Individual ambidexterity and cognitive strain : the moderating effect of social capital

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Individual ambidexterity and cognitive strain: The

moderating effect of social capital

Master Thesis

Student name: Donny van Soest Student number: 10678700

Date: 24-06-2017

Study: Master of Science in Business Administration – Strategy track Institution: University of Amsterdam

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Statement of originality

This document is written by Student Donny van Soest 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.

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Abstract

This study examines the effect of the level of ambidexterity within an individual and its cognitive strain. An individual is seen as ambidextrous when it is capable of balancing the learning behaviors, exploitation and exploration. As in line with earlier research, I propose that individuals that balance exploration and exploitation have a higher level of cognitive strain than individuals that don’t balance exploitation and exploration. Moreover I propose that the social capital of this individual moderates the relationship between ambidexterity and cognitive strain and reduces the cognitive strain as consequence of acting ambidextrous. Using the data collected for this paper I find that individuals that balance exploration and exploitation have indeed higher levels of cognitive strain then managers that don’t balance exploitation and exploration. In this data no evidence was found that social capital moderates the relationship between individual’s ambidextrous behavior and his level of cognitive strain. The findings of the first hypothesis are in line with my predictions and suggest that

individuals that are ambidextrous experience more cognitive strain than people that are not ambidextrous. The findings of the second hypothesis were not in line with my expectations as I expected that social capital would reduce the level of cognitive strain as consequence of ambidextrous behavior.

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Introduction

In the past years, research on the ambidextrous firm and its two patterns of organizational learning behavior, exploitation and exploration, have had an increasing interest in the organization and management science, because exploration and exploitation can jointly influence firm performance (He & Wong, 2004; Jansen et al., 2006; Raisch & Birkinshaw, 2008; Stettner & Lavie, 2013). Where exploitation is about activities that make use of known knowledge and competencies and is focused on the short term, exploration is about activities that open up new knowledge and competencies and is more focused on the long term (March, 1991; Raisch & Birkinshaw, 2008). When a firm is able to simultaneously explore and exploit it is seen as ambidextrous (Raisch & Birkinshaw, 2008). Ambidexterity is in the literature positively linked to the performance of a firm (Raisch & Birkinshaw, 2008; Stettner & Lavie, 2013). This makes research on the topic of ambidexterity important for practitioners. In the current literature exploration and exploitation are mainly studied at the level of the firm or at the level of the business unit (Mom et al., 2007).

More recently a new stream of research exists that focusses on the exploration and exploitation activities at the individual level of analysis (Mom et al., 2007). According to Mom et al., (2007) this is an important stream of research because these studies give insight in the exploration and exploitation activities of individuals and how these activities can be influenced, which would increase the understanding of how to build exploration and exploitation within a business unit or firm.

In the field of research on individual ambidexterity several studies have been conducted concerning antecedents of ambidexterity. These were among others about the effect of dynamic contexts on individual ambidexterity (Good & Michel, 2013), the role perceptions and actual behaviors of individuals in the exploitation and exploration trade-off (Bonesso et al., 2013) and transformational leadership as antecedent of individual

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ambidexterity and cognitive strain as an outcome (Keller & Weibler, 2015). As with organizational ambidexterity, it is important for a manager to find a balance between exploring and exploiting activities in order to be ambidextrous.

According to the literature managing the trade-offs of exploitation and exploration is important to benefit from both if resources are scarce (Cao et al., 2009). Because an

individual has a limited supply of cognitive resources, exploration and exploitation can’t be pursued simultaneously (Laureiro-Martínez et al. 2010). Laureiro-Martínez et al. (2010) also states that the exploitation and exploration involve different modes of human attention, which means that exploitation and exploration can’t be pursued by an individual at the same time, leading managers to choose between exploration and exploitation activities. Therefore the chance of trade-offs increases and thus the chance the chance of conflicts between exploration and exploitation increases (Gupta, Smith & Shalley, 2009).

Other authors however state that exploration and exploitation can be pursued

simultaneously by an individual known as the combination perspective of ambidexterity (Cao et al., 2009; He & Wong, 2004; Jansen et al., 2008; Mom et al., 2009). Because managers need different modes of attention and cognitive resources are scarce for managers it makes it difficult for exploration and exploitation to be pursued at the same time. Therefore we will follow the balance perspective of ambidexterity. This means that managers focus on either exploitation or exploration and alternate between these two patterns. Although ambidexterity is desirable it can also be costly. Mom et al., (2009) states that ambidextrous managers are multitasking persons and host contradictions. Because exploration and exploitation rely on different logics and track different goals, ambidextrous managers have to fulfill multiple roles, which can cause distress and role conflict (Floyd & Lane, 2000; Keller & Weibler, 2015).

