The Impact of Leadership on Boosting Employee Creativity: The Role of Knowledge Sharing as a Mediator

Abstract

In this study, we examined the role that knowledge sharing plays in mediating the relationship between the employee trust in leadership and employee innovation in the service sector in the United Arab Emirates (UAE). We included 346 people employed in the service industry. According to the study’s findings, having faith in one’s leader has a beneficial and discernibly positive impact on the degree to which employees share their knowledge and innovate. Knowledge sharing has a positive and substantial effect on the creativity of employees, and vice versa. According to the study’s findings, the openness of leaders partially mediates the willingness of employees to try new things and share information, which is a consequence of the trust that employees have in their leaders and their willingness to experiment with new concepts.

1. Introduction

The openness of an organization to new ideas and changes is important in the adaptation to the rapidly shifting nature of the modern workplace (Hosking and Anderson 2018). According to Potočnik and Anderson (2016), innovation is the process of pursuing oriented change to achieve the organization’s goals. In times gone by, organizations focused their attention on maintaining high levels of stable productivity. However, in the modern world, the purpose of every organization is to reach innovative levels of performance, which can create more value in their complex and always-changing environments (Chen et al. 2020; Kostis et al. 2018).

Investing in innovation is a lot like buying call options for the future, and a company’s innovative ideas give it an edge over its rivals on a consistent basis (Avelino 2021). Furthermore, innovation contributes to less stressful workplaces, increased productivity, and improved work quality through the generation of new competitive methods of conducting business operations, overcoming obstacles, resolving market orders, and enhancing the current organization (Chen et al. 2022; Beard and Burger 2017; Hollywood et al. 2016). All of an organization’s employees are responsible for sparking its culture of innovation through their creative actions (Batool et al. 2022; Kalargiros and Manning 2015). Each person brings something to the group as a whole, which is the foundation upon which new ideas can be thought up, made real, and sustained (Dogan 2017).

Innovating means bringing fresh ideas, procedures, products, or guidelines to adoption units in a way that is both relevant and intended to benefit the individual, group, or society (Avelino et al. 2019). The foundation of any high-performing organization is the innovative behavior of its employees (Tidd and Bessant 2020). The creative work generated by innovative actions forms the foundation for the growth of the product or service competitiveness (Bani-Melhem et al. 2018; Weisburd and Braga 2019).

Education is the key to fostering innovation (Pachura 2017; Anderson 2018; Vlados 2019), and knowledge sharing is important in shaping creative actions. Knowledge sharing is the information that is held by an individual or small group that can be disseminated and used by a larger group to improve their operations and create innovative goods and services (Bani-Melhem et al. 2021; Castaneda and Cuellar 2020). An individual’s knowledge provides the raw materials that an organization requires to generate knowledge and innovation (Batool et al. 2022). However, suppose that information is not disseminated throughout the organization? In this case, it stays with the original owners and has little to no effect on how well the business works or how well it can generate new ideas (Rumanti et al. 2018).

Throughout the course of human history, the importance of employee creativity has traditionally been more attributed to the manufacturing and service sectors, in which the introduction of new goods plays an important role (Lin et al. 2022; Ritala et al. 2015). Furthermore, researchers have pinpointed the resources that make the highest contributions to service sector innovation (Bani-Melhem et al. 2020; Xiong et al. 2022). However, there is a dearth of research that examines the factors that encourage or discourage innovative behavior among service sector workers. Many researchers overlook innovation in the service sector because they believe it is too difficult to study, which could be due to the unique circumstances of individual businesses. Berraies (2019) states that innovation occurs in a company when a small number of factors define a product or service change.

Maintaining high research standards could provide a lasting advantage in today’s business climate, which places a premium on adaptability, originality, and customer satisfaction (Kokt and Makumbe 2020). When it comes to ensuring that service industries remain innovative, employees play an essential role. That their creative problem-solving skills are a factor in studies that find a correlation between creativity and positive results is a possibility (Khassawneh and Mohammad 2022a; Al-Husseini et al. 2021). Employees are instructed to perform tasks as specified in their job descriptions; thus, they may not take the initiative to engage in creative problem solving. However, the work of professionals is performed without supervision. Therefore, the innovation that is associated with skilled workers belongs to the relevant field of academic study. In Industry 4.0, workers are told to be more independent and responsible in terms of their work.

