Introduction

The hotel sector is highly competitive due to customer expectations and their significant impact on the world’s economies (Law et al., 2021). In Ghana, the hospitality and tourism sector has become one of the economy’s most important foundations and significantly contributes to the nation’s gross domestic product (Aduhene & Osei-Assibey, 2021). Before the COVID-19 outbreak, the industry contributed USD 2967.1 million to the national GDP and generated approximately 693,000 employments in 2016 (World Travel & Council, 2017). Also, the tourism industry recorded an unprecedented flood of over 1 million international visitors due to the Year of Return, Ghana 2019 campaign, which pumped USD 1.9 billion into the domestic economy (International Labor Organization, 2020; Reality Check team, 2020).

Owing to these successes chopped in the sector, it is evident that some managers exhibit supportive behaviors, which has led to the well-being of the frontline employees (Kang et al., 2015). It is worth noting that frontline employees are critical in providing exceptional customer service, achieving customer happiness, and representing the company’s image (Peng et al., 2021). This study then explores how employees relate to supervisors who exhibit supportive behaviors to improve their engagement, which leads to exhibiting helping behaviors to coworkers. This line of theorization is imperative since it is quite significant to ascertain how employees emotionally relate and engage with such managers in an organization (Ampofo, 2021; Kang et al., 2015) in displaying helping behaviors as the sector has been described by studies to be ill-famed for poor wages, working conditions, and low implementation of HR practices (Amissah et al., 2016).

However, previous research, based on social exchange theory (SET) (Blau, 1964), implies that supportive supervisors have a positive impact on employees’ attitudes and behaviors (Kang et al., 2015). Rooney and Gottlieb ( 2007) described supportive supervisor behavior as psychological, physical, cognitive, and esteem assistance provided to employees. Such support is vital because frontline employees face unique challenges, such as inflexible frontline employee work hours and strict and irregular work schedules (Goh & Baum, 2021). Hence, supportive supervisor behavior could influence an employee’s engagement levels and proclivity to extra-role like OCBI.

Studies have focused on employees’ helping behaviors like organizational citizenship behavior (OCB) (Zhao & Guo, 2019). OCB towards the individual (OCBI) [Hereinafter employees’ helping behavior (EHB)] is regarded as a prosocial or discretionary helping behavior displayed by organizational members (Organ, 1988). The study concentrates on EHB as a criterion variable for the following reasons. First, EHB comprises behaviors that immediately benefit individuals (Zúñiga et al., 2022). Second, customers are served by multiple frontline employees in a typical hotel business, an integrated process that involves numerous interactions and assistance among employees (Ye et al., 2021). Last, supervisors’ supportive behaviors improve frontline employees’ loyalty, high-quality service delivery, and coworker support (Lyu et al., 2016; Ye et al., 2021). Therefore, EHB is noted as voluntary helping behavior among employees and team members, which varies depending on the behaviors of supervisors (Wong et al., 2021).

According to Kahn (1992), being mentally present while occupying and fulfilling an organizational role is what engagement connotes. Given that employee engagement requires beyond mere responsibility fulfillment, Soane et al. (2012) proposed three dimensions, namely: intellectual engagement, which presents the degree to which one is cognitively engaged in work, while social engagement connotes the degree to which one has socially linked to the workplace and shares core values with coworkers. Also, affective engagement describes the degree to which one feels a state of positive affect about one’s professional role. One of the positive states of hotel employees is high employee engagement (Sun & Yoon, 2022; Tsaur et al., 2019). Jung and Yoon ( 2016) opine that hotel employees who are highly engaged at work are happier and devote more time to their jobs. Researchers assert that managerial leadership is crucial in determining workers’ motivation and attitudes, like employee engagement (Singh et al., 2022; Vakira et al., 2022). Therefore, employee engagement is considered a conduit through which supportive behavior will influence EHB as studies have proven that supervisors high on supportive behavior greatly influence employee engagement (Suan & Nasurdin, 2016; Zhao & Guo, 2019), and employee engagement influences EHB (Sun & Yoon, 2022).

A situation encountered and deemed useful in an organization will elicit positive or useful responses, whereas the opposite case will produce a negative attitude or behavior (Koçak & Kerse, 2022). Organizational obstruction is an employee’s perception that their organization precludes them from achieving goals. Employees who perceive the organization as a source of obstruction from the standpoint of social exchange feel obligated to retaliate through attitudes and behaviors. Research has found perceived organizational obstruction to reduce employee loyalty (Lee, 2016) and citizenship behavior (Mackey et al., 2018). Lee ( 2016) assert that loyal employees are highly engaged and committed to organizations. Given this, we contend that organizational policies instituted by an organization showcase the supervisor’s supportiveness since employees view supervisors as leaders. This perception could diminish/increase the positive net effect of employee engagement on EHB. This assertion is imperative since the perceived organizational obstruction concept is perceptive; even if there is no real obstruction, it can be perceived by the employees.

Based on the SET, reciprocity norm (Gouldner, 1960), and perceived organizational support (POS) (Eisenberger & Stinglhamber, 2011), this study contributes to the supportive supervisor behavior and the EHB literature for at least three reasons. First, studies that endeavored supportive supervisor behaviors linkage to OCB tested supportive manager behavior (Kaur & Randhawa, 2021) as a direct causal effect on OCB. However, rarely has studies tested a supervisor’s supportive behaviors’ influence on EHB. Therefore, the study addresses the impact of a supervisor with supportive behavior on frontline employees’ helping behaviors as that benefits coworkers. Also, managers’ support towards employees in Ghanaian hospitality has only gained lip service. Our study then contends that supervisors have been supportive and positively impacted employees’ helping behavior (Wang et al., 2022) irrespective of the damaging impacts of abusive supervision reported in the literature (Al-Hawari et al., 2020; Ampofo et al., 2022). Hence, we sought to provide practical recommendations on how supportive behaviors debunk destructive behaviors (Gonzalez-Morales et al., 2018).

