Journal of Entrepreneurship, Management and Innovation (2024)

Volume 20 Issue 3: 62-77

DOI: https://doi.org/10.7341/20242034

JEL Codes: M12, O31

Sultan Alzyoud, Assistant Professor, Department of Business Administration, Business School, The Hashemite University, Zarqa, 453J+5C5, Damascus Hwy, Zarqa, Jordan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Waed Ensour, Associate Professor, Department of Business Administration, Business School, The Hashemite University, Zarqa, 453J+5C5, Damascus Hwy, Zarqa, Jordan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Ayman Harb, Associate Professor, Department of Hotel Management, School of Tourism and Hospitality, The University of Jordan /Aqaba Branch, Aqaba, H2MF+PHC, Aqaba, Jordan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

PURPOSE: In reality, service failures are inevitable. However, poor service recovery can decrease customer trust and exacerbate customer dissatisfaction. Previous studies have focused on service failure types, reasons for failure, and successful recovery actions from the customers’ perspective. Accordingly, this study aims to present adifferent view by investigating the factors that could improve hotel recovery performance from the employees’ perspective. Therefore, amodel was developed to study the influence of employees’ voice, tacit knowledge sharing, and employee innovation on service recovery performance. METHODOLOGY: This quantitative study used an online survey to gather data from employees in the hotel industry in Jordan. Atotal of 214 valid responses were obtained. Participants were targeted randomly, mainly through Facebook groups for hotel employees. PLS-SEM (Partial Least Squares Structural Equation Modeling) was employed in this research to analyze the data using Smart PLS 3 software. FINDINGS: The results indicated that employee voice is positively associated with tacit knowledge sharing. Furthermore, it was found that tacit knowledge sharing is positively related to employee innovation. The findings demonstrated that tacit knowledge plays apartial mediating role in the association between employee voice and employee innovation. Additionally, it was discovered that employee innovation has apositive association with service recovery performance. Finally, the results indicate that employee innovation partially mediates the relationship between tacit knowledge and service recovery performance. IMPLICATIONS: Hoteliers are suggested to create asupportive work climate where employees can express their thoughts, ideas, and concerns without fear of retribution. Furthermore, hotel managers are advised to establish clear expectations for employees regarding the significance of their opinions and insights, and recognize and reward innovative ideas that can hopefully enhance hotels’ performance. ORIGINALITY AND VALUE: This research provides new insights and contributes to the understanding of the role of employee voice, tacit knowledge sharing, and employee innovation in enhancing service recovery performance, particularly in acontext that has received little attention from researchers, which is the hotel sector, and in adeveloping country, Jordan. Compared to past studies, this study offers amodel that demonstrates how to leverage service recovery efforts in hotels by illustrating structured relationships between employee voice and service recovery performance through the mediation of tacit knowledge sharing and employee innovation.

Keywords: employee voice, service recovery performance, employee innovation, tacit knowledge sharing, hotels, Jordan, hotel sector, quantitative research, Structural Equation Modeling

INTRODUCTION

Service failure is inevitable (Ahmad, Liu, Asif, Ashfaq, & Irfan, 2022). It is challenging for organizations, especially hotels, to eliminate all service failures and achieve a service encounter with no defects (Alzyoud & Abuzaid, 2023). Service recovery actions are necessary to rectify mistakes and assist organizations in altering negative customer attitudes toward their services whenever a service failure occurs (Alzyoud & Abuzaid, 2023).

Studies have shown that dissatisfied customers may share their negative experiences with 10-20 people (Mattila, 2001). However, effective service recovery can eliminate negative word-of-mouth publicity (Liao, 2007; Vázquez-Casielles, Iglesias, & Varela-Neira, 2017). According to Ashill, Carruthers, and Krisjanous (2005), successful recovery can transform a dissatisfied customer into a satisfied one. Furthermore, according to Vázquez-Casielles et al. (2017), service recovery enhances customers’ word-of-mouth recommendations, repurchase intentions, and overall satisfaction with the service. According to Liao (2007), previous studies suggest the existence of a ‘service recovery paradox,’ wherein customers who are pleased with the recovery efforts have higher levels of customer satisfaction and support intentions than those who are not. On the contrary, poor service recovery can decrease customer trust and exacerbate customer dissatisfaction, resulting in a ‘double deviation’ effect.

Service recovery performance is directly related to the competencies and behaviors of workers in identifying and resolving service failures (Ahmad et al., 2022). Recognizing complexities and developing ideas or remedies begin with human innovation (Ahmad et al., 2022). They added that the workers’ ability to innovate may affect customers’ reactions to service recovery. Sharing knowledge is one of the factors that enhance employees’ innovation, which can improve service performance recovery. In this context, Montani and Staglianò (2022) propose that employees can enlarge their knowledge base and improve their innovative potential through knowledge sharing.

Yener and Arslan (2017) argue that tacit knowledge is perhaps the most crucial type of knowledge among various types of knowledge. Polanyi (1966) argues that all types of knowledge are either tacit or based on tacit knowledge, making tacit knowledge an essential component of all knowledge. Tacit knowledge, which refers to practical know-how (Koskinen & Vanharanta, 2002), is widely recognized as a crucial element of innovation (Koskinen & Vanharanta, 2002; Seidler‐de Alwis, Hartmann, & Gemünden, 2004). Indeed, tacit knowledge is essential at every stage of the innovation process (Seidler‐de Alwis et al., 2004). Furthermore, tacit knowledge, also known as ‘know-how,’ plays a significant role in decision-making during the innovation process. However, according to Blackman and Sadler-Smith (2009), it is possible for people and organizations to have knowledge that cannot be fully expressed in words or other symbolic representations and that also cannot be foreseen or consciously known in advance. This implies that an organization’s social setting may contain latent or tacit knowledge that is only waiting to be expressed and transformed. Herein lies the importance of employees’ voices in this process.

