The Nexus between Team Culture, Innovative Work Behaviour and Tacit Knowledge Sharing: Theory and Evidence

Abstract

Tacit knowledge sharing is an essential intellectual capital for frontline employees in hotel enterprises. While the relationship of knowledge sharing with team culture (TC) and innovative work behavior (IWB) was investigated in the extant literature, little is known about the extent to which tacit knowledge sharing affects TC and IWB. In this regard, the purpose of this study is to investigate the role of tacit knowledge sharing in the relationship between TC and IWB. For this purpose, data were gathered from 360 department managers of Turkish 4–5 star hotels. The results were analyzed utilizing Smart PLS 3 using bootstrapping to determine the level of significance of the relationships between tacit knowledge sharing, TC and IWB. The results show statistically significant relationships between tacit knowledge sharing, TC and IWB. Moreover, tacit knowledge sharing has a mediating role in the relationship between team culture and innovative work behavior.

1. Introduction

Tacit knowledge is of paramount importance to institutional success across all industries. Tacit knowledge sharing is particularly valuable in the hospitality industry due to the nature of the service products, where service distribution requires interaction between the customer and the employee as well as employees’ having information about customers in order for them to ensure customer satisfaction [1]. In addition to tacit knowledge being inimitable, its features, such as being unique, incapable of being copied and easily transferred, increase the strategic importance of such knowledge for hotel businesses. For this reason, tacit knowledge sharing provides a sustainable competitive advantage to hotel businesses [2]. For instance, if an employee, such as the front office staff, who is in close contact with the guests, knows the guests’ expectations without contacting a service provider, the guests are likely to be satisfied with the employee’s services. For this reason, using tacit knowledge in hotel businesses ensures the creation of better value for customers [3]. Tacit knowledge sharing have increased IWB which is necessary for adapting changing tourist expectation and demand [4].

In addition, team culture (TC) facilitates innovative work behavior by supporting tacit knowledge sharing [5,6]. TC further creates a strategic commitment among team members, provides better communication in the form of formal or informal social interaction and motivates others, which leads to a better service innovation performance [7]. For this reason, we assert that tacit knowledge sharing plays a central role in the relationship between TC and IWB. This relation structure is very important for the success of hotel enterprises, as an understanding of the relationship among these three variables helps hotel managers how can develop new and unique service for guests.

However, despite the rising recognition of the importance of tacit knowledge sharing to increase IWB in the context of the hospitality industry, there is a lack of academic research. A limited number of previous research has explored the relationship of knowledge sharing with TC and IWB in hotel enterprises [5,6]. Tacit knowledge sharing was not considered in these studies, and instead, knowledge sharing was considered as symbiosis, reputation, and altruism.

Considering this gap in the literature, the main objective of this study is to investigate the role of tacit knowledge sharing in the relationship between TC and IWB. For this purpose, a model was developed based on the extant literature and the social exchange theory (SET). According to SET, individuals enter into social exchange relationships with the expectation of mutual benefit [8]. In this framework, employees acquire new information by sharing their tacit knowledge with each other. This knowledge would benefit employees in displaying new and different service behavior in the future [9]. In addition, TC provides social benefits such as establishing a long-term relationship based on mutual trust [10], providing new information, motivating and connecting team members to each other [11]. Also, employees can solve the issues they face comfortably with intra-team cooperation due to strong team culture [12].

The novelty of this research comes from: (a) suggesting a new variable, i.e., tacit knowledge socialization and tacit knowledge externalization, which has not been examined previously in the innovation literature, especially in the context of the tourism and hospitality sector, (b) emphasizing the complex mechanism that promotes innovative work behavior in the tourism and hospitality sector by conceptualizing the mediation effect of tacit knowledge socialization and tacit knowledge externalization between the relationship of team culture and innovative work behavior.

To this end, this study theoretically contributes to the extant literature in terms of the effect of tacit knowledge sharing on the relationship between TC and IWB. The findings from this study conceptualize the effect of TC on tacit knowledge sharing based on SET, emphasizes the basic importance of tacit knowledge sharing for IWB, and demonstrates that TC facilitates IWB by facilitating tacit knowledge sharing. The findings are expected to guide hotel managers in the practices of tacit knowledge sharing in hotel businesses and in practices for developing IWB.

The rest of the paper is constructed as follows: Section 2 gives the theoretical framework and development of the hypotheses. Section 3 offers the data and methodological approach. Section 4 exhibits empirical results. Finally, Section 5 includes a discussion of the results, the contributions of the paper and suggests possible areas for further research.

2. Theoretical Framework and Hypotheses

2.1. Team Culture

TC is shown as a key resource of sustainable competitive advantage and organizational productivity [13]. TC is the most important labor force factor behind a successful hotel enterprise. Due to the human-oriented feature of the tourism industry, there is an intense relation among guests, employees and managers. This intensity requires communication skills. TC allows easy communication among hotel departments [14]. TC is defined as an “emergent and simplified set of rules and actions, work capability expectation and perceptions that are shared by team members, developed by themselves and enacted after a range of team member interactions” [6].

TC in hotel businesses can be explained by an explicit system approach, wherein complex explicit systems connect team members to each other and their environments. Teams can be big or small, which is composed of department employees and managers [15]. From this perspective, every department in the hotel business has a direct or indirect relationship with each other and its environment. As such, it is possible to consider each hotel department as a team.

