HAPPINESS MANAGEMENT AND TURNOVER INTENTION: SECTORAL DIFFERENCES IN STRESS MEDIATION EFFECTS

HAPPINESS MANAGEMENT E INTENCIÓN DE ROTAR: DIFERENCIAS SECTORIALES EN LOS EFECTOS DE MEDIACIÓN DEL ESTRÉS

Orlando Josué Martínez-Arvizu¹ (Universidad Autónoma de Tamaulipas, México)

Mario Salazar-Altamirano*² (Universidad Autónoma de Tamaulipas, México)

Esthela Galván-Vela³ (CETYS Universidad, México).

Rafael Ravina-Ripoll⁴ (Universidad de Cádiz, Cádiz, España)

Abstract

Talent retention and the reduction of work-related stress have become key challenges in contemporary organisational management. This study explores the impact of Happiness Management on turnover intention, considering work-related stress as a mediating variable, and assessing differences between public and private sector employees. Based on the Job Demands-Resources (JD-R) theory, a quantitative, non-experimental, and cross-sectional design was adopted. Data were collected via a structured online questionnaire from 414 employees in Mexico. The data were analysed using Covariance-Based Structural Equation Modelling (CB-SEM) and Multigroup Analysis (MGA) to compare sectoral differences. The results show that Happiness Management significantly reduces turnover intention both directly and indirectly by lowering work-related stress. These effects are more pronounced in the private sector, where job instability makes employees more sensitive to workplace well-being. In contrast, in the public sector, stress exerts a stronger influence on turnover intention, indicating that bureaucratic constraints and a lack of incentives may diminish the impact of happiness initiatives. The findings highlight the importance of tailoring organisational strategies to the institutional context. Specifically, they suggest that private organisations may benefit more from implementing well-being initiatives, while public institutions should prioritise stress-reduction measures. This study provides empirical support for the integration of Happiness Management into strategic human resource practices and offers sector-specific insights to enhance talent retention and workplace well-being.

Keywords: happiness management, work-related stress, turnover intention, JD-R theory, multigroup analysis.

JEL codes: J28, M12, M54, D23, L32

Resumen

La retención del talento y la reducción del estrés laboral se han convertido en desafíos clave en la gestión organizacional contemporánea. Este estudio analiza el impacto del Happiness Management sobre la intención de rotación, considerando el estrés laboral como una variable mediadora y evaluando las diferencias entre empleados del sector público y privado. Con base en la teoría de demandas y recursos laborales (JD-R), se adoptó un diseño cuantitativo, no experimental y transversal. Los datos se recopilaron mediante un cuestionario estructurado aplicado en línea a 414 empleados en México. El análisis se realizó utilizando modelado de ecuaciones estructurales basado en covarianza (CB-SEM) y análisis multigrupo (MGA) para comparar las diferencias sectoriales. Los resultados muestran que el Happiness Management reduce significativamente la intención de rotación, tanto de forma directa como indirecta, al disminuir el estrés laboral. Estos efectos son más marcados en el sector privado, donde la inestabilidad laboral hace que los empleados sean más sensibles al bienestar organizacional. En contraste, en el sector público, el estrés tiene una mayor influencia sobre la intención de rotación, lo que indica que la burocracia y la falta de incentivos pueden limitar el impacto de las iniciativas de felicidad laboral. Los hallazgos destacan la importancia de adaptar las estrategias organizacionales al contexto institucional. En particular, sugieren que las organizaciones privadas pueden beneficiarse más de implementar iniciativas de bienestar, mientras que las instituciones públicas deberían priorizar medidas de reducción del estrés. Este estudio ofrece evidencia empírica para integrar el Happiness Management en la gestión estratégica de recursos humanos y propone enfoques diferenciados para mejorar la retención del talento y el bienestar laboral.

Palabras clave: happiness management, estrés laboral, intención de rotar, teoría JD-R, análisis multigrupo.

Códigos JEL: J28, M12, M54, D23, L32

1. INTRODUCTION

In an increasingly complex and globalised professional ecosystem, characterised by economic volatility, international competitiveness, the implementation of digital tools such as artificial intelligence, and a growing concern for employee well-being, the concept of Happiness Management has gained unprecedented relevance (Jambrino-Maldonado et al., 2022). In light of these developments, contemporary organisations, particularly those operating in global markets, have begun to recognise that workplace happiness has a particular effect on individual performance, which in turn influences talent retention—an essential factor in the current phenomenon of the "Great Resignation" (Nigoti et al., 2025). This movement, which has destabilised various industries worldwide and revealed widespread dissatisfaction among workers with traditional labour conditions, has redefined priorities in organisational management (Watermeyer et al., 2024). In this scenario, work-related stress plays a significant role, as it can modify the relationship between Happiness Management and turnover intention, influencing employees’ decisions to remain in or leave an organisation (Subramaniam et al., 2024).

From a perspective aligned with the Sustainable Development Goals (SDGs), particularly SDG 8 on "Decent Work and Economic Growth", organisational well-being and employees’ mental health have become strategic pillars for business sustainability (Martínez-Falcó et al., 2024). According to Xue, Jiang et al. (2022), fostering healthy work environments enhances productivity and supports compliance with responsible corporate governance standards. In the context of increasingly globalised and interconnected markets, the promotion of Happiness Management reflects a broader commitment to sustainable and human-centred business models (Cuesta-Valiño et al., 2024c). However, in many emerging contexts, such as Mexico, a gap remains in the academic literature regarding how Happiness Management influences turnover intention and how work-related stress mediates this relationship (Ravina-Ripoll et al., 2024).

From a psychological standpoint, theories such as Job Demands-Resources (JD-R) suggest that workplace resources, including effective Happiness Management, can counterbalance job demands and reduce stress, thereby decreasing turnover intention (Shujahat et al., 2024). Nevertheless, the lack of empirical studies confirming this relationship across different organisational sectors, particularly in public and private enterprises in emerging economies, constitutes a significant research gap (Dirzyte and Patapas, 2022). Moreover, existing literature has addressed the effects of workplace happiness and work-related stress separately, yet few studies have examined the mediating role of stress between Happiness Management and turnover intention (Salazar-Altamirano et al., 2025; Xue, Wang et al., 2022).