On the contrary, preventing employees from expressing their opinions hinders communication, limits opportunities to modify routines, and restricts knowledge sharing (Gambarotto & Cammozzo, 2010). The innovation deficit may result from silence, as new ideas, capabilities, and the sharing of knowledge require a conducive environment (Gambarotto & Cammozzo, 2010). Therefore, employees’ voices should enhance knowledge sharing, leading to improved innovation, which, in turn, should promote better service recovery performance. However, these relationships have not received adequate attention, especially in the hotel industry.

Furthermore, although several studies have examined service recovery performance, most of these studies have focused on customers’ perspectives or specific recovery actions made by organizations (Guchait, Paşamehmetoğlu, & Dawson, 2014). Previous studies have examined various types of service failures, the reasons for them, and the methods used to recover from them (Guchait et al., 2014). In a similar context, Lin (2007) claims that little research has been done on investigating service failures and recoveries from the viewpoint of organizations or employees. This starkly contrasts the vast majority of earlier literature, which has focused on the customers’ perspectives. Koc (2019) conducted a literature review and found that service failures and recovery research have predominantly focused on customer satisfaction, service quality, culture, justice, empowerment, and attribution. While there is steady development in studies related to justice theory, the field is primarily saturated with a concentration on customer satisfaction, repeat purchase intentions, and complaint behavior. Notably, research on empowerment exhibits similarities in its association with customer satisfaction. Furthermore, justice studies have primarily explored this concept from the customer’s perspective. Therefore, Koc (2019) proposes enhancing service recovery studies by integrating organizational theories and concepts. Similarly, Lin (2010) concluded that most of the existing literature has predominantly concentrated on examining amendments and responses related to service recovery, primarily from the vantage point of consumers, while limited research was conducted to investigate internal organizational action to prevent service failure and enhance recovery. Thus, service recovery studies have primarily focused on different types of service failures, reasons for these failures, and actions taken by organizations to recover from service failures from customers’ perspective, indicating a gap in the literature regarding the organizational and employee perspectives on service failures and recoveries.

Furthermore, the hotel industry has not given much attention to the factors that improve service recovery performance, employee innovation, tacit knowledge sharing, and employee voice from the viewpoint of the employees. Several researchers have called for more studies to investigate these crucial concepts (e.g., Alzyoud, Abuzaid, & Hamdan, 2023; Alzyoud, Partington, Mitchell, & Dieck, 2017). Overall, this study aims to examine the associations among employees’ expression of opinion, tacit knowledge, innovation, and service recovery performance from the perspective of employees.

LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT

Employee voice and tacit knowledge sharing

Tacit knowledge is knowledge derived from personal experience and is often challenging to express directly in words (Anand, Muskat, Creed, Zutshi, & Csepregi, 2021). Instead, they are often conveyed through metaphors and other forms of expression that do not rely on formal language. Research indicates hidden value in tacit knowledge, with Blackman and Sadler-Smith (2009) considering tacit knowledge as an untapped reserve of valuable skills and knowledge, often residing in personal experiences. Similarly, Puusa and Eerikäinen (2010) emphasize that a significant portion of overall knowledge is hidden in people’s experiences and is often challenging to access and share due to its personal and abstract nature. Accordingly, tacit knowledge is highly personal and abstract, making it difficult to make visible. Boiral (2002) claims that, as tacit knowledge is difficult to codify and is personal, having channels for the employee voice has the potential to provide a mechanism for employees to express and communicate their tacit knowledge.

To release the potential of tacit knowledge, Blackman and Sadler-Smith (2009) recommend that companies should manage ways to access, leverage, and utilize this valuable source through systematic activities fostering dialogue, encouraging diverse perspectives, and promoting individual and collective learning. Boiral (2002) stresses the need for employee voice to serve as a mechanism for employees to express and communicate their tacit knowledge, bridging the gap between hidden knowledge and its dissemination. Seidler‐de Alwis et al. (2004) highlight the importance of personal connections in making tacit knowledge accessible and call for fostering a culture of commitment and a safe, open atmosphere for knowledge sharing within organizations. Alzyoud et al. (2023) emphasize that ‘employee voice,’ which involves employees voicing issues and sharing experiences, is crucial for promoting tacit knowledge sharing within organizations. Gambarotto and Cammozzo (2010) stress the importance of effective governance, innovation, and the space to allow employees to build their identity within the organization through their voices. Based on the above, it is proposed that:

H1: Employee voice is positively associated with tacit knowledge sharing.

