Green work-life synergy? Exploring pathways from green HRM to organizational environmental performance
- Open Access
- 10-02-2025
- Original Paper
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Abstract
1 Introduction
The dynamic interplay between private and professional lives continues to present significant challenges for both companies and their employees. The interactions between work and personal life, which can either lead to conflict or enrichment, have long been a focal point for scholars (for a review, see, e.g., Calzón-Menéndez et al. 2021; Rashmi and Kataria 2022). However, this topic has gained renewed attention in the wake of the COVID-19 pandemic, as the widespread adoption of technology along with flexible work arrangements has fundamentally revolutionized the way we live and work (Bouncken et al. 2022; Feery and Conway 2023; Schäfer et al. 2023). This renewed scrutiny also coincides with growing concerns about climate change and increasing societal and stakeholder pressure, urging companies to prioritize sustainability initiatives that promote employee well-being, environmental conservation, and community welfare (e.g., Amrutha and Geetha 2020). As companies evolve towards integrating digital transformation and adopting sustainable development goals, there is a heightened focus on green innovations and initiatives as pivotal strategies for achieving long-term competitive advantage and for tackling global climate change and environmental degradation (Chang et al. 2024; Chopra et al. 2024; He et al. 2024b). Furthermore, the implementation of practices aimed at enhancing work-life balance has emerged as a key corporate responsibility, reflecting their commitment to social responsibility and ethical conduct (Heikkinen et al. 2021).
The growing focus on green innovation and work-life practices reflects a broader transition towards more holistic ways of living and working. This trend underscores a company’s commitment to sustainability and responsibility, both crucial in boosting competitiveness, cultivating a sustainable work environment, improving societal outcomes, and improving the overall quality of life (Chang et al. 2024). Human resource management (HRM) plays a key role in assisting companies and employees in harmonizing work-life commitments and pursuing sustainability goals where employee effort and commitment are essential (Yeşiltaş et al. 2022). Within HRM, the flourishing subset of green HRM “is concerned with transforming normal employees into green employees so as to achieve environmental goals of the organization and finally to make a significant contribution to environmental sustainability” (Opatha and Arulrajah 2014, p.104). The goal is to promote environmentally friendly policies and practices, both at an organizational level (e.g., energy efficiency, waste reduction, and recycling programs) and by directly engaging with employees (e.g., green recruitment, green training, and green rewards). In both cases, the aim is to diminish the company’s “ecological footprint” and contribute to environmental conservation while optimizing organizational environmental performance (e.g., Gilal et al. 2019; Guerci et al. 2016; Ogiemwonyi et al. 2023).
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One key green HRM practice is precisely green work-life balance (Muster and Schrader 2011; Ren et al. 2018; Pham et al. 2020). This is defined as “the reconciliation of working life and private life with regard to environmental values, attitudes and behavior. It comprises mutual enforcement and the harmonization of environmentally friendly orientations in private life and working life” (Muster and Schrader 2011, p. 148). This innovative approach seeks to promote eco-friendly behavior in both the professional and private spheres (Bangwal et al. 2017; Cinderby et al. 2023; Datta 2015; Vasa and Sowdamini 2017). In this context, individuals can transfer information and green behaviors from their private lives to their professional ones, thereby enriching and positively affecting the company’s environmental performance (Muster and Schrader 2011). This type of performance refers to a company’s commitment to design business activities and strategies that encourage environmentally-sustainable behaviors working towards ecosystem conservation and protection (Aftab and Veneziani 2024). The literature demonstrates that green HRM and employees’ pro-environmental behavior are significant facilitators of organizational environmental performance (Aftab and Veneziani 2024).
To analyze the impact of green HRM on organizational environmental performance and the role of employees’ green behavior both at work and in their private life, we draw on the Ability-Motivation-Opportunity (AMO) framework (e.g., Renwick et al. 2013), and Spillover (e.g., Edwards and Rothbard 2000; Hanson et al. 2006; Nash et al. 2019) and Identity Process theories (e.g., Breakwell 1986, 2021; Jaspal and Breakwell 2014; Verfuerth et al. 2019). Building on the idea that work and private life behaviors interact and influence each other in an iterative process, Muster and Schrader (2011) warn that focusing solely on workplace behavior is clearly insufficient, emphasizing the need for a greater understanding of the private sphere’s role in this context. As these authors state, “green HRM might fail in realizing its full potential if they focus merely on employees in their working role” (Muster and Schrader 2011, p. 144). Studies exploring the spillover of green behavior between work and private life settings are still limited (e.g., Cinderby et al. 2023). Evidence suggests that only green behavior at work serves as a mediator in the influence of green HRM on environmental performance, while no mediation effect has been observed for green behavior at home (Bangwal et al. 2017). In light of these restricted insights, we aim to investigate the influence of both work-related and private-life green behaviors in the relationship between green HRM and organizational environmental performance. To achieve this objective, we intend to perform a serial mediation analysis to scrutinize the contextual spillover effects across the work and private life. To the best of our knowledge, this mediation pathway has not been examined previously. Using survey data from 237 employees of a Portuguese consultancy firm certified for pro-environmental practices, our findings emphasize that green HRM practices (particularly recruitment, performance appraisal, and rewards) have a greater impact on enhancing organizational environmental performance than the serial mediation pathway involving green behaviors of employees in both work and private life contexts.
This study contributes to the field of green HRM and organizational pro-environmental research – a sphere still needing further exploration (Jnaneswar 2023) – by broadening understanding in the emerging area of green work-life balance (Ravenswood 2022). By exploring the dynamics of merging the workplace and private spheres to improve organizational environmental performance, where there is evidence of spillover effect driven by environmental identity (Verfuerth et al. 2019), this study is unique in its approach, as it empirically examines a serial explanatory pathway in which green behavior in both spheres mediates the relationship between green HRM and organizational environmental performance. Although the results indicate that green HRM practices have a more substantial impact on environmental performance than green behavior in either sphere, the findings provide insightful information for creating effective programs and policies. Given the need to accelerate societal change to tackle sustainability issues such as climate change (Frezza et al. 2019), these insights can empower companies to extend their environmental impact beyond the workplace by generating positive spillovers.
2 Literature review and hypothesis development
2.1 Green HRM practices and organizational environmental performance
Companies are increasingly formulating strategies that incorporate and prioritize environmental performance, reflecting a commitment to adopt business practices that contribute to the preservation and protection of the environment (Aftab and Veneziani 2024). This focus represents the environmental pillar of sustainable performance, which also includes financial and social performance (Khan et al. 2024).
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Innovative measures to enhance environmental performance include implementing green processes in manufacturing that reduce waste and emissions; improving energy efficiency; and developing eco-friendly products, green packaging, and green product labeling (e.g., Yusoff et al. 2020). Companies can monitor environmental performance through various techniques, including environmental reporting, scorecards, resource acquisition, usage tracking, and conducting environmental audits. Compliance with international standards such as ISO 14,001 provides a structured framework for achieving high environmental performance (Johnstone and Hallberg 2020). Companies can gain a competitive advantage and enhance public recognition (i.e., through winning sustainability awards) by reducing environmental impacts, aligning with environmental standards, and investing in the production and distribution of environmentally friendly products. This is all done with the overall objective of improving the organization’s performance (García-Sánchez et al. 2024; Mugoni et al. 2024).