In this regard, differentiating between the public and private sectors is crucial, as working conditions, organisational policies, and job stability vary considerably between these environments (Lee, 2021). While public sector employees may experience less pressure regarding job security, productivity demands in the private sector can heighten work-related stress and, consequently, increase turnover intention (Ahmad, 2022). Based on these premises, this study aims to contribute to understanding how Happiness Management and work-related stress influence employees’ decisions to leave their organisations, providing useful evidence for corporate governance, policymakers, and organisational leaders seeking to strengthen talent retention. By clarifying these relationships, more effective workplace well-being and organisational sustainability strategies can be designed.

In this context, this study focuses on the Mexican setting, an emerging economy where organisational environments are shaped by structural dualities, limited institutional resources, and marked differences in employment conditions between the public and private sectors. While global academic discourse has increasingly addressed workplace well-being, there remains a paucity of empirical evidence concerning the specific role of Happiness Management in influencing turnover intention within the Mexican context. This gap is particularly salient when considering the mediating effect of work-related stress, a factor that, according to the Job Demands-Resources (JD-R) theory, may significantly alter the relationship between organisational practices and employee outcomes. By conducting a comparative analysis between public and private institutions, this study seeks to address the geographical and institutional limitations of existing research and to contribute a more nuanced perspective on how happiness-oriented strategies function across diverse organisational environments.

Building on this foundation, the general objective of this study is to examine the effect of Happiness Management on turnover intention, considering work-related stress as a mediating variable. Furthermore, the study aims to explore whether these relationships differ significantly between public and private sector organisations in Mexico. The scientific contribution lies in its comparative approach, integrating the JD-R model with multigroup structural equation modelling to uncover sector-specific dynamics. This framework supports a more context-sensitive understanding of retention strategies in emerging economies and provides empirical insights for both academic and organisational practice. To achieve this objective, the article is structured as follows: the second section reviews the existing literature on key concepts; the third describes the methodology used for data collection and analysis; the fourth presents the results and discussion of findings; and finally, the fifth section discusses the theoretical and practical implications of the research, along with its limitations and future research directions.

2. THEORETICAL FRAMEWORK

This study considers key variables whose analysis allows us to understand organisational turnover intention dynamics. Based on recent contributions from the specialised literature and within the framework of the Job Demands and Resources (JD-R) theory, a model is proposed that integrates the management of happiness at work, job stress and turnover intention, also incorporating a sectoral perspective that distinguishes between the public and private spheres in Mexico.

Figure 1 shows the proposed theoretical model, which considers direct and indirect relationships between the variables and the mediating role of job stress. This conceptual structure forms the basis for formulating the research hypotheses presented below.

2.1. Turnover intention

Turnover intention is defined as an employee’s predisposition to leave their organisation in the near future, whether voluntarily or involuntarily (Peltokorpi et al., 2022). Currently, this phenomenon has attracted the interest of corporate governance and has been studied in organisational management due to its implications for operational stability and organisational culture (Dutschke, 2013; Lin and Huang, 2020). The significance of its study lies in the need to understand the factors that influence employees' decisions to remain in their positions or seek new opportunities (Liu-Lastres et al., 2022). In today's business reality, characterised by highly competitive labour markets and a growing focus on employee well-being, labour turnover has become a strategic challenge for organisations aiming to attract and retain talent (Hartwig et al., 2024).

Enriched by this scientific knowledge, various empirical studies have explored the factors that determine turnover intention, highlighting its relationship with workplace happiness management. An illustrative example is the study conducted in Mexico by Galvan-Vela et al. (2024), which surveyed 393 employees in the education sector. The findings indicated that implementing Happiness Management strategies significantly reduces turnover intention by strengthening employees' emotional connection with the institution and improving their perception of workplace well-being. According to the study, employees who perceive that their organisation invests in their workplace happiness tend to show greater commitment and loyalty to the company, thus reducing their intention to seek alternative employment. However, findings have not been consistent across different contexts. A notable case is the study by Ayele (2022) in Ethiopia, which surveyed 101 public sector employees and concluded that, despite the implementation of workplace well-being programmes, turnover intention did not significantly decrease. In this case, the availability of more attractive job opportunities outside the organisation was a decisive factor in employees’ decisions to leave, highlighting the need for complementary strategies such as salary improvements and career advancement opportunities.

Alternatively, work-related stress has been identified as an undeniable factor influencing turnover intention, as it affects employees' mental health and performance (Salazar-Altamirano et al., 2024a). For this reason, it has been the subject of numerous studies. A paradigmatic case is the study conducted in Malaysia with 391 employees by Rusbadrol et al. (2021), which found that high levels of work-related stress significantly increase turnover intention, as employees seek to avoid work environments perceived as harmful to their psychological well-being. In contrast, some studies have found that the effect of work-related stress on turnover intention can be moderated by other organisational factors. For example, the study by Saraswati and Lie (2021) in Indonesia, involving 225 employees, showed that while work-related stress influences turnover intention, its effect is mitigated when employees perceive a high level of organisational justice. In this case, employees who feel their efforts are recognised and that workplace conditions are fair are more likely to remain in the organisation, even when experiencing stress.

As previously mentioned, some studies analyse the relationship between turnover intention and either Happiness Management or work-related stress separately. However, there is a lack of research integrating both factors. A concrete example is the study conducted in Indonesia by Khairina (2022) with 55 employees, which analysed the interaction between these factors and found that a combination of effective Happiness Management and strategies to reduce stress can decrease turnover intention. The findings indicated that when organisations create a positive work environment and provide mechanisms to manage stress, employees feel more committed and are less likely to seek new job opportunities.

