1. Introduction
In the current climate of hotel firms’ rapid growth, increasing competition, and choppy market conditions, hotel businesses are investing more than ever in building solid brands (Eriksson et al. 2022). Due to the “intangibility, inseparability, and heterogeneity” of services, hotel brands differ from other product brands (Xie et al. 2014). As a result, a strong brand is a vital performance driver for any hospitality service firm because it distinguishes its service offerings from its competitors, building guest trust and lowering apparent financial, social, and safety-related risks (Simões and Dibb 2001). Thus, the service delivery conduct of frontline guest-contact staff significantly influences guests’ perceptions of a hotel service brand (Hartline et al. 2000). Therefore, it is not sufficient for service people to merely act in a manner that fulfills the brand’s promise to develop a strong brand for the company; instead, they are urged to go above and beyond their formal in-role performance to meet the expectations of the brand and customers (Pornpitakpan et al. 2017). Here, hotels can resort to employees’ brand citizenship behaviors (BCBs) to use their extra-role behaviors to defend, promote, and enhance the brand. Through BCB, hotel employees, for example, can help solid brand-establishing efforts by discretionary positive word of mouth (extra role) as corporate representatives to friends, family, clients, potential clients, and other stakeholders (Löhndorf and Diamantopoulos 2014). Previous research has indicated that the factors that push employees toward brand citizenship behavior, specifically affective and cognitive functions via which brand-supportive behaviors are developed, have yet to receive adequate attention (Burmann and Zeplin 2005; Chang et al. 2012; Helm et al. 2016).
Many scholars have focused on organizational pride (OP) as an essential antecedent to encourage employees to go the extra mile (Tracy and Robins 2007) to demonstrate a passion for their brand and become brand champions (Chiang et al. 2013); thus, OP is expected to motivate hotel employees to display BCB. However, this concept has received little attention from business and marketing studies, and most claims concerning pride are based on intuition, underlining the demand for empirical proof on pride in business contexts (Gouthier and Rhein 2011).
In the same vein, employees will only feel proud of their companies when they believe they support community development, improve people’s health, and safeguard the environment and natural resources (Al Kerdawy 2019). According to Jia et al. (2018), employees also feel pride when engaging in their firm’s green practices, such as recycling actions, saving energy, and utilizing green products. Accordingly, Gilal et al. (2019) concluded that green human resource management (GHRM) practices are critical to generating organizational pride, as well as motivating employees to show brand citizenship behaviors (Elshaer et al. 2023a).
Agreeing with the “supplies–values fit” (SVF) theory, prior research underlines that the function of a fit between employees and their brands, in terms of beliefs or values, is paramount in facilitating brand-supportive behaviors (Hurrell and Scholarios 2014). Thus, we argue that individual green values of employees that are congruous with GHRM principles will play a crucial role in boosting and supporting employees’ BCBs and perceived organizational pride (Yasin et al. 2023).
Although several studies have examined how GHRM practices affect employees’ attitudes and behaviors (Singh et al. 2020; Ren and Hussain 2022; Freire and Pieta 2022), the majority of these studies have concentrated on the direct correlation between GHRM and outcomes rather than the psychological mechanisms by which GHRM practices affect employee attitudes and behaviors (Hameed et al. 2019). Moreover, very little research has been conducted to document the linkage between positive emotions like pride and green behavior (Schneider et al. 2017; Kotabe et al. 2019; Mukherjee and Chandra 2022). Therefore, various mediating variables still need to be explored to better understand the underlying mechanisms of GHRM. Consequently, this study seeks to address some of the above gaps by exploring the relationship between GHRM and employees’ BCBs, taking into account the mediating effect of organizational pride (OP) and the moderating interactions of individual green values (IGVs).