2.2. Tacit Knowledge Socialization

According to Nonaka and Takeuchi’s knowledge creation theory, tacit knowledge sharing takes place in two forms: (1) socialization (from tacit knowledge to tacit knowledge), (2) externalization (from tacit knowledge to explicit knowledge). Tacit knowledge socialization (TKS) is the stage of creating tacit knowledge through shared experience. It is used to highlight the transformation of tacit knowledge to new tacit knowledge during the shared activities—being together, spending time, existing in the same environment—rather than through written and verbal directions [16]. Thus, socialization emerges from a close relationship between mentor and apprentice. It happens through observation, imitation and practice [17]. There is an intense relation between employee-employee and employee-customer in hotel businesses. More often than not, employees share the same environment. This situation is mostly carried to the outside world as well. Therefore, they have the opportunity to transfer their experiences to each other. For instance, a new employee may not know the consumption habits of certain customers. In such cases, she can obtain information from the department manager that she is working with via verbal communication on how to provide the service. This employee can then transfer this information to another employee in the future as a new piece of information after making her own interpretation. For example, not all cocktails can be written in books, but an experienced bar chef can teach all the cocktails she knows to her employees. Similarly, a cook apprentice can obtain much information that is not written in the books by observing and imitating the executive chef.

2.3. Tacit Knowledge Externalization

The tacit knowledge externalization (TKE) stage refers to the conversion of tacit knowledge to explicit knowledge. When tacit knowledge is converted to explicit knowledge, knowledge is crystallized, thus allowing it to be shared by others, and it becomes the basis of new knowledge. The success of the externalization stage depends on the use of metaphor, analogy and model. During this stage, an individual commits to the group, thus becomes one with the group. Methods, such as applying the most successful examples in which experiences are shared and recorded, systems of expertise and case-based logic, storytelling and information exchange minutes are used in the transformation of tacit knowledge into explicit knowledge. For example, the Marriott hotel chain has developed a coding system to keep its employees’ information about their daily and standard operating procedures to provide more stable service to their customers. This approach brings a reward system in which new information about work is shared and created [16].

A study carried out in Portuguese rural tourism lodgings by Pereira et al. [18] demonstrated that be understood tacit knowledge of customers by employees promoted customer loyalty. Another study conducted in 3, 4 and 5-star hotels in Northern Greece revealed that Interpersonal relationships, leadership and formal communication structure are correlated with tacit knowledge sharing [19]. Another of Avdimiotis’s [20] studies in the same country showed that emotional intelligence and tacit knowledge are strongly related. Zhang et al.’s ++ [21] research in southern China lodging firms showed that tacit knowledge spillover among firms facilitates the successful development of a sustainable destination. In addition, Sigala and Chalkiti’s [22] study in the Greek hotels reported that tacit knowledge impacts business performance. However, there is a lack of evidence regarding the influence of tacit knowledge sharing on innovative work behavior in the context of hotel firms.

2.4. Innovative Work Behavior

IWB can be described as “all individual actions directed at the generation, introduction and application of beneficial novelty at any organizational level”. De Jong and Den Hartog [23] distinguish IWB into four dimensions and label them as idea exploration, idea generation, idea championing, and idea implementation. Idea exploration involves finding ways to develop current products, services or processes or attempting to think about them in alternative ways. The next suggested factor of IWB is idea generation that includes recombining internal and external knowledge into new patterns. The third stage of IWB is idea promotion or championing. It involves finding support and building alliances that can help with the implementation of the generated idea. The final phase of the IWB is idea implementation. It includes producing a prototype or model of the innovation that can be experienced and ultimately implemented in a work role, a group or the whole organization [24].

Innovative work behavior in hotel firms has been a preoccupation of researchers for several decades [25]. A synthesis of the relevant literature propounds studies about antecedents of innovative behavior. However, none of them has included tacit knowledge sharing. For example, Dhar’s [26] study in Uttarakhand, India, indicated that ethical leadership enhanced innovative service behavior of the hotel employees mediated through leader-member exchanges. In a study carried out in Beijing, China, on hotels and restaurant frontline employees, Li and Hsu [27] reported that customer participation significantly impacts the innovative behavior of employees. In addition, another study carries out the same researchers found that customer-employee exchange (CEX) influences IWB in the context of Shenzhen, China hotels. Arasli et al.’s [28] study in Turkey, highlighted that psychological safety and engagement in creative work mediated the relationship between constructive leadership and service innovative behavior. Using hotel employees in Pakistan as the sample of the study, Afsar et al. [29] demonstrated that job crafting behaviors mediated the influence of transformational leadership on an employee’s innovative work behavior. Further, this study reveals that knowledge sharing moderates this relationship. In addition to these studies, IWB requires creative thinking, expertise [30], work motivation and engagement [31], justice [32], leader-member exchange [33], work place happiness and co-worker support [25]. IWB provides some benefits to hotels such as: new product or service developing, enhanced service process, influence visitor decision-making, satisfaction and quality. For instance, a restaurant chef’s creating a new foods during the production [31].

2.5. Team Culture and Tacit Knowledge Sharing

Support provided by teammates streamlines sharing knowledge and expertise with others for employees (tacit knowledge socialization), especially when employees face a new and complex task. In addition, TC develops trust and loyalty relationships. This relation provides TKS among team members [34]. And also, TC supports TKS by giving responsibility to employees, enabling feel free to share their ideas and providing a “collaborative, not competitive” atmosphere. Therefore, TC supports the TKS by allowing team members to share their tacit knowledge voluntarily. Furthermore, Yang [35] states that dialogue is of great importance in transforming tacit knowledge into explicit knowledge (tacit knowledge externalization). Employees who have to meet the customer demands in the most accurate way and solve the problems that arise together (team culture) are in constant dialogue [36]. Thus, it can be argued that the TC is closely related to the TKE.

