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Article

Does ESG Affect Mental Health of Employees? Focusing on the Moderating Effects of Job Crafting and Relationship Conflict

by
Ga-Rog Han
1 and
Jae-Eun Lee
2,*
1
K-Humanities Innovation Center, Andong National University, Andong 36729, Republic of Korea
2
Department of International Trade, Sunchon National University, Suncheon 57922, Republic of Korea
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(14), 6076; https://doi.org/10.3390/su16146076
Submission received: 7 June 2024 / Revised: 10 July 2024 / Accepted: 11 July 2024 / Published: 16 July 2024
Versions Notes

Abstract

:
This study examines the dark side of ESG, which has emerged as a new paradigm in that the concept is broad and must respond to stakeholder pressure. This study aims to conceptualize Environmental, Social, and Governance (ESG) stress, or the stress experienced by employees due to ESG, and empirically analyze its impact on mental health. We also examined the moderating effects of job crafting and relationship conflict using the job demand-resource model. Based on a survey of 228 ESG managers with at least five years of work experience, the results of the regression analysis are as follows. First, ESG stress (ESG complexity and ESG uncertainty) was found to cause depression, a negative mental health outcome. Second, job creation was found to moderate depression caused by ESG stress (ESG complexity and ESG uncertainty). Third, relationship conflict was found to reinforce depression caused by ESG stress (ESG complexity and ESG uncertainty). This study is significant because it identifies the relationship between ESG stress and mental health, as ESG has become a requirement for corporate sustainability. Additionally, this study is expected to extend ESG research by examining the moderating effects of job crafting and relationship con-flict from the JD-R on ESG stress and mental health.

1. Introduction

As the business environment becomes more complex and rapidly evolving, work becomes a factor that leads to poor mental health, such as fear, worry, and anxiety [1]. In particular, new Environmental, Social, and Governance (ESG) paradigms have exposed organizations to various pressures, such as effectively responding to new policies, regulations, laws, and institutional environments [2] and meeting the demands of various stakeholders inside and outside the corporation [3,4]. Today, ESG has become a standard for measuring corporate sustainability and a prerequisite for maintaining competitiveness in the global market [5,6,7,8]. Accordingly, in a management environment that emphasizes only ESG, employees in charge of ESG-related tasks are under considerable pressure to meet both social and stakeholder demands arising from new policies, regulations, and social requirements created by ESG within the organization [9]. The pressure created by ESG translates into psychological pressure and mental fatigue for employees due to new job redistribution and increased workload within the organization [10]. The pressure and mental fatigue experienced by employees ultimately become stress, which can lead to burnout, anxiety, or depression, potentially harming their mental health [11,12,13]. Therefore, this study aimed to identify the impact of ESG stress, considered as the psychological pressure that employees experience in handling ESG-related tasks, on mental health based on job demands and resources (JD-R). JD-R explains the effects of job demands and resources on employees’ physical and mental health and job behavior [14]. JD-R assumes that strengthening job resources alleviates the negative impact of job demands on employees’ organizational performance.
Some scholars have actively attempted to identify factors that mitigate the negative impact of job stress on mental health by expanding the JD-R [14,15]. Previous studies that focused on factors that moderate the relationship between job stress and mental health based on JD-R suggest that positive factors such as equitable rewards [4], resilience [15,16], self-efficacy [15,17,18], optimism [18], and job crafting [19,20] alleviate impaired mental health through interaction with job stress. In contrast, if employees are placed in a situation where they can no longer recover due to continuous and excessive job demands, they may not be able to properly perform the required tasks, leading to conflicts among team members [21,22]. These conflicts among employees can ultimately have a negative impact on job performance, further deteriorating the employees’ mental health. Therefore, this study aimed to examine the moderating effects of job crafting and relationship conflict on the relationship between ESG stress and mental health based on the JD-R, which has not been explored in previous studies.
The results of this study are expected to have the following effects. First, it is mean-ingful in that it looks at the relationship between ESG stress, which is the psychological pressure on tasks received by ESG, and mental health from the perspective of job demands in the existing JD-R. Second, it contributes to the expandability of ESG research by examining the moderating effects of job crafting and relationship conflict on the relationship between ESG stress and mental health from a JD-R perspective. Finally, this study is expected to broaden the scope of research for ESG researchers by examining the dark side of ESG, which has become an essential requirement for sustainability and can show a positive image at the firm level but can be a considerable pressure for employees to meet both social demands and stakeholder pressures.

