Ambidextrous leadership and innovation : the role of temporal flexibility

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AMBIDEXTROUS LEADERSHIP AND INNOVATION – THE ROLE OF

TEMPORAL FLEXIBILITY

Course: Master thesis

Author: Thais Taylor (10694412)

Date: 30-07-2016

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1 Statement of Originality

This document has been written by student Thais Taylor, who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document are 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

Ambidextrous leadership has recently emerged as an appropriate response to the challenge faced by organizations in promoting high levels of innovative performance in teams and individuals. Ambidextrous leadership theory suggests that the interaction of leaders’ open and closed behaviors will produce higher levels of innovation performance through the enactment of employees’ explorative and exploitative behaviors, with the condition that leaders have the ability to display temporal flexibility throughout the innovation process. The goal of this study was to extend the current research on this topic on the individual level of analysis, as well as to evaluate whether temporal flexibility of the leader is needed for achieving improved innovative performance within the framework of ambidextrous leadership. The data has been collected from self-reported survey responses from 111 individuals selected from an R&D organization and from a convenience sample. The results of this study did not fully support the hypotheses. However, the results suggested that open leader behaviors are related to employee explorative behaviors, and closed leader behaviors are related to employee exploitative behaviors. With respect to the innovative performance, the results indicated that only open leader behaviors are positively related to improved innovative performance and that this relationship is mediated by employee explorative behaviors. Limitations of the study are addressed and suggestions for future research are provided.

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1. INTRODUCTION

Innovation is a powerful force for organizational performance and has become increasingly relevant due to many factors such as rapid technological development and globalization (Drazin, Glynn, & Kazanjian, 1999; Mumford, Scott, Gaddis, & Strange, 2002; Tushman & O’Reilly, 1996). However, innovation is also a complex topic and poses a challenge for leaders in today’s organizations who are responsible for steering and managing the innovation process (Bledow, Frese, & Mueller, 2011). This complexity is brought about firstly by the different nature of the innovation tasks, which entails the generation of ideas and also its efficient implementation (Bledow, Frese, Anderson, Erez, & Farr, 2009; Gebert, Boerner, & Kearney, 2010). Idea generation, on one hand, is related to exploration and requires risk taking and experimentation (Bledow et al., 2011; March, 1991). On the other hand, idea implementation relates to exploitation and requires coordination and efficient execution (Bledow et al., 2011; March, 1991). These differences bring about conflicting demands for leaders who need to balance between the exploration and the exploitation of ideas throughout the innovation process (Bledow et al., 2009). Secondly, achieving innovation is considered complex because of the lack of linearity of the innovation process, which prompts the conflicting demands of exploration and exploitation to alternate throughout the innovation process without predictability (Anderson, De Dreu, & Nijstad, 2004; King, 1992; Rosing, Frese, & Bausch, 2011). In the past, it was common to depict the innovation process as a well-defined stage model which would provide a fixed framework to be followed, ranging from the initial stage of brainstorming of ideas (i.e. exploratory stage) until the implementation of the innovation (i.e. exploitative stage) (e.g. Zaltman, Duncan, & Holbek, 1973). However, more recently, researchers have challenged this idea by claiming that innovation unfolds in a spontaneous way and during each point in time in this process, it might be required to shift between exploring and exploiting (Anderson et al., 2004). Therefore, the complexity of

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5 innovation is a challenge for researchers and practitioners who aim to pursue a better understanding of the factors which can influence the achievement of higher levels of innovation in individuals, groups and organizations.

Leadership has been considered one of the most important drivers of innovation (Nemanich & Vera, 2009; Oke, Munshi, & Walumbwa, 2009; Yukl, 2009). However, it is not clear which specific leader behaviors or styles contribute to improved innovation (Bledow et al., 2011; Rosing et al., 2011). Meta-analysis has shown that different leadership behaviors can be positively related to innovation (Hulsheger, Anderson, & Salgado, 2009, cited by Bledow et al., 2011). Similarly, a recent meta-analytical review of the literature concerning leadership and innovation led to the conclusion that the most popular leadership theories (i.e. transformational, transactional, leader-member exchange, initiating structure, consideration, supervisor support and participative leadership) are not consistent in relation to innovation outcomes. This means that the correlations between leadership and innovation found in the previous literature vary within a wide range, which in turn challenges the reliability of those individual results (Rosing et al., 2011). For example, while transformational leadership has been positively linked to innovation by some researchers (e.g. Gong, Huang, & Farh, 2009; Shin & Zhou, 2003), the results of the meta-analysis suggested that transformational leadership can either foster or suppress innovation. Conversely, alternative studies which have captured the influence of more specific types of leadership behaviors in relation to creativity and innovation, such as supervisor support, either remain inconclusive or lack robust empirical support (Anderson et al., 2014; Rosing et al., 2011). This analysis has led researchers to suggest that mainstream leadership styles are too broad in order to tackle effectively the complementary leadership behaviors which can best enable innovation (Bledow et al., 2011; Rosing et al., 2011). Acknowledging the paradoxical nature of the innovation process and building upon the dialectic perspective of innovation (Bledow et al., 2009), Rosing et al. (2011) coined the

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6 ambidextrous leadership theory which specifically address the conflicting demands of innovation within one single leadership concept. Ambidextrous leadership refers to the ability of a leader to appropriately enact both open and closed leadership behaviors, which will influence explorative and exploitative employee behaviors along the innovation task, which in turn will contribute to improved innovative performance (Rosing et al., 2011). Although similar dichotomies of leadership behaviors and styles exists within the leadership literature, such as participative and directive leadership (Somech, 2006) task-oriented and relations oriented leader (Yukl, 2008), the distinction between open and closed leader behaviors brings about a tailor-made approach with the intention to explicitly influence the behaviors of exploration and exploitation in employees (Rosing et al., 2011). Ambidextrous leadership theory has been considered promising for advancing the literature of leadership and innovation, but empirical support is quite limited (Anderson, Potonik, & Zhou, 2014). To date, only a few studies have been conducted to support ambidextrous leadership’s effectiveness in promoting innovation (e.g. Zacher, Robinson, & Rosing, 2014; Zacher & Rosing, 2015; Zacher & Wilden, 2014). Although these studies have reported initial empirical support for the ambidextrous leadership theory in regards to innovation outcomes, none of these studies so far has taken into consideration the temporal flexibility feature of the ambidextrous leadership. That is, it is unclear whether temporal flexibility is needed to bring ambidextrous leadership’s positive effects on innovation to full fruition. This is surprising given that temporal flexibility has been theorized as the most important characteristic of ambidextrous leadership (Rosing et al., 2011).

This present study aims to contribute to the research on leadership and innovation firstly by investigating ambidextrous leadership in an R&D context, where innovation is the major business output. When compared to other business units such as factories, R&D can be considered to be the unit where the majority of employees are directly involved in producing innovation, and therefore the quality of innovation is emphasized as a performance outcome.