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In the current literature focus was on the antecedents of individual ambidexterity. However this caused researchers to overlook the consequences of the pursuit for

ambidexterity. Keller and Weibler (2015) were the first to also focus on the consequences of ambidexterity and found a dark side on the pursuit for ambidexterity. They found a positive relationship between a manager’s level of ambidexterity and his level of cognitive strain, which is caused by higher cognitive demands in balancing exploration and exploitation. This cognitive strain can affect the psychological well-being of the individual and can have serious consequences if it persists over time, such as a depression (Keller & Weibler, 2015).

This will also have negative effects on organizations’ productivity, as managers suffering from occupational stress will be less productive than managers with lower stress levels (Lerner et al., 2010). It is therefore important that the cognitive strain of ambidextrous individuals is avoided and reduced as much as possible. In the current literature the effects of an individual’s level of ambidexterity and his level of cognitive strain has been identified. Also the moderating effect of the individual’s personality characteristics on the relationship between ambidexterity and cognitive strain has been studied (Keller & Weibler, 2015). However this is the only study that focusses on the negative side of ambidexterity.

Because we want to minimize the cognitive strain caused by ambidexterity, it is important to research this relation more closely and find out what moderates the relationship between ambidexterity and cognitive strain in order to minimize the cognitive strain. As mentioned before, Keller and Weibler (2014; 2015) researched in their article the moderating effect of personality on the relationship between individual ambidexterity and cognitive strain. In doing so they took personality dimensions from the big five personality traits, openness to experience, extraversion, agreeableness, neuroticism and conscientiousness (Barrick & Mount, 1991; Keller & Weibler, 2014). In the article of Keller and Weibler (2015) they only focused on the dimensions of openness to experience and conscientiousness,

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because these were linked with individual learning behavior and could be linked to the two patterns of organizational learning behavior, exploitation and exploration. They found that the relation between ambidexterity is positively moderated by a manager’s level of

conscientiousness and negatively moderated by a manager’s level of openness to experience. Keller and Weibler (2015) focused on personality characteristics which are difficult to change and can only be changed in an organization by hiring employees with the right

personality characteristics to minimize the cognitive strain. While this is a valuable first step in minimizing cognitive strain more research is needed. Especially about what a company can do to minimize the level of cognitive strain for its employees.

As mentioned before the cognitive strain is caused by the increased cognitive demands for balancing exploitation and exploration. Because exploration and exploitation rely on different logics and track different goals, ambidextrous managers have to fulfill multiple roles, which can cause distress and role conflict (Floyd & Lane, 2000; Keller & Weibler, 2015). Cognitive strain is also increased because exploration and exploitation involves different modes of human attention (Laureiro-Martínez et al. 2010).

Support from superiors and coworkers are said to lower employees stress (Bliese & Castro, 2000; Stamper & Johlke, 2003), so it can also have a lowering effect on the cognitive strain of an individual. For this support it is important that there is a relation between

employees in which they feel supported and can discuss their problems. According to Turner et al., (2015) trust is an important aspect of the social capital construct within an organization. Social capital enhances the richness of information exchange among employees and is seen as an example of how it facilitates interaction and the exchange of ideas (Subramejan & Youndt, 2005). They define social capital as the knowledge embedded within, available through and utilized by interactions among employees and their networks of relationships. This makes it that the use of social capital can support an individual which has as effect that the individual

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feels supported and cognitive strain is reduced. Therefore the research question of this paper is: How does social capital moderate the relationship between ambidexterity and cognitive strain?

By answering this question this paper contributes to current literature by studying the relation between ambidexterity and cognitive strain more closely. Something only Keller and Weibler (2015) have done before. They focused on the moderating effect of openness to experience and conscientiousness on the relationship between ambidexterity and cognitive strain. This paper will build onto that by examining of a relation between ambidexterity and cognitive strain can be found in a different dataset. This paper also contributes to current literature by examining whether social capital can minimize the cognitive strain which is caused by balancing exploitation and exploration. The results of this study can be used to minimize cognitive strain by focusing on the social capital in an organization.

The remainder of the paper is organized as follows. The next section gives a

theoretical background and develops the hypotheses. The method, data analysis and results are discussed in the subsequent sections. This paper is concluded with a discussion and implications for the literature on ambidexterity, cognitive strain and social capital.

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Theory and hypothesis

The following section discusses the main insight of the existing literature on individual ambidexterity, cognitive strain and social capital and presents the hypothesis of this research.

Individual ambidexterity

Ambidexterity is in the current literature mainly researched at the organizational or business unit level of analysis (Mom et al., 2007). However more recently a new stream of research exists that focusses on the individual level of analysis. This stream of research makes use of research about the ambidextrous firm and its two patterns of organizational learning behavior, exploitation and exploration (He & Wong, 2004; Jansen et al., 2006; March, 1991; Raisch & Birkinshaw, 2008; Stettner & Lavie, 2013).