2. Theoretical Background

JD–R is a theory that excessive job demands faced while performing a job cause negative emotions such as exhaustion and depression in employees [14,23,24]. Job demands refer to paying physiological and/or psychological costs in terms of the physical, psychological, social, or organizational aspects of a job [23]. Job resources refer to functional elements such as control, authority, and the roles necessary to handle job demands [23]. Therefore, according to JD-R, if the job performer is given appropriate job resources to respond to job demands, physiological and/or psychological costs can be significantly alleviated [23,24]. Accordingly, many studies have viewed the physiological and/or psychological costs as work-related stress.
The majority of previous studies that identified the relationship between work-related stress and mental health based on the JD-R argued that work-related stress has a negative impact on mental health and suggested psychological disorders, burnout, emotional exhaustion, and depression as subdimensions of negative mental stress [15,25,26,27]. For example, Law et al. [15] argued that workplace bullying, such as continuous aggressive behavior and sexual harassment, causes psychological disorders based on the JD-R. Therefore, work engagement should be supported as a job resource to alleviate this. Hu et al. [25] argued that the degree of investment in work, such as time, energy, and skills spent at work, varies among employees; in particular, high levels of job demands lead to burnout. Huang et al. [27] argue that excessive supervision by managers when employees perform their duties makes them feel burnt and emotionally exhausted. Lee et al. [26] found that high levels of work intensity that are difficult to control lower an individual’s self-esteem [28] and ultimately increase depression [26]. Thus, various job-related demands trigger negative mental health effects such as psychological disorders, burnout, and depression. This study focused on depression among various types of negative mental health issues and conducted an empirical analysis. The reasons for focusing on depression in terms of negative mental health were as follows:
Previous studies that focused on employee depression cannot accurately explain (not clarify) the difficulties employees with depression face in the process of work participation [29]. Moreover, depression affects an individual’s cognitive abilities, such as memory, intellect, and learning, and is difficult to identify [29,30]. Accordingly, previous studies have pointed out that if there are employees with depression within an organization, work productivity decreases, or continuous work absenteeism occurs, making it difficult for them to participate in work smoothly [29,31]. Therefore, this study intends to focus on depression among mental health factors because depression can affect work participation, such as ESG.
However, although ESG is a concept that is receiving social and practical attention, few people accurately perceive the concept of ESG [32], and some still view it as an unfamiliar concept. ESG is a broad concept that specifically explains environmental, social, and governance factors [33]; therefore, so ESG can be considered an ambiguous concept [34]. The fact that the concept of ESG is broad and unclear can act as a new barrier for employees in charge of performing their work, and there is a high possibility that they do not have a deep understanding of ESG [27]. In this context, ESG, a new form of job demand, can cause work-related stress. Therefore, this study focuses on the fact that ESG work can be complex and highly uncertain for ESG employees, divides ESG stress into ESG complexity and ESG uncertainty, and analyzes their impact on depression.
Meanwhile, previous studies have presented JD-R as a perspective to identify moderating variables to mitigate the negative impact of work-related stress on mental health. Among these, job crafting is the most representative. Previous studies that focused on job crafting emphasized that job crafting can be an important factor in alleviating the negative impact of stress on mental health because it is a self-directed redesign of one’s job that gives meaning to work and work identity [35]. For example, Tims and Bakker [36] argued, based on JD-R, that job crafting, as a preaction that changes an employee’s job, has a positive effect on work performance, such as motivating work or gradually improving work results. Sakuraya et al. [37] emphasized that job crafting is the only factor that promotes job engagement and relieves job-related suffering. Thus, job crafting can alleviate the negative impact of ESG stress on depression because it can motivate work and relieve job-related suffering. However, to date, no previous study has analyzed the impact of ESG stress on depression based on the JD-R. Therefore, this study considers job crafting to be a moderating variable.
However, jobs that are continuously in demand by employees can exert greater pressure on employees, causing stress, which can put employees’ mental health in a negative situation that is difficult to recover from, leading to work-relation conflicts among team members [21,22]. For example, Semmer [22] argued that conflicts between employees in work situations cause greater stress and that a considerable number of employees decide to leave their jobs to resolve these conflicts. Therefore, Semmer [22] emphasized that to prevent conflicts among team members, it is necessary to provide autonomy in employees’ work and create a work environment where employees want to work so that employees’ competencies can be improved. Colligan and Higgins [21] also argued that when there are difficult relationships with administrators and/or coworkers or conflicts between employees and the job demands placed on them, stress occurs. Prolonged exposure to stress can lead to absenteeism, organizational dysfunction, decreased work productivity, and, in the worst case, even physiological and psychological disorders [21]. Thus, conflicts between employees can ultimately have a negative impact on job performance, making employees feel ESG stress more strongly and reinforcing the negative impact on depression. Therefore, based on the JD-R, this study considers job crafting and relationship conflict as moderating variables and empirically analyzes whether job crafting and relationship conflict moderate the relationship between ESG stress and depression.

