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Advocacy versus depart: How perceived organizational support influences employee well-being and shapes their intentions

Published online by Cambridge University Press:  08 November 2024

Catherine Viot
Affiliation:
IRGO, University of Bordeaux, Bordeaux, France
Laila Benraiss-Noailles*
Affiliation:
IRGO, University of Bordeaux, Bordeaux, France
*
Corresponding author: Laila Benraiss-Noailles; Email: laila.benraiss-noailles@u-bordeaux.fr
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Abstract

This study investigates the influence of perceived organizational support (POS) on employees’ intentions to recommend their employer or leave the organization. Based on social exchange theory, it explores how POS affects employee well-being and shapes behaviors such as loyalty and advocacy. An online survey gathered data from 604 French employees across various sectors, analyzing variables like POS, positive and negative well-being, and intentions to leave or recommend the employer. Structural equation modeling was used to examine the relationships among these variables and to test the mediating role of well-being. Results show that POS positively influences employee well-being. High POS is associated with improved positive well-being, which decreases the intention to leave and increases the intention to recommend. Similarly, reduced negative well-being linked to high POS lowers the desire to leave and lessens negative effects on recommendation intentions. The study confirms the mediating role of well-being between POS and employee intentions. The study provides new insights into the impact of POS on employee intentions by highlighting the pathways of positive and negative well-being. For human resource practices, strengthening POS is essential to boost employee retention and encourage positive behaviors, thereby enhancing the organization’s reputation and attractiveness.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press in association with Australian and New Zealand Academy of Management.

Introduction

As companies face increasing challenges in attracting talent through traditional channels like media advertisements or job platforms, they are turning more toward employee recommendations, which have emerged as a potent complementary recruitment method. Employees, including current, former, or prospective ones, now often evaluate their employers on various platforms, contributing ratings that significantly influence an organization’s public image (Carpentier & Van Hoye, Reference Carpentier and Van Hoye2021). These platforms have become crucial in shaping an employer’s reputation, as noted by Kollitz, Ruhle, & Wilhelmy (Reference Kollitz, Ruhle and Wilhelmy2022), making them a primary resource for job seekers evaluating potential workplaces.

This shift highlights the rising significance of word-of-mouth in recruitment strategies, where the act of employees recommending their employers is a powerful endorsement that conveys trust and authenticity. Barrow and Mosley (Reference Barrow and Mosley2005) link this phenomenon closely with employer branding, where positive internal perceptions are projected externally through employee advocacy. Unlike traditional advertising, these recommendations are seen as more genuine and are not perceived to stem from commercial incentives (Matos & Rossi, Reference Matos and Rossi2008), enhancing their appeal to job seekers who value transparency and honest reviews (Breaugh, Reference Breaugh2013; Van Hoye et al., Reference Van Hoye, Weijters, Lievens and Stockman2016).

The impact of such employee-driven endorsements on an employer’s image and their ability to attract high-quality candidates is well-established (Van Hoye et al., Reference Van Hoye, Weijters, Lievens and Stockman2016; Evertz, Kollitz, & Süß, Reference Evertz, Kollitz and Süß2021). Nevertheless, understanding what motivates employees to recommend their workplaces – or why some may hesitate – remains underexplored and necessitates further research to fully leverage this strategy.

Recognizing why certain employees act as brand ambassadors while others do not can help organizations tailor programs that encourage positive word of mouth. This strategic emphasis not only aids in building a robust employer brand but also nurtures an organizational culture that promotes the sharing of positive experiences. Such a culture is crucial for sustaining the effectiveness of word of mouth as a recruitment tool.

Extensive research confirms that recommendations often have a more significant impact than traditional recruitment messages (Breaugh & Starke, Reference Breaugh and Starke2000; Van Hoye & Lievens, Reference Van Hoye and Lievens2009; Collins & Stevens, Reference Collins and Stevens2002; Zottoli & Wanous, Reference Zottoli and Wanous2000). Therefore, these endorsements play a critical role in modern recruitment strategies, affecting both the organization’s attractiveness and the job application intentions and decisions of potential candidates (Van Hoye et al., Reference Van Hoye, Weijters, Lievens and Stockman2016; Nikolaou, Reference Nikolaou2014). This dual influence underscores the need for companies to understand and strategically use positive word of mouth (WOM)to enhance their recruitment processes and overall brand image.

To date, Human Resource Management (HRM)research has mainly focused on the effects of employer recommendations made by employees (Cable & Turban, Reference Cable, Turban, Cable and Turban2001; Collins & Stevens, Reference Collins and Stevens2002; Van Hoye & Lievens, Reference Van Hoye and Lievens2005, Reference Van Hoye and Lievens2007a). Research into the factors that encourage employees to recommend their employer is relatively rare, however (Uen, Ahlstrom, Chen, & Liu, Reference Uen, Ahlstrom, Chen and Liu2015; Uen, Peng, Shu-Yuan, & Chien, Reference Uen, Peng, Shu-Yuan and Chien2011). The literature identifies certain individual characteristics, such as social ties, expertise, and personality (Collins & Stevens, Reference Collins and Stevens2002; Van Hoye & Lievens, Reference Van Hoye and Lievens2005, Reference Van Hoye and Lievens2007a, Reference Van Hoye and Lievens2007b, Reference Van Hoye and Lievens2009) as determining factors in the intention to recommend an employer. Aside from these individual factors, we examine whether other levers specific to the professional environment, such as perceived organizational support (POS), encourage the intention to recommend an employer. We thus analyze the indirect effects of POS, considered as a probable antecedent to the intention to recommend and/or leave one’s employer, through the lens of well-being at work. We base our analysis on the theory of social exchange (Blau, Reference Blau1964), which enables us to understand employees’ behavior toward the organization that employs them in return for perceived work-related gains.

The present study enriches the existing literature by exploring the antecedents of employees’ intentions either to recommend their employer or to leave the organization. Existing studies (Cheng & Lin, Reference Cheng and Lin2017; Rasool, Wang, Tang, Saeed, & Iqbal, Reference Rasool, Wang, Tang, Saeed and Iqbal2021; Wattoo, Zhao, & Xi, Reference Wattoo, Zhao and Xi2018) frequently prioritize the examination of employees’ intention to leave, while largely neglecting the intention to recommend the employer, which remains a comparatively underexplored dimension in the literature. Specifically, this study highlights the role of POS in fostering such outcomes. When employees sense that their organization supports them, this perception enhances their well-being, which not only encourages them to advocate for their employer but also increases their loyalty and propensity to stay with the company. This dual effect of POS underscores its importance as a strategic lever in human resource practices and employee retention policies.

Overall, in comparison with the literature, our research proposes both a dual focus on behavioral intentions and a two-dimensional approach regarding well-being. Indeed, with regard to behavioral intentions, our research explores both employees’ intention to recommend their employer and their intention to leave. This bivalent approach enables us to better understand the dynamics of retention and promotion within an organization. In addition, the approach to well-being as a bi-dimensional construct enables us to distinguish between positive and negative well-being. The effects of POS are thus analyzed separately on the positive and negative well-being of employees. This distinction adds nuance to the impact of the POS and provides more detailed insights into the different aspects of well-being at work, in contrast to existing studies which take a more holistic view of well-being.

Our managerial contributions relate to issues of attractiveness. The beneficial effects of recommendations have been widely demonstrated in the marketing context (Bone, Reference Bone1995; Brown & Reingen, Reference Brown and Reingen1987; Ward & Reingen, Reference Ward and Reingen1990). Recommendations by loyal customers who act as ambassadors offer an effective way of recruiting new customers. Similarly, a current employee’s recommendation of an employer can be an effective way of encouraging potential employees to apply (Cable & Turban, Reference Cable, Turban, Cable and Turban2001). Knowing what motivates employees to recommend their employer is therefore a crucial issue for organizations, particularly in sectors and/or professions where recruitment is a major challenge. The issue is of growing interest at present, not only due to difficulties recruiting staff, but also because of the widespread use of social networks when looking for a job (Benraiss-Noailles & Viot, Reference Benraiss-Noailles and Viot2012). To compensate for information asymmetry, candidates seek information directly from current employees, notably on specialist platforms such as Choose my company, Indeed, Glassdoor, etc. This form of recruitment communication, however, represents a potential risk for the company, as it is beyond its control. While they cannot control it directly, organizations nonetheless need to create the right conditions to encourage employees to promote their employer.

