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

Catherine Viot, Laila Benraiss-Noailles

► To cite this version:

Catherine Viot, Laila Benraiss-Noailles. Advocacy versus depart: How perceived organizational support influences employee well-being and shapes their intentions. Journal of Management and Organization, 2024, 31 (1), pp.195-214. 10.1017/jmo.2024.60. hal-05472153

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ADVOCACY VERSUS DEPART: HOW PERCEIVED ORGANIZATIONAL SUPPORT
INFLUENCES EMPLOYEE WELL-BEING AND SHAPES THEIR INTENTIONS

Benraïss-Noailles L., Viot, C. (2025), Advocacy versus depart: how perceived organizational support influences employee well-being and shapes their intentions, *Journal of Management & Organisation*, 31, 195-214.

**Abstract**

**Purpose:**

The study investigates the influence of Perceived Organizational Support (POS) on employee intentions to either recommend their employer or to leave the organization. Anchored in social exchange theory, this research examines how employees' perceptions of organizational support impact their well-being and shape subsequent behaviors such as loyalty and advocacy towards the employer.

**Design/Methodology/Approach:**

A comprehensive online survey was conducted, gathering data from 604 French employees across various sectors. The variables analyzed included POS, positive and negative well-being, Intention to Leave (IL), and Intention to Recommend the Employer (IR). The relationships between these variables, including the mediating effect of employees' well-being on their intentions towards the employer, were tested using structural equation modeling.

**Findings:**

The findings reveal that POS significantly influences both positive and negative dimensions of employee well-being. Improved positive well-being due to high POS is linked with a decreased intention to leave and an increased intention to recommend the employer. Conversely, reduced negative well-being associated with high POS correlates with a lower intention to leave and a diminished negative impact on the intention to recommend. The study confirms the mediating role of well-being between POS and employee intentions, underscoring the complex interplay of organizational support, employee well-being, and workplace intentions.

**Originality:**

This research contributes to the existing literature by clarifying how POS impacts employee intentions through both positive and negative well-being pathways, a topic that has not been extensively explored before. The use of structural equation modeling to confirm well-being as a mediator adds a robust analytical layer to the study, providing deeper insights into the
dynamics of organizational support.

**Practical Implications:**

The study highlights critical implications for human resources practices, emphasizing the need for organizations to enhance POS to leverage employee subjective well-being, hence encouraging positive employee behaviors. By fostering an environment that values and supports employees, organizations can not only improve retention rates but also encourage employees to act as brand ambassadors, furthering the organization's reputation and attractiveness.

**Key words**

Perceived organizational support, Well-being at work, Intention to leave the employer, Intention to recommend the employer
Introduction

As companies face increasing challenges in attracting talent through traditional channels like media advertisements or job platforms, they are turning more towards 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, 2021). These platforms have become crucial in shaping an employer's reputation, as noted by Kollitz et al., 2022), 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 (2005) 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, 2008), enhancing their appeal to job seekers who value transparency and honest reviews (Breaugh, 2013; Van Hoye et al., 2016).

The impact of such employee-driven endorsements on an employer's image and their ability to attract high-quality candidates is well-established (Evertz et al., 2021; Van Hoye et al., 2016). 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, 2000; Zottoli & Wanous, 2000; Collins & Stevens, 2002; Van Hoye & Lievens, 2009). 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 (Nikolaou, 2014; Van Hoye et al., 2016). This dual influence underscores the need for companies to understand and strategically use positive WOM to enhance their recruitment processes and overall brand image.
To date, HRM research has mainly focused on the effects of employer recommendations made by employees (Cable & Turban, 2001; Collins & Stevens 2002; Van Hoye & Lievens, 2005; 2007a). Research into the factors that encourage employees to recommend their employer is relatively rare, however (Uen et al. 2011; Uen et al., 2015). The literature identifies certain individual characteristics, such as social ties, expertise, and personality (Collins & Stevens, 2002; Van Hoye & Lievens 2005; 2007a; 2007b; 2009) 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, 1964), which enables us to understand employees' behavior towards 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, 2017; Rasool et al., 2021; Wattoo et al., 2018) frequently prioritise 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 (Brown & Reingen, 1987; Ward & Reingen, 1990; Bone, 1995). 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, 2001). 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 (Benraïss-Noailles & Viot, 2012). To compensate for information asymmetry, candidates seek information directly from current employees, notably on specialist platforms such as *Choose my company*, *Indeed*, *Glassdor*, 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.