March (1991) defined exploitation as refinement, choice, production, efficiency, selection, implementation and execution,” in contrast with exploitation, which involves “search, variation, risk-taking, experimentation, play, flexibility, discovery, and innovation” (p. 71). This definition was quite broad and allowed for various interpretations. In a later work the definition was restricted to the knowledge domain and exploitation was defined as the activities that make use of known knowledge and competencies and is focused on the short term, while exploration is about activities that open up new knowledge and competencies and is more focused on the long term (Bonesco, Gerli, & Scapolan, 2014; Lavie, Stettner, & Tushman, 2010; Levinthal & March, 1993; March, 1991; Raisch & Birkinshaw, 2008).

Recently, some scholars reverted to the original definition of exploitation and

exploration as defined by March (1991). However, by using the first definition of exploration and exploitation you also open up to the various interpretations that were given to exploration and exploitation. According to Lavie, Stettner and Tushman (2010) this could have

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and unwarranted generalization. For this reason we use the definition of exploitation and exploration in the knowledge domain as Levinthal and March (1993) suggested.

When a firm is able to simultaneously explore and exploit to its best advantage, it is seen as ambidextrous (Keller & Weibler, 2014; Raisch & Birkinshaw, 2008). Current

literature shows support that firms should engage in both learning behaviors (Cao et al., 2009; He & Wong, 2004; Jansen et al., 2006). While it is supported to engage in both learning behaviors it is also important to keep a balance between exploitation and exploration. Too much reliance on exploration, which generates higher potential benefits and higher potential costs, may cause the firm to operate with less efficiency since it is constantly renewing its knowledge base without fully utilizing it (Bonesso et al., 2014; Levinthal & March, 1993). On the other hand, if a firm only focuses on exploitative learning, where returns are more certain, in the short term and known than the firm may risk its continuity because its knowledge base becomes obsolete (Bonesso et al., 2014; Levinthal & March, 1993).

However engaging in both types of tasks is difficult for firms because each

organizational learning behavior is underpinned by fundamentally different logic systems (Keller & Weibler, 2014). According to Keller and Weibler (2014) the competing for scarce resources, such as time and money, doesn’t make it easier to engage in both learning

behaviors. As mentioned by Nosella, Cantarello and Filippini (2012, in Bonesso et al., 2013) the literature took a macro level of analysis in identifying solutions that orientate behaviors towards balanced learning. These solutions were structural ambidexterity, cycling or sequential ambidexterity and contextual ambidexterity (Bonesso et al., 2014; Gupta et al., 2006; Raisch & Birkinshaw, 2008).

As with organizational ambidexterity, it is important for an individual to find a balance between exploring and exploiting activities in order to be ambidextrous. As stated by Keller

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and Weibler (2014) exploitation and exploration are underpinned by fundamentally different logic systems, which has as effect that exploitation and exploration involve different modes of human attention (Laureiro-Martínez et al. 2010). According to Laureiro-Martínez et al. (2010) this means that exploitation and exploration can’t be pursued by an individual at the same time. A consequence is that an individual has to make a choice between exploitation and explorationactivities and consider a trade-off, between the two behavioral learning patterns, when shifting their attention from exploitation to exploration and from exploration to exploitation (Keller & Weibler, 2015). Cao et al., (2009) states that, in order to be

ambidextrous, trade-offs between exploitation and exploration needs to be managed to benefit from both when resources are scarce. Where a company can make use of multiple employees to engage in exploitative and explorative activities, an individual can’t. Due to a limited supply of cognitive resources of an individual exploration and exploitation can’t be pursued simultaneously (Laureiro-Martínez et al. 2010). Therefore the chance of trade-offs between exploitative and explorative activities increases (Gupta, Smith & Shalley, 2009).

Other authors however state that exploration and exploitation can be pursued

simultaneously by an individual known as the combination perspective of ambidexterity (Cao et al., 2009; He & Wong, 2004; Jansen et al., 2008; Lavie et al., 2010; Mom et al., 2009). Lavie et al., (2010) state that the distinction between exploration and exploitation should be seen as a matter of degree and not of kind. They suppose that exploration and exploitation should be seen as a continuum rather than a choice between the two. While this might work for organizations it is not applicable for individuals, because individuals need different modes of attention and cognitive resources are scarce it makes it difficult for exploration and

exploitation to be pursued at the same time. Therefore it is more likely that an individual makes trade-offs between exploitation and exploration activities. Following Laureiro-Martínez et al. (2010) and Keller & Weibler (2015) I do not agree with the combination

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perspective of ambidexterity, which is that exploitation and exploration can be pursued simultaneously by an individual. Rather, exploration and exploitation tasks have to be conducted consecutively and in close correspondence to the situational context. So in this paper individual ambidexterity is operationalized as the balance perspective of ambidexterity.