However, a company’s environmental performance effectiveness hinges on employees’ adherence to standards and their willingness to engage in behaviors consistent with the above-mentioned overall goal. It is therefore crucial for companies to establish an HR policy aligned with strategic environmental objectives and which incorporates green components to encourage employee participation in these initiatives (Gilal et al. 2019; Yusoff et al. 2020). Nonetheless, achieving this alignment proves challenging when employees display indifference towards the implementation of green practices, with such behavior being often based on the perception that the company lacks genuine commitment to its environmental values, which makes employees less inclined to embrace and support such initiatives (Rashid and Mohammad 2012). It is worth noting that employees’ perceptions often hold more weight than the firm’s actual actions (Tosti-Kharas et al. 2017).
The green policies, practices, and procedures encompassed in HRM – known as green HRM – contribute to the environmental sustainability of companies and promote pro-environmental behaviors among employees, thus benefiting individuals, society, and the environment (Opatha and Arulrajah 2014). Through the implementation of green HRM practices, the company communicates its commitment to environmental sustainability beyond mere economic gains, actively involving employees in eco-conscious decisions and initiatives (Renwick et al. 2013). Green HRM should align with a company’s environmental values and strategies, designed to achieve high environmental performance and thus a competitive advantage (Saeed et al. 2019; Shah 2019; Yasin et al. 2023; Yong et al. 2020). Empirical evidence emphasizes that green HRM practices are instrumental in achieving broader sustainability objectives, going beyond compliance mechanisms or short-term gain strategies (Chang et al. 2024). Nevertheless, green HRM presents various challenges for companies, such as finding candidates with aligned environmental values, encouraging employees to adopt pro-environmental behaviors effectively, and assessing employees through green performance appraisals, together with problems in recruiting or fostering environmentally sensitive leaders who can influence others and the slow progress in developing a green organizational culture (Hosain and Rahman 2016). These challenges reflect the wider context of corporate social responsibility activities, which impact firm performance in varying ways, showing positive and negative effects depending on implementation degree. Instead of bringing immediate benefits, these activities typically yield advantages only after surpassing a certain threshold (Lin 2024).
Green HRM encompasses various practices, all of which are prefixed with “green”. For example, green recruitment and selection emphasize the hiring of individuals with strong ecological values, thereby promoting the development of a green-collar workforce (Renwick et al. 2013). Employers incorporate green criteria, such as including environmental values in job descriptions, tend to ask ecological questions during interviews, and also employ remote selection processes (Mwita and Kinemo 2018; Opatha and Arulrajah 2014; Renwick et al. 2013), while eco-sensitive candidates are attracted to companies with strong green branding (Shah 2019). Green training cultivates environmental values and skills in employees, enhancing their commitment and motivation to adopt eco-friendly behavior and contribute to the company’s green objectives (e.g., Saeed et al. 2019; Tang et al. 2018; Yusoff et al. 2020). Green performance appraisal is an assessment of employees that offers feedback on the achievement of environmental goals (Jabbour et al. 2010). These results influence green rewards – which can be either monetary (e.g., bonuses) or non-monetary (e.g., awards, tax breaks for eco-friendly vehicles, or discounts on public transportation) – that recognize pro-environmental behavior and contribute to advancing environmental goals (e.g., Saeed et al. 2019; Shah 2019; Yusoff et al. 2020). Green involvement refers to employees’ participation in environmental decision-making, where they are given opportunities to engage in environmental management. Examples include forming teams dedicated to environmental initiatives, establishing problem-solving groups, appointing “champions” of best practices, and encouraging remote work and carpooling (Renwick et al. 2013; Tang et al. 2018).
These practices are interconnected and mutually reinforcing, as evidenced by numerous studies that aggregate them into clusters based on the AMO theory (e.g., Fawehinmi et al. 2022; Renwick et al. 2013). According to this theory, green recruitment and selection along with green training enhance employees’ abilities; green performance management and green rewards promote motivation, while green involvement creates opportunities (e.g., Guerci et al. 2016). When these practices operate together, they encourage employees to engage in environmentally sustainable behavior at the workplace, thereby contributing positively to organizational environmental performance (e.g., Aftab et al. 2022; Aftab and Veneziani 2024; Bangwal et al. 2017; Kularathne 2020; Yusoff et al. 2020). Green recruitment ensures that the workforce possesses the necessary skills and sensitivity to adopt and implement the organization’s environmental management systems effectively, which is essential for bolstering organizational sustainability performance (Jamil et al. 2023). Green training equips employees with practices and work methods designed to save energy, reduce waste, and improve the ecological system, ultimately enhancing the organization’s environmental performance (Deshpande and Srivastava 2023; Pham et al. 2020). Green performance appraisal fosters a culture centered on environmental performance, driven by clearly defined green objectives, criteria, and indicators (Yusoff et al. 2020), which are all crucial for efficient performance management systems and environmental performance (Guerci et al. 2016; Tang et al. 2018). Green rewards support environmental management efforts by motivating employees to adopt pro-environmental behavior and achieve sustainability goals (Saeed et al. 2019; Yusoff et al. 2020). Lastly, green involvement strengthens employees’ commitment and contribution to achieving high environmental performance, by offering them the opportunity to leverage their skills and knowledge in support of environmental goals (Ari et al. 2020; Mishra 2017; Renwick et al. 2013; Tang et al. 2018).
Despite some studies reporting contradictory findings (e.g., Bhatti et al. 2022; Rehman et al. 2021), green HRM practices – whether implemented individually or collectively – are generally seen as positively contributing to an organization’s environmental performance (e.g., Aftab et al. 2022; Aftab and Veneziani 2024; Bangwal et al. 2017; Kularathne 2020; Yusoff et al. 2020). Therefore, in this context, we propose the following hypothesis:
H1.
Green HRM positively influences organizational environmental performance.
2.2 Green work-life behavior
The portfolio of green HRM practices plays a critical role in fostering sustainable behavior by encouraging employees to act and make decisions concurrent with the company’s environmental values (Muster and Schrader 2011). The literature consistently highlights the influence of green HRM practices on employees’ green behavior at work (e.g., Saeed et al. 2019; Yeşiltaş et al. 2022), contributing to the overall environmental performance of the organization (e.g., Dumont et al. 2017; Jabbour and Santos 2008; Roy et al. 2013). Green behaviors can be performed at work, either within or outside the scope of employee’s role. They can directly affect the environment (e.g., through activities that benefit it) or indirectly (e.g., by encouraging colleagues to behave more sustainably), and can vary from low-intensity (e.g., energy saving) to high-intensity actions (e.g., creating proposals for the improved environmental performance of the company) (Bentler et al. 2023).