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7 As ambidextrous leadership is a tailor-made leadership approach for improving innovative performance, it is imperative to investigate its relevance within the context where innovation is very pertinent. In line with ambidextrous leadership, it is suggested that the interaction between the distinctive open and closed leadership behaviors, rather than each of these behaviors alone, will most positively relate to innovative performance (Figure 1a). Furthermore, drawing on the statement that leadership is a process of inducing people to attain a determined outcome (de Jong & Den Hartog, 2007), it is suggested that ambidextrous leader behaviors will lead to improved innovative performance by inducing employee behaviors of exploration and exploitation (Figure 1a). Secondly, this study further expands the knowledge on ambidextrous leadership by taking into account the role of the temporal flexibility of the leader by proposing a measure for this variable and investigating its relevance on the relationship between ambidextrous behavior and innovative performance (Figure 1b).

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2. HYPOTHESIS DEVELOPMENT

2.1 Ambidextrous leadership and innovative performance

Ambidexterity is a concept which has been used by organizational researchers in order to describe the ability of an organization to manage conflicting task demands in order to maintain the viability of its operations in the short and long term (Raisch & Birkinshaw, 2008). In the management literature, ambidextrous organizations have been praised as successful, as these are able to fulfill the efficiencies that short-term operations require while at the same time, being able to adapt effectively to changes in the environment in an effort to ensure performance in the longer-term (Raisch & Birkinshaw, 2008). The central feature of the ambidexterity concept is the reconciliation of internal tensions and conflicting demands of task environments (Raisch & Birkinshaw, 2008). This means that instead of opting solely for one direction or option when confronted with contradictions, the ambidextrous organization will tackle the complexity which is posed by conflicting demands by pursuing ways to settle opposing forces (Raisch & Birkinshaw, 2008). Similarly to the general complexity of organizations which inspired ambidextrous approaches, innovation is inherently characterized by contradictions, conflicting demands and opposing forces (Bledow et al., 2009; Gebert et al., 2010; Rosing et al., 2011; Sheremata, 2000). Innovation researchers have emphasized the distinction between two opposing features of innovation, describing the tasks of idea generation and idea implementation, as on one hand innovation requires the generation of high-quality ideas, and on the other hand, it requires these ideas to be effectively implemented, usually within time and budget constraints (Amabile, 1988; Mumford & Gustafson, 1988; Sheremata, 2000). Idea generation and idea implementation are contrasting activities because they pose conflicting demands on individuals, teams and organizations; as idea generation requires divergent thinking, variability and exploration of ideas, while idea implementation requires convergent thinking, consensus and exploitation of ideas (Bledow et al., 2009).

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9 In line with the ambidextrous concept, researchers have suggested that in order to foster innovation in organizations and teams, it is important to have a dialectic approach to innovation, and therefore combine opposing strategies, which would enable the creation of positive synergies and lead to improved innovation outcomes (Bledow et al., 2009; Gebert et al., 2010; Lewis, Welsh, Dehler, & Green, 2002; Sheremata, 2000). Sheremata (2000) describes two forces which are complementary for the process of innovation, namely centripetal and centrifugal forces, which together will effectively address the conflicting demands of innovation. Centrifugal forces are described as those which are directed outwards and are related to organic organizational structures, the increase of variance and the generation of ideas (Sheremata, 2000). Conversely, centripetal forces are directed inwards and are related to mechanistic organizational structures, the diminishment of variance and knowledge integration (Sheremata, 2000). The study argues that innovative output will be the highest when both of these forces are highly present in the organization (Sheremata, 2000). Within the context of innovative teams, arguing that the temporal separation between the conflicting features of innovation (i.e. knowledge generation and implementation) can be dysfunctional for the innovation process, Gebert et al. (2010) suggests that open and closed strategies (e.g. delegative and directive leadership, respectively) are complementary for fuelling team innovation. For example, directive leadership would be beneficial for aligning teams into coordinated implementation plans, while at the same time, it would increase the rigidity of teams which could result in less creative outputs (Gebert et al., 2010). Accordingly, delegative leadership can be beneficial for empowering team members in coming up with new ideas and solutions for problems, while at the same time, it can decrease the efficiencies of tasks which need to be coordinated (Gebert et al., 2010). Therefore, it is argued that the combination of these opposing action strategies into a single strategy, although paradoxical, would benefit innovative performance of teams through the generation of synergies (Gebert et al., 2010).

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10 Furthermore, these recent studies acknowledge that the leadership influence is important for enacting a paradoxical strategy, as leaders are able to influence and steer the behaviors of followers into appropriate directions (Gebert et al., 2010; Sheremata, 2000).

In line with the studies above, ambidextrous leadership emphasizes the integration of opposing strategies, with a focus on the behaviors of the leader as one of the main drivers of the innovation process (Rosing et al., 2011). The ambidextrous leader is capable of enacting high levels of open and closed leadership behaviors, which are enabled appropriately throughout the innovation process (Rosing et al., 2011). Open leadership behaviors are those which encourage employees to do things differently, boosting experimentation, promoting trial-and-error and independent thinking of subordinates (Rosing et al., 2011). In contrast, closed leadership behaviors are those which aim to reduce variance, such as, monitoring of performance, setting structure, providing guidelines and ensuring compliance (Rosing et al., 2011). This means that under high levels of open leader behaviors and low levels of closed leader behaviors, subordinates will be likely to express their independent creative thinking while being less likely to coordinate their efforts efficiently towards a common goal. Similarly, under low levels of open leader behaviors and high levels of closed leader behaviors, subordinates are likely to follow more efficient ways of working based on old established structures. However, under high levels of both open and closed leader behaviors, innovation will flourish, as subordinates will be steered not only towards creation, but also implementation. Therefore, in line with the ambidextrous leadership theory, the following hypothesis is proposed:

Hypothesis 1: There is an interactive relationship between open and closed leader behavior on innovative performance such that innovation will be highest when both open and closed leader behaviors are high rather than low.

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2.2 Employee exploration and exploitation

As stated by Yukl (2008), “leaders can improve the performance of an organization by influencing the performance determinants”; more specifically, the study states that leaders can influence their subordinates through their behaviors (Yukl, 2008). Therefore, leadership in the present study is understood as a process of inducing people to attain a determined outcome (de Jong & Den Hartog, 2007). Within ambidextrous leadership, open and closed leader behaviors are proposed to influence explorative and exploitative behaviors in employees respectively, which will lead to improved innovation performance (Rosing et al. (2011). Exploration and exploitation are concepts coined by March (1991) that originate in the organizational learning literature. March (1991) stated that in order to secure their survival, organizations should engage in both the exploration of the unknown and the exploitation of alternatives which are well known, as the careful balancing between exploring and exploiting would ensure prosperity and organizational survivor. Exploration refers to the search for the new, increased variation, experimentation, risk-taking, flexibility, discovery, adaptability and radical innovations (Gibson & Birkinshaw, 2004; Gupta, Smith, & Shalley, 2006; March, 1991; Tushman, Smith, Wood, Westerman & O’Reilly, 2010). Conversely, exploitation is related to the refinement of existing knowledge, diminishing variation, execution, efficiency, production and incremental innovation (Gibson & Birkinshaw, 2004; Gupta et al., 2006; March, 1991; Tushman et al., 2010). Building on the proposition of March (1991), organizational researchers have demonstrated that tackling both exploration and exploitation is the main characteristic of ambidextrous organizations that are successful in achieving innovation (e.g. He & Wong, 2004; Raisch & Birkinshaw, 2008). More recently, the concepts of exploration and exploitation have been extended to the individual level of analysis, as researchers have argued that the capacity of an organization to explore and exploit is rooted in the ability of employees to behave in explorative and exploitative ways (Mom, Van Den Bosch, & Volberda, 2007). Explorative

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12 activities have a long-term orientation and are focused on the variety of experience, such as looking for new ways of conducting tasks, experimenting with new technology, and re-evaluating existing norms (Mom et al., 2007). In contrast, exploitative activities have short-term orientation and are centered in creating reliability and efficiency, such as refining known concepts and improving existing competencies.