The article is organized into four parts. First, the theoretical and conceptual frameworks are presented, followed by the methodology. We then present the results, followed by a discussion.

Employee’s intentions toward the employer through social exchange theory

Social exchange theory

Social exchange theory (Blau, Reference Blau1964) examines social behavior within the framework of interactions between two agents who utilize a cost-benefit analysis to assess the risks and benefits associated with maintaining a relationship. According to this theory, if one of the agents perceives a lack of reciprocity, where the compensation obtained is perceived to be less than the cost of the relationship, the relationship may ultimately be terminated or abandoned. The theory of social exchange has been effectively and successfully applied to employment relations, as it provides a deeper understanding of certain employee behaviors, such as loyalty and commitment (Koomson, Reference Koomson2022). For instance, employees are more likely to consider staying with an organization in return for work-related benefits or gains (Arnold, Reference Arnold1990). This theory helps elucidate why employees might choose to remain loyal to an employer who provides them with sufficient rewards and support.

Social exchange theory also helps explain why organizational support (Eisenberger, Huntington, Hutchinson, & Sowa, Reference Eisenberger, Huntington, Hutchinson and Sowa1986) leads to positive employee responses. When employees perceive that the organization supports them and values their contributions, they develop positive feelings about their work and a positive attitude toward the organization that employs them (Tsarenko et al., Reference Tsarenko, Leo and Tse2018). This perception fosters a sense of appreciation and loyalty. If employees are satisfied and accept the valence of support from their organization, they are much more likely to continue the relationship (Arasanmi & Krishna, Reference Arasanmi and Krishna2019). Additionally, the acknowledgment of their efforts by the organization enhances their sense of belonging and commitment, which further solidifies their desire to remain with the employer. As a result, the reciprocity established through POS not only motivates employees but also strengthens their bond with the organization, leading to long-term positive outcomes for both parties involved.

Organizational support as a lever for well-being at work

Organizational support refers to the degree to which an employer is interested in its employees’ professional well-being and appreciates their efforts and personal commitment (Authors, Reference Viot and Benraiss-Noailles2019; Eisenberger et al., Reference Eisenberger, Huntington, Hutchinson and Sowa1986). POS is the general belief that the organization cares about the contributions and well-being of its employees (Eisenberger et al., Reference Eisenberger, Huntington, Hutchinson and Sowa1986). It depends on the perceived sincerity and frequency of the employer’s goodwill gestures toward employees, over and above contractual obligations (Aselage & Eisenberger, Reference Aselage and Eisenberger2003).

Employees who perceive a high level of support experience greater job satisfaction and reduced stress (Eder & Eisenberger, Reference Eder and Eisenberger2008). POS also increases employees’ commitment and contributions to their employer (Wayne et al., Reference Wayne, Shore and Liden1997; Eisenberger, Cummings, Armeli, & Lynch, Reference Eisenberger, Cummings, Armeli and Lynch1997), which can lead to improved organizational performance. Research highlights that employee well-being is a critical factor in determining engagement and retention. Workers who experience higher levels of well-being, particularly in supportive environments, are more likely to remain committed to their employer and act as advocates for the organization. Conversely, a lack of perceived support can diminish well-being and increase turnover intentions (Rasool et al., Reference Rasool, Wang, Tang, Saeed and Iqbal2021).

POS plays a crucial role in enhancing employee well-being, which subsequently impacts performance and retention. Employees who perceive high levels of support from their organization demonstrate higher productivity and are more inclined to advocate for their employer (Setyoko & Kurniasih, Reference Setyoko and Kurniasih2022). This underscores the importance of organizational support as a strategic lever for improving employee outcomes.

Finally, POS contributes significantly to employee well-being (Authors, Reference Viot and Benraiss-Noailles2019; Caesens, Stinglhamber, & Ohana, Reference Caesens, Stinglhamber and Ohana2016). According to organizational support theory (Kurtessis et al., Reference Kurtessis, Eisenberger, Ford, Buffardi, Stewart and Adis2015), by meeting employees’ socioemotional needs, POS fosters a self-enhancement process, leading to improved subjective well-being. Conversely, when organizations fail to acknowledge employees’ contributions, perceptions of organizational support decline (Authors, Reference Viot and Benraiss-Noailles2019; Eisenberger et al., Reference Eisenberger, Cummings, Armeli and Lynch1997), potentially having a detrimental effect on well-being at work.

Employee well-being is a subjective global judgment of the quality of work experiences (Turban & Yan, Reference Turban and Yan2016) which describes the overall quality of how an employee lives and functions at work (Guest, Reference Guest2017). Warr (Reference Warr1990) attributes two dimensions to the concept, one positive (positive well-being) and the other negative (negative well-being).

Unsurprisingly, organizational support is linked to well-being at work. For Guerrero and Herrbach (Reference Guerrero and Herrbach2009), the way in which an organization manages its human resources reflects the way in which an employer takes its employees’ well-being into account. Indeed, when employees perceive support from their employer, it signals the extent to which the latter values their contributions and cares about their well-being (Aselage & Eisenberger, Reference Aselage and Eisenberger2003).

This leads us to put forward two hypotheses.

Hypothesis 1: Employee’s perceived organizational support has a positive impact on employees’ positive well-being at work.

Hypothesis 2: Employee’s perceived organizational support has a negative impact on employees’ negative well-being at work.

The effects of employee well-being on intentions toward the employer

The intention to leave an employer is defined as the employee’s plan to look for another job because they are no longer satisfied with the current work environment (Aliyu, Muktar, Yusoff, & Ahmad, Reference Aliyu, Muktar, Yusoff and Ahmad2014). According to Greenawald (Reference Greenawald2019), the decision to leave is often not spontaneous, but builds up gradually over time. The build-up period can provide a window, which spans a continuum between intention and action, that companies can use to dissuade an employee from leaving. This interval gives employers an opportunity to intervene and motivate the employee to decide to stay. The intention to leave thus provides companies with a reasonable gauge for predicting actual departure (Cheng, Bartram, Karimi, & Leggat, Reference Cheng, Bartram, Karimi and Leggat2016).

Several studies argue that the intention to leave an employer is linked to the employee’s well-being at work (Cooper, Wang, Bartram, & Cooke, Reference Cooper, Wang, Bartram and Cooke2019; Ho & Kuvaas, Reference Ho and Kuvaas2020; Ogbonnaya & Messersmith, Reference Ogbonnaya and Messersmith2019). If an employee feels positive well-being at work, it reduces his or her intention to leave the employer (Chicu et al., Reference Chicu, Ryan and Mirela2016).

Our research proposition is based on a dual conceptualization of well-being (positive and negative well-being). The moderating effect of well-being distinguishes our study from the existing literature, as we examine mediation across two dimensions: positive and negative well-being. In the aforementioned studies, particularly Cheng and Lin (Reference Cheng and Lin2017), employee well-being is considered as a singular, global construct. Attributing this observation to the two dimensions of well-being (i.e., positive and negative), we formulate the following hypotheses:

Hypothesis 3: Employee’s positive well-being at work has a negative impact on the intention to leave an employer.

Hypothesis 4: Employee’s negative well-being has a positive impact on the intention to leave an employer.

The intention to recommend the company is a form of positive WOM (East, Hammond, Lomax, & Robinson, Reference East, Hammond, Lomax and Robinson2005; Mangold, Miller, & Brockway, Reference Mangold, Miller and Brockway1999). It is one of the oldest and most important channels of interpersonal information exchange (Ismagilova, Dwivedi, Slade, & Williams, Reference Ismagilova, Dwivedi, Slade, Williams, E. Ismagilova, Y. K. Dwivedi, E. Slade and M. Williams2017). With the emergence of digital social networks, brand and/or employer recommendations are of even greater interest.