Although influencing behavior in private life is not the primary aim of firms adopting green HRM practices, these workplace initiatives are still effective in encouraging employees to adopt sustainable habits and behavior outside work (Bangwal et al. 2017; Muster and Schrader 2011; Piligrimiene et al. 2019). For instance, companies with successful waste management programs, or those that offer organic products in their cafeterias, can respectively present information and aid for recycling and waste reduction at home or facilitate bulk purchasing from local organic farmers (Muster 2011). Such behavior underscores the importance of mutual influence between individuals’ private and professional lives (e.g., Edwards and Rothbard 2000). In other words, employees who engage in green practices at work are likely to repeat these behaviors in their private lives. This occurs because individuals, in essence, are the same both as employees and in their personal lives, applying and reinforcing environmentally-conscious behavior across all life sectors (Muster 2011; Muster and Schrader 2011). This interconnection underscores the relevance of green work-life balance, an emerging field of study that broadens the traditional work-life balance framework to incorporate environmental protection (Ravenswood 2022).
The potential synergy between work and private life spheres may originate from either affective experiences (e.g., positive affective states in one sphere can generate positive energy in others), behaviors (e.g., behaviors learned in one sphere can assist in achieving goals in other spheres), or value-based spillover (e.g., values acquired and exercised in one life sphere can be reinforced by and permeate others) (Hanson et al. 2006). This synergy can also stem from identity processes, as our sense of self (our identity) promotes behavioral consistency across time and contexts, thereby driving spillover effects (Frezza et al. 2019; Verfuerth et al. 2019). Environmental identity, a facet of self-concept, describes individuals’ perceived identification with the physical and natural world (Clayton and Czellar 2023). As per the Identity Process Theory (IPT), an individual’s identity is viewed as “a dynamic process and a dynamic state of being” (Breakwell 2014, p. 25), a multifaceted phenomenon continually adjusting to social context and ongoing social changes (Breakwell 1986; 2014). This theory elucidates how changes in one life sphere can impact an individual’s self-concept. The self’s integrity is governed by specific principles (Breakwell 1986, 2021), including continuity over time (ensuring congruity between past, present, and future identities), distinctiveness from others (feelings of uniqueness and differentiation), self-esteem (an individual’s subjective appraisal of personal worth), and self-efficacy (individuals’ perception of their competence and control over their life and situations). Later, other principles were included, such as belonging, meaning, and coherence (Jaspal and Cinnirella 2010; Vignoles 2011). Threats to these principles stimulate coping strategies. When changes are experienced as positive or well-aligned with core values, individuals may assimilate these changes into their identity, reinforcing a cohesive sense of self. In contrast, when changes are perceived as threatening, individuals may use coping mechanisms to protect their identity, potentially resisting or compartmentalizing aspects that are not aligned with their existing self-image.
Since changes in social context can lead to shifts in identity, it is arguable that green HRM practices, as a workplace intervention, enhance employees’ ability, motivation, and opportunity to engage in organizational green activities, thereby shaping their self-concept (in line with AMO theory, as explained above). Consequently, this is likely to bolster their efforts towards improving organizational environmental performance and may inspire their families and friends, thus extending the firm’s environmental impact to the broader community (Ravenswood 2022). This widespread influence further enhances the company’s reputation as a socially responsible organization, which, in turn, enhances the company’s overall environmental performance (Muisyo et al. 2022). It may thus be inferred that both spheres of an employee’s life potentially exert a positive influence on the company’s environmental performance. In light of these possibilities, it is important to test the following hypotheses:
H2.
Employees’ green behavior at work mediates the relationship between green HRM and organizational environmental performance.
H3.
Employees’ green behavior in their private lives mediates the relationship between green HRM and organizational environmental performance.
2.3 Green spillover processes
In the environmental domain, a spillover occurs when one environmentally sustainable behavior influences the likelihood of engaging in, disengaging from, or showing no effect on a subsequent behavior, resulting in positive, negative, or neutral spillover effects (Nash et al. 2019; Nilsson et al. 2017; Verfuerth et al. 2019). Such an observable behavior change occurs in response to a specific intervention (Truelove et al. 2014). A spillover can be categorized as behavioral (across different types of behavior, such as recycling and using public transport), contextual (across different settings, such as energy-saving practices at work translated into corresponding actions at home), or temporal (having an effect at different time points) (e.g., Nilsson et al. 2017).
In particular, in terms of cross-contextual spillovers, which have received limited attention to date (Verfuerth et al. 2019; Frezza et al. 2019), past studies exhibit mixed results, with some showing little spillover between work and life settings (e.g., Littleford et al. 2014; Wells et al. 2016), while others report positive influences (e.g., Rashid and Mohammad 2012; Tudor et al. 2007). Despite inconsistent empirical evidence, workplaces serve as ideal settings for implementing sustainable and eco-friendly practices, offering a “learning space” (Muster 2011), where employees acquire and adopt new environmental behavior that have the potential to foster sustainable consumption patterns beyond the organizational context. By adopting sustainable practices, firms can create unique opportunities to influence and reinforce such behaviors in employees’ private lives (Klade et al. 2013), as employees tend to act as producers at work and consumers in their private lives (Muster 2011). Likewise, an individual who has adopted ecological habits at home may seek to implement similar behavior at work (Muster and Schrader 2011; Deshpande and Srivastava 2023). It is worth noting, though, that green behavior at work is not often controlled by employees but by their roles or workplace policies. A lack of autonomy, control, or support from managers and colleagues can become a significant barrier in the organizational context, inhibiting the transfer of green behavior from home to the workplace (Bentler et al. 2023; Cinderby et al. 2023).
To promote cross-contextual synergies, implementing practices or programs designed to foster sustainable routines at work can shape shared meanings and competencies, thereby improving workplace sustainability and inciting positive changes in employees’ personal lives (Frezza et al. 2019). This underscores the value of framing green HRM policies and practices in a way that encourages employees to adopt pro-environmental behavior. Ultimately, these policies can influence their attitudes in both professional and private spheres (Piligrimiene et al. 2019). This alignment stems from individuals’ efforts to maintain a consistent self-concept across various contexts, ensuring coherence and avoiding internal conflict. This identity-driven spillover is reinforced by green HRM practices that are designed to reward or recognize these behaviors, rendering them part of the employees’ self-concept. Grounded in IPT, Verfuerth et al. (2019) present an integrated framework of identity-related processes that can either lead to the presence (positive or negative) or absence of contextual spillover effects. When integration occurs, engaging in environmental behavior reinforces individuals’ environmental self-identity, increasing the likelihood of a positive spillover. Conversely, when integration is unsuccessful, identity compartmentalization occurs, which may lead to the following: less likelihood of spillover, the emergence of conflicting identities, and the suppression of environmental identity. In the absence of spillover, the tendency is to consequently strengthen a non-environmental identity to resolve the conflict, which in turn is likely to trigger environmentally-harmful behavior and lead to negative spillover effects.