Ambidextrous leadership proposes that improved innovative performance stems from the ability of leaders to foster higher levels of exploration and exploitation in subordinates (Rosing et al., 2011). Therefore, it is proposed that employee exploration and exploitation are the mechanisms via which open and closed leader behaviors will influence improved innovative performance:

Hypothesis 2: The interactive effect between open and closed leader behaviors on innovative performance is mediated by employee explorative and exploitative behaviors.

2.3 Temporal flexibility of the leader

As described in the literature, the need to integrate conflicting demands is not the only factor contributing to the complexity of the innovation process, but also its lack of linearity. Non-linearity assumes that the innovation process is not composed of a series of steps that unfolds in a logical manner, but it is rather an iterative, cyclical and disjunctive process (Anderson et al., 2004; Godin, 2006). This means that demands of exploration and exploitation may alternate with little predictability, requiring leaders to flexibly adjust their behaviors according to the situation at hand (Anderson et al., 2004; Rosing et al., 2011). Due to this fact, researchers claim that the leader’s propensity to enact both open and closed behaviors is not enough to foster innovation, as these behaviors will need to be shown according to what a given

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13 situation requires (Rosing et al., 2011). In this way, the temporal flexibility of the leader, that is the ability of the leader to switch between behaviors according to the different innovation tasks in a given moment, is considered to be the essence of ambidextrous leadership (Lewis et al., 2002; Rosing et al., 2011).

The empirical examinations of the ambidextrous leadership framework so far have considered solely the ability of the leader to enact both open and closed behaviors (Zacher et al., 2014; Zacher & Rosing, 2015; Zacher & Wilden, 2014). However, the temporal flexibility of the leader has so far been neglected and has never been empirically tested. Previous studies have considered the concepts of managerial flexibility and leader behavior flexibility, which are similar to the definition of temporal flexibility (Jones, Rafferty, & Griffin, 2006; Zaccaro, Gilbert, Thor, & Mumford, 1991). Within this previous research, it has been suggested that the levels of managerial flexibility can vary among individuals (Jones et al., 2006). As explained by Raudsepp (1991) more flexible individuals are able to explore a wider range of responses and tactics to deal with a situation while maintaining their focus on their main goal, while less flexible individuals are more focused on stability and may not cope so well with changing environments. Furthermore, social intelligence research suggests that successful leaders are those able to accurately perceive the social environment around them and to display behavioral flexibility (Zaccaro et al., 1991). The concept of leader behavior flexibility is defined by Zaccaro et al. (1991) as the ability and willingness of the leader to respond in significantly different ways to correspondingly different situational requirements. Leader behavioral flexibility is determined not only by the leaders’ access to a wide behavioral repertoire but as also by their cognitive capacity to adapt and match behaviors to a particular environmental demand (Zaccaro et al., 1991). Similarly, within the context of ambidextrous leadership and innovation, it is suggested that a leader must be able to demonstrate higher levels of temporal flexibility in order to adapt his or her specific behaviors purposefully, according to

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14 the continuously changing demands of the innovation process (Bledow et al., 2011; Rosing et al., 2011). Therefore, in line with the theoretical framework of ambidextrous leadership, I propose that the temporal flexibility of the leader positively influences employee innovative performance.

Hypothesis 3: Leader temporal flexibility moderates the interactive relationship between employee exploration and exploitation behavior and innovation such that innovation will be highest when leader temporal flexibility, explorative and exploitative employee behaviors are high rather than one or more of these variables being low.

3. METHOD

3.1 Sample and procedure

Data for this study came from a combination of two samples, totaling 111 participants who were recruited in two different ways. The first sample consists of 72 employees of an international R&D center operating in the fields of infant and medical food industry, distributed among departments of life science research, technology development, and support functions. Access to the sample of respondents and e-mail addresses of employees have been requested via the management team and works council of the center. Within the R&D center, a total of 213 employees have been approached via e-mail to respond to an online questionnaire via Qualtrics survey tool and 72 employees have fully completed the questionnaire, resulting in a response rate of 33.8%. The second sample consists of 39 respondents and is a convenience sample, in which respondents have been recruited via social media. The only two requirements for participation were that respondents had to be employed and reporting to a manager. The equivalent questionnaire has been made available on social media, containing minor adaptations in order to incorporate the questions regarding the conditions for eligibility for participation (i.e. being an employee and reporting into a manager). In order to motivate

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15 participation, respondents could opt to participate in the draw for winning a dinner voucher. Data anonymity was assured by detaching this information from the sample of responses prior to its analysis.

In the total combined sample, 38 (34.2%) of respondents were male and 73 (65.8%) were female. The age distribution of participants ranged from 18 to 54 years, with an average of 33.07 years (SD = 7.16), while two respondents did not report their age. The majority of respondents had a master or postgraduate university degree (61; 55%), followed by a bachelor or undergraduate degree (28; 25.2%), 18 (16.2%) respondents held a Ph.D. and 4 (3.6%) respondents held a secondary education or high school. Among the respondents from the R&D center, 56 (77.78%) have reported an educational background, the vast majority deriving from food technology education (26; 46.43%), followed by participants deriving from an education related to nutrition (13; 23.21%), 10 (17.86%) respondents originate from biology or biomedical sciences education, 5 (7.14%) reported a background in business, design, and legal education and 3 (5.36%) respondents reported an education background in the field of chemistry. Within the convenient sample, a total of 29 (74.36%) respondents reported their educational backgrounds to be in the fields of business management (15; 51.72%), engineering (3; 10.34%), law (3; 10.34%), architecture & urban planning (2; 6.90%), communications (2; 6.90%), anthropology (1; 3.45%), food science (1; 3.45%), informatics (1; 3.45%) and psychology (1; 3.45%).

3.2 Measures

Innovation. Respondents were asked to rate themselves regarding their own innovation

performance. The four-item scale from Welbourne, Johnson, and Erez (1998) has been used, as it has been considered a well-validated measure by leadership researchers (e.g. Bono & Judge, 2003; Zacher & Rosing, 2015). Based on these previous studies, a five-point scale ranging from 1 (needs much improvement) to 5 (excellent) was used to collect answers.