Tacit knowledge sharing and employee innovation

The sharing of tacit knowledge has been suggested as a means to enhance organizations’ innovative capabilities (Ganguly, Talukdar, & Chatterjee, 2019) and promote various types of innovation (Islam, Zahra, Rehman, & Jamil, 2022). Employees are a vital source of innovative ideas in the workplace and play an essential role in implementing innovative solutions. Employee innovation can be defined as the efforts made by employees to develop creative and innovative notions that can positively affect a hotel and its operations (Alzyoud, 2019). Several studies have confirmed the association between knowledge sharing and increased potential for employee innovation (e.g., Ahmad et al., 2022; Berraies, Hamza, & Chtioui, 2021; Montani & Staglianò, 2022). Regarding tacit knowledge, Seidler‐de Alwis et al. (2004) claim that tacit knowledge enhances the perception of ideas, thereby encouraging creativity and positively influencing business activities. Furthermore, Koskinen and Vanharanta (2002) stated that having a diverse range of knowledge and in-depth expertise is particularly crucial in resolving complex problems. Seidler‐de Alwis et al. (2004) argued that during the initial stages of the innovation process, particularly in the phase of ‘idea discovery and generation,’ the intangibility is high. Therefore, it is assumed that the significance of tacit knowledge sharing plays a more vital role in this phase. However, they added that success in innovation is often achieved when a crisis is overcome at any stage of the innovation process, either through accelerating the process or preventing interruptions. It is evident that effective management of tacit knowledge enables flexible problem solving, and sharing tacit knowledge is crucial for innovation success in all stages of the process. Furthermore, Kucharska (2021) has concluded that the innovation process is significantly accelerated by tacit knowledge, leading to successful innovation outcomes. Accordingly, it is proposed that:

H2: Tacit knowledge sharing is positively associated with employee innovation.

Employee voice, tacit knowledge sharing, and employee innovation

As previously mentioned, employees’ voices are perceived to activate the sharing of tacit knowledge (e.g., Alzyoud et al., 2023; Gambarotto & Cammozzo, 2010; Koskinen & Vanharanta, 2002; Seidler‐de Alwis et al., 2004; Yener & Arslan, 2017). On the other hand, tacit knowledge is perceived to promote employee innovation (e.g., Koskinen & Vanharanta, 2002; Seidler‐de Alwis et al., 2004).

According to Gambarotto and Cammozzo (2010), there is a relationship between three constructs: voice, knowledge, and innovation. They argue that voice is a strategy for transferring knowledge from the lower, individual level to the higher, organizational level. Therefore, when individuals engage in voice behavior, such as participation, they become more competent and qualified. Additionally, the organization benefits from learning and becoming more innovative. Seidler‐de Alwis et al. (2004) suggested, based on related literature, that a prerequisite for activating tacit knowledge in the process of innovation is to detect appropriate tacit knowledge within an organization through knowledge sharing. This involves critiquing ideas and perspectives while still respecting individuals. This requires a safe space for individuals to express their voices. Furthermore, Koskinen and Vanharanta (2002) argued that the innovation process requires not only the processing of objective information but also the presence of personal attitudes, opinions, and insights. Moreover, according to Gambarotto and Cammozzo (2010), for the voice to become an effective tool, it requires innovative governance and space to establish its identity within the organization.

In a similar context, Cox and Evans (2020) stated that in order to share knowledge, organizations should create a trusting environment and establish effective means for open communication where everyone has an equal voice. Seidler‐de Alwis et al. (2004) added that diverse perspectives foster creativity, including tacit knowledge, in a well-managed process. The intellectual conflict between these viewpoints produces energy that can be channeled into generating new ideas. Tacit knowledge becomes visible when it is shared and applied and can then be utilized in the innovation process. Tacit knowledge can be activated through the process of generating new scientific knowledge, also known as ‘learning to learn.’ Alzyoud et al. (2023) summarized this relationship as follows: when employees feel safe to express their opinions and believe that their voices are heard, they are more likely to share their experiences at the workplace, propose novel ideas, or suggest different ways to complete tasks. This can serve as a motivation for employees to contribute to the organization’s growth and development. This, in turn, is vital to inspire employees to participate in innovative acts, as knowledge is the basis for innovation. Gambarotto and Cammozzo (2010) emphasized the significance of employees’ voices in sharing tacit knowledge and suggested that vocal behavior enhances individuals’ competence and qualifications. Furthermore, utilizing voice enables organizations to learn and foster innovation. Therefore, employees’ voices are crucial for fostering innovation. However, without the proper knowledge to unleash their hidden potential, their voices would be of no use in this equation. Therefore, it is logical to propose that:

H3: Tacit knowledge sharing mediates the relationship between employee voice and employee innovation.

Employee innovation and service recovery performance

Given the significant role of human collaboration in the hotel sector, service failures are inevitable (Alzyoud & Abuzaid, 2023; Susskind, 2002). Furthermore, Lin (2010) stated that service failures and service recovery performances have been extensively studied in the hospitality sector due to the frequent interactions between customers and employees. Furthermore, after a failure has occurred, it is essential to implement a recovery strategy to minimize the negative impact on customers’ experiences.

Service recovery refers to ‘doing things very right the second time’ (Yadav & Dhar, 2021). Boshoff and Allen (2000), as well as Liao (2007), have described service recovery performance as the actions taken by the employees who are responsible for handling customer complaints directly, in order to restore customer satisfaction and loyalty following service failures. Furthermore, research suggests that an employee’s ability to recover from a service failure is more crucial than providing error-free service (Liao, 2007; Lin, 2010). This study adhered to the definition of service recovery performance provided by Boshoff and Allen (2000) and Liao (2007).

Innovation is essential for the success of hotels. Alzyoud et al. (2023) explain that the hotel industry heavily relies on the performance and competencies of its employees. Therefore, employees’ innovative ideas are vital to enhancing service recovery performance, which, in turn, can influence customers’ satisfaction and loyalty. In a similar context, Ahmad et al. (2022) have stated that the performance of service recovery is directly related to the competencies and behaviors of workers in identifying and resolving service failures. They explained that human innovation begins with recognizing complexities and developing ideas or remedies. Therefore, the workers’ ability to innovate can impact customer response to service recovery. Ahmad et al. (2022) claim that, in service recovery cases, if individuals are not allowed to utilize their full potential or they are unable to handle service recovery encounters effectively, it can result in customer dissatisfaction and can decrease overall performance. As such, the following is proposed:

H4: Employee innovation is positively associated with service recovery performance.