2. Theoretical Foundations and Hypotheses Formulation
2.1. Green Human Resources Management (GHRM) and Brand Citizenship Behavior (BCBs)
Recent research has highlighted GHRM as an emerging concept being investigated for its effects on employee behavior and perceptions in the workplace (Dumont et al. 2017; Cao et al. 2023). The past period has also noticed a proliferation of GHRM research in a hospitality and tourism industry context, with a growing number of hotels adopting initiatives for new GHRM approaches to promote green individual and organizational performance (Úbeda-García et al. 2022). Previous studies contend that hotels work to benefit from GHRM practices such as selecting and hiring new staff with green awareness, values, and knowledge; preparing training to develop and reinforce staff members’ green competencies and skills; conducting green performance assessments with specific criteria for evaluating green work behaviors and performance; and rewarding staff based on the successful accomplishment of green organizational goals (Renwick et al. 2013; El Baroudi et al. 2023), in order to improve organizational citizenship behavior (OCB) toward the environment (Elshaer et al. 2023a), promote in-role green work behaviors (Karatepe et al. 2022; Pham et al. 2020), develop a circular economy (Jabbour et al. 2019), improve social reputation (Pan et al. 2022), and promote innovative performance, green values, and job satisfaction (Elshaer et al. 2022b). However, few studies address whether GHRM motivates employees’ discretionary extra-role behaviors, such as BCB, in the organization, or its effect on some self-worth and self-esteem behaviors, such as organizational pride.
Employing the concept of OCB, Burmann et al. (2009) identified BCB as “the intention of each employee to voluntarily exhibit certain generic (brand- and sector-independent) behavioral characteristics outside of the formally defined role expectation system, which strengthen the identity of the brand.” Thus, both concepts (OCB and BCB) go beyond in-role duties and are non-enforceable; nevertheless, BCB concentrates on behaviors that enhance the positive corporate brand’s external perception, whilst OCB typically focuses on intraorganizational aspects (Burmann and Zeplin 2005). In this context, according to the BCB concept, employees can play an influential role as brand ambassadors in building a solid brand within the hospitality industry (Van Nguyen et al. 2019; Hoang 2022). Scholars have investigated many antecedents of employee BCB, such as brand commitment (Piehler 2018), perceived organizational support (Xie et al. 2014), brand-psychological ownership, and brand-centered human resource management (HRM) (Chang et al. 2012). Perceived brand-centered HRM refers to employees’ beliefs regarding HRM practices, including hiring, selecting, training, appraising performance, rewarding, and developing initiatives that could help them internalize the brand identity (Aurand et al. 2005). Accordingly, implementation of the ethical, social, and environmental symbols incorporated in GHRM assists the organization in improving its social reputation and word of mouth (WOM) and drives employees to take the initiative to reinforce their connection with the organization through their extra role (BCB); organizational identity also improves in this operation (Úbeda-García et al. 2021; Cao et al. 2023). These practices ensure positive employee attitudes and behaviors toward the brand (Chang et al. 2012), such as the desire to interact with customers in a way that benefits the hotel brand and clarifies any misunderstandings that customers may have about it (Hoang 2022). Here, this is based on the notion that social exchange theory (SET) supports a win-win situation by mutualizing resources between the employee and the organization (Cropanzano et al. 2003). Thus, employees boost their confidence in the organization when there is a beneficial exchange of resources between them and the organization (Cropanzano and Mitchell 2005), potentially enhancing positive discretionary behaviors (BCBs). Depending on these arguments, we can propose the following hypothesis.
GHRM is positively associated with BCB.
2.2. Green Human Resources Management (GHRM) and Organizational Pride (OP)
Previous studies have recommended that more investigations are needed to determine the role of CSR and eco-friendly related practices in controlling organizational pride (Latan et al. 2018; Shahzadi et al. 2019; Farooq and Salam 2020; Elshaer et al. 2023b, 2022a). Specifically in the hospitality business, where most previous empirical studies have only concentrated on the macro-level impact (i.e., firm level) of GHRM, especially intra-organizationally, whereas the micro-level (i.e., individual level) effect of GHRM, especially extra-organizationally, is still relatively less investigated (Hur et al. 2018; Chen et al. 2019; Farooq and Salam 2020). Organizational pride refers to an employee’s sense of perceived happiness and satisfaction of being a member of his organization (Boezeman and Ellemers 2014; Gouthier and Rhein 2011). According to Kraemer and Gouthier (2014), OP is also the creation of a favorable, encouraging work environment, which necessitates a high level of social identification with the business. According to appraisal theories, an employee’s feeling of pride is frequently associated with the perceived value of his deeds carried out in the workplace (e.g., honored as the year’s top employee) (Gouthier and Rhein 2011). Employees, on the other hand, feel a sense of OP when they are emotionally connected to their company and proud of its accomplishments (i.e., GHRM practices) (Boezeman and Ellemers 2014; Tang et al. 2020).