# 1. Employee's intentions towards the employer through social exchange theory

## 1.1 Social exchange theory

Social exchange theory (Blau, 1964) 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, 2022). For instance, employees are more likely to consider staying with an organization in return for work-related benefits or gains (Arnold, 1990). 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 et al., 1986) 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 towards the organization that employs them (Tsarenko et al., 2018). 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, 2019). 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.

**1.2 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 (Eisenberger et al. 1986; Viot & Benraiss-Noailles, 2019). POS is the general belief that the organization cares about the contributions and well-being of its employees (Eisenberger et al., 1986). It depends on the perceived sincerity and frequency of the employer's goodwill gestures towards employees, over and above contractual obligations (Aselage & Eisenberger, 2003).

Employees who perceive a high level of support experience greater job satisfaction and reduced stress (Eder & Eisenberger, 2008). POS also increases employees' commitment and contributions to their employer (Eisenberger et al., 1997; Wayne et al., 1997), 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 organisation. Conversely, a lack of perceived support can diminish well-being and increase turnover intentions (Rasool et al., 2021).

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 organisation demonstrate higher productivity and are more inclined to advocate for their employer (Setyoko et al., 2022). This underscores the importance of organisational support as a strategic lever for improving employee outcomes.

Finally, POS contributes significantly to employee well-being (Caesens et al., 2016; Viot & Benraiss-Noailles, 2019). According to organisational support theory (Kurtessis et al., 2015), by meeting employees' socioemotional needs, POS fosters a self-enhancement process, leading to improved subjective well-being. Conversely, when organisations fail to acknowledge employees' contributions, perceptions of organisational support decline (Eisenberger et al., 1997; Viot & Benraiss-Noailles, 2019), potentially having a detrimental effect on well-being at work.
Employee well-being is a subjective global judgement of the quality of work experiences (Turban & Yan, 2016) which describes the overall quality of how an employee lives and functions at work (Guest, 2017). Warr (1990) 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 (2009), 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, 2003).

This leads us to put forward two hypotheses.

H1: Employee's perceived organizational support has a positive impact on employees' positive well-being at work.

H2: Employee's perceived organizational support has a negative impact on employees' negative well-being at work.

**1.3. The effects of employee well-being on intentions towards 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 et al., 2014). According to Greenawald (2019), 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 et al., 2016).

Several studies argue that the intention to leave an employer is linked to the employee's well-being at work (Cooper et al., 2019; Ogbonnaya & Messersmith; 2019; Ho & Kuvaas; 2020). If an employee feels positive well-being at work, it reduces his or her intention to leave the employer (Chicu et al., 2016).

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 (2017), 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:

H3: Employee's positive well-being at work has a negative impact on the intention to leave an
employer.

H4: 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 (Mangold et al., 1999; East et al., 2005). It is one of the oldest and most important channels of interpersonal information exchange (Ismagilova et al., 2017). With the emergence of digital social networks, brand and/or employer recommendations are of even greater interest.

Applied to the field of HR, the intention to recommend is an effective source of information for external recruitment and an organization's attractiveness (Cable & Turban 2001; Collins & Stevens 2002; Van Hoye & Lievens 2005, 2007a). Recommendation is a powerful lever for the employer's brand (Charbonnier-Voirin & Vignolles, 2016). "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, 2016, p. 169). Through their recommendations, employees determine the credibility of the messages communicated by the company (Berthon et al., 2005).