Finally, some empirical studies have explored differences in turnover intention across sectors. One such study by Freire and Azevedo (2023) found that private sector nurses in Portugal exhibited a higher turnover intention compared to their public sector counterparts due to differences in organisational happiness, perceived support, and work-related stress. Conversely, Jovović et al. (2022) argue that the effect of work-related stress on turnover intention is similar across both sectors, suggesting that job stability in the public sector is not always sufficient to reduce turnover.

Based on these arguments, the following research hypotheses are proposed:

H1: Happiness Management has a negative and significant effect on turnover intention.

2.2. Happiness management

Workplace happiness, commonly referred to as Happiness Management, has become a guiding principle in human talent management and organisational psychology (Ravina-Ripoll, Rodríguez et al., 2021). In recent literature, this concept is understood as a strategic approach to promoting employee well-being through emotional, psychological, and social dimensions, with the aim of enhancing both personal fulfilment and organisational outcomes (Cuesta-Valiño et al., 2024c). This discipline focuses on creating work environments that facilitate and stimulate employee well-being and happiness, based on the premise that happy workers are more productive, committed, and resilient in the face of organisational challenges (Del Socorro Encinas-Grijalva et al., 2024; Mercader et al., 2025). Unlike traditional models based exclusively on economic incentives, Happiness Management adopts a holistic view of well-being, incorporating emotional, psychological, and social aspects (Martínez-Falcó et al., 2024). Recent scientific research has highlighted that promoting workplace happiness not only has a positive effect on individual performance but also strengthens organisational cohesion and reduces labour turnover, with employee satisfaction and trust emerging as fundamental pillars in sustaining these outcomes (Aragón et al., 2024; Cuesta-Valiño et al., 2023; Firmansyah and Wahdiniwaty, 2023).

Additionally, academic and business interest in this field has grown exponentially in recent years due to its close relationship with talent retention, which has become a strategic challenge for organisations (Espasandín-Bustelo et al., 2020). In a context of labour uncertainty, rapid change, and an increasing demand for work-life balance, companies seek innovative strategies to enhance employee experience (Ravina-Ripoll, Nuñez-Barriopedro et al., 2021). Over the past fifteen years, accumulated literature has emphasised that implementing organisational happiness policies benefits employees, impacts sustainability, and ultimately improves business profitability by fostering a culture of commitment and loyalty (Alnuaimi and Assali, 2024).

Given this multifaceted situation, one of the most relevant topics within Happiness Management research is its relationship with work-related stress. From this perspective, a study conducted in India with 336 employees by Pradhan et al. (2021) identified that Happiness Management acts as a buffer against work-related stress, promoting greater emotional stability and reducing anxiety levels associated with workload. The findings indicated that employees who perceive organisational support for their well-being experience less burnout and higher job satisfaction, suggesting that happiness-oriented policies can be an effective strategy for mitigating the negative effects of stress in the workplace.

Conversely, while there is consensus on some aspects, not all studies have found a positive relationship between Happiness Management and the reduction of work-related stress. Evidence of this is the study conducted by Sylejmani and Meško (2024) in Kosovo with 60 employees from the business sector, which analysed stress management at work and its effects on organisational performance. Despite efforts to implement well-being strategies, the results showed that factors such as organisational culture, leadership, and job demands could limit the impact of Happiness Management in reducing stress. In this case, employees reported that while happiness initiatives improved the work environment, they were not always sufficient to counteract the effects of excessive workload and organisational pressures.

Based on the above, the following research hypothesis is put forward:

H2: Happiness Management has a negative and significant effect on work-related stress.

2.3. Work-related stress

Work-related stress is a psychological and physiological response to job demands that exceed a worker’s available resources to manage them (Demerouti and Bakker, 2022; Rebolledo and Maturana, 2021). In this regard, models such as Job Demands-Resources (JD-R) explain that this phenomenon occurs when organisational demands surpass individual capabilities, leading to adverse effects on mental health and job performance (Satata et al., 2022). Considering this unfavourable scenario, Marsh et al. (2021) acknowledge that this issue warrants special attention in the current context, where digitalisation, the rise of artificial intelligence, high competitiveness, and increased workloads have intensified stress levels across various industries.

Furthermore, academia has intensified its focus on work-related stress due to its impact on productivity, employee turnover, and organisational well-being (Ilyas et al., 2022). Similarly, the identification of risk factors and the development of intervention strategies are high-impact areas in business management, as prolonged stress can lead to burnout syndrome and ultimately affect organisational competitiveness (Salazar-Altamirano et al., 2024b). Lastly, from a practical perspective, various corporations, particularly multinational companies, have made significant efforts to implement well-being policies and positive leadership strategies to mitigate the effects of stress on employees. However, their effectiveness may vary depending on organisational culture and the productive sector, highlighting the urgency of further exploring their applicability across different contexts (Díaz et al., 2024).

Based on the discussion, the following hypothesis is established:

H3: Work-related stress has a positive and significant effect on turnover intention.

2.4. Mediation of work-related stress in the relationship between happiness management and turnover intention and the Job Demands-Resources (JD-R) Theory

The Job Demands-Resources (JD-R) theory suggests that employees face job demands that can be buffered by organisational and personal resources, ultimately affecting their well-being and performance (Demerouti and Bakker, 2022). Within this framework, Happiness Management is considered an organisational resource that strengthens job commitment, while work-related stress acts as a mediator that can alter the relationship between workplace happiness and turnover intention. According to Van Heerden et al. (2022), workplace well-being can reduce turnover intention; however, this relationship is not linear, as stress can either mitigate or amplify this effect depending on workplace conditions.

Work-related stress has also been identified as a predictor of turnover intention, as it generates emotional exhaustion and reduces organisational commitment (Salama et al., 2022). Within the JD-R framework, when job demands exceed available resources, employees experience greater stress, which increases their likelihood of leaving the organisation (Bakker and De Vries, 2020). In this regard, a study by Van Heerden et al. (2022) conducted in the banking sector of South Africa with 239 employees found that work-related stress not only increases turnover intention but also reduces the positive effect of Happiness Management on job retention.