The articles, mentioned earlier, focused on antecedents of ambidexterity or solutions to enable the pursuit for exploration and exploitation simultaneously. Although ambidexterity is desirable it can also be costly. Ambidextrous managers are multitasking persons and host contradictions Mom et al., 2009; Tushman & O’Reilly, 1996). This at first seems to be in favor of the ambidextrous individual in balancing exploitation and exploration. However, because exploration and exploitation rely on different logics and track different goals, ambidextrous managers have to fulfill multiple roles, which can cause distress and role conflict (Floyd & Lane, 2000; Keller & Weibler, 2015).

Many authors have described the exploitation and exploration relationship as tense, because both patterns follow a different and paradoxical logic (Keller & Weibler, 2015; Laureiro-Martínez et al., 2010; Lavie et al., 2010; March, 1991). Keller and Weibler (2015) identified that this can have consequences for the individual, for the pursuit of ambidexterity does not have only positive outcomes but also a negative outcome in the form of cognitive strain

Individual ambidexterity and Cognitive Strain

Albers (1997) found that the amount of cognitive resources consumed by information

processing is very high and often operates near the border of overload. Because ambidextrous individuals pursuit exploration and exploitation, they are involved in great deal of information processing. Where exploitation makes use of the current knowledge base and competences the amount of information processing will be minimized and thus the cognitive demand for the

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activity will be lower (Bonesco et al., 2014; Lavie, Stettner, & Tushman, 2010; Levinthal & March, 1993; March, 1991; Raisch & Birkinshaw, 2008).The exploration learning behavior however is about activities that open up new knowledge and competencies (Bonesco et al., 2014; Lavie, Stettner, & Tushman, 2010; Levinthal & March, 1993; March, 1991; Raisch & Birkinshaw, 2008). Exploration involves thus the learning of new knowledge and involves a great deal of information processing, which is very demanding of the cognitive resources (Albers, 1997).

Albers (1997) also states that people do not allocate resources in proportion to the significance of the task. Instead, individuals tend to use equal-scheduling. The result of equal scheduling is a mismatch of cognitive resources to demand. This is because some tasks do not get enough cognitive resources to be complete while other tasks got too much cognitive resources allocated (Albers, 1997). In the case of ambidexterity this could have negative consequences, as the capability to be ambidextrous for an individual is about the balance between exploration and exploitation. If the individual would assign not enough resources to either exploitation or exploration, than there is a change for misbalance. This is also a problem because due to information processing exploration is more demanding than exploitation. This would result in not enough cognitive resources for the exploration activities, which result in a cognitive overload for the individual (Albers, 1997).

According to Kellog (1994; in Albers, 1997) this has also the effect that the individual often settles for less than optimal performances. He says that instead of maximizing output, individuals economize on cognitive resources and produces satisfactory output with minimal cognitive effort. Rather than finding ways to effectively handle the cognitive demand, the individual often reduces the cognitive strain by dumping parts of the problem and return to what is previously learned (Bettman, Johnson, and Payne, 1990). When we translate this towards ambidexterity it would mean that an individual would no longer pursuit exploration,

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due to cognitive strain. This makes it important for organizations to reduce the strain on their employees, because the pursuit for exploration is necessary in order for an individual to be ambidextrous.

Also Bliese and Castro (2000) agree to this view. They state that high levels of

cognitive strain occurs when an individual is working on an activity that has low levels of job control and high levels of demand. For exploration activities there are low levels of job control because the employee is accumulating new knowledge, so no procedure exist of what must be done. (Levinthal & March, 1993). This indicates that the exploration activities of ambidexterity increase the level of cognitive strain for employees. In addition Bliese and Castro (2000) also state that with high levels of control there is a change of low levels of cognitive strain. Because exploitation activities make use of an existing knowledge base it is easy to know what is expected within your function. Therefore it is possible to exert high levels of control, which can increase the level of cognitive strain by employees.

It is a challenge for individuals to be able to succeed at both exploration and

exploitation (Gupta, Smith, & Shalley, 2006). Individuals who behave ambidextrously likely attempt to do both at the same time (Gibson & Birkinshaw, 2004; He & Wong, 2004;

Tushman & O’Reilly, 1996). However it is more likely that an individual rapidly switches between exploration and exploitation in order to be ambidextrous (Good & Michel, 2013).

Keller & Weibler (2015) already examined this relationship in their paper and found a positive relationship between a manager’s level of ambidexterity and his level of cognitive strain, which is caused by higher cognitive demands in balancing exploration and

exploitation.

