What leader behaviors evoke employee innovative work behavior in Asia? Validation of a new survey scale

Abstract

In Asian workplaces, effective innovative work behavior (IWB) presents challenges. Knowledge on how Asian leaders can promote employee IWB through their behavioral repertoire is needed. This assumption prompted us to develop and validate the so-called Innovative Leader Survey (ILS), covering a repertoire of leader behaviors by which employee IWB is stimulated in Asia. Study 1 interviewed 60 high-performing leaders and employees on such behaviors, bringing forth three leader-behavioral dimensions and survey items for fostering employee idea generation, promotion, and implementation, labeled Envisioning, Energizing, and Enabling. Study 2 involved 1,037 survey respondents through which we validated these three sets of specific leader behaviors. Study 3, with 287 respondents, established ILS’s discriminant validity while all of its 11 operationalized leader behaviors were found to predict their followers’ IWB after 4 months. Future research with the ILS is proposed to enrich theory and empirical research on the relationship between effective leadership and employees’ IWB in Asian organizations.

Introduction

In the face of rapidly evolving customer demands, organizations are under increasing pressure to innovate their products, services, and processes. Given their close interactions with both internal and external stakeholders, employees possess invaluable insights into current-day customers’ needs (Wang, Eva, Newman, & Zhou, 2021). Acknowledging that employees’ individual-level creativity (idea generation) and innovation (idea implementation) are paramount for organizational survival (Anderson, Potočnik, & Zhou, 2014; Riaz, Xu, & Hussain, 2018), it becomes evident that leaders also play a critical role in fostering an environment that is conducive to realize (a continuous flow of) innovation (De Jong & Den Hartog, 2007; Hughes, Lee, Tian, Newman, & Legood, 2018; Lee et al., 2020), thereby enhancing financial performance (Katsaros, Tsirikas, & Kosta, 2020). Understanding how leaders influence followers’ innovative behaviors in these contexts holds the key to sustaining competitiveness and organizational success amidst dynamic market demands.

Despite the recognized significance of leadership in influencing individual employee innovation, previous research primarily delved into the correlation between leadership styles and conventional performance metrics, rather than focusing on innovative outcomes (Hughes et al., 2018; Lee et al., 2020). Furthermore, existing leadership models and measurement instruments, such as the American Multifactor Leadership Questionnaire (Bass & Avolio, 1997) and the Leader Behavior Description Questionnaire (Judge, Piccolo, & Ilies, 2004; Stogdill, 1962), lack broad applicability when it comes to leading Asian employees toward innovation (Watts, Mulhearn, Todd, & Mumford, 2017). Due to global market dynamics, effectively leading innovative followers in Asian work environments (and other collectivistic cultures) is likely to become of paramount importance.

The concept of transformational leadership (TFL) has often been hailed as universally beneficial for individual- and organizational-level innovation (e.g., Bass, 1997; Gumusluoglu & Ilsev, 2009; Steele, Watts, & Den Hartog, 2018). However, apart from the fact that scholars have called for considering ‘more nuanced behaviors’ instead of leadership styles (Hughes et al., 2018, p. 564), the cultural nuances in Asian countries such as Singapore, where risk aversion is prominent, can shape leaders’ reluctance to endorse disruptive or risky employee decisions – factors often correlated with organizational innovation elsewhere (Cheng & Hong, 2017; Dorfman, Javidan, Hanges, Dastmalchian, & House, 2012; Tan, Van Dun, & Wilderom, 2021, 2023). Especially for the Asian context, we need for a more nuanced understanding of leader behaviors that specifically foster innovation; in this context, we felt the need to develop and validate a culturally attuned scale for assessing innovative leader behavior in Asia (Engelen, Schmidt, Strenger, & Brettel, 2014). This is because prevailing (potentially innovation-inducing) leadership measurement instruments largely reflect Western paradigms and might not encompass the entire spectrum of behaviors essential for eliciting employee innovative behavior within Asian work contexts (Engelen et al., 2014). This notion is echoed by various alternative ideal-leader constructs proposed for collectivistic cultures (Dorfman et al., 2012; Yammarino, Salas, Serban, Shirreffs, & Shuffler, 2012). On top of that, recent publications on TFL have questioned the validity of available survey measures (Fischer & Sitkin, 2023; Siangchokyoo, Klinger, & Campion, 2020). Thus, the limitations of existing instruments underscore the urgency to explore an alternative approach that capture the multifaceted nature of leadership in fostering innovation among followers in Asian work settings.

Many scholars noted that a national culture has an effect on leader behaviors and practices (Lukes & Stephan, 2017). For instance, Engelen et al.’s (2014) study of 951 firms in eight countries on four continents showed that top management’s articulation of a vision has a significant relationship with developing employees’ intrinsic motivation, especially in individualistic countries. Leaders’ provision of individualized support is uncommon in high power-distance cultures, whereas intellectual stimulation notably motivates employees to deal innovatively with problems in low uncertainty avoidance cultures. Shao and Webber (2006) uncovered a negative correlation between TFL and innovation in China, given the country’s high power distance and preference for centralized authority.

Understanding the influence of culture on leader behaviors and practices is pivotal in discerning the behavioral nuances involved when wishing to shape organizational innovation. That is why it is important to investigate leader behaviors that are conducive to innovation, particularly in collectivistic Asian work environments (Mousa, Chowdhury, & Gallagher, 2023; Wang et al., 2021). This study therefore set out to identify which specific leader behaviors are likely to evoke employee innovative work behavior (IWB) in Asian organizations. By developing a culturally sensitive survey instrument, this research seeks to provide insights into the specific leader behaviors conducive to foster innovation, thereby contributing to both theoretical and practical implications for leader recruitment, selection, training, and development initiatives across Asia. Our research question is: Which specific leader behaviors can be captured in a survey instrument to assess, reliably and validly, their association with employee innovative work behaviors in Asian contexts?

In this paper, we report three studies. Study 1 offers a literature review as a theoretical basis for analyzing 60 in-depth interviews with which we constructed a survey scale (Hinkin, 2005; Lambert & Newman, 2022). Based on two different multisource feedback studies, with two different samples, we then established the factor structure of this newly developed Innovative Leader Survey (ILS) and ensured the tool’s validity: by linking Scott and Bruce’s (1994) three stages of innovation behavior – idea generation, promotion, and implementation – with specific leader behaviors that are likely to evoke IWBs among Asian employees.