Second, regarding employee engagement mediating the effects of supportive supervisor behavior on employees helping behaviors in Ghana’s hospitality and tourism industry has not gained enough investigations. Therefore, it is critical to assess employee engagement as a mechanism that could encourage/discourage employees’ loyalty (Lee, 2016) and citizenship behavior (Mackey et al., 2021); and empirically predict EHB (Saks, 2019; Soane et al., 2012) taking the supervisor’s behavior into perspective. Moreover, it is imperative to note that high employee engagement demonstrates positive states of hotel employees (Sun & Yoon, 2022; Tsaur et al., 2019). Therefore, we opine that supportive behavior will determine the engagement disposition an employee is likely to exhibit; thus, an employee is to be intellectually, socially, and affectively engaged, as proposed by Soane et al. (2012). Therefore, how a supervisor unleashes supportive behaviors could influence employees’ outcome variations caused by the employees’ social connectedness, knowledge capability, and enthusiasm in displaying helping behaviors.

Third, our study extends the hospitality industry in Ghana literature by assessing the boundary effect of organizational obstruction. Amissah et al. (2016) and Ampofo (2021) asserted that the hospitality industry faces low take-up HR practices indicating that employees face unfair workplace policies. Given this, it is imperative to encapsulate an absolute theoretical picture of the employee–organizational policies interaction to assess how unfriendly policies diminish employee engagement and helping behaviors. This notion is important since supervisors are policy framers, and their behavior is vital in such situations. Hence, our paper examines whether employee engagement mediates the effects of supportive supervisor behaviors on EHB using data obtained from frontline employees in Ghana’s hospitality industry.

Theoretical foundation and hypotheses

SET, the reciprocity norm, and POS took center stage in accounting for the relationships in this study. SET and reciprocity norm are the most common exchange rule between parties in an organization (Blau, 1964; Gouldner, 1960). SET explains leadership behavior and associated actions. According to SET (Blau, 1964), responsibilities are established through interactions between mutually interdependent individuals. Gouldner (1960) believes that individuals must assist those who have previously helped them and as such, individuals should not do anything that might harm those who have previously helped them. Saks (2021) opines that individuals are exceedingly willing to reciprocate their engagement for resources offered by managers. Accordingly, employees feel bound to respond with a commensurate level of engagement if a supervisor offers these employees economic and socioemotional support. Thus, employees tend to resort to negative behaviors when saddled with unsupportive policies thereby rippling negative aspects of SET (Gibney et al., 2009).

Regarding the norm of reciprocity, subordinates who receive support from supervisors are likely to “payback” by having tremendous positive views toward the managers (Jose & Mampilly, 2015). This assertion aligns with Robinson et al’s. (2004) view of employee-supervisor engagement as a two-way interaction. Besides, Huang et al. (2016) agree that employee engagement is the surest way to reciprocate support. Hence, employees may exhibit intellectual, social, and affective engagement in response to the support provided by supervisors. Therefore, we claim that intellectual, social, and affective engagements are reactions that an employee is keen to exhibit to fulfill an individual’s work roles, depending on the supervisor’s economic and socioemotional support (Soane et al., 2012).

It is worth noting that the social exchange theory dominates research on the employee–organizational interaction (Gibney et al., 2009). However, POS is an attitudinal process that people use to infer the commitment of others to social relationships (Eisenberger et al., 2001). POS is deemed reciprocation influenced by various aspects of an employee’s treatment by the organization and, in turn, affects the employee’s interpretation of organizational motives underlying that treatment, hence, used to espouse the concept of organizational obstruction. Given this assertion, perceived organizational obstruction will undoubtedly lead to negative behaviors by employees as a way of reciprocation. Owing to this contention, the research model demonstrates the relationships among the constructs under investigation with SET as the fundamental theoretical underpin in Fig. 1.

Fig. 1
figure 1

Conceptual framework of the study

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Supportive supervisor behavior and EHB

Supervisory support generally improves EHB in the hospitality industry (Akram et al., 2018; Dai et al., 2018). Besides, supportive manager behavior is acknowledged as positively impacting employees’ attitudes in the workplace (Kaur & Randhawa, 2020). Relying on the reciprocity norm, workers reciprocate the support supervisors give them by displaying helping behaviors (Saks, 2021). Supportive supervisor behavior is expressed as the degree to which employees observe that their superiors support, encourage, and care for them (Suan & Nasurdin, 2016). Dutton et al., 1997) opine that the survival of a business entity is heavily reliant on supervisors’ creativity, innovativeness, and intelligence. Therefore, a supervisor should support subordinates by providing emotional, instrumental, informational, and esteem support (Quansah et al., 2022). This act places supervisors in a position to engage in social exchanges with their workers. This exchange between the supervisors and the employees can facilitate improved performance or retrogress performance. Indeed, Teoh et al. (2016) posited that employee and supervisor support are two participants in the exchange relationship. Drawing from the SET, workers who engage in roles other than their assigned duties do so with expectations in mind (Cropanzano & Mitchell, 2005). Supervisors’ failure to meet these expectations demotivates employees’ effectiveness in demonstrating helping behaviors (Reader et al., 2017) and affirms organizational support theory’s system of emerging trust in a relationship. In light of this knowledge, previous investigations have established that enhanced supervisory support inspires employees to display EHB and is positively related (Arshad et al., 2021; Yadav & Rangnekar, 2015). Hence, a supervisor exhibiting supportive behaviors is likely to promote employees’ high participation in their work. Therefore, we hypothesize that:

H1: Supportive supervisor behavior will have a significant positive influence on EHB.