Skills in dealing with the desires of diverse stakeholders are an absolute necessity in today’s workplace. Workers are trusted to make technology development and implementation decisions based on their judgment and the policies that best suit their unique situations. As a result, the service industry emphasizes innovative employee behavior because employees are considered to be the driving force behind new service developments (Bhatti et al. 2020; Khassawneh 2018; Ofori et al. 2015). A company’s innovation heavily relies upon its professional staff. Professionals also use their new and unique experiences with college students and coworkers to improve their performance. However, this research sector is underdeveloped.

Organizational success in the service sector can be enhanced when skilled workers pool their expertise and share what they have learned. As a result, it is crucial for service industry organizations to promote knowledge sharing (Hung et al. 2021; Mohammad 2019). The establishment of a culture of knowledge sharing is crucial to the success of the service sector, which heavily relies on communication among workers and between workers and customers. Despite the importance of knowledge sharing, Al-Husseini and Elbeltagi (2015) found that it only occurs after trust is established. They argue that trust should be prioritized when building systems for sharing information.

Trust, as defined by the study’s authors, is characterized by the readiness to help others and the willingness to accept their assistance (Joo et al. 2022; Kim and Shim 2018). There is not one single agreed-upon definition of trust. However, it has generally been understood to facilitate communication, reduce tension, and unite diverse groups to form effective teams (Berraies 2019). As Vlados (2019) noted, trust is critical in efficient knowledge sharing and originality in action. Some researchers have found knowledge sharing to be an important driver and enabler of innovative action (Abukhait et al. 2019). Knowledge sharing serves a dual purpose as both the result of the followers’ confidence in their leaders and a precursor to risk-taking actions. Therefore, we assume that the dissemination of information mediates the relationship between the confidence in management and initiative. We analyzed the link between a leader’s credibility and creative action, and we discuss how information exchange acts as a bridge.

We used a conceptual framework based on studies performed on organizational trust, knowledge management, and creative actions (Zhao et al. 2020; Anderson 2018). We present the conceptual framework in Figure 1, which states that trust in the leader substantially affects knowledge sharing, which affects innovative behavior. As a result, the creative actions and information exchange of followers are impacted by their leaders’ trustworthiness in immediate and far-reaching ways.

H1. 

Knowledge sharing is substantially influenced by leaders’ credibility.

The belief of individuals in one another reflects their conviction that the group members are telling the truth and are acting according to their beliefs and values. Mutual trust exists among peers, superiors, and those that they supervise (Khassawneh and Mohammad 2022b; Dalati and Alchach 2018). Workers may have faith in each other but mistrust management. Thus, various tiers of trust should be considered. According to several studies, knowledge sharing within an organization is more likely to be successful if its members have a high level of trust. As defined by Le and Lei (2018), the level of trust between the members of an organization depends on how confident each party is that the others will work together toward a common goal.

The authors found that, when employees trust one another, they are encouraged to share information, which can boost productivity. If workers lose faith in their leader, then they are less likely to form the close working relationships that make knowledge sharing possible. They will then either keep the knowledge a secret or twist it, especially if it is something crucial (Ansong et al. 2022; Phong et al. 2018).

According to Le and Lei’s (2017) research on the topic, when employees have a high level of trust in their leaders, there is a corresponding increase in the knowledge sharing across teams. The fear of being manipulated and losing power and value due to knowledge sharing is a primary reason that people in the service industry might not partake in it.

Knowledge sharing and eliminating such worries are among the many positive effects of a trustworthy leader (Dalati and Alchach 2018). According to Gui et al. (2021), followers who trust their managers are more likely to take their advice. As a result, the flow of data is optimized. Researchers have found a link between following a leader that one trusts and being honest about what one knows. We base the hypothesis in this study on these data.

Researchers have found that organizations with high concentrations of knowledge assets have a better chance of being innovative (Hu and Zhao 2016). According to research by Khan and Khan (2019), the worth of a company’s knowledge assets is proportional to its ability to innovate. Because people tend to hold on to their knowledge, teams need to exchange information to establish new sets of norms and perspectives that aid in problem solving (Edú-Valsania et al. 2016). Hussein et al. (2016) and Zeb et al. (2020) argue that, for this to happen, the company needs to build a culture of knowledge creation and, even more importantly, knowledge sharing.