Tacit knowledge sharing, employee innovation and service recovery performance

As previously mentioned, several studies have confirmed the role of tacit knowledge in enhancing employees’ innovation (e.g., Alzyoud et al., 2023; Koskinen & Vanharanta, 2002). In this context, Seidler‐de Alwis et al. (2004) found that tacit knowledge has a crucial impact on driving and facilitating innovation. It has been claimed that innovation plays a positive role in enhancing service recovery performance (Ahmad et al., 2022; Alzyoud et al., 2023). Alzyoud et al. (2023) argue that there is a positive relationship between knowledge sharing, employee innovation, and service recovery performance. Specifically, they suggest that knowledge sharing can improve employees’ innovative behavior, which, in turn, can enhance service recovery performance. This could happen by providing innovative ideas and/or solutions. Therefore, hotel management must ensure staff members believe their opinions and efforts are wanted and respected. This will inspire them to express themselves, exchange knowledge, and develop inventive ideas that can accelerate recovery efforts (Alzyoud et al., 2023). Overall, tacit knowledge, which encompasses employees’ practical ‘know-how’, should enhance their ability to generate creative and novel ideas, suggestions, and solutions when a service failure occurs. This, in turn, can improve service recovery performance. Based on the above, we propose the following hypothesis:

H5: Employee innovation mediates the relationship between tacit knowledge sharing and service recovery performance.

Figure 1. The research model

RESEARCH METHODS

Participants

This is a quantitative study in nature, where an online self-administered questionnaire was developed to test the study model presented in Figure 1. The target population was employees in the hotel industry in Jordan. According to the Ministry of Tourism and Antiquities in Jordan (2023), there are 21,835 employees in the hotel sector in Jordan (2,364 of them are women) working in 607 different hotels in the country. A total of 214 valid responses were received, representing about 1% of the total population. Facebook groups for hotel employees in Jordan were targeted to reach the target population. The researchers visited those Facebook groups and randomly screened the members’ profiles and then contacted them explaining the aim of the study and asking them to participate in the study and share the questionnaire link with their friends and colleagues working in the hotel industry. Most of the people whom the researcher contacted were working in operations. The researchers provided a brief description of the study’s purpose and assured the responders’ anonymity to encourage them to provide honest answers. As the first question, a filtering question was used to ask employees if they are currently working in hotels or not to ensure that all the participants are working in hotels.

Instrument

An online self-administered survey was developed using Microsoft Forms to gather data from the target population. The questionnaire consists of 25 questions, seven of which were demographic questions. Moreover, the questionnaire consists of six sections: the first is an introduction to the study’s aims and an assessment of the anonymity of the participants. The second section included four questions about employee voice. The third section consisted of three questions related to tacit knowledge sharing. The fourth section involved six questions about employee innovation. The fifth section had five questions regarding service recovery performance. The last section consisted of seven questions about participants’ demographic information.

This study used a self-administered survey where the participants filled out the questionnaire at a single point in time. However, this may raise concerns regarding the Common Methods Bias (CMB) issue. As such, the remedies of Podsakoff, MacKenzie, and Podsakoff (2012) to mitigate CMB were considered in this study, such as using clear and straightforward questions and avoiding jargon and ambiguous questions, assuring the anonymity of the respondents and explaining the study aims to motivate them to provide honest responses; and informing the participants that their participation in the study is voluntary and they can withdraw at any time. Furthermore, the study performed the test of Harman’s single-factor to assess CMB, as recommended by Podsakoff, MacKenzie, Lee, and Podsakoff (2003). The outputs revealed that the measurement items accounted for 39.12% of the variance, which is less than the cut-off value of 50% that is proposed by Podsakoff et al. (2003). This indicates that CMB is not a factor of concern in this research.

Measures

The measurement items were adopted from different sources, and all of them were originally written in English. As English is an essential language in the hotel sector, the questionnaire items were written in English, and a translation for Arabic was provided underneath each question, in case the respondent had doubts regarding the meaning of the question. The translation was written by a bilingual academic staff member and reviewed by another two academic staff. All measurement items were constructed on a 5-point Likert scale with responses anchored from 1 = strongly disagree to 5 = strongly agree.

Employee voice was measured using four items that were adopted from Van Dyne and LePine (1998). These items were found valid and reliable in past studies in the hospitality industry, such as in the work of Detert and Burris (2007). Sample items included “In this hotel, I can speak up with ideas for new projects or changes in procedures” and “In this hotel, I can communicate my opinions about work issues to others even if my opinions are different and others disagree with me”. Cronbach alpha for this measure was 0.86.

Tacit knowledge was measured through three items from Bock, Zmud, Kim, and Lee (2005). Sample items are “I share my experience or know-how from work with other hotel members more frequently” and “I share my expertise from my education or training with other hotel members in a more effective way.” Alpha reliability for this measure was 0.86.

Employee innovation was measured through a 6-item scale that was adopted from Scott and Bruce (1994). This scale was found to be valid and reliable in past studies in the hotel industry (e.g., Alzyoud, 2019). Samples of the scale items included “I generate creative ideas at work” and “I promote and champion ideas to others.” Alpha reliability for this measure was 0.83.

Service recovery performance was measured through a 5-item scale that was developed by Boshoff and Allen (2000). Examples of the scale items were “Resolving a complaint for a customer is a great thrill for me” and “Considering all the things I do, I handle dissatisfied customers very well.” The alpha reliability for this measure was 0.84.