If we look at the current literature we see that the two behavior learning behavior might have an impact on the cognitive strain. According to Albers (1997) information

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processing is an antecedent of cognitive strain. When we look at the construct of

ambidexterity we see that it exist out of two different learning patterns, one of which is about accumulating new knowledge, which needs high levels of information processing. Also Bliese and Castro (2000) added to this by stating that when an individual has low control and high demands the level of cognitive strain increases. When we take this in consideration together with the paper of Keller & Weibler (2015) in which this relation was already significant, it is reasonable to assume that individual ambidexterity raises the level of cognitive strain within an individual. Therefore the first hypothesis is:

Hypothesis 1: Individuals that are ambidextrous experience higher levels of cognitive strain than individuals that are not ambidextrous

Because ambidextrous managers find it difficult to switch off from work, their high levels of cognitive strain can be regarded as a critical indication of forthcoming psychological exhaustion that could cause serious harm to their psychological well-being if this persists over time (Keller & Weibler, 2015;Laureiro-Martínez et al., (2010); Lerner et al., 2010).

Therefore it is important to minimize the level of cognitive strain an individual experiences. According to Albers (1997) the easiest way to reduce the cognitive strain is to stop working and ask someone for help. According to Adler relationships at the work floor are important to reduce the cognitive strain. These relationships are embodied in the social capital of a firm.

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The moderating effect of social capital

Social capital has its origins in the field of community studies and is together with human capital and organizational capital the constructs for intellectual capital (Nahapiet & Ghoshal, 1998; Turner, Swart & maylor, 2013). Where human capital is defined as the knowledge, abilities and skills residing in and utilized by an individual. Organizational capital is the institutionalized knowledge and codified experience residing within and utilized through databases, patents, manuals, structures, systems, and processes and social capital is defined as the knowledge embedded within, available through, and utilized by interactions among individuals and their networks of interrelationships (Nahapiet & Ghoshal, 1998; Subramejan & Youndt, 2005).

Social capital can be divided into three dimensions which are the structural, cognitive and relational/ affective dimension (Turner et al., 2013; Nahapiet & Ghoshal, 1998). The structural network can be understood in terms of strong ties and weak ties, in which strong ties represent frequent communication and weak ties a wide range of occasional contacts. In the cognitive dimension the individual is an integrator, where he brings together different knowledge domains while keeping an overview of the project. In the affective dimension, trust emerged as a critical factor in enabling the relationships (Turner et al., 2013).

According to Turner et al., (2013) these networks of relationships can be crucial for organizational performance at the operational level. Tiwana (2008) provides a powerful conception of ambidexterity in terms of social ties. He looks at the effect of weak/bridging ties that can be used for exploratory access and strong ties that can be used for exploitative activities. Tiwana (2008) states, that a network with strong ties has a higher capacity to implement ideas, but has a lower capacity to generate these ideas. A network that makes use of weaker ties has a higher capacity to generate new ideas, but has lower capacity to

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According to Tiwana (2008) it is important for individuals to have both, where the strong ties should complement the weak ties. This leads to a situation where an individual has access to specialized knowledge and be able to implement them (Tiwana, 2008). This can help

Individuals to lower their cognitive strain, because if they are cognitive overloaded, they can make use of their relations at work to help them solve the problem so cognitive resources can again be used.

Also Subramejan and Youndt (2005) found in there paper that social capital was significantly related to incremental innovative capabilities and radical innovative capabilities. These findings indicate that social capital has a positive relationship on the exploration activities performed by an individual as it appears to be the bedrock of innovative capabilities (Subramejan & Youndt, 2005).

Given that innovation is a collaborative effort, social capital assumes a central role in generating both incremental and radical innovations. Thus, communication and the sharing and assimilating of knowledge are vital elements of innovative capabilities, irrespective of their type of innovation. (Subramejan & Youndt, 2005). Therefore using relational ties within the organization can help an individual to find solutions for problems it can’t solve itself due to not sufficient cognitive resources. This social support from coworkers solving problems can lower the cognitive strain of an individual (Bliese & Castro, 2000).

If we look at the construct of social capital we see that there are different aspects that can help an employee to overcome problems. First of all an individual can use his social ties in order to help with exploration activities when an individual has not enough cognitive resources to solve it himself. This also lowers the amount of information processing, which had a positive effect on cognitive strain. Also Subramejan and Youndt (2005) found that social capital is positively related with innovation capabilities and thus with the exploration activities of an individual. This leads me to believe that social capital can reduce the cognitive

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strain, due to the relations an individual has in his work place. Therefore the second hypothesis of this paper is:

Hypothesis 2: Social capital reduces the cognitive strain of an employee which is caused by his level of ambidexterity

In figure 1 the conceptual model can be found, in which the expected relationships between the variables is shown together with the location of the hypotheses.

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Method

This chapter explains the research design of this paper. First the sampling strategy will be discussed. Next is a detailed operationalization of the dependent, independent, moderating and control variables. The last section discusses the models used to analyze the collected data.