Applied to the field of Human Resource (HR), the intention to recommend is an effective source of information for external recruitment and an organization’s attractiveness (Cable & Turban, Reference Cable, Turban, Cable and Turban2001; Collins & Stevens, Reference Collins and Stevens2002; Van Hoye & Lievens, Reference Van Hoye and Lievens2005, Reference Van Hoye and Lievens2007a). Recommendation is a powerful lever for the employer’s brand (Charbonnier-Voirin & Vignolles, Reference Charbonnier-Voirin and Vignolles2016). ‘If an employee is proud of their employer, they spontaneously recommend them as a reference, becoming ambassadors capable of informing and convincing potential candidates to join their organization’ (Charbonnier-Voirin & Vignolles, Reference Charbonnier-Voirin and Vignolles2016, p. 169). Through their recommendations, employees determine the credibility of the messages communicated by the company (Berthon, Ewing, & Hah, Reference Berthon, Ewing and Hah2005).

The HR literature mainly deals with the effects of recommendations. Recommendations are perceived as authentic and influential when they come from a well-informed source that a potential job candidate might consider credible (Collins & Han, Reference Collins and Han2004; Saks, Reference Saks, Evers, Anderson and Voskuijl2005; Zottoli & Wanous, Reference Zottoli and Wanous2000). Employee recommendations thus have a positive effect on recruitment performance, regardless of the phase considered. The beneficial effects are observed before recruitment (quantity and quality of candidates) and continue throughout the relationship (job satisfaction, professional performance, and reduction in voluntary departures) (Breaugh & Starke, Reference Breaugh and Starke2000). Recommendations of the employer by current employees thus offer a useful recruitment tool for boosting the employer’s attractiveness in the early stages of recruitment (Van Hoye & Lievens, Reference Van Hoye and Lievens2007a, Reference Van Hoye and Lievens2007b).

We noted that POS is an antecedent of well-being at work, which in turn translates into positive behavior on the part of employees. However, the literature linking well-being to intention to recommend is scarce, both in marketing and in HRM. The link has been studied in the context of services by Abdalla, Altaf, Trocooli and Trinta (Reference Abdalla, Altaf, Trocooli and Trinta2012), who show that well-being positively influences the intention to recommend a brand both directly and indirectly via satisfaction and perceived service quality. Transposing the results of this study carried out in a marketing context to the HR context, we postulate that employee well-being can encourage the latter to recommend their employer and distinguish between the two dimensions of well-being.

Hypothesis 5: Employee’s positive well-being at work has a positive impact on the intention to recommend the employer.

Hypothesis 6: Employee’s negative well-being at work has a negative impact on the intention to recommend the employer.

Well-being at work as a mediator between POS and employee’s intentions

Employees who perceive strong support from their organization experience higher levels of subjective well-being (Authors, Reference Viot and Benraiss-Noailles2019; Caesens et al., Reference Caesens, Stinglhamber and Ohana2016). Conversely, a lack of organizational support can lead to a deterioration in employee well-being. Additionally, employee well-being influences their intentions (Cooper et al., Reference Cooper, Wang, Bartram and Cooke2019; Ho & Kuvaas, Reference Ho and Kuvaas2020; Ogbonnaya & Messersmith, Reference Ogbonnaya and Messersmith2019). This causal relationship between POS, which results from human resource management practices, well-being, which is the subjective and psychological consequence of POS on employees, and behavioral intentions (such as leaving the employer or recommending it), suggests the existence of a mediating effect of well-being. The mediation of employee well-being we propose differs from that considered in the existing literature (Rasool et al., Reference Rasool, Wang, Tang, Saeed and Iqbal2021; Wattoo et al., Reference Wattoo, Zhao and Xi2018). While Rasool et al. (Reference Rasool, Wang, Tang, Saeed and Iqbal2021) explore the mediating role of work-family facilitation and work-family conflict between POS and employee well-being, our article investigates how well-being serves as a mediator between POS and employees’ behavioral intentions. Wattoo et al. (Reference Wattoo, Zhao and Xi2018) similarly examine the mediating role of work-family facilitation and conflict in the relationship between POS and employee well-being, without explicitly distinguishing between positive and negative well-being.

In line with Brunetto et al. (Reference Brunetto, Xerri, Shriberg, Farr-Wharton, Shack-Lock, Newman and Dienger2013) who studied the effect of workplace relations in Australian and US hospitals, and whose results suggest that well-being is a predictor of employee’s intentions, we formulate four hypotheses for the mediation of well-being between POS and employee intentions. These hypotheses aim to clarify the mediating role of well-being in the relationship between POS and employee intentions.

Employees who feel supported by their organization are more likely to experience positive well-being, which reduces their intention to leave the company. Conversely, insufficient organizational support can increase feelings of negative well-being, thereby increasing turnover intentions.

Hypothesis 7: Employee’s perceived organizational support has a negative indirect effect on the intention to leave the employer, through positive well-being.

Hypothesis 8: Employee’s perceived organizational support has a negative indirect effect on the intention to leave the employer, through negative well-being.

Employees who feel supported by their organization are more likely to experience positive well-being, which reduces their intention to leave the company. Conversely, insufficient organizational support can increase feelings of negative well-being, thereby increasing turnover intentions.

Hypothesis 9: Employee’s perceived organizational support has a positive indirect effect on the intention to recommend the employer, through positive well-being.

Hypothesis 10: Employee’s perceived organizational support has a positive indirect effect on the intention to recommend the employer, through negative well-being.

The conceptual model and assumptions pertaining to direct effects (assumptions Hypothesis 1 to Hypothesis 6) are shown in Fig. 1.

Figure 1. Conceptual model and research hypotheses.

Methodology

Measurement of variables

The variables were measured using previously published scales (Appendix 1). POS was assessed using the seven-item scale developed by Coyle-Shapiro and Conway (Reference Coyle-Shapiro and Conway2005). They selected the seven items with the highest factorial loadings from Eisenberger et al.’s original 36-item scale (Reference Eisenberger, Armeli, Rexwinkel, Lynch and Rhoades2001). In this measurement scale, six items reflect positive valence (for example, ‘My employer cares about my opinion’, ‘My employer considers my goals and values’), while the seventh item indicates the absence of POS (‘My employer shows very little concern for me’).

For well-being at work, we adopted Warr’s (Reference Warr1990) two-dimensional conceptualization, which includes a positive factor (positive well-being) and a negative factor (negative well-being). Research conducted by Warr (Reference Warr, Kahneman, Diener and Schwarz1999, Reference Warr2007) is highly influential in the field of employee well-being (Pradhan & Hati, Reference Pradhan and Hati2022). Warr conceptualized employee well-being from the standpoint of overall employee experiences and specific job-related aspects. Job-specific well-being is considered a subset of domain-specific well-being, referring to individuals’ feelings of well-being in relation to their employment. Warr (Reference Warr, Kahneman, Diener and Schwarz1999, Reference Warr2007) highlighted three contrasting dimensions: (a) displeasure and pleasure, (b) anxiety and comfort, and (c) depression and enthusiasm. He posited that most well-being research utilizes these dimensions as dependent variables. Displeasure/pleasure is one of the affective dimensions, related to general negative and positive work-related emotions. While both anxiety and comfort encompass states of mild pleasure, they differ in terms of mental stimulation levels, with anxiety being high and comfort being low in mental stimulation. The third dimension, depression and enthusiasm, ranges from extremes of positive motivation to sadness. Several researches (Cotton & Hart, Reference Cotton and Hart2003; Warr, Reference Warr, Kahneman, Diener and Schwarz1999) argue that well-being measures are crucial for capturing the cognitive and affective experiences of employees at work, along with all their nuances, complexities, and variations. Warr’s scale facilitates this measurement.

In contrast to some measurement scales recently employed (Ahmed et al., Reference Ahmed, Zehou, Raza, Qureshi and Yousufi2020; Rasool et al., Reference Rasool, Wang, Tang, Saeed and Iqbal2021), the Warr’s (Reference Warr, Kahneman, Diener and Schwarz1999) scale enables an assessment of well-being independent of POS, the latter being separately measured in our study. Other scales, which purport to measure well-being, actually include items that assess POS. This is exemplified by the scale recently utilized by Ahmed et al. (Reference Ahmed, Zehou, Raza, Qureshi and Yousufi2020)and Rasool et al. (Reference Rasool, Wang, Tang, Saeed and Iqbal2021). One of the items is, in fact, phrased as follows: ‘When I am stressed, I feel I have the support available for help.’ This item, rather than measuring well-being, actually assesses POS in response to stress.

