Mediation Effect of Knowledge Sharing Quality on Employee Creativity

Employee creativity requires knowledge sharing, according to many experts. What aspects of the knowledge sharing cycle encourage employee creativity? In this study, authors examined three factors, i.e., „opportunity for exchange (OFE), value anticipation (VA), and motivation to engage (MTE)‟, that influence the production of intellectual capital (as antecedents) and its effects on employee creativity (as outcomes) through knowledge sharing (KS) and quality of knowledge sharing (QKS: as mediating mechanism). To test the hypothesized relationships, Mplus was used to analyze 371 Russian IT employees. The findings suggest that OFE, VA and MTE are important antecedents of both KS and QKS. Moreover, KS and QKS mediates the relationship between antecedents (OFE, VA and MTE) and outcome variable (employee creativity). Theoretical contribution and future research are discussed.

technology, and economic resources all contribute to innovation, knowledge sharing between employees is critical. Product development, according to Cardinal et al. (2001), entails technical, physical, and knowledge components. The innovation process can be conceptualized in three ways: through the employees, their activities, and the modes of innovation (Diercks, Larsen, & Steward, 2019).
Thus, using intellectual capital constructs as antecedents, this study investigated "how the quality of KS and QKS" affect employee creativity OFE, VA and MTE. The study's underlying significance is to raise awareness in both business and academia that KS alone is not sufficient to consider in terms of employee and team creativity; rather, the QKS is what truly has a clear impact on an organization's well-being. The study was conducted to insight a better understanding of how KS and QKS affects employee creativity.

Relationship Between Antecedent: Knowledge Sharing and Outcome: Employee Creativity
KS promotes creativity, according to the scholars, innovation and creativity is unlikely without KS (Kremer et al., 2019). Collaboration has proven to be an efficient way of gaining knowledge and skills (Adams et al., 1998). Products and services can be improved or created by exchanging knowledge. Knowing how to share ideas, know-how, and expertise is considered to be a critical factor in employee creativity because sharing ideas, know-how, and expertise increases organizational capital (Cabrera, Al-Kurdi, Nahapiet & Ghoshal, 1998;Shen et al., 2021b), and integrating individuals' knowledge results in synergy (Nahapiet & Ghoshal, 1998) Innovation tasks are impossible for a single person to complete in any complex work process; only by assembling an effective team of people with a variety of skills can they be completed (Dong et al., 2017;Zá rraga & Bonache, 2003). Aside from that, the team's ability to think creatively requires them to look at things from a variety of perspectives and combine previously unrelated elements to create something new and improved (Aggarwal et al., 2019). Consequently, the concept of KS has received a great deal of attention from academics.
Researchers who have investigated employee creativity in the past (for example, Ahmad et al., 2019;Park et al., 2018;Muhammad et al., 2017;Shen et al., 2021a;Subramaniam & Venkatraman, 2001) have frequently employed knowledge and/or intellectual capital as independent variables, with employee creativity as an outcome variable. "While the invention or conception of innovative ideas may be an individual activity, innovation (the invention and implementation of new ideas) is a collective achievement," Van de Ven (1986) asserted. When it comes to organizations' ability to innovate, their intellectual capital and their ability to leverage their knowledge resources are both important factors to consider. Kane (2017) and others have emphasized that new product development is an expression of organizational knowledge, while others have described employee creativity as a knowledge management process (e.g., Madhavan and Grover, 1998;Yan et al., 2021) or described innovative firms as knowledge-creating organizations (e.g., Madhavan & Grover, 1998;Nonaka et al, 2018). Muhammad et al. (2017) revealed that, in organization employee talent and knowledge management are critical primary resources in today's competitive market.
Many studies have been conducted to examine the impact of internal knowledge management and talent management strategies in under developing countries (e.g., Chinese manufacturing firms), but few have examined the impact of external knowledge management and talent management strategies. The value of KS has long been recognized by the academic community.
Both the creation and application of organizational knowledge (Hendriks, 2004), which are critical processes in organizational innovation and knowledge management, require knowledge sharing. However, some researchers believe that knowledge sharing is not always beneficial to employee creativity and team performance, and that it can even be harmful in some cases (Cornell & Stone, 2010;Haas & Hansen, 2007). Numerous attempts have been made to address the issue of KS quality, including the development and application of knowledge quality measures (Doronin et al., 2020), and KS effectiveness and quality (Raab, Ambos, and Tallman, 2014;Shah et al., 2021). There is still no clear and justifiable measure of the link between knowledge sharing and employee performance.