Data analysis

PLS-SEM (Partial Least Squares Structural Equation Modeling) was employed in this research to analyze the data using Smart PLS 3 software due to its sophisticated estimate and popularity in the social sciences (Harb, Khliefat, Alazaizeh, & Eyoun, 2023; Rasoolimanesh & Ali, 2018). When employing the structural model, the PLS-SEM is a powerful tool for topic analysis to specify and analyze the variables (Janib, Rasdi, & Zaremohzzabieh, 2022). Janib et al. (2022) assert that data analysis can be effectively conducted using the PLS-SEM approach, which involves utilizing the structural model to define and analyze variables. The study examined the data in two steps, as advised by the PLS-SEM literature (Siyal, Ding, & Siyal, 2019). As indicated in Table (2), the initial PLS-SEM phase of the approach began with an examination of the measurement model to examine the inter-item reliability, internal consistency, and convergent validity of the scale measurements. The second phase assesses the structural model to examine research hypotheses (Schuberth, Rademaker, & Henseler, 2023).

RESULTS

The online survey garnered a total of 214 responses in the period from August to October 2022. Table 1 shows that about 78.5% of the respondents were males, whereas only 21.5% were females. Around 50% of the respondents were 25 years old and below. About 61% hold a bachelor’s degree, and 64% of the respondents have less than 5 years of experience. The majority of the respondents work in five-star hotels (60%). Furthermore, half of the respondents (50%) were employees, and the rest were from supervisory and managerial positions. Finally, just over 60% of the participants were from the front office and food and beverage departments.

Table 1. Profile of respondents (N = 214)

Characteristics	Frequency (n)	Percentage (%)
Characteristics	Frequency (n)	Percentage (%)
Gender Male Female	168 46	78.5% 21.5%
Age (Year) 25 and below 26-30 31-35 36-40 41 and above	108 44 23 15 24	50.5% 20.5% 11% 7% 11%
Education Level High school and below Diploma Bachelor Masters PhD	35 40 131 5 3	16.5% 19% 61% 2% 1.5%
Hotel Stars 5-Star 4-Star 3, 2 and 1-star Other	129 30 38 17	60% 14% 18% 8%
Experience 1 year and less More than 1 year to less than 5 years 5 years to 10 years 11 years and more	66 71 37 40	31% 33% 17% 19%
Position Employee Supervisor Assistant Manager Manager Other	107 37 20 42 8	50% 17% 9% 20% 4%
Department Front Office Housekeeping Food and Beverage Sales and Marketing Human resources Finance and accounting department Other departments	63 14 71 15 10 11 30	29.5% 6.5% 33% 7% 5% 5% 14%

Evaluation of measurement model

To determine the convergent validity of the measurement model, the following have been examined by the researchers: (1) the composite reliability (CR), which should exceed 0.70 as recommended by Chin (1998); (2) the average variance extracted (AVE) should be more than 0.50 as stated by Fornell and Larcker (1981); and (3) the item loadings, should be larger than 0.70 as mentioned by Fornell and Larcker (1981) and Chin (1998). Table (2) illustrates the mean, standard deviation, composite reliability, extracted average variance, and item loading of the research model’s construct measures. Table 2 shows that all convergent validity criteria were met, the composite reliability varied from 0.83 to 0.86, and the AVEs ranged from 0.55 to 0.78. All of the item loadings had maturities greater than 0.7.

Table 2. Mean scores and the reliability statistics of the measurement model

Indicators and factors	Mean (SD)	CR	AVE	Loadings
Indicators and factors	Mean (SD)	CR	AVE	Loadings
F1: Employee Innovation	4.01 (0.81)	0.88	0.55
EInn1	4.00 (0.86)			0.753
EInn2	3.99 (0.79)			0.788
EInn3	3.97 (0.79)			0.767
EInn4	3.85 (0.89)			0.717
EInn5	3.95 (0.81)			0.801
EInn6	4.27 (0.74)			0.710
F2: Employee Voice	4.02 (0.86)	0.90	0.70
EV1	4.07 (0.86)			0.824
EV2	4.06 (0.82)			0.858
EV3	3.81 (0.95)			0.793
EV4	4.14 (0.81)			0.865
F3: Service Recovery	4.37 (0.68)	0.89	0.62
SR1	4.41 (0.60)			0.838
SR2	4.35 (0.69)			0.722
SR3	4.44 (0.67)			0.764
SR4	4.23 (0.78)			0.774
SR5	4.42 (0.66)			0.830
F4: Tacit Knowledge	4.42 (0.69)	0.91	0.78
TK1	4.31 (0.71)			0.892
TK2	4.49 (0.67)			0.845
TK3	4.46 (0.68)			0.910

The criteria proposed by Gefen and Straub (2005) for measuring discriminant validity were used in this study, and to meet discriminant validity in this criteria, the square root of the average variance extracted (AVE) for a construct should exceed its correlation with other constructs in the model. Table (3) shows the square root of the AVE for each construct, with the AVE being compared to the highest variance that each construct has with the other constructs in the model. The results highlighted low correlations between the measure of interest and the measures of other dimensions.

Table 3. Fornell-Larcker criterion

Factor	Einn	EV	SR	TK
EInn	0.739
EV	0.650	0.836
SR	0.586	0.605	0.787
TK	0.436	0.361	0.580	0.883

The discriminant validity was further evaluated using the Heterotrait-Monotrait (HTMT) criteria. HTMT is defined as the average item correlations across constructs compared to the average correlations among items measuring the same construct (Hair, Sarstedt, & Ringle, 2019). Table 4 represents the findings of the HTMT. The results show that all values in Table 4 are less than 0.85, indicating no discriminant validity issues based on the HTMT criteria (Henseler, Ringle, & Sarstedt, 2015).