Supportive supervisor behavior and employee engagement

Based on SET, we contend that supportive behavior improves the quality of social contact between frontline employees and supervisors (Peng et al., 2014). Literature postulate that supportive supervisor behavior has a significant and positive impact on subordinates’ motivation and attitudes at work, such as employee engagement (Kaur & Randhawa, 2020). Supervisor behaviors that instill support, confidence, constancy, resiliency, and competency, according to Kahn (1990), allow employees to express and engage their actual selves without fear of harming their self-image, status, or career. Moreover, supportive supervisor behavior is a critical job resource that will positively impact frontline employees’ intellectual, social, and affective engagement. There is growing acknowledgment that social engagement is a requirement for employees to work collectively given the right support from supervisors (Jackson et al., 2006). Relationships with supervisors can be antecedents of social engagement (Saks, 2006). Regarding the study by Saks (2019), the perceived positive link between supportive supervisor behavior and employee engagement is addressed. Saks (2019) posited that several antecedents, such as job characteristics, perceived organizational support, and supervisory support, were found to positively affect employee engagement in the model proposed by Saks (2006) study. Fast forward, Saks (2019) study evaluated Saks (2006) model against the existing research that used different engagement measures to assess the extent to which the antecedents of his model predict employee engagement, employee engagement influencing the consequences (OCBI, job satisfaction, and turnover intentions) in his model, and the employee engagement mediating relationships between antecedents and consequences. Findings from Saks (2019) study confirmed the validity and generalization of employee engagement model and affirming that supervisory support predicts employee engagement. In addition, Contreras et al. (2020) observed that frontline employees are highly engaged in intellectual engagement, social engagement, and affective engagement when receiving support from supervisors. Hence, we hypothesize that:

H2a: Supportive supervisor behavior will have a significant positive influence on intellectual engagement.

H2b: Supportive supervisor behavior will have a significant positive influence on social engagement.

H2c: Supportive supervisor behavior will have a significant positive influence on affective engagement.

Employee engagement and EHB

The positive association between employee engagement and EHB is receiving more attention in extant literature (Luu, 2017; Saks, 2019; Sun & Yoon, 2022). Research proves that one of the possible outcomes of employee engagement is EHB since the engaged state involves positive emotions and fosters beneficial behaviors (Gupta et al., 2021). Therefore, intellectual engagement, social engagement, and affective engagement show how individuals display focus and are concerned with discharging tasks. Kahn (1992) postulates that engaged employees are inclined to institute EHB since participation is part of a positive cycle of rewarding results. Regarding SET, the association between intellectual, social, and affective engagement, and EHB indicates that engaged frontline employees demonstrate positive behaviors toward coworkers; thus, others’ behaviors are more likely to be recognized and reciprocated (Saks, 2006). Research indicates that engaged employees are highly productive and demonstrate greater EHB (Chernyak-Hai & Tziner, 2014; Gupta et al., 2021). Hence, we propose that:

H3a: Intellectual engagement will have a significant positive influence on EHB.

H3b: Social engagement will have a significant positive influence on EHB.

H3c: Affective engagement will have a significant positive influence on EHB.

Mediating role of employee engagement

Work intensity may hinder frontline employees’ engagement demands enforced by supervisors who engage in destructive (Bailey et al., 2017) or disparaging behaviors (Tepper, 2007). Given this, abused frontline employees may exercise a penchant for deviant behavior, such as subversion (Carlson et al., 2011; Xu et al., 2012). Contrary to these assumptions, frontline employees enjoying supervisors’ supportive behavior respond creatively to workplace mistreatment, leading to high employee engagement (Idike et al., 2020; Oh & Farh, 2017). Hence, vastly supported employees become highly engaged and experience positive emotions (Li et al., 2021), and typifies high in-role and extra-role performance (Christian et al., 2011). Employees intellectually engaged possess a high level of knowledge engrossed in work and represent the cognitive dimension of engagement; it concerns the relationship between the engaged state and cognitive activity geared toward completing a work function (Crawford et al., 2010). Also, socially engaged employees feel connected to others, which could be coworkers or anyone with whom the work function interacts, demonstrating the importance of employees working together (Jackson et al., 2006). Moreover, affective engagement presents the extent to which an individual experiences a state of positive affect in relation to an individual’s work responsibility; by exploring employees’ enthusiastic and energetic levels in terms of physical engagement (Kim et al., 2022). Supportive supervisor behavior facilitates employees’ performance to be valuable and essential; and establishes identity to work itself, which is related to employee engagement (Ding & Yu, 2021; Grant, 2012), thereby promoting a sense of EHB. Employee engagement is an individual-level construct that leads to employee performance; however, it must first impact individual-level outcomes (Saks, 2006). Along these lines, it is imperative to expect employee engagement to be related to individuals’ attitudes, intentions, and behaviors. According to SET, supervisors’ support is considered resources from the organization, and employees respond with greater levels of engagement (Cropanzano & Mitchell, 2005). Therefore, employees feel obliged to bring themselves more deeply into exercising helping behaviors as repayment for the resources they receive from their organization. Hence, supportive supervisor support impact helping behaviors of employee through employee engagement (Saks, 2019). Also, frontline employees parade good behaviors toward coworkers due to supportive supervisor behavior through an increased frontline employees engagement (Kaur & Randhawa, 2020). Hence, we propose the following:

H4a: Intellectual engagement will mediate the relationship between supportive supervisor behavior and EHB.