Moreover, a multigroup analysis between the private and public sectors is essential to understand how these dynamics vary according to the organisational context (Kim and Kim, 2024). In the private sector, where job demands are typically higher and job stability lower, stress can amplify its effect on turnover intention (Alblihed and Alzghaibi, 2022). Conversely, in the public sector, where greater employment security and institutional benefits exist, the impact of stress on turnover may be less significant (Wang et al., 2022). A clear example is the study conducted by Aminihajibashi et al. (2024) in Norway with 256 mental health therapists, which found that professional burnout and work-related stress had a differential impact on turnover intention depending on the level of resources available in each work environment. In organisations with greater resources and structural support, stress had a lower effect on turnover intention, reinforcing the importance of analysing this relationship within a sectoral context. Therefore, this research aims to contribute to the JD-R theory by examining how work-related stress mediates this relationship and varies depending on the organisational context, providing a more contextualised approach to the interaction between these factors.

Based on the theoretical evidence gathered, the following hypotheses are formulated:

H4: Work-related stress mediates the relationship between Happiness Management and turnover intention.

H5: The relationships between Happiness Management, work-related stress, and turnover intention differ significantly between public and private sector employees, showing sector-specific patterns.

3. METHODOLOGY

3.1. Participants and procedure

This study employed a quantitative approach with a non-experimental and cross-sectional design, as this methodology enables the objective measurement of variables and facilitates hypothesis testing through statistical analysis. Given the study’s theoretical foundation and the need to assess relationships among latent constructs, this approach was considered the most appropriate for achieving the research objectives. Data collection was conducted between August and September 2024 using a structured questionnaire distributed digitally through non-probability sampling. Although random sampling was not applied, the composition of the final sample was reviewed to ensure heterogeneity across key demographic and occupational variables. This included representation from various job positions, organisation sizes, and both public and private sectors. Participation was voluntary, ensuring anonymity and confidentiality of responses. The instrument included questions related to sociodemographic variables and job characteristics relevant to the research objectives.

To mitigate potential common method bias (CMB), several strategies were implemented. Firstly, participants' anonymity was ensured, reducing the likelihood of responses being influenced by social desirability. Additionally, neutral language was used in formulating the questions to prevent biased interpretations. As an additional measure, Harman’s single-factor test was conducted, confirming that no dominant latent variable explained most of the variance, indicating that CMB did not pose a significant risk to the validity of the findings (Podsakoff et al., 2003). These measures, combined with a careful survey design, contributed to minimising measurement and selection biases, thereby enhancing the internal validity of the study.

The sample size of 414 participants is considered adequate for covariance-based structural equation modelling, as it ensures reliable parameter estimation and sufficient statistical power for multigroup analysis (Hair et al., 2019). The participants ranged in age from 18 to 70 years (M = 36.9, SD = 9.92). In terms of gender, 63.04% identified as female, while 36.96% identified as male. Regarding job positions, 38.41% held junior roles, 47.10% were in middle management, 7.25% belonged to senior management, and an equal percentage were business owners. Concerning company size, most participants (53.86%) worked in large companies, followed by 18.36% in medium-sized firms, 12.80% in small enterprises, and 14.98% in microenterprises. Finally, 51.69% were employed in public institutions, while 48.31% worked in the private sector. Table 1 provides a detailed breakdown of the sample.

3.2. Instruments

To collect information, a structured questionnaire was designed, incorporating previously validated scales to measure the key variables of the study: Happiness Management, work-related stress, and turnover intention. This instrument was digitally distributed and employed a 5-point Likert scale, where 1 represented "strongly disagree" and 5 "strongly agree." The questionnaire structure allowed for detailed responses regarding participants' perceptions of each variable, facilitating the analysis of their relationships within the workplace environment.

Happiness Management was assessed using the Happiness at Work Scale, in its adapted and validated version by Feitor et al. (2022), consisting of five items measuring the level of satisfaction, motivation, and well-being experienced by employees in their work environment. Meanwhile, work-related stress was measured using eight items from the Inoue et al. Scale (2014), designed to capture perceptions of emotional workload and professional pressure. Finally, turnover intention was evaluated through six items from the Bothma and Roodt Scale (2013), which reflect employees' predisposition to consider new job opportunities. The full list of items used in this study can be found in Appendix 1.

3.3. Data analysis technique

The statistical analysis was conducted using Jamovi software (version 2.3.28), a widely recognised tool valued for its accessibility and capability to perform complex analyses efficiently (Şahin and Aybek, 2019). In the initial phase, a univariate exploration of the data was carried out, including the analysis of central tendency measures such as the mean and standard deviation, along with skewness and kurtosis to assess normality. This procedure ensured the adequacy of the dataset and allowed for the evaluation of the internal consistency of the items comprising each latent construct.

Subsequently, Covariance-Based Structural Equation Modelling (CB-SEM) was applied to test the theoretical model and examine the structural relationships between constructs (Dash and Paul, 2021). This technique was selected over PLS-SEM in view of the study’s confirmatory purpose and the model’s theoretical foundation in the JD-R framework. Moreover, the sample size and distributional characteristics met the statistical assumptions required for CB-SEM, supporting its appropriateness in this context. This method also facilitates the assessment of overall model fit and provides more rigorous estimations of structural parameters (Hair et al., 2019; Hubona et al., 2021), thereby enhancing the robustness and validity of the findings. In line with recent methodological practices, the selection of CB-SEM over PLS-SEM aligns with the criteria outlined by Cuesta-Valiño et al. (2024a, 2024b), who advocate for the choice of estimation technique based on the research objective, theoretical development stage, and model complexity, thus enhancing the robustness and validity of the findings.