Table 4. HTMT results

Factor	Einn	EV	SR
EInn
EV	0.763
SR	0.693	0.701
TK	0.499	0.410	0.679

These results show that the study measures have strong convergent and discriminant validity. In conclusion, the measurement model findings are adequate, indicating that the structural model assessment is acceptable to proceed. The discriminant validity was also evaluated using the cross-loading method, and this indicates that each item’s outer loading on the construct with which it is related should be greater than the item’s loading on other constructs (Chin, 1998). Table 5 represents the findings of cross-loadings. The results show that the outer loading of each item on its associated construct is greater than the loading of the item on other constructs (Chin, 1998).

Table 5. Cross loadings

	EInn	EV	SR	TK
	EInn	EV	SR	TK
EInn1	0.753	0.491	0.456	0.330
EInn2	0.788	0.407	0.396	0.317
EInn3	0.767	0.417	0.439	0.334
EInn4	0.617	0.376	0.378	0.216
EInn5	0.801	0.520	0.459	0.322
EInn6	0.690	0.360	0.455	0.387
EV1	0.408	0.824	0.476	0.274
EV2	0.402	0.858	0.538	0.353
EV3	0.479	0.793	0.472	0.252
EV4	0.567	0.865	0.526	0.312
SR1	0.533	0.458	0.838	0.461
SR2	0.418	0.362	0.722	0.389
SR3	0.437	0.409	0.764	0.477
SR4	0.413	0.477	0.774	0.429
SR5	0.489	0.449	0.830	0.432
TK1	0.432	0.340	0.413	0.892
TK2	0.288	0.266	0.473	0.845
TK3	0.411	0.339	0.544	0.910

To evaluate multicollinearity, the variance inflation factor (VIF) of each indicator should be less than 5 and above 0.20 (Hair, Ringle, & Sarstedt, 2011). Table 6 represents the findings of VIF. The results show that all VIF values are less than 5 and above 0.20.

Table 6. VIF values

Item	VIF
EInn1	1.761
EInn2	2.269
EInn3	2.043
EInn4	1.380
EInn5	2.022
EInn6	1.406
EV1	1.949
EV2	1.980
EV3	1.833
EV4	2.230
SR1	2.036
SR2	1.520
SR3	1.677
SR4	1.805
SR5	2.083
TK1	2.090
TK2	2.082
TK3	2.480

Structural model results

As indicated in Figure 2, the study model was evaluated through testing hypotheses, which include path coefficient estimation, the variance explained (R2 value), and statistical significance. The factor loadings vary from 0.707 to 0.948, indicating that the constructs are well formed.

Note: EV=Employee voice; TK=Tacit knowledge sharing; EInn=Employee innovation; SR=Service recovery performance.

Figure 2. The final structural model with standardized parameter estimates

The results of the hypothesized structural model are presented in Table 7, displaying various measures such as estimated path coefficients, R2, CI, adjusted bias CI, F square, t-values, and p-value. Based on the model performance statistics, the proposed model has a good fit for the data. Bootstrapping was employed to assess the significance of each path. The model accounts for 13% of the variance in employee tacit knowledge, 20% of the variance in employee innovation, and 35% of the variance in service recovery. All F-Square values are above 0.02, which indicates that the predictor variable has a substantial influence (Cohen, 1988). Furthermore, confidence intervals that do not include a zero suggest statistical significance (Hair & Alamer, 2022), which are illustrated in Table 7.

Employee voice and tacit knowledge sharing

Hypothesis 1 proposes that employee voice is positively associated with tacit knowledge sharing. The path coefficient was 0.361. This supports the first hypothesis that employees’ free expression of their voice, which embraces their experience, perceptions, and ideas, is a useful way to express and share their tacit knowledge.

Tacit knowledge sharing and employee innovation

Hypothesis 2 proposes that tacit knowledge sharing is positively associated with employee innovation. The path coefficient was 0.436. This provides support for the second hypothesis, indicating that when employees are encouraged to share tacit knowledge, this can enhance employees’ innovation capabilities.

Employee voice, tacit knowledge sharing, and employee innovation

Hypothesis 3 proposes that tacit knowledge sharing mediates the relationship between employee voice and employee innovation. The result revealed that tacit knowledge partially mediates the relationship between employee voice and innovation with a path coefficient of 0.256. This means that when employees are free to express what they know, their prior experiences, and perceptions, it will likely improve the innovative process by bringing fresh viewpoints, original ideas, new techniques, and divergent approaches to handling and solving problems. The fact that employees’ tacit knowledge partially mediates this relationship suggests that other types of knowledge could also play a role.

Employee innovation and service recovery performance

According to Hypothesis 4, it is proposed that employee innovation is positively associated with service recovery performance. The path coefficient was 0.586. This provides support for the fourth hypothesis. Thus, a more effective response to errors and improved means of resolving customers’ failure experiences would result from employees’ capacity to offer and implement unique ideas as well as new problem-solving techniques, which would improve service recovery performance.

Tacit knowledge sharing, employee innovation, and service recovery performance

The mediation results have also revealed that employee innovation partially mediates the relationship between tacit knowledge and service recovery performance with a path coefficient of 0.158, providing partial support for Hypothesis 5. Thus, although tacit knowledge sharing was positively associated with innovation, and innovation was positively and directly associated with recovery performance, innovation partially mediates the relationship between the two variables, indicating that other factors could play such a role.