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Open and closed leadership behaviors. Respondents were asked to rate their team

leaders on the scale developed by Zacher et al. (2015) consisting of fourteen items, half dedicated to assessing open leadership behaviors and seven dedicated to assessing closed leadership behaviors. In line with this previous study, answers were available on a 5-point scale ranging from 1 (not at all) to 5 (frequently, if not always). The developers have conducted an exploratory factor analysis and gained initial evidence for the validity of the scale (Zacher et al., 2015).

Employee exploitative and explorative behaviors. Respondents were asked to rate

themselves in regards to the extent to which they engage in explorative and exploitative behaviors, on eleven items developed by Mom, Van Den Bosch, and Volberda (2007). Five items were dedicated to explorative behaviors and six to exploitative behaviors, for which answers were provided on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree), in line with the developers’ study. In addition, this scale has been used by (Zacher et al., 2014) in the context of ambidextrous leadership.

Temporal flexibility of the leader. I developed a measure of temporal flexibility of the

leader for the purpose of this study. The first item “Ability to adapt his/her personal approach

to the situation at hand” is adapted from the measure of individual flexibility from Jones,

Rafferty, and Griffin (2006). The following two items “Flexibly employs different approaches

which are relevant to what I need” and “Demonstrates variability in behaviors when dealing with different types of problems” have been developed proposed by the study. Answers have

been collected on a seven-point scale ranging from 1 (strongly disagree) to 7 (strongly agree), according to the first item’s original measurement.

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3.3 Control variables

Sample of respondents. This categorical variable indicates whether respondents are part

of the R&D sample of respondents, which responses have been collected within a known R&D center or the convenient sample, which responses have been collected from social media channels.

Demographic variables. Respondents have reported their age, gender (female, male).

3.4 Analytical strategy

The data representative of 111 respondents has been collected digitally using Qualtrics survey tool. The data has been downloaded into SPSS so that it could be analyzed. Firstly, in order to check for missing variables, a frequency test has been applied to all scale variables, which reported two missing items within the variable “age” of the dataset. These missing items have been given a particular number (999), which signalizes the absence of the response of the two participants. Following this preliminary analysis, the scale means have been computed for constructs of interest, namely open leadership behavior, closed leadership behavior, employee explorative behavior, employee exploitative behavior, temporal flexibility of the leader, and employee innovative performance, Once the scale means were computed, they have been subjected to normality checks, for which descriptive statistics have been used, namely skewness and kurtosis have been analysed. Regarding kurtosis, all variables are between -0.5 and 0.5, which indicates that there is no extreme positive or negative kurtosis in the variables. Regarding skewness, two variables have demonstrated to be moderately negative skewed, namely open leadership behavior (-0.703) and temporal flexibility of the leader (-0,845). Besides these variables, the remaining variables are considered normally distributed, with skewness values ranging between -0.5 and 0.5. Even though new variables could be created via transformation, the original variables have not been transformed, as stated by Tabachnick

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18 and Fidell (2001) reasonably large samples would not be substantially impacted from skewness in the analysis.

All variable constructs have been subjected to reliability analysis, which confirmed a Cronbach’s alpha above 0.7. Only one variable, namely employee exploitative behavior, has reported a Cronbach’s alpha below 0.7 being α = 0.688 when all original items had been considered as part of the construct. Deleting one item “I engage in activities primarily focused on achieving short-term goals” could have improved internal consistency. However, as the final construct would report a minor increase of 0.026 (α = 0.714) the original variable has been used in the study and no items have been discarded.

4. RESULTS

4.1 Descriptive Statistics

Table 1 provides the mean, standard deviation, correlation and Cronbach’s alpha of this study’s variables. Closed leader behavior (BE), temporal flexibility of the leader and employee exploitative BE were not related to employee innovative performance. Innovative performance was positively related to open leader BE (r = 0.22, p < .05) and employee explorative BE (r = 0.47, p < .01). In addition, open leader BE was positively correlated with leader temporal flexibility of the leader (r = 0.63, p < .01) and employee explorative BE (r = 0.31, p < .01). Also, temporal flexibility of the leader was positively related to employee explorative BE (r = 0.23, p < .05).

It has been checked whether the respondents within the two samples (R&D and convenience) were similar in the way they evaluate their leaders in regards to open and closed BEs and temporal flexibility, and themselves in regards to explorative and exploitative BEs and innovative performance. Significant differences have been found in the way employees from the two samples reported open leader BEs, where the R&D sample reported higher levels

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19 of leader open BEs (R&D: M = 3.88, SD = 0.60; convenient: M = 3.33, SD = 0.78), F(1, 109) = 5.06, p < .05, n2 = _{.04, and temporal flexibility of the leader (R&D M = 5.07, SD = 1.03;}

convenient M = 4.5, SD = 1.31), F(1, 109) = 6.05, p < .05, n2 = .05. No significant differences have been found in relation to which employees in both samples evaluated closed leader BE

F(1, 109) = 0.89, p =.35, n2 = .01 employee explorative BE F(1, 109) = 0.43, p = .51, n2 = .00 employee exploitative BE F(1, 109) = 2.99, p = .09, n2 = .03, and innovative performance F(1, 109) = 0.00, p = .98, n2 = _.00.

Table 1.

Means, Standard Deviations, Correlations

Note. N = 111. Male was coded “0”, Female was coded “1”. Sample of respondents from R&D was coded “0”, from convenience “1”.

* p < .05; ** p < .01.

4.2 Hypotheses testing

The hypotheses of this study have been tested by using hierarchical regression analysis (Cohen, Cohen, West, & Aiken, 2013). Initially, independent, mediators, moderator and control variables were centered by subtracting their mean values. Thereafter, the multiplicative interaction terms which were used in the regression equations of this study have been computed.

Variables M SD 1 2 3 4 5 6 7 8

1. Age 33.06 7.16

2. Gender 0.66 0.48 *-0.21

3. Sample of respondents 0.35 0.48 **0.32 0.09

4. Open leader behavior 3.77 0.68 0.05 0.08 *-0.21 (.86)

5. Closed leader behavior 3.24 0.57 0.04 0.01 -0.09 0.01 (.69)

6. Temporal flexibility of the leader 4.87 1.16 -0.30 0.05 *-0.23 **0.63 0.14 (.81)

7. Employee explorative behavior 4.07 0.49 -0.04 0.05 0.06 **0.31 0.05 *0.23 (.73)

8. Employee exploitative behavior 3.82 0.54 -0.01 *0.21 0.14 0.14 0.14 0.06 0.07 (.71)

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Table 2.

Results of Hierarchical Regression Analyses with Innovative Performance as Outcome

Note. N = 111. Male was coded “0”, Female was coded “1”. Sample of respondents from R&D was coded “0”, from convenience “1”.

* p < .05; ** p < .01.