Al-Husseini et al. (2021) claim that when employees share what they know, they are more likely to develop novel solutions to problems and participate in innovation. Researchers have extensively studied knowledge sharing and innovation, and the researchers who have examined the link between the two have reached a consensus: effective knowledge sharing can lead to innovative behavior, which is because innovation is more likely to take place when workers are able to have open and honest conversations with one another and freely exchange the kinds of novel ideas that fuel it. According to Zhang et al. (2022), knowledge diffusion affects creative actions. Based on the study’s results, as mentioned earlier, knowledge sharing among employees is essential to the development of an organization’s knowledge and the promotion of innovative practices. As a result, we put forth the following hypotheses.

H2. 

Information sharing boosts innovative team thinking.

Taştan and Davoudi (2015) found that, on the one hand, a willingness to take risks is a universal feature of trustworthy relationships. Trust, on the other hand, is unique in that it requires a person to take on the weaknesses and risks of others. Employees who trust one another are more likely to take risks and develop creative solutions. In most cases, the innovative actions of people are based on their free will. As a result, this kind of behavior serves a dual purpose as both the result of the followers’ confidence in their leaders and a precursor to risk-taking actions. Moreover, each person must take full responsibility for their shortcomings.

As a result of this uncertainty, there is a robust correlation between following a trusted leader and taking creative risks (Ullah et al. 2021; Hao and Yazdanifard 2015). Employees heavily rely on their representatives to secure the information, resources, and social support that they need to cultivate, preserve, and produce original ideas within the context of the business (Mohammad et al. 2021; Kremer et al. 2019). When employees believe in their supervisors, they are more likely to take risks and develop novel solutions to problems (Lee et al. 2019). When a superior and subordinate work together to form a team, the subordinate may be given more opportunities to exercise policy and make independent decisions, both of which are conducive to developing creative approaches to problems. Additionally, when there is a higher level of trust between leaders and their subordinates, employees are more likely to take initiative in the organization’s growth (Lei et al. 2019).

Working with coworkers is crucial for developing new business concepts (Javed et al. 2018). While coming up with concepts and making assessments at work can be independently performed, in most cases, the members of one’s workgroup impact how creative one is (Islam and Asad 2021; Kesting et al. 2015). Jaiswal and Dhar (2017) emphasize the value of brainstorming with coworkers to spur creativity. We developed the following theory on the basis of the findings of an earlier study in which the authors investigated the connection between trust and original problem solving.

H3. 

Innovation among employees is substantially influenced by the leader’s credibility.

As we have seen, knowledge sharing is associated with an increased and positive influence on innovative actions (Khassawneh and Abaker 2022; Le and Lei 2018). Knowledge sharing not only serves as an expression of trust, but also as a precursor to creative actions. Researchers have reasoned that because knowledge sharing occurs between people, it must facilitate trust and creative thinking. We look into how this kind of trust affects the ability of people to develop new ideas, and we explain how the information exchange in these relationships acts as a mediator.

We based our conceptual framework on previous research on the connections between organizational trust, knowledge management, and innovative behavior (Kim 2019), in which the author argues that trust between colleagues and leaders substantially affects knowledge sharing, which may positively affect innovative behavior. This implies that the trust between employees and management indirectly and immediately affects innovative behavior. As a result, we propose the following research hypothesis.

H4. 

Knowledge sharing, as a mediator of trust in leadership, has a substantial impact on employee creativity.

As stated by Dalati and Alchach (2018), the theoretical framework is the basis of the entire research project. We derived a testable hypotheses from the theoretical framework to determine the proposed theory’s veracity. We then evaluated the theory with the help of proper statistical methods. As shown below, we created a research model based on the existing research and theoretical ideas.

2. Research Method

Because there are multiple relationships to explore between independent and dependent variables, and because this study is quantitative in nature, we used the dyadic approach (Kenny et al. 2020). To gather the information on the various factors that make up the proposed framework, we designed a systematic survey. In this work, we used established instruments from other studies to gauge the proposed variables (we describe the sources below). Individuals employed in the service industry made up the bulk of this study’s respondents (hotels, hospitals, insurance companies, educational institutes, and banks). We applied the findings to the service sector because we were advised to do so (Ledermann and Kenny 2017).