In the same line of appraisal theories, according to social identity theory, people believe that strengthening their connection to a group allows them to share its positive, admirable traits (i.e., GHRM practices) leading to a rise in their sense of self-worth and self-esteem (i.e., organizational pride) (Hewstone et al. 2002). Thus, positive perceptions about a corporation shaped by its CSR activities boost employees’ pride (John et al. 2017) and intention to support its brand reputation (Ellemers et al. 2004; Hur et al. 2018). Employees are increasingly likely to experience pride when they realize that customers opt for their green brand, making them feel proud to contribute to pro-environmental and pro-social endeavors (Maior et al. 2022). Moreover, our study argues that GHRM is correlated (i.e., as an antecedent) to organizational pride (Kuo et al. 2016; Kim et al. 2020). Based on this discussion, the below hypothesis was proposed:
GHRM is positively associated with OP.
2.3. Organizational Pride (OP) and Brand Citizenship Behavior (BCBs)
According to SET, organizational pride is a primary intrinsic motivator for positive employee behaviors (Katzenbach 2003). Organizational pride makes employees feel highly appreciative of and attached to their employer, encouraging them to conduct pro-organizational initiatives (BCBs) (Kraemer and Gouthier 2014). Generally, as a valuable psychological resource, organizational pride encourages employees to demonstrate both general organizational citizenship behavior (OCB) (Sabrina Helm 2013) as well as environmental behavior (Hameed et al. 2019). In the green context, in particular, some studies assert that OP boosts pro-social behaviors (Katzenbach 2003; Wubben et al. 2012). Therefore, Helm et al. (2016) argued that organizational pride resulting from green practices (i.e., GHRM practices), could broaden the tendency of the OCB concept and positively associate with BCB. These arguments direct to the below hypothesis:
OP is positively associated with BCB.
Employing the social identity theory (SIT) and the social exchange theory (SET) and integrating prior evidence, as well as relying on the justifications cited beforehand of the suggested three direct hypotheses between the study’s variables, we presented the following hypothesis for the mediation relationship:
OP mediates the association between GHRM and BCB.
2.4. Individual Green Values (IGVs) as a Moderator
The congruity between employees and their brands is paramount to creating a solid brand (Hurrell and Scholarios 2014). Congruity in terms of values or beliefs between employees and their brands facilitates appropriate brand-supportive behaviors (Helm et al. 2016) and places more energy, dedication, voluntary behaviors (BCBs), and passion (organizational pride) into their work (Raza et al. 2021). According to SIT, when a company adopts GHRM practices, employees with higher IGV levels are more compatible and consistent with their company (Cao et al. 2023). Therefore, varying IGV levels among employees could potentially be a factor in variations in GHRM results (Gilal et al. 2019). IGVs, as the name implies, represent the views of the organization’s employees on environmental sustainability (Raza and Khan 2022). Studies have indicated that employees with green values and beliefs feel organizational pride when carrying out green duties (Anwar et al. 2020; Hooi et al. 2022). Furthermore, Gilal et al. (2019) indicated that IGVs positively moderate the positive influence of GHRM practices on environmental passion (pride). Similarly, IGVs improve employees’ willingness to contribute to in-role and extra-role behaviors to support their organization (i.e., BCB) (Pham et al. 2019; Boiral, 2009).
Based on the supply-value-fit theory (Edwards 1996), providing green values from the firm (e.g., GHRM practices) is deemed the best congruent for individuals with high green values levels (Islam et al. 2021). Accordingly, the current study proposes that IGVs reflect employees’ green ethical level, and if employees have a higher level of IGVs, their green OP will be more significant because of GHRM practices, and their BCBs will also be more significant due to the impact of green organizational pride. Thus, this study suggests the following two hypotheses, as illustrated in Figure 1:
IGVs moderate the influence of GHRM on OP, such that the relationship will be stronger when IGVs are high.
IGVs moderate the influence of OP on BCB, such that the relationship will be stronger when IGVs are high.
