Review of Literature and Hypotheses Development

IWB is the ability of an individual to adopt, implement, and/or make use of creative ideas to solve problems in his/her work role, work unit, and/or organization. ^{Janssen (2005)} states that IWB is the individual behavior that manifests before and during the implementation of a creative idea. Examples of such behaviors include search of new technology or process, suggesting new ways of achieving goals, finding resources considered necessary to implement new ideas, and application of novel working methods to benefit job performance, work unit, or organization. IWB has long been considered to be a crucial factor in facilitating innovation in an organization (^{Isaksen & Akkermans, 2011}), as IWB is considered to be "a voluntary willingness by employees to perform on-the-job innovation" (^{Bysted & Jespersen, 2014}, p. 218).

Coworker Knowledge Sharing and Innovative Work Behavior

Knowledge is an important resource to solve problems, propose new solutions, create core competencies, learn new techniques, and initiate positive change (^{Liao et al., 2009}). In organizations, knowledge often is "embedded not only in documents or repositories but also in organizational routines, process, practices, and norms" (^{Ma et al., 2008}, p. 98). It is a valuable resource that individuals share with each other, and when shared regularly and frequently becomes an organization's property. Although knowledge is powerful and essential, it must be exchanged successfully to make it useful. In organizations, knowledge management practices explore how knowledge is created, stored, shared, and disseminated. Knowledge sharing is the foundation and most critical phase of knowledge management. Knowledge sharing is characterized as an individual level construct as knowledge is stored in an individual's mind and it is their discretion as to how and when to utilize or share it. Innovation is mostly dependent on knowledge diversity as well as employees’ ability to take the initiative of sharing their knowledge with others.

Coworkers, in particular, can provide useful knowledge and information that could be helpful to enhance IWB ^{Kim et al. (2015)} call for further research on the effect of CKS and SKS on creative endeavors of individuals at the workplace. Support of coworkers is positively associated with an employee's creativity (^{Zhou & Hoever, 2014}). ^{Zhou and George (2001)} have reported that employees who experienced high job dissatisfaction demonstrated more creativity when they had coworkers’ help and support. According to ^{Chiaburu and Harrison (2008)}, coworkers are better aware of the tasks and challenges faced by focal employees, therefore, their knowledge and expertise could help focal employees to perform more efficiently and effectively. ^{Bakker et al. (2004)} applied the job resource perspective to identify coworkers as a valuable job resource whose knowledge sharing contributions could help focal employees to improve their job performance. Coworker support is a type of social support received by employees in organizational settings; it is the extent to which employees believe that their coworkers would support them in work-related tasks and challenges.

As mentioned earlier, since employees spend one-third of their lives at workplaces, and in some cases they spend more time with coworkers than with their families, supportive coworkers could improve the overall wellbeing of focal employees and help them reduce their work stress (^{Halbesleben & Wheeler, 2015}). Coworker support enable employees to be more productive, creative, and innovative, especially when they are faced with difficult tasks and situations. CKS is a critical type of coworker support that might facilitate generation and implementation of new ideas. As focal employees and their coworkers work in similar organizational settings, they are expected to share knowledge as a norm.

There are reasons to believe that CKS enhances employees’ IWB First, when coworkers share knowledge and information, a focal employee gets more diverse perspectives to solve problems. This further enhances employees’ likelihood of adopting unconventional approaches to generating novel responses (^{Amabile & Pratt, 2016}). Without shared knowledge/information, ^{Amabile and Pratt (2016)} argue that employees have limited horizon to suggest novel and acceptable solutions. Second, coworker knowledge is highly relevant and it exactly addresses issues that the organization is facing. ^{Chiaburu and Harrison (2008)} suggest that coworkers are an integral part of social environment and are in immediate access to organizational employees. Their knowledge is easily accessible and employees find it convenient to have brain storming sessions with them. Furthermore, during discussions, better and constructive ideas evolve because coworkers possess technical knowledge and perspectives that are needed by a focal employee. Third, to implement ideas, the initiator of the idea needs strong social support and trusting relationships. Ideas become successful if they are executed with minimum resistance. Therefore, those who initiate an idea in the workplace need minimum resistance to make it successful. Coworker knowledge sharing is based on strong interpersonal relationships resulting in a supportive work environment that encourage employees to exchange knowledge and expertise, actively and constructively, which grants them the freedom to support each other's ideas. Fourth, sharing relevant knowledge can nurture a positive climate between focal employees and coworkers who share this knowledge. This helps in alleviating fear of failure in organizational employees. On the other hand, as one also uses knowledge to maintain expert power within an organization, most employees are often unwilling to share their knowledge for fear of losing their competitive advantage at the workplace (^{Kim et al., 2015}). This hoarding of knowledge/information from coworkers leads to a feeling of distrust amongst them (^{Černe et al., 2014}). When knowledge is shared by someone, it is interpreted as a benevolent behavior, thus increasing interpersonal trust among peers. In such an environment, employees are more likely to offer new ideas or novel solutions, with less fear of being embarrassed or dejected in case the ideas are eventually ineffective. Previous research has shown how information exchange develops trusting relationships, which leads to increase IWB s (^{Gong et al., 2012}). Fifth, coworker knowledge sharing reflects the norm of reciprocity from repeated social interactions resulting in reciprocated helping activity, responsibility, or obligation to reciprocate by creating and implementing new ideas. Based on the above arguments, we expect the following:

Hypothesis 1: Coworker knowledge sharing is positively related to employees’ innovative work behavior.

The Moderating Effect of Supervisor Knowledge Sharing

By taking an interactional perspective, we first discuss the situational factor in describing the boundary conditions of the influence of coworker knowledge sharing on IWB Although CKS may significantly influence an employee's IWB, this sharing of knowledge by a coworker may depend on various situational factors. One such situation factor may be leaders/supervisors themselves. As they are powerful organizational actors, their behavior would critically moderate the relationship between CKS and IWB Since supervisors and coworkers are key actors in the workplace, it is worthwhile to examine the interaction effect of CKS and SKS on IWB Thus, this research specifically examines the moderating role of supervisor knowledge sharing and predicts that knowledge shared by these two sources, that is, supervisor and coworkers, will play complementary roles to enhance IWB of focal employees.

Supervisors exert substantial influence over their subordinates by virtue of their legitimate authority and control over resources (e.g., budget and scheduling) and outcomes (e.g., performance appraisal and salary) that are important for employees (^{Eisenberger et al., 2002}). Receiving support from coworkers may prove detrimental to a focal employee's morale if supervisors fail to advice on how to allocate resources to those decisions in the context of the flow of work within organizational units. Although knowledge/skills shared by coworkers are useful, their effect on focal employees’ IWB can vary. Supervisor support offers distinct resource advantages to a focal employee over his or her coworkers. Given that members in a group form distinct exchange relationships with their supervisor, they view supervisor support as a desirable yet limited resource (^{Dineen et al., 2006}). Therefore, when employees receive knowledge from supervisors, they think of it as a favorable treatment and tend to apPRA ise the situation as resource abundant and feel indebted. They take this knowledge more relevant, realistic, and congruent with organizational goals. When a supervisor shares knowledge, he/she has a trade-off to manage. Supervisors often share knowledge about the ways to accomplish tasks . They are more concerned to meet targets that are usually short term and allocate greater resources to achieve these targets. Therefore, they share knowledge that is focused on plans to improve operational processes and bring efficiency in task related performance. Supervisors might inculcate fear among employees who want to engage in IWB due to ideas, information, knowledge, and dynamic perspectives from coworkers. Employees then strive for a balance between what coworkers share and what their supervisors share. They might feel a contradiction because coworkers would share knowledge without worrying too much about resources needed for the new ideas. However, supervisors think about resources and might be stringent towards allocating resources to these ideas. This would lead to weakening the effect of CKS on IWB

^{Szulanski (2000)} states that usefulness of shared knowledge largely depends on the acceptance and assigned value by recipients. Furthermore, since supervisors are in a more authoritative position to dictate critical workplace decisions, due to their relevant and up to date knowledge, they may very well counter the positive effect of knowledge shared by coworkers on employees’ IWB Innovation is not only about generating an idea but actually realizing and implementing it in organizational settings. Employees would feel better supported in case of implementing innovative ideas if they take forward information and knowledge shared by their supervisors. Due to the risky nature of individual innovation (uncertainty associated with the outcome of the idea), employees need support from their supervisors in executing the idea. Knowledge shared from a supervisor might be perceived as less risky and more contemporary in nature as supervisors have a broader perspective about potential opportunities and threats. They are well-informed about current organizational strategies as well as plans of the competitors. Their knowledge about future demands of their respective departments and organizations is more refined and relevant as compared to subordinates working in their departments. Therefore, employees might perceive supervisors’ knowledge to be more authentic, Practical, novel, realistic, and specific as compared to their coworkers’ (^{Ng & Sorensen, 2008}).