Literature review

Employee IWB

The concept of employee IWB encompasses ‘the intentional creation, introduction and application of new ideas within a work role, group or organization, in order to benefit role performance, the group, or the organization’ (Janssen, 2000, p. 288). This definition implies that IWB is more than mere creativity arousing, although employee creativity is a necessary part of IWB, especially in the beginning, in order to generate new and useful ideas (Scott & Bruce, 1994). The scope of employee IWB further includes idea promotion and implementation of generated innovations for the expansion and renewal of products and services as well as the evolution of production processes and management systems (Montani, Battistelli, & Odoardi, 2017).

In the innovation literature, there are different perspectives on employee IWB. Dorenbosch, Engen, and Verhagen (2005) distinguish between the conception and implementation of ideas, while Scott and Bruce (1994) elaborate a triadic model comprising the generation of novel and useful ideas, the search for sponsorship, and the implementation of generated and promoted ideas. Indeed, innovation processes can be characterized as a mix of interrelated discontinuous activities (Kanter, 1988), where employees and leaders are most likely to be involved in any combination of these activities at any one point in time (Janssen, 2000; Scott & Bruce, 1994). We adopted a unidimensional yet comprehensive perspective on IWB, encapsulating Scott and Bruce’s (1994) three-stage model, as elaborated below.

First, employees can generate ideas by exploring opportunities to address performance gaps, overcome workflow challenges, and identify sources for customer dissatisfaction. The inclination toward this exploratory behavior hinges on the perceived need, willingness, and ability to innovate, denoting a readiness for change (Holt, Armenakis, Field, & Harris, 2007; Holt & Daspit, 2015; Tan et al., 2021). In the idea championing phase, employees forge alliances with supportive leaders and colleagues who can provide the necessary resources to propel proposed changes (such as personnel, funding, and time) (Amabile, Schatzel, Moneta, & Kramer, 2004; Denti & Hemlin, 2012). Notably, a conducive environment that embraces change is instrumental in fostering innovation champions (Amankwaa, Gyensare, & Susomrith, 2019; Scott & Bruce, 1994; Tan et al., 2021). The culmination of the process lies in the implementation phase, where employees invest effort in refining, testing, and actualizing an idea (Kanter, 1988). It is important to recognize that workplace innovation transcends job requirements, underscoring the need for organizational leaders and managers to understand and facilitate IWB (Montani et al., 2017).

Leader behaviors and IWBs of followers

Although no ultimate definition of leadership exists (Yukl, 2002), most definitions of leadership reflect basic elements, including ‘group’, ‘influence’, and ‘goal’ (Northouse, 2018). We define leadership here as the interpersonal process of influencing others toward achieving a desired outcome. Although a plethora of leadership styles have demonstrated positive associations with innovation, TFL is the style that has been argued to be generically effective for stimulating creativity and innovation (Mumford & Hemlin, 2017; Mumford, Scott, Gaddis, & Strange, 2002). Transformational leaders motivate their followers by communicating appealing visions, encouraging them to think of different ways of solving problems, recognizing their higher-order needs, and serving as role models (Bass & Riggio, 2006). Especially in Western work settings, TFL has been found to be positively related to employees’ innovative behaviors and organizational innovations (e.g., García-Morales, Jiménez-Barrionuevo, & Gutiérrez-Gutiérrez, 2012; Gumusluoglu & Ilsev, 2009; Rosing, 2017; Sarros, Cooper, & Santora, 2008; Steele et al., 2018). The diversity of these findings on effective leadership may stem from TFL’s theoretical emphasis on idea generation (Hughes et al., 2018; Lee et al., 2020), to the detriment of idea promotion and implementation (Wang et al., 2021). Consequently, scholars have proposed that innovation-inducing leader behaviors must supplement TFL (e.g., Anderson et al., 2014; Denti & Hemlin, 2012; Hughes et al., 2018; Siangchokyoo et al., 2020; Yukl, Mahsud, Prussia, & Hassan, 2019). Hence, the complexity of the relationship between leader behaviors that promote IWB among followers is likely to include moderating, mediating, including contextual factors (Amankwaa et al., 2019; Fischer & Sitkin, 2023; Hughes et al., 2018; Rosing, 2017; Van Knippenberg & Sitkin, 2013).

Indeed, several researchers have emphasized that effective leadership for IWB needs to consider both idea generation and the processes necessary for the implementation of ideas (De Jong & Den Hartog, 2007). Indeed, the qualitative study of 12 leaders of knowledge-intensive services revealed a broader range of leader behaviors tapping either idea generation (e.g., providing vision) or idea application (e.g., providing resources) or both (e.g., monitoring progress) (De Jong & Den Hartog, 2007). The concept of ambidextrous leadership goes one step further; leaders may stimulate idea generation and idea implementation by using paradoxical leader behaviors (Rosing, Frese, & Bausch, 2011). Whereas opening behaviors (e.g., encouraging alternative ways of accomplishing tasks) enhance employees’ exploration behaviors, closing behaviors (e.g., taking corrective action) foster employees’ exploitation activities (Rosing et al., 2011). Hence, leaders need to switch between opposing behaviors (e.g., allowing for errors vs. sanctioning errors) to foster both idea generation and idea implementation. Already in their repertoire of behaviors, leaders wishing to effectively rouse and establish effective innovative behavior among their followers must reconcile the potentially conflicting perceptions that others, and especially their followers, may have about them.

Given the complexity of effective organizational leadership for IWB, and for resolving the followers’ paradox of idea generation, development/promotion, and implementation, we argue here that leaders’ broad behavioral repertoire must carefully match followers’ activities in the innovation process; only then leaders can effectively evoke employees’ IWB. There is already some research that focused on the various stages of the innovation process (e.g., Amabile et al., 2004; George & Zhou, 2007), but very few studies have focused on the idea that different stages of innovation may require different leader behaviors in facilitating the various activities of the followers involved (Basu & Green, 1997; Gerpott, Bledow, & Kühnel, 2022). Therefore, we still know little about which and to what extent leader behaviors are effective in evoking employees’ innovative behaviors, let alone in Asian contexts. The different stages of innovation provide a useful theoretical foundation for identifying specific leader behaviors that promote employees’ innovative efforts. Specifically, we propose that different leader behaviors are required for stimulating followers’ idea generation, promotion, and implementation. In the below, we review scholarly leadership insights underpinning the three-pronged empirical approach.