SET is the most prevalent theory in explaining knowledge-sharing behavior. The theory emphasizes the need for long-term social interaction and social relationships with various workplace partners for social exchange [25]. According to this argument, tacit knowledge sharing requires intense social interaction in hotel businesses. The tourism industry’s labor-intensive feature allows this interaction [2]. Hence, social interaction within the team in tourism enterprises and trust are also necessary for tacit knowledge sharing. The reciprocal interdependence of team-workers in work-related tasks strongly motivates employees to work together to achieve common goals and facilitates strong, cohesive relationships. Employees who are committed to each other do not hesitate to share their knowledge about the work [37]. Therefore, we postulate the following hypotheses:

Hypothesis 1 (H1).

Team culture is positively related to tacit knowledge socialization.

Hypothesis 2 (H2).

Team culture is positively related to tacit knowledge externalization.

2.6. Team Culture and Innovative Work Behavior

Simple innovations are often made by individual workers, while the achievement of more complicated innovations usually necessitates teamwork based on various specific knowledge, ability and work role. TC provides better communication in the forms of formal or informal social interaction among team members. Such communication enhances organizational commitment and increases motivation. Thus, the employees’ IWB develops [14]. In the enterprises, which have a strong TC, team members’ sharing common expectations have facilitated the IWB of both individuals and team [6]. Therefore, TC is seen as an important requirement for IWB in service enterprises. Hence, the enterprises where TC is established can more easily overcome various challenges, such as regeneration and providing quality customer service. Teams can also accurately, quickly and effectively adapt to new knowledge and changes as they are more sensitive to changing events and customer demands [14].

Indeed, SET supports this view [8]. According to the reciprocity principle of the SET, team members engage in social exchange with each other to increase their capacity for innovation, create new ideas about the business and even find support for these ideas. For example, it can provide TC members with social exchange factors such as mutual interaction, trust, solidarity, loyalty, and ultimately such mutually beneficial relationships can improve employees’ IWB skills [6]. SET also explains the value resulting from the relationship between individuals or social interactions. When an employee within the organization is satisfied with this relationship, she tends to perform well in return. Based on this argument, we postulate that reciprocal relations between team members create high-quality connections and increase IWB, and therefore we propose the following hypothesis:

Hypothesis 3 (H3).

Team culture is positively related to innovative work behavior.

2.7. Tacit Knowledge Sharing and Innovative Work Behavior

The effective use and sharing of knowledge increase the innovation performance of organizations. It is seen that the enterprises that make innovative projects produce new products and ideas by collecting knowledge and thus increase their innovation performance. Specifically, the proficiency of an enterprise in acquiring and integrating tacit knowledge makes it unique, rare and difficult for rivals to imitate, and hence enterprises achieve sustainable innovation capability. Thus, tacit knowledge sharing is seen as the key factor of innovation, efficiency and competitiveness in hotel enterprises. An organization can create novel knowledge through the conversions among the tacit personal knowledge of individuals, who are capable of producing creative insights and the shared explicit knowledge, which the organization needs to launch new goods and to innovate. According to SET, an individual feels it compulsory to get rid of social and organizational pressure in addition to thanking her colleagues for their help [8]. In this respect, individuals expect to be socially rewarded, appreciated, approved and respected by sharing knowledge. As a result, as tacit knowledge sharing increases, the relationship of reciprocity increases, and the employee is more likely to get new ideas and support from others and seize stronger opportunities to show IWB.

Although the experimental model is presented in Figure 1, an alternative model has been proposed to better understand the relationship between knowledge sharing and innovative work behavior. Studies investigating the relationship between knowledge sharing and IWB proposed that team culture in hotels is one of the most important organizational variables that facilitate knowledge sharing [14]. According to the principle of reciprocity, if there is no quality relationship between team members, knowledge sharing is impossible. Jamshed and Majeed [14] suggest that good relationships between team members have increased team cohesiveness. Thus, team members are more willing to share their experiences with other members. Therefore, better team culture suggests an increased IWB in hotels. Applying this framework to our alternative model, then, we predict that the relationship between KS and IWB is moderated by team culture. We thus put forward the following hypothesis:

Several studies emphasize the effect of tacit knowledge on innovation. Wang and Wang [38] state that tacit knowledge sharing has a positive effect on innovativeness. Similarly, in their study in which they examined current research on knowledge management and knowledge sharing in tourism, Shaw and Williams [39] emphasize the importance of tacit knowledge sharing for innovation. Consistent with this view, Yang [35], who investigated the factors that affect knowledge sharing in international hotel communications in Taiwan, states that the SECI model focuses on knowledge creation, and the main purpose of the four components of the model is continuous innovation. Lee and Kim [40], in their study on restaurant employees, concluded that the mutual sharing of their tacit knowledge with each other increased the level of their innovative work behavior. Based on this information, the following hypotheses were proposed:

Hypothesis 4 (H4).

Tacit knowledge socialization is positively related to innovative work behavior.

Hypothesis 5 (H5).

Tacit knowledge externalization is positively related to innovative work behavior.