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 (Zottoli & Wanous, 2000; Collins & Han, 2004; Saks, 2005). 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, 2000). 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, 2007a; 2007b).

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 et al. (2012), 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.
H5: Employee's positive well-being at work has a positive impact on the intention to recommend the employer.

H6: Employee's negative well-being at work has a negative impact on the intention to recommend the employer.

**1.4 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 (Caesens et al., 2016; Viot & Benraiss-Noailles, 2019). 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., 2019; Ogbonnaya & Messersmith, 2019; Ho & Kuvaas, 2020). 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., 2021; Wattoo et al., 2018). While Rasool et al. (2021) 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. (2018) 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. (2013) 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 perceived organizational support 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.

H7: Employee's perceived organizational support has a negative indirect effect on the intention to leave the employer, through positive well-being.

H9: 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.

H8: Employee's perceived organizational support has a positive indirect effect on the intention to recommend the employer, through positive well-being.

H10: 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 H1 to H6) are shown in Figure 1.

----- Insert Figure 1 about here -----

# 2. Methodology

## 2.1. 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 (2005). They selected the seven items with the highest factorial loadings from Eisenberger et al.'s original 36-item scale (2001). 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 perceived organizational support ("My employer shows very little concern for me").

For well-being at work, we adopted Warr's (1990) two-dimensional conceptualization, which includes a positive factor (positive well-being) and a negative factor (negative well-being). Research conducted by Warr (1999, 2007) is highly influential in the field of employee well-being (Pradhan & Hati, 2022). 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 (1999, 2007) 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, 2003; Warr, 1999) 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., 2020; Rasool et al., 2021), the Warr's (1999) scale enables an assessment of well-being independent of Perceived Organizational Support (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. (2020) and Rasool et al. (2021). 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 two 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, 2000). We used Moore's (2000) 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, 2003): "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 et al. (2012).

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
perceived organizational support 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").

**2.2 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. (2003). 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 1). 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).

**2.3 Statistical analysis**

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

**3. Results**
**3.1 Measurement model**

Although we used existing scales, we first verified their structure using principal component
analyses (PCA). For the POS, PCA confirmed unidimensionality with an explained variance of
72.74%. The Kaiser-Meyer-Olkin (KMO) index (0.935) and Bartlett's test (p < 0.001) indicated
satisfactory results confirming the correlations among the items, a prerequisite for PCA.
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 KMO index (0.891) and
Bartlett's test (p < 0.001) 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 KMO index was 0.809, and Bartlett's test of
sphericity confirmed the correlations among the items (p < 0.001). 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). PCA
confirmed unidimensionality. The reliability of the measures, as indicated by Cronbach's alpha,
ranged between 0.84 and 0.93 (Table 1).

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; χ<fnref n="2" /> = 513 (df = 180, p< 0.001).

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 alpha, 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
et al., 2018). The scales therefore show good internal consistency, with indicators between 0.84
and 0.94 (Table 1).

Convergent validity<fnref n="1" />, assessed through average variance extracted<fnref n="2" /> (AVE), 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

<footnote n="1">¹ The items that are indicators of specific construct should converge, or share a high proportion of variance in common (Hair et al., 2018).</footnote>

<footnote n="2">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., 2018).</footnote>
explains more than half of the variance of its indicators. All the latent variables demonstrated AVE 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 alpha and composite validity are not reported in the table.

For discriminant validity<fnref n="3" />, we used Fornell and Larcker's (1981) 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<fnref n="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.

----- Insert Table 1 about here -----

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 ($M_{negative\ well-being} = 2.20; \sigma = 0.88$). Conversely, intention to recommend the employer is relatively high ($M_{Rec.} = 4.2; \sigma = 1.32$).