Assuming that individuals remain the same in their private and professional spheres (Muster 2011; Muster and Schrader 2011), and considering they spend a considerable portion of their daily lives either at work or at home (Verfuerth et al. 2019), their behavior in both settings is significant for sustainability, where the interactions between work and private lives can facilitate the adoption of green behavior in both contexts. To summarize, a positive contextual spillover is clearly desirable, and thus implementing green HRM practices in the workplace does not just support and encourage employees’ sustainable behavior, but can also trigger a spillover effect where this behavior extends to their private lives, as shown in previous research (Datta 2015; Gayathri and Karthikeyan 2013; Muster and Schrader 2011; Ragas et al. 2017). Bangwal et al.’s (2017) study shows that the positive impact of green HRM on organizational environmental performance is mediated by employees’ green behavior at work, but not by their green behavior in their private lives. This suggests the potential to test a serial mediation model, which proposes that green HRM – although not explicitly intended to encourage green behavior beyond the workplace – can influence the adoption of similar behavior at home, as individuals strive to align their actions with their identity to avoid dissonance, and in turn foster a positive spillover effect, increasing overall commitment to sustainability, and ultimately enhancing organizational environmental performance.
H4.
Employees’ green behavior both at work and in their private life acts as a serial mediation in the relationship between green HRM and organizational environmental performance.
Drawing from the literature review, Fig. 1 illustrates the research model, showcasing the relationships explored in the study.
Fig. 1
Research model
3 Methods
This study utilized structural equation modeling (SEM) with a partial least squares (PLS) estimation (Hair et al. 2018). The data were analyzed using SmartPLS 4 software, a variance-based technique, which was employed to test the hypothesized research model (Ringle et al. 2020). This technique is particularly appropriate for research models including higher-order latent constructs and complex model structures such as multiple mediation relationships (Hair et al. 2017a; Iqbal et al. 2020). The data were subjected to initial normality tests in SPSS software using the Kolmogorov-Smirnov test and Shapiro-Wilk, yielding results that indicate a non-normal distribution. Therefore, the choice of PLS is appropriate, given that it does not necessitate data to be normally distributed (Hair et al. 2011).
3.1 Sample and procedures
The study sample is comprised of employees working for the same consulting firm in Portugal. Sustainability has been a concern for this firm since 2015 but only became an integral part of its values and strategy during the COVID-19 pandemic in 2020. The firm holds ISO 14,001 certification, which is widely recognized as a strong sign of a firm’s commitment to environmental protection. By following this standard, firms adjust their operational practices to better safeguard the environment, thereby increasing their likelihood to embrace efforts aimed at advancing green innovation and sustainable practices (He et al. 2024). A significant component of this commitment is evident in the firm’s adoption of green HRM practices, designed to drive employees’ green behavior and improve the company’s environmental performance. However, the specific details of these practices are kept confidential by the firm. Among its disclosed green practices, the firm disseminates ecological information internally via an intranet page dedicated to reducing and offsetting carbon emissions, and shares informative videos on its corporate television. It also promotes sustainability through a weekly suggestion board on the internal social network, a biweekly sustainability section in the internal magazine, and digital training sessions on related topics. Further, the firm supports electric vehicles by providing charging stations and offering agreements and discounts for hybrid and electric car leases. They also utilize green energy in their offices and encourage the use of reusable items by providing drinking fountains, cups, and glass bottles to employees, actively combating the use of disposable products in the workplace.
For this study, data collection entailed distributing a survey via the company’s intranet platform in April 2022, following the HR department’s approval. The questionnaire dispatch was paired with a cover letter to explain the study’s objective, assure anonymity, and request voluntary participation with informed consent. The research employed a cross-sectional design, and a total of 345 questionnaires were returned, constituting a 14.3% response rate. After excluding incomplete submissions, a sample of 237 questionnaires was secured – suitable for subsequent PLS analysis (e.g., Goodhue et al. 2012; Hair et al. 2011; Ringle et al. 2020). Respecting the company’s anonymity request – restricting additional sociodemographic dimension disclosure – the provided data reveals that 59% of respondents were female, with an average age of 31 (SD = 8.7), 24% have children, and 32% hold managerial roles. The average company tenure stands at 5 years (SD = 7.2).
3.2 Measures
This study employs validated scales to measure all constructs, with all items assessed using a 5-point Likert scale that ranges from 1 (strongly disagree) to 5 (strongly agree), including a “don’t know/no response” option. Green HRM is evaluated using a scale devised by Tang et al. (2018), with the following subdimensions: green recruitment and selection (three items) (e.g., “We use green employer branding to attract green employees”), green training (three items) (e.g., “We develop training programs in environment management to increase environmental awareness, skills, and expertise of employees”), green performance appraisal (four items) (e.g., “Our firm sets green targets, goals, and responsibilities for managers and employees”), green rewards (three items) (e.g., “Our firm has recognition-based rewards in environment management for staff (public recognition, awards, paid vacations, time off, and gift certificates”), and green involvement (five items) (e.g., “Our company has a clear developmental vision to guide the employees’ actions in environment management”). The Organizational Environmental Performance (five items), Employees’ Green Behavior at Work (five items), and Green Behavior in Private Life (five items) are measured using scales developed by Bangwal et al. (2017). Examples of scale items are, respectively: “Green HRM within my firm encourages the internal and external reutilization and recycling of waste”; “I can express my green innovative ideas at work”; and “Family members, friends, and acquaintances have started doing green practices at home because of me”.
3.3 Assessment of common method bias
Data collected through self-reporting may encounter the potential challenge of common method bias (CMB) (Podsakoff et al. 2012). For this reason, procedural and statistical mitigations are implemented to control and minimize CMB. For procedural remedies, complete confidentiality and anonymity for participants are ensured to prevent dishonest responses (Podsakoff et al. 2003, 2012). In relation to statistical methods, two tests are employed to assess the presence of CMB in the dataset. Initially, Harman’s single factor test is performed, with the results indicating that a single unrotated factor explains 33.35% of the total variance, which suggests that CMB is not a concern in this study. Following this, in line with Kock (2015), a full collinearity test is performed using PLS-SEM to generate variance-inflated factors (VIF). The threshold set for VIF is 3.3. VIF is a multivariate measure indicating the existence of multicollinearity in a regression analysis, and it provides an estimation of how much the variance of each predictor (i.e., the regression coefficient) is inflated due to multicollinearity in the model (Kock and Lynn 2012; Thompson et al. 2017). The outcomes suggest that VIF values lie below 3.3 and range from 1.00 to 2.37, which reaffirms that CMB does not appear to be an issue in this research.
4 Results
4.1 Measurement model assessment
The research model employs first- and second-order constructs, utilizing the reflective-reflective type in the repeated indicator approach (Rezaei et al. 2017; Wetzels et al. 2009). According to Sarstedt et al. (2019), when a research model incorporates higher-order constructs, it becomes crucial to consider the measurement model of the first-order (lower-order) components, as well as the measurement model of the second-order (higher-order) construct. These are characterized by the relationships between the higher-order component and its associated lower-order elements.
First, we evaluate the first-order latent variables based on a PLS-SEM measurement of the outer model. Table 1 presents the means, standard deviations, and factor loadings of the retained first-order reflective indicators. These indicators do not conform to a normal distribution, as revealed by the Kolmogorov-Smirnov and Shapiro-Wilk tests, as previously reported. An initial analysis employing the PLS revealed instances of low reliability, consequently excluding these indicators from the analysis (Hair et al. 2011). This resulted in the elimination of the green involvement and green training first-order constructs.