2.8. The Mediating Role of Tacit Knowledge Sharing

IWB develops in a strong TC. Jamshed and Majeed [6] claim that the most important reason for this is that TC facilitates tacit knowledge sharing. TC, which allows mutual relations, increases the tendency of the employees to display IWB by facilitating tacit knowledge sharing. TC has influenced an individual’s perception, behavior and attitude within the group. The individual is thus sensitive to her social environment and does not hesitate to follow the norms of the team she belongs to. As a result, she shares his knowledge with others without any coercion. Thus, new ideas and concepts usually appear from group activities wherein people interact face-to-face with each other, share ideas freely and are motivated about sharing tacit knowledge [17].

We can explain the relationship between TC and tacit knowledge sharing behavior according to SET. While the individual shares her tacit knowledge with other individuals, she both incurs some costs and gains benefits from this sharing; knowledge is power, and employees do not want to bear the cost of losing this power. Employees have the concern of losing their status and promotion opportunities. However, sometimes employees may see their own knowledge as invaluable. Such reasons can be perceived as costs by employees. Factors such as increasing professional recognition through sharing, strengthening friendship bonds and the pleasure of contributing to developing the profession can be perceived as benefits. The SET suggests that individuals engage in a mutual social exchange relationship with expectations, such as trust, love and friendship. Accordingly, TC provides employees with mutual trust, support and recognition [10]. TC motivates team members to support for the benefit of everyone. It connects team members to each other [11]. The support provided by teammates makes it easier for employees to share their knowledge and expertise with others, especially when employees face a new and complex task. If the employee has someone, who will support him/her to accomplish a task and share their experiences, he/she gains confidence in achieving difficulties and being innovative. Working with helpful and supportive colleagues creates an environment where innovative ideas can be discussed freely and openly. Thus, intraorganizational innovative behaviors develop and increase [25]. Therefore, team culture supports the relationship of interpersonal social exchange, and individuals can share their knowledge and experience more easily because they benefit from each other in team culture. Therefore, we postulate the following hypotheses:

Hypothesis 6 (H6).

Tacit knowledge socialization mediates the relationship between team culture and innovative work behavior.

Hypothesis 7 (H7).

Tacit knowledge externalization mediates the relationship between team culture and innovative work behavior.

Based on the above theoretical framework and hypotheses, a proposed research model was developed, as shown in Figure 1.

2.9. Alternative Model

Team culture has a moderating effect between knowledge sharing and innovative service performance in hotels. When team culture is supported in hotels, the relationship between knowledge sharing and innovative behavior stronger. For this reason, team culture is closely related to innovative work behavior [6]. Based on this current frame study has asserted that team culture moderates the relationship between tacit knowledge sharing and innovative work behavior in hotel enterprises.

To sum up, due to the increased competition in the tourism industry, changing demands and expectations and technological innovations forced hotel firms to adapt to these changes and to improve the innovative behavior of their employees [4]. Innovative behavior requires cooperation, knowledge and experience. Thus, team culture is seen as a strong facilitator for individuals to improve their innovative ability [41]. Because teamwork provides employees to trust each other and thereby experienced persons share their tacit knowledge with others [40]. This framework gives important evidence to hotel managers on how innovative work behavior can be encouraged and to get a competitive advantage (Please see Figure 2).

Hypothesis 8 (H8).

Team culture positively moderates the relationship between knowledge collecting and innovative work behavior.

Hypothesis 9 (H9).

Team culture positively moderates the relationship between knowledge donating and innovative work behavior.

3. Methodology

3.1. Sample

Data were collected from the department managers of the front office, housekeeping, restaurant, and kitchen in Turkish 4–5 star hotels with convenience sampling technique. Convenience sampling is most often used during the exploratory phase of a research project and is perhaps the best way of getting some basic information quickly and efficiently [42]. Participants were requested to respond to the questions in a self-administrative manner. The database of the Republic of Turkey, Ministry of Culture and Tourism, was used to obtain information about 4 and 5-star hotels. Currently, a total of 1457 four and five-star hotels operate in Turkey.

The front office, housekeeping, restaurant, and kitchen department managers in each hotel were included in the study. Accordingly, the research population was determined as 5828 (1457 × 4 departments manager). According to the sample size for a given population size advised by Sekaran [43], in this study, we considered a minimum sample size of 360 respondents sufficient. Then, a survey was conducted through personal interviews until this number was reached in 2018. We further used G*power software to estimate the minimum sample size. Accordingly, the latent construct that has the highest number of predictors (arrows) was evaluated. IWB has three predictors (see Figure 1), and for the PLS, the construct IWB determines the minimum sample size to be used. Therefore, the calculated minimum sample, for the example, should be 77 cases. However, it is beneficial to double or triple this amount to have a more consistent model [44]. Hence, the sample size was found to be sufficient in this study. In addition, the determined sample size meets the 10-times rule [45].

The majority of the respondents were male (69.4%), and the percentage of those aged between 36 and 45 was 55%. The rate of the participants who received tourism education was 76.1%. The rate of the departments that had eight or more employees was 72.8%. In addition, 39% of the department managers had worked in their current business for 3 to 6 years, and 70.5% of them had more than 10 years of sector experience. The percentage of 4-star hotel enterprises was 55%. The percentage of hotel enterprises included in the study and operating as a private company was 54.4%. In terms of the professional status, 32.9% of the participants were front office managers, 27.4% were housekeeping chiefs, 24.7% were F and B managers, and 15.1% were chief cooks.

