Introduction
The increasing uncertainty and complexity of today’s business world in a fast-paced, technology-driven, and ever-competitive business environment requires constant innovation as an essential strategy that is vital to firm performance, growth, and survival (Busola Oluwafemi, Mitchelmore, & Nikolopoulos, Reference Busola Oluwafemi, Mitchelmore and Nikolopoulos2020; Zhang & Law, Reference Zhang and Law2021). Employees are on the front lines of processes and products. As such, they can identify opportunities for improvement and new developments (Bos-Nehles, Renkema, & Janssen, Reference Bos-Nehles, Renkema and Janssen2017) and are a key source of innovation (Newman, Tse, Schwarz, & Nielsen, Reference Newman, Tse, Schwarz and Nielsen2018). Accordingly, organizations should foster employees’ innovative work behavior (EIB) – defined as the generation, championing, and implementation of ideas (Jong & Hartog, Reference Jong and Hartog2010; Wang, Eva, Newman, & Zhou, Reference Wang, Eva, Newman and Zhou2021).
There is broad consensus in both research and practice that leadership plays a critical role in fostering and enhancing EIB (e.g. Anderson, Potočnik, & Zhou, Reference Anderson, Potočnik and Zhou2014; Wang et al., Reference Wang, Eva, Newman and Zhou2021). However, current reviews of the field reveal a complex and fragmented research landscape, lacking clear, actionable recommendations for how leaders can effectively boost EIB (Hughes, Lee, Tian, Newman, & Legood, Reference Hughes, Lee, Tian, Newman and Legood2018; Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020). A significant gap remains in identifying which specific leadership variables predict EIB and understanding their relative importance (Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020). This gap is largely due to an overemphasis on broad leadership styles (particularly transformational leadership), which, while demonstrating general correlations between positive leadership and innovation, fall short in offering targeted, practical guidance. In response to this, Hughes et al. (Reference Hughes, Lee, Tian, Newman and Legood2018) advocate for a shift away from these broad leadership styles to a more nuanced examination of specific leader behaviors, which could enhance our understanding of the fundamental elements of leader influence. A behavior-based approach, therefore, holds promise for providing more precise recommendations on leadership behaviors that effectively promote EIB (Jong & Hartog, Reference Jong and Hartog2007; Liehr & Hauff, Reference Liehr and Hauff2023; Portnova & Peiseniece, Reference Portnova and Peiseniece2017). Although some researchers have begun exploring this approach (Jong & Hartog, Reference Jong and Hartog2007; Kaudela-Baum & Nussbaum, Reference Kaudela-Baum and Nussbaum2022; Liehr & Hauff, Reference Liehr and Hauff2023; Vlok, Reference Vlok2012), a cumulative and coherent body of knowledge has yet to emerge.
The aim of this study is thus to develop and test a model of innovation-specific leadership behavior, i.e., leadership behavior that explicitly aims to increase EIB. For this purpose, we build on the Ability–Motivation–Opportunity (AMO) framework (Appelbaum, Bailey, Berg, & Kalleberg, Reference Appelbaum, Bailey, Berg and Kalleberg2000) in order to identify specific leader behaviors that can help foster EIB. More specifically, we assume that EIB can be fostered if leadership behavior provides employees with the knowledge, skills, and abilities that are necessary to be innovative, by motivating them to engage in innovative behavior and by providing opportunities that help to develop and implement new ideas. Accordingly, we distinguish between ability-enhancing, motivation-enhancing, and opportunity-enhancing leader behaviors and analyze which specific leader behaviors within these three domains are the most important drivers for EIB.
With this study, we make several contributions to the literature on the influence of leadership on EIB. First, we focus on leadership behaviors (rather than broad leadership styles) that specifically foster EIB (Hughes et al., Reference Hughes, Lee, Tian, Newman and Legood2018). The existing overemphasis on transformational leadership and related approaches (such as authentic, ethical, and servant leadership) not only prevents practical recommendations but it is also questionable whether these approaches can be used as a means for increasing EIB, as they have been developed in relation to general performance outcomes (e.g., effectiveness or efficiency) rather than innovation-related outcomes (Jong & Hartog, Reference Jong and Hartog2007; Mumford & Licuanan, Reference Mumford and Licuanan2004). Thus rather than examining the effects of leadership styles that were not originally designed to promote innovation-specific outcomes (Hughes et al., Reference Hughes, Lee, Tian, Newman and Legood2018; Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020), we identify innovation-specific leadership behaviors.
Second, although leadership styles typically consist of multiple lower-order factors or components, studies to date have tended to operationalize these leadership styles through a single scale score, thereby ignoring and obscuring the relationships at the sub-factor level. With our study, we contribute to removing this ambiguity about which leadership variable(s) are the strongest predictors with the greatest relative importance for the EIB (Hughes et al., Reference Hughes, Lee, Tian, Newman and Legood2018; Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020; Miao, Newman, & Lamb, Reference Miao, Newman and Lamb2012). In doing so, we also respond to calls for further research to prioritize actionable knowledge that enables managerial implications for leadership development and the promotion of EIB in organizations (Hughes et al., Reference Hughes, Lee, Tian, Newman and Legood2018; Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020).
Finally, we contribute to research by using the AMO framework as an overarching approach to explain why specific leader behaviors are associated with EIB. In doing so, we expand the theoretical toolkit of research on leadership behavior and EIB by introducing an approach that helps illuminate the detailed mechanisms behind leader influence on EIB. This approach can serve as a basis for further research and provide a better understanding of the limited findings to date.