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 (CVB). Following the guidelines of Podsakoff et al. (2003), we carried out the Harman's single-factor test (Harman, 1976). The variance explained by the first factor (48%) falls below the recommended threshold of 50%.

## 3.2 Testing the model and indirect effects

Directs and indirect effects were examined using structural equation modelling 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=5000), the AMOS software provided confidence intervals and a P-value for each estimated parameter.

<footnote n="3">³ Discriminant validity is the extent to which a construct is truly distinct from other constructs (Hair et al., 2018).</footnote>

<footnote n="4">⁴ Not reported in the paper.</footnote>
The adjustment indices ($\chi^2 = 617$; 182 df; $p < 0.001$; $\chi^2/df = 3.39$; SRMR= 0.0556; CFI= 0.955; RMSEA= 0.063) are in line with generally accepted standards. The model fits the data well.
All of the model's estimated parameters are significant (Appendix 2). POS has a positive influence on positive well-being ($\lambda= 0.710^{**}$, p= 0.003) and a negative influence on negative well-being ($\lambda= -0.591^{**}$, p= 0.005). Hypotheses H1 and H2 are therefore validated. Positive well-being has a positive influence on intention to recommend ($\lambda= 0.264^{**}$, p= 0.003) and a negative influence on intention to leave ($\lambda= -0.237^{**}$, p= 0.004). Hypotheses H3 and H5 are therefore also validated. Negative well-being negatively influences intention to recommend the company ($\lambda= -0.102^{**}$, p= 0.005) and positively influences the intention to leave the employer ($\lambda= 0.290^{**}$, p= 0.005), giving support to both hypotheses H4 and H6.

------ Insert Figure 2 about here ------

For hypotheses H7 to H10, which propose an indirect effect of POS on the responses of current employees, we conducted specific mediations tests using AMOS software<fnref n="5" />. We therefore used the "Edit Specific Estimand Indirect Effects" function provided by AMOS, as suggested by Collier (2020). We first named the parameters and defined the four indirect effects corresponding to hypotheses H7 to H10. 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).

The POS demonstrates a negative indirect effect on the intention to leave the employer ($\beta = -0.189$; $p = 0.007$) and a positive indirect effect on the intention to recommend the employer ($\beta = 0.221$; $p = 0.002$) through positive well-being, supporting hypotheses H7 and H8, respectively. Furthermore, the POS has a negative indirect effect on the intention to leave the employer ($\beta = -0.193$; $p = 0.004$) and a positive indirect effect on the intention to recommend the employer ($\beta = 0.071$; $p = 0.011$) through negative well-being, supporting hypotheses H9 and H10 respectively.

<footnote n="5">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).</footnote>
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 = 0.004) and on the intention to leave the employer (β = - 0.213; p = 0.002) are also significant (Table 3). These results confirm the mediation of well-being at work, albeit partial, and thus provide support for hypotheses H7 to H10.

# 4. 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 (2017), Rasool et al. (2021), and Wattoo et al. (2018), 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, 1964), 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 (Eisenberger et al., 1997; Caesens et al., 2016). 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.

## 4.1 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, 1964) and due to the reciprocity norm in the workplace (Arnold, 1990), our findings significantly contribute to the theory of organizational support (Kurtessis et al., 2015). 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. (2016); Kurtessis et al. (2015), and Tsarenko et al. (2018). 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 (1990). 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 (2016). 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.

## 4.2 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 et al., 2022). 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.

## 4.3 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., 2021). Affective Events Theory asserts that work environment characteristics trigger diverse work events (Weiss & Cropanzano, 1996), leading to different work attitudes in employees through shifting affective reactions to work events (Shi et al., 2021).

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, 2007b). A potential antecedent of employee advocacy would be the perception of a high fit between the person and the organization (Chatman, 1991). 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 CSR issues.