3.2. Measurement

A survey was used as a measurement tool in this study (see Appendix A), which consisted of five sections and 45 items: (1) TC; (2) TKS; (3) TKE; (4) IWB; and (5) demographic information. Question items were answered on a seven-point Likert scale, with 1 referring to strongly disagree and 7 referring to strongly agree. TC was measured by a 16-item scale adapted from Molose and Ezeuduji [43]. Cronbach’s reliability for TC was 0.844. TKS and TKE were measured by an 8 and 7-item scale, respectively. Cronbach’s reliability for both was 0.859 and 0.817, respectively. IWB was measured by a 10-item scale adapted from De Jong and Den Hartog [23]. Cronbach’s alpha coefficient for this scale was 0.868. De Jong and Den Hartog [23] distinguished IWB into four dimensions and labeled them as idea exploration, idea generation, idea championing, and idea implementation. However, it is seen that the IWB scale is evaluated as one-dimensional in many studies on IWB in tourism businesses [6]. In addition, in the development process of the scale De Jong and Den Hartog [23], which evaluates IWB in 4 dimensions, it benefited from the works of Scott and Bruce [46]. Both studies are frequently used in the tourism sector and are one-dimensional. In addition, in this study, the IWB scale is applied to a different area in terms of both culture and sample. In addition, as a result of confirmatory factor analysis, some items of the scale were below the 0.60 threshold value recommended by Hair et al. and these items were excluded from the scale because this situation impairs the construct validity (see

Table 1. Measurement model results.

Construct	Items	Loadings	AVE	CR	CA
Team culture	I support knowledge and technical information sharing	0.784	0.641	0.901	0.844
	This hotel coordinates teamwork through formal rules and procedures	0.768
	This hotel coordinates teamwork through pre-designed work plans and processes	0.825
	This hotel coordinates teamwork through leaders or their assistants	0.847
	This hotel assigns coordinators to coordinate teamwork	0.832
	This hotel coordinates work by directly communicating with knowledgeable team members	0.781
	This hotel’s members hold regular meetings to coordinate teamwork	0.777
	This hotel’s members meet freely to discuss the coordination of teamwork	0.762
	Each member of this team contributes equally to our hotel’s service innovation	0.800
	The members of the team I am responsible possesses a fine spirit	0.834
	Members of this team have a strong sense of participation	0.789
Tacit knowledge socialization	In team discussion, I actively share my experience with others	0.831	0.639	0.898	0.859
	In my work team, my teammates and I share life or work experience with each other	0.807
	During discussion, I bring up some concepts, thoughts or ideas	0.738
	I often encourage others to express their thoughts.	0.821
	I teach others through demonstrating the craftsmanship and expertise	0.798
Tacit knowledge externalization	I can describe professional or technical terms with conversational language to help communication in a team.	0.793	0.733	0.892	0.817
	I will help others to clearly expressing what he/she has in mind by encouraging them to continue what they are saying.	0.880
	When others cannot express themselves clearly, I usually help them clarify their points.	0.892
Innovative work behavior	I wonder how things can be improved	0.779	0.656	0.905	0.868
	I generate original solutions for problems	0.818
	I find new approaches to execute tasks	0.744
	I contribute to the implementation of new ideas	0.847
	I put effort into developing new things	0.855

Note: CA = Cronbach’s alpha; CR = composite reliability; AVE = average variance extracted. All item loadings > 0.6 indicate indicator reliability [47]. All average variance extracted (AVE) > 0.5 indicates convergent validity [48]. All composite reliability (CR) > 0.7 and all Cronbach’s alpha > 0.7 indicate internal consistency [47,48].

) [47]. The remaining items revealed the unidimensional structure of the scale. Therefore, the IWB scale was evaluated as one dimension in this study.

3.3. Data Analysis

To test the inter-item reliability and the clarity of the survey instructions, a pilot test (n = 50) was conducted with hotel departments’ managers. The value of Cronbach’s alpha exceeds the cutoff point of 0.70, indicating sufficient internal consistency in each section of the questionnaire [48]. To test the research model, Partial Least-Squares (PLS-SEM) was used. This technique does not require assumptions on the multivariate normality of the data and works efficiently with small sample sizes and complex models. This study does not provide the assumption of univariate normality. It is explorative, and the sample size is not very large (n = 360). For this reason, PLS-SEM was preferred to test the research model. This method proposes a two-stage analysis process, including assessment of the measurement model and structural model [47]. (Please see Appendix A and Appendix B).

4. Results

4.1. Measurement Model Assessment

The internal consistency reliability, convergent validity and discriminant validity were assessed following the procedure suggested by Fornell and Larcker [49]. Table 1 shows the related results. Sixteen items with factor loading below the threshold value (0.60) were removed [47]. Internal consistency reliability was examined by Cronbach’s alpha (CA) and composite reliability (CR). The results obtained show that it is above 0.70, which is the recommended threshold for both values [47,49]. The average variance extracted (AVE) exceeds the cutoff point of 0.50 [48]. Therefore, the model is sufficient in terms of intrinsic reliability and convergent validity values.

In addition, the discriminant validity of the constructs was evaluated using Fornell–Larcker criterion. The Fornell–Larcker criterion says that a factor’s square root of AVE should be higher than its squared correlations with all other factors in the model [50].

Table 2. Discriminant validity.