Finally, a multigroup analysis (MGA) was conducted to explore potential differences in structural relationships between public and private sector organisations. Following the methodological recommendations of Byrne (2016), measurement invariance was tested prior to the comparison of structural coefficients. This process enabled the identification of statistically significant group differences, offering insight into how sectoral context may influence the relationships proposed within the model.

4. RESULTS

4.1. Exploratory factor analysis

An Exploratory Factor Analysis (EFA) was conducted to assess the internal structure and validity of the scales used to measure Happiness Management, work-related stress, and turnover intention. Initially, item correlations were analysed, showing moderate ranges for Happiness Management (0.509 - 0.732) and work-related stress (0.353 - 0.604), while turnover intention displayed high correlations (0.657 - 0.794), all with a significance level of p < 0.001, indicating significant associations between items within each scale (see Table 2).

The sampling adequacy analysis was performed using the Kaiser-Meyer-Olkin (KMO) test, yielding values of 0.848 for Happiness Management, 0.799 for work-related stress, and 0.918 for turnover intention, all exceeding the recommended threshold of 0.6, confirming the suitability of the data for factor analysis (Kaiser, 1974). Additionally, Bartlett’s test of sphericity was significant in all cases (p < 0.001), indicating that the item correlations were appropriate for EFA application.

Communalities ranged between 0.581 and 0.760 for Happiness Management, 0.513 and 0.682 for work-related stress, and 0.713 and 0.831 for turnover intention, suggesting that the items explain an adequate proportion of the variance for each construct. Finally, the total variance explained was 67.88% for Happiness Management, 59.11% for work-related stress, and 77.00% for turnover intention, indicating that the scales used capture a significant proportion of data variability (Hair et al., 2014).

4.2. Correlational analysis

To examine the relationship between Happiness Management, work-related stress, and turnover intention, a bivariate correlation analysis was conducted using Pearson’s correlation coefficient. This procedure allowed for determining the direction and magnitude of associations among the key variables of the study. The results (see Table 3) indicate that Happiness Management and work-related stress exhibit a significant negative correlation (r = -0.427, p < 0.01), suggesting that as employees experience higher levels of workplace happiness, their stress levels tend to decrease.

Additionally, a stronger negative correlation was observed between Happiness Management and turnover intention (r = -0.573, p < 0.01), demonstrating that employees with greater workplace satisfaction are less likely to consider leaving their organisation. Conversely, work-related stress showed a significant positive correlation with turnover intention (r = 0.448, p < 0.01), indicating that employees who perceive high levels of stress are more predisposed to seeking new job opportunities. These findings confirm the theoretical relationship between Happiness Management, work-related stress, and turnover intention, providing empirical evidence of the impact of employees’ emotional well-being on their retention within the organisation.

4.3. Structural equation modelling

To evaluate the theoretical model and the relationships between Happiness Management, work-related stress, and turnover intention, the Covariance-Based Structural Equation Modelling (CB-SEM) approach was employed using Jamovi software. The analysis included an assessment of model fit and construct validity, ensuring the robustness of the proposed relationships. Additionally, a multigroup analysis (MGA) was conducted to identify potential differences in the model structure among participants based on the type of institution (public vs private). This methodology allowed for examining both direct effects and interactions between variables in different organisational contexts, providing a comprehensive framework to understand how Happiness Management and stress influence turnover intention in distinct workplace environments.

4.3.1. Convergent and discriminant validity

To assess the quality of the measurements used in the model, the convergent and discriminant validity of the constructs Happiness Management, work-related stress, and turnover intention were analysed. In terms of convergent validity, Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE) were calculated for each construct (see Table 4). The results indicate that all scales exhibit satisfactory levels of internal consistency, with Cronbach’s alpha values exceeding the recommended threshold of 0.7 (Nunnally, 1975). Specifically, Happiness Management obtained an alpha of 0.871 in the overall sample (0.876 in the private sector and 0.865 in the public sector), while work-related stress recorded an alpha of 0.857 in the total sample (0.784 in the private sector and 0.762 in the public sector).

Turnover intention showed the highest levels of internal consistency, with an alpha of 0.940 in the general sample (0.932 in the private sector and 0.962 in the public sector). Similarly, composite reliability (CR) values for all constructs exceeded the 0.7 threshold, ranging from 0.774 to 0.952, confirming the stability of the measurements (Hair et al., 2019). Additionally, AVE values ranged between 0.542 and 0.767, ensuring that a significant proportion of the variance in the items is explained by their respective constructs, meeting the minimum recommended threshold of 0.50 (Fornell and Larcker, 1981).

To examine discriminant validity, both the Fornell-Larcker criterion and the Heterotrait-Monotrait Ratio (HTMT) were applied, with results also presented in Table 4. According to the Fornell-Larcker criterion, the square root of the AVE for each construct was greater than its correlations with the other constructs, indicating that each variable is conceptually distinct from the others (Fornell and Larcker, 1981). Specifically, the square root of the AVE for Happiness Management was 0.805, which was higher than its correlations with work-related stress (-0.427) and turnover intention (-0.573), confirming an appropriate differentiation between the constructs. Likewise, the HTMT values were below the critical threshold of 0.85, with 0.376 between Happiness Management and work-related stress, 0.611 between Happiness Management and turnover intention, and 0.437 between work-related stress and turnover intention, reinforcing the discriminant validity of the scales used (Henseler et al., 2015).

4.3.2. Model fit indicators

The quality of the structural model was assessed using various fit indices, categorised into absolute, incremental, and parsimonious fit measures, with the results presented in Table 5. Regarding absolute fit indices, the CMIN was 198 for the total sample and 267 for the multigroup analysis (MGA). Although the associated significance value (p = 0.001) did not meet the standard acceptance criterion (p > 0.05), this result is common in structural models with large samples and does not necessarily compromise the model’s fit (Hair et al., 2019). In terms of SRMR, the values obtained were 0.052 for the total sample and 0.055 for the MGA, both within the recommended threshold of < 0.08, indicating that the discrepancy between the observed and predicted matrices is low (Hu and Bentler, 1999). Similarly, the RMSEA yielded values of 0.075 for the total sample and 0.078 for the MGA, both within the acceptance range, suggesting that the model adequately represents the observed data structure (Browne and Cudeck, 1992).