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, 1964), 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 organisation. When employees perceive strong organisational support, they experience higher levels of positive well-being, which fosters loyalty and increases their likelihood of recommending the organisation to others. Conversely, insufficient support heightens negative well-being, increasing turnover intentions and reducing advocacy. This dual pathway underscores the necessity for organisations to create supportive environments to maintain high levels of employee well-being and capitalise on its positive outcomes.

In alignment with the findings of Cheng and Lin (2017), Rasool et al. (2021), and Wattoo et al. (2018), 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 behaviours emphasises the importance of supporting employee well-being to foster positive workplace behaviours.

Our study further contributes to social exchange theory by demonstrating how POS shapes employee well-being, which, in turn, influences intentional behaviours. For organisations, it is essential to develop strategies to increase POS, such as recognising employee efforts and implementing support programmes. Promoting a favourable 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, 2017; Rasool et al., 2021; Wattoo et al., 2018), 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 behaviours. Employees who perceive strong organisational support and experience positive well-being are more likely to act as advocates for their organisation, 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 organisation, making it a preferred choice for top talent. Understanding these antecedents provides valuable insights for organisations aiming to leverage employee advocacy as a strategic tool for improving their reputation and competitive advantage.

By fostering supportive organisational 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 organisation'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.

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<figure><img src="image_2.png" /><figcaption>Figure 2. Results</figcaption></figure>

<figure><img src="image_3.png" /></figure>
<table><caption>Table 1. Correlation matrix, composite reliability and square root of average variance extracted</caption><thead><tr><th rowspan="2"></th><th rowspan="2">α</th><th rowspan="2">CR</th><th rowspan="2">AVE</th><th rowspan="2">M(α)</th><th colspan="5">Corrélation entre construits</th></tr><tr><th>POS</th><th>WB<sup>+</sup></th><th>WB<sup>-</sup></th><th>IL</th><th>IR</th></tr></thead><tbody><tr><th>POS</th><td>.93</td><td>.94</td><td>.68</td><td>3.78 (1,13)</td><td><strong>.82</strong></td><td></td><td></td><td></td><td></td></tr><tr><th>WB<sup>+</sup></th><td>.89</td><td>.89</td><td>.68</td><td>3.57 (1,02)</td><td>.701**</td><td><strong>.82</strong></td><td></td><td></td><td></td></tr><tr><th>WB<sup>-</sup></th><td>.84</td><td>.84</td><td>.51</td><td>2.20 (0,88)</td><td>-.576**</td><td>-.654**</td><td><strong>.72</strong></td><td></td><td></td></tr><tr><th>IL</th><td>.93</td><td>.92</td><td>.76</td><td>3.20 (1,5)</td><td>-.533**</td><td>-.551**</td><td>-.549**</td><td><strong>.87</strong></td><td></td></tr><tr><th>IR</th><td>-</td><td>-</td><td>-</td><td>4.20 (1,32)</td><td>.738**</td><td>.655**</td><td>-.502**</td><td>-.458**</td><td><strong>1</strong></td></tr></tbody></table>

Keys: α = Cronbach' alpha, CR = composite reliability, AVE = average variance extracted, M = means

Notes: 1) Bold numbers on the diagonal represent the square root of AVE; 2) ** p<.01.

<table><caption>Table 2. Specific indirect effects</caption><thead><tr><th rowspan="2">Estimated parameter</th><th rowspan="2">Coefficient</th><th colspan="2">Confidence interval</th><th rowspan="2">P value</th></tr><tr><th>LLCI</th><th>ULCI</th></tr></thead><tbody><tr><td>POS → PWB → IR</td><td>.221**</td><td>.146</td><td>.311</td><td>.002</td></tr><tr><td>POS → PWB → IL</td><td>-.189**</td><td>-.288</td><td>-.088</td><td>.007</td></tr><tr><td>POS → NWB → IR</td><td>-.193**</td><td>-.274</td><td>-.124</td><td>.004</td></tr><tr><td>POS → NWB → IL</td><td>.071*</td><td>.014</td><td>.130</td><td>.011</td></tr></tbody></table>

Note: 1) * p<.05; ** p<.01 2) POS = Perceived Organizational Support; P/N WB = Positive/Negative Well-Being; IR = Intention to Recommend; IL = Intention to Leave.