	Mean	SD	IWB	TKE	TKS	TC
IWB	6.316	0.806	0.810
TKE	6.211	0.815	0.766	0.856
TKS	6.365	0.912	0.797	0.737	0.800
TC	6.075	1.042	0.557	0.522	0.627	0.800

Note: bold values of the diagonal are the square root of the AVE.

indicates that all of the square roots of the AVE (values in bold, off-diagonal) are greater than the correlations in the respective columns and rows. Therefore, the measurement model demonstrated adequate discriminant validity. In addition, for the model fit assessment, the SRMR value was used [50]. A value less than 0.10 or 0.08 is considered a good fit [51]. In our case, we obtained 0.058 for the saturated model and 0.094 for the estimated model, which means that the proposed model has a good fit for the data.

Common method variance (CMV) was tested with Harman’s single-factor test [52], partially out of general factor test [53,54] and full collinearity test [55]. The result of Harman’s single-factor test revealed that one factor was not accounted for the majority (33%) of the variance. The R² value of the endogenous construct before and after adding the general factor was observed. The R² value of IWB, TKS and TKE were 0.765, 0.402 and 0.282 before adding the general factor, respectively. After adding the general factor, the R² value of IWB, TKS and TKE was slightly increased to 0.767, 0.404 and 0.297, respectively. Thus, adding this factor does not lead to any significant change in the R² value of the endogenous constructs. In addition, all VIFs resulting from a full collinearity test are equal to and lower than 3.3. All results are presented in

Table 3. Results of R², Q² and full collinearity.

	R2 without Common Factor	R2 with Common Factor	Q2		Inner VIF Values
TKS	0.393	0.394	0.230		IWB	KE	KS	TC
TKE	0.273	0.274	0.188	IWB		2.8	2.6	3.3
IWB	0.707	0.708	0.424	TKE	2.2		2.5	2.7
				TKS	2.7	3.1	1.5	3.0
				TC	1.7	1.6

. Therefore, our data did not suffer from CMV.

4.2. Structural Model and Hypothesis Testing

The structural model was assessed based on Hair et al. [45]. Accordingly, we evaluated collinearity, R², beta (β) and the t-values via a bootstrapping procedure. In addition, we reported the predictive relevance (Q²). Since all variance inflation factor (VIF) values are under the threshold value of 5, we have no multicollinearity in our structural model. VIF values that belong to TKS, TKE and TC are 2.653, 2.216 and 1.669, respectively. Table 3 shows the R² and Q² values. [47] suggested that R² values 0.75, 0.50 and 0.25 are classified as substantial, moderate, and weak effects, respectively. In this study, while R² values of innovative work behavior were substantial, R² values of TKS and TKE were moderate. Q² values were investigated for predictive relevance. The value of Q² higher than zero indicates that our structural model is acceptable for predictive relevance.

Our structural model was tested in two steps. First, (model 1), we analyzed the relationships between TC and the three variables: TKS, TKE IWB. As can be seen in Figure 3, all three relationships were positive and significant (TC → TKS, path = 0.627, p < 0.001; TC → TKE, path = 0.523, p < 0.001; TC → IWB, path = 0.561, p < 0.001), supporting Hypotheses 1, 2, and 3. We further examined the direct effects of TKS and TKE on IWB. Both variables had positive significant effects on IWB (TKS → IWB, path = 0.478, p < 0.001; TKE → IWB, path = 0.385, p < 0.001). Therefore, H4 and H5 were supported. Results are seen in

Table 4. Hypotheses’ testing bootstrap direct effect results.

Hypotheses	Paths	Path Coefficients	t-Values	CI-BC
H1	TC→IWB	0.561	7.089 ***	[0.387, 0.698]
H2a	TC→TKS	0.627	8.426 ***	[0.470, 0.756]
H2b	TC→TKE	0.523	6.380 ***	[0.349, 0.668]
H3a	TKS→IWB	0.478	6.177 ***	[0.338, 0.631]
H3b	TKE→IWB	0.385	5.129 ***	[0.225, 0.512]

*** p < 0.001; CI-BC: bias corrected confidence intervals.

.

Second, to identify the multiple mediation effects of TKS and TKE, we conducted a comparison between model 1 (Figure 3) and model 2 (Figure 4), where model 2 included the links from the mediators (TKS and TKE) and the dependent variable. In this stage, we determined whether the mediators (TKS and TKE) affect IWB when the independent variable (TC) is controlled. If TKS and TKE completely mediate the relationship between TC and IWB, the path between them should then become non-significant.

First, we calculated the significance of a multiple mediation effect in the smartpls3. As can be seen in Figure 4, the path model 2 from TC to IWB became non-significant. This confirms that the effect of TC on IWB was completely mediated by TKS and TKE.

We next conducted the bootstrap test developed by Preacher and Hayes [56] and used it to test the mediation analysis. As can be seen in

Table 5. Mediation results.

Hypotheses	Specific Indirect Effect	Path Coefficients	t-Values	CI-BC	VAF
H4a	H6:TC→TKS→IWB	0.299	4.744 ***	[0.186, 0.446]	0.842
H4b	H7:TC→TKE→IWB	0.201	4.247 ***	[0.111, 0.298]	0.939

VAF: variance accounted for; *** p < 0.001; CI-BC: bias corrected confidence intervals.