Knowledge Sharing as a Mediator
Numerous attempts at addressing the issue of KS quality have been made, including the development and application of knowledge quality measures (Darroch & Mcnaughton, 2002). The style of KS can make a company unique and characteristic, affecting its performance. Moreover, explicit knowledge influences the speed of innovation, while tacit knowledge influences the quality of innovation (Liao et al., 2007). Since the year 2000, there has been an increase in the amount of literature on KS and innovation (Castaneda & Cuellar, 2019). Cavusgil et al. (2003) found that the more tacit knowledge transferred, the more innovative the firm. This study examines the concept of KS and QKS, which is viewed as a complex construct that can have a range of effects on an organization's social, intellectual, and human capital, depending on the information shared and the manner in which it is shared. This investigation employs a previously established methodology, as numerous previous studies have raised similar concerns (Chiu et al., 2006;Cavusgil et al., 2003;Ghobadi, 2015). The purpose of this article is to fill a gap in the literature on the relationship between KS and innovation. Others have stressed the importance of studying innovation and KS together. The parallel mediation model is used in this investigation (Preacher & Hayes, 2008). Although in previous studies, scholars have realvead "KS" as dependent variable (e.g., Cabrera et al., 2006;Cavaliere, Lombardi, and Giustiniano, 2015), it has also been considered as an independent variable (e.g., Hussain et al., 2018;Safa et al., 2016) or as a mediator influencing creativity and performance (e.g., Ali et al., 2015;Safa & Von Solms, 2016;Dong & Yang, 2016;Soto-Acosta &Cegarra-Navarro, 2016). Consequently, the current study offers a fresh perspective on how KSg can be studied while also emphasizing the dual nature of the phenomenon: knowledge as an input and KS as a process.

Knowledge Sharing Antecedents
A great deal of work has been done to determine what influences KS and how it is influenced. In light of the fact that high-quality KS is thought to be a key factor in the development of intellectual capital , this study makes use of the Nahapiet and Ghoshal (1998) variables of OFE, VA, and MTE. Tacit knowledge, explicit knowledge, and relationships with other people make up the three types of intellectual assets known as intellectual capital.

OFE.
When we speak of OFE, we are referring to the existence of a specific medium for knowledge transfer (Saifi et al., 2016). According to both social presence theory (Bickle et al., 2019) and media richness theory (Daft & Lengel, 1986), a specific task necessitates the use of a specific type of media channel; this is not necessarily the most advanced or richest, but rather the one that can provide sufficient resources to appropriately transmit and receive information in the most efficient manner (Ali et al., 2017).
VA. The importance of engaging in communication and KS should be recognized by all parties involved in the process. The concept of anticipation of reciprocity, which is relevant to knowledge management theory, has been found to have a strong positive relationship with knowledge sharing behavior (Lai et al., 2014). At the same time, anticipating risks makes it difficult to share information Tamjidyamcholo et al., 2014).

MTE.
Individual intentions are required in order to carry out high-quality KS activities. When a sharer shares, his or her intentions should be such that he or she can contribute to the team's success, is useful, and wishes to assist others. As a result of his research, Wang (2015) discovered a link between KS intentions and the self-determination theory.

Hypothesis Development
If organizations or firms required their employees to be creative, they need to encourage them and need to provide enviorment that encourages to share their knowledge with each other. This increases organizational capital, which is created when people's knowledge is integrated (Cabrera and Artacho, 2006;Nahapiet and Ghoshal, 1998). One person cannot effectively innovate in a complex process; only by assembling a group of people with diverse backgrounds and skill sets can this be accomplished (Butt et al., 2020;Eisenbeiss, 2008;Zá rraga & Bonache, 2003). It is also important for a team's creativity to be able to communicate its goals to each other Pearce & Ensley, 2004). There is a theory that says that employee creativity isn't always linked to a company's willingness to share its knowledge (Tang, 2019). Employee creativity is a result of an increase in intellectual capital as a result of high-QKS (Leitner, 2015).
In this study, it was proposed that knowledge exchange can improve each of intellectual capital's three components (Wang, 2014). Relationships with strong ties, trusting relationships, and a shared vision necessitate, OFE and combine knowledge before the knowledge resources embedded in those relationships can be fully leveraged (Argote& Ingram, 2000;Hassan et al., 2019;Nahapiet & Ghoshal, 1998;Weerakoonet al., 2020). According to Nahapiet & Ghoshal (1998), the QKS can be positively correlated with the amount of intellectual capital that is created. The five and two quality dimensions adopted from previous studies Tsai et al., 2014) that suggested a positive correlation between intellectual capital creation of KS and QKS and respectively. However, only if the quality of employee creativity and intellectual capital creation is taken into account can these two concepts be linked (Ellwart et al., 2015). Based on above-mentioned discussion, following hypotheses are proposed: knowledge.
H1b: Opportunity for exhange and employee creativity relationship will be mediated by quality of knowledge-sharing.
H2a: Value anticipation and employee creativity relationship will be mediated by quality of knowledge.
H2b: Value anticipation and employee creativity relationship will be mediated by quality of knowledge-sharing.
H3a: Motivation to engage and employee creativity relationship will be mediated by quality of knowledge.
H3b: Motivation to engage and employee creativity relationship will be mediated by quality of knowledge-sharing.