This scale comprises 12 items which, depending on the formulation, can assess both work-related and non-work-related well-being. We used the work-related version. Respondents rated the frequency of their experiences of certain feelings over the previous 2 weeks on a scale ranging from (1) ‘never’ to (6) ‘always’. This measurement scale is considered bi-dimensional: six items have positive valence (Calm, Contented, Relax, Cheerful, Enthusiastic, and Optimistic), while the other six present negative valences (Tense, Uneasy, Worried, Depressed, Gloomy, and Miserable).

One way to address the issue of employee retention is to ask employees about their intention to leave the company. The intention to quit, considered the best indicator of overt withdrawal behavior, reflects an employee’s desire to leave the organization voluntarily (Moore, Reference Moore2000). We used Moore’s (Reference Moore2000) four-item scale to measure the intention to leave the company. Two items on this scale refer to the intention to leave one’s employer (for example, ‘I will probably look for a job at a different company in the next year’) and two items reflect the intention to remain loyal to one’s employer (for example, ‘I will be with this company five years from now’). Lastly, intention to recommend the company was measured using a single-item scale derived from the question proposed in the Net Promoter Score (Reichheld, Reference Reichheld2003): ‘I intend to recommend my company to my friends and family,’ with responses given on a 6-point Likert scale (from 1 ‘strongly disagree’ to 6 ‘strongly agree’), as previously administered by Schmitt, Meyer and Skiera (Reference Schmitt, Meyer and Skiera2012).

Except for well-being, which comprised two dimensions (positive well-being and negative well-being), the measurement scales used in this research were unidimensional. Since some measurement scales included items with opposite valences, a reversal of the obtained scores was necessary once the data were collected. This reversal was performed for one item on the POS scale and for two items on the intention to leave the current employer scale. Respondents indicated their level of agreement on a 6-point Likert scale (from 1 ‘strongly disagree’ to 6 ‘strongly agree’).

Sample and data collection

Employees residing in France were invited to complete an online questionnaire, regardless of their occupation, industry sector, or company size (N = 604). The measures of the constructs included in the model were obtained from the same individuals (employees). To control for ex-ante common method bias, we followed the recommendations of Podsakoff et al. (Reference Podsakoff, MacKenzie, Lee and Podsakoff2003). Firstly, we minimized such biases by guaranteeing the respondents’ anonymity, thus reducing evaluation apprehension bias. Secondly, the study employed two versions of the questionnaire, each with a different order of items measuring a given construct, thus diminishing consistency and implicit theory biases. Respondents were randomly assigned to one of the two versions.

In terms of age distribution, the majority of respondents were between 25 and 55 years old. Most (92.7%) had fixed-term contracts (Appendix 2). The level of education was relatively high, with over 57% of respondents holding a Master’s degree 1 or 2, and 19% having qualifications higher than a 5-year degree. This high level of education is consistent with executive status, which dominates the sample. Professional experience was also relatively high, with 52.5% of respondents having over 15 years of professional experience, and only 21.2% having less than 5 years’ experience, which is consistent with the age distribution of the respondents. Men were over-represented in the sample (57.8%), exceeding the proportion found in the French population by INSEE (47.5% according to INSEE, 2021). Nearly a third of the surveyed individuals (31.4%) were employed by companies with fewer than 100 employees, and just over a third (37.2%) by companies with more than 500 employees. The sample is predominantly composed of the following sectors: healthcare (15%), education and training (10%), heavy industry (9%), banking, finance, and insurance (8%), public administration (7%), and business services and retail (6% each).

Statistical analysis

The analyses were conducted in two stages. We first assessed the validity and reliability of the scales through exploratory factor analysis using SPSS software, followed by confirmatory factor analysis using AMOS software. Subsequently, we tested the causal model and mediations using structural equation modeling with AMOS.

Results

Measurement model

Although we used existing scales, we first verified their structure using principal component analyses. For the POS, principal component analysis confirmed unidimensionality with an explained variance of 72.74%. The Kaiser–Meyer–Olkin index (0.935) and Bartlett’s test (p < .001) indicated satisfactory results confirming the correlations among the items, a prerequisite for principal component analysis. Communalities ranged between 0.566 and 0.824. Regarding the well-being measurement scale, to achieve the expected two-dimensional structure, three items (calm, contented, and tense) were excluded from further analyses. These items were initially correlated with a third, difficult-to-interpret factor. Once these items were removed, the Kaiser–Meyer–Olkin index (0.891) and Bartlett’s test (p < .001) yielded acceptable results, with communalities above 0.5. The variance explained by the two factors was 68.38%. For the intention to leave the employer construct, the explained variance was 82.9%, the Kaiser–Meyer–Olkin index was 0.809, and Bartlett’s test of sphericity confirmed the correlations among the items (p < .001). Communalities, representing the amount of variance an original variable shares with all other variables included in the analysis, were well above the required threshold of 0.5 (between 0.782 and 0.868). Principal component analysis confirmed unidimensionality. The reliability of the measures, as indicated by Cronbach’s α, ranged between 0.84 and 0.93 (Table 1).

Table 1. Correlation matrix, composite reliability, and square root of average variance extracted

α = Cronbach’s alpha; CR = composite reliability; AVE = average variance extracted; M = means.

Bold numbers on the diagonal represent the square root of AVE.

** p < .01.

We then employed structural equations modeling, using AMOS, to verify the quality of the measurement model. The measurement model fitted the data well: root mean square error of approximation (RMSEA) = 0.055; comparative fit index (CFI) = 0.966; standardized root mean residual (SRMR) = 0.0324; χ2 = 513 (df = 180, p < .001).

Internal reliability, composite validity, and discriminant validity were established for all the constructs (Table 1). Internal reliability, measured by Jöreskog’s rho and interpreted as Cronbach’s α, is considered acceptable between 0.6 and 0.7, and satisfactory to good between 0.7 and 0.9. Values above 0.95 are problematic as they indicate item redundancy (Hair, Black, Babin, & Anderson, Reference Hair, Black, Babin and Anderson2018). The scales therefore show good internal consistency, with indicators between 0.84 and 0.94 (Table 1).

Convergent validity,Footnote 1 assessed through average variance extracted,Footnote 2 exceeded the recommended threshold of 0.5 for all latent variables. Convergent validity corresponds to the average variance extracted, which should be greater than 0.5, indicating that the latent variable explains more than half of the variance of its indicators. All the latent variables demonstrated average variance extracted values greater than 0.5, ranging from 0.51 for positive well-being to 0.75 for intention to leave the employer (Table 1). As intention to recommend the employer is measured by a single item, Cronbach’s α and composite validity are not reported in the table.

For discriminant validity,Footnote 3 we used Fornell and Larcker (Reference Fornell and Larcker1981) method, according to which the square root of average variance extracted must be greater than the correlations between the constructs. This condition is well met, as evidenced by the values reported in Table 1. Finally, all standardized factor weights of the measurement model were found to be significant.Footnote 4

These successive statistical analyses confirm the validity and reliability of the measurement model. Validation of the measurement model was nonetheless accompanied by the removal of certain items from the well-being scale, which were correlated with a third factor that was difficult to interpret.

The mean values and standard deviations for each construct as shown in Table 1, indicate that negative well-being is relatively low compared to the means of the other constructs (M negative well-being = 2.20; σ = 0.88). Conversely, intention to recommend the employer is relatively high (M Rec. = 4.2; σ = 1.32).

As the measures of the constructs included in the model are derived from the same persons (employees), it is advisable to check for the presence of common variance bias. Following the guidelines of Podsakoff et al. (Reference Podsakoff, MacKenzie, Lee and Podsakoff2003), we carried out the Harman’s single-factor test (Harman, Reference Harman1976). The variance explained by the first factor (48%) falls below the recommended threshold of 50%.

Testing the model and indirect effects

Directs and indirect effects were examined using structural equation modeling with AMOS software. Testing indirect effects with Amos requires specifying direct relationships between X and Y, that is the relationship between POS and intention to leave/intention to recommend the employer, although we did not hypothesize a direct effect between POS and intention to recommend and/or leave the company. Using a bootstrap method (N = 5,000), the AMOS software provided confidence intervals and a P-value for each estimated parameter.