Table 7. Results of Partial Least Square-Structural Equation Modeling (PLS-SEM)

	Original Sample (O)	CI	CI Bias Corrected	F Square	T Statistics (|O/STDEV|)	P-Value
EV -> TK	0.361	0.361	0.013	0.150	5.463	0.000
TK ->EInn	0.436	0.436	0.008	0.235	8.035	0.000
EV -> TK ->EInn	0.158	0.158	0.011	-	3.585	0.000
EInn -> SR	0.586	0.586	0.007	0.524	13.533	0.000
TK ->EInn -> SR	0.256	0.256	0.009	-	5.849	0.000

Note: *->: relationship link between two constructs.

DISCUSSION

This research investigates the complex and interrelated relationships among employee voice, tacit knowledge sharing, employee innovation, and service recovery performance. Tacit knowledge represents an intangible dimension of human capital that is concealed within individuals’ minds. This kind of knowledge results from individuals’ accumulated experience, knowledge, and skills. However, this valuable untapped capital is often difficult to express directly in words, which, in turn, hinders its sharing. Useful knowledge cannot be fully utilized unless it is shared and disseminated effectively. Allowing employees to freely express their thoughts, experiences, perceptions, and ideas is a valuable means of sharing their tacit knowledge. This result is consistent with Gambarotto and Cammozzo’s (2010) recognition of the importance of employee voice in sharing and utilizing tacit knowledge.

Sharing tacit knowledge was found to have a positive association with employee innovation. This outcome is consistent with previous studies (e.g., Ahmad et al., 2022; Bari, Ghaffar, & Ahmad, 2020; Montani & Staglianò, 2022). The innovative capability of employees is rooted in their knowledge, expertise, and experience, even if this knowledge is only tacit and resides solely in their minds. In a similar context, Seidler‐de Alwis et al. (2004) explained that tacit knowledge enhances the perception of ideas, thereby stimulating creativity. Kucharska (2021) has concluded that tacit knowledge can significantly accelerate the innovation process, leading to successful innovation outcomes. The findings presented here are consistent with previous studies that suggest tacit knowledge sharing can foster employee innovation.

Furthermore, it has been found that sharing tacit knowledge partially mediates the relationship between employee voice and employee innovation. When employees are given the opportunity to share their knowledge, thoughts, past experiences, and perceptions about future demands or specific problems, it can enhance the innovation process. This allows for new perspectives, novel ideas, and innovative techniques to emerge, as well as divergent approaches to problem solving. This relationship is partially mediated by employees’ tacit knowledge, which is hidden in their minds. This suggests that other types of knowledge may also play a role in mediating this relationship. This result supports Alzyoud et al.’s (2023) theoretical proposition that tacit knowledge sharing mediates the influence of employee voice on employee innovation in the hotel industry.

The results also indicate that employee innovation is positively associated with service recovery performance. Employees’ capacity to introduce and implement innovative ideas and utilize new problem-solving techniques can lead to an effective response to mistakes and improved methods for resolving customers’ negative experiences, ultimately enhancing service recovery performance. This result confirms the claim made by Ahmad et al. (2022) that service recovery performance is directly related to the competencies and behaviors of the workers. Ahmad et al. (2022) argue that recognizing complexities and developing remedies for them begins with human innovation. They further argue that if individuals are constrained from using their potential skills or are unable to manage service recovery encounters, it can lead to customer disappointment and decrease overall performance. The results support the argument that employees’ innovative endeavors, such as proposing creative solutions or trying new work methods to satisfy customers, can accelerate service recovery efforts in hotels.

The findings from this work indicate that employee innovation partially mediates the association between tacit knowledge sharing and service recovery performance. This indicates that the competencies, hidden knowledge, and accumulated experience of employees from their practical proficiency can assist in improving the approach to dealing with complex service failures and increase the likelihood of successfully repairing any damages. Moreover, sharing tacit knowledge with colleagues can promote employee innovation, ultimately expediting their efforts to recover services. Although employee innovation was revealed to influence service recovery performance directly, it only partially contributes to the relationship between tacit knowledge and service recovery performance.

Table 8. Summary of the results

Hypotheses	Results
H1: Employee voice is positively associated with tacit knowledge sharing.	Supported
H2: Tacit knowledge sharing is positively associated with employee innovation.	Supported
H3: Tacit knowledge sharing mediates the relationship between employee voice and employee innovation.	Supported
H4: Employee innovation is positively associated with service recovery performance.	Supported
H5: Employee innovation mediates the relationship between tacit knowledge sharing and service recovery performance.	Supported

Table 8 presents a summary of the research hypotheses and indicates whether they were supported or not. It can be clearly seen that all the proposed hypotheses were confirmed. For instance, the study proposed a positive association between employee voice and tacit knowledge sharing, and this proposition was confirmed. In addition, it has been hypothesized that tacit knowledge sharing is positively related to employee innovation, and this hypothesis was supported. Moreover, tacit knowledge sharing was suggested to mediate the relationship between employee voice and employee innovation, and this claim was also confirmed. Employee innovation was proposed to affect service recovery performance positively; the findings supported this hypothesis. Finally, it has been proposed that employee innovation mediates the relationship between tacit knowledge sharing and service recovery performance, and the results confirmed this proposition.