Table 1
Means, standard deviations and loadings of the first-order constructs
Construct | Indicator | Mean | Std. dev. | Loading | t-test | p-value |
|---|---|---|---|---|---|---|
GR | GR1 | 2.079 | 0.985 | 0.806 | 36.242 | 0.000 |
GR2 | 2.309 | 1.036 | 0.699 | 11.639 | 0.000 | |
GR3 | 2.174 | 1.074 | 0.752 | 16.648 | 0.000 | |
GR&S | GRS1 | 3.707 | 0.880 | 0.712 | 14.578 | 0.000 |
GRS2 | 3.051 | 0.828 | 0.751 | 16.280 | 0.000 | |
GRS3 | 2.764 | 0.874 | 0.854 | 43.622 | 0.000 | |
GPA | GPA1 | 3.856 | 1.030 | 0.654 | 12.972 | 0.000 |
GPA2 | 2.152 | 1.021 | 0.844 | 41.681 | 0.000 | |
GPA3 | 2.156 | 1.032 | 0.771 | 19.826 | 0.000 | |
GBW | GBW1 | 3.953 | 0.986 | 0.775 | 26.000 | 0.000 |
GBW2 | 3.996 | 0.944 | 0.585 | 8.883 | 0.000 | |
GBW3 | 2.966 | 1.353 | 0.752 | 24.227 | 0.000 | |
GBW4 | 3.970 | 0.991 | 0.773 | 20.437 | 0.000 | |
GBW5 | 3.143 | 1.248 | 0.664 | 12.186 | 0.000 | |
GBPL | GBPL1 | 4.250 | 0.878 | 0.576 | 8.798 | 0.000 |
GBPL2 | 2.587 | 1.172 | 0.749 | 17.274 | 0.000 | |
GBPL4 | 3.433 | 1.115 | 0.843 | 46.992 | 0.000 | |
GBPL5 | 3.772 | 0.923 | 0.751 | 19.429 | 0.000 | |
OEP | OEP1 | 3.709 | 0.807 | 0.817 | 21.914 | 0.000 |
OEP2 | 4.056 | 0.858 | 0.777 | 17.205 | 0.000 | |
OEP3 | 3.657 | 0.824 | 0.871 | 34.272 | 0.000 | |
OEP4 | 3.671 | 0.831 | 0.770 | 13.276 | 0.000 |
Table 1 demonstrates the reliability and convergent validity of the first-order latent variables in the model. We assessed construct reliability using Cronbach’s alpha and composite reliability (CR). According to Table 1, all variables exhibit excellent internal consistency, with the CR values exceeding 0.7, and the Cronbach’s alpha values surpassing 0.6. Both are deemed acceptable thresholds for exploratory studies (Hair et al. 2011, 2017a). We evaluated convergent validity using the average variance extracted (AVE) and confirmed its existence – all AVEs exceeded 0.5. This indicates that the constructs explain over 50% of the variance in the items representing the constructs (Hair et al. 2019).
In complementing the analysis of the convergent validity of the measurement models, Table 2 shows that the factor loadings of the constructs are statistically significant (t > 3.29; p < 0.001) (Hair et al. 2019).
Table 2
Reliability and convergent validity of the first-order constructs
Construct | Cronbach´s α | CR | AVE |
|---|---|---|---|
GR | 0.627 | 0.797 | 0.567 |
GR&S | 0.665 | 0.818 | 0.600 |
GPA | 0.629 | 0.803 | 0.578 |
GBW | 0.760 | 0.837 | 0.509 |
GBPL | 0.713 | 0.823 | 0.542 |
OEP | 0.825 | 0.884 | 0.656 |
According to Hair et al. (2011), if all indicator loadings are statistically significant at 0.001, only consider removing the loadings between 0.40 and 0.70 from the scale if their deletion results in an increased CR above the suggested threshold. All loadings are significant and exceed 0.5, so they are thus considered relevant (Hair and Alamer 2022; Hair et al. 2019). For comparison, past studies reported loadings between 0.4 and 0.7 (e.g., Ertz et al. 2016; Truong and McColl 2011).
In research models that contain higher-order constructs, discriminant validity requires additional atention, as they must display discriminant validity both with each other and with all other constructs in the model except their higher-order constructs (Sarstedt et al. 2019). Consequently, following Henseler et al.’s (2015) heterotrait-monotrait (HTMT) criterion for discriminant validity, Table 3 clearly illustrates all values are below the threshold of 0.90, thus confirming the discriminant validity of the first-order measurement model.
Table 3
Discriminant validity (HTMT) of the first-order constructs
Construct | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
1.GBPL | ||||||
2.GBW | 0.886 | |||||
3.GPA | 0.677 | 0.517 | ||||
4.GR | 0.585 | 0.327 | 0.862 | |||
5.GR&S | 0.836 | 0.576 | 0.866 | 0.752 | ||
6.OEP | 0.674 | 0.551 | 0.496 | 0.339 | 0.613 |
The second-order construct, green HRM, is developed by utilizing the latent variable scores of the first-order constructs (Wetzels et al. 2009). To appraise the measurement model with these constructs, we assess the indicator reliability and validity of the latent variable at the second-order level (Sarstedt et al. 2019). The value for the CR is 0.874, and all path coefficients (standardized factor loadings) exceed the threshold value of 0.7, holding significance at the 0.001 level. This suggests strong construct reliability for the second-order construct (see Table 4) (Hair et al. 2017b). The AVE value is 0.699, surpassing the threshold of 0.5, thereby confirming the convergent validity of the second-order construct (Hair et al. 2019).
Table 4
Reliability, convergent validity and loadings of the second-order construct
Second-order construct | First-order construct | Loading | Cronbach´s α | CR | AVE |
|---|---|---|---|---|---|
Green_HRM | 0.812 | 0.874 | 0.699 | ||
GR | 0.811 | ||||
GR&S | 0.847 | ||||
GPA | 0.849 |
The second-order construct should exhibit discriminant validity with all other constructs in the model (Sarstedt et al. 2019). As shown in Table 5, all the values fall below the 0.90 threshold of the HTMT criterion, which confirms the discriminant validity of the structural model (Henseler et al. 2015).
Table 5
Discriminant validity (HTMT) of the structural model
Construct | 1 | 2 | 3 | 4 |
|---|---|---|---|---|
1.GBPL | ||||
2.GBW | 0.886 | |||
3.Green_HRM | 0.752 | 0.509 | ||
4.OEP | 0.674 | 0.551 | 0.520 |
4.2 Model estimation analysis
Since the measurement model has shown evidence of validity and reliability, the structural model can now be evaluated to test the hypotheses (Henseler et al. 2015). Bootstrapping is utilized to calculate the path coefficients reported in Fig. 2 (Hair et al. 2017b).
Fig. 2
Significant results of direct relationships. Note: *p < 0.05; **p < 0.01; ***p < 0.001; significant standardized regression coefficient
Table 6 illustrates the direct relationships within the research model. All relationships are significant, as the t-values exceed 1.96 (p < 0.05) (Hair et al. 2017b). Thus, the positive impact of green HRM on organizational environmental performance is confirmed (β = 0.195, p = 0.000), supporting Hypothesis 1.