3. Materials and Methods
3.1. Participants and Process of Data Collection
The researchers gathered data for the study by conducting a questionnaire survey of guest-contact staff at hotels in Sharm El-Sheikh, Egypt. This city was chosen because it has several high-ranking five-star hotels. Only employees with a minimum of three years of experience were allowed to participate in the survey, as they were considered to have enough knowledge and expertise to answer the research questions. Data were collected during January 2023 using convenience sampling and drop-and-collect methods. According to Bornstein et al. (2013), convenience sampling is the most frequently used non-probability sampling method in developmental science because it is cost effective, time efficient, and easy to conduct. The survey was separated into two stages. In the first survey stage, employees were instructed to provide the required information for GHRM practice, BCB variables, and demographic data. A month later, in the same Sharm El-Sheikh hotels, employees finished the organizational pride (OP) and individual green values (IGVs) variables questionnaire. In both surveys, 500 questionnaire records were distributed. After removing the unqualified forms, 328 responses were considered, with an efficient recovery rate of 65.6%. The study sample incorporated 253 males (77.1%) and 75 females (22.9%). The participants’ age spectrum ranged mainly from 24 to 58 years old. All targeted participants were non-managerial positions where the largest proportion (41%) were front desk receptionists, followed by 25% who worked in room service, 20% in housekeeping, and 14% in the spa department.
3.2. Measures
The questionnaire items for all variables were obtained from the existing literature and employed in the study. A five-point Likert scale was utilized to assess all variables. The GHRM practices were operationalized by six items based on the suggestion of Kim et al. (2019). The BCB variable was measured by a seven-item scale recommended by Van Nguyen et al. (2019). For the OP, four items were adopted from Ng et al. (2019). Finally, the measurement items for the IGVs were adopted from Chou (2014). To render the survey questions clearer and easier to understand, they were transcribed and edited. The poll was tested by a total of 16 people, including eight academics and eight practitioners in the relevant sector, to confirm its validity. The survey’s content was not altered throughout this procedure and thus remained unchanged.
3.3. Data Analysis Methods
“Structural equation modelling” (SEM) was employed using “partial least squares” (PLS) with SmartPLS 4.0 to test the proposed model. PLS is appropriate and practical when the study’s primary goal is to predict one or more dependent variables rather than to verify a previously established theoretical model (Hair et al. 2017). PLS-SEM is a suitable method for this study because it explores relationships between the GHRM and BCB variables with the mediating role of the OP and moderating role of the IGV variable. Moreover, the PLS method is effective across a wider variety of sample sizes and is a more sophisticated model with fewer data restrictions, as well as being an effective technique (Hair et al. 2011). Using PLS-SEM also allows for the inclusion of more reflective items per factor compared to other statistical methods. According to Leguina (2015), the PLS-SEM method uses two steps: measurement modeling and structural modeling.
4. The Study Results
4.1. Measurement Model Assessment (Outer Model)
The measure measurement model tests the convergent validity (CV) and discriminant validity (DV) to investigate data quality. The CV evaluates the association between indicators by using Cronbach’s alpha (higher than 0.50) (Leontitsis and Pagge 2007), composite reliability (CR) (higher than 0.60) (Fornell and Larcker 1981), average variance extracted (AVE) (higher than 0.50) (Hair et al. 2011), and factor loading (higher than 0.50) (Afthanorhan 2013) as evaluation criteria. Furthermore, DV claims that the observed values must be capable of being discriminated against when applying different methods to measure other constructs. According to Fornell and Larcker (1981) when the of the construct is higher than the correlation between that construct and others in the model, the construct meets the statistical requirement for discriminant validity. On the other hand, due to the numerous complaints that were leveled against Fornell and Lacker’s criterion, several researchers evaluated the heterotrait–monotrait (HTMT) ratio of correlation to determine discriminant validity (Sarstedt and Cheah 2019). The threshold value of HTMT is 0.9, according to Gold et al. (2001).
The CV indicators in Table 1 show that all of the advised minimum and/or maximum levels were satisfactory, indicating that the proposed outer model is appropriate. In terms of dimensions for DV, both the , HTMT, Fornell and Larcker values, as shown in Table 2, Table 3 and Table 4 met the recommended thresholds, indicating that the scale has adequate discriminant validity.