Practical implications

This study shed light on how hotel management could accelerate service recovery efforts in their hotels by focusing on the vital role of employee voice, tacit knowledge sharing, and employee innovation, which contributes substantially to the practitioners in the hotel sector if this opportunity is to be exploited. The study’s findings suggest several practical implications for hoteliers:

1. Encouraging employee voice: Hoteliers should foster a supportive work climate that promotes knowledge sharing and learning. They can achieve this by organizing regular meetings or sessions where employees can express their thoughts, ideas, and concerns without fear of retribution. An open-door policy or an anonymous suggestion box can facilitate this. In addition, hoteliers should create a safe and supportive environment where employees feel comfortable sharing their opinions.
2. Setting clear expectations: Hoteliers must establish clear expectations for employees regarding the significance of their opinions and insights. Leaders should model the behavior they wish to see in their employees, such as actively seeking and valuing employee input. They should also offer feedback and recognition to employees who contribute their ideas and insights.
3. Rewarding and appreciating knowledge-sharing behaviors: Hoteliers can incentivize knowledge-sharing behaviors by rewarding and recognizing employees who contribute to the quantity and quality of innovation. They can accomplish this through bonuses, promotions, or other forms of recognition. Hoteliers can also provide opportunities for employees to showcase their ideas and insights through presentations, workshops, or other events.

Limitations and future research directions

This section discusses several limitations and directions for future research. First, this cross-sectional study eliminates the possibility of proposing cause-and-effect relationships between the study’s variables. Therefore, a longitudinal study is recommended to examine the causality amongst employee voice, tacit knowledge sharing, employee innovation, and service recovery performance. Second, a self-administered questionnaire was employed to gather the primary data, which may raise the issue of biased responses. For instance, participants may provide biased responses when they are asked about their voice, innovative acts, knowledge-sharing attitudes, or service recovery behaviors. However, the suggestions of Podsakoff et al. (2003) and Podsakoff et al. (2012) were followed to tackle this issue, such as using clear, simple, and unambiguous questions; avoiding jargon and double-barreled questions; ensuring the anonymity of the participants to motivate them to give honest responses; and other remedies that were discussed earlier in this article. Nevertheless, future studies are recommended to gather data from both employees and their supervisors to overcome potential biases. Finally, the data of this study was collected mainly from the hotel sector in Jordan, which may make the results of this study not transferable to other sectors because of the variances in the job-related characteristics of the respondents. Therefore, the conclusion of this study needs to be tested in other countries and in different sectors to evaluate whether it could be replicable.

CONCLUSION

This study sought to contribute to the growing research interest in service recovery performance in the hotel sector. As such, this study examined the relationships between employee voice, tacit knowledge sharing, employee innovation, and service recovery performance. Various findings were revealed by collecting 214 valid responses from different hotels in Jordan using an online survey. For example, employee voice was found to be positively associated with tacit knowledge sharing, and the latter was found to be positively related to employee innovation. Tacit knowledge sharing was found to be partially mediating the relationship between employee voice and employee innovation. Furthermore, employee innovation was shown to influence service recovery performance. Finally, employee innovation was revealed to partially mediate the relationship between tacit knowledge sharing and service recovery performance. To conclude, making employees feel safe to speak up at work (employee voice) can encourage the sharing of tacit knowledge amongst employees, which may promote their innovativeness, which, in turn, can enhance service recovery performance in hotels.

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Biographical notes

Sultan Alzyoud is Assistant Professor at the Department of Business Administration, School of Business, The Hashemite University, in Jordan. He obtained a Ph.D. in hotel management from Manchester Metropolitan University in the United Kingdom in 2019. He worked as head of the Department of Marketing at the School of Business from 2021 to 2023. Over the past five years, he won the best paper award at two international conferences. Dr. Alzyoud is a trainer in leadership and marketing. His research interests lie in employee innovation, entrepreneurship, psychological safety and leadership, mainly in the field of hospitality.

Waed Ensour is an Associate Professor in the Department of Business Administration at the Hashemite University in Jordan. She holds a Ph.D. in human resource management from the University of Hull, England. Currently, she is the Dean of the School of Business at The Hashemite University. Her research focuses on human resource development, women’s career development, and organizational behavior. 

Ayman Harb is an Associate Professor of hospitality and tourism management and the Dean of the Tourism and Hospitality School at the University of Jordan-Aqaba Branch. He is a sustainable tourism and hospitality expert specializing in human capital development, tourism and hospitality education and training, and a tourism and hospitality entrepreneurship consultant and trainer. Dr. Harb is a dynamic, self-starter with over 15 years of national and international experience in teaching and working in tourism and hospitality. His research interests lie in the areas of tourism, hospitality management, and entrepreneurship. He has collaborated actively with researchers in several other disciplines of the management field. He has published several scientific articles in well-known journals.

Authorship contribution statement

Sultan Alzyoud: Conceptualization, Data Curation, Methodology, Formal Analysis, Project Administration, Writing – Original Draft, Writing – Review & Editing, References and Citation. Waed Ensour: Conceptualization, Writing – Original Draft (Theoretical Background and Discussion Sections). Ayman Harb: Conceptualization, Writing – Original Draft (Introduction, Abstract, and Conclusion Section).

Conflicts of interest

The authors declare no conflict of interest.

Citation (APA Style)

Alzyoud, S., Ensour, W., & Harb, A. (2024). Linking employee voice to service recovery performance in the hotel sector: The mediating role of tacit knowledge sharing and employee innovation. Journal of Entrepreneurship, Management and Innovation, 20(3), 62-77. https://doi.org/10.7341/20242034

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Received 20 July 2023; Revised 25 October 2023, 16 November 2023; Accepted 20 November 2023.

This is an open access paper under the CC BY license (https://creativecommons.org/licenses/by/4.0/legalcode).