H4b: Social engagement will mediate the relationship between supportive supervisor behavior and EHB.

H4c: Affective engagement will mediate the relationship between supportive supervisor behavior and EHB.

Moderating role of perceived organizational obstruction

Perceived organizational obstruction represents employees’ perception that the organization impedes, impairs, or hinders their ability to achieve objectives, harming their well-being (Gibney et al., 2011). With high perceived organizational obstruction, one could envisage that SET could decline, forming the negative aspect of SET. The negativity of SET opines that individuals involved in negative behaviors reciprocate undesirable organizational behavior (Gibney et al., 2009). Obstruction is perceived when frontline employees believe that the unfavorable supervisor’s policies, which are sometimes characterized by their behaviors, render work challenging regarding goal attainment (Guillaume et al., 2021). Likewise, POS argues that organizational policies susceptible to unsupportive behaviors have pernicious consequences that deplete employees’ enthusiastic ability to attain goals (Eisenberger & Stinglhamber, 2011). Therefore, perceived organizational obstruction is addressed in this study as a negative attribution to investigate the consequences of negative organizational treatment perception drawing on POS. Frontline employees are usually oblivious to the threats they can be exposed to due to their relations at the workplace. Also, frontline employees’ impressions of how they are treated at work are evinced by perceived organizational obstruction. Perceived organizational obstruction is considered a negative outcome that cannot be eliminated but can be minimized. Also, research has found perceived organizational obstruction to reduce employee loyalty and EHB (Lee, 2016; Mackey et al., 2018). Given this, we believe engaged employees are loyal to organizations and that the emergence of perceived organizational obstruction dampens the positive link between employee engagement and EHB. Owing to these suppositions, we affirm that perceived organizational obstruction impedes frontline employees’ growth and well-being, as asserted by studies (Akhtar et al., 2020; Gibney et al., 2011), which may negatively impact the facets of employee engagement – EHB relationships. Thus, we propose that:

H5a: Perceived organizational obstruction moderates the association between intellectual engagement and EHB such that at high perceived organizational obstruction, intellectual engagement decreases, hence, low EHB.

H5b: Perceived organizational obstruction moderates the association between social engagement and EHB such that at high perceived organizational obstruction, social engagement decreases, hence, low EHB.

H5c: Perceived organizational obstruction moderates the association between affective engagement and EHB such that at high perceived organizational obstruction, affective engagement decreases, hence, low EHB.

Materials and methods

Participants and procedure

Participants included full-time frontline employees (e.g., front‒desk agents, bartenders, waiters or waitresses, and bell attendants). Data were collected using a questionnaire survey approach after authorization from HR managers of 3 five-star, 7 four-star, and 8 three-star hotels in four cities in Ghana, namely; Accra, Kumasi, Takoradi, and Sunyani. These cities were chosen because they are regional capitals in productive business regions in Ghana, where most four-star, five-star, and three-star hotels are situated. Senbeto and Hon (2021) recommendation on convenience sampling was adopted in selecting the companies and the employees, considering the willingness and accessibility of companies and respondents since some companies and the respondents were unwilling to partake due to the strict COVID-19 pandemic measures. A selection criterion was designed, requiring that (a) one was a full-time employee of the company; (b) one had served in the company for a minimum of six months to guarantee each participant has had considerable experience with the leadership of the company; and (c) one had at least basic education or the capability to read and write in the English language, which was used to communicate questionnaire items. We initially selected and interviewed 30 employees per the criteria to ascertain their knowledge about the used variables and answer the questions as a pre-test study. This act was to verify the suitability of the scale’s application in a developing country like Ghana, as proposed by Yen and Niehoff (2004), and to determine the reliability and validity, readability, and understandability of the scales’ items. Also, the outcome helped make some amendments to the survey’s layout and formatting (e.g., the definition of the survey’s specific goals, topics, and concepts; determination of survey content; length; response categories and consistency; and apprehension minimization) (Dillman, 2000). These employees were not included in the final study. The final questionnaire survey included a cover letter outlining the study’s goal, guaranteeing participants’ confidentiality, and confirming discretionary participation as the participants signed a consent form. Approximately the survey could last for twenty-five minutes (25 min). Also, a prepaid envelope was attached to the questionnaires to facilitate the participants to mail it when completed. Included in the prepaid envelope are branded pen and pocket-size 2022 diary as an incentive and a thank you for their participation, irrespective of whether a participant would return the questionnaire.

We adopted a two-wave data collection procedure with time spaced six months apart following the suggestion of Podsakoff et al. (2003) as a technique to eliminate common method variance. Participants were educated to resort to codes (i.e., the last three digits of their national identity card number) to maintain anonymity and facilitate tracking participants’ returns and responses on the questionnaires. Participants were asked to use the same code for the two-wave questionnaires. Volunteers were trained to facilitate the process. Managers were instrumental in the process; however, they were excluded from the study due to their role as co-supervisors in the questionnaire administration and response.