Data collection and sample

In order to be able to answer the research question, whether social capital moderates the relationship between individual ambidexterity and cognitive strain, and test the hypotheses data is collected. This data is collected by making use of a survey. For this thesis the survey method is chosen, because with the use of the internet it saves time (Wright, 2005). Wright (2005) stated that online surveys allow a researcher to reach many people in a short time. He also said that using an online survey can save money by avoiding costs for paper, postage and data entry. A potential disadvantage of using an online survey is a low response rate. By sending the candidates a reminder after two weeks an attempt is made to increase the response rate. With the survey data was collected or the variables cognitive strain, individual

ambidexterity, social capital and the control variables. As the level of analysis is on the individual level all individuals that had a job were identified as potential candidates.

Candidates received an e-mail with an introduction letter. Both the e-mail as the introduction letter had a link towards the survey. In total 157 responses were recorded. In analyzing the data a frequencies check was performed in order to check for errors within the dataset. There were no errors found within the dataset. The next step was to deal with missing data. In order to deal with missing data excluding cases listwise was used, so only cases that had no missing data were analyzed. This had as effect that the number of cases was reduced from 157 to 113 cases. In the survey was one item that was counter indicative. This was an item of the

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half of the participant in this study are male (57.5%). Of them 85.8% said to have a university degree.

Dependent variable

Cognitive strain. The dependent variable in this study is the cognitive strain of an individual.

Cognitive strain will be measured by three items from the irritation scale by Mohr, Müller, and Rigotti (2005). According to Mohr, Müller, and Rigotti (2005) this scale is recommended particularly for occupational context. The three items ask respondents about the rumination at their work. The items can be rated on a 7-point Likert scale from 1, strongly disagree, to 7 for strongly agree. A high score on these items means that an individual experiences cognitive strain from work related activities. The Cronbach’s alpha value of the three item scale was .84. The corrected item-total correlations indicate that all the items have a good correlation with the total score of the scale (all above .30). None of the items would substantially affect the reliability if they were deleted.

Independent variable

Individual ambidexterity. Individual ambidexterity will be measured using the 14 item scale

developed by Mom et al., (2009). Items are answered on a seven point Likert scale, in which 1 stands for a very small extent and 7 for a very large extent. To confirm that the items that were used measuring exploration and exploitation as intended, a confirmatory factor analysis was performed. With the exception of one exploitation item and two exploration items, factor loadings of the items were above .5 and loaded into their own factor. Both scales proved to be reliable with Cronbach’s alpha of .79 for exploration and .76 for exploitation. The corrected item-total correlations indicate that all the items have a good correlation with the total score of the scale (all above .30). None of the items would substantially affect the reliability if they were deleted.

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Accordingly the seven exploitation items measure the extent to which the individual in his current function engages in activities that lets the individual make use of known knowledge and competencies and is more focused on the short term. The seven exploration items measure the extent to which the individuals performs activities that open up new knowledge and competencies and is more focused on the long term. Prior studies combined exploitation and exploration measures to assess ambidexterity (Gibson & Birkinshaw, 2004; He & Wong, 2004; Mom et al., 2009). Gibson and Birkinshaw (2004) and Mom et al., (2009) made use of the same conceptualization of ambidexterity. Therefore their approach is followed in

assessing an individual’s ambidexterity by computing the multiplicative interaction between an individual’s exploration activities and his exploitation activities.

Moderating variable

Social capital. Social capital will be measured using a 5 items from the intellectual capital

scale (Subramejan & Youndt, 2005). The 5 items ask individuals how well they can exchange information with coworkers in order to solve problems. The items can be rated on a 7-point Likert scale from 1, strongly disagree, to 7 for strongly agree. A high score on these items means that an individual is able to communicate with coworkers and can use social

relationships to solve problems. The Cronbach’s alpha value of the five item scale was .78. The corrected item-total correlations indicate that all the items have a good correlation with the total score of the scale (all above .30). None of the items would substantially affect the reliability if they were deleted.

Control variables

Because the sample captured data form both males and females, a control variable for gender is inserted. As in line with Mom et al., (2009) we checked for the experience in terms of age and tenure. According to Tushman and O’Reilly (1996) can be expected that age and tenure

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positively relates to an individual’s level of ambidexterity. Birkinshaw and Gibson (2004) however state that a long tenure in the current position is associated with increased levels of specialization and has a negative effect on an individual’s level of ambidexterity. Education is associated with increased ability to learn and process information. For educational effects is controlled by including a dummy variable reflecting individuals with a master degree or higher. Environmental dynamism may influence to which extent an individual engages in exploration or exploitation activities or both (Good & Michel, 2013; Mom et al., 2009). Therefore a five item scale (α =.7) is included that measures the degree of environmental dynamism that an individual faces (Jansen et al., 2006). Sample items are “Environmental changes in our local market are intense” and “In our market, the volumes of products and services to be delivered change fast and often”. According to Jansen et al., (2009)

formalization positively influences exploitative innovation. Therefore we control for

formalization. A five item scale (α = .78) is included that measures the degree of

formalization within the organization an individual has to cope with (Jansen et al., 2006). Example items are “There is a written job description for going about my tasks” and “Rules occupies a central place in my work related activities”.