Furthermore, most of the times employees may only be able to draw similar knowledge, pertaining to various organizational tasks, from their coworkers and supervisors alike. This overlap may lead to knowledge redundancy for recipients and thus utilizing both sources for knowledge/information may not always be incrementally beneficial. This makes supervisor support more sought after as compared to coworker support (e.g., ^{Ng & Sorensen, 2008}). In fact, in their meta-analysis, ^{Ng and Sorensen (2008)}demonstrated a stronger relationship between supervisor support and employees’ increased job satisfaction, increased affective commitment, and lowered turnover intention as compared to their coworker support. From the above arguments and related findings, we assert that the positive relationship between CKS and IWB would be attenuated when the level of knowledge shared by supervisors is high rather than when it is low. Thus we expect the following:

Hypothesis 2: Supervisor knowledge sharing moderates the relationship between coworker knowledge sharing and employee's IWB such that this relationship will be weaker when supervisor knowledge sharing is high.

The Moderating Effect of Thriving at Work

^{Spreitzer et al. (2005, p. 538)} define thriving at work as the "psychological state in which individuals experience both a sense of vitality and learning at work". ^{Nix et al. (1999)} define vitality as "feelings of energy and aliveness and a zest for work". Similarly, ^{Edmondson (1999)} defines learning as "the acquisition of skills and knowledge to build confidence and capability". Individuals who are thriving at work are not only constantly learning new things, but they are also highly energetic, motivated, and committed to their work roles. Vitality and learning go hand in hand for employees who want to thrive at work. Thriving individuals gauge their progress through self-regulation (^{Porath et al., 2012}). It also helps employees to adjust their context at work as well as to promote their personal growth as an adaptive function. ^{Spreitzer et al. (2005)} suggest that employees having higher thriving gauge their development much better than those who have lower thriving. They not only emphasize on improving short-term effectiveness but also strive to increase long-term adaptability to their work contexts. Thriving employees do have an intrinsic motivation to engage in activities and behaviors that are more meaningful and purposeful to them, such as creativity and innovation (^{Amabile & Pratt, 2016}; ^{Anderson et al., 2014}).

The vitality dimension of thriving makes employees passionate about what they do. When coworkers share knowledge, higher thriving individuals would take that knowledge as an opportunity to further develop their own competencies and a sense of personal growth (^{Spreitzer et al., 2012}). ^{Feeney and Collins (2015)} assert that the aspects of growth, learning, meaningfulness, development, and prosperity are integral to the concept of thriving at work. It lets employees learn new things as well as seek new opportunities; instead of believing in status quo, they try to proactively engage in exploring new ways of doing things while improving existing systems (^{Lerner et al., 2011}). Knowledge and information from coworkers are taken as opportunities to learn, grow, prosper, and develop when thriving at work is high. ^{Moreover, Kark and Carmeli (2009)}argue that high vitality individuals are more prone to creative work behavior. Similarly, ^{Carmeli and Spreitzer (2009)} demonstrated that thriving at work increases employees’ IWB Employees would thus try to take this opportunity to generate and implement novel and Practical ideas.

Thriving employees exhibit superior performance due to their continuous learning ability when interacting with their peers (^{Paterson et al., 2014}; ^{Spreitzer et al., 2012}). According to Zhou and Hoever (2014), success of such interactions is determined by coworkers who share their knowledge with focal employees. Knowledge sharing by coworkers acts as a facilitator for thriving employees aspiring for enhanced performance as they are continuously learning from their interactions with these coworkers (^{Gerbasi et al., 2015}). Furthermore, according to ^{Spreitzer et al. (2012)}, high thriving employees are likely to be more resilient. Thriving at work enables employees to acquire knowledge which contributes towards their continued confidence building. This resulting knowledge accumulation increases these employees’ abilities to spot more organizational opportunities for improving their organizational processes (^{Magni & Maruping, 2013)}. Furthermore, these employees have high work engagement, coupled with intrinsic motivation and willingness, to solve organizational issues and to improve team performance (^{Zhang & Bartol, 2010}). Therefore, it enhances employees’ willingness to challenge current status quo for organizational improvement, as well as increasing their capabilities for implementation of new ideas. Therefore, it is reasonable to propose that the relationship between CKS and IWB further strengthens when thriving at work is high rather than low.

Hypothesis 3: Thriving at work moderates the relationship between coworkers’ knowledge sharing and employees’ innovative work behavior, such that this relationship will be stronger when levels of employees’ thriving at work are high rather than when they are low.