We selected 500 workers for the sample, to whom we randomly distributed the survey. The number of valid questionnaire returns was 364 (see

Table 1. Respondent profiles.

Employee Details (n ¼ 314)	Frequency	Leader Details (n ¼ 50)	Frequency
Gender		Gender
Female	144	Female	19
Male	170	Male	31
Age (years)		Age (years)
20–29	98	20–29	1
30–39	77	30–39	11
40–49	83	40–49	16
50–59	36	50–59	12
Above 60	20	Above 60	10
Experience		Experience
Less than 1 year	33	Less than 1 year	0
1–10 years	152	1–10 years	7
11–20 years	83	11–20 years	30
More than 20 years	46	More than 20 years	13
Education		Education
Postgraduate	44	Postgraduate	17
Undergraduate	270	Undergraduate	33

: respondent profiles). A total of 44.32% of the population believed that the credibility, fairness, and competence of leaders, and the extent to which their followers share these traits are all important, as measured by the trust in leaders instrument. We used the ten items (TL1–TL10) created by Aryee et al. (2002) to measure this concept. When people talk about “knowledge sharing”, they are referring to the act of imparting the information that they have learned on the job to other people. Lee et al. (2019) developed a set of measurement standards that we used in this study across four items. The authors devised a six-point scale (s1–s6) to assess the distribution of the information. The term “employee innovation” refers to the process by which workers propose and implement novel ways of performing their work to boost the efficiency and effectiveness of their employers. We used five items (EI7–E21) created by Anderson (2018) to gauge creative thinking and action. We used the Likert scale for all the measurements. For each question or statement that could be answered with an open-ended response, we assigned one of five possible ratings: 5 points for strongly agree (SA), 4 points for agree (A), 3 points for neutral (N), 2 points for disagree (DA), and 1 point for strongly disagree (SDA). Data processing often involved the use of PLS and the accompanying Smart PLS 3.0 software.

3. Measures

We measured all the variables in this analysis using well-established previously validated scales that have been utilized in numerous other studies and found to be accurate.

Trust in Leadership: We used ten items from the multifactor leadership questionnaire (5X-Short) to determine the levels of the trust in leadership (Aryee et al. 2002). The MLQ measures trust through four dimensions of leadership behavior, including “idealized influence”, “individual consideration”, and “intellectual stimulation”. The scale’s Cronbach’s alpha dependability was 0.805. An example statement is “My leader inspires me to work independently”.

Knowledge sharing: The Cronbach’s alpha reliability of the eight-item scale created by Hu and Zhao (2016) to measure knowledge sharing was 0.865. An example statement is “I make it a point to teach my coworkers new skills whenever possible”.

Employee creativity: We used a Likert scale to quantify the employees’ creativity. The scale’s Cronbach’s alpha reliability was 0.852. Employees who actively seek new technological solutions, operational improvements, and/or product concepts are examples of a desirable feature. We rated both the employees’ willingness to share their knowledge and their inventiveness on a five-point scale (i.e., 1–5: from strongly disagree to strongly agree).

We examined certain non-independent observations using a one-way analysis of variance test to prevent disagreements in the assessments made by the leaders. This exam ensured that the ratings of the employees’ creative potential would not be influenced by the answers of other employees. We did not find any statistically significant variations in the rankings of the dependent variables by the supervisors after the analysis (F = 0.896; p = 0.723).

4. Control Variables

Due to the contradictory relationship between age, gender, education, and experience, which could lead to task-domain competence or knowledge, which, in turn, could play a role in predicting the creative performance, we followed the current studies on creativity and controlled for these factors (Lenz and Sahn 2021).

5. Analytical Approach

We used SPSS and AMOS 20th edition to perform the individual-level analyses on the data. To ensure that each scale was a good fit, we performed a CFA, which revealed a connection between the observables and their corresponding latent components. We employed several fit indices, including the comparative fit index (CFI), root mean square error of approximation (RMSEA), normed fit index (NFI), goodness-of-fit index, and modified goodness-of-fit index, to assess the accuracy of the model. When the RMSEA was less than 0.05, we considered the degree of fit to be good, and when it was between 0.07 and 0.09, we considered the approximation logical.