Parallel Mediation Model
This study's single-stage parallel mediation model uses only two mediators, but theoretically any number could be used. The relationship between mediators is described as "parallel" because no one mediator affects the other. Only one of the mediators is required for the transition from independent to dependent variables (i.e., the KS and QKS here). Other models with a large number of mediators (Cheung, 2007; exist, but this study only uses single-step models (Figure 1).

Analysis Technique
The relationship between three antecedent variables "OFE, VA and MTE" that have an impact on the creation of intellectual capital is investigated in the current research. More precisely, how these antecedents influence employee creativity is being investigated via the mediating effect of the KS and QKS dimensions. The initial screening tests and exploratory factor analysis (EFA) were carried out using the Statistical Package for Social Science (SPSS) 21 version of the software (IBM). The AMOS 21 version was used to calculate model fit indices and confirmatory factor analysis (CFA) for individual variables and for the entire sample of variables. To proceed with further analysis, it was determined that the results of EFA and reliability check via CFA were satisfactory. Mplus software (version 7) was used to analyze the parallel mediation and whole model hypotheses in order to verify the proposed hypotheses.

Survey
For data collection, an author first discussed the study objectives with the appropriate autho rities, and after receiving permission, 450 respondents working in Russian software development firms were randomly selected. A total of 371 people responded to the survey. Both English and Russian were used in the survey, several studies used same aaproach (e.g., Ali et al., 2019). Respondents were asked if there were any phrases or terms that they found difficult or unclear. Following receipt of the questionnaires, no major changes to the text were required. Internal consistency and reliability were checked using Cronbach's alpha. OFE had a Cronbach's alpha of 0.892, VA had a Cronbach's alpha of 0.897, and MTE had a Cronbach's alpha of 0.941. Similarly, mediating variables, KS was 0.919, 0.856 for QKS, and dependent variable (employee creativity) was 0.898, meet the requirement (Nunnally & Bernstein, 1994). See Table 1 for more information.
This study used an additive approach to create a unitary index of knowledge quality by categorizing the entire set of items into five factors and then combining them to form an aggregate measure of kno wledge quality. Table 2 summarizes the results of the confirmatory factor analysis for KS and QKS. For QKS, the goodness-of-fit values for the model were χ2 = 16.832, df = 8, p > 0.00, CFI = 0.990, TLI = 0.910, and RMSEA was 0.050, indicating that a hierarchical factorial structure was an adequate representation of the data. In a similar vein, a higher-order structure explained the two first-order factors of knowledge sharing quality, and a unitary index was calculated based on the explanation. The same method was used to evaluate the level of knowledge. For QK, the goodness-of-fit values for the model are presented in Table 2.

Measurement Model
The items and constructs' reliability and validity were investigated in the measurement model. Analyzing the measurement model yields the loadings, which give the researcher an idea of the measurement's sturdiness. The measurement model's psychometric properties were evaluated by looking at its reliability, convergent validity, and discriminant validity (Fornell & Larcker, 1981).
Mean inter-item correlation was applied to verify that all survey-items measures the same constructs because it refers to the mean inter-item correlation (Bryman & Cramer, 2004;Clark & Watson, 1995). It can be evaluated using composite reliability and Cronbach's alpha. Item reliability is assessed using Cronbach's alpha; composite reliability is assessed using Cronbach's alpha (Hoque, 2016). As can be seen in Table 4, the Cronbach's alpha values for each of the variables under consideration are quite high.

