < 0.01 0.7211 0.6832 0.7202 0.6759 0.6254 0.6959

0.0452 0.0578 0.0243 Variable B SE B β B SE B β B SE B β Step 1 Age -2.307 1.407 -0.332 -1.060 1.177 -0.180 -0.406 0.874 -0.097 Organizational Tenure 0.836 1.039 0.157 0.302 0.847 0.069 0.112 0.629 0.036 Education 0.315 1.110 0.044 1.393 0.927 0.231 -0.137 0.688 -0.032 Step 2 Age -1.389 0.914 -0.200 0.034 0.651 0.006 0.342 0.544 0.081 Organizational Tenure 0.519 0.668 0.097 -0.086 0.466 -0.019 -0.057 0.392 -0.018 Education -0.620 0.778 -0.088 1.389 0.496 0.229*** -0.899 0.434 -0.210** Sensing 0.346 0.095 0.405*** 0.106 0.090 0.175 Seizing 0.723 0.198 0.618*** 0.501 0.107 0.708*** Reconfiguring 0.313 0.267 0.189 0.709 0.151 0.501*** R² Step 1 Step 2 ΔR² Step 2 - Step 1 Note: N=48. * p < 0.1, ** p < 0.05, *** p < 0.01 0.6371 0.7620 0.6642 0.5614 0.6668 0.6586

0.0757 0.0952 0.0056

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6. Discussion

6.1 Accepted hypotheses

It is hypothesized that agreeableness is negatively related to seizing opportunities which has been accepted in this study. The seizing stage is a stage in which a lot of decisions have to be made (Teece, 2007) and as stated by Zhao and Seibert (2006) the agreeable person suffers in less predictable environments and. As pointed out in this study, there are signs that

agreeableness even has a negative impact in all stages. This finding will be discussed later. As hypothesized, conscientiousness would be positively related with reconfiguration. The results indeed show that the strongest relationship can be found in this stage. This could be explained by the fact that conscientious type of persons are deliberate and willing to achieve (Digman, 1990). These characteristics are likely to result in a motivated worker, also during a reconfiguration process, where shirking and free riding become threats (Teece, 2007).

The two hypotheses in regard to openness to new experience are being accepted. Openness to new experience have a positive relationship with sensing opportunities and reconfiguration; it seems that the open and flexible character indeed positively impacts the sensing stage

(Digman, 1990). It is also known that these type of persons positively affect the ability to adapt and this might influence the ability to reconfigure (Le Pine et al, 2000). There are even signs that openness to new experience is the strongest driver in the whole process of dynamic capability building since it has a positive relationship with all stages with highest beta’s. This effect is being discussed later.

6.2 Other effects

This study shows, taken both genders together, that sensing, seizing and reconfiguring are also related to each other. It is argued that someone who is capable of sensing, also knows how to seize and reconfigure, and vice versa. Since openness to new experience has a positive relation with all stages, it is suggested that openness to new experience is the main driver

“What is the relationship between personality traits of the Five-Factor Model and the process of sensing and seizing opportunities, and reconfiguration?”