6. Results

We present the correlation matrix together with the means and standard deviations in

Table 2. Descriptive statistics and correlations.

Variable	Mean (SD)	1	2	3	4	5	6	7	8
Age	5.81 (0.83)
Education	4.87 (0.91)	−0.19 **
Gender	47.69 (2.69)	−0.04	−0.04
Experience	12.91 (0.75)	0.07	−0.03	−0.27 **
Trust in leadership	0.39 (0.16)	−0.11	0.19 *	−0.16 *	(0.19 *)
Knowledge sharing	2.66 (0.79)	0.29 **	0.06	−0.23 **	−0.26 **	(0.02)
Employee creativity	2.68 (0.51)	0.16	0.10	−0.18 *	0.09	−0.13	0.23 **	(0.13)	0.02

* p < 0.05. ** p < 0.01. Notes: for discriminant validity, the italic numbers in the cells of diagonal line are AVE values.

. The study of the measurement model by means of a CFA was the primary method used to examine the data, and according to the results, the model fit the data quite well (χ² = 690.9; (df) = 521; GFI = 0.899; AGFI = 0.909; NFI = 0.978; CFI = 0.980; RMSEA = 0.033).

For leadership trust, the estimated loadings were between 0.54 and 0.86, and for employee inventiveness, they were between 0.88 and 0.90. Convergent validity occurs when there is a correlation between the observed variables of the construct in accordance with the theoretical basis. Convergent validity (Post 2016) is indicated by the high composite reliability and substantial loadings presented in

Table 3. Item loadings, Cronbach alphas, composite reliabilities, and average variances extracted (AVEs).

Variable	Item	Loading	Cronbach’s Alpha	Composite Reliability	AVE
Trust in leader (TL)	1	0.826	0.805	0.847	0.530
	2	0.758
	3	0.705
	4	0.646
	5	0.691
	6	0.983
	7	0.762
	8	0.599
	9	0.861
	10	0.891
Knowledge sharing (KS)	11	0.776	0.865	0.897	0.595
	12	0.783
	13	0.746
	14	0.791
	15	0.739
	16	0.796
Employee creativity (EC)	17	0.836	0.852	0.891	0.630
	18	0.742
	19	0.752
	20	0.830
	21	0.806

. According to the outcomes, the adaptability of the model was adequate. For more clarity on the level of separation between the various constructs, we also conducted tests on the discriminant validity (Walker et al. 2017). We present the construct-level correlations in Table 2, all of which were substantially lower than the AVE square roots in both the dependent and independent variables. The model’s discriminant validity was strengthened as a result. We also combined the AVE values with the MSV and ASV data. If all the ASV and MSV values are fewer than their corresponding AVE values, then discriminant validity exists, as stated by Hair et al. (2010). According to Table 3, the defined discriminant validity requirement was met. We performed a Harman’s one-factor test (Fuller et al. 2016) to examine the issue of prevalent technique bias. To examine the potential for common method bias, Kock (2015) applied the idea of Harman’s one-factor analysis. When the same respondents evaluate both the predictor and measure variables in a research, a common method bias might arise. Researchers use the one-factor test developed by Harman to investigate this issue. Everything is entered as a primary component in this statistical method. A factor analysis without rotation should produce a result lower than 50%. The model had four components, with the largest explaining 45.07% (less than half) of the covariance. We also employed the use of the proposed latent factor of Fuller et al. (2016) in AMOS. We allowed all the items to load on both the theoretical constructs that they were designed to measure and a latent common technique component, with all the detected variables of the model. The outcome exhibited that the common variance in all the variables was zero. Consequently, common method bias was not a concern.

7. Hypothesis Testing

To test the propositions, we completed a hierarchical regression analysis by separating the control variables from the study variables. We present the results of the hierarchical regression test conducted on H1–H4 in

Table 4. Regression analyses.