4.2. Hypotheses Testing (Inner Model Assessment)
In order to prevent the impact of variables on the model’s contribution, the study examines collinearity concerns using the variance inflation factor (VIF) to determine whether or not there is a problem with collinearity between variables. Following the guidance of Hair et al. (2011), VIF values which range below five do not necessitate fixing multicollinearity. The regression model’s explanatory precision has also been evaluated using the coefficient of determination (R2) and Stone-Geisser’s Q2. In behavior studies, an R2 result of 0.20 is regarded as a high benchmark Hair et al. (2011). Similarly, Q2 values surpassed the suggested threshold value of 0.0 (Hair et al. 2014). Table 5 displays the VIF, R2, and Q2 results.
PLS, in contrast to covariance-based SEM (CBSEM), does not offer a variety of statistical measures for model validation, such as X2 and other model fit measurements (Henseler and Sarstedt 2013). “The GoF represents an operational solution to this problem as it may be meant as an index for validating” (Tenenhaus et al. 2005). The following is the GoF calculation method, according to Mital et al. (2018) and Tenenhaus et al. (2005):
According to Tenenhaus et al. (2005), GoF small = 0.1, GoF medium = 0.25, and GoF high = 0.36. The GoF value of the suggested model is 0.535, which indicates that our model has a considerable GoF index. Additionally, the study assesses the model’s fit by comparing the variances in observed correlations using the “Standardized Root Mean Square Residual” (SRMR). SRMR < 0.08 denotes a good enough model fit (Hu and Bentler 1998). The suggested model’s SRMR value, which is 0.078, indicates a good model fit.
Once the accuracy of the outer and the inner model was confirmed, we could further investigate the suggested hypotheses of the study. Smart PLS4 was utilized to perform a 5,000 bootstrapping repetition to calculate the regression weights (β), t-statistics, and significance p level of the direct, indirect, and moderating effects. We assessed a total of six hypotheses, consisting of three direct hypotheses, and one with mediating and two with moderating effects, as presented in Table 6.
Based on the results presented in Figure 2 and Table 6, the GHRM had a significant and positive impact (p < 0.000) on BCB (β = 0.415, t = 6.110, p < 0.000) and OP (β = 0.270, t = 3.780, p < 0.000), providing support for H1 and H2. The findings also indicate that OP significantly and positively influenced BCB at β = 0.293, t = 3.899, p < 0.000, confirming H4. Moreover, the variables of OP mediated the relationship between GHRM and BCB at β = 0.079, t = 2.919, p < 0.004, indicating that H5 could be accepted.
The assessment of the moderating effects revealed that IGVs have a significant impact on the relationship being tested, as illustrated in Figure 3 and Figure 4. Specifically, the SmartPLS analysis showed that the IGV strengthens the significant influence of GHRM on OP (β = 0.206, t = 2.293, and p = 0.022), indicating support for H5. Similarly, the IGV strengthens the significant influence of OP on BCB (β = 0.191, t = 4.001, and p = 0.000), supporting H6.
5. Discussion
Recent studies have begun to concentrate on GHRM outcomes that are non-green (Amjad et al. 2021). Despite this, the hospitality and tourism studies still lack proof of the possible green and non-green favorable results of GHRM practices among hotel staff (Nisar et al. 2021; Aboramadan and Karatepe 2021). Furthermore, the majority of academic empirical works on GHRM have been achieved in Western contexts and manufacturing industries (Cabral and Jabbour 2020). To respond to this, this study utilizes data gathered in hotels at Sharm El-Sheikh in Egypt (as one of the African developing countries) to examine the interrelationships of GHRM, two non-green variables (i.e., BCB and OP), and one green variable (i.e., IGV). Accordingly, the findings of our empirical study achieved their purposes and objectives by contributing to the current literature on GHRM and theoretical development through the proposed model. The results revealed that GHRM practices positively impact BCB (H1). Here, mainly according to the job demands-resources (JD-R) theory (Bakker and Demerouti 2017), employees are enthusiastic, goal-oriented, and effectively do work-related duties and extra-role activities when they have positive emotions about their jobs (Ozturk et al. 2021). Moreover, Nisar et al. (2021) indicated that an employee with green knowledge, skills, and abilities effectively completes his task duties and extra-mile behavior. Thus, we argue that GHRM practices have a critical role in supporting BCBs.