<table><caption>Table 3. Direct and total effect</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Estimated parameter</th><th rowspan="2">Coefficient</th><th colspan="2">Confidence interval</th><th rowspan="2">P value</th></tr><tr><th>LLCI</th><th>ULCI</th></tr></thead><tbody><tr><td rowspan="2">Direct effect</td><td>POS → IR</td><td>.490**</td><td>.394</td><td>.572</td><td>.004</td></tr><tr><td>POS → IL</td><td>-.213**</td><td>-.331</td><td>-.102</td><td>.002</td></tr><tr><td rowspan="2">Total effect</td><td>POS → IR</td><td>.738**</td><td>.695</td><td>.774</td><td>.005</td></tr><tr><td>POS → IL</td><td>-.552**</td><td>-.611</td><td>-.485</td><td>.004</td></tr></tbody></table>

Note: 1) ** p<.01 2) POS = Perceived Organizational Support; IR = Intention to Recommend; IL = Intention to Leave.
Appendix 1. Measurement scales

**Well-being at work (Warr, 1990)**

*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 (2005)**

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 (2000)**

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 (2003) ; Schmitt et al. (2012)

IR: I intend to recommend my company to my friends and family
Appendix 2. Respondents profile

Respondents' age

<table><thead><tr><td></td><td>Percentage</td></tr></thead><tbody><tr><td>&lt; 25</td><td>5.6</td></tr><tr><td>[25 - 35]</td><td>25.3</td></tr><tr><td>[36 - 45]</td><td>33.4</td></tr><tr><td>[45 - 55]</td><td>27.0</td></tr><tr><td>&gt; 55</td><td>8.6</td></tr></tbody></table>

Education

<table><thead><tr><td></td><td>Percentage</td></tr></thead><tbody><tr><td>No degree/no qualification ?</td><td>.2</td></tr><tr><td>Below A-levels</td><td>2.0</td></tr><tr><td>A-level (bacalaureate)</td><td>4.6</td></tr><tr><td>Undergraduate level (bachelor's degree)</td><td>16.2</td></tr><tr><td>Master's degree</td><td>57.3</td></tr><tr><td>&gt; Master's degree</td><td>19.7</td></tr></tbody></table>

Job status

<table><thead><tr><td></td><td>Percentage</td></tr></thead><tbody><tr><td>Worker</td><td>12.4</td></tr><tr><td>Technician/Master</td><td>11.8</td></tr><tr><td>Executive/Engineer</td><td>72.0</td></tr><tr><td>Other</td><td>3.8</td></tr></tbody></table>

Work experience in years

<table><thead><tr><td></td><td>Percentage</td></tr></thead><tbody><tr><td>&lt; 5 years</td><td>21.2</td></tr><tr><td>[5 - 10]</td><td>10.4</td></tr><tr><td>[11 - 15]</td><td>15.9</td></tr><tr><td>[16 - 20]</td><td>17.1</td></tr><tr><td>[21 - 25]</td><td>15.7</td></tr><tr><td>&gt; 26 years</td><td>19.7</td></tr></tbody></table>