Theory
Innovative work behavior
EIB is a multistage process that requires different activities and different individual behaviors at each stage. The first stage – idea generation – involves the identification of a problem and the creative development of ideas or solutions that are either new or adapted. Idea generation can relate to new products, services, or processes. The key to idea generation is the combination and reorganization of information and existing concepts to solve problems or improve performance (Jong & Hartog, Reference Jong and Hartog2010). The next phase – idea championing – becomes relevant once an idea has emerged. Idea championing involves seeking support and building coalitions by expressing enthusiasm and confidence about the success of the innovation, being persistent and involving the right people (Howell, Shea, & Higgins, Reference Howell, Shea and Higgins2005). The third phase of the innovation process – idea implementation – completes EIB. Depending on the nature of the idea, this may involve a prototype or model of the innovation, a change in process, or something that can be manufactured, productively used, or institutionalized (Kanter, Reference Kanter1988; Scott & Bruce, Reference Scott and Bruce1994). Putting ideas into practice requires considerable effort and a results-oriented attitude (Jong & Hartog, Reference Jong and Hartog2010).
Leadership and EIB
The relationship between leadership and innovation has been examined using various leadership constructs. In their review, Hughes et al. (Reference Hughes, Lee, Tian, Newman and Legood2018) summarize the key trends of the myriad leadership variables identified in the literature related to EIB. Their findings show that previous research on innovative leadership has focused heavily on established leadership approaches, particularly transformational and transactional leadership, but also other ‘positive’ or ‘moral’ leadership styles such as ethical or authentic leadership. These leadership styles are positively related to EIB to about the same extent. That is, there is a consistent pattern of low to moderate positive correlations between these leadership styles and EIB, regardless of the type of style (Hughes et al., Reference Hughes, Lee, Tian, Newman and Legood2018). Similar results were found in the meta-analytic study by Lee et al. (Reference Lee, Legood, Hughes, Tian, Newman and Knight2020) in which the authors examined the relationship between 13 leadership variables (transformational, transactional, ethical, humble, executive sharing, benevolent, authoritarian, entrepreneurial, authentic, serving, empowering, supportive, and destructive) and innovation. Their results also showed that ‘almost all leadership variables were modestly correlated with […] innovation’ (Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020, p. 31).
Remarkably, most studies on the relationship between leadership and EIB examine the role of leadership styles that were originally developed for other purposes, such as assessing the impact of leaders on employee performance or effectiveness, rather than innovation-specific outcomes (Jong & Hartog, Reference Jong and Hartog2007). For example, the goal of transformational leadership (which is primarily studied in the context of EIB) is originally to ‘transform’ employees. Leaders who adopt a transformational leadership style focus on the growth and development of their employees’ value systems, inspiration, and morale, thus aiming to create higher levels of motivation and performance among employees (Bass, Reference Bass1985). However, it is questionable whether leadership styles developed for general performance outcomes can be fully generalized to foster EIB (Mumford & Licuanan, Reference Mumford and Licuanan2004).
Recent studies also show that most research focuses on the effects of leadership in terms of ‘leadership style,’ ignoring individual sub-factors within these broader constructs of leadership (Hughes et al., Reference Hughes, Lee, Tian, Newman and Legood2018; Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020). Despite the fact that leadership styles typically consist of several lower-order factors or components, previous studies tend to operationalize leadership styles through a single scale score, thereby ignoring and obscuring any relationship at the sub-factor level (Miao et al., Reference Miao, Newman and Lamb2012). Regarding transformational leadership, for example, there might be behavioral sub-factors that are more relevant than others. By ignoring the sub-factors of leadership, we do not know which leadership variable(s) are the strongest predictors with the greatest relative importance for EIB.
Given these shortcomings, Hughes et al. (Reference Hughes, Lee, Tian, Newman and Legood2018) called for further research to move away from broad leader styles and to consider more nuanced, innovation-specific leadership behaviors that effectively promote EIB. Similarly, Lee et al. (Reference Lee, Legood, Hughes, Tian, Newman and Knight2020) called for future research to prioritize which leadership variables are unique and useful for promoting EIB. To date, research on single leadership behaviors related to EIB is quite limited and no cumulative and coherent body of knowledge has emerged (for notable exceptions, see Jong & Hartog, Reference Jong and Hartog2007; Kaudela-Baum & Nussbaum, Reference Kaudela-Baum and Nussbaum2022; Liehr & Hauff, Reference Liehr and Hauff2023; Portnova & Peiseniece, Reference Portnova and Peiseniece2017; Shavinina, Reference Shavinina2011). In response to these calls, we seek to identify individual leader behaviors that relate specifically to EIB and determine the relative importance of these innovation-specific behaviors for EIB. This allows us to identify which leadership behavior are the key drivers with the greatest impact on EIB. The results may provide important insights, especially for practical application.