Statistical model

The data contained information on numerical variables. All variables were normally

distributed and no patterns could be found in the residuals. Therefore is the statistical model that is used to test the hypothesis a multiple regression analysis. Following Mom et al.,

(2009), all the variables are mean-centered before creating the interaction variables to mitigate any potential multicollinearity problems. In order to test the hypothesis I used SPSS to

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Results

In the following section the results of this paper will be presented. First the descriptive statistics for the variables in this study are discussed to provide an overview of the data. Then the multiple regressions, that test the hypothesis as formulated in the theoretical part, will be

discussed.

Descriptive statistics and correlation analysis

Table 1 provides descriptive statistics and the bivariate correlation analysis of the variables for the final dataset. On the diagonal the Cronbach’s alpha are reported. The relations were investigated using the Pearson correlation coefficient. First, the correlations between the dependent variable and control variables are presented. Subsequently, the correlations between the dependent variable and the independent variables are outlined. Finally, some of the correlations between the moderating variable and independent variables, and the

correlations between the moderating variable and the control variables are discussed.

When considering the correlation between the dependent variable and the control variables, cognitive strain was negatively correlated with the hierarchical status of an individual at the 0.1 level (r = -0.17). As with cognitive strain and the hierarchical status, cognitive strain is also negatively correlated with age at the 0.1 level (r = -0.17). All of the other control variables had no correlation with cognitive strain. When we look at the correlation between cognitive strain and individual ambidexterity, we see that there is a positive correlation at the 0.1 level of analysis (r = 0.17).

Besides that individual ambidexterity correlates positively at the 0.1 level of significance with cognitive strain, it also correlates with some of the control variables. Individual ambidexterity correlated positively with formalization (r = .24, p <.01). This was

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expected, because according to Jansen et al., (2009) formalization positively influences exploitative innovation, which is one of the interaction variables to compute individual ambidexterity. Individual ambidexterity also positively correlated with environmental dynamism (r = .4, p<.01). This was also expected because environmental dynamism may influence to which extent an individual engages in exploration or exploitation activities or both (Good & Michel, 2013; Mom et al., 2009). Individual ambidexterity also positively correlated with exploitation (r = 75, p<.01) and exploration (r = .83, p<.01). This was also expected because individual ambidexterity is computed from the interaction between

exploration and exploitation. Therefore it makes sense that ambidexterity positively correlates with exploration and exploitation.

When we look at the relationship between the moderating variable social capital and the control variables we see that social capital is positively correlated with hierarchical status at the 0.1 level (r = .18). Besides this social capital also positively correlates with

formalization (r = .19). Social capital has a stronger correlation with environmental dynamism (r = .22). This can be explained because with high levels of environmental dynamism more knowledge and cooperation is needed, for which the relations on the work floor are used. Social capital also positively correlates with the two types of organizational learning

behaviors. Social capital is positively correlated to exploration (r = .42). When we look at the correlation between social capital and exploitation (r = .31). We see that this is positively correlated as well, only the correlation between social capital and exploitation is weaker than that of social capital and exploration. When we look at the moderating variable and the

independent variable, we see that social capital is moderate positive correlated with individual ambidexterity (r= .47). For the full set of the correlation, refer to table 1.

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26 Table 1. Descriptive statistics

N Mean S.D. 1 2 3 4 5 6 7 8 9 10 11 12 1. Cognitive strain 114 3.88 1.58 (.84) 2. Gender 113 1.42 0.50 .14 3. Hierarchical status 113 2.10 0.73 -.17* -.21** 4. Age 113 34.56 10.86 -.17* -.11 .47*** 5. Education 113 3.44 0.94 .05 .05 .05 .14 6. Formalization 150 2.68 0.96 -.11 -.14 .08 -.06 .115 (.78) 7. Tenure 113 5.96 0.90 -.15 -.14 .38*** .77*** -.004 -.09 8. Environmental dynamism 114 5.13 1.00 .42 -.07 .05 .21** .06 .09 .12 (.70) 9. Exploration 156 4.55 1.06 .15 -.11 .13 -.01 .05 .32*** -.11 .40*** (.79) 10. Exploitation 156 5.01 0.90 .11 -0.09 -.0.18 .04 .01 .032 .05 .20** .24*** (.76) 11. Individual ambidexterity 156 4.77 0.77 .17* -.134 .07 -.01 .03 .24*** -0.51 .40*** .83*** .75*** 12. Social capital 114 5.71 0.91 .07 -0.85 .18* -.01 .10 .19** -0.33 .22** .42*** .31*** .47*** (.78)

***. Correlation significant at the 0.01 level (2-tailed). ** Correlation significant at the 0.05 level (2-tailed). *. Correlation significant at the 0.1 level (2-tailed).