Data collection was conducted from July 2021 to March 2022. During the first wave of data gathering, the questionnaires were administered to 655 participants to collect personal information (gender, age, and length of service) and supportive manager behavior, which yielded 601 responses. Six months later, participants’ views on employee engagement, EHB, and perceived organizational obstruction were measured in wave two survey (the rationale for the time lag was to satisfy the selection criterion (b) aforementioned), with the same participants in wave one. 557 responses were received. The codes were then verified by comparing each respondent to the questionnaires to identify the responses bearing the same respondent’s code. We then checked the personal information and matched the questionnaires from separate waves if two of them had duplicate identification. This procedure resulted in 511 two-set of responded questionnaires. However, we omitted 42 invalid replies (owing to more than 5% of the data lost) because some data were lost, remaining 469 valid responses.

Out of the total responses, 268 (57.14%) were male, while 201 (42.86%) were female. The study also revealed that respondents’ age ranged from 18 to 29 (52.78), 30–40 (31.66), and 41–50 (15.56). Regarding the statistics on respondents’ length of service, 64 (13.65%) had served for 12 years or more, 91 (19.40%) had served for 9 to 12 years, 120 (25.59%) had served for 4 to 8 years, and 194 (44.36%) had served for 3 years or shorter.

Measures

To operationalize the study constructs, we employed well-established scales. The essential items were taken from actual studies available in the literature.

Supportive supervisor behavior

Supportive manager behavior was measured with a nine-item from Inventory of Supportive Managerial Behaviours scale developed by Rooney and Gottlieb (2007). A sample item includes “when I am experiencing difficulties, my manager sympathizes with me.” Cronbach Alpha (α) value was 0.945. Previous studies such as Teoh et al. (2016) and Quansah et al. (2022) used and validated the scale’s reliability by recording α values of 0.94 and 0.975, respectively. Response options ranged from 1 (strongly disagree) to 5 (strongly agree).

Employee engagement

This study explains the ISA engagement scale as a psychological mechanism of engagement framework whose development is rooted in work-role focus, activation, and positive affect of employees. The ISA engagement scale comprises intellectual, social, and affective engagement, which measures the extent employees are highly/less psychologically present, related, integrated and focused on their role performances (Rich et al., 2010). It is noted that self-report perceptual measures are considered more suitable than supervisor or coworker ratings for work engagement (Agarwal, 2014). Hence, we assessed employee engagement with 9 items from the ISA Engagement Scale developed by Soane et al. (2012). The scale had 3 items, each measuring intellectual, social, and affective. Example of intellectual engagement includes “I pay a lot of attention to my work.” A sample item for social engagement includes “I share the same work attitudes as my colleagues.” The affective engagement scale includes sample items like “I feel positive about my work.” The α value for intellectual engagement was (α = 0.868), social engagement (α = 0.905), and affective engagement (α = 0.892) were high, indicating good internal consistency. The combined α was 0.957. The ISA engagement scale has been used for its reliability by studies such as Mañas-Rodríguez et al. (2016), who recorded the following α index: 0.92 for intellectual engagement; 0.93 for social engagement; 0.91 for affective engagement; and 0.91 for the overall construct and Schmiedehaus et al. (2023) who measured the scale unidimensional and had 0.86 as α value. Response options ranged from 1 (never) to 7 (always).

EHB

We adopted the OCBI 8-item scale proposed by Lee and Allen (2002). A sample item includes “I willingly give my time to help others who have work-related problems.” The α value was 0.895. Several studies have adopted this scale and verified its reliability. For instance, Adil et al. (2021) and Lilly and Virick (2013) studies recorded acceptable α values of 0.83 and 0.89, respectively. Responses to the items ranged from 1 (never) to 7 (always).

Perceived organizational obstruction

This was measured with a five-item scale developed by Gibney et al. (2009). A sample item includes “My organization is a detriment to my well-being,” with α value of 0.918. The scale’s reliability has been verified by other studies like Guillaume et al. (2021), who had an acceptable α value of 0.95. Respondents’ answers ranged from 1 = strongly disagree to 5 = strongly agree. The construct reliabilities (CR) and average variance extracted (AVE) of all the variables surpass the threshold, hence, high internal consistency (see Table 1).

Table 1 CFA Factor loadings
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Control variables

Demographic factors were assessed to control their effects. As advocated by some earlier researchers, gender, age, and job tenure affects organizational citizenship behaviors toward the individual (Zhao & Zhou, 2021). Given this, gender, age, and length of service were controlled.

Data analysis

The statistical package for social science (SPSS) version 22 and analysis of moment structure (AMOS) version 21 were used in analyzing the data. The study carried out EFA to ascertain how the various items under each variable were loaded under their respective components. To assess the fit of the data, AMOS was employed to analyze the data through CFA. AMOS was chosen due to its reliability in data correctness and certainty (Shek & Yu, 2014). Furthermore, to assess that the data under usage is accurate and appropriate, AMOS was used to check if the data suffered from negative indeterminacy to confirm the data’s correctness. With the help of AMOS plugins originated by Gaskin and Lim (2016), the reliabilities and the validities were assessed.