Path Analysis
The KS and QKS were examined as mediators between independent variables (OFE, VA, MTE), and dependent variable (employee creativity). The Monte Carlo simulation procedure was used to test the mediation hypothesis. This procedure was used to accurately reflect the asymmetric nature of an indirect effect's sampling distribution (Preacher et al., 2010). Table 4 illustrates the relationship between OFE, VA, MTE, and employee creativity and the KS and QKS.
According to this study, the indirect effects of OFE on QK and QKS on employee creativity were both positive  Table 4. In the study, the findings revealed that OFE, VA, and MTE were all positively and significantly related to employee creativity, both in terms of KS and QKS, respectively.

Theoretical Contribution
The results showed unequivocally that employee creativity is influenced by the quality dimensions of KS. While some studies have found a negative link between employee and organizational performance and KS (Liu et al., 2011;Tang, 2019), others have found a positive one. Regardless of the discrepancy in findings, no one knows for sure how to measure KS. There are a variety of ways to measure how effective KS is from a quantitative perspective, such as the number of reports or responses, or the number of feedbacks (Hau et al., 2016). However, the actual study focused on the quality of the information shared.
According to Nonaka (1998), there are four steps or processes that lead to the creation of new knowledge. Here, we can compare the quality of codification and KS by comparing them to the quality of externalization. These processes are supposed to lead to greater intellectual capital creation and subsequent creativity by employees, in theory, if they are executed well. KS in future research must be understood in terms of what knowledge is shared (quantity, impartiality, verifiability and relevance), as well as how it is shared (comprehensibility and timeliness).
Employee innovation is examined in this study, which focuses on the dual nature of KS, manifested in the form of parallel mediation. Future studies can be guided by the study's findings, which quantify the KS and QKS. Furthermore, it emphasizes the significance of both the content and the dissemination of knowledge in fostering inventiveness. These quality dimensions of KS are used in the current study to assess the relationship between employee creativity and the previously identified antecedents of intellectual capital creation. So the research shows that there is a link between the theory of social capital and employee innovation.

Practical Contribution
Knowledge management literature will insight greatly from this study's findings. According to the results of the current study, KS has a greater effect on employee creativity when knowledge is shared in a high-quality environment. As a result, rather than attempting to replicate teamwork and KS through policies and procedures, organizations should look for ways to improve the QKS. Social capital theory is taken into account in this study as the driving force behind the creation of intellectual capital and the creativity of employees.
Knowledge-intensive organizations and firms should exercise caution when implementing KS initiatives that are solely focused on quantitative outcomes, such as the number of reports produced or the number of feedback messages sent, according to the findings of the research. This policy, which encourages sharing for the sake of sharing, may have no effect on the performance of an employee or the performance of the company. As an alternative, the study emphasizes the fact that high-quality KS, rather than large amounts of it, produces the greatest number of benefits.
When it comes to innovation and business performance, knowledge management has emerged as one of the most important disciplines for modern organizations to keep in mind. Knowledge-intensive organizations, such as universities, information technology, banks, and other financial institutions, can benefit from the study's findings, which provide a deeper look at KS processes.

Limitations and Future Research
This study has several limitations. First, in this study author targetd the respondents were based in Russia, which has a number of implications for both geography and culture. The information technology industry, in particular, is regarded as a knowledge-intensive and relatively new field. There is a significant limitation in the study's findings because of the problem of representativeness. This means that further study could be done in other regions and industries. The development, testing, and refinement of sound instruments in the KM literature continues to be a work in progress. Additional studies are needed to confirm the external validity of our results despite the fact that the dataset's reliability and validity have been empirically tested. In the third point, it would be interesting to examine the construct using a multi-level approach and to include some objective measures because the study relied on subjective Likert scale responses from team members. The proposed quality-based construct can be used to test other antecedents of knowledge sharing.

Conclusion
All hypotheses were supported, indicating that quality dimensions of KS are important for increasing employee creativity and productivity. The researchers also discovered that Nahapiet and Ghosal's (1998) four conditions for creating intellectual capital were positively related to all of the study's quality dimensions of KS.The last decade has seen a surge in interest in KS. This study examines the QKS and added academics a high-quality perspective on KS. Using previously untapped theoretical perspectives, this paper examined how KS can influence employee creativity. These three elements are critical to the process of combining KS and QKS.