Ability-, motivation-, and opportunity-enhancing leadership behaviors as innovation-specific leader behaviors
To identify innovation-specific leader behaviors, we rely on the AMO framework (Appelbaum et al., Reference Appelbaum, Bailey, Berg and Kalleberg2000; Boxall & Purcell, Reference Boxall and Purcell2003). The AMO framework originates from organizational psychology and is widely used in strategic human resource management (HRM) (Boselie, Reference Boselie2010; Ogbonnaya & Valizade, Reference Ogbonnaya and Valizade2018; Paauwe, Reference Paauwe2009) and in leadership research (e.g. Abid, Contreras, Rank, & Ilyas, Reference Abid, Contreras, Rank and Ilyas2022; Fischer, Dietz, & Antonakis, Reference Fischer, Dietz and Antonakis2017; Krapež Trošt, Škerlavaj, & Anzengruber, Reference Krapež Trošt, Škerlavaj and Anzengruber2016; Le Thuan & Thanh, Reference Le Thuan and Thanh2019; McDermott, Conway, Rousseau, & Flood, Reference McDermott, Conway, Rousseau and Flood2013; Vashdi, Levitats, & Grimland, Reference Vashdi, Levitats and Grimland2019). According to this framework, effective organizations need employees who have the necessary skills (ability), who are motivated to make a useful contribution (motivation), and who can perform their tasks and duties within appropriate structures (opportunities) (Boxall & Purcell, Reference Boxall and Purcell2011). Clearly, leadership has a significant impact on all three dimensions (Carton, Murphy, & Clark, Reference Carton, Murphy and Clark2014; Lepisto & Pratt, Reference Lepisto and Pratt2017; McDermott et al., Reference McDermott, Conway, Rousseau and Flood2013). In the following, we elaborate on the leader behaviors that are discussed in the research as a means of fostering EIB and that can be assigned to the three dimensions of the AMO framework.
Ability-enhancing leader behaviors. Individual knowledge, intelligence, and experience are particularly important for creativity in innovative idea generation (Amabile & Pratt, Reference Amabile and Pratt2016; Mumford, Scott, Gaddis, & Strange, Reference Mumford, Scott, Gaddis and Strange2002). In order to be innovative, employees rely on their ability to develop, promote, and implement ideas. Creativity-related skills are one of the most important prerequisites for the successful generation of ideas and are essential for the development of new and useful ideas. These skills determine the different ways and flexibility of cognitive ways to problem solving, as well as the extent of specific pathways to pursue solutions (Amabile, Reference Amabile1983, Reference Amabile1988; Le Thuan & Thanh, Reference Le Thuan and Thanh2019). For the development of innovations, these skills are necessary for the most novel and useful ideas (Amabile & Pratt, Reference Amabile and Pratt2016; Pratoom & Savatsomboon, Reference Pratoom and Savatsomboon2012).
Leaders can influence employees’ ability to innovate. By fostering collaborative knowledge sharing within and between teams, leaders can promote skills and knowledge at the individual level to strengthen abilities (Cabrera & Cabrera, Reference Cabrera and Cabrera2005; Damodaran & Olphert, Reference Damodaran and Olphert2000). Knowledge sharing is a fundamental way in which employees can exchange their information, ideas, and perspectives (Jackson, Harden, & Jiang, Reference Jackson, Harden and Jiang2006; Wang & Noe, Reference Wang and Noe2010) which will contribute to EIB (Radaelli, Lettieri, Mura, & Spiller, Reference Radaelli, Lettieri, Mura and Spiller2014; Vandavasi, McConville & Yepuru, Reference Vandavasi, McConville and Yepuru2020). Thus by encouraging collaborative knowledge sharing among team members and between team, leaders can contribute to the improvement of individuals’ abilities and thus to EIB (Cui, Wang, & Zhang, Reference Cui, Wang and Zhang2022; Yu, Reference Yu, Yu and Yu2013).
In addition, leaders can foster the skills of their employees by giving them feedback to help them structure and evaluate their ideas (Mumford et al., Reference Mumford, Scott, Gaddis and Strange2002). Feedback serves as a valuable source of knowledge for employees about how tasks should be performed and whether their own performance is conducive to achieving desired goals. With feedback, employees are better able to identify and address problems and opportunities (Bos-Nehles et al., Reference Bos-Nehles, Renkema and Janssen2017). Feedback from supervisors on work processes and performance increases work-related knowledge and can therefore have a positive influence on EIB (Knol & van Linge, Reference Knol and van Linge2009). Developmental feedback from leaders aims to guide employees to learn and develop. When leaders provide helpful and valuable knowledge to their employees through developmental feedback, they encourage employees to learn and apply both creativity-related and domain-relevant skills (Le Thuan & Thanh, Reference Le Thuan and Thanh2019; Zhou, Reference Zhou2003). This applies not only to idea generation, but also to idea implementation, where feedback helps employees to keep track of work processes, allowing them to better structure their tasks, and thus have more room to implement ideas (Noefer, Stegmaier, Molter, & Sonntag, Reference Noefer, Stegmaier, Molter and Sonntag2009). Therefore, we propose:
Hypothesis 1: Ability-enhancing leader behaviors will increase EIB.
Motivation-enhancing leader behaviors
Motivation is considered to be one of the most important determinants of innovative behavior (e.g. Bysted & Jespersen, Reference Bysted and Jespersen2014; Zhang & Bartol, Reference Zhang and Bartol2010). Highly motivated employees make greater use of their expertise and skills for creative and innovative performance (Amabile, Reference Amabile1997; Messmann & Mulder, Reference Messmann and Mulder2014). Both intrinsic and extrinsic motivation are important for EIB. Intrinsically motivated individuals have been shown to be more creative because this motivation tends to foster curiosity, cognitive flexibility, and risk-taking, which promotes idea generation in particular (e.g. Deci & Ryan, Reference Deci and Ryan1985; Devloo, Anseel, Beuckelaer, & Salanova, Reference Devloo, Anseel, Beuckelaer and Salanova2015; Grant & Berry, Reference Grant and Berry2011). Extrinsic motivation influences EIB when employees are not intrinsically motivated to engage in innovative activities. In this case, they will perceive innovative behavior as additional effort and are more likely to be extrinsically motivated and respond to extrinsic incentives (Bos-Nehles et al., Reference Bos-Nehles, Renkema and Janssen2017; Bysted & Jespersen, Reference Bysted and Jespersen2014).