The adjustment indices (c 2 = 617; 182 df; p < .001; c 2/df = 3.39; SRMR = 0.0556; CFI = 0.955; RMSEA = 0.063) are in line with generally accepted standards. The model fits the data well (Fig. 2).

Figure 2. Results.

All of the model’s estimated parameters are significant (Appendix 3). POS has a positive influence on positive well-being (λ = 0.710**, p = .003) and a negative influence on negative well-being (λ = −0.591**, p = .005). Hypotheses 1 and 2 are therefore validated. Positive well-being has a positive influence on intention to recommend (λ = 0.264**, p = .003) and a negative influence on intention to leave (λ = −0.237**, p = .004). Hypotheses 3 and 5 are therefore also validated. Negative well-being negatively influences intention to recommend the company (λ = −0.102**, p = .005) and positively influences the intention to leave the employer (λ = 0.290**, p = .005), giving support to both Hypotheses 4 and 6.

For Hypotheses 7–10, which propose an indirect effect of POS on the responses of current employees, we conducted specific mediations tests using AMOS software.Footnote 5 We therefore used the ‘Edit Specific Estimand Indirect Effects’ function provided by AMOS, as suggested by Collier (Reference Collier2020). We first named the parameters and defined the four indirect effects corresponding to Hypotheses 7–10. This step was crucial as without it, AMOS would only provide the total indirect effect of POS on the intention to recommend and the intention to leave dependent variables, without distinguishing between the two mediators (positive and negative well-being). The results confirm that positive and negative well-being indeed mediate the relationship between POS and the intention to leave the company and/or to recommend it (Table2).

Table 2. Specific indirect effects

POS = perceived organizational support; P/N WB = positive/negative well-being; IR = intention to recommend; IL = intention to leave.

* p < .05, **p < .01.

The POS demonstrates a negative indirect effect on the intention to leave the employer (β = −0.189; p = .007) and a positive indirect effect on the intention to recommend the employer (β = 0.221; p = .002) through positive well-being, supporting Hypotheses 7 and 8, respectively. Furthermore, the POS has a negative indirect effect on the intention to leave the employer (β = −0.193; p = .004) and a positive indirect effect on the intention to recommend the employer (β = 0.071; p = .011) through negative well-being, supporting Hypotheses 9 and 10 respectively.

The indirect effects of POS on the intention to recommend and/or to leave the employer are statistically significant (Table 2). However, the direct effects of POS on the intention to recommend (β = 0.490; p = .004) and on the intention to leave the employer (β = −0.213; p = .002) are also significant (Table 3). These results confirm the mediation of well-being at work, albeit partial, and thus provide support for Hypotheses 7–10.

Table 3. Direct and total effect

POS = perceived organizational support; IR = intention to recommend; IL = intention to leave.

** p < .01

Discussion

These results confirm the significant role of POS in influencing both positive and negative well-being, thereby shaping employee intentions to either leave or recommend their employer. Similar to the studies conducted by Cheng and Lin (Reference Cheng and Lin2017), Rasool et al. (Reference Rasool, Wang, Tang, Saeed and Iqbal2021), and Wattoo et al. (Reference Wattoo, Zhao and Xi2018), we examine the influence of POS on employee behavior, exploring the mediating role of workplace well-being in this relationship. However, these studies primarily focus on turnover intentions, while our article also addresses employees’ intentions to recommend their employer. The findings are consistent with prior theoretical frameworks discussed in the literature, particularly social exchange theory (Blau, Reference Blau1964), which posits that the perceived support from an organization enhances employees’ sense of reciprocity. This sense of reciprocity, in turn, manifests through increased commitment and advocacy behaviors, as demonstrated in the present study’s results. Furthermore, the robustness of these findings, verified through structural equation modeling and the use of AMOS software, aligns with previous research methodologies that employed similar statistical rigor to assess indirect effects (Caesens et al., Reference Caesens, Stinglhamber and Ohana2016; Eisenberger et al., Reference Eisenberger, Cummings, Armeli and Lynch1997). The use of bootstrapping for mediation analysis further underscores the validity of our model, providing deeper insight into how well-being mediates the relationship between POS and employee outcomes.

Theoretical contributions

Our research has three theoretical contributions: the first relates to the organizational benefits, the second to the employee benefits, and the last to the knowledge enhancement resulting from using a dual conceptualization of subjective well-being.

Firstly, drawing on social exchange theory (Blau, Reference Blau1964) and due to the reciprocity norm in the workplace (Arnold, Reference Arnold1990), our findings significantly contribute to the theory of organizational support (Kurtessis et al., Reference Kurtessis, Eisenberger, Ford, Buffardi, Stewart and Adis2015). The results confirm that POS fosters a sense of obligation among employees to reciprocate the organization’s valuation and care. This sense of obligation manifests in beneficial behaviors such as increased loyalty and advocacy for the organization. When employees perceive that their organization supports them, their subjective positive well-being increases, which in turn encourages them to recommend their employer and to remain loyal. These results support and reinforce the findings of Caesens et al. (Reference Caesens, Stinglhamber and Ohana2016); Kurtessis et al. (Reference Kurtessis, Eisenberger, Ford, Buffardi, Stewart and Adis2015), and Tsarenko et al. (Reference Tsarenko, Leo and Tse2018). Conversely, when employees perceive insufficient support from their organization, there is a substantial risk that their overall well-being will deteriorate. According to Warr’s conceptualization, this deterioration can simultaneously manifest as a significant decrease in positive well-being and a notable increase in negative well-being. This dual impact can consequently lead to a higher risk of turnover, as employees become more likely to leave the organization. Furthermore, there is a corresponding reduction in their propensity to recommend the employer to others, reflecting a diminished level of satisfaction and engagement with the organization.

Secondly, beyond the benefits for the organization, our research also contributes to the literature by showing that a high level of POS is beneficial for employees in terms of subjective well-being. Our findings make significant theoretical contributions at the individual level by demonstrating that POS directly influences both the positive and negative dimensions of employee well-being, as described by Warr (Reference Warr1990). By meeting the socio-emotional needs of employees, POS enhances their quality of work life, thereby strengthening their loyalty and commitment to the organization, which aligns with the work of Turban and Yan (Reference Turban and Yan2016). These new insights enrich the understanding of workplace well-being by highlighting the importance of organizational support in improving employee well-being.

A final key contribution of our research lies in the central role of employee well-being in the employer-employee relationship. The contributions are even greater given that we considered two dimensions of employee well-being – positive and negative well-being. Although the results confirm a direct effect of POS on the intention to leave the employer and on the intention to recommend it, they also show a reinforcement of POS influence via employee well-being. The POS itself acts as a turnover reducer, but this effect is reinforced when the employee feels a high level of positive well-being. Similarly, by reducing negative well-being, POS helps reducing turnover. POS is also an important driver of employee advocacy. Once again, the influence of POS is direct, but gains in intensity when positive well-being is high. In the same way, POS tends to reduce the negative well-being felt by the employee, hence diminishing the deleterious effects of the latter in terms of intention to quit and/or to recommend one’s own employer.

From a theoretical point of view, our research offers arguments that demonstrate the role of POS and well-being on the intention to recommend the employer. As little research has previously focused on the links between these three variables, identifying the antecedents of recommendation is crucial.

Managerial contributions

The findings have promising practical implications for organizations. Firstly, companies can learn from this research how to naturally encourage employees’ recommendation behaviors. Since POS and employee well-being are effective drivers of employee ambassadorship, employers have a strong interest in acting in a way that gives employees the impression that the organization they work for cares for and values them. Post-pandemic studies have shown that POS significantly enhances both employee well-being and performance, suggesting that HR policies should prioritize fostering supportive work environments. By ensuring that employees feel valued and supported, organizations can reduce turnover and enhance advocacy behaviors (Setyoko & Kurniasih, Reference Setyoko and Kurniasih2022). Human resources policies must therefore recognize individual efforts and reward personal investment to maintain high levels of POS, thereby contributing to employee well-being. Well-being is an essential factor if the organization wishes to encourage employees to adopt behaviors that benefit the organization.

Secondly, when employees feel supported, their work experience tends to improve, leading to increased satisfaction and engagement.