GHRM practices not only activate pro-environmental behaviors but can also stimulate non-green positive attitudinal and behavioral consequences (Shafaei et al. 2020). In line with this, our study proved that the GHRM practices positively affected OP (H2). In this context, few empirical studies have explored how GHRM influences hotel employees’ non-green positive workplace attitudes and behaviors outcomes (Aboramadan and Karatepe 2021), such as OP. Specifically, pride as a positive shape of self-conscious emotions has been overlooked or has not received much attention in environmental literature (Kotabe et al. 2019; Mukherjee and Chandra 2022). Within this petite knowledge, this result is consistent with the argument that valuable organizational characteristics can be considered a source of OP for individual employees (Pham et al. 2021), and GHRM practices can thus be an essential source of OP. Additionally, few research studies approved a reasonably strong linkage between positive emotions, such as OP and green behavior (Onwezen et al. 2014; Bissing-Olson et al. 2016). On the same statistical path, the study results found that OP positively affects BCB (H3). Here, Tyler and Blader (2003) argued that OP would predict employees’ psychological attachment to their organization and, thus, extra-role behaviors (BCBs).
The study aimed to test whether OP mediates the relationship between GHRM and BCB (H4). The study’s results, which supported the previous three hypotheses, showed that OP was indeed a mediator between GHRM and BCB. In the context of this result, Du et al. (2010) indicated that employees feel pride in their organization when they receive CSR messages (or realize its GHRM practices). Organizations often adopt GHRM practices to generate employees’ positive emotions (e.g., OP) in order to improve brand reputation (Chang et al. 2016) through BCBs.
Finally, our PLS-SEM results confirmed the moderation impacts of IGVs on the links between GHRM and OP (H5) as well as those between OP and BCB (H6). In general, the congruity between organizational and individual values significantly positively affects employees’ work-related attitudes and behaviors (Islam et al. 2021). IGVs have been found to strengthen the connection between GHRM practices and employees’ environmental passion (Gilal et al. 2019) (e.g., OP) and OCB in general (Dumont et al. 2017), specifically BCBs. Finally, in sum, managers of green hotel brands can communicate “green pride” stemming from GHRM practices that are congruent with employees’ green values as a way to motivate employees to participate in BCB behaviors (Maior et al. 2022).
6. Conclusions
This research paper explored the relationship between green human resource management (GHRM) practices, brand citizenship behavior (BCBs), organizational pride, and individual green values in the hotel industry. The study found that GHRM practices have a positive impact on BCB, and this relationship is partially mediated by organizational pride. Additionally, the study showed that individual green values (IGVs) play a moderating role in the relationship between GHRM practices and BCB.
The findings of this study have several theoretical implications for the fields of human resource management and sustainability. First, the study contributes to the growing body of literature on GHRM practices by providing empirical evidence of the positive impact of GHRM practices on brand citizenship behavior (BCB) in the hotel industry. This study extends the current literature by highlighting the importance of OP and IGVs as moderators in the relationship between GHRM practices and BCB. Second, this study contributes to the literature on sustainable behavior by emphasizing the role of OP and IGVs in promoting sustainable behavior. The findings suggest that OP and IGVs are important factors in determining the extent to which employees engage in sustainable behavior. This study provides a theoretical foundation for future research to investigate the role of OP and IGVs in promoting sustainable behavior in other industries and contexts.
The practical implications of this study are relevant for hotel managers seeking to enhance their brand’s reputation for sustainability and promote sustainable behavior among employees. First, the study suggests that the adoption of GHRM practices can promote sustainable behavior among employees and enhance their commitment to the organization. Hotel managers can use GHRM practices such as training, communication, and performance management to promote sustainable behavior and enhance the organization’s sustainability performance. Second, the study highlights the importance of OP in promoting sustainable behavior. Hotel managers can promote OP by providing opportunities for employees to participate in sustainability initiatives, recognizing and rewarding sustainable behavior, and communicating the organization’s sustainability goals and achievements to employees. Thirdly, the study emphasizes the importance of IGVs in promoting sustainable behavior. Hotel managers can promote IGVs by hiring employees who share the organization’s sustainability values, providing training and development opportunities, and creating a supportive work environment that encourages sustainable behavior.