Hypothesis 1 stating that there is an interactive relationship between open and closed leader BE on innovative performance such that innovation will be highest when both open and closed leader BEs are high rather than low, has been tested via a two-way interaction between open leader BE and closed leader BE in relation to employee innovative performance. Results are reported in Table 2 steps one, two (a) and three (a). In the first step, the control variables of age, gender, and sample of respondents were entered into the regression equation. The variable age was significantly positively related to innovative BE (β = 0.21, p < 0.05), whereas the other control variables did not have significant effects, gender (β = 0.06, p = .58) and sample of respondents (β = 0.08, p = .46). During step two (a), the variables of open and closed leadership BEs were entered. Open leader BE was significantly and positively related to innovative performance (β = 0.24, p < 0.05), while closed leadership BE did not have a

Step 1 Step 2 (a) Step 2 (b) Step 3 (a) Step 3 (b) Step 4

Outcome: Innovative performance

Step 1: Control

Age *0.21 (0.08) *0.20 (0.07) *0.20 (0.07) *0.21 (0.08) *0.23 (0.07) *0.23 (0.07)

Gender 0.06 (0.15) 0.03 (0.15) 0.03 (0.15) 0.03 (0.15) 0.03 (0.14) 0.03 (0.14)

Sample of respondents 0.08 (0.15) 0.13 (0.16) 0.13 (0.15) 0.13 (0.16) 0.1 (0.15) 0.10 (0.15)

Step 2a: Main effects

Open leader behavior *0.24 (0.07) *0.24 (0.07)

Closed leader behavior -0.01 (0.07) -0.00 (0.07)

Step 2b: Main effects

Employee explorative behavior **0.44 (0.07) 0.66 (0.30) 0.66 (0.30)

Employee exploitative behavior -0.11 (0.06) 0.23 (0.25) 0.23 (0.26)

Temporal flexibility of the leader 0.09 (0.07) 0.09 (0.07) 0.09 (0.07)

Step 3a: Two-way interactions

Open leader behavior x Closed leader behavior -0.03 (0.08)

Step 3b: Two-way interactions

1. Employee explorative behavior x Employee exploitative behavior 0.01 (0.05) -0.01 (0.25)

2. Employee explorative behavior x Temporal flexibility of the leader -0.22 (0.06) -0.22 (0.06)

3. Employee exploitative behavior x Temporal flexibility of the leader -0.35 (0.05) -0.35 (0.05)

Step 4: Three-way interaction

4. Employee explorative behavior x Employee exploitative behavior x

Temporal flexibility of the leader 0.02 (0.05)

R² 0.04 0.09 0.27 0.09 0.28 0.28

F 1.34 2.09 *6.20 1.74 *4.23 *3.77

ΔR² 0.04 0.06 0.23 0.00 0.01 0.00

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21 significant effect (β = -0.01, p = .91). Lastly, during step three (a) of the regression equation, the interaction term, open leader BE x closed leader BE, was entered, and additional variance has failed to be explained (ΔR² = .001, p = .12), and the relationship between the interaction of open and closed leader BEs and innovative performance was not significant (β = -0.03, p = .80). An additional bootstrap procedure has been followed in order to test Hypothesis 1, by using the PROCESS macro for SPSS, specifying 1000 bootstrap samples, bias-corrected bootstrap confidence internal method and 95% confidence intervals (Hayes, 2012). For the bootstrap procedure, the unstandardized regression coefficients are used.The control variables of age, gender, and sample of respondents were entered into the model 1 of PROCESS macro for SPSS (Hayes, 2012), simultaneously with the independent variables of open and closed leadership BEs and the dependent variable innovative performance. The relationship between the interaction of open and closed leader BEs and innovative performance was non-significant (b = -0.05, p = .80), and therefore Hypothesis 1 has been rejected.

In order to test Hypothesis 2, a mediation analysis has been carried out by estimating the indirect effect of the relationship between the interaction between open and closed leader BEs on innovative performance through employee explorative and exploitative BEs (Field, 2013).

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22 A bootstrap procedure has been conducted in order to analyze Hypothesis 2 (Hayes, 2012). This procedure has been conducted by entering the control variables (i.e. age, gender and sample of respondents), the independent variable (i.e. interactive term of open and closed leader BEs), the two mediators (i.e. employee explorative and exploitative BEs) and the dependent variable (i.e. innovative performance) in model four of PROCESS for SPSS (Hays, 2009). The relationship between the interactive term of open and closed leader BEs and employee explorative BEs were significant (b = 0.04, SE = 0.01, p < .05), and the relationship between employee explorative BE and innovative performance were also significant (b = 0.68,

SE = 0.13, p < .01), which represents path a and b of Figure 2. The indirect effect ab for the

mediator employee explorative BE was significant (Sobel’s Z = 2.52, p < .05), which partially supports hypothesis 2. The relationship between the interactive term of open and closed leader BEs and employee exploitative BE was significant (b = 0.04, SE = 0.01, p < .05), which represents path a of Figure 2. However, the relationship between employee exploitative BE and innovative performance was non-significant (b = -0.15, SE = 0.13, p = .24), which represents path b of Figure 2. Therefore, no indirect effect has been found for employee exploitative BE as a mediator of the relationship proposed by Hypothesis 2. Hypothesis 2 is partially supported, as the interactive relationship between open and closed leader BEs and innovative performance is only mediated by employee explorative BE.

Hypothesis 3 has been tested via hierarchical regression analysis which proposes a three-way interaction between employee explorative BE, employee exploitative BE and temporal flexibility of the leader such that employee innovative performance will be the highest when all three independent variables are high rather than low. Results are reported in table 1 steps one, two (b), three (b) and 4. The variables employee explorative BE, employee exploitative BE and temporal flexibility of the leader have been entered in step two (b). Employee explorative BE was positively and significantly related to innovative performance

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23 (β =0.44, p < 0.01), whereas employee exploitative BE (β = -0.11, p = .24) and temporal flexibility of the leader (β = -0.09, p = .31) did not have a significant effect. During step three (b) of the regression equation, the interaction terms, employee explorative BE x employee

exploitative BE, employee explorative BE x temporal flexibility of the leader and employee exploitative BE x temporal flexibility of the leader, were entered, and none of them have a

significant effect (XXX β = 0.01, p = .91; XXX β = -0.22, p = .59; XXX: β = -0.35, p = .32) respectively, and additional variance has failed to be explained (ΔR² = .01, p = .67). Lastly, the interaction term 4, representing the three-way interaction was entered (employee explorative

BE x employee exploitative BE x temporal flexibility of the leader), for which no significant

effect has been found (β = 0.02, p = .90).

An additional bootstrap test has been conducted in order to test Hypothesis three. For the bootstrap analysis, the unstandardized regression coefficients are reported. The control variables of age, gender, and sample of respondents were entered into the model 3 of PROCESS macro for SPSS (Hayes, 2012), simultaneously with the independent variables of employee explorative and exploitative BEs and temporal flexibility of the leader, and the dependent variable innovative performance. The bootstrap analysis has shown a positive significant relationship in regards to the effect of the control variable age with innovative performance (b = 0.24, p < .05), and employee explorative BE and innovative performance (b = 0.66, p < .001). The remaining variables and interaction terms were non-significantly related to the outcome variable, gender (b = 0.05, p = .71), sample of respondents (b = 0.15, p = .32), employee exploitative BE (B = -0.17, p = .92), the interaction of employee explorative BE and employee exploitative BE (b = 0.03, p = .98 ), the interaction of employee explorative BE and temporal flexibility of the leader (b = -0.07, p = .89), the interaction of employee exploitative BE and temporal flexibility of the leader (b = -0.10, p = .87) and the interaction of employee explorative

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24 BE, employee exploitative BE and temporal flexibility of the leader (b = 0.01, p = .97). Therefore, Hypothesis 3 has been rejected.