Regarding the results from the EFA and the recommendations by Hair et al. (2010) and Finch (2019), items having values of 0.50 and above were considered suitable for further analysis. According to the rule of thumb, 0.50 or greater is considered better for the minimum loading of an item without cross-loadings (Burton & Mazerolle, 2011). However, EHB5, EHB6, and EHB8 were deleted since their loadings were below 0.50. This study’s remaining factor loadings were significant and surpassed the threshold. The inter-factor correlation was performed using SPSS to provide preliminary support for the hypotheses. The various hypothetical paths were estimated using hierarchical regression in SPSS.

Results

Measurement model

Regarding the CFA factor loading results, the values were higher than 0.60 and were significant at a 95% bias-corrected confidence interval when the sample was bootstrapped to 5,000. In general, the model had CFA values of chi-square (X2) = 557.918, chi-square (χ2)/degrees of freedom (df) ratio = 1.259, root mean square error of approximation (RMSEA) = 0.024, goodness-of-fit index (GFI) = 0.931, Tucker–Lewis Fit Index (TLI) = 0.989, standardized root mean square residual SRMR = 0.03, CFI = 0.98, demonstrating model fit. About the reliability analysis, the construct reliability (CR) coefficient for each measure ranged from 0.868 to 0.947, indicating strong internal consistency; the average variance extracted (AVE) for each variable in the validity test varied from 0.665 to 0.76, indicating good convergent validity (Hair et al., 2010) (see Table 1). The discriminant validity values were greater than the inter-factor correlation coefficients and are shown in Table 2, indicating that the variables were distinct.

Table 2 inter-factor correlation analysis, Means, standard deviation, and discriminant validity
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Assessment of common method variance

Common method variance (CMV) affects self-reported data collection (Podsakoff et al., 2003; Quansah et al., 2022). Hence, we safeguarded respondents’ identities and alleviated concerns about the evaluation process to mitigate CMV. Participants were informed that the study was solely for academic purposes and that their responses would be kept strictly confidential. Assurance was that there were no correct or incorrect replies and that participants should respond to questions as honestly as possible. The items’ order was randomized, and the time lag of temporal separation between independent and dependent constructs was created to eliminate variances (Podsakoff et al., 2003). Again, Harman’s single factor test was used through EFA in SPSS version 22 software to check CMV. Results demonstrate that the data set explained 30.42% of the variance of a single factor which is less than 50%, indicating no CMV. However, regarding the drawbacks of Harman’s single-factor test, as proven by Podsakoff et al. (2003), an unmeasured latent factor test was performed with a single latent factor. The obtained model fit was subpar because the comparison of the CFA of the substantive measurement model (Chi-square = 557.918) to the CFA of the single latent factor (Chi-square = 554.788) revealed a 3.13 difference in Chi-square. This outcome indicates that CMV was not an issue since the lower Chi-square difference was insignificant.

Descriptive statistics

Table 2 shows the variables’ inter-factor correlation, means, and standard deviation. The mean values for all variables are between 2.734 and 3.590, with standard deviations between 0.907 and 1.230. The Pearson correlations show that supportive supervisor behavior positively and significantly correlates with EHB (r = 0.217, p < 0.01), intellectual engagement (r = 0.213, p < 0.01), social engagement (r = 0.195, p < 0.01), and affective engagement (r = 0.302, p < 0.01). These results indicate initial support for the hypotheses.

Hypotheses testing

Testing the main effects and mediating effects of employee engagement

Hierarchical regression (SPSS V. 22) was used to test the hypotheses. Model 2 in Table 3 shows supportive supervisor behavior exercised a positive and statistically significant influence on EHB (β = 0.228, p < 0.001), validating H1. Model 3 showed supportive supervisor behavior exercised a positively significant effect on intellectual engagement (β = 0.246, p < 0.001), thus, H2a was supported. Furthermore, when intellectual engagement was treated as an independent variable in Model 4, intellectual engagement predicted EHB (β = 0.149, p < 0.001) positively and significantly. Hence, H3a was supported. Regarding the estimate in Model 5, when EHB was regressed on supportive manager behavior and intellectual engagement, supportive supervisor behavior still significantly influenced EHB (β = 0.203, p < 0.001). Also, intellectual engagement still exerted a positively significant influence on EHB (β = 0.104, p < 0.01). Hence, intellectual engagement partly mediated the relationship between supportive supervisor behavior – EHB. Thus, H4a was supported.

Table 3 Mediating effect of employee engagement in the relationship between supportive supervisor behavior and EHB
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Regarding Model 6, supportive supervisor behavior positively and significantly influenced social engagement (β = 0.194, p < 0.001), supporting H2b. In Model 7, social engagement had a slightly significant positive influence on EHB (β = 0.021, p < 0.05), hence, H4b was supported. When EHB was regressed on supportive supervisor behavior and social engagement in Model 8, supportive supervisor behavior had a positive and significant effect on EHB (β = 0.237, p < 0.001). Social engagement also exercised a positive and significant effect on EHB (β = 0.044, p < 0.05). Hence, social engagement partly mediated supportive supervisor behavior – EHB relationship. Thus, H5b was supported.

In Model 9, affective engagement was positively and significantly influenced by supportive supervisor behavior (β = 0.235, p < 0.001), providing support for H2c. In Model 10, affective engagement exerted a positive and significant influence on EHB (β = 0.046, p < 0.05), thus, H4c was supported. EHB was then regressed on supportive supervisor behavior and affective engagement in Model 11, supportive supervisor behavior had a positive and significant effect on EHB (β = 0.239, p < 0.001). Also, affective engagement exercised a positive and significant effect on EHB (β = 0.044, p < 0.05), indicating partial mediation. thus, H5c was supported.