Leader behaviors for follower idea generation, promotion, and implementation in Asian contexts

We do know that Asian leadership styles often reflect cultural values such as collectivism, harmony, and respect for authority (Zheng, Graham, Farh, & Huang, 2021). Leaders in Asian workplaces tend to adopt a more participative and inclusive approach to encourage idea generation among followers (Hofstede, 2001). This participative leadership style fosters a sense of belonging and psychological safety among employees, empowering them to contribute innovative ideas without fear of criticism (Javed, Naqvi, Khan, Arjoon, & Tayyeb, 2019). Such leadership behaviors include clearly communicating shared objectives for change, appreciating, and encouraging employees’ creative endeavors, actively listening to their inputs, and demonstrating a willingness to provide support. These actions foster a positive attitude among the followers, thereby encouraging collective engagement in the exploration of new and innovative ideas and solutions (Cheng & Hong, 2017; Janssen, Van de Vliert, & West, 2004). Leaders in Asian cultures often emphasize the importance of humility, which creates an environment where followers are more likely to share their ideas openly (Hu, Erdogan, Jiang, Bauer, & Liu, 2018).

The promotion of ideas in Asian work environments is influenced by the cultural emphasis on interpersonal relations and communications (Lee & Kim, 2021). To propagate employees’ ideas, managers should connect with the organizational decision-makers (Byrne, Mumford, Barrett, & Vessey, 2009), and in many cases, champion innovation themselves (Rogers, 2010). Achieving this may necessitate active relationship-building with members of other business units, stimulating cross-functional collaboration and enhancing employee ideal success. High-quality exchanges between leaders and followers not only empower greater autonomy but also provide access to better information, mitigating the fear of failure and thereby bolstering employee courage in promoting their ideas (Prieto & Pérez-Santana, 2014). These relations-oriented behaviors (Yukl, 2012; Yukl et al., 2019) help leaders maintain their followers’ task commitment and cooperation.

In Asian cultures, where followers are more anchored in their leader’s role modeling (Engelen et al., 2014), we assume that leaders demonstrating IWB themselves can effectively catalyze employee IWB (De Jong & Den Hartog, 2007). Employees can learn from their leaders’ innovation capacity through observation and renewed interaction with others (Tierney & Farmer, 2004). This reasoning is also in line with the social learning theory, which states that learning takes place vicariously by modeling and self-control (Bandura, 1982).

Implementing ideas in Asian workplaces requires leaders who can navigate the diverse cultural landscape and ensure alignment of innovative initiatives with organizational goals (Ahmad, Butt, Chen, & Liu, 2023). Authentic leadership, characterized by transparency and ethical decision-making, is particularly valuable in gaining employees’ trust and facilitating idea implementation (Lv, Jiang, Chen, & Zhang, 2022). Leaders can leverage on their extensive network, both internal and external, to garner support and resources for implementing innovative ideas, exemplifying the importance of team leadership and social capital in idea realization (Hitt, Lee, & Yucel, 2002). To ensure employees can implement (their) ideas, leaders may adopt task-oriented behaviors (Yukl, 2012; Yukl et al., 2019) encompassing planning improvement activities, clarifying roles and objectives, role-modeling, and monitoring (innovation) performance, and fostering mutual accountability for exceeding team objectives (Mumford et al., 2002; Wang et al., 2021). Leaders can thus grant employees some autonomy to determine independently how to execute a job or task and to participate in decision making (Lee, Choi, & Kang, 2021; Yukl, 2012). The opportunity to exercise self-direction and control makes employees feel important, competent, and respected (Xiong Chen & Aryee, 2007). This will therefore motivate employees to experiment in their jobs, leading to IWB. Leaders can also use constructive feedback to communicate to employees how (idea implementation) tasks should be executed and assessing whether their performance aligns with desired outcomes (Lee et al., 2021).

In sum, follower IWB is substantially influenced by leader behaviors that stimulate its three process dimensions. The subsequent sections delve into the development of a measurement instrument to assess leader innovation-stimulating behaviors that impact employee IWB.

Paper overview: Three empirical studies conducted in Singapore

Three consecutive empirical studies were conducted in public and private service organizations in Singapore (see Table 1). This city state as the research site is driven by a distinctively Asian blend of characteristics and therefore a relevant setting for investigating the Asian interplay between specific leader behaviors and employee IWBs. Singapore’s economic growth hinges already on innovation, and specifically on organizational innovation (Ng, 2012). Singapore is often seen as a microcosm of Asia, showcasing a multicultural society that encompasses Chinese, Malay, Indian, and other ethnic groups (Pang & De Meyer, 2015). Its strong emphasis on collectivism resonates with the broader Asian cultural trait of valuing harmony, group cohesion, and shared goals. Consequently, it provides a good site for developing a new survey instrument for the study of effective leader behaviors that stimulate effective follower IWB in Asian work environments.

Table 1. Scale development process

Note: KMO = Kaiser–Meyer–Olkin.

While Singapore’s leadership landscape has been influenced by Western leadership theories and practices, the nuances of the broader cultural context call for a better understanding of leader behaviors that promote followers’ IWBs. Addressing this gap has implications for leadership development, talent management, and organizational innovation strategies. In Study 1, we followed Hinkin (1998) scale-development steps by generating survey items through semi-structured interviews with leaders and employees in private and public service systems. In Study 2, we examined the reliability and factor structure of the ILS in a public service organization, following the methodology outlined by Lambert and Newman (2022). Study 3 validates the scale with a multi-actor sample comprising both support staff and academic staff from a higher educational institute located in Singapore.

Study 1

To identify a comprehensive set of leader innovation-stimulating behaviors, we held in-depth interviews: a qualitative, explorative method (Eisenhardt, 1989). The findings were interpreted with the relevant literature in the form of a new survey instrument that experts commended.

Item generation

For item development, we followed Hinkin’s (1998) recommendation to use both deductive and inductive approaches. In the first step, we specified the key employee tasks required for innovation, using existing IWBs (e.g., De Jong & Den Hartog, 2010; Janssen, 2000). Utilizing the earlier-mentioned three-stage model of innovation, Janssen’s (2000) IWB scale measures individual’s idea generation, promotion, and realization behavior in the workplace. The items developed by De Jong and Den Hartog (2010) enabled us to further define employee activities involved in idea generation, championing, and application.

Next, we reviewed the literature (presented in the above) on the relationship between leadership and innovation to identify a broad range of leadership behaviors that may promote employees’ innovative efforts within the innovation process. Moreover, we conducted semi-structured interviews with 20 leaders and 40 employees from four large service organizations in Singapore: an information and technology corporation; a public service organization which facilitates trade documentation and security administration; a company providing event and advertising services; and an educational institute targeted at special needs of individuals (see Table 2). These four organizations were purposefully selected as they had attained either a Singapore Quality Class award, Innovation Award, or People Developer Award; we thus sought to identify the best leadership behavior that support high employee IWB (Eisenhardt & Graebner, 2007). The number of leaders ranged between 4 and 15 leaders per organization, to allow for a representative leader sample in each organization.