4.3 Additional analysis

Additional tests have been conducted in order to further explore the relationships between open leader BE, employee explorative BE and innovative performance, as well as open and closed leader BEs and employee exploitative BEs, always taking into consideration the control variables of age, gender, and sample of respondents. I have investigated whether open leader BEs will have a relationship with employee explorative BE, as well as whether employee explorative BE mediates the relationship between open leader BEs and innovative performance. Furthermore, the direct relationship between open and closed leader BEs and employee explorative and exploitative BE has also been explored.

Figure 3: Additional analysis

A bootstrap procedure has been conducted for this additional analysis. This procedure has been conducted by entering the control variables (i.e. age, gender and sample of respondents), the independent variable, open leader BE, the mediator, employee explorative BE, and the dependent variable, innovative performance, in model four of PROCESS for SPSS (Hays, 2009). Open leader BE is significantly positively related to employee explorative BEs

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25 (b = 0.26, p < .001). In addition, employee explorative BEs fully mediates the relationship between open leadership BEs and innovative performance (Sobel’s Z = 2.96, p < .01).

Although this study has failed to show that there is a relationship between the closed leader BE and innovative performance, as well as employee exploitative BEs with innovative performance, as the last consideration, it is interesting to investigate whether open and closed leader BEs are related to employee exploitative BEs. Results have demonstrated that closed leader BE is significantly positively related to employee exploitative BEs (B = 0.19, p < .05), while the significance was not observed for the relationship between open leader BE and employee exploitative BE (B = 0.12, p = .21).

5. DISCUSSION

Ambidextrous leadership has been proposed to be a matching response to the complexity posed by innovation (Bledow et al., 2011; Rosing et al., 2011). It is argued that the interaction of two distinct leadership behaviors, namely open and closed behaviors, will specifically steer behaviors of exploration and exploitation in employees which are both required for innovation (Rosing et al., 2011). The ability of leaders to show temporal flexibility has been theorized as being the most important feature of ambidextrous leadership, as this flexibility will allow the leader to adapt open and closed behaviors appropriately throughout the innovation process (Rosing et al., 2011). Although some preliminary studies have found support for the beneficial effects of ambidextrous leadership (Zacher et al., 2014; Zacher & Rosing, 2015; Zacher & Wilden, 2014), this theory has not yet been tested in many different contextual settings, likewise, the concept of temporal flexibility, has never been taken into consideration in these previous studies. This present research aimed to provide extended empirical support to the ambidextrous leadership theory, by using a different sample of

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26 respondents and by investigating whether temporal flexibility indeed plays a role in enhancing the effects of ambidextrous leadership on innovative performance.

The ambidextrous leadership literature suggests that open leader behavior will instill employee explorative behaviors, while closed leader behavior will instill exploitative behavior (Rosing et al., 2011). In line with this idea, present results show that open leader behaviors can encourage employees to behave in an explorative way. For example, by allowing errors and giving their employees space to come up with their own ideas, leaders may influence followers to demonstrate higher levels of adaptability and engagement in the search for new ways to approaching tasks. Equally, it has been shown that leaders behaving in a closed way will steer exploitative behaviors in their employees. For example, by establishing routines and monitoring goal achievement, leaders would be instilling followers to accumulate experience and to focus on short-term goals. However, the ambidextrous leadership theory specifies that in order to achieve improved innovation, high levels of both open and closed leader behaviors need to be present (Rosing et al., 2011). This interactive effect of leader behaviors on innovation has not been observed in the context of this study. The interactive relationship between open and closed leader behaviors was only significantly related to innovative performance once fully mediated by employee explorative behaviors.

Previous evidence for the ambidextrous leadership has been found, supporting the suggestion that high levels of both open and closed leader behaviors will lead to higher levels of innovative performance (Zacher & Rosing, 2015), but these results could not be replicated in this research. Although the present findings are not in line with the hypothesized effects, previous research on leadership and innovation has also led to similar results found in this study. For example, Somech (2006) defends that participative leadership rather than directive leadership is associated with team innovation. Participative, leaders are prone to demonstrating open behaviors, such as encouraging experimentation with new ideas, which have been related

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27 to team innovation (Somech, 2006). On the other hand, directive leadership which is more in line with the closed behaviors proposed by this study has been positively related to the in-role performance, but not the innovative performance of these teams (Somech, 2006). Furthermore, studies conducted with R&D teams have demonstrated that leadership styles related to open behaviors (e.g. considerate, consultative) have been significantly related to innovation, while leadership styles focused on more closed behaviors (e.g. initiating structure) have not presented the same evidences (Stoker, Looise, Fisscher, & Jong, 2001). This suggests that open leader behaviors are more consistently related to innovation, while the influence of closed behaviors on innovation might be dependent on other factors, such as the context in which innovation takes place. For example, previous evidence for the positive effects of ambidextrous leadership on innovation has been found using a sample of employees coming from architectural and interior design firms (Zacher & Rosing, 2015). Whereas evidence for the effect of open types of leadership behaviors on innovation have been found in the educational (Somech, 2006) and R&D sectors (Stoker et al., 2001). The similarity between R&D professionals and teachers might be the distance of this specific group of employees from commercial operations, while both are strongly involved with the creation of content and products. Therefore, in this study, the fact that the majority of the respondents come from R&D employees might have contributed to the lack of hypothesized effect.

Temporal flexibility in this study has failed to provide additional explanation to the ambidextrous leadership theory, as there were no significant effects observed, even though it positively correlated with open leader behavior innovative performance.

5.1 Limitations and further research

This present study has several limitations to be addressed, as well as important suggestions for further research. Firstly, the sample size of this study was relatively small, with

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28 111 participants, which reduced the power to differentiate statistically significant effects (Field, 2013). Though similar leadership studies which involve interactive effects have been conducted with small sample sizes (e.g. Zacher & Rosing, 2015), future studies can benefit from larger sample sizes. Another limitation regarding the sample is the fact that 35% of responses have been collected via a convenience sample and have been merged to the remaining sample originated from R&D responses, which brought about heterogeneity to the total sample. These differences have been accounted for by creating a control variable “sample of respondents”.

Second, data has been collected from single-source employee self-reports which are subjected to bias, for example, due to self-enhancement bias and social desirability (Saunders, Lewis & Thornhill, 2012). In regards to the assessment of leader behaviors, Yukl (1994) suggested the use of follower’s perception in order to explore the influence of leadership on organizational outcomes, supporting the approach taken by this study. On the other hand, as the remaining variables of this study have been based on employee self-assessment, common-method bias is also a potential problem which may artificially result in overestimated correlations between variables (Mackenzie & Podsakoff, 2008). As pointed by Zacher et al. (2014), there is a disagreement among researchers in regards to the ability of the employee to self-rate their innovative performance, for example Shalley, Gilson, and Blum (2009) believe that followers should be capable of rating their own innovative performance, while Nemeth and Ormiston (2007) have found disparities between perceived and objective performance measures of creativity. Therefore, future research may opt to measure innovative performance in a more objective way, by either asking supervisors or experts to rate the innovative performance of employees or by obtaining access to relevant reports.