Future research could investigate the impact of GHRM practices on employee well-being and job satisfaction, as well as the relationship between sustainable behavior and financial performance. In addition, future studies could examine the influence of external factors, such as government regulations and industry norms, on the adoption of GHRM practices in the hotel industry. Furthermore, the study focused on the hotel industry, and it would be interesting to see if the findings can be applied to other industries as well. Future research could explore the applicability of these findings in other sectors and industries, such as the manufacturing and service industries using a different methodology in the collecting and/or analysis of the data. Finally, the study used a cross-sectional survey design, which limits the ability to make causal inferences. Future research could employ longitudinal or experimental designs to establish causal relationships between GHRM practices, BCB, OP, and individual green values.
Conceptualization, I.A.E., C.K., and S.F.; methodology, I.A.E., S.F., C.K., and A.M.S.A.; software, I.A.E. and S.F.; validation, I.A.E., A.M.S.A., C.K., and S.F.; formal analysis, I.A.E. and A.M.S.A.; investigation, I.A.E., S.F., C.K., and A.M.S.A.; resources, I.A.E.; data curation, I.A.E.; writing—original draft preparation, S.F., I.A.E., C.K., and A.M.S.A.; writing—review and editing, I.A.E., S.F., C.K., and A.M.S.A.; visualization, I.A.E.; super-vision, I.A.E.; project administration, I.A.E., S.F. and A.M.S.A.; funding acquisition, I.A.E. and A.M.S.A. All authors have read and agreed to the published version of the manuscript.
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the deanship of the scientific research ethical committee, King Faisal University (project number: 3220, date of approval: 25 April 2022).
Informed consent was obtained from all subjects involved in the study.
Data is available upon request from researchers who meet the eligibility criteria. Kindly contact the first author privately through e-mail.
The authors declare no conflict of interest.
Footnotes
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Psychometric metrics.
| Loadings | a Value | CR | AVE | |
|---|---|---|---|---|
| Green Human Resources Management (GHRM) | 0.917 | 0.935 | 0.705 | |
| GHRM/1 | 0.859 | |||
| GHRM/2 | 0.848 | |||
| GHRM/3 | 0.829 | |||
| GHRM/4 | 0.849 | |||
| GHRM/5 | 0.841 | |||
| GHRM/6 | 0.810 | |||
| Brand Citizenship Behavior (BCBs) | 0.941 | 0.952 | 0.737 | |
| BCB/1 | 0.866 | |||
| BCB/2 | 0.874 | |||
| BCB/3 | 0.876 | |||
| BCB/4 | 0.862 | |||
| BCB/5 | 0.869 | |||
| BCB/6 | 0.865 | |||
| BCB/7 | 0.797 | |||
| Organizational Pride (OP) | 0.904 | 0.933 | 0.777 | |
| OP/1 | 0.877 | |||
| OP/2 | 0.918 | |||
| OP/3 | 0.912 | |||
| OP/4 | 0.817 | |||
| Individual Green Values (IGVs) | 0.880 | 0.926 | 0.806 | |
| IGV/1 | 0.874 | |||
| IGV/2 | 0.913 | |||
| IGV/3 | 0.907 | |||
Fac. Cross-loadings.
| GHRM | BCB | OP | IGV | |
|---|---|---|---|---|
| GHRM/1 | 0.859 | 0.655 | 0.420 | 0.499 |
| GHRM/2 | 0.848 | 0.644 | 0.430 | 0.543 |
| GHRM/3 | 0.829 | 0.458 | 0.345 | 0.473 |
| GHRM/4 | 0.849 | 0.454 | 0.326 | 0.441 |
| GHRM/5 | 0.841 | 0.515 | 0.425 | 0.448 |
| GHRM/6 | 0.810 | 0.488 | 0.349 | 0.392 |
| BCB/1 | 0.519 | 0.866 | 0.295 | 0.444 |
| BCB/2 | 0.554 | 0.874 | 0.276 | 0.443 |
| BCB/3 | 0.520 | 0.876 | 0.272 | 0.372 |
| BCB/4 | 0.506 | 0.862 | 0.353 | 0.391 |
| BCB/5 | 0.548 | 0.869 | 0.347 | 0.455 |
| BCB/6 | 0.596 | 0.865 | 0.359 | 0.456 |
| BCB/7 | 0.635 | 0.797 | 0.457 | 0.508 |
| OP/1 | 0.436 | 0.402 | 0.877 | 0.426 |
| OP/2 | 0.423 | 0.386 | 0.918 | 0.414 |
| OP/3 | 0.384 | 0.308 | 0.912 | 0.425 |
| OP/4 | 0.377 | 0.294 | 0.817 | 0.304 |
| IGV/1 | 0.525 | 0.448 | 0.349 | 0.874 |
| IGV/2 | 0.504 | 0.488 | 0.400 | 0.913 |
| IGV/3 | 0.483 | 0.452 | 0.454 | 0.907 |
Bold scores: for discriminant validity, the outer factor loading of the reflective items have should have higher value than the cross-loading related scale measures.