Table 6
Direct effects
Relationship | Β | f2 | t-test | p-value |
|---|---|---|---|---|
Green_HRM -> GBW | 0.420 | 0.215 | 8.406 | 0.000 |
Green_HRM -> GBPL | 0.368 | 0.264 | 6.474 | 0.000 |
Green_HRM -> OEP | 0.195 | 0.036 | 2.191 | 0.028 |
GBW -> GBPL | 0.529 | 0.546 | 9.058 | 0.000 |
GBW-> OEP | 0.182 | 0.026 | 2.043 | 0.041 |
GBPL -> OEP | 0.280 | 0.048 | 2.716 | 0.007 |
To assess the magnitude of the effect of each predictor, we utilize f2 (Hair et al. 2018). As per the parameters set by Cohen (1988); Hair et al. (2017b), f2 values exceeding 0.02, 0.15, and 0.35 symbolize weak, moderate, and robust effects correspondingly. Table 6 delineates the potent effect of green behavior at work on green behavior in private life (f2 = 0.546). Further, the effect of green HRM on green behavior at work (f2 = 0.215) and in private life (f2 = 0.264) are both classified as moderate.
Table 7 presents the indirect effects. Hypothesis 2 is confirmed as the p-value is 0.10, indicating that green behavior at work partially mediates the relationship between green HRM and organizational environmental performance (β = 0.076, p = 0.053). However, since the significance level is slightly above 0.05, this result should be interpreted cautiously. Additionally, green behavior in private life partially mediates between green HRM and organizational environmental performance (β = 0.103, p = 0.009), thereby affirming Hypothesis 3. Furthermore, there exists partial mediation by both green behavior at work and green behavior in private life in the relationship between green HRM and organizational environmental performance (β = 0.062, p = 0.017), validating Hypothesis 4.
Table 7
Indirect effects
Relationship | Β | t-test | p-value |
|---|---|---|---|
Green_HRM -> GBW -> OEP | 0.076 | 1.937 | 0.053 |
Green_HRM -> GBPL -> OEP | 0.103 | 2.602 | 0.009 |
Green_HRM -> GBW -> GBPL -> OEP | 0.062 | 2.382 | 0.017 |
Regarding the model’s explanatory power, the determination coefficient (R2) signifies the degree to which the endogenous variables explain the exogenous variables (Hair and Alamer 2022). The model’s results demonstrate that it accounts for 57.8% of the variance in green behavior in private life, 17.7% in green behavior at work, and 31.3% in organizational environmental performance.
Recent literature has underscored that analyzing blindfolding-based Q2 is not a reliable indicator for assessing predictive power. Instead, PLSpredict is recommended for this purpose (Sarstedt et al. 2023). Thus, the predictive power of the structural model has been calculated using PLSpredict, as advised by Shmueli et al. (2019). As the Q2predict is greater than zero for all indicators of the measurement model, there is confirmation of some predictive relevance. The subsequent step involves analyzing the distribution of prediction errors. Given that the prediction errors are not symmetrically distributed, the Mean Absolute Error (MAE) is the most applicable prediction statistic (Shmueli et al. 2019). Shmueli et al. (2016) proposed a benchmarking approach that employs a linear regression model (LM) to generate predictions for the manifest variables of each indicator of the dependent construct, and it subsequently regresses the indicators of the exogenous latent variables in the PLS path model. As the PLS-SEM is less than the LM for the manifest variable for most of the dependent construct’s indicators, the model demonstrates only medium predictive power (Shmueli et al. 2019).
Lastly, in line with Mai et al.’s (2021) recommendations for effectively assessing the most appropriate indicators and cutoffs for the study, we applied their proposed guidelines to analyze the model. These guidelines suggest using a decision tree to identify the optimal fit indicator. For this study, the evaluated steps included: the purpose of the research (testing a novel model rather than estimating an established one), the focus of the estimation (structural model analysis, instead of confirmatory factor analysis), and the sample size (N > 200, not N < = 200). Therefore, the recommended goodness-of-fit indicator is the standardized root mean square residual (SRMR), which in our study is 0.12. The authors also recommend a subjective interpretation of model fit, as cutoffs should be viewed only as a benchmark that fit indicators aim to approach (Mai et al. 2021). We argue that, although the SRMR value in this study exceeds the 0.10 threshold (Kock 2020), PLS-SEM differs from covariance-based SEM (CB-SEM), which largely depends on the concept of model fit indices (Hair et al. 2019), because in PLS, these indices can be useful even in purely confirmatory studies (Hair and Alamer 2022). Thus, even bootstrap-based model fit assessments like SRMR should be considered very carefully in PLS (Hair et al. 2019). In a review of multiple HRM studies published in prominent journals over 30 years using PLS-SEM, Ringle et al. (2020) concluded that the use of goodness-of-fit measures is less significant in PLS compared to CB-SEM, and that researchers should primarily focus on criteria that evaluate the predictive performance of the model.
5 Discussion
The environmental performance of companies is significantly influenced by the behavior of their employees (e.g., Opatha and Arulrajah 2014; Renwick et al. 2013). Therefore, to achieve success in this area, companies must implement strategies, policies, and HRM practices that not only provide guidance but also encourage the adoption of sustainability-oriented behavior (Saeed et al. 2019; Shah 2019; Yasin et al. 2023; Yong et al. 2020). The confirmation of Hypothesis 1 aligns with previous research (Bangwal et al. 2017; Kularathne 2020; Yusoff et al. 2020), strengthening the contribution of our study, by indicating that the collected data are appropriate for the intended research.
Although not explicitly hypothesized, we formulated a model to scrutinize the effects of various green HRM practices. Green recruitment and selection, green performance appraisal, and green rewards all enhance green HRM, echoing findings from previous studies (Jabbour et al. 2010; Saeed et al. 2019; Shah 2019; Yusoff et al. 2020). As per AMO theory, these practices improve employees’ abilities and motivation. However, since green training and green involvement did not contribute as much as expected in our findings – contradicting key trends in literature (Ari et al. 2020; Mishra 2017; Saeed et al. 2019; Tang et al. 2018; Yusoff et al. 2020) – the opportunities aspect seems to be lacking. This suggests that employees may not discern an organizational culture that is designed to foster engagement in knowledge-sharing, contributing to problem-solving and decision-making, and participating actively in environmental activities (Rayner and Morgan 2018; Renwick et al. 2013). This outcome might be connected to the distinctiveness of the data used in our study. In fact, as noted above, the company here at stake places a strong emphasis on circulating green information internally via numerous channels, such as an intranet page, an internal social network, a company magazine, and digital training sessions. Even though these initiatives support green involvement (Renwick et al. 2013; Saeed et al. 2019), the firm may not actively encourage its employees to participate in these initiatives (e.g., by contributing to the newsletter and fostering shared responsibility), thus positioning them as mere receivers of information. Studies have revealed that when employees are encouraged to participate, they tend to feel more engaged and are more likely to align with a company’s environmental objectives (Ojo et al. 2022). Similarly, the firm provides green training, but it is possible that, as suggested by the literature, employees might perceive this as being “politically correct” (Renwick et al. 2013), which can lead them to question the sincerity or effectiveness of the company’s environmental initiatives. To ensure the success and effectiveness of green training, it is fundamental that participants are prepared, willing to learn, and committed to the process (Zibarras and Coan 2015). Therefore, practices such as job involvement or training may not be perceived as significant by the employees. This lack of significance could be consistent with the fact that our results are powered by performance appraisal and reward systems designed to induce quick change. Nonetheless, as the self-determination theory argues, relying solely on extrinsic motivation (such as rewards), may not be truly transformative. It is therefore essential to also nurture intrinsic motivation by addressing employees’ need for autonomy, competence, and relatedness (Ryan and Deci 2008). This can be attained via green recruitment, which focuses on hiring individuals who are intrinsically motivated to engage in green behavior as it resonates with their personal values and knowledge (Renwick et al. 2013).