Leaders can influence employees’ motivation to innovate through their behavior (Amabile, Reference Amabile1988). A first motivation-enhancing leader behavior is communicating a vision. Communicating a vision helps employees to focus on the ‘big picture.’ Through this overarching construct, employees can connect their work to the leader’s vision, giving them a sense of purpose in their work. This sense of meaning and purpose in one’s work increases intrinsic motivation (Barrick, Mount & Li, Reference Barrick, Mount and Li2012; Carton et al., Reference Carton, Murphy and Clark2014; Lepisto & Pratt, Reference Lepisto and Pratt2017). Thus, the communication of a vision by the leader motivates followers to increase their efforts to realize the idealized future of their organization (Carton et al., Reference Carton, Murphy and Clark2014; Kirkpatrick, Reference Kirkpatrick2016). Accordingly, it is assumed that visioning has a motivational effect that promotes EIB (Jong & Hartog, Reference Jong and Hartog2007).
In addition, leaders can provide employees with a motivating direction by setting goals. Leaders stimulate the motivation to innovate through clear goal setting and monitoring progress as part of a performance management (Locke, Reference Locke1990; Rosing, Frese, & Bausch, Reference Rosing, Frese and Bausch2011). By setting goals, employees are aware of what is expected of them and can align their performance with these expectations (Ernst et al., Reference Ernst, Banks, Loignon, Frear, Williams, Arciniega and Subramanian2022). However, this goal setting behaviors must not have a controlling focus, otherwise it will have a negative impact on the EIB. Nevertheless, a certain degree of goal orientation and progress activities is desirable to ensure the progress of innovations (Jong & Hartog, Reference Jong and Hartog2007).
Furthermore, innovative role modeling by the leader stimulates employees’ motivation to innovative (Jong & Hartog, Reference Jong and Hartog2007). Leaders serve as role models for employees, and positive leader behavior motivates followers to follow in his or her footsteps (Bandura & Walters, Reference Bandura and Walters1977). An innovative role model is characterized by a change-oriented attitude, and actively strives for change. A leader who creates innovation themselves demonstrate desired, innovation related behavior and thus motivates employees to innovate in order to become like their leader (Iqbal, Nazir, & Ahmad, Reference Iqbal, Nazir and Ahmad2022; Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020; Purwanto, Asbari, Hartuti, Setiana, & Fahmi, Reference Purwanto, Asbari, Hartuti, Setiana and Fahmi2021).
Finally, rewards have been shown to influence employees’ willingness and commitment to innovation (e.g. Bysted & Jespersen, Reference Bysted and Jespersen2014; Zhang & Begley, Reference Zhang and Begley2011). Employees who feel that their efforts are fairly rewarded will feel obligated to reciprocate through innovative behavior (Janssen, Reference Janssen2000). Motivation to innovate is a prerequisite for EIB, and leaders can significantly influence employee’s motivation. We therefore propose:
Hypothesis 2: Motivation-enhancing leader behaviors will increase EIB.
Opportunity-enhancing leader behaviors
Referring to the contextual and situational performance constraints, employees must experience opportunities within the organization to innovate (Appelbaum et al., Reference Appelbaum, Bailey, Berg and Kalleberg2000; Vashdi et al., Reference Vashdi, Levitats and Grimland2019). Opportunity encompasses the contextual or environmental factors that are beyond the direct control of the individual. These factors either limit a person’s opportunities or enable achievement (Bos‐Nehles, Townsend, Cafferkey, & Trullen, Reference Bos‐Nehles, Townsend, Cafferkey and Trullen2023).
Opportunities to behave innovatively arise when employees can participate in organizational processes (e.g. Escribá-Carda, Balbastre-Benavent, & Teresa Canet-Giner, Reference Escribá-Carda, Balbastre-Benavent and Teresa Canet-Giner2017; Patel, Messersmith, & Lepak, Reference Patel, Messersmith and Lepak2013) and when they have a correspondingly large scope for decision-making (e.g. Amabile & Gryskiewicz, Reference Amabile and Gryskiewicz1987; Hammond, Neff, Farr, Schwall, & Zhao, Reference Hammond, Neff, Farr, Schwall and Zhao2011). Thus, a first opportunity-enhancing leader behavior is empowering leader behavior. When leaders empower their employees they foster perceived self-efficacy and autonomy, factors that are crucial for employees to generate new ideas and to independently take steps to implement them (Dediu, Leka, & Jain, Reference Dediu, Leka and Jain2018; Zhang & Bartol, Reference Zhang and Bartol2010). Reducing unnecessary control and providing discretion is essential for creativity in the idea generation phase (Abstein & Spieth, Reference Abstein and Spieth2014; Hammond et al., Reference Hammond, Neff, Farr, Schwall and Zhao2011; Sarmah, van den Broeck, Schreurs, Proost, & Germeys, Reference Sarmah, van den Broeck, Schreurs, Proost and Germeys2022). Creative employees need the autonomy to make choices about how to complete tasks and a sense of control over their work and ideas (Amabile, Conti, Coon, Lazenby, & Herron, Reference Amabile, Conti, Coon, Lazenby and Herron1996; Amabile & Gryskiewicz, Reference Amabile and Gryskiewicz1987). This discretion allows employees to experiment with different approaches and methods, facilitating idea generation and laying the ground for successful implementation.