Third, even though this study presents associations between variables, the causality in those relationships might not be implied, due to the cross-sectional design applied. Although it

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29 can be argued that leader behaviors will have an influence on follower behaviors (Yukl, 2008), future studies might benefit from a longitudinal design so that the direction of the proposed relationships can be identified.

Fourth, the lack of a validated measure of the variable temporal flexibility may be criticized. Temporal flexibility of the leader correlated strongly with open leader behaviors in this study, which might point a problem in the measurement of this variable. Even though this has been the first attempt to test ambidextrous leadership by taking into consideration the temporal flexibility of the leader as perceived by employees, future studies could benefit from other measures which have been validated by previous studies or different ways of measuring temporal flexibility (e.g. measuring leader behavior over time). As well, future research might look into the social intelligence levels of leaders and investigate whether it is related to the leader’s ability to demonstrate temporal flexibility due to the similarity of this concepts. Social intelligent leaders are those able to accurately perceive the social environment around them and to display behavioral flexibility (Zaccaro et al., 1991), and therefore might be able to demonstrate temporal flexibility throughout the innovation process.

Furthermore, future research should emphasize contextual factors which might have an impact on the ability of the ambidextrous leader in promoting innovation. For example, the present study has been conducted in the Netherlands, where levels of power-distance are relatively low, compared to countries such as Brazil where power-distance levels are relatively high (Hofstede, Hofstede, & Minkov, 1991). This difference suggest that in Brazil managers usually take complete responsibility for matters, and hierarchy is much more respected than in the Netherlands, where managers are expected to consult with their employees, and the communication between manager and employees are informal and participative, which in turn can be linked to natural tendencies of these leaders towards open and closed behaviors (Hofstede, Hofstede, & Minkov, 1991). Therefore, it is important to extend the research on

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30 ambidextrous leadership to other countries, regions, and industries, so that relevant contextual and cultural differences can be explored.

6. CONCLUSION

Innovation is an important but complex challenge for organizations, due to the different nature of its task demands, as well as for the high level of unpredictability of the innovation process (Rosing et al., 2011). Increasingly, researchers have been proposing an integrative approach to the opposite forces which are inherent in the innovation process (e.g. Bledow et al., 2011; Gebert et al., 2010; Sheremata, 2000), and the ambidextrous leadership style is one of this latest approaches, which suggests specific open and closed leader behaviors which combined with temporal flexibility of leaders will lead to improved innovative performance of individuals and teams (Zacher & Rosing, 2015). The aim of this research was to extend the knowledge on this novel leadership style in a different environmental context and to investigate whether temporal flexibility of the leader is needed for achieving higher levels of innovative performance. Despite some methodological limitations, the results presented in this study support the proposition made by Rosing et al. (2011) that open leader behaviors and closed leader behaviors will each influence one type of employee behavior, namely employee explorative or exploitative behaviors respectively. However, the hypothesized effect, that the combination of high open and closed leader behaviors would be more positively related to innovative performance, is not observed in this study. As well, differently than what has been hypothesized, the interactive relationship between open and closed leader behaviors relates to innovative performance only when mediated through employee explorative behaviors. These present results stress the importance of open leader behaviors in promoting explorative behavior in employees which is the mechanism via which innovative performance is positively

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31 impacted. Using a preliminary measure of temporal flexibility of the leader, temporal flexibility did not moderate the interactive relationship between employee explorative and exploitative behaviors and innovative performance. In conclusion, this study has contributed to the research on ambidextrous leadership and innovation and I hope that the challenges and suggestions reported in this study will be helpful for future studies in this field.

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REFERENCES

Amabile, T. M. (1988). A model of creativity and innovation in organizations. Research in

organizational behavior, 10(1), 123-167.

Anderson, N., De Dreu, C. K. W., & Nijstad, B. A. (2004). The routinization of innovation research: a constructively critical review of the state-of-the-science. Journal of

Organizational Behavior, 25(2), 147–173.

Anderson, N., Poto nik, K., & Zhou, J. (2014). Innovation and Creativity in Organizations: A State-of-the-Science Review, Prospective Commentary, and Guiding Framework.

Journal of Management, 40(5), 1297–1333.

Bledow, R., Frese, M., Anderson, N., Erez, M., & Farr, J. (2009). A Dialectic Perspective on Innovation: Conflicting Demands, Multiple Pathways, and Ambidexterity. Industrial

and Organizational Psychology, 2(3), 305–337.

Bledow, R., Frese, M., & Mueller, V. (2011). Ambidextrous leadership for innovation: the influence of culture. Advances in Global Leadership, 6, 41–49.

Bono, J. E., & Judge, T. A. (2003). Self-concordance at work: Toward understanding the motivational effects if transformational leaders. Academy of Management Journal,

46(5), 554–571.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied Multiple

Regression/Correlation Analysis for the Behavioral Sciences. Routledge.

de Jong, J. P. J., & Den Hartog, D. N. (2007). How leaders influence employees’ innovative behaviour. European Journal of Innovation Management, 10(1), 41–64.

Drazin, R., Glynn, M. A., & Kazanjian, R. K. (1999). Multilevel Theorizing About Creativity in Organizations: A Sensemaking Perspective. Academy of Management Review, 24(2), 286–307.

Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.

Gebert, D., Boerner, S., & Kearney, E. (2010). Fostering Team Innovation: Why Is It Important to Combine Opposing Action Strategies? Organization Science, 21(3), 593– 608.

Gibson, C. B., & Birkinshaw, J. (2004). The Antecedents, Consequences, and Mediating Role of Organizational Ambidexterity. Academy of Management Journal, 47(2), 209–226. Godin, B. (2006). The Linear model of innovation the historical construction of an analytical

framework. Science, Technology & Human Values, 31(6), 639-667. Gong, Y., Huang, J.-C., & Farh, J.-L. (2009). Employee Learning Orientation,

Transformational Leadership, and Employee Creativity: The Mediating Role of Employee Creative Self-Efficacy. Academy of Management Journal, 52(4), 765–778. Gupta, A. K., Smith, K. G., & Shalley, C. E. (2006). The Interplay Between Exploration and

Exploitation. Academy of Management Journal, 49(4), 693–706.

Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable

mediation, moderation, and conditional process modeling [White paper]. Retrieved from http://www.afhayes.com/ public/process2012.pdf

(34)

33 He, Z. L., & Wong, P. K. (2004). Exploration vs. exploitation: An empirical test of the

ambidexterity hypothesis. Organization science, 15(4), 481-494.

Hofstede, G., Hofstede, G. J., & Minkov, M. (1991). Cultures and organizations: Software of

the mind (Vol. 2). London: McGraw-Hill.