Hypotheses 2 and 3 consider the mediation of employees’ green behavior at work and in their private lives, respectively, yielding intriguing results. Hypothesis 2, with its borderline p-value of 0.053, is not accepted in a more stringent 5% analysis. Conversely, Hypothesis 3 is confirmed (β = 0.103, p < 0.01). If we take the non-confirmation of Hypothesis 2 as contradicting previous studies on employees’ adoption of green behavior in the workplace (Bangwal et al. 2017; Muster and Schrader 2011; Piligrimiene et al. 2019), the acceptance of Hypothesis 3 corroborates the theories of Edwards and Rothbard (2000) and Greenhaus and Powell (2006) regarding the general spillover effect. However, assuming Hypotheses 2 and 3 are both confirmed, this is somewhat surprising in this study’s context, since the mediation presents an indirect effect value significantly lower than the direct effect value. This observation indicates that the adoption of green behavior at work and in private life is less effective in influencing organizational environmental performance than the introduction of green HRM practices aiming at environmental performance. The confirmation of Hypothesis 4 aligns with the literature (Datta 2015; Gayathri and Karthikeyan 2013; Muster and Schrader 2011; Ragas et al. 2017), accomplishing serial mediation. However, the mediation process’s indirect effect (β = 0.062) is less than the direct effect of the relationship between green HRM and organizational environmental performance (β = 0.195). This implies, to a certain extent, the mediation’s marginal effectiveness in practice.
In light of IPT, the smaller effect of the mediations might suggest that in our study, employees did not successfully integrate the organizational intervention (i.e., green HRM practices) into their self-concept, resulting in limited or non-lasting changes to their green identity and a lack of spillover effects. One possible interpretation could be that respondents might be employing a “compartmentalization strategy”, in which they separate their workplace identity from their home identity. This strategy could assist in avoiding conflicts between various social norms and roles by containing the impact of green practices solely within the professional arena, where the stimulus (in this scenario, green HRM) was received, which, in turn, could limit the probability of behavioral shifts in other contexts (Verfuerth et al. 2019, 2021). Such a finding might occur because employees generally possess more agency and control at home compared to their workplace (Littleford et al. 2014). Indeed, when employees perceive a lack of control over a situation, it may threaten their self-efficacy (Breakwell 1986, 2021), which consequently reinforces the compartmentalization of their identities.
By merging the results from Hypotheses 2, 3, and 4 with the findings from the development of green HRM – where green recruitment and selection, green performance appraisal, and green rewards were all considerably decisive – we can hypothesize that in the context under research, organizational environmental performance is primarily driven by the combined effectiveness of the green HRM practices noted above. While employees might compartmentalize their workplace identity from their home identity, failing to completely transfer behavior between the two, green hiring remains a critical component in building a workforce that aligns with the company’s environmental objectives and is intrinsically motivated to bolster the company’s sustainability endeavors, particularly when these objectives align with their personal habits. Green hiring attracts “green employees” (Renwick et al. 2013) to the company, i.e., those who already demonstrate environmental sensitivity, values, and behavior. Contrary to green recruitment and selection, which attract employees already motivated by environmental concerns, considering the combined impact of performance appraisal and reward mechanisms on mediation outcomes suggests that the green HRM practices in consideration may be less effective in maintaining such behavior over time. This is because behavior prompted by performance appraisals and incentivized by seemingly non-transformative measures is less likely to be long-lasting (Ryan and Deci 2008).
To interpret the data, it is essential to acknowledge that our research was conducted within an organization that only recently (since 2020) started investing in the implementation of green HRM practices, which may have influenced its spillover effects. A plausible explanation is that behavioral change may still be in progress. Moreover, our findings suggest that employees’ perceptions are more important than the actual actions taken by the organization and thus they might not fully comprehend the firm’s commitment to sustainability, perceiving the green HRM practices either as a genuine commitment towards the environment or as a business strategy intended to enhance the firm’s reputation through impression management and cost savings (Tosti-Kharas et al. 2017). As a result, while organizational goals for environmental performance may be met via green HRM practices – contributing to improved efficiency in critical areas like energy consumption and waste management – these practices may fail to foster behavioral changes among employees or encourage spillover effects in their personal lives.
6 Conclusions
The results of this research lead to two primary conclusions. First, there is a significant and positive relationship between green HRM practices and organizational environmental performance, which highlights the importance of adopting green practices to enhance environmental performance. Notably, practices such as green recruitment and selection, green performance appraisal, and green rewards serve pivotal roles. Green recruitment is essential for aligning employees with sustainability goals, even if they separate their work and personal identities. Under pressure to achieve results, a company might be tempted to rely solely on performance appraisal and rewards; however, this approach may be risky because once these practices lose their focus on environmental goals, they become less effective. Secondly, findings from the serial mediation process show that altering sustainability-oriented behavior is more demanding than implementing green HRM practices alone. On the whole, these conclusions emphasize the need for caution when attempting to enhance organizational environmental performance. This study has also presented an innovative model that enables observing behavioral changes among employees in different contexts, both work and private life. As such, the serial mediation proposed in this research acts as a framework for understanding behavioral changes among employees exposed to green HRM practices aimed at improving environmental performance levels. To the best of our knowledge, this proposal is unique. Despite the less pronounced impact of serial mediation compared with the direct effect of green HRM practices on environmental performance, our study maintains the importance of green work-life balance, and managers are advised to adopt a more comprehensive approach by integrating work-based green HRM practices with personal and community initiatives, thus fostering a wider impact on organizational culture and driving environmental performance.