A second opportunity-enhancing leader behavior is social support for innovative contributions. Social support is especially important in the first phase of EIB. When developing new ideas, employees are highly dependent on the support of their supervisors, who initially advise and encourage them (Dediu et al., Reference Dediu, Leka and Jain2018). Leader support creates opportunities for exploratory and critical thinking and a working environment in which unconventional and risk-taking approaches and innovations are highly valued (Krapež Trošt et al., Reference Krapež Trošt, Škerlavaj and Anzengruber2016). Social support plays two important roles within the innovation process. First, the leader provides actual support when needed. Second, this behavior provides reassurance that support is available when needed. Both roles increase the individual’s control over their work, which has a positive impact on EIB (Dediu et al., Reference Dediu, Leka and Jain2018). Social support also leads to a people-oriented, friendly, encouraging, and trustworthy work environment (Vashdi et al., Reference Vashdi, Levitats and Grimland2019). In such a work environment, there is a higher tolerance for unsuccessful attempts at innovation and employees are more willing to take risks to implement new ideas (Sethi, Smith, & Park, Reference Sethi, Smith and Park2001). Thus supportive supervisors create an environment in which employees feel safe to propose novel and original ideas (Hunter & Cushenbery, Reference Hunter and Cushenbery2011).
Finally, EIB is often a risky endeavor for employees as new ideas do not necessarily lead to success (Lee, Reference Lee2008). Leaders who accept uncertainty and risk and are willing to learn from failure encourage innovative work behaviors. These leaders create opportunities to innovate and support others in implementing change (Bel, Reference Bel2010; Contreras et al., Reference Contreras, Juarez, Cuero Acosta, Dornberger, Soria-Barreto, Corrales-Estrada and Foroudi2020). Thus, we propose:
Hypothesis 3: Opportunity-enhancing leader behaviors will increase EIB.
Method
Data collection and sample
We distributed the survey via personal contacts and via the SoSci Panel. The SoSci Panel is a non-commercial project that provides academic research with access to high quality samples. Participation in the panel is voluntary and panelists receive no financial remuneration. Only professionals, living in Germany were invited to participate in the survey. We used a speed index and a check for unrealistic response behavior to clean the data. The final sample consists of 1214 employees, including 368 males, 825 females, and 7 diverse participants. The mean age was 45.1 years (SD = 11.1). 89.7% had permanent employment status; 44.7% worked in private organizations; 44.2% of participants worked in a large organization with more than 500 employees. 75.6% had no leadership responsibilities. 60.0% of participants had a university degree or higher.
Measures
Employees’ innovative work behavior. EIB was measured using a six-item scale adapted from Jong and Hartog (Reference Jong and Hartog2010). We adapted the wording of the original items to allow employees to self-rate their innovative work behavior. The items were measured on a 5-point Likert scale, with values ranging from 1 = never to 5 = always. Idea generation, idea championing, and idea implementation were measured with two items for each dimension. Sample items are ‘How often do you find new approaches to execute tasks?’ and ‘How often to you contribute to the implementation of new ideas?’ The Cronbach’s α for EIB was 0.87.
Innovation-specific leader behavior. To measure the identified individual innovation-specific leader behaviors, we adopted existing scales (e.g. Liden, Wayne, Zhao, & Henderson, Reference Liden, Wayne, Zhao and Henderson2008; Podsakoff, MacKenzie, Moorman, & Fetter, Reference Podsakoff, MacKenzie, Moorman and Fetter1990). We used three items to measure ability-enhancing leader behavior, six items to measure motivation-enhancing leader behavior, and three items to measure opportunity-enhancing leader behavior. Appendix 1 shows the full set of items. All items were measured on a 5-point Likert scale ranging from 1 = never to 5 = always. We conceptualized innovation-specific leader behavior as a formative-formative higher order construct (HOC), in which ability-, motivation-, and opportunity-enhancing leader behaviors represent the lower order components (LOCs).
Control variables. Following previous studies, we controlled for the following variables that were shown to be related to our study variables: gender, age, educational level, job tenure, firm size, and sector (Afsar, Badir, & Saeed, Reference Afsar, Badir and Saeed2014; Janssen, Reference Janssen2000; Javed, Naqvi, Khan, Arjoon, & Tayyeb, Reference Javed, Naqvi, Khan, Arjoon and Tayyeb2019; Jong & Hartog, Reference Jong and Hartog2010; Jung, Chow, & Wu, Reference Jung, Chow and Wu2003; Pieterse, van Knippenberg, Schippers, & Stam, Reference Pieterse, van Knippenberg, Schippers and Stam2010; Scott & Bruce, Reference Scott and Bruce1994; Wang, Fang, Qureshi, & Janssen, Reference Wang, Fang, Qureshi and Janssen2015; Yidong & Xinxin, Reference Yidong and Xinxin2013). We additionally controlled for the sample access (see above). Table 1 shows the mean, standard deviation, and correlations of our variables.