3. Hypothesis Development

3.1. ESG Stress and Depression

ESG becomes socially essential and new policies, regulations, laws, etc., related to ESG gradually increase [33], the level of social demands related to ESG and the level of stakeholders’ ESG demands are also increasing [27,32]. However, because the concepts that constitute ESG are broad, it is difficult to define ESG clearly [38,39]. This makes it difficult for the ESG staff to perform their duties based on a deeper understanding of ESG. High ESG complexity requires ESG staff to invest resources to understand regulations and laws related to ESG policies, even if they are in charge of the ESG [38,39]. In particular, situations in which ESG data must be disclosed every year or ESG ratings must be obtained owing to the nature of ESG [40] further increase the complexity of the work for ESG staff. ESG complexity leads to an increase in workload, and employees’ efforts to meet the high level of ESG requirements of stakeholders can lead to mental pressure. The burden and mental pressure on employees to perform ESG tasks can lead to depression [41].
It is thought that the ESG stress experienced by employees will be great in situations where the concept of ESG is not yet sufficiently established and understood and job resources are lacking [27,34]. Employees not only spend considerable time, effort, and money to understand and perform ESG with limited job resources, but their efforts to meet stakeholders’ demands can also impair mental health and trigger depression. Based on the above discussion, the following hypotheses are proposed.
Hypothesis 1 (H1).
ESG stress will have a positive (+) effect on depression.
Hypothesis 1a (H1a).
ESG complexity will have a positive (+) effect on depression.
Hypothesis 1a (H1b).
ESG uncertainty will have a positive (+) effect on depression.

3.2. Moderating Effect of Job Crafting

Employees with job crafting will redesign their jobs to navigate through them, even if their jobs are complex and uncertain [35]. Employees who redesign and overcome difficulties in their jobs gradually begin to feel an interest in their work [42] and can assign meaning or identity to their jobs through the pleasure of work [35]. In this context, even if ESG is complex and uncertain, ESG staff members can redesign their jobs to navigate through it. Employees who have made efforts to redesign their work and overcome difficulties in uncertain work situations will gradually begin to feel an interest in ESG work. Through the pleasure of work, they will be able to assign meaning or identity to their jobs. Thus, employees who assign meaning or identity to ESG work have increased job satisfaction, become motivated to work, and contribute to continuously improving the work process [36]. In other words, they will develop skills in exploring ESG-related policies, regulations, laws, and so on. They will also find ways to handle the ESG-related discussions demanded by stakeholders. Although the concept of ESG is broad, it is possible to find ESG activities suitable for our company within the broad concept. In other words, if the ESG work process is improved, it can promote ESG work engagement and relieve the suffering from complex and uncertain ESG-related work [37]. Based on the above discussion, the following hypotheses are proposed.
Hypothesis 2 (H2).
Job crafting will negatively (−) moderate the positive (+) relationship between ESG stress and depression.
Hypothesis 2a (H2a).
Job crafting will negatively (−) moderate the positive (+) relationship between ESG complexity and depression.
Hypothesis 2b (H2b).
Job crafting will negatively (−) moderate the positive (+) relationship between ESG uncertainty and depression.