Method

Results

Correlations among the study variables are provided in Table 1. The table also presents Spearman-Brown coefficient for each variable. Equal length Spearman-Brown coefficients are presented for variables with even number of items (IWB and thriving), while equal length Spearman-Brown coefficients are presented for variables with odd number of items (CKS and SKS). It is a well-known fact that there is a difference between observed and true correlations. Furthermore, it is also noticed that the observed correlation underestimates the true correlation between the study variables (^{Salgado et al., 2019}). In Table 1 we have presented uncorrected correlation coefficients between the study variables, especially between independent variables (CKS), moderators (SKS, thriving), and the dependent variable (IWB) that are underestimated. To overcome this issue, we also present corrected correlation between these variables. The measurement error in Xand Ywas calculated by employing the formula to correct observed correlation for attenuation (e.g., ^{Kline, 2011}; ^{MacKinnon, 2012}; ^{Schmidt, 2015}). As this formula required reliability coefficients for the study variables, they were attained from calculated internal consistency of CKS, SKS, thriving and IWB scales of the current sample. Corrected correlations between dependent, independent, and moderating variables are also presented in Table 1.

Table 1. Correlation among Study Variables and Corrected Correlations between Dependent, Independent and Moderating Variables 

Note. ¹Spearman-Brown coefficient equal length. ²Spearman-Brown coefficient unequal length. IWB = innovative work behavior; CKS = coworker knowledge sharing; SKS = supervisor knowledge sharing.

^*p < .05 (2-tailed)

^**p < .01 (2-tailed).

It can be observed from Table 1 that the Spearman-Brown coefficient reliability coefficients for study variables are above the acceptable value of .70 (^{Eisinga et al., 2013}). Furthermore, a positive and significant correlation between variables under investigation is observed. The table also presents corrected correlations of IWB with CKS (.681, ∆R= .082), SKS (.458, ∆R= .064), and thriving (.584, ∆R= .059). It is also worth mentioning that average difference between the observed and real correlation is 13.7%. These statistics provide ample support for the approval of H1 as real and observed statistics present a positive relationship between CKS and IWB

Hierarchical multiple regression was used to evaluate the effects of independent variables and the interaction terms upon the dependent variable IWB Table 2 includes partial correlation between variables to test the strength and direction of the linear relationship. Furthermore, we also calculated the squared population cross-validity coefficient (R²_cv) for each model, employing it along R, R²and adjusted R². According to ^{Salgado et al. (2019)}, multiple regression analyses are biased as they capitalize on chance. This dependence on chance leads to change in R²size when applied from one sample to another. R²_cvis a much more effective estimate of effect size than other estimates generated from regression analyses. This study used ^{Browne's (1975)} formula to estimate the squared population cross-validity as Monte Carlo examinations show that its efficacy is higher than other formulae.

Table 2. Hierarchical Regression Analyses 

Note. IWB = innovative work behavior; CKS = coworker knowledge sharing; SKS = supervisor knowledge sharing.

^*p < .05 (two-tailed)

^**p < .01 (two-tailed)

In the first step of hierarchical regression analyses, only control variables were entered. It can be noticed that control variables had non-significant relationships with IWB However, in sum, they explained 1.9% (p< .05, R²_cv= .015) variance in IWB The second step of this analysis aimed at testing Hypothesis 2. It could be noticed from the results that CKS had a significant positive effect on IWB (β = .596, p< .001). Furthermore, CKS along with control variables explained 36.6% (p< .01, R²_cv= .36) variance in IWB The third step of the analysis was carried out to test SKS 's moderating effects on the relationship between CKS and employee IWB Moderator SKS had a positive and significant effect on IWB (β = .116, p< .001). Furthermore, the interaction term between CKS and SKS was also significant (β = -.046, p< .05). The squared population cross-validity coefficient, R²_cv, reported for this model was .362. Partial correlation of control, independent, and interaction effects with IWB were assessed to identify any significant differences with correlation. Partial correlations reported in Table 2 are smaller than the simple correlation and greater than 0. However, none of the partial correlations was found significant while adjusting the effect of additional variables. Results were plotted using ^{Aiken and West's (1991)} procedure as follows.

As can be observed from Figure 1, SKS dampens the positive relationship between CKS and IWB Asimple slope (see Table 3) was also developed for this study to further evaluate the dynamics of interaction variables. Table 3 shows that the relationship between CKS and IWB is significant for both +1 and -1 standard deviation level of moderator SKS However, it is stronger when SKS is low, -1SD(simple slope = .716, CI[.604, .828] and weaker when SKS is high, +1SD(simple slope = .623, CI[.508, .738]. The results from the hierarchical regression analyses, plots, and simple slope analysis provide considerable support for the acceptance of Hypothesis 2.