6.1 Contributions to literature
Our findings emphasize the significance of adopting green HRM practices to enhance organizational environmental performance (e.g., Aftab et al. 2022; Aftab and Veneziani 2024; Bangwal et al. 2017; Kularathne 2020; Yusoff et al. 2020). Moreover, these findings expand the existing literature on green work-life balance and contextual spillover processes by addressing the call for more research, especially in real-world settings (Muster and Schrader 2011; Paulet et al. 2021; Pham et al. 2020; Verfuerth et al. 2019). To the best of our knowledge, this research is the first to examine the serial mediation of green behavior both at work and in private life within the relationship between green HRM and organizational environmental performance. Even though the impact of the serial mediation was less pronounced compared to the direct effect between green HRM and organizational environmental performance, it does not imply that the concept of green work-life balance is invalid or merely a greenwashing tactic, as suggested by some authors (Iddagoda et al. 2021). Rather, our study contributes to the literature by incorporating serial mediation, prompting valuable reflection and underscoring the importance of green HRM practices in enhancing organizational environmental performance. Within a context where the literature presents mixed results, our findings support previous studies that have discovered a positive relationship (e.g., Aftab et al. 2022; Aftab and Veneziani 2024; Bangwal et al. 2017; Kularathne 2020; Yusoff et al. 2020). Additionally, this study exemplifies the importance of the “best-to-fit-a-specific purpose” approach outlined by by Mai et al. (2021).
6.2 Implications for managers
In terms of practical implications, companies should give more attention to green HRM practices, considering both their effect on organizational environmental performance and potential spillover effects. Green HRM practices present a triple-benefit scenario as they: (i) improve organizational environmental performance, (ii) foster a sustainable workplace culture, and (iii) contribute positively to the environment via collective green efforts. To maximize these benefits, it is essential to introduce programs promoting the adoption of green behaviors. Further, examining the spillover effects of these programs not only at work but in private life, might reveal new strategies for promoting behavioral change and thus provide valuable insights into initiatives that encourage sustainable practices (Nilsson et al. 2017).
Companies are advised to empower employees to contribute more significantly to organizational environmental performance by ensuring that their efforts are comprehensively appraised and recognized (Rashid and Mohammad 2012). The incorporation of metrics to assess the adoption of green behavior into performance evaluation systems, coupled with the establishment of employee competitions, could effectively drive the implementation of these behaviors and boost sustainability performance (Chang et al. 2024). Concurrently, companies can also stimulate employee involvement and participation in designing and implementing green activities within the organization, by encouraging them to integrate their personal experiences into these initiatives. Such integration could involve strategies such as organizing an “idea competition” with an appropriate incentive system, providing time off to support employees’ individual environmental projects within the company, or promoting participation in corporate environmental volunteering programs (Muster and Schrader 2011). Similarly, considering the significance of a green knowledge management culture that promotes the dissemination and sharing of green information among individuals (e.g., He et al. 2024; Tu 2024), managers can create platforms to share innovative ideas, evaluate them, and celebrate successes, while integrating them into the overarching business strategy (Chang et al. 2024).
Given the lack of a positive spillover effect of green behavior beyond the workplace, companies should actively incorporate green HRM practices into broader programs. This encourages employees and their families to adopt green behavior, thus reducing potential identity threats felt by employees that limit a positive contextual spillover. Examples might include organizing “open family days” featuring team-building activities centered on environmental themes (Rashid and Mohammad 2012), or offering training sessions on new environmental legislation, technologies, and best practices to both employees and their families to keep them informed and updated (Chang et al. 2024). For the implementation of work-life policies, financial resources (either from external sources or from an internal budget) are crucial, as is a positive attitude by managers towards these green initiatives (Adame-Sánchez et al. 2018). The overriding goal is to cultivate an approach that links work-based green HRM practices with personal and community lifestyle initiatives, thereby fostering a lasting impact on organizational culture towards sustained change.
6.3 Societal implications
By examining organizational environmental performance and integrating both workplace and private spheres, this study’s results hold broader implications for both society and the environment. Improving a company’s environmental performance is essential for achieving the Sustainable Development Goals (SDGs), where the private sector, primarily large and multinational corporations, plays a key role. However, achieving the SDGs requires active collaboration between private, public, and civil society actors (Giri and Chaparro 2023). Such collaboration mandates a reimagining of business and society, with an unwavering focus on the human factor and the significance of human resources (Ammirato et al. 2023). Given that addressing sustainability challenges demands lifestyle changes holistically (Frezza et al. 2019), and considering that employees are not just workers but also family members who influence their communities (Ravenswood 2022), it is crucial to incorporate these collaborative efforts into all aspects of life. Therefore, understanding the spillover effects could inform the development of more effective programs and policies (Truelove et al. 2014), enabling companies to drive wider societal change with the potential to enhance their environmental impact beyond the workplace.
Our results suggest that green behaviors in both personal life and the workplace have a less significant impact on organizational environmental performance compared to the implementation of green HRM practices. Therefore, the primary driver for enhancing environmental performance appears to be the development and implementation of green HRM. By comparison, just as Walmart revolutionized retail through the introduction of large-scale discounting and McDonald’s transformed dining out with the fast-food concept – both having considerable societal impacts –, similar effects can be achieved through HRM practices. The focus must be on hiring employees who exhibit ecological awareness and provide training on environmental topics, followed by appropriate evaluation and compensation for eco-friendly behavior. Indeed, green HRM practices can shape broader societal behavior, as the roles of individuals as employees and in their private lives are interconnected.
6.4 Limitations and agenda for future research
Several limitations of this study should be pointed out to suggest new avenues for future research. Firstly, the utilization of a single case study brings the usual challenges, such as constricted generalizability and potential biases based on the case’s specific context. However, this method also offers several benefits. It enables the collection of detailed data from a specific context, facilitating a comprehensive examination of nuanced, context-specific information that can serve as a foundation for broader research (e.g., Denzin and Lincoln 2011). Furthermore, our study’s data collection was restricted due to the company’s anonymity request, limiting the exploration of sociodemographic factors. Secondly, the study’s cross-sectional design and reliance on self-reported data constrains causality. However, the literature provides substantial evidence of a strong correlation between self-reported behavioral measures and actual green behavior, and it shows that spillover effects are often derived from self-reported intentions instead of observed behavior changes (Kormos and Gifford 2014; Xu et al. 2018). Thirdly, our study depends on subjective measures to evaluate organizational environmental performance.
Given these limitations, we recommend that future research should broaden the scope of investigated influences through the adoption of a qualitative research design, thereby gaining deeper insights into the spillover effects. Conducting interviews to comprehend employee reflections and their reasons for the nonexistence of a contextual spillover pathway (similar to the approach adopted by Verfuerth et al. 2021) might yield useful insights, especially worthwhile when coupled with studies into how social dynamics or personal/situational characteristics shape the likelihood of spillover. For instance, it might be insightful to investigate how different generations address the green work-life balance, as each generation perceives environmental issues and work-life balance differently (e.g., Baran and Sypniewska 2024; Islam et al. 2022), or to investigate its effects across different career stages and positions (Darcy et al. 2012; Drnovšek et al. 2024). Further enlightenment could arise from longitudinal studies exploring the time gaps between the effects on work and personal life. Moreover, a study of variation in green HRM practices across industries and organizational sizes could shed light on their effects on organizational environmental performance, as well as the influence of external stakeholders, like customers and suppliers, on sustainability initiatives. Lastly, to address possible discrepancies between subjective and objective performance measures, we suggest future research consider collecting objective environmental performance data to enhance their validity.
Declarations
Conflict of interests
The authors declare that they have no conflict of interest with respect to the research, authorship, and/or publication of this article.
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