3.3. Moderating Effect of Relationship Conflict

Since the concept of ESG is very broad, if a deep understanding of ESG is required, ESG staff may not know exactly what tasks they should perform [43,44]. In this case, if ESG work is complex and uncertain, there may be conflicts among team members due to a lack of clear information on job performance [43,45], and other employees may interfere with the work of ESG staff. Continuous conflict among team members can ultimately weaken the employee productivity of ESG staff [21,46,47]. ESG staff with decreased work productivity may, in the worst case, be absent from work or leave their jobs, ultimately impairing organizational functions [23,24]. Relationship conflict is a type of stress [44,45], and conflicts among team members in work situations can further exacerbate psychological distress, fatigue, and pressure in employees with ESG stress [22,46,47]. Because conflicts among team members exacerbate ESG stress, they can increase depression. Based on the above discussion, the following hypotheses are established.
Hypothesis 3 (H3).
Relationship conflict will positively (+) moderate the positive (+) relationship between ESG stress and depression.
Hypothesis 3a (H3a).
Relationship conflict will positively (+) moderate the positive (+) relationship between ESG complexity and depression.
Hypothesis 3b (H3b).
Relationship conflict will positively (+) moderate the positive (+) relationship between ESG uncertainty and depression.

4. Research Method

4.1. Sample and Data

This study aimed to understand the impact of ESG stress on depression and determine whether employee job crafting and relationship conflicts moderate the relationship between ESG stress and depression. In this study, the ESG staff with at least five years of work experience had a general understanding of ESG. Because employees with more experience in the same job have mastered the knowledge, skills, and knowledge of the job [48,49]. A research company commissioned this study to conduct an online survey. The survey questions were pilot-tested with two ESG experts to refine the questionnaire and ensure that the respondents were able to provide correct answers. Questionnaires were distributed to 300 office workers, and 228 were identified as having more than 5 years of work experience and overseeing ESG-related tasks. Therefore, this study conducted an empirical analysis of 228 people.
Table 1 shows the distribution of survey samples by country. As you can see from the table, the response rate was the highest for those in the 40–49 age group (70, 228%), and it was higher for males (150, 65.6%) than for females. General managers (58; 25.4%) had the highest response rate.

4.2. Measurement of Variables

4.2.1. Dependent Variable

Depression: According to Shaver and Brennan’s [50] study, the degree of agreement with four items was measured on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree): (1) I was bothered by things that usually do not affect me; (2) I did not feel like eating; my appetite was poor; (3) I felt that I could not shake off the blues even with help from my family or friends; (4) I felt lonely; (5) I had trouble keeping my mind on what I was doing; (6) I felt depressed; and (7) I felt that everything I did was an effort.

4.2.2. Independent Variables

ESG complexity: Adapted from Tarafdar et al.’s [51] techno-complexity to ESG in a way suitable for this study, the degree of agreement with four items: (1) I do not know enough about this ESG to handle my job satisfactorily, (2) I need a long time to understand and use ESG, (3) I do not find enough time to study and upgrade my ESG skills, and (4) I often find it too complex for me to understand and use ESG was measured on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).
ESG uncertainty: Adapted from Tarafdar et al.’s [51] techno-complexity to ESG in a way suitable for this study, the degree of agreement with four items: (1) there are always new developments in ESG information, (2) there are constant changes in ESG information, (3) there are constant changes in ESG information, and (4) there are frequent upgrades in ESG measured on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).

4.2.3. Moderating Variables

Job crafting: According to Slemp and Vella-Brodrick [52], the degree of agreement with four items: (1) introduce new approaches to improve your work, (2) change the scope or types of tasks that you complete at work, (3) introduce new work tasks that you think better suit your skills or interests, (4) choose to take on additional tasks at work, and (5) give preference to work tasks that suit your skills or interests was measured on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).
Relationship Conflict: According to De Dreu and Van Vianen’s [53] study, the degree of agreement with eight items such as “In my team, we usually deal with these relationship conflicts by (1) discussing the issues to work out mutually acceptable decisions, (2) cooperating to understand others’ views and positions better, (3) settling the issues through give and take, (4) putting pressure on others to accept one’s ideas, (5) sticking to one’s positions, (6) raising one’s voice and using threats, (7) avoiding the issues, and (8) acting as if nothing has happened” was measured on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).

4.2.4. Control Variables

Gender: Male sex was set as reference variable 1, and females were measured as 0.
Age: 20~29 was measured as 1, 30~39 as 2, 40~49 as 3, 50~59 as 4, and 60~ as 5.
Level of education: High school graduation was measured as one, junior college graduation as two, university graduation as three, master’s degree as four, and doctoral degree as five.
Job position: Staff was measured as 1, assistant manager as 2, manager as 3, senior manager as 4, deputy general manager as 5, general manager as 6, and top management as 7.
Work experience: Work experience was measured in months.
Number of employees: As the size of an organization can potentially impact ESG, we used the number of employees in our analysis.