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Regression analysis

Table 2 presents a summary of the results of the hierarchical regression analysis. Model 1 shows the base model consisting only of the control variables. The independent variable is added in model 2 and the moderating effect is shown in model 3.

Model 1 shows the effect of the control variable gender, hierarchical status, age, education, formalization, tenure and organizational dynamism. Model 1 has a R² of .09. When we look at the result of the regression we can see that this model is not significant what means that the model is not a good fit. Also none of the control variables positively correlates with the dependent variable cognitive strain.

In order to test the first hypothesis, whether individuals that are ambidextrous experience higher levels of cognitive strain than individuals that are not ambidextrous, a hierarchical regression analysis was performed. Model 2 shows the results of this regression. The variance of cognitive explained by this model is 12% (R²= .12) at the level of .1

significance. When we look at the data we see that formalization has a negative relationship with cognitive strain (r = -.29) at the 0.1 level of significance. This is interesting because in the first model there was no significant relation between cognitive strain and formalization.

Furthermore we see that individual ambidexterity has a significant positive

relationship with cognitive strain (r =.45). This means that individuals that have a higher level of ambidexterity experience more cognitive strain than individuals that are not ambidextrous. This is in line with our first hypothesis which is thus supported.

The next hypothesis was whether social capital reduces the cognitive strain of an employee which is caused by ambidexterity. In order to test for the moderating effect of social capital the PROCESS by Hayes (2013) was used. The results of this analysis can be found in

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model 3. If we look at the Model we can see that the variance explained by this model is .03. Except that this is a low score the model is also not significant, meaning that social capital does not moderate the relationship between individual ambidexterity and the cognitive strain of an individual. Therefore the second hypothesis is not supported.

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*. Significant at the .1 level (2-tailed) **. Significant at the .05 level (2-tailed)

Table 2. Hierarchical regression model for cognitive strain

Model 1 Model 2 Model 3

Variables Control SE Main SE Interaction SE

Gender .30 .31 .35 .31 .35 .31 Hierarchical status -.15 .23 -.19 .23 -.19 .23 Age -0.3 .02 -0.03 0.02 -0.03 0.02 Education .15 .17 .15 .16 .15 .16 Formalization -.23 .16 -.29* .16 -.29* .16 Tenure .01 .04 .01 .04 .01 .04 Environmental dynamism .183 .15 .05 .17 .05 .17 Individual ambidexterity .45** .22 -.31 Social capital -,6 Individual ambidexterity x Social capital .12 Model F 1,423 1.799* 1.3132 R² .09 .12 .03 N 112 112 114

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Discussion

This research was set out to examine whether social capital could moderate the relationship between individual ambidexterity and cognitive strain. Overall, the results of the data analysis are not congruent with the predictions. While the first hypothesis whether individuals that are ambidextrous experience higher levels of cognitive strain than individuals that are not

ambidextrous was supported, was this not the case for the second hypothesis. Resulting in the rejection of the second hypothesis, which means that social capital does not moderate the relationship between individual ambidexterity and cognitive strain. This also means that cognitive strain can’t be used as a mechanism to minimize the cognitive strain in individual that pursuit ambidexterity.

In the current literature there has been a debate about the positive effects of

ambidexterity and the antecedents of ambidexterity. In doing so, scholars forget to look at the dark side of ambidexterity. With this study I tried to shed more light on this dark side of ambidexterity. The results show indeed that ambidexterity has a dark side in the form of cognitive strain. By testing the relationship between ambidexterity and cognitive strain, this paper was second paper to do so. The results were in line with the results as demonstrated by Keller and Weibler (2015). Next I tried to look more closely on this relationship and tried to find a mechanism that minimized the effect of ambidexterity on cognitive stain. According to the literature social capital could be a mechanism that minimized cognitive strain due to its nature in knowledge sharing. The data however showed that social capital does not moderate the relationship of individual ambidexterity and cognitive strain and thus can’t be used as a mechanism to minimize the cognitive strain that is caused by ambidextrous behavior.

A limitation in this study is the number of cases within the data. With more cases probably more variables would be significant and better predictions could be done.

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Conclusion

This research was set out to examine whether social capital could moderate the relationship between individual ambidexterity and cognitive strain. Overall, the results of the data analysis are not congruent with the predictions. While the first hypothesis whether individuals that are ambidextrous experience higher levels of cognitive strain than individuals that are not

ambidextrous was supported, was this not the case for the second hypothesis. Resulting in the rejection of the second hypothesis, which means that social capital does not moderate the relationship between individual ambidexterity and cognitive strain. This also means that cognitive strain can’t be used as a mechanism to minimize the cognitive strain in individual that pursuit ambidexterity.

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Individual ambidexterity and cognitive strain : the moderating effect of social capital