, specific indirect effects were found significant. Both TKS (TC → TKS → IWB, path = 0.299, p < 0.001) and TKE (TC → TKE → IWB, path = 0.201, p < 0.001) are mediator in the relationship between TC and IWB. In addition, an interval of mediating effects contains no zero. Thus, H6 and H7 were supported. In determining mediation’s strength, the variance accounted for (VAF) was computed [47]. Accordingly, VAF less than 20% indicates no mediation, and larger than 80% indicates full mediation, and VAF ranging from 20% to 80% indicates partial mediation. All of the results are seen in Table 5. Accordingly, TKS and TKE fully mediated the relationship between TC and IWB.

4.3. Assessment of Alternative Model

Figure 5 shows the results for the alternative model. As shown by the t-statistics and path coefficient, both dimension of tacit knowledge sharing, namely socialization (path = 0.446, p < 0.001) and externalization (path = 0.370, p < 0.001) had significant effect on innovative work behavior at 0.01 level. Thus, H1 and H2 are supported. As presented in Table 4, the moderating effect of team culture on the relationship between tacit knowledge externalization and innovative work behavior (path = 0.005, p > 0.001) and on the relationship between tacit knowledge socialization and innovative work behavior (path = 0.042, p > 0.001) were not statistically significant. Thus, H3 and H4 rejected Table 4.

5. Discussion

We analyzed the effects of TC, TKS, TKE on IWB and moderating roles of TKS and TKE on the relationship between TC and IWB in Turkish 4–5 star hotels. The analysis consisted of a two-stage process. In the first stage, the direct effect of TC on TKS, TKE and IWB was tested. In the second stage, the indirect effect of TC on IWB was tested considering the mediating effect of TKS and TKE in addition to the direct effect of TKS and TKE on IWB.

Our findings clearly suggest that TC does not mitigate the effect of knowledge sharing on IWB. These results suggest that the relationship between TKS and IWB and TKD and IWB is not moderated by the team culture, which contradicts the findings in former studies [6,14]. In the current study, we considered knowledge sharing as knowledge collecting and knowledge donating. Such a distinction has not been made in the previous studies.

The results showed that TKS and TKE have a full mediating effect on the relationship between TC and IWB, thus supporting H6 and H7. Accordingly, TC alone is not a strong predictor of IWB; however, TC has facilitated tacit knowledge sharing, suggesting that tacit knowledge sharing is an important determinant of innovativeness. Jamshed & Majeed [6] investigated the moderating effect of TC in the relationship between knowledge sharing and innovative service behavior, while Hussain et al. [14] focused on the mediating role of it within the same relationship structure. However, in some studies that address relationships between variables differently [6,14,43], the mediation role of tacit knowledge sharing on the relationship between TC and IWB has not been explored in previous studies.

Another result is the significant and positive direct influence of TC on IWB. This finding, which supports H3, is consistent with the results of similar studies previously conducted on hotel business employees [14]. This means that, as Jamshed and Majeed [6] stated, sharing the common expectations of the team members in hotel businesses with strong TC facilitates both individual and team innovation. Hotel departments’ working in harmony with each other is important for quality and different service provision to customers. To achieve this goal, there is a need for teams that focus on the same goal. In addition, teams can adopt new information and changes faster in hotel businesses where customer demands and requests are constantly changing since they are more sensitive to events and customer demands. This approach increases the level of innovation within teams [6]. SET provides concrete explanations for this outcome. According to the theory, an individual communicates with other people with reciprocal expectation and share her knowledge with them. TC provides its member-reciprocal benefits. In this culture, individuals build friendship relationships, help each other and together develop more successful and innovative services.

Also, TC has a significant direct effect on TKS and TKE, thus supporting H1 and H2. This means that employees can easily share their tacit knowledge in businesses where mutual trust, a collaborative and learning-supporting culture (team culture) exist. Furthermore, the mutual interdependence of team employees in work-related tasks facilitates tacit knowledge sharing [37]. High social interaction and trust relationships within the team are necessary for tacit knowledge sharing. The labor-intensive feature of the tourism industry further enhances this social interaction [2]. This result partially corresponds with the findings of the studies investigating the impact of organizational culture [57] on knowledge-sharing behavior in tourism enterprises.

Lastly, TKS and TKE positively and significantly affect IWB directly, partially in line with the research results in the field of tourism (e.g., [34]). For this reason, H4 and H5 are supported. This outcome suggests that tacit knowledge sharing in hotel operations increases the IWB skills of employees [6]. Unlike the findings of previous studies, this study considered tacit knowledge sharing as an important antecedent of IWB. Various reasons can be effective in the emergence of this result. Hotel enterprises offer more different and newer services than their competitors with experienced workers. In addition, experience and expertise knowledge named “know-how” cannot be imitated by others [2]. This strategy makes the hotel enterprises superior to their competitors. Therefore, tacit knowledge sharing is an important determinant of IWB.

5.1. Theoretical Implications

This study contributes to the extant literature on knowledge management and innovation and to tourism and hospitality literature. Former studies have investigated the effect of TC and knowledge sharing on IWB in hotel businesses [14]. However, prior studies did not take tacit knowledge sharing into consideration, which is of strategic importance to hotel businesses [7]. Therefore, the extent to which tacit knowledge sharing influences IWB was not clear. In this study, a model that emphasizes the mediating role of tacit knowledge sharing in the relationship between TC and IWB in hotel enterprises was developed and tested in order to fill this gap. Research findings show that team culture and tacit knowledge sharing directly affect innovative business behavior in hotel businesses. This result expands upon the results of previous studies. For example, Hussain et al. [14] found that TC and knowledge sharing directly and positively affect IWB in a study conducted in hotel businesses in Malaysia. A similar result was also found by Molese and Ezeudiji [13] in accommodation businesses in South Africa and Jamshed & Majeed [6] in hotel businesses in Taiwan. In addition, the results of this study show that, unlike other studies, tacit knowledge sharing supports IWB and that TC facilitates tacit knowledge sharing. With this aspect, this study provides an in-depth understanding of the importance of tacit knowledge sharing in hotel businesses.