Table 2. Profile of the interviewees in Study 1

Furthermore, following qualitative research principles, the sample size was co-determined based on carefully tracing signs of data saturation, as advocated by Guest, Bunce, and Johnson (2006), and reinforced by recent studies by Khan, Hossain, Jahed, Akter, and Pappas (2024) and Patton (2023). When we started to approach our sample size of 60 participants, new themes and insights ceased to emerge from the interviews, pointing to thematic saturation. Hence, the sample size of 60 allowed for gathering in-depth insights while remaining operationally feasible.

To ensure a broad representation of leader behaviors stimulating innovation across various industries, we have sampled a diverse set of leaders and employees, reflecting the heterogeneous business environments in Asia (Hennink, Kaiser, & Marconi, 2023). The diversity of participants also enhances the transferability of the findings across various organizational context (Patton, 2023). The final set of interviewees were predominantly male (55%), ranged between 28 and 65 years of age, and nearly every educational and socioeconomic background was represented in the sample. The employees had worked for at least 2 years with their organizations, and had been nominated by their Human Resources departments as high-performing staff: all of them agreed to participate. The inclusion of high-performing employees ensures that the study was not just based on leaders’ own self-reported behaviors, but also employees’ reflection on the relationship between leadership and (successful) innovation. The leaders were C-suite level, departmental heads, or frontline supervisors. All the participants were informed of the purpose of the in-depth interviews: to gather information about leader behaviors that evoke employee IWB. After being assured of anonymity and confidentiality, all the participants agreed to being audio-recorded.

At the start of each interview, we provided the participant with our definition of innovation-stimulating behaviors adapted from West and Anderson (1996). In addition, the participants read brief descriptions of the different innovation stages based on Scott and Bruce (1994). The interview format consisted of three open-ended questions. The questions for the employees were (1) What do managers of a highly innovative work team do? That is, what behaviors come to mind when you think of a manager who has led you effectively to be innovative? (2) Describe a time when your manager successfully convinced you that a change in process or approach was necessary for success: What behaviors did they demonstrate? And (3) Think of a situation when your manager affected the team/individual’s performance: What did your manager do to block the team/individual from being innovative? How did your manager’s behavior diminish the team/individual’s success? The same three questions were rephrased to the self-context for the leaders’ interviews. The average interview duration was 45 minutes. All the responses were transcribed immediately afterward, and all interviewees confirmed their transcript.

Leader behaviors were identified through independent transcript content coding by two researchers using Gioia’s inductive approach (Gioia, Corley, & Hamilton, 2013; Locke, Feldman, & Golden-Biddle, 2020). Both researchers generated a list of behaviors mentioned in the interviews and copied each one onto separate index cards. Differences were discussed and resolved. On removing the redundant cards, the two researchers sorted the total 110 behaviors into groups according to conceptual similarities. As recommended by Corbin and Strauss (2014) and Mathieu, Luciano, D’Innocenzo, Klock, and LePine (2020), we also used the literature to think of innovation-stimulating leader behavior categorizations. We then used Yukl (2008, 2012) meta-categories and comprehensive hierarchical taxonomy of daily managerial work to classify the specific leader behaviors. The final classification consisted of 11 leader behaviors which were mapped onto Scott and Bruce’s (1994) three employee IWB stages. Table 3 shows their initial classification and definitions based on the wider literature.

Table 3. Overview of Study 1’s leader behaviors related to the IWB subdimensions based on Scott and Bruce (1994)

Note: GI = generate idea; CI = champion idea; II = implement idea.

Content validity

Based on the 11 leader behaviors, we assessed the content validity of the generated leader behavior items that evoke employee IWB with a panel of experts, following Lambert and Newman (2022). Where possible, the survey item phrases were taken from the original interviews. In line with Kaplan and Saccuzzo (2017), we excluded draft items that appeared too complex, ambiguous, had double negatives, or did not describe a certain behavior. The remaining 42 items were then arranged in a logical and systematic way (also utilizing Yukl, 2012; Yukl, Gordon, & Taber, 2002; Yukl et al., 2019) to assist the participants to easily complete the survey involving the 11 leader behaviors.

At the item-development stage, the item-objective congruence (IOC) index was used to evaluate content validity (Rovinelli & Hambleton, 1977; Turner & Carlson, 2003). Here, the 42 items were sent to a panel of five experts (Rovinelli & Hambleton, 1977) with an IOC form which asked them to evaluate whether the items did denote what they were supposed to measure by assigning a score of +1 (clearly measures a depicted leader behavior), 0 (the content measurement is not clear or ambiguous), or −1 (clearly does not measure a depicted leader behavior); a space was provided for comments regarding the clarity and understandability of the items. The five experts had a master or a PhD degree, had worked in various innovative industries, and had been in their current role for more than 10 years. This panel consisted of two content experts with relevant quantitative research experience and three lay experts who were potential research subjects. To determine their general degree of agreement over each statement, an average IOC was calculated (Turner & Carlson, 2003). If the score was greater than 0.5, the item was deemed to be fitting (Shaikh, 2018).

Results

As shown in Table 4, most of the items achieved the required IOC scores. Two of the 42 items had a low IOC score and had to be rephrased. Item 10 was amended from ‘Implements idea generation activities’ to ‘Implements idea generation activities (e.g., brainstorming sessions, focus group discussions, strategy sessions, etc.)’. Item 36 was amended from ‘Is curious and frequently challenges the status quo during idea generation activities’ to ‘Is curious and frequently challenges the status quo’.

Table 4. Index of item-objective congruence (IOC) of each statement included in the Innovative Leader Survey (ILS) scale

Note:

^a Items were deleted as a result of correlation analysis in Study 2. The italic-faced items were amended because of a low IOC.

Study 2

The second phase of our study aimed to rigorously validate the ILS instrument developed in Study 1. Following Lambert and Newman (2022), we sought to assess the reliability and validity of the ILS, which comprised 42 items representing 11 leader behaviors. This validation process involved administering the ILS to the members of a multisource sample of focal leaders, their bosses, followers, peers, and external partners/customers. Prior research by Kim and Yukl (1995) and Thach (2002) indicated that leader effectiveness is more closely correlated with subordinates’ (or other’s) evaluations of leader behaviors than with leaders’ self-reported behaviors.