Table 1. Means (M), standard deviations (SD), and correlations of variables
** Correlation is significant at the 0.01 level (two-tailed). N = 1.214.
Analysis
For our analyses, we used partial least squares structural equation modeling (PLS-SEM) using SmartPLS 4 software (Ringle & Wende, Reference Ringle, Wende and Becker2022). We obtained PLS-SEM results by using the following settings in all analysis steps: Path weighting scheme, 300 iterations, stop-criterion 0.0000001, and mean value replacement of missing values. We determined significance by applying the bootstrapping procedure with the following settings: Percentile bootstrap, 10,000 subsamples, no sign changes, and one-tailed testing with a 0.05 significance level.
We first estimated an initial control model containing all of the above control variables (according to Nielsen & Raswant, Reference Nielsen and Raswant2018). The results showed that only participants’ age and the sample source were significantly related to EIB. Accordingly, we excluded all other control variables from our final model (Fig. 1).
Figure 1. Conceptual model.
Results
Measurement models
To ensure the validity and reliability of our reflective measurement model, we assessed the indicator reliability, internal consistency, and convergent and discriminant validity (see Table 2) (Hair, Hult, Ringle, & Sarstedt, Reference Hair, Hult, Ringle and Sarstedt2022). The outer loadings of all items were above the desired threshold of 0.70. Cronbach’s α was 0.87 and composite reliability (ρA) was 0.88. The average variance extracted was 0.61. These results confirmed the reliability and validity of our reflective construct.
Table 2. Formative measurement model validity
The formative measurement models were assessed on the basis of multicollinearity and their relevance to the formative construct (see Table 2) (Hair et al., Reference Hair, Hult, Ringle and Sarstedt2022). None of the variance inflation factor (VIF) scores indicated a problem of multicollinearity, as all values were below the threshold of 3. As some of the indicator weights were not significant, their absolute contribution had to be considered. Two items had a factor loading slightly below the threshold of 0.5 but were retained in the model due to the significance of their loadings.
We used the disjoint two-stage approach (Gholamzade, Ringle, & Sarstedt, Reference Gholamzade, Ringle and Sarstedt2023) to evaluate the formative-formative higher-order measurement model. That is, we first estimated a model containing only the LOCs as independent variables. We then used the resulting constructs scores of the LOCs as indicators of the HOC’s measurement model. The higher-order formative measurement models were assessed based on multicollinearity and their relevance for the formative construct (see Table 3) (Hair et al., Reference Hair, Hult, Ringle and Sarstedt2022). None of the VIF scores indicated a problem of multicollinearity, with all having a value below the conservative threshold of 3. One of the indicator weights was not significant but was retained in the model owing to the loading. Overall, these results confirmed the measurement model of our HOC (Hair et al., Reference Hair, Hult, Ringle and Sarstedt2022).
Table 3. Higher order construct validity
Structural model
The final model explained 7.5% of the variance in EIB. Following the recommendations of Hair et al. (Reference Hair, Hult, Ringle and Sarstedt2022), we consider the 95% confidence intervals to prove significance of the path coefficients. Innovation-specific leader behavior was positively related to EIB (β= .25; 95% CI [0.185; 0.300]) (see Table 4). The results in Table 5 show that ability-enhancing leader behavior does not significantly impact EIB (β= .01; 95% CI [−0.079; 0.086]); therefore, Hypothesis 1 is not supported. Motivation-enhancing leader behavior significantly impacts EIB (β= .15; 95% CI [0.073; 0.208]); therefore, Hypothesis 2 is supported. Our results indicate a significantly positive impact of opportunity-enhancing leader behavior on EIB (β= .20; 95% CI [0.134; 0.275]), thereby confirming Hypothesis 3.
Table 4. Results for the final model
Significance testing based in 10,000 bootstrap samples.
* Coefficients significant at the level 0.05 (two-tailed).
Table 5. Total effects
Another aim of this study was to gain insights into the importance of single behaviors within the behavioral dimensions of innovation-specific leader behavior. The use of formative-formative second-order measurement models for innovation-specific leader behavior makes it possible to determine the importance of individual behaviors within these dimensions in predicting EIB (see Table 6). The behaviors with the highest indirect effects on EIB were empowering leader behavior (.10), followed by the support for innovative contributions (.07), leaders own creation of innovation (.06), and rewarding innovative contributions (.04). Setting objectives (−.05) negatively affected EIB.
Table 6. Effects of innovation-specific leader behaviors
Effects of single behaviors via the LOCs and the HOC;
* indicates effects with significant paths and weights.
Discussion
Theoretical implications
By analyzing the relationship between innovation-specific leader behaviors and EIB, our study makes several contributions. First, we contribute to research by identifying innovation-specific leader behaviors. In particular, our empirical findings support four innovation-specific leader behaviors: Leaders who exhibit empowering behavior and support their employees, reward innovative contributions and actively drives own innovations enhancing EIB. These behaviors are partly reflected in broader leadership styles. For example, leaders support represents a behavior of the individual consideration dimension of transformational leadership (Avolio & Bass, Reference Avolio and Bass1995; Podsakoff et al., Reference Podsakoff, MacKenzie, Moorman and Fetter1990), and leader’s rewarding of innovative contributions can be considered an element of transactional leadership style (Bass & Riggio, Reference Bass and Riggio2010). Interestingly, our results show that setting objectives, another sub-factor of transactional leadership, negatively influences EIB. This finding suggests that employees may perceive goal setting by the leader as pressure and controlling behavior, which inhibits EIB (e.g. Amabile et al., Reference Amabile, Conti, Coon, Lazenby and Herron1996). Furthermore, our results have shown that behaviors that are neither part of transformational nor transactional leadership have a significant impact on EIB. More specifically, we found a positive influence on EIB through the leader’s empowering behavior, which is fundamental to empowering leadership (Sharma & Kirkman, Reference Sharma and Kirkman2015) and also a part of servant leadership (Liden et al., Reference Liden, Wayne, Zhao and Henderson2008). Finally, we identified the active promotion of own innovations by the leader as an innovation-promoting behavior that cannot be assigned to any of the established leadership styles.