Moderation effect of perceived organizational obstruction

Hierarchical regression was used to investigate the hypothesized moderated relationships. We mean-centered intellectual engagement, social engagement, affective engagement, and perceived organizational obstruction to generate the interaction terms to test the moderation effects. In Table 4 Model 3, the findings revealed that intellectual engagement positively impacted EHB (β = 0.078, p < 0.001). However, perceived organizational obstruction, though positive, was not statistically significant in influencing EHB (β = 0.016). Using intellectual engagement as the independent variable, the interaction of intellectual engagement and perceived organizational obstruction was statistically significant (β = 0.075, p < 0.05). Hence, perceived organizational obstruction moderated the relationship between intellectual engagement – EHB. In Model 5, the findings revealed that social engagement exerted a negative and nonsignificant impact on EHB (β = − 0.070). Perceived organizational obstruction had a negative and nonsignificant effect on EHB (β = − 0.003). The interaction of social engagement and perceived organizational obstruction was positive but statistically insignificant (β = 0.020); hence, no moderation. Furthermore, in Model 7, affective engagement exercised a negative and nonsignificant effect on EHB (β = − 0.065). Perceived organizational obstruction exerted a negative and nonsignificant effect on EHB (β = − 0.064). Likewise, the interaction of affective engagement and perceived organizational obstruction was positive and nonsignificant (β = 0.030); therefore, no moderation effect.

Table 4 Moderating effect of Perceived organizational obstruction on the relationship between employee engagement and EHB
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Discussion

The current study investigates the role of intellectual, social, and affective engagement as conduits through which supportive supervisor behavior predicted EHB and the moderating influence of perceived organizational obstruction on the relationships among intellectual, social, affective engagement, and EHB. The findings given above have resulted in several key conclusions.

First, supportive supervisor behavior increases the EHB. This finding corroborates a previous study (Arshad et al., 2021). Supervisors’ support instills a sense of trust, positive work values, enthusiasm, and respect in employees, motivating and empowering employees to work voluntarily (Stinglhamber & Vandenberghe, 2003). Additionally, a supervisor’s support keeps employees highly involved, which leads to greater EHB. This assertion aligns with the SET (Cropanzano & Mitchell, 2005); when one party acts to benefit a second party, the latter returns the favor. In the Ghanaian hospitality perspective, unsupported frontline employees always feel unappreciated, decrease their sense of belongingness, and feel oppressed, promulgating their ineffectiveness in the workplace (Ampofo et al., 2022). Therefore, a supervisor needs to regularly display supportive behavior for employees to feel appreciated, become loyal, and effective, as it discourages destructive behaviors (Gonzalez-Morales et al., 2018).

Second, the results showed that high intellectual engagement is achieved if employees are exposed to supportive behaviors, confirming an earlier study (Ibrahim et al., 2019). When employees are resourced to become knowledgeable, they become highly engaged and assist their coworkers in discharging duties. Moreover, when employees perceive to be respected and socially supported by enjoying social ties and sharing the same work values with coworkers (i.e., high social engagement), they invest in work. Hence, frontline employees appreciate carrying out unassigned tasks (Contreras et al., 2020). Consistent with SET (Cropanzano & Mitchell, 2005), employees benefiting from supervisory support display excellent citizenship behavior (Quansah et al., 2022). Also, when employees receive managers’ support and care, they respond by exhibiting high engagement (Saks, 2021). Furthermore, it was revealed that the frontline employees become enthused in assisting individuals due to the support received, demonstrating high affective engagement. Likewise, high intellectual engagement, social engagement, and affective engagement as a result of supportive behaviors increase frontline employees’ motivation to engage in altruism, civic virtue, and sportsmanship (Soane et al., 2012). Surprisingly, social and affective engagement had a slightly significant influence on EHB. The reason is certain missing factors like employees that receive low social connectedness and enthusiasm may not recognize the significance of unleashing helping behaviors, according to Soane et al. (2012). Moreover, since the study was conducted in the era of and post-COVID-19, workers were made to obey social distancing. Therefore, employees were working in isolation, which could have decreased their desire for engagement (Mensah & Boakye, 2021). In this case, employee engagement may have minimal effect on how employees perform extra-role like citizenship behavior in the organizations. In this regard, social engagement and affective engagement exerted an infinitesimal impact on EHB.

Third, frontline employees that feel valued because of supportive supervisor behavior experience psychological, social, and emotional well-being (Gupta et al., 2021). Such feeling gives vast recognition to an individual and a sense of expressiveness, sharing job goals with coworkers, and optimism about the individual’s job and soothes employee engagement (Soane et al., 2012). Therefore, intellectual, social, and affective engagement partly mediated supportive supervisor behavior – EHB relationship. This outcome is not staggering, as satisfaction in working with supervisors and coworkers is deemed a vital relational resource in a workplace (Ampofo & Karatepe, 2021). Also, since Ghana practices collectivist culture, prioritizing relationships supersedes tasks (Ampofo & Karatepe, 2021; Hofstede et al., 2005).