Sampling procedure

The data were obtained from one of the organizations that had previously participated in Study 1. This large public-service organization has received a Digital Service Award for their innovative way of facilitating Singapore’s cross-border trades. They had embarked on a leadership development program for their upper and middle management. One of the researchers was engaged to conduct the program.

Several weeks before the program started, a questionnaire was distributed with an accompanying note outlining this study’s purpose. The final sample size was 1,037 respondents, consisting of focal leaders (N = 86), the focal leaders’ bosses (some had two bosses due to a matrix structure, N = 117), at least three followers (N = 390), at least three peers (N = 319), and at least three external partners or customers (N = 125). The focal leaders’ ages ranged from 30 to 65 years, with a mean of 41 years. Of these, 59.9% were males and 40.1% were females. Moreover, 64% of focal leaders had occupied their current positions for over a year.

The multilevel sampling strategy ensured diverse representation of perspectives within the organization, thereby enhancing the validity and generalizability of the study’s findings (Ruvio, Shoham, Vigoda‐Gadot, & Schwabsky, 2014; Van Dun, Hicks, & Wilderom, 2017). Moreover, the inclusion of a minimum of three respondents from each rater type, such as followers, peers and external partners or customers, further enhanced the depth and breadth of insights gathered. This approach allowed for a comprehensive examination of leadership behaviors and their impacts across the organizational contexts and relationships (Van Dun et al., 2017; Van Dun & Wilderom, 2021).

Data collection procedure

The survey was administered on an online platform, with focal leaders providing a self-assessment of their own behaviors. The other raters were tasked to assess the frequency of each behavior exhibited by their focal leader. We adopted the frequency scale rather than the Likert-type agreement scale to avoid the negatively sounding ‘disagreement’ rating points: as Shipper, Hoffman, and Rotondo (2007) recognized, criticism should be avoided in most Asian cultures. This is also why we chose a 7-point scale with three points above the midpoint to allow for more variation, where 1 = ‘Never’ and 7 = ‘Always’. The raters were informed that the focal leaders would receive composite feedback on their behaviors during the workshop. All the participants were assured that the individual ratings would be used exclusively for research purposes and would remain confidential.

Data analysis

Given the known differences in self- and other-ratings, particularly in Asian cultures (Dorfman et al., 2012), we commenced our analysis by comparing self-ratings to other-ratings. As the data was not normally distributed, Mann–Whitney U tests were performed. Subsequently, we conducted intercorrelation analyses across the 11 behavior scales and 42 items. After that, we performed exploratory factor analysis using R (version 4.2.1) to ascertain whether the behaviors and items converged into a single construct. Principal axis analysis and a promax rotation (with 200 iterations) were employed in Lavaan, version 0.6-12. The use of promax rotation, which accounts for correlations between the components, was preferred over varimax rotation (Kline, 2014). Items had to have a minimum factor loading of .4 on one factor only and a minimum difference in factor loading of .2 (Kline, 2014). Also, confirmatory factor analysis (CFA) was used to evaluate the assumed factor structure (Kline, 2014). We considered both single-factor and multiple-factor models. The appropriateness of each model was examined using several indices of fit such as the ratio of chi-square to its degree of freedom, its P-value, the root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), and the comparative fit index (CFI) (Hu & Bentler, 1999).

Results

The internal consistency reliability of the 11 behaviors in the scale was computed separately for the self and others ratings. The resulting Cronbach’s alpha coefficients are presented in Table 5, demonstrating satisfactory levels overall. However, the Cronbach’s alpha of one leader-behavioral construct fell below the recommended threshold of 0.70. As suggested by Briggs and Cheek (1986) and DeVellis (2016), a lower Cronbach’s alpha might still be acceptable especially to the earlier phase of construct development (similar to Luthans, Avolio, Avey, & Norman, 2007) if the indicators show effective measurement of the intended construct, particularly in cases where the scale is brief or when measuring complex constructs. Table 6 displays the intercorrelations among these 11 behaviors, indicating moderate levels of correlation (p < .01). Hence, the ILS instrument appears to effectively capture the set of innovative leader behaviors.

Table 5. Descriptive statistics for the leader behavior scales and Mann–Whitney U Tests for the comparison between the focal leaders and all-others ratings in Study 2

Note: N _leaders = 86 (Focal Leaders); N _AllOthers = 951 (N _Boss = 117; N _Follower = 390; N _Peer = 319; N _Customer = 125.

* p < .001 (two-tailed, based on a Mann–Whitney U two-independent-samples test).

Table 6. Intercorrelation among the 11 Scales in Study 2

Note: The lower left triangle shows correlations among the scales from self-ratings; the upper right triangle shows correlations among scales for ratings from all others (i.e., boss, followers, peers, customers/partners). All correlations are significant at p < .01 level.

Comparison of the self-rated and all the other ratings of leader behaviors

Table 5 shows the descriptive statistics of all 11 behavior scales for the focal leaders’ self-ratings (ratees) and the composite of all the other-ratings (raters). The self-ratings were significantly lower (p< .05) than the corresponding means from the other raters for all the leader behaviors. This pattern of results is consistent with the view that self-rating tends to be deflated in Asia. Hofstede (2001) pointed out that Asian cultures tend to have higher power distance and collectivism scores than Western cultures. Confucian Asian employees (e.g., in China, Hong Kong, Singapore, South Korea) value workplaces where harmony, relationships, and group recognition, rather than individual achievements and confrontation, are emphasized. In some Asian cultures, emphasizing individual achievements – even if based on truth – is seen as boasting and not well accepted. Hence, the reliability of the results are not diminished as they reflect a well-known social norm and confirm the importance of using other ratings in survey studies in Asia.

Factor analysis and model fit

Next, we obtained a correlation matrix for the items associated with the 11 behaviors and deleted eight items with low inter-item and item-total correlations (see Table 7 for the deleted items). We then performed exploratory factor analysis on 34 items which converged into a three-factor model. The three factors accounted for 50.90% of the variance. The results showed a high degree of sampling adequacy (Kaiser–Meyer–Olkin), of .9873, χ² = 1283, df = 462, and a p-value of <.001.

Table 7. Results of the exploratory factor analysis in Study 2

Notes. KMO = .9873; χ² = 1032; df = 375, p < .001. Items 6 and 19 were deleted due to cross-loading. Item 29 was deleted due to low factor loadings.