Furthermore, well-supported and satisfied employees can also serve as external ambassadors for the organization, attracting quality talent and helping to establish a solid reputation in the industry. Companies could thus benefit from a more diverse and higher-quality pool of candidates, reducing the costs and efforts associated with recruitment.

Limitations and suggestions for future research

Well-being at work in the present research is considered to be a fixed and stable state. However, it is changeable and can be subject to fluctuation (Shi et al., Reference Shi, Gordon and Tang2021). Affective Events Theory asserts that work environment characteristics trigger diverse work events (Weiss & Cropanzano, Reference Weiss, Cropanzano, Staw and Cummings1996), leading to different work attitudes in employees through shifting affective reactions to work events (Shi et al., Reference Shi, Gordon and Tang2021).

Our study focuses on the intention to share a positive message about one’s employer. It would also be interesting to consider the effects of POS and well-being on negative feedback about one’s employer. This is a sensitive issue, as dissatisfied employees may fear employer reprisals.

In this study, we identified two antecedents of the intention to recommend one’s employer (POS and employee well-being at work). To hone the findings further, it might be interesting, in future research, to introduce the different forms (ratings, open comments, testimonials) and channels of recommendation (online or offline) available to employees today. Some studies have taken this differentiation into account, but for a different purpose, as in a comparison of the effectiveness of WOM and testimonials, for instance (Van Hoye & Lievens, Reference Van Hoye and Lievens2007b). A potential antecedent of employee advocacy would be the perception of a high fit between the person and the organization (Chatman, Reference Chatman1991). This fit could play a key role in today’s world. Some people are looking for an organization whose values are congruent with their own, particularly when it comes to Corporate Social Responsibilityissues.

An additional promising extension of our study is to investigate the relationship between employer brand equity and employee recommendation. It would be interesting to examine how employees’ perceptions of each dimension of employer brand influence their willingness to recommend the company, and how well-being acts as a mediator in this relationship.

Conclusion

Grounded in social exchange theory (Blau, Reference Blau1964), our research confirms that POS significantly influences both the positive and negative aspects of employee well-being, which in turn shape employees’ intentions to either recommend their employer or leave the organization. When employees perceive strong organizational support, they experience higher levels of positive well-being, which fosters loyalty and increases their likelihood of recommending the organization to others. Conversely, insufficient support heightens negative well-being, increasing turnover intentions and reducing advocacy. This dual pathway underscores the necessity for organizations to create supportive environments to maintain high levels of employee well-being and capitalize on its positive outcomes.

In alignment with the findings of Cheng and Lin (Reference Cheng and Lin2017), Rasool et al. (Reference Rasool, Wang, Tang, Saeed and Iqbal2021), and Wattoo et al. (Reference Wattoo, Zhao and Xi2018), a high level of POS reduces turnover intentions by improving well-being. Positive well-being strengthens the intention to recommend the employer, while negative well-being diminishes this intention. The direct and indirect impact of POS on turnover and advocacy behaviors emphasizes the importance of supporting employee well-being to foster positive workplace behaviors.

Our study further contributes to social exchange theory by demonstrating how POS shapes employee well-being, which, in turn, influences intentional behaviors. For organizations, it is essential to develop strategies to increase POS, such as recognizing employee efforts and implementing support programs. Promoting a favorable work environment that addresses employee needs can reduce turnover and increase positive recommendations, thereby enhancing the employer’s brand.

In contrast to existing studies (Cheng & Lin, Reference Cheng and Lin2017; Rasool et al., Reference Rasool, Wang, Tang, Saeed and Iqbal2021; Wattoo et al., Reference Wattoo, Zhao and Xi2018), which primarily focus on turnover intention, our research expands the scope by also examining employee advocacy. A major contribution of this study is the exploration of employee advocacy and its antecedents. Our research shows that POS and employee well-being are significant predictors of advocacy behaviors. Employees who perceive strong organizational support and experience positive well-being are more likely to act as advocates for their organization, promoting it positively to potential recruits and other external stakeholders. This advocacy not only strengthens the employer’s brand but also enhances the overall attractiveness of the organization, making it a preferred choice for top talent. Understanding these antecedents provides valuable insights for organizations aiming to leverage employee advocacy as a strategic tool for improving their reputation and competitive advantage.

By fostering supportive organizational environments, companies can cultivate loyalty and advocacy, enriching both theoretical understanding and offering practical insights for creating engaging workplaces. Strategic implementation of these insights can lead to a more committed and proactive workforce, ultimately contributing to the organization’s long-term success and sustainability.

Assessing the effectiveness of interventions aimed at improving POS and well-being, and understanding their impact on advocacy and turnover intentions, will provide further valuable insights.

Acknowledgements

This study was made possible through financial support from the French State within the framework of the Investments for the Future program, managed by the IdEx Université de Bordeaux/GPR HOPE.

Conflict of interest

The authors declare none.

Appendix 1. Measurement scales

Well-being at work (Warr, Reference Warr1990)

Positive well-being (PWB)

PWB1. Calm

PWB2. Contented

PWB3. Relax

PWB4. Cheerfull

PWB5. Enthusiastic

PWB6. Optimistic

Negative well-being (NWB)

NWB7. Tense

NWB.8. Uneasy

NWB9. Worried

NWB10. Depressed

NWB11. Gloomy

NWB12. Miserable

Perceived organizational support (POS) (Coyle-Shapiro and Conway, Reference Coyle-Shapiro and Conway2005)

POS1. My employer cares about my well-being

POS2. … values my contributions to its well-being

POS3. … cares about my opinions

POS4. … considers my goals and values

POS5. … cares about my general satisfaction at work

POS6. … is willing to help me when I need a special favor

POS7. … shows very little concern for me (-)

Intention to leave the employer (IL) (Moore, Reference Moore2000)

IL1. I will probably look for a job at a different company in the next year

IL2. … take steps during the next year to secure a job at a different company

IL3. … working in the same company this time next year (-)

IL4. … be with this company five years from now (-)

Intention to recommend the employer (IR) (Reichheld, Reference Reichheld2003; Schmitt et al. Reference Schmitt, Meyer and Skiera2012)

IR: I intend to recommend my company to my friends and family

Appendix 2. Respondents profile

Appendix 3. Estimates of causal model

Catherine VIOT is Professor of Marketing at IAE Bordeaux Graduate School of Management – University of Bordeaux. She is a member of the Institut de Recherche en Gestion des Organisations (IRGO). Her fields of research include Brand Equity, Human Resources Marketing (employer brand equity and its effects in terms of attractiveness and employee loyalty), the Digital Transformation of Retailers, and finally Consumer behavior. Her research has been published in the Journal of Business Ethics, Journal of Business Research, Management International, International Journal of Retail & Distribution Management, Journal of Product & Brand Management, Recherche et Applications en Marketing, Revue Française de Gestion, and other leading scientific journals.

Laïla BENRAISS-NOAILLES is Professor of Human Resource Management at IAE Bordeaux Graduate School of Management – University of Bordeaux, and head of IRGO’s HR research team, since 2017. Her fields of research include Human Resources Marketing. She has published in academic journals such as the Journal of Business Ethics, Journal of Business Research, Employee Relations, Revue Française de Gestion, and other top-tier scientific journals.

Footnotes

1 The items that are indicators of specific construct should converge, or share a high proportion of variance in common (Hair et al., Reference Hair, Black, Babin and Anderson2018).

2 The average variance extracted is calculated as the mean variance extracted for the items loading on a construct and it is a summary indicator of convergence (Hair et al., Reference Hair, Black, Babin and Anderson2018).

3 Discriminant validity is the extent to which a construct is truly distinct from other constructs (Hair et al., Reference Hair, Black, Babin and Anderson2018).

4 Not reported in the paper.

5 The parallel mediation model proposed by the Hayes macro-process is not appropriate, as the two mediators – positive well-being and negative well-being – are statistically correlated (Table 2).