Dependent Variable	Employee Creativity
	Model 1			Model 2
	B	SE B	β	B	SE B	β
Control Variables
Age	0.18	−0.05	0.21 **	0.08	0.03	0.18 *
Gender	0.12	0.06	−0.24	0.09	0.02	0.19 *
Experience	0.10	−0.03	0.04	0.11	0.09	0.07
Education	0.07	0.06	0.13	−0.18	0.04	−0.04
Independent Variables
Trust in leadership	0.12 ***			0.19 ***
Moderator
Knowledge sharing	0.16 ***			0.22 ***
Interaction
Employee creativity × knowledge sharing				0.09 ***
F-value	1.27 *	22.19 *	16.16 *	33.17	56.19 *	44.10 *
R2	0.09	0.18	0.44	0.35	0.34	0.64
Adjusted R2	0.00	0.25	0.47	0.39	0.30	0.55

* p < 0.05; ** p < 0.01; *** p < 0.001.

. In H1, we propose that knowledge sharing is associated with leadership trust. Table 4 demonstrates a positive association between knowledge sharing and trust in leadership (β ¼ 0.12; p < 0.001; Model 1), validating Hypothesis 1. In addition, H2 states that employee innovation is associated with information sharing. As demonstrated by Model 1, knowledge sharing is associated with employee creativity (β ¼ 0.16; p < 0.001), which confirms Hypothesis 2. In H3, we suggest that leadership trust influences creativity. As demonstrated by Model 1, trust in leadership is associated with creativity (β ¼ 0.12; p < 0.001), which confirms Hypothesis 3. We hypothesized that knowledge sharing attenuates the association between leadership trust and employee creativity. We included the interaction factor in the regression model for this reason (Aiken et al. 1991). Model 2 indicated that information sharing has a substantial moderating effect on the connection between trust in leadership and employee creativity (β ¼ 0.9; p < 0.001), which provides support for Hypothesis 4.

As expected, when information sharing is low, trust in leadership has a smaller influence on employee creativity, and when knowledge sharing is high, the association between trust in leadership and employee creativity is reinforced.

8. Discussion

In this study, we aimed to determine whether there is a correlation between employee trust in leadership and the employee propensity to engage in innovative behavior, and if so, how other types of knowledge mediate this influence. Knowledge sharing demonstrates a person’s willingness to assume the risk associated with every piece of knowledge in a competitive organizational environment. Because of their sensitivity to this risk, employees may choose to withhold or alter crucial information if they do not trust each other. However, if there is trust, they can work together in a way that allows them to feel safe enough to offer each other assistance and share what they have learned. Hosking and Anderson (2018) argue that individuals must take chances for confidence to develop; thus, it is crucial to grasp the importance of the risk in building trust.

The authors imply that taking risks within a relationship leads to trust. In their role as service providers to customers, staff members draw on a wide range of experiential and personal knowledge in their daily work. This anecdotal information could be vertically shared between superiors and reports, and horizontally shared among peers. In other words, when a subordinate receives information from a superior, that subordinate must have faith in the veracity of the data being passed along. When employees have faith in their superiors, they are more likely to take their advice seriously (Avelino 2021).

When workers have faith in their leader, they are more likely to work together, increasing knowledge sharing and ultimately boosting productivity (Kalargiros and Manning 2015). When there is trust between coworkers, people are likelier to try new things and are open to criticism of their decisions (Żywiołek et al. 2022; Pachura 2017). In other words, trust among coworkers encourages employees to be more creative (Dogan 2017). However, according to the findings of this study, trust among coworkers has no bearing on creative actions. Based on the findings of this study, even if workers get along well, they will not be able to come up with satisfying innovative behavior unless they communicate with one another.

Therefore, it is unreasonable to assume that employees solely adopt innovative practices and make necessary adjustments through the development of trusting relationships within their workplace. We think this is mainly because service providers accommodate their clients’ schedules, although many of them are only there temporarily. As a result, their level of mutual trust indirectly affects the level of creativity that they display. The study’s findings highlight the importance of leader trust in influencing the propensity of followers to be creative (Castaneda and Cuellar 2020). Staff members who have earned their leaders’ trust are given more freedom to make decisions as long as they do not go against policy.

As a result, workers feel more comfortable experimenting with new approaches at work, which can only be good for creativity. Rumanti et al. (2018) found that when workers have faith in their managers, they are more likely to take the initiative and develop novel solutions to problems. According to Xiong et al. (2022), when leaders and subordinates get along better, subordinates are given more leeway in their day-to-day tasks and decision making, which, in turn, encourages them to be more creative in their approaches to problems.