Three items had to be deleted due to either cross-loadings (items 6 and 19, Table 6) or low factor loadings (item 29, Table 7). After running another exploratory factor analysis, the results showed a Kaiser–Meyer–Olkin of .9873, χ² = 1032, df = 375, and a p-value of <.001. The same three factors emerged and accounted for 52.1% of the variance.

We then conducted CFA with the 31 remaining items. The three-factor model fitted the data well: CMIN/df = 4.075, p < .001, CFI = 0.953, RMSEA = 0.054, SRMR = 0.039. The reliability coefficient for the three retrieved subscales revealed good internal consistency (α = .959 for factor 1, .904 for factor 2, and .963 for factor 3). To label the three factors, we modified Yukl’s three dimensions (2012, 2019): change-oriented behaviors, relations-oriented behaviors, and task-oriented behaviors, to: Envision, Energize, and Enable, respectively.

Study 2 thus showed that three meta-categories of behaviors seem to be important for an Asian leader’s promotion of IWB among his or her followers. Although this procedure was the first step in establishing the ILS’s factor structure, a more rigorous cross-validation with an independent sample was carried out next.

Study 3

The main purpose of Study 3 was to find out if we could replicate Study 2’s three-factor structure in a different sample. We administered the ILS instrument in a large higher education institute in Singapore. The leaders’ self-evaluations were collected along with multisource feedback and, 4 months later, their followers self-reported their IWB.

Sampling procedure

We used a mixture of purposive and convenience sampling techniques, leveraging the first researcher’s access to the sample and the difficulty of gathering a large, diverse group of participants from one organization (May & Perry, 2022). First of all, we purposively selected a leading educational institute in Singapore for Study 3, which is renowned for its innovation in education and research, providing an ideal setting to explore the leader behavioral repertoire in progressive, innovation-oriented organizations. The institution’s proactive nurturing of innovation facilitated a diverse and large pool of leaders for our study, enhancing the credibility and scope of our data collection and analysis. To allow for the representation of diverse viewpoints and experiences, both academic and non-academic support-staff leaders and employees were invited to participate, thereby enriching the dataset and the applicability of our findings across different organizational contexts (Eagly & Chin, 2010; Esen, Bellibas, & Gumus, 2020).

The convenience element of the sampling strategy was due to the first author’s involvement in a leadership development course at the studied organization (Etikan, Musa, & Alkassim, 2016), which also led the organization to allocate time for its leaders to participate voluntarily. This practical access allowed direct engagement with participants across the organization (both in highly professionalized roles to more administrative support roles) that were interested in leadership development (Patton, 2023). This streamlined participant recruitment and increased the likelihood of participation (Belliveau & Yakovenko, 2022).

Several weeks before the first leadership development workshop was to be conducted, the 26 focal leaders comprising 12 academic and 14 non-academic staff (middle and upper-level) were asked to nominate their raters. Similar to Study 2, in terms of sample size we aimed to include a minimum of three respondents from each rater type per focal leader. Thus, apart from their direct bosses, we asked them to name at least three of their followers, at least three peers (i.e., same-level colleagues from the same unit), and at least three external partners or customers. This multisource feedback approach facilitated a comprehensive evaluation of leader behaviors from diverse viewpoints. Crucially, the nomination was overseen and approved by the HR manager responsible for staff development, ensuring fairness and transparency in the selection of raters. All the respondents were assured that their individual reports would not be seen by their managers or anyone else in the organization and that only composite feedback on the behaviors would be presented to the focal leaders for leadership development purposes. The response rate was 99.3% (287 out of 289 invited raters, N _Leader = 26, N _Boss = 26, N _Follower = 78, N _Peer = 71, N _Others = 86). In the second wave of data collection 4 months later, 76 (97.4%) of the 78 followers responded.

Measures

The online ILS instrument included the 31 items representing the three subscales (Table 7). All the raters were asked to assess the frequency of the focal leader’s behaviors with the 7-point scale (1 = never, 7 = always). The Cronbach’s alpha for the Envision subscale (α_Leader = .952, α_All-others = .96) was .973, for Energize (α_Leader = .873, α_All-others = .921) was .924, and for Enable (α_Leader = .953, α_All-others = .972) was .981.

To measure the discriminant validity of the ILS conducted 4 months later, we also assessed the raters’ IWB using the nine Janssen (2000) items, again on a 7-point scale (1 = never, 7 = always). An example item is: ‘I seek new working methods, techniques or instruments’. Its Cronbach’s alpha was .930.

Data analysis

First, we ran Mann–Whitney U tests to compare the self-ratings with all the other raters to confirm Study 2’s findings. Then, we investigated whether the developed factor structure of the ILS could be replicated by conducting a CFA on the item-level data to examine the factor structure of the proposed instrument. The model fit was examined with several indices such as the chi-square, the RMSEA, CFI, as well as SRMR.

Next, we ran a multiple linear regression analysis of the leaders’ Envision, Energize, and Enable behaviors with the dependent variable: their followers’ IWB 4 months later. This approach was chosen to delve deeply into the nuanced interactions between these leader behaviors and the assumed subsequent follower outcome. Furthermore, we employed structural equation modeling to investigate the moderating influence of Envision, Energize, and Enable on followers’ IWB. Structural equation modeling was selected due to its ability to construct comprehensive measurement models for both the independent and dependent latent variables, each supported by multiple observed variables. This method not only allowed us to assess the individual impact of Envision, Energize, and Enable on IWB but also to explore the interrelationships between the leader behaviors. Considering the constraint of small sample size and the non-normal, categorical data, we utilized a robust variant of the diagonally weighted least squares estimator within the Lavaan version 0.6-12 software. This robust approach was essential for accurate analysis, providing robust standard errors and a scaled test statistic as suggested by Yuan and Bentler (2007).

Results

Comparison of the self-rated leader behaviors with other raters

The Mann–Whitney U tests confirmed Study 2’s findings, i.e., the leaders’ self-ratings were significantly lower than those from all the other raters for the three ILS subscales (Envision: W = 2,326, p-value = .02, Energize: W = 2,409, p-value = .03, Enable: W = 2,298, p-value = .01).

ILS factor confirmation

The entire sample’s data were tested for factorability which yielded a Kaiser–Meyer–Olkin of .99. The presumed three-factor model could be confirmed through CFA in terms of its model fit indices: χ²₍₄₃₁₎ = 985.789 with p-value = .000, CFI = .935, RMSEA = .067, and SRMR = .039. All 31 items loaded positively with standardized factor loadings of at least .719 on the three ILS scales (Table 8).