References

Abdalla, M., Altaf, J., Trocooli, I., & Trinta, J. (2012). Antecedents of the intent to recommend: A problem with fast food restaurants. Revista Brasileira de Gestão de Negócios, 14(43), 234250.Google Scholar
Ahmed, M., Zehou, S., Raza, S. A., Qureshi, M. A., & Yousufi, S. Q. (2020). Impact of CSR and environmental triggers on employee green behavior: The mediating effect of employee well‐being. Corporate Social Responsibility and Environmental Management, 27(5), 22252239.CrossRefGoogle Scholar
Aliyu, A., Muktar, S., Yusoff, R., & Ahmad, I. (2014). Effects of customer relationship management strategy on call centre’s employee intention to quit: Evidence from Malaysia call centers. Procedia-Social and Behavioural Sciences, 130, 305315.Google Scholar
Arasanmi, C., & Krishna, A. (2019). Employer branding: perceived organizational support and employee retention – The mediating role of organizational commitment. Industrial and commercial Training, 51(3), 174183.CrossRefGoogle Scholar
Arnold, J. (1990). Predictors of career commitment: A test of three theoretical models. Journal of Vocational Behavior, 37(3), 285330.CrossRefGoogle Scholar
Aselage, J., & Eisenberger, R. (2003). Perceived organizational support and psychological contracts: A theoretical integration. Journal of Organizational Behavior, 24(5), 491509.CrossRefGoogle Scholar
Barrow, S., & Mosley, R. (2005). The employer brand: Bringing the best of brand management to people at work. Hoboken (New Jersey): John Wiley & Sons. 978-0-470-01273-4Google Scholar
Benraiss-Noailles, L., & Viot, C. (2012). Les médias sociaux dans les stratégies de recrutement: Quelle compatibilité avec la vie privée? Revue Française de Gestion 5, 125138.CrossRefGoogle Scholar
Berthon, P., Ewing, M., & Hah, L. (2005). Captivating company: Dimensions of attractiveness in employer branding. International Journal of Advertising, 24(2), 151172.CrossRefGoogle Scholar
Blau, P. (1964). Exchange and power in social life. New York: John Wiley.Google Scholar
Bone, P. (1995). Word of mouth effects on short-term and long-term product judgments. Journal of Business Research, 32(2), 213223.CrossRefGoogle Scholar
Breaugh, J. (2013). Employee recruitment. Annual Review of Psychology, 64, 389416.CrossRefGoogle ScholarPubMed
Breaugh, J., & Starke, M. (2000). Research on employee recruitment: So many studies, so many remaining questions. Journal of Management, 26(3), 405434.CrossRefGoogle Scholar
Brown, J., & Reingen, P. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer Research, 14(3), 350362.CrossRefGoogle Scholar
Brunetto, Y., Xerri, M., Shriberg, A., Farr-Wharton, R., Shack-Lock, K., Newman, S., & Dienger, J. (2013). The impact of workplace relationships on engagement, well-being, commitment and turnover for nurses in Australia and the USA. Journal of Advanced Nursing, 69(12), 27862799.CrossRefGoogle ScholarPubMed
Cable, D. M. & Turban, D. B. (2001) Establishing the Dimensions, Sources and Value of Job Seekers’ Employer Knowledge during Recruitment. In Cable, D. M., and Turban, D. B. (Eds.), Research Personal and Human Resources Management (pp. 115–163). Bingley Emerald Group Publishing Limited.CrossRefGoogle Scholar
Caesens, G., Stinglhamber, F., & Ohana, M. (2016). Perceived organizational support and well-being: A weekly study. Journal of Managerial Psychology, 31(7), 12141230.CrossRefGoogle Scholar
Carpentier, M., & Van Hoye, G. (2021). Managing organizational attractiveness after a negative employer review: Company response strategies and review consensus. European Journal of Work & Organizational Psychology, 30(2), 274291.CrossRefGoogle Scholar
Charbonnier-Voirin, A., & Vignolles, A. (2016). Enjeux et outils de gestion de la marque employeur: Point de vue d’experts. Recherches En Sciences de Gestion, 112, 153172.CrossRefGoogle Scholar
Chatman, J. A. (1991). Matching people and organizations: Selection and socialization in public accounting firms. Administrative Science Quarterly, 36, 459484.CrossRefGoogle Scholar
Cheng, C., Bartram, T., Karimi, L., & Leggat, S. (2016). Transformational leadership and social identity as predictors of team climate, perceived quality of care, burnout and turnover intention among nurses. Personnel Review, 2(2), 2041.Google Scholar
Cheng, K., & Lin, Y. (2017). Congruence in organizational support and new generation employees’ turnover intention: The mediating role of employee well-being. Acta Psychologica Sinica, 49(12), 15701580.CrossRefGoogle Scholar
Chicu, D., Ryan, G., & Mirela, V. (2016). Determinants of customer satisfaction in call centers. European Accounting and Management Review, 2(2), 2041.CrossRefGoogle Scholar
Collier, J. (2020). Applied structural equation modeling using AMOS, basic to advanced techniques. New York: Routledge.CrossRefGoogle Scholar
Collins, C., & Han, J. (2004). Exploring applicant pool quantity and quality: The effects of early recruitment practice strategies, corporate advertising, and firm reputation. Personnel Psychology, 57(3), 685717.CrossRefGoogle Scholar
Collins, C., & Stevens, C. (2002). The relationship between early recruitment-related activities and the application decisions of new labor-market entrants: A brand equity approach to recruitment. Journal of Applied Psychology, 87(6), 11211133.CrossRefGoogle ScholarPubMed
Cooper, B., Wang, J., Bartram, T., & Cooke, F. (2019). Well‐being‐oriented human resource management practices and employee performance in the Chinese banking sector: The role of social climate and resilience. Human Resource Management, 58(1), 8597.CrossRefGoogle Scholar
Cotton, P., & Hart, P. M. (2003). Occupational wellbeing and performance: A review of organisational health research. Australian Psychologist, 38(2), 118127.CrossRefGoogle Scholar
Coyle-Shapiro, J. A.-M., & Conway, N. (2005). Exchange relationships: Examining psychological contracts and perceived organizational support. Journal of Applied Psychology, 90(4), 774781.CrossRefGoogle ScholarPubMed
East, R., Hammond, K., Lomax, W., & Robinson, H. (2005). What is the effect of a recommendation? The Marketing Review, 5(2), 145157.CrossRefGoogle Scholar
Eder, P., & Eisenberger, R. (2008). Perceived organizational support: Reducing the negative influence of coworker withdrawal behavior. Journal of Management, 34(1), 5568.CrossRefGoogle Scholar
Eisenberger, R., Armeli, S., Rexwinkel, B., Lynch, P. D., & Rhoades, L. (2001). Reciprocation of perceived organisational support. Journal of Applied Psychology, 86(1), 4251.CrossRefGoogle Scholar
Eisenberger, R., Cummings, J., Armeli, S., & Lynch, P. (1997). Perceived organizational support, discretionary treatment, and job satisfaction. Journal of Applied Psychology, 82(5), 812820.CrossRefGoogle ScholarPubMed
Eisenberger, R., Huntington, R., Hutchinson, S., & Sowa, D. (1986). Perceived organizational support. Journal of Applied Psychology, 71(3), 500507.CrossRefGoogle Scholar
Evertz, L., Kollitz, R., & Süß, S. (2021). Electronic word-of-mouth via employer review sites – The effects on organizational attraction. The International Journal of Human Resource Management, 32(16), 34283457.CrossRefGoogle Scholar
Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 3950.CrossRefGoogle Scholar
Greenawald, E. (2019). Worried about your employee turnover? See how it stacks up. Retrieved December 14, 2020 from www.reflektive.com/blog/average-retention-industry/.Google Scholar
Guerrero, S., & Herrbach, O. (2009). La confiance organisationnelle au cœur de l’échange social: Et si bien traiter ses employés était payant? Relations Industrielles, 64(1), 626.CrossRefGoogle Scholar
Guest, D. (2017). Human resource management and employee well-being: Towards a new analytic framework. Human Resource Management Journal, 27(1), 2238.CrossRefGoogle Scholar
Hair, J., Black, W., Babin, B., & Anderson, R. (2018). Multivariate data analysis (8th ed.). Boston, Massachusetts: Cengage.Google Scholar