For employees to feel safe taking chances and being innovative in the workplace, they need to trust their leaders and expect their representatives to encourage local performances and flexible and innovative behavior. This finding adds credence to the theory that the followership of a trustworthy leader is correlated with creative action (Ofori et al. 2015). The group and its members benefit from open communication and information sharing, which will inevitably decrease without a system of effectively dividing knowledge (Jin and Suntrayuth 2022; Kearns and Lederer 2003).

According to one of this study’s findings, exchanging information boosts creative actions, which highlights the fact that knowledge sharing is a precondition for innovative behavior, as has been shown in other research (El-Kassar et al. 2022; Al-Husseini and Elbeltagi 2015). The knowledge gained by an organization can be categorized as either “tangible” (such as a capital, shares, explicit data, or information) or “intangible” (such as information, abilities, or employee experiences). Knowledge sharing of this nature impacts the propensity of workers to be creative. Zhang et al. (2022) showed that an organization’s level of innovation is affected by the amount of knowledge that it has.

The propensity of employees toward innovation can be nurtured by fostering open lines of communication within an organization (Ceschi et al. 2014). Ceschi et al. (2014) note that the knowledge sharing of employees about their jobs and daily routines has the potential to, and should, help businesses become more creative. Therefore, an efficient business should have a mechanism by which workers can contribute to the managerial process and suggest novel approaches to innovation. This study’s findings support that information sharing among workers has a salutary effect on the propensity of employees to engage in creative problem solving and can be similarly interpreted.

Internal company communication is the bedrock of innovation and the creation of opportunities for employees to help and support one another. Knowledge sharing among workers increases the number of improvements that can be made on the job. In conclusion, according to this study’s additional analysis, knowledge sharing plays a full mediating role in the connection between the trust and innovative behavior among workers. Trust among coworkers does not directly affect the propensity of employees to be innovative. However, the knowledge-sharing activity that arises when coworkers feel comfortable enough to share information is a cornerstone of the propensity of employees to be innovative. Alternatively, knowledge sharing partially mediates followers’ trust in leaders and their subsequent creative actions. This means that leadership has a direct effect on innovative behavior but no indirect effect on the practice of sharing one’s knowledge.

9. Conclusions

This study delves into the factors that inspire employees to think outside the box to better position their companies in the service sector. In particular, we examined how employees’ trust in one another and their superiors affects their propensity to take creative risks. In addition, we examined whether the relationship’s mediation comes from the exchange of knowledge. The theoretical contribution of this study is that it shows how important it is for employees to be open to new ideas and trust their managers and coworkers.

This research confirms the importance of a conducive work environment in which employees feel comfortable expressing their ideas and opinions. This study’s findings emphasize the importance of team dynamics, particularly in fostering a culture of trust among workers. We also show that trust indirectly affects innovative behavior via the spread of information. In addition to its theoretical relevance, this research also has real-world applications. A joint organizational flaw hampers knowledge sharing in the service industry. For instance, one worker may attribute some of their skills to the knowledge that they have gained through work experience. As a result, they will be hesitant to teach others or will only teach a fraction of what they know (Mohammad and Khassawneh 2022; Kremer et al. 2019).

This kind of selfishness hinders the sharing of information within the company and causes friction among workers. Therefore, it must be processed at the organizational level, and one approach to addressing this issue is to foster a more trusting environment among workers. The service manager of an organization is responsible for fostering a positive work environment by encouraging participation in any existing employee networks, whether formal or informal. Woodward and Shaffakat (2017) suggest employee empowerment as a managerial practice for boosting an organization’s trustworthiness, and they also argue that the promotion of knowledge sharing should be a part of this effort. With a knowledge-sharing system in place, managers can foster a sharing culture that encourages learning and growth among employees, which, in turn, stimulates more creative thinking. The importance of this study lies in the fact that it empirically explores the factors that influence innovative behavior, with employees as the primary focus of the analysis. One of this study’s limitations is that we interpret and analyze the variable as a multidimensional concept. This is one of the reasons why the study has this limitation. Interpersonal trust is possible; it just requires a different strategy than the multitiered one used for vertical and horizontal trust. Second, innovative behavior encompasses organizational and collective innovation, which are conceptually distinct from individual innovation. More concretely evaluating innovative behavior across a more expansive space will yield more relevant results in future studies.