The findings from this study further contribute to the social exchange theory [8]. Employees in hotel businesses do not want to share their tacit knowledge, which they see as the basis of individual competition [7]. According to the SET, if the employees think that they will benefit from tacit knowledge sharing, they do it. For this reason, although employees have the risk of losing the power of knowledge, they tend to increase efficiency and productivity by acquiring and transferring knowledge to other colleagues. Furthermore, this behavior can motivate the employees to transform their tacit knowledge into explicit knowledge by documenting and storing acquired knowledge somewhere in organizational memory. This new knowledge can develop new and different services in the future [58]. Therefore, this study provides evidence for the applicability of the social exchange theory in the hospitality industry, with an emphasis on the importance of the mutual benefit principle of this theory in tacit knowledge sharing.

5.2. Practical Implications

The findings of this study offer strong benefits for managers and practitioners in the accommodation industry. The research findings offer an original perspective to hotel managers since it demonstrates that TC provides tacit knowledge sharing, which is one of the most important premises in supporting IWB in hotel businesses. To form a team culture and support tacit knowledge sharing, managers should provide their employees with an organizational environment where they can share the same rules, expectations and roles. Managers should further encourage intraorganizational assistance and solidarity in the organization. Both knowledge socialization and knowledge externalization are vital to facilitate employees’ innovative work behaviors in the context of hotels. Therefore, hotel managers should understand employees’ tacit knowledge sharing behaviors, such as work-related experience and abilities and the need to include their knowledge application behaviors to promote employees’ innovative work behaviors. In addition, hotel businesses should focus on organizational goals rather than individual targets and explain their benefits and importance to their employees. Managers could show explicit examples to their employees explaining the mutual benefits they can gain by sharing their experience and business skills. In addition, when tacit knowledge is shared and turned into explicit knowledge, the new knowledge obtained is stored in organizational memory. This new knowledge is no longer lost and becomes the corporate culture of the business even though the staff quits his/her job. Therefore, hotels should create a system where the knowledge gained from experienced personnel is recorded. New knowledge gained as a result of tacit knowledge socialization will provide a competitive advantage to hotel businesses. Thus, this knowledge should be kept within hotel businesses, which can be achieved by reducing employee turnover. That is, hotel businesses should take measures to increase employee satisfaction and decrease turnover.

Considering the contribution of the tourism industry to Turkey’s economy, these results are also important for policymakers in Turkey [59]. The Turkish government demonstrates the ability to develop new services that meet customer demands and needs among the most basic conditions to compete in the tourism market. Therefore, the empirical model presented in this research provides an approach to policymakers in developing innovative business behavior in hotel businesses.

On the other side, this study gives some insight into hotel firms after the COVID-19 pandemic. The tourism industry worldwide is being among the most damaged industries from the COVID-19 lockdowns. Some studies in the hospitality industry indicate that innovative capabilities of firms can be a solution to recover from [41,60,61,62,63,64,65,66,67,68,69] and overcome COVID-19 during and after the crisis [70,71]. Breier et al.’s [70] suggest business model innovation to cope with the pandemic, while Shin and Kang [72] technological innovation. Health concern is among the most important factors affecting travel motivation. Same as during the pandemic process, after the pandemic, too, tourists will be reluctant to visit destinations or hospitality properties [73]. For that reason, after COVID-19, hotels should feature their individual capabilities such as innovative employees to allure visitors and give confidence to them. In this scope, the current study suggests a model that shows innovative work behavior can be enhanced within in team culture that facilitates tacit knowledge sharing. In that sense, the model will assist hotel firms in what can be done after the pandemic.

5.3. Limitation and Research Direction

Despite its contribution to the extant literature, this study has some limitations. First, research data are cross-sectional. Therefore, a longitudinal study approach could be undertaken in future studies. Although Harman’s single factor test showed that CMV was not a serious problem in the present study, data were largely self-reported, and therefore, there was a probability of CMV. In addition, this study explains the impact of team culture on innovative business behavior and the mediating role of tacit knowledge sharing. Although the validity and utility of the research model have been proven, researchers may consider including other variables that may have an impact on innovative work behavior in future studies. For example, future studies may include internal motivation, leadership styles, and organizational justice and support variables as the precursors of innovative business behavior. Furthermore, this study is only limited to Turkish 4–5 star hotels. The tourism industry also contains other sectors, such as travel and catering. Future research should take that into consideration in their studies. Fourth, this study includes hotel businesses in Turkey. Future studies can test the same model and variables on hotel businesses of different countries. Five, due to the COVID-19 pandemic process, Turkish 4–5 star hotels are closed. For this reason, we could not collect data again and interview managers. Finally, no distinction was made between resort and business hotels while collecting data in this study. Accordingly, this situation may prevent the generalizability of the results. Future studies that will carry out similar research may apply the research model to subject groups separately and interpret the results comparatively.