Harman, H. (1976). Modern factor analysis (3rd ed.). Chicago, IL: The University of Chicago Press. 978-0226316529.Google Scholar
Ho, H., & Kuvaas, B. (2020). Human resource management systems, employee well‐being, and firm performance from the mutual gains and critical perspectives: The well‐being paradox. Human Resource Management, 59(3), 235253.CrossRefGoogle Scholar
INSEE (2021). 14 chiffres à connaître sur les cadres français. Retrieved April 19, 2024 from www.cadremploi.fr/editorial/conseils/conseils-carriere/detail/article/12-chiffres-a-connaitre-sur-les-cadres-francais.html#ancre-1.Google Scholar
Ismagilova, E., Dwivedi, Y. K., Slade, E., & Williams, M. (2017). Electronic word-of-mouth (eWOM). In E. Ismagilova, Y. K. Dwivedi, E. Slade, & M. Williams, (Eds.), Electronic word of mouth (eWOM) in the marketing context (pp. 1730). Cham: Springer.Google Scholar
Kollitz, R., Ruhle, S., & Wilhelmy, A. (2022). How to deal with negative online employer reviews: An application of image repair theory. International Journal of Selection and Assessment, 30(4), 526544.CrossRefGoogle Scholar
Koomson, S. (2022). A conceptual framework of employees’ perceived organisational support on student loyalty, IIM Ranchi Journal of Management Studies, 1(2), .CrossRefGoogle Scholar
Kurtessis, J., Eisenberger, R., Ford, M. T., Buffardi, L. C., Stewart, K. A., & Adis, C. S. (2015). Perceived organizational support: A meta-analytic evaluation of organizational support theory. Journal of Management, 43(6), 18541884.CrossRefGoogle Scholar
Mangold, W., Miller, F., & Brockway, G. (1999). Word‐of‐mouth communication in the service marketplace. Journal of Services Marketing, 13(1), 7389.CrossRefGoogle Scholar
Matos, C., & Rossi, C. (2008). Word-of-mouth communications in marketing: A meta-analytic review of the antecedents and moderators. Journal of the Academy of Marketing Science, 36, 578596.CrossRefGoogle Scholar
Moore, J. (2000). One road to turnover: An examination of work exhaustion in technology professionals. MIS Quarterly, 24(1), 141168.CrossRefGoogle Scholar
Nikolaou, I. (2014). Social networking web sites in job search and employee recruitment. International Journal of Selection and Assessment, 22(2), 179189.CrossRefGoogle Scholar
Ogbonnaya, C., & Messersmith, J. (2019). Employee performance, well‐being, and differential effects of human resource management subdimensions: Mutual gains or conflicting outcomes? Human Resource Management Journal, 29(3), 509526.CrossRefGoogle Scholar
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879903.CrossRefGoogle ScholarPubMed
Pradhan, R. K., & Hati, L. (2022). The measurement of employee well-being: Development and validation of a scale. Global Business Review, 23(2), 385407.CrossRefGoogle Scholar
Rasool, S. F., Wang, M., Tang, M., Saeed, A., & Iqbal, J. (2021). How toxic workplace environment effects the employee engagement: The mediating role of organizational support and employee wellbeing. International Journal of Environmental Research & Public Health, 18(5), .CrossRefGoogle ScholarPubMed
Reichheld, F. (2003). The one number you need to grow. Harvard Business Review, 81(12), 4654.Google ScholarPubMed
Saks, A. (2005). The impracticality of recruitment research. In Evers, A., Anderson, N. & Voskuijl, O. (Eds.), Handbook of personnel selection (pp. 419439). Oxford: Blackwell.Google Scholar
Schmitt, P., Meyer, S., & Skiera, B. (2012). Étude du lien entre l’intention de recommander une entreprise et la valeur à vie de ses clients. Recherche Et Applications Marketing, 27(4), 121143.Google Scholar
Setyoko, P. I., & Kurniasih, D. (2022). The role of perceived organizational support (POS), organizational virtuousness (OV) on performance and employee well-being (EWB) of non-profit organizations in the post-pandemic period. Journal of Pharmaceutical Negative Results 13 (8), 19401944.CrossRefGoogle Scholar
Shi, X., Gordon, S., & Tang, C. (2021). Momentary well-being matters: Daily fluctuations in hotel employees’ turnover intention. Tourism Management, 83, .CrossRefGoogle Scholar
Tsarenko, Y., Leo, C., & Tse, H. (2018). When and why do social resources influence employee advocacy? The role of personal investment and perceived recognition, Journal of Business Research, 82, 260268.CrossRefGoogle Scholar
Turban, D. B., & Yan, W. (2016). Relationship of eudaimonia and hedonia with work outcomes. Journal of Managerial Psychology, 31(6), 10061020.CrossRefGoogle Scholar
Uen, J., Ahlstrom, D., Chen, S., & Liu, J. (2015). Employer brand management, organizational prestige and employees’ word‐of‐mouth referrals in Taiwan. Asia Pacific Journal of Human Resources, 53(1), 104123.CrossRefGoogle Scholar
Uen, J., Peng, S., Shu-Yuan, C., & Chien, S. (2011). The impact of word of mouth on organizational attractiveness. Asia Pacific Management Review, 16(3), 239253.Google Scholar
Van Hoye, G., & Lievens, F. (2005). Recruitment‐related information sources and organizational attractiveness: Can something be done about negative publicity? International Journal of Selection and Assessment, 13(3), 179187.CrossRefGoogle Scholar
Van Hoye, G., & Lievens, F. (2007a). Social influences on organizational attractiveness: Investigating if and when word of mouth matters1. Journal of Applied Social Psychology, 37(9), 20242047.CrossRefGoogle Scholar
Van Hoye, G., & Lievens, F. (2007b). Investigating web‐based recruitment sources: Employee testimonials vs word‐of‐mouse. International Journal of Selection and Assessment, 15(4), 372382.CrossRefGoogle Scholar
Van Hoye, G., & Lievens, F. (2009). Tapping the grapevine: A closer look at word-of-mouth as a recruitment source, Journal of Applied Psychology, 94(2), 341352.CrossRefGoogle Scholar
Van Hoye, G., Weijters, B., Lievens, F., & Stockman, S. (2016). Social influences in recruitment: When is word‐of‐mouth most effective? International Journal of Selection and Assessment, 24(1), 4253.CrossRefGoogle Scholar
Viot, C., & Benraiss-Noailles, L. (2019). The link between benevolence and well-being in the context of human-resource marketing. Journal of Business Ethics, 159(3), 883896.CrossRefGoogle Scholar
Ward, J., & Reingen, P. (1990). Socio-cognitive analysis of group decision making among consumers. Journal of Consumer Research, 17(3), 245262.CrossRefGoogle Scholar
Warr, P. (1990). The measurement of well‐being and other aspects of mental health. Journal of Occupational Psychology, 63(3), 193210.CrossRefGoogle Scholar
Warr, P. (1999). 20 Well-being and the workplace. In Kahneman, D., Diener, E. & Schwarz, N. (Eds.), Foundations of hedonic psychology (p. ). New York City: Russell Sage Foundation.Google Scholar
Warr, P. (2007). Work, happiness, and unhappiness (p. 562). Mahwah, NJ: Erlbaum.Google Scholar
Wattoo, M. A., Zhao, S., & Xi, M. (2018). Perceived organizational support and employee well-being: Testing the mediatory role of work-family facilitation and work-family conflict. Chinese Management Studies, 12(2), 469484.CrossRefGoogle Scholar
Wayne, S., Shore, L., & Liden, R. (1997). Perceived organizational support and leader-member exchange: A social exchange perspective. Academy of Management Journal, 40(1), 82112.CrossRefGoogle Scholar
Weiss, H., & Cropanzano, R. (1996). Research in organization behavior. In Staw, B. M., and Cummings, L. L. (Eds.), Affective events theory: A theoretical discussion of the structure, causes and consequences of affective experiences at work (pp. 174). Stamford, CT: JAI Press.Google Scholar
Zottoli, M., & Wanous, J. (2000). Recruitment source research: Current status and future directions. Human Resource Management Review, 10(4), 353382.CrossRefGoogle Scholar
Figure 0

Figure 1. Conceptual model and research hypotheses.

Figure 1

Table 1. Correlation matrix, composite reliability, and square root of average variance extracted

Figure 2

Figure 2. Results.

Figure 3

Table 2. Specific indirect effects

Figure 4

Table 3. Direct and total effect