Overall, our analysis and findings underscore the importance of adopting a behavior-based approach to studying leadership’s influence on EIB. When research focuses solely on broad leadership styles, the impact of specific behaviors on EIB can become obscured, as these styles often include elements unrelated to EIB. This approach also risks overlooking important behaviors (for instance, studying the influence of transformational leadership on EIB might miss the impact of behaviors outside that style). Therefore, it is crucial to emphasize leadership behaviors that are directly related to EIB.
Second, by prioritizing leadership variables that can help promote EIB, we help close the knowledge gap regarding about which leadership variable(s) are the strongest predictors and have the greatest relative importance for EIB (Hughes et al., Reference Hughes, Lee, Tian, Newman and Legood2018; Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020). Our results show that empowering leader behavior is most important for EIB followed by leaders’ support for innovative contributions. This is consistent with previous research, as several authors have pointed out that discretion and lack of control are keys for employees to be creative, develop new ideas, and experiment with alternative approaches. For example, Krause (Reference Krause2004) showed that the granting of degrees of freedom and discretion by the leader directly fosters EIB. The importance of leader support was for example demonstrated by Hernaus, Dragičević and Hauff (Reference Hernaus, Dragičević and Hauff2024). Compared to empowerment and support, the creation of own innovation and rewarding innovative contributions are slightly less important but further support EIB. Overall, our results show that EIB can best be promoted by showing opportunity-enhancing leader behavior (in terms of empowering behavior and leader support), while motivation-enhancing leader (in terms of creating own innovation and reward) can provide an additional boost to EIB.
Third, we contribute to the literature by using the AMO framework to identify and classify innovation-specific leader behaviors, and to explain the link between single leader behaviors and EIB. According to this framework, employees need necessary skills (ability), the motivation to make a useful contribution, and opportunities to carry out their tasks and duties in appropriate structures (Boxall & Purcell, Reference Boxall and Purcell2011). Since EIB represents a specific performance outcome, we adopted the AMO framework to identify innovation-specific leader behaviors. Although the AMO framework has been used in previous studies to understand the impact of HRM practices on EIB (for an overview, see Bos-Nehles et al., Reference Bos-Nehles, Renkema and Janssen2017), there are no studies on the relationship between AMO dimensions of leader behavior and EIB to our knowledge so far. Thus, we innovatively extend this line of research by adding a theoretical framework that can help illuminate the detailed mechanism of leadership influence on EIB.
Using the AMO model as a guiding framework allowed us to identify ability-enhancing, motivation-enhancing, and opportunity-enhancing leader behaviors for EIB. While our assumptions regarding motivation-enhancing and opportunity-enhancing leader behaviors have largely been supported (see discussion above), we could not prove that the identified ability-enhancing leader behaviors promote EIB. One possible explanation could be that employees may acquire the necessary abilities to innovate through sources other than their leaders. Indeed, research suggests that abilities are also fostered through organizational interventions, especially HRM practices (e.g. Bos-Nehles et al., Reference Bos-Nehles, Renkema and Janssen2017; Bysted & Jespersen, Reference Bysted and Jespersen2014; Knol & van Linge, Reference Knol and van Linge2009). For example, training and development programs at an organizational level improve employees’ skills and knowledge (Knol & van Linge, Reference Knol and van Linge2009; Pratoom & Savatsomboon, Reference Pratoom and Savatsomboon2012). Evaluation and appraisal systems may substitute supervisory feedback (Chang, Hsu, Liou, & Tsai, Reference Chang, Hsu, Liou and Tsai2013; Battistelli, Montani, & Odoardi, Reference Battistelli, Montani and Odoardi2013). Thus, abilities for EIB are not necessarily developed at the interpersonal level between leader and employee but at the organizational level. Overall, we believe that the AMO approach is a valuable theoretical tool for deepening our understanding of how leader behavior influences EIB. Our research has focused on behaviors that have been discussed in previous studies, but this approach also has the potential to uncover additional factors specific to EIB. Future research should leverage this framework to explore behaviors that have not yet been adequately addressed. This would be a significant step in expanding the research perspective and providing a more detailed exploration of the mechanisms by which leaders influence EIB.
In summary, our study sheds light on which individual leader behaviors are specific to EIB. Prioritizing the relative importance of specific behaviors provides highly relevant insights on how to improve leadership effectiveness in promoting EIB. Furthermore, using the AMO framework to identify leader behaviors that promote EIB provides a new approach and perspective for further research.