Table 8. Results of Study 3’s confirmatory factor analysis

Relationship between ILS and IWB

The correlations in Table 9 indicated that there was a strong relationship among the factors (r _min = .870, r _max = .947), i.e., the behaviors observed in the ILS seemed to be compatible or homogeneous. Moreover, they correlated significantly with employees’ IWB.

Table 9. Summary of Study 3’s descriptive statistics and zero-order correlations of the ILS factors and followers’ IWB

Note: Cronbach’s alpha values are presented on the diagonal between brackets. All correlations are significant with p < .01.

We wanted to know, though, if the single factors were also significantly related to employee IWB. Thus, we tested different models, starting with the direct influence of the three factors (Envision, Energize, and Enable) on employee IWB by performing a simple linear regression. The result showed a significant relationship (p-value = .000, β = .899, R ² = .879). Although we saw that the ILS can be used to predict IWB, we wished to break down the ILS in terms of its latent variables: Envision, Energize, and Enable, and show their relationship with IWB. Hence, we conducted a multiple linear regression with these three predictors and IWB as the dependent variable. However, this model was rejected due to strong covariances between Envision, Energize, and Enable, indicated by high variance inflation (VIF_Envision = 9.67, VIF_Energize = 6.41, VIF_Enable = 14.67), leading to insignificant relationships between Energize and IWB as well as Enable and IWB. Therefore, we used structural equation modeling starting with the moderating effect of Energize between Enable and employee IWB (Model 1, Table 10). The model fit indicators were all unsatisfactory, with CFI = .018, TLI = .039, RMSEA = .085 and SRMR = .164 (Schreiber, Nora, Stage, Barlow & King, 2006). Similar results were obtained on testing the moderating effect of Energize between Envision and Enable (Model 2, Table 10). Swapping the predictors and moderators around did not yield better results.

Table 10. Model fit indices to establish the relationship between ILS and IWB in Study 3

Note: DWLS = diagonally weighted least squares estimator, ML = maximum likelihood.

Considering that Energize had the weakest direct correlation with IWB (Table 10), it could be assumed that Energize functions better as an intermediate variable between other predictors. Hence, we tested Energize as the mediator. Model 3 (Table 10) shows better fit indices than achieved with the moderation models. However, the CFI, TLI, RMSEA, and SRMR were still mediocre. Additionally, a p-value of .000 for the Chi-Squared test highlighted that there were significant differences between the model and the data (Kline, 2014; Schreiber et al., 2006). Since we had ordinal discrete data, analyzing Model 3 with the maximum likelihood estimation method delivered non-satisfactory model fit indices (see Table 10). Hoyle and Isherwood (2013) noted maximum likelihood was developed for continuous data but that the diagonally weighted least squares estimaton method is robust against deviations from normality and so better suited for ordinal discrete data. Hence, Model 4 was analyzed utilizing the diagonally weighted least squares estimation method leading to much better model fit indices such as CFI = .930, TLI = .925, RMSEA = .023, and SRMR = .041 (see Table 9). The p-value for the Chi-Squared test was .224 meaning this model did not deviate significantly from the analyzed data (Table 10 and Fig. 1).

Notes. Env = Envision, Enr = Energize, Enb = Enable, IWB = Innovative work behavior of followers. Survey items 6, 19, and 29 are not included. Description and item labels can be found in Table 7. All effects are significant with p < .001.

Figure 1. Structural model on effects of leader behaviors on followers’ IWB, Study 3.

In addition, we used the previously established structural equation model with each of the innovation process stages, i.e., idea generation, championing, and implementation. Although there is a significant relationship between all the subscales and stages (Table 11), the results show that employees’ idea generation behaviors are mostly driven by leaders’ Envision behaviors (β = 1.037), whereas leaders’ Energize behaviors support more employee idea championing (β = .748), and leaders help employees best via Enable behaviors to implement their ideas (β = .838). Thus, the three ILS subscales paralleled the logic of the three employee-innovation stages our research began with.

Table 11. Effects of the ILS subscales on employees’ idea generation, championing, and implementation behaviors, study 3

Note: All effects are significant with p < .001.

Discussion

Previous attempts to investigate the connection between leader behaviors and employee innovation mainly involved TFL in Western settings (Watts, Steele, & Den Hartog, 2020). It is uncertain if such leader behaviors correlate with employee IWB in Asia (Yukl, 2012; Yukl et al., 2019). Moreover, empirical studies exploring the impact of innovation-driving leader behaviors on individual employee innovation behaviors in Asia are still scarce and needed.

In this paper, we therefore presented the development of a new survey scale for assessing specific leader behaviors that evoke employee IWB in Asian contexts: the ILS. Drawing upon Scott and Bruce’s (1994) three-stage model of innovation, we suggest the importance of complementary leader innovation-stimulating behaviors in facilitating or evoking employee efforts to generate, promote, and implement innovative ideas. By linking leader behaviors directly to (Asian) employees’ innovation realization, our study contributes to deepening cross-cultural leadership models, acknowledging the intricacies of leader behaviors that stimulate innovation in non-Western, collective work settings. By situating our research within Asia and emphasizing concrete, observable behaviors, we challenge the universality of Western theories of effective leadership, advocating leader behavior models fit for a particular purpose or situation, and sensitive to cultural variations (Dorfman et al., 2012; House, Hanges, Javidan, Dorfman, & Gupta, 2004). Our findings reinforce the importance of tailoring leadership approaches to specific cultural contexts, paving the way for a more globally relevant leadership theory that recognizes the diversity of leadership practices and behaviors and their impacts on innovation (Cheng & Hong, 2017; Hofstede, 2001).

Furthermore, our study highlights the behavioral-specific extension of the Scott and Bruce’s (1994) three-stage model of innovation, we show that the matching three-stage ILS dimensions, Envision (11 items), Energize (6 items), and Enable (14 items), promote the required employee activities in the innovation stages. The items belonging to these three sets of IWB inducing leader behaviors underscore the pivotal importance of leaders fostering an environment of respect and psychological safety for learning and open, emphatic communication, elements often overlooked in traditional Western-centric leadership models (Javed et al., 2019). The items also aim to measure the genuine involvement of leaders in actively seeking new ideas, also by actively challenging the status quo, and then incorporating these ideas into actual decisions, nurturing an atmosphere in which people can jointly learn and innovate (Kim & Senge, 1994). Our findings advocate for a more inclusive understanding of leader behaviors that stimulate innovation, one that acknowledges the cultural and contextual diversity of the global workplace. Thus, a key contribution of this research lies in its direct linkage of three types of specific leader behaviors to the three stages of employee-driven innovation within an Asian context.