Fornell–Larcker criterion matrix.
| BCB | GHRM | IGV | OP | |
|---|---|---|---|---|
| Brand Citizenship Behavior | 0.859 | |||
| Green Human Resources Management | 0.651 | 0.839 | ||
| Individual Green Values | 0.516 | 0.560 | 0.898 | |
| Organizational Pride | 0.398 | 0.461 | 0.449 | 0.882 |
Bold scores: for a proper discriminant validity, AVE values (bold) have to show values that are higher than the inter-variable correlation coefficient.
HTMT Matrix.
| BCB | GHRM | IGV | OP | |
|---|---|---|---|---|
| Brand Citizenship Behavior | ||||
| Green Human Resources Management | 0.681 | |||
| Individual Green Values | 0.561 | 0.619 | ||
| Organizational Pride | 0.421 | 0.498 | 0.497 |
HTMT: Heterotrait–monotrait matrix. For adequate discriminant validity, all HTMT scores need to be <0.90.
VIF, R2, and Q2 results.
| Items | VIF | Items | VIF | Items | VIF | Items | VIF |
|---|---|---|---|---|---|---|---|
| GHRM/1 | 2.901 | BCB/1 | 3.554 | OP-1 | 2.455 | IGV-1 | 2.195 |
| GHRM/2 | 2.723 | BCB/2 | 3.838 | OP-2 | 3.589 | IGV-2 | 2.695 |
| GHRM/3 | 2.601 | BCB/3 | 3.903 | OP-3 | 3.565 | IGV-3 | 2.547 |
| GHRM/4 | 3.455 | BCB/4 | 3.586 | OP-4 | 2.050 | ||
| GHRM/5 | 2.715 | BCB/5 | 4.391 | ||||
| GHRM/6 | 2.254 | BCB/6 | 3.710 | ||||
| BCB/7 | 2.267 | ||||||
| Brand Citizenship Behavior (BCBs) | R2 | 0.518 | Q2 | 0.366 | |||
| Organizational Pride (OP) | R2 | 0.302 | Q2 | 0.220 | |||
Hypotheses testing (inner model results).
| Hypotheses | β | t | p | Results |
|---|---|---|---|---|
| Direct-Paths | ||||
| H1—GHRM → BCB | 0.415 | 6.110 | 0.000 | Confirmed |
| H2—GHRM → OP | 0.270 | 3.780 | 0.000 | Confirmed |
| H3—OP → BCB | 0.293 | 3.899 | 0.000 | Confirmed |
| Indirect mediating Paths | ||||
| H4—GHRM → OP → BCB | 0.079 | 2.919 | 0.004 | Confirmed |
| Moderating Effects | ||||
| H5—GHRM * IGV → OP | 0.206 | 2.293 | 0.022 | Confirmed |
| H6—OP * IGV → BCB | 0.191 | 4.001 | 0.000 | Confirmed |
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; Azazz, Alaa M S 2
; Kooli, Chokri 3
; Fayyad, Sameh 4
1 Department of Management, College of Business Administration, King Faisal University, Al-Ahsaa 380, Saudi Arabia; Hotel Studies Department, Faculty of Tourism and Hotels, Suez Canal University, Ismailia 41522, Egypt
2 Department of Tourism and Hospitality, Arts College, King Faisal University, Al-Ahsaa 380, Saudi Arabia; Tourism Studies Department, Faculty of Tourism and Hotels, Suez Canal University, Ismailia 41522, Egypt
3 The Telfer School of Management, The University of Ottawa, 75 Laurier Avenue East, Ottawa, ON K1N 6N5, Canada;
4 Hotel Studies Department, Faculty of Tourism and Hotels, Suez Canal University, Ismailia 41522, Egypt