Respondents' company size

<table><thead><tr><td></td><td>Percentage</td></tr></thead><tbody><tr><td>&lt; 50</td><td>18.0</td></tr><tr><td>[50 - 100]</td><td>13.4</td></tr><tr><td>[101 - 300]</td><td>23.5</td></tr></tbody></table>
<table><tr><td>[301 - 500[</td><td>7.8</td></tr><tr><td>[501 - 1000[</td><td>9.1</td></tr><tr><td>> 1000</td><td>28.1</td></tr></table>
<table><caption>Appendix 3. Estimates of causal model</caption><thead><tr><th>Parameter</th><th></th><th>Estimate</th><th>LLCI.</th><th>ULCI</th><th>P</th></tr></thead><tbody><tr><td>PWB</td><td>← POS</td><td>.710</td><td>.670</td><td>.751</td><td>.005</td></tr><tr><td>NWB</td><td>← POS</td><td>-.591</td><td>-.635</td><td>-.538</td><td>.007</td></tr><tr><td>IL</td><td>← NWB</td><td>.290</td><td>.203</td><td>.371</td><td>.004</td></tr><tr><td>IL</td><td>← PWB</td><td>-.237</td><td>-.333</td><td>-.131</td><td>.007</td></tr><tr><td>IL</td><td>← POS</td><td>-.213</td><td>-.312</td><td>-.117</td><td>.002</td></tr><tr><td>IR</td><td>← NWB</td><td>-.102</td><td>-.173</td><td>-.028</td><td>.012</td></tr><tr><td>IR</td><td>← PWB</td><td>.64</td><td>.194</td><td>.354</td><td>.003</td></tr><tr><td>IR</td><td>← POS</td><td>.490</td><td>.416</td><td>.562</td><td>.004</td></tr><tr><td>IL4_inv</td><td>← IL</td><td>.794</td><td>.768</td><td>.818</td><td>.004</td></tr><tr><td>IL3_inv</td><td>← IL</td><td>.818</td><td>.792</td><td>.839</td><td>.007</td></tr><tr><td>IL2</td><td>← IL</td><td>.944</td><td>.932</td><td>.954</td><td>.004</td></tr><tr><td>IL1</td><td>← IL</td><td>.935</td><td>.920</td><td>.945</td><td>.009</td></tr><tr><td>PWB2</td><td>← PWB</td><td>.811</td><td>.777</td><td>.837</td><td>.007</td></tr><tr><td>PWB4</td><td>← PWB</td><td>.784</td><td>.750</td><td>.811</td><td>.005</td></tr><tr><td>PWB5</td><td>← PWB</td><td>.883</td><td>.863</td><td>.906</td><td>.002</td></tr><tr><td>PWB6</td><td>← PWB</td><td>.814</td><td>.784</td><td>.840</td><td>.004</td></tr><tr><td>NWB8</td><td>← NWB</td><td>.628</td><td>.577</td><td>.673</td><td>.003</td></tr><tr><td>NWB9</td><td>← NWB</td><td>.575</td><td>.529</td><td>.627</td><td>.003</td></tr><tr><td>NWB10</td><td>← NWB</td><td>.819</td><td>.782</td><td>.845</td><td>.007</td></tr><tr><td>NWB11</td><td>← NWB</td><td>.835</td><td>.798</td><td>.861</td><td>.008</td></tr><tr><td>NWB12</td><td>← NWB</td><td>.722</td><td>.679</td><td>.755</td><td>.007</td></tr><tr><td>POS1</td><td>← POS</td><td>.854</td><td>.833</td><td>.873</td><td>.004</td></tr><tr><td>POS2</td><td>← POS</td><td>.823</td><td>.798</td><td>.847</td><td>.004</td></tr><tr><td>POS3</td><td>← POS</td><td>.853</td><td>.831</td><td>.873</td><td>.003</td></tr><tr><td>POS4</td><td>← POS</td><td>.896</td><td>.877</td><td>.911</td><td>.005</td></tr><tr><td>POS5</td><td>← POS</td><td>.898</td><td>.881</td><td>.912</td><td>.003</td></tr><tr><td>POS6</td><td>← POS</td><td>.749</td><td>.712</td><td>.777</td><td>.005</td></tr><tr><td>POS7_inv</td><td>← POS</td><td>.697</td><td>.658</td><td>.732</td><td>.003</td></tr></tbody></table>