For incremental fit indices, the results further support the robustness of the model. Both CFI and IFI exceeded the 0.900 threshold, with CFI values of 0.962 (total sample) and 0.960 (MGA), and IFI values of 0.963 (total sample) and 0.961 (MGA), indicating that the model effectively explains the covariance among the data (Hu and Bentler, 1999). Likewise, the TLI values were 0.950 for the total sample and 0.948 for the MGA, confirming that the model presents an adequate fit compared to a null model. In terms of parsimonious fit, the CMIN/DF was 3.35 for the total sample and 2.26 for the MGA, values considered acceptable for structural models with a certain level of complexity (Hair et al., 2019). Finally, the PGFI values were 0.562 for the total sample and 0.561 for the MGA, exceeding the 0.500 threshold, indicating that the model achieves an appropriate balance between fit and structural simplicity (Mulaik et al., 1989).

4.4. Multigroup analysis (MGA)

A Multigroup Analysis (MGA) was conducted to assess whether the proposed relationships in the model differed between the public and private sectors. To ensure comparability between the groups, an invariance analysis was performed by estimating configural, metric, and scalar models, allowing verification of whether the structures and relationships between constructs were equivalent across both subgroups. This evaluation ensured that any differences observed in the structural coefficients were due to actual variations in the relationships between variables rather than inconsistencies in measurement. Subsequently, hypothesis testing was carried out, enabling the identification of significant differences in the influence of Happiness Management, work-related stress, and turnover intention based on the type of institution. This provided a more detailed understanding of how these factors interact in different organisational contexts.

4.4.1. Invariance analysis

The invariance analysis was performed to evaluate the equivalence of measurements between the groups and ensure the validity of comparisons in the MGA. The results, presented in Table 6, include the configural, metric, and scalar models, allowing determination of whether the factorial structures and relationships between constructs remain consistent across both groups. In the configural model, the fit indices reflected a stable factorial structure between the groups, with X² = 267, CFI = 0.960, RMSEA = 0.078, and SRMR = 0.055, indicating that the unconstrained model fits the data adequately for both sectors (Cheung and Rensvold, 2002).

When imposing restrictions on factor loadings in the metric model, X² increased to 284, with a variation of 17 compared to the configural model, while CFI remained practically unchanged (0.959, ∆CFI = 0.001). Additionally, RMSEA improved to 0.076 (∆RMSEA = 0.002), suggesting that factor loadings can be considered equivalent between the groups. Finally, in the scalar model, where intercepts were also restricted, X² increased to 312, with a variation of 28 compared to the metric model. CFI decreased slightly to 0.954 (∆CFI = 0.005), while RMSEA remained stable (0.077, ∆RMSEA = 0.001) and SRMR increased to 0.066, values still within acceptable limits (Byrne, 2016). These results confirm that the criteria for factorial invariance are met, allowing for a valid comparison between the groups and ensuring that the observed differences in structural relationships are not attributable to variations in construct measurement.

4.4.2. Hypothesis testing

To assess the robustness and stability of the estimated parameters, a bootstrapping procedure with 5,000 resamples was conducted. This non-parametric technique allowed for the generation of bias-corrected confidence intervals for all direct and indirect effects. The results obtained through bootstrapping were consistent with those reported in the primary analysis, confirming the reliability of the structural relationships within the proposed model.

The results of the hypothesis testing, presented in Table 7, indicate significant effects in the proposed model relationships. Regarding H1, which posits that Happiness Management (HM) negatively influences turnover intention (TI), a significant negative effect was found in the total sample (β = -0.624, p < 0.001), with a stronger effect in the private sector (β = -0.764, p < 0.001) compared to the public sector (β = -0.567, p < 0.001). The difference between sectors (Δ = -0.197) suggests that employees in the private sector experience a greater reduction in turnover intention when perceiving a higher level of Happiness Management compared to those in the public sector.

For H2, which examines the relationship between work-related stress (JS) and turnover intention (TI), the effect was positive and significant in the total sample (β = 0.392, p < 0.001), indicating that higher levels of work-related stress increase turnover intention. When broken down by sector, the effect was stronger in the public sector (β = 0.436, p < 0.001) than in the private sector (β = 0.349, p < 0.001), with a difference of Δ = -0.087. This suggests that while work-related stress increases turnover intention in both sectors, its impact is more pronounced in public sector employees. Regarding H3, which posits that Happiness Management negatively influences work-related stress, the results show a significant negative effect in the total sample (β = -0.362, p < 0.001), with a stronger effect in the private sector (β = -0.478, p < 0.001) compared to the public sector (β = -0.223, p < 0.001). The difference between groups (Δ = -0.255) indicates that higher levels of Happiness Management are associated with a greater reduction in work-related stress in the private sector.

Finally, for H4, which examines the mediating effect of work-related stress in the relationship between Happiness Management and turnover intention, a significant negative indirect effect was found in the total sample (β = -0.142, p < 0.001). This effect was stronger in the private sector (β = -0.167, p < 0.001) than in the public sector (β = -0.097, p < 0.001), with a difference of Δ = -0.070. This suggests that while work-related stress acts as a mediator in both sectors, its impact is more pronounced in the private sector, where reducing stress through a greater perception of Happiness Management further decreases turnover intention. These findings confirm that workplace well-being management not only has a direct effect on reducing turnover intention but also indirectly influences it through the reduction of work-related stress.

In Figure 2, the structural model developed to analyse the relationship between Happiness Management (HM), work-related stress (JS), and turnover intention (TI) in the total sample is presented. The arrows in the diagram represent the direct effects between the variables, as well as the mediating effect of work-related stress in the relationship between Happiness Management and turnover intention. This model provides a visual representation of how the variables interact and contribute to explaining the levels of work-related stress and turnover intention among participants.