Practical implications
Our results show that leaders directly influence EIB through certain behaviors. Our final model provides clear guidance for leaders to promote EIB. To foster EIB, leaders should concentrate in showing innovation specific opportunity- and motivation-enhancing behavior. More specifically, empowerment and the leader’s own creation of innovation are the key behaviors to promote EIB, complemented by providing support and rewarding innovative contributions from employees. Leaders who aspire to EIB should focus on these behaviors and acquire and promote them, e.g. through self-development. In addition, our findings provide a guide for HR professionals to effectively develop leaders who optimize organizational performance through innovative employees. For HR practitioners, developing and implementing innovative leadership is challenging as the fragmented research base prevents evidence-based practical recommendations (Hughes et al., Reference Hughes, Lee, Tian, Newman and Legood2018; Lee et al., Reference Lee, Legood, Hughes, Tian, Newman and Knight2020). HR practitioners can use our findings within selection, evaluation, appraisal systems, or training and development of leaders. These specific behaviors should be addressed and reinforced in training and development approaches and considered in the comprehensive range of leadership development interventions, such as mentoring, job assignments, feedback systems, on-the-job experiences, developmental relationships, and formal training (McCauley & Hughes-James, Reference McCauley and Hughes-James1994). In addition, appraisal systems should be aligned. Thus, our results show which behaviors need to be considered when describing the target requirements for innovative leadership.
Limitations and future research
Like other studies, the present study has strengths, but also some limitations that point to opportunities for future research. First, we used a self-report measure of innovative behavior, which may introduce bias into current methods. To test for common method bias, we conducted a marker variable analysis. As our data did not include a specific marker variable, we used the smallest observed correlation among all substantive variables as a proxy, as suggested by Lindell and Whitney (Reference Lindell and Whitney2001). The lowest correlations turned out to be below r = 0.005, so common method bias should not affect our results. The use of self-reported measures is justified on several theoretical empirical grounds. Using self-assessment of EIB is not uncommon (Amankwaa, Gyensare, & Susomrith, Reference Amankwaa, Gyensare and Susomrith2019; Khaola & Coldwell, Reference Khaola and Coldwell2019) and was deliberately chosen because innovative behavior also involves cognitive processes; therefore, employees are more likely to be aware of their involvement in this process (Javed, Abdullah, Zaffar, Haque, & Rubab, Reference Javed, Abdullah, Zaffar, Haque and Rubab2019; Jones & Nisbett, Reference Jones and Nisbett1971; Zhou & Shalley, Reference Zhou and Shalley2011). While supervisors’ assessment of EIB may be biased as they only perceive the innovative activities that impress them and are therefore likely to ignore some genuine ideas (Janssen, Reference Janssen2000; Javed et al., Reference Javed, Abdullah, Zaffar, Haque and Rubab2019; Organ & Konovsky, Reference Organ and Konovsky1989), self-report measurement of innovative behavior can avoid these biases (Chen & Hou, Reference Chen and Hou2016; Jong & Hartog, Reference Jong and Hartog2007). However, comparing employees’ responses with their leaders’ ratings could provide further information. Second, our conclusion regarding the causality of the relationships is questionable due to the use of a cross-sectional design; further research should test our results using a longitudinal design. A final limitation concerns the generalizability of the results found in this study. The sample consisted of German participants; the cultural context may have an influence on our results.
Our findings offer additional opportunities for future research. First, the integration of mediating and moderating factors (underlying processes; contextual factors; personality; work experience; identification-based or social-relational factors) could be an approach for further research to better reflect and understand the influence of leaders on EIB. Second, further research could also investigate whether and how innovation-related HRM practices (Bos-Nehles et al., Reference Bos-Nehles, Renkema and Janssen2017) and leader behavior interact complement or substitute each other in influencing EIB (Hauff, Felfe, & Klug, Reference Hauff, Felfe and Klug2022; Leroy, Segers, van Dierendonck, & Hartog, Reference Leroy, Segers, van Dierendonck and Hartog2018). In such an analysis, it would be very interesting to determine whether and through which combinations a joint use of HRM practices and leadership behavior would be most effective in improving the EIB. Third, future research should examine the influence of leadership on EIB as a multidimensional construct. Like most articles, we consider EIB as a one-dimensional construct (Bos-Nehles et al., Reference Bos-Nehles, Renkema and Janssen2017; Jong & Hartog, Reference Jong and Hartog2010). Since the requirements for innovative behavior differ in the phases of idea generation, idea promotion, and idea implementation, it could be useful to analyze the influence of leadership on EIB in a more differentiated and multidimensional way.
Acknowledgements
The authors acknowledge support by the SoSci Panel (www.soscipanel.de) that conducted the data collection free of charge.
Conflicts of interest
None.
Appendix 1. Items to measure leader behavior
Jennifer Liehr is a doctoral student at the Chair of Labor, Human Resources and Organization at the Helmut Schmidt University/University of the Federal Armed Forces Hamburg. Her research interests include leadership, innovation and human resource management. Overall, Jennifer’s research examines leadership and its impact on individual performance factors in organizations. She teaches courses on the principles of human resource management and on management of change.
Sven Hauff is Professor of Human Resource Management and head of the Chair of Labor, Human Resources and Organization at the Helmut Schmidt University/University of the Federal Armed Forces Hamburg. His main research interests are in the interrelationships between the design of human resource management and its effects on employees and organizational performance. Most recently, he has worked on HRM systems, job quality, job satisfaction, as well as the influence of national institutions and culture. His scientific works have been published in leading international journals such as Human Resource Management, Human Resource Management Journal, International Journal of Human Resource Management, Journal of International Management, and International Business Review.
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