Jones, R. A., Rafferty, A. E., & Griffin, M. A. (2006). The executive coaching trend: towards more flexible executives. Leadership & Organization Development Journal, 27(7), 584– 596.

King, N. (1992). Modelling the innovation process: An empirical comparison of approaches.

Journal of Occupational and Organizational Psychology, 65(2), 89–100.

Lewis, M. W., Welsh, M. A., Dehler, G. E., & Green, S. G. (2002). Product Development Tensions: Exploring Contrasting Styles of Project Management. Academy of

Management Journal, 45(3), 546–564.

Mackenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: causes, mechanisms, and procedural remedies. Journal of Retailing, 88(4), 542-555.

March, J. G. (1991). Exploration and Exploitation in Organizational Learning. Organization

Science, 2(1), 71–87.

Mom, T. J. M., Van Den Bosch, F. A. J., & Volberda, H. W. (2007). Investigating Managers’ Exploration and Exploitation Activities: The Influence of Top-Down, Bottom-Up, and Horizontal Knowledge Inflows. Journal of Management Studies, 44(6), 910–931. Mumford, M. D., & Gustafson, S. B. (1988). Creativity syndrome: Integration, application,

and innovation. Psychological Bulletin, 103(1), 27–43.

Mumford, M. D., Scott, G. M., Gaddis, B., & Strange, J. M. (2002). Leading creative people: Orchestrating expertise and relationships. The Leadership Quarterly, 13(6), 705–750. Nemanich, L. A., & Vera, D. (2009). Transformational leadership and ambidexterity in the

context of an acquisition. The Leadership Quarterly, 20(1), 19–33.

Nemeth, C. J., & Ormiston, M. (2007). Creative idea generation: harmony versus stimulation.

European Journal of Social Psychology, 37(3), 524–535.

Oke, A., Munshi, N., & Walumbwa, F. O. (2009). The Influence of Leadership on Innovation Processes and Activities. Organizational Dynamics, 38(1), 64–72.

Raisch, S., & Birkinshaw, J. (2008). Organizational Ambidexterity: Antecedents, Outcomes, and Moderators. Journal of Management, 34(3), 375–409.

Raudsepp, E. (1991). Are you flexible enough to succeed? Supervision, 52(11), 6.

Rosing, K., Frese, M., & Bausch, A. (2011). Explaining the heterogeneity of the leadership-innovation relationship: Ambidextrous leadership. The Leadership Quarterly, 22(5), 956–974.

Saunders, M. N., Lewis, P., & Thornhill, A. (2012). Research methods for business students. Harlow, England: Pearson.

Shalley, C. E., Gilson, L. L., & Blum, T. C. (2009). Interactive Effects of Growth Need Strength, Work Context, and Job Complexity On Self-Reported Creative Performance.

(35)

34 Sheremata, W. A. (2000). Centrifugal and centripetal forces in radical new product

development under time pressure. Academy of Management Review, 25(2), 389–408. Shin, S. J., & Zhou, J. (2003). Transformational leadership, conservation, and creativity:

evidence from Korea. Academy of Management Journal, 46(6), 703–714.

Somech, A. (2006). The Effects of Leadership Style and Team Process on Performance and Innovation in Functionally Heterogeneous Teams. Journal of Management, 32(1), 132– 157.

Stoker, J. I., Looise, J. C., Fisscher, O. A. M., & Jong, R. D. De. (2001). Leadership and innovation: relations between leadership, individual characteristics and the functioning of R&D teams. The International Journal of Human Resource Management, 12(7), 1141–1151.

Tabachnick, B. G., & Fidell, L. S. (2001). Tabachnick, Fidell_2001.pdf. Using Multivariate

Statistics.

Tushman, M. L., & O’Reilly, C. A. (1996). The Ambidextrous Organizations: Managing Evolutionary and Revolutionary Change. California Management Review, 38(4), 8–30. Tushman, M., Smith, W. K., Wood, R. C., Westerman, G., & O’Reilly, C. (2010).

Organizational designs and innovation streams. Industrial and Corporate Change, 19(5), 1331–1366.

Welbourne, T. M., Johnson, D. E., & Erez, A. (1998). The role-based performance scale: validity analysis of a theory-based measure. Academy of Management Journal, 41(5), 540–555.

Yukl, G. A. (1994). Leadership in organizations (3rd ed.). Englewood Cliffs, NJ: Prentice Hall.

Yukl, G. (2008). How leaders influence organizational effectiveness. The Leadership

Quarterly, 19(6), 708–722.

Yukl, G. (2009). Leading organizational learning: Reflections on theory and research. The

Leadership Quarterly, 20(1), 49–53.

Zaccaro, S. J., Gilbert, J. A., Thor, K. K., & Mumford, M. D. (1991). Leadership and social intelligence: Linking social perspectiveness and behavioral flexibility to leader

effectiveness. The Leadership Quarterly, 2(4), 317–342.

Zacher, H., Robinson, A. J., & Rosing, K. (2014). Ambidextrous Leadership and Employees’ Self-Reported Innovative Performance: The Role of Exploration and Exploitation Behaviors. The Journal of Creative Behavior, n/a–n/a.

Zacher, H., & Rosing, K. (2015). Ambidextrous leadership and team innovation. Leadership

& Organization Development Journal, 36(1), 54–68.

Zacher, H., & Wilden, R. G. (2014). A daily diary study on ambidextrous leadership and self-reported employee innovation. Journal of Occupational and Organizational Psychology,

87(4), 813–820.

Zaltman, G., Duncan, R., & Holbek, J. (1973). Innovations and organizations (Vol. 1973). New York: Wiley.

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APPENDICES

Appendix 1: E-mail with request to the works council (anonymised)

This e-mail has been sent by the HR manager of the R&D center to the works council members on 29-09-2016.

Dear Works Council Members,

I'd like to inform you about a voluntary survey for which we will seek voluntary participation after the close of this year's xxxx Satisfaction Survey.

As a master student of Leadership & Management in the University of Amsterdam, Thais Taylor, who works as a xxxx at xxxx is currently conducting her Master's thesis by

investigating the influence of leadership on the innovation performance of employees. Her study aims to understand how leadership behaviors can enable the highest level of innovation from our employees. The method chosen to conduct this investigation is quantitative and therefore a multiple-choice questionnaire has been developed making use of an online survey tool provided by the University of Amsterdam.

Thais would like to administer the questionnaire to managers and employees of xxxx in the next coming months, ideally from mid-October until the end of November --after the close of the xxxx Satisfaction Survey. The surveys have been developed in a way that is easy to respond and won't cost too much time to fill in -- and participation is voluntary. The

responses of employees are strictly confidential. In addition, the data will be handled with the utmost confidentiality, no names or measures on the individual or team level will be

disclosed. The analysis will be conducted on the basis of aggregated data only.

Besides the scientific relevance of her research, this thesis can deliver valuable insights for xxxx about our prevalent leadership styles and the perception of our innovative performance

Ambidextrous leadership and innovation : the role of temporal flexibility