The R² values indicate the explanatory power of the model regarding the dependent variables. Specifically, the R² for work-related stress was 0.182, suggesting that Happiness Management explains 18.2% of the variability in work-related stress. Meanwhile, the R² for turnover intention reached 0.379, indicating that Happiness Management and work-related stress together explain 37.9% of the variability in turnover intention. According to the criteria of Hair et al. (2013), these values reflect a moderate level of model fit, indicating that, while the variables considered in the model influence stress and turnover intention, other factors not included in the analysis may also play a role in these relationships.

5. DISCUSSION AND CONCLUSIONS

The findings of this study provide a deeper understanding of the relationships between Happiness Management (HM), work-related stress (JS), and turnover intention (TI), considering differences between the public and private sectors. In line with the Job Demands-Resources (JD-R) theory (Demerouti and Bakker, 2022), the results confirm that Happiness Management acts as a key organisational resource to reduce both work-related stress and employees’ propensity to leave their organisation, providing empirical evidence on the importance of workplace well-being in talent retention.

Regarding H1, the results indicate that Happiness Management negatively influences turnover intention, with a significant effect in the total sample (β = -0.624, p < 0.001) and a stronger effect in the private sector (β = -0.764, p < 0.001) compared to the public sector (β = -0.567, p < 0.001). This finding supports previous studies highlighting that when organisations prioritise employee well-being, workers develop a stronger sense of belonging and commitment, thereby reducing their turnover intention (Galván-Vela et al., 2024; Khairina, 2022). The difference between sectors suggests that private sector employees rely more on their perception of workplace well-being to remain in their jobs, whereas in the public sector, job stability may partially mitigate the impact of this factor (Wang et al., 2022).

Regarding H2, work-related stress had a positive effect on turnover intention (β = 0.392, p < 0.001), confirming that higher levels of stress increase employees’ likelihood of leaving the organisation. However, this effect was stronger in the public sector (β = 0.436, p < 0.001) than in the private sector (β = 0.349, p < 0.001), partially contradicting previous studies that suggest stress has a greater impact in sectors with lower job stability (Rusbadrol et al., 2021). A possible explanation is that, although the public sector offers greater job security, high levels of bureaucracy and rigidity in management can increase stress, affecting employees’ willingness to stay in their positions.

For H3, the results indicate that Happiness Management significantly reduces work-related stress in the total sample (β = -0.362, p < 0.001), with a stronger effect in the private sector (β = -0.478, p < 0.001) than in the public sector (β = -0.223, p < 0.001). This finding aligns with previous studies suggesting that Happiness Management acts as a buffer for work-related stress, fostering a positive work environment and reducing employees’ perception of workload (Pradhan et al., 2021). The difference between sectors suggests that, in the private sector, where productivity pressures are higher and job stability lower, the effects of workplace well-being on stress reduction are more significant (Alblihed and Alzghaibi, 2022).

Regarding H4, which posits that work-related stress mediates the relationship between Happiness Management and turnover intention, the results confirmed a significant negative indirect effect in the total sample (β = -0.142, p < 0.001). However, this effect was stronger in the private sector (β = -0.167, p < 0.001) than in the public sector (β = -0.097, p < 0.001), suggesting that work-related stress plays a more decisive role in turnover intention within the private sector. This finding is consistent with prior research indicating that in contexts with lower job security, stress becomes a critical factor influencing employees' decisions to seek new opportunities (Saraswati and Lie, 2021).

Finally, H5, which posits sectoral differences in the relationship between Happiness Management, work-related stress, and turnover intention, was confirmed. It was identified that, in the private sector, Happiness Management has a stronger impact on reducing stress and turnover intention, suggesting that, in this context, workplace well-being is a key resource for talent retention (Espasandín-Bustelo et al., 2020; Martínez-Falcó et al., 2024). This aligns with previous studies indicating that in highly competitive environments with lower job stability, employees’ perception of well-being has a greater influence on their willingness to stay (Ravina-Ripoll, Nuñez Barriopedro et al., 2021).

On the other hand, in the public sector, work-related stress had a more pronounced effect on turnover intention, indicating that employees may be more affected by factors such as bureaucracy, lack of incentives, or perceived limited career growth (Kim and Kim, 2024; Alblihed and Alzghaibi, 2022). Prior studies have found that, despite higher job stability, public sector employees may experience elevated stress levels due to rigid administrative processes (Aminihajibashi et al., 2024). Research by Freire and Azevedo (2023) suggests that while turnover intention may be higher in the private sector due to market pressure, job stability in the public sector is not sufficient to prevent turnover if organisational conditions generate stress. Thus, these findings reinforce the need for sector-specific strategies: in the private sector, strengthening workplace well-being initiatives, and in the public sector, improving stress management and organisational flexibility to reduce turnover rates.

The multigroup analysis confirms that the relationships between Happiness Management, work-related stress, and turnover intention vary notably between public and private sectors. In the private sector, Happiness Management plays a more decisive role in reducing both stress and turnover intention, highlighting the importance of organisational well-being in contexts with lower job stability. In contrast, in the public sector, turnover intention appears to be more strongly influenced by work-related stress, likely due to factors such as bureaucracy and limited incentives. These findings underscore the need for sector-specific approaches: while private organisations may benefit from strengthening well-being initiatives to retain talent, public institutions should prioritise strategies aimed at stress reduction and structural flexibility. Overall, this study provides a differentiated and context-sensitive perspective on the strategic role of Happiness Management in managing employee retention.

6. PRACTICAL, THEORETICAL AND SOCIAL IMPLICATIONS

The findings of this research contribute to the literature on Happiness Management, work-related stress, and turnover intention, providing empirical evidence on the role of Happiness Management as an organisational resource that influences talent retention. In line with the Job Demands-Resources (JD-R) theory (Demerouti and Bakker, 2022), the results reinforce the idea that workplace resources, such as a positive organisational environment, can reduce the negative effects of stress and enhance employee retention within an organisation.