4.3. Statistical Analysis

In this study, a sample power analysis was conducted before the validity and reliability analyses. The Kaiser-Meyer-Olkin (KMO) test result was 0.844, and Bartlett’s test for sphericity was 9579.981 (p < 0.000). Accordingly, we determined that the sample size for the regression analysis was adequate. Table 2 presents the results of the validity and reliability analysis. As a result of the exploratory factor analysis for validity check, each factor’s loading value was greater than 0.56, confirming that there were no major problems with validity. Based on the results of the validity analysis, mean values were derived for each factor, and correlation and regression analyses were conducted using the derived mean values. Cronbach’s alpha value was used to analyze the reliability of the measurement variable, and Cronbach’s alpha values were all over 0.7, confirming that there was no major problem with the reliability of the measurement variable [54].
Table 3 presents the descriptive statistics and correlation analysis results for the variables used in this study. In addition, because of checking the variance inflation factor (VIF) value to verify the possibility of multicollinearity, the maximum value was less than two, confirming that multicollinearity is not a cause for concern [55].

5. Analysis Results

5.1. Results of Regression Analysis

Table 4 presents the results of the regression analysis used to verify the research hypotheses. Since this study examined the relationship between ESG stress and depression, focusing on the moderating effect of job crafting and relationship conflict, the average centering technique was used for the analysis [56].
First, Model 1 in Table 4 presents the effects of the control and independent variables on the dependent variable, degression. As can be seen from Model 1, the regression analysis showed that the level of education (p < 0.01) had a negative effect on depression. Still, the independent variables ESG complexity (p < 0.05) and ESG uncertainty (p < 0.01) had a significant positive effect on depression. As shown in Model 2, the regression analysis showed that the level of education (p < 0.01) had a negative effect on depression. Still, the independent variables ESG complexity (p < 0.05) and ESG uncertainty (p < 0.01) had a significant positive effect on depression. Next, we confirmed moderating effects and found that job crafting (p < 0.001) had a significant negative effect on depression, and relational conflict (p < 0.001) had a significant positive effect on depression. Thus, Hypothesis 1 is supported. Model 3 presents the results of the regression analysis, including the control, independent, and moderating variables. As shown in Model 3, the control variable education (p < 0.01) and the independent variables ESG complexity (p < 0.05) and ESG uncertainty (p < 0.05) have a significant positive effect on depression, the moderator variable job crafting (p < 0.001) has a significant negative effect on depression, and relational conflict (p < 0.001) has a significant positive effect on depression. We examined the influence of the interaction term between ESG complexity and depression (ESG complexity × job crafting, p < 0.01). We found that job crafting mediated the positive relationship between ESG complexity and depression in a negative direction. As shown in Model 4, the control variable education (p < 0.05) and the independent variables ESG complexity (p < 0.05) and ESG uncertainty (p < 0.05) had significant positive effects on depression. Similarly, the moderator variable of job competence (p < 0.001) had a significant negative effect on depression, but relational conflict (p < 0.001) had a significant positive effect on depression. Checking the influence of the interaction term between ESG uncertainty and depression (ESG uncertainty × job crafting, p < 0.01), we found that job crafting mediated the positive relationship between ESG complexity and depression in the direction of definition. As shown in Model 5, the control variable level of education (p < 0.01) and the independent variables ESG complexity (p < 0.05) and ESG uncertainty (p < 0.05) have a significant positive effect on depression, the moderator variable job crafting (p < 0.001) has a significant negative effect on depression, and relational conflict (p < 0.001) has a significant positive effect on depression. We examined the influence of the interaction term between ESG complexity and depression (ESG complexity × job crafting, p < 0.01). We found that job crafting mediates the positive relationship between ESG complexity and depression in a positive direction. As shown in Model 6, the control variable education (p < 0.05) and the independent variables ESG complexity (p < 0.05) and ESG uncertainty (p < 0.05) had a significant positive effect on depression. Similarly, the moderator variable of relationship conflict (p < 0.05) had a significant negative effect on depression, but relationship conflict (p < 0.05) had a significant positive effect on depression. Checking the influence of the interaction term between ESG uncertainty and depression (ESG uncertainty × relationship conflict, p < 0.05), we found that job crafting mediated the positive relationship between ESG uncertainty and depression in the direction of definition.
In summary, the results of this study are as follows. ESG stress (ESG complexity and uncertainty) increases depression. Thus, Hypothesis 1, including Hypotheses 1a and 1b, was supported. Job crafting weakened the positive relationship between ESG stress and depression. Therefore, we found support for Hypothesis 2, including Hypotheses 2a and 2b. Finally, relationship conflicts strengthened the positive effect of ESG stress on depression.