Finally, the moderation results seem staggering since perceived organizational support slightly impacted the relationship between intellectual engagement and EHB. Indeed, it sheds more light on how well-engaged employees cope with perceived organizational support in organizations as most employees may have disidentified themselves (Akhtar et al., 2020); instead, employees applied intellectual capabilities as a focus direction to display EHB. Surprisingly, the relationships between social engagement – EHB and affective engagement–EHB were not moderated. We assume employees facing obstruction perceive that their values and the firm’s ideals are at odds, thereby disidentifying with activities that indirectly affect them (Gibney et al., 2011); hence, social and affective disengagement. Moreover, the study reveals that employees resort to relational resources among coworkers leading to a high display of EHB, causing a lack of effect on the relationship between social engagement–EHB and affective engagement–EHB. Contextually, although frontline employees perceive some level of obstruction in the organization, they do not pay much attention to such obstruction since employees are high on intentions to quit (Ampofo & Karatepe, 2021; Obeng et al., 2021). Moreover, because there is some managerial support, employees were relieved from perceiving obstruction, indicating that managers’ policies were supportive. Figure 2a,2b, and 2c support the moderation effects.

Fig. 2
figure 2

a Moderation graph showing perceived organizational obstruction effect on intellectual engagement and EHB relationship, b Moderation graph showing perceived organizational obstruction effect social engagement and EHB relationship, c Moderation graph showing perceived organizational obstruction effect on affective engagement and EHB relationship

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Theoretical implication

The outcomes reported in this research contribute to a new pathway in hospitality and tourism industry literature by assessing supportive supervisor, intellectual, social, and affective engagement and endorsing their significant positive effects as mediators. As was proposed in the study that frontline employees are highly engaged, which leads to the ‘valence’ (the extent to which an emotion is positive or negative) nature of emotion that manifested in the employees. Thus, valence permeated the fundamental level of employee engagement, given the behavior of the supervisors (supportive), which affects the engaged employees in the range of the affect spectrum (Macey & Schneider, 2008). These assertions provided variations in employee engagement since the variance explained varied from each other’s outcomes. This notion is significant considering previous research on supportive supervisor behavior and EHB has failed to expand employee engagement knowledge (Ampofo, 2021; Kang et al., 2015).

In addition, the study contributed to literature in the social exchange spectrum as SET (Cropanzano & Mitchell, 2005) and reciprocity norm validates that supportive supervisor behavior enhances the social exchange relationship (Peng et al., 2014), improving employees’ work-related behaviors, thus employee engagement and EHB. Also, since managers represent organizations, employees perceive managers’ behaviors as the organization’s view; being supportive leads to a positive response; thus, employees repay by helping coworkers (Saks, 2006, 2021).

Lastly, we contribute to the literature by identifying the potential effect of organizational obstruction interacting with intellectual, social, and affective engagement. We validate that employees with high intellectual engagement keep engaging in citizenship behaviors directed toward individuals despite the perception in the workplace. Thus, employees with high knowledge acquired through supervisor support stop at nothing to concentrate and help coworkers when the job is related.

Practical implication

The present study offers several implications for practice. The study highlights that supportive supervision is beneficial to organizations because of the significant value associated with it, such as high employee engagement and helping behaviors. Top management should design strategies for hiring that are suitable and effective, like behavioral-based interviews, which could help prevent supervisors who are susceptible to abusive behavior. Furthermore, supervisors should be trained and aware of the negative consequences of not being supportive toward employees, such as declining employee engagement (Peng et al., 2014) and EHB (Aryee et al., 2007).

In addition, support training strategies (benevolence, sincerity, fairness, and experiential processing) that harness supportive supervision should be instituted; this could help encourage supervisors to substitute offensive supervision for supportive supervision (Gonzalez-Morales et al., 2018). Nevertheless, supervisors who may exhibit belligerent supervision should be given a work shift or perhaps a suspension. Moreover, top management should design training programs for employees to improve their emotional steadiness through counseling to properly cope with perceived organizational obstruction. As this empirical investigation demonstrates, supervisors and colleague support are vital engagement means within leaders’ and subordinates’ relationships, (Biggs et al., 2014; Swanberg et al., 2011).

It is worth stating that top management supporting employees in their grievances against supervisors could go against the firmly ingrained value of authority; therefore, top management should spearhead possibilities for genuine support methods and policies that positively affect employee engagement. Also, top management should instigate autonomy and feedback-friendly designs on job effectiveness; and ensure that frontline employees have adequate and suitable resources in cooperation with supportive supervisor behavior.

Lastly, organizations should evaluate whether or not employees perceive their supervisors as supportive and whether they believe the workplace is a source of impediment. Given this avowal, management should be more attentive to perceived organizational support because frontline employees are more affected by “terrible” experiences (Gibney et al., 2009).

Limitations and recommendations for future research

Despite the significant theoretical and empirical contributions to the extant literature on supportive supervisor behavior, employee engagement, and EHB, the present study has some limitations that could form future studies. The strength of the current work focused mainly on the mediating and moderating effects of employee engagement and perceived organizational obstruction, respectively. Future studies can explore other variables as mediators and moderators, such as employee involvement and perceived job insecurity. Also, since the study tested the associations among the variables, future works should rather test for the causalities of the variables. furthermore, a joint investigation of supportive and abusive supervisor behaviors would be examined in the future. Moreover, because the convenience sampling technique diminishes the generalizability of the study’s outcomes, imminent studies should adopt a random sampling technique in selecting participants. Furthermore, the study’s data were gathered from frontline employees of hospitality firms. As a result, generalizing the findings could be detrimental to future research. Therefore, we recommend that future studies could collect data through employee-leader pairing. Finally, future studies could direct their investigations toward other industries such as mining, construction, oiland gas, etc., considering the variables under investigation.