Furthermore, the confirmation of H5 offers a novel perspective, demonstrating that the relationship between Happiness Management, work-related stress, and turnover intention varies significantly between the public and private sectors. While previous studies have examined these factors separately (Ravina-Ripoll, Nuñez Barriopedro et al., 2021; Xue, Wang et al., 2022), this study provides a holistic perspective on how these relationships are structured differently in each sector. These findings expand the theoretical framework by emphasising the importance of contextual and sectoral factors in managing workplace well-being and talent retention.

From an organisational perspective, the results highlight the need to design sector-specific strategies to improve talent retention through the implementation of targeted Happiness Management practices. In the private sector, where job stability is generally lower, organisations can introduce structured well-being programmes that include regular emotional climate assessments, flexible work arrangements, recognition systems, and employee development plans. Promoting positive leadership, transparent communication, and participatory decision-making processes can further enhance employees' sense of belonging and purpose, thereby reducing turnover intention and improving satisfaction.

Conversely, in the public sector, where work-related stress exerts a stronger influence on turnover intention, it is essential to implement stress-reduction initiatives tailored to bureaucratic environments. These may include mental health support services, workload redistribution policies, conflict resolution mechanisms, and resilience training workshops. Additionally, offering non-monetary incentives such as career progression pathways, internal mobility programmes, and enhanced feedback systems can strengthen employees' perceived value within the organisation, helping to mitigate the negative impact of structural rigidity and procedural inefficiencies. Moreover, fostering open communication and better alignment between organisational actions and employee expectations, as highlighted by Penelas-Leguía et al. (2023), could enhance employee satisfaction and organisational commitment in the public sector.

Workplace well-being and reduced turnover have broader social implications beyond the organisational level. Lower employee turnover contributes to economic stability for workers and their families, reducing financial uncertainty and fostering long-term professional development. Moreover, promoting organisational happiness is linked to the development of broader management models focused on citizen satisfaction and social trust, helping strengthen social structures and democratic participation (Núñez-Barriopedro et al., 2024). Additionally, employees who perceive high levels of workplace happiness tend to experience lower levels of emotional exhaustion and stress, improving their quality of life and psychological well-being (Subramaniam et al., 2024).

From a broader perspective, this study reinforces the importance of workplace well-being as a factor aligned with the Sustainable Development Goals (SDGs), particularly SDG 8: Decent Work and Economic Growth (Martínez-Falcó et al., 2024). Organisations that prioritise employee well-being not only generate positive impacts at an individual level but also enhance productivity, labour market stability, and sustainable economic growth. In this sense, the findings could serve as a foundation for future public policies aimed at improving working conditions and promoting a corporate culture centred on employee well-being.

7. STUDY LIMITATIONS AND FUTURE RESEARCH DIRECTIONS

This study presents several methodological and contextual limitations that should be considered when interpreting the results. The use of a cross-sectional design restricts the ability to establish causal relationships between the variables analysed, as data were collected at a single point in time. Additionally, the research focused solely on employees in Mexico, which may limit the generalisability of the findings to other socio-cultural and economic contexts. Organisational dynamics, perceptions of workplace well-being and turnover intention may vary significantly in different regions, thereby affecting the external validity of the conclusions.

Moreover, the use of non-probability sampling introduces potential selection bias and reduces the representativeness of the sample. While the final sample included diversity in job positions, sectors and organisation sizes, it cannot be considered statistically representative of the broader population. Regarding data analysis, CB-SEM was selected due to the theoretical nature of the model and the adequacy of the sample, but the technique relies on assumptions such as multivariate normality and large sample sizes. Although these were met, the exclusive use of this method may limit analytical flexibility. Furthermore, the model focused on Happiness Management and work-related stress, without accounting for other potentially influential variables such as leadership, organisational culture, salary satisfaction, or professional development opportunities.

Building on the identified limitations, future research could explore the impact of internal marketing on the relationship between Happiness Management, work-related stress, and turnover intention. Strategies such as organisational communication, employee recognition, and the development of a strong corporate identity could play a crucial role in talent retention, promoting greater workplace happiness and reducing perceived job uncertainty. Additionally, future studies could examine how these strategies vary by company size, as internal marketing may play a more structural role in large corporations, whereas in small businesses, the proximity between employees and leaders may be a differentiating factor in the perception of workplace well-being.

Furthermore, it is recommended to expand the multigroup analysis beyond the public-private sector comparison, incorporating variables such as gender, age, hierarchical level, or generational differences. This would allow for identifying whether perceptions of Happiness Management and work-related stress vary among millennials, Generation Z, and older employees, or whether differences are more pronounced among employees in leadership positions versus those in operational roles. Additionally, replicating this study across different industries, such as technology, education, or healthcare, would be valuable, as workload and job stability may influence turnover intention differently across sectors.

Finally, future studies could adopt a longitudinal approach to assess how these relationships evolve over time and whether the impact of Happiness Management on reducing stress and turnover intention is sustainable in the long term. This would enable the analysis of how economic changes or shifts in organisational culture affect employee retention, and whether workplace well-being strategies need to be dynamically adjusted to evolving market conditions.

FUNDING

This research has not received external funding.

AUTHOR CONTRIBUTIONS

All authors have equally contributed to the study’s conception, methodological design, data collection, and analysis, manuscript drafting, and subsequent review and editing. Additionally, they have been involved in the supervision of the research process, conducted a critical review of the content, and approved the final version of the document.

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APPENDIX

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^* Autor de correspondencia: mario_salazar_altamirano@hotmail.com

¹ ORCID: https://orcid.org/0000-0003-3499-5184

² ORCID: https://orcid.org/0009-0005-7110-3378

³ ORCID: https://orcid.org/0000-0002-8778-3989

⁴ ORCID: https://orcid.org/0000-0001-7007-3123