5.2. Additional Analysis and Robustness Test

To verify the robustness of this study, an additional analysis was conducted on 234 ESG staff members, including new employees. The results of the analysis of 234 ESG staff members are presented in <Table 5>. First, by verifying Model 2 to confirm Hypothesis 1, we found that ESG complexity (p < 0.001) had a significant positive (+) effect on depression. Similarly, ESG uncertainty (p < 0.01) is found to have a significant positive (+) effect on depression. Therefore, Hypothesis 1 was supported.
Next, the moderating effect of job crafting was verified in Models 3 and 4. In model 3, the interaction term (ESG complexity × job crafting) (p < 0.01) between ESG complexity and job crafting was found to have a significant negative (−) effect on depression. Likewise, in model 4, the interaction term (ESG uncertainty × job crafting) (p < 0.001) between ESG uncertainty and job crafting was found to have a significant negative (−) effect on depression. Accordingly, it was confirmed that both Hypotheses 1 and 2 were supported.
Finally, the moderating effect of relationship conflict can be observed in Models 5 and 6. In Model 5, the interaction term (ESG complexity × relationship conflict) (p < 0.001) between ESG complexity and relationship conflict had a significantly positive (+) effect on depression. In Model 6, the interaction term (ESG uncertainty × relationship conflict) (p < 0.001) between ESG uncertainty and relationship conflict had a significantly positive (+) effect on depression. Therefore, all three Hypotheses are supported.

6. Discussion and Conclusions

6.1. Discussion

This study analyzed the impact of ESG stress experienced by ESG-related work subjects on depression, focusing on the moderating effects of job crafting and relationship conflict based on the JD-R. The results of the empirical analysis of 228 ESG staff members are as follows: First, both ESG complexity and uncertainty, which are ESG stressors, were found to have significant positive effects on depression. As previous studies emphasize, these results show that the concepts that make up ESG are broad [38], so it is necessary to spend more time and money learning about ESG. In addition, depression has been interpreted as being caused by increased ESG-related work pressure [32] to meet the needs of stakeholders. Second, job crafting alleviates the significant positive effects of ESG stress, complexity, and uncertainty on depression. These results show that even if job crafting is stressed by the ESG complexity and ESG uncertainty of ESG staff, they will be increasingly interested in ESG-related work by redesigning their job process [52]. This is believed to be because it promotes work engagement and relieves the pain caused by ESG [14]. Finally, conflict reinforced the significant positive effects of ESG stress, complexity, and uncertainty on depression. Relationship conflict can weaken the work productivity of ESG staff. Decreased work productivity causes employees to lose work motivation and, in the worst case, leads to absenteeism or turnover, resulting in impaired organizational functions [21].

6.2. Implication

This study has both academic and practical implications. The academic implications of this study are as follows. First, it is academically meaningful in that it presents the concept of ESG stress that employees may experience owing to ESG, which has become a prerequisite for corporate sustainability, and identifies the impact of ESG stress on depression based on the JD-R. Second, it presents research results showing that job crafting alleviates the relationship between ESG stress and depression. In contrast, relationship conflict strengthens the relationship between ESG stress and depression based on the JD-R. Third, because this study uses ESG stress as the main variable, it can contribute to the expansion of sustainability research by examining a new aspect of the dark side rather than the positive side of sustainability-related research. Fourth, considering variables such as stress, which are the negative effects of mental health, job crafting, and relationship conflict, the interaction with ESG stress can be considered, which can contribute to the development of research related to organizational psychology.
The practical implications of this study are as follows: First, as ESG stress experienced by employees due to ESG, which is considered important for corporate sustainability, has a positive effect on depression, it is necessary to provide guidelines for performing ESG-related tasks at the organizational level to manage ESG staff stress. Second, as job crafting alleviates the positive effect of ESG stress on depression, it is necessary to provide organizational-level support or appropriate compensation so that ESG staff can perform job crafting, such as training, to strengthen employees’ competencies so that they can perform their work independently and proactively. Third, because conflict strengthens the positive effect of ESG stress on depression, efforts should be made to resolve conflict among team members to improve the work productivity of ESG staff. Fourth, this study is meaningful in that it has laid the groundwork for establishing ESG strategies at the business unit level, not at the company-wide level, for ESG researchers. The research subjects are employees within the organization who are stressed by ESG work in companies responding to ESG.