Figure 1. Moderating Effect of Supervisor Knowledge Sharing (SKS) on the Relationship between Coworker Knowledge Sharing (CKS) and Innovative Work Behavior (IWB). 

Table 3. Simple Slope Analysis 

Note. Dependent variable = IWB ; independent variable = CKS ; LLCI= lower level confidence interval; ULCI= upper level confidence interval; SD= standard deviation.

The last step of hierarchical regression analyses (step 4) evaluated the moderating effects of thriving on the relationship between CKS and IWB The moderator (thriving) had a positive and significant effect on IWB (β = .152, p< .05). The interaction between the independent variable CKS and thriving was also significant (β = .092, p< .05). Similarly, the squared population cross-validity coefficient was also generated for this model with reported R²_cv= .362.

Figure 2 shows that employee thriving strengthens the positive relationship between CKS and IWB The relationship between CKS and IWB is significant for both +1 and -1 standard deviation level of moderator (thriving). However, it is stronger when thriving is high, +1SD(simple slope = .577, CI[.45,.70) and weaker when thriving is low, -1SD(simple slope = .39, CI[.25, .52) in Table 3. These results provide ample support for the acceptance of Hypothesis 3.

Figure 2. Moderating Effect of Employee Thriving on the Relationship of Coworker Knowledge Sharing (CKS) and Innovative Work Behavior (IWB). 

Discussion

The purpose of our study was to investigate the effect of coworkers’ knowledge sharing on focal employee's IWB Taking an interactional perspective, our study examined the individual and situational factors that foster IWB Our research suggests a significant effect of coworker knowledge sharing on employee IWB and the important conditions (supervisor knowledge sharing and employees’ thriving at work) in this relationship. There are three major findings to report in the current study. First, coworker knowledge sharing is found to enhance focal employees’ innovative work behavior. ^{Li and Liu (2019)} found that employees with highly useful feedback and help/support from coworkers exhibited the highest level of firm service innovation. They suggest that future research should examine the effect of coworkers’ knowledge sharing on innovative performance at the individual level. This study addresses the call by ^{Li and Liu (2019)} and found that when coworkers are willing to share knowledge, ideas, information, and skills more readily, the innovativeness of individuals enhance significantly. Previously, the creativity literature had focused on support and helping (^{Zhou & George, 2001}), work strain (^{Van Dyne et al., 2002}), and competition (^{Shalley & Oldham, 1997}) dimensions of coworker influences as antecedents of individual IWB s. In this research, we examined a specific type of coworker support, i.e., coworkers’ knowledge sharing, as a predictor of IWB In light of the componential model of creativity (^{Amabile & Pratt, 2016}), our study implies that through enhancing their problem solving and domain-relevant skills, organizational employees may increase their individual IWB, specifically through the knowledge shared by their coworkers.

Second, this study found that there are some boundary conditions that can affect the relationship between CKS and IWB More specifically, the finding suggests that when supervisors share knowledge more frequently, the effect of CKS on IWB weakens. ^{Duffy et al. (2002)} found that the significant interactional influence of supervisor undermines coworker support on somatic complaints and passive counterproductive behavior at individual level. Their results showed that the negative effect of coworker support on a focal employee's emotional distress and counterproductive work behavior strengthens due to supervisors’ support. A meta-analysis demonstrated that supervisor-aggression has a more substantial influence on employees’ job satisfaction, affective commitment, and performance as compared to coworker-aggression (^{Hershcovis & Barling, 2010}). Third, the study confirmed the moderating role of thriving at work on CKS -IWB link. When a focal employee has higher level of thriving at work, the positive effect of CKS on his/her IWB further strengthens. This result is consistent with the finding of ^{Riaz et al. (2018)} that thriving serves as an important regulatory mechanism that operates as an internal gauge for innovation.

This study provides insights into how employees can enhance IWB through coworker knowledge sharing by staying attuned to their psychological state of thriving in order to influence their own innovative behaviors. ^{Spreitzer et al. (2005)} seminal theoretical work on thriving gives only passing notice to the role of individual predispositions and how they may influence agentic work behaviors which are the "engine of thriving." Our study elaborates on this suggestion and provides empirical evidence that thriving serves as an important self-regulatory mechanism that operates as an internal gauge of personal development and growth through which coworkers’ knowledge sharing translates into higher (lower) IWB by focal employees. The results of this study support our hypotheses that the positive relationship between coworkers’ knowledge sharing and employees’ IWB does vary depending on the degree of supervisor knowledge sharing behavior and the thriving of employees’ at work.