Additionally, by demonstrating how the ‘Energize’ dimension acts as a crucial mediator between envisioning and enabling innovative efforts, this research delineates a sequence that begins with leaders captivating their followers with a compelling vision and cumulates in building trust-based relationships that facilitate support for voicing and promoting innovative ideas as well as for their development and implementation (Mumford et al., 2002; Prieto & Pérez-Santana, 2014). We provide empirical evidence supporting the idea that leadership can significantly impact innovation through a specific order of targeted behaviors (Amabile & Pratt, 2016). This insight enriches the discourse on transformational and other leadership styles in relation to innovation by offering a detailed, behaviorally anchored framework that can be operationalized across different cultural contexts (Antonakis & House, 2014; House et al., 2004).

Overall, our study contributes to the theoretical understanding of effective leadership and innovation by offering a nuanced, empirically validated model of innovation-simulating leader behaviors tailored to Asian contexts. To further advance our knowledge of the link between leader behavior and innovation, given the complex (sometimes even paradoxical) and ambidextrous nature of effective leadership (Wang et al., 2021), we propose as a first step that carefully delineated sets of leader behaviors should be derived from its own cultural context. Only at a later stage more generic effective-leader theories can be crafted, so that the cultural consequences can then be incorporated. Our research therefore calls for further explorations of the culturally contingent nature of effective leader behaviors that foster innovation in a complex interplay.

Practical implications

Many organizations rely on survey research to assess and learn about organizational behaviors for their own continuous organizational development. Moreover, organizations across the globe are particularly interested in boosting leader behaviors that foster follower innovation behaviors because it is widely acknowledged that leaders can (and must) stimulate followers to produce innovations that lead to high performance (De Jong & Den Hartog, 2007; Hughes et al., 2018; Lee et al., 2020). The here presented ILS offers a reliable and valid measurement to gauge the extent of innovation-stimulating leader behaviors in organizations. While offering participating managers a valid behavioral ‘mirror’, the ILS empowers organizations with a comprehensive 360-degree tool, designed to evaluate and cultivate managers’ behaviors for nurturing more effective innovation among their followers.

Specifically for Asian managers, the identified behaviors should support them to overcome their typical fear of failure (‘kiasu’) (Cheng & Hong, 2017). Kiasu is entrenched in many Asian cultures which can impede innovation due to risk aversion and uncertainty avoidance (Hofstede, 2001). By utilizing insights from the ILS, leaders can implement targeted interventions that address these cultural nuances, creating environments that encourage risk-taking and experimentation, thereby reducing the negative impact of ‘kiasu’. These insights can help leaders develop strategies that create psychological safety within their teams, empowering team members to take calculated risks without the fear of negative repercussions. Additionally, the ILS can offer strategies for developing a growth mindset among the employees, which can diminish the paralyzing effects of ‘kiasu’ by embracing productive failure as a critical learning process (Kapur & Bielaczyc, 2012).

Training initiatives grounded in ILS findings equip leaders with tools to envision, energize, and enable innovative behaviors within their teams. By addressing cultural impediments head-on, organizations pave the way for breakthrough innovations and sustainable organizational growth. Armed with the insights gathered with the ILS, leaders can strategically initiate leader-behavioral changes by championing a culture of transparency and collective learning, where successes and failures alike are celebrated as opportunities of growth (Edmondson, 2003). By creating safe spaces for open dialogue and knowledge sharing, leaders can cultivate an ethos of continuous improvement and innovation. Also, encouraging employees to reflect on and learn from their experiences promote a culture of inclusivity and adaptability, helps organizations to thrive in an ever-changing landscape (Javed et al., 2019).

The ILS can also serve as a valuable tool for talent management and succession planning efforts within organizations. By identifying and developing leaders who exhibit strong innovation-stimulating behaviors, organizations can build a pipeline of future leaders capable of driving innovation and, thus, organizational growth. Moreover, the ILS can inform recruitment and selection processes, enabling organizations to identify candidates with the potential to thrive in roles that require innovative leader behavior.

Limitations and future research

This paper provides the first empirical account of a new set of innovation-stimulating leader behaviors, designed to fit Asian work contexts. While it provides an invaluable empirical account of a spectrum of innovation-stimulating leader behaviors, tailored for Asian work environments, it is important to recognize that this research is not definitive; Future exploration must investigate deeper into the alignment between the identified ILS behaviors and corresponding actions as documented in the leadership-and-innovation literature. This exploration holds the promise of refining the ILS tool to enhance its (ideally joined) practical and scholarly utility. Although many of today’s organizational practices would need the deployment of the scale introduced herein as part of a comprehensive leadership behavior assessment, it might be hampered by the fact that the current scale comprises many (31) items. In today’s rapidly evolving corporate landscape, simplicity and ease of use are becoming pivotal factors in the adoption of any organizational tool. However, the depth and breadth of the scale also provide a wealth of data for future exploration. The extensive dataset can be leveraged to explore intricate relationships between innovation-stimulating leader behaviors and various innovation-related constructs. By delving deeper into these relationships, researchers can potentially identify subsets of items that capture the essence of effectively evoking or leading innovations of various sorts. This process of refinement, guided by empirical evidence, could lead to a more concise yet equally insightful version of the scale, balancing depth, and practicality.

Moreover, as our empirical research focus was mainly on large Asian service organizations, other leader behaviors might be found in other sectors. One behavior could be the induction of disruptive innovation, which is needed in all types of organizations, especially in today’s operating environment. Future research on leader innovation-stimulating behaviors needs to also examine the role of organizational characteristics in shaping or constraining innovation-inducing behaviors.

Future academic research with the ILS must establish its external validity. While this study involved organizations in Singapore, one could assume that employing the current version of the ILS instrument is limited to similar organizations, or at least to organizations in Asia. Yet, we encourage more evidence via cross-national deployments of the ILS. A final limitation of our research so far lies with the small sample size and the multi-rater nature of our data sets. Moving forward, it would be prudent to perform CFA with grouping variables, as recommended by Kline (2014). Additionally, scale validity of one dataset does not necessarily extrapolate to all datasets, as highlighted by Lambert and Newman (2022), warranting the need for careful consideration of each ILS application through CFA. In conclusion, our research lays the foundation for the ILS as the vanguard instrument for Asian organizations seeking to amplify their innovation-stimulating leader behaviors. Refining and augmenting the ILS’s utility will hopefully also foster innovation-stimulating leader behaviors across diverse Asian organizational landscapes.