6.3. Limitations

The limitations of this study were as follows. First, although various types of ESG stress exist, this study classifies ESG stress only into complexity and uncertainty. Future research should include various stress factors such as overload and invasion. Second, although mental health has various sub-factors, such as anxiety, anger, and post-traumatic stress disorder (PTSD), in addition to depression, this study focused only on depression. Therefore, future studies should include more diverse mental health factors. Third, although various factors such as resilience, optimism, and self-efficacy can alleviate the relationship between ESG stress and depression, this study only considered job crafting. In future research, it will be necessary to identify variables that can alleviate the relationship between ESG stress and depression using more diverse variables. Finally, we did not consider industry characteristics as control variables, although ESG may vary depending on an industry’s structure and characteristics. Future studies should identify industry characteristics and use them for empirical analyses.

Author Contributions

Methodology, G.-R.H.; Writing—original draft, G.-R.H.; Writing—review & editing, J.-E.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by a Research promotion program of SCNU.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Distribution of research sample.
Table 1. Distribution of research sample.
VariableDimensionNumber%
GenderMale15022865.6100
Female7834.4
Age20–29122285.2100
30–398336.3
40–497030.6
50–595122.7
60–69125.2
Job positionStaff222289.6100
Assistant Manager114.8
Head Manager4921.5
General Manager5825.4
Deputy Manager5222.8
Executive Manager2912.8
CEO73.1
Table 2. Results of validity and reliability test.
Table 2. Results of validity and reliability test.
ConstructsLoadingsEigen ValueVariance Ratio (%)Cumulative Variance (%)Cronbach’s α
Relationship conflict 10.7535.73920.49820.4980.939
Relationship conflict 20.852
Relationship conflict 30.833
Relationship conflict 40.824
Relationship conflict 50.861
Relationship conflict 60.816
Relationship conflict 70.847
Relationship conflict 80.820
Depression 10.8644.80717.16837.6660.921
Depression 20.866
Depression 30.766
Depression 40.894
Depression 50.799
Depression 60.646
Depression 70.717
Job crafting 10.8023.64513.01850.6840.962
Job crafting 20.815
Job crafting 30.803
Job crafting 40.848
Job crafting 50.838
ESG complexity 10.8843.62312.93963.6240.864
ESG complexity 20.892
ESG complexity 30.912
ESG complexity 40.871
ESG uncertainty 10.8822.88410.373.9230.901
ESG uncertainty 20.891
ESG uncertainty 30.820
ESG uncertainty 40.685
Table 3. Descriptive statistics and correlations.
Table 3. Descriptive statistics and correlations.
Construct1234567891011
1. Gender1
2. Age−0.0370 **1
3. Level of education−0.039−0.0611
4. Job position0.443 **−0.497 **−0.209 **1
5. Work experience−0.295 **0.596 **0.040−0.446 **1
6. Number of employees−0.1010.208 **0.394 **0.382 **0.177 **1
7. ESG complexity0.0050.124 *−0.062−0.0130.060−0.295 **1
8. ESG uncertainty−0.192 **0.116 *0.041−0.1070.0270.0400.457 **1
9. Job Crafting−0.1130.222 **0.161 **−0.129 *0.0970.0540.0570.202 **1
10. Relationship Conflict−0.156 **0.007−0.0310.029−0.021−0.156 **0.117 *0.268 **0.0521
11. Depression 0.070−0.093−0.176 **0.141 *−0.0750.133 *0.179 **0.183 **−0.330 **0.307 **1
S.D.0.5011.0380.7751.8780.3032.7050.9781.3061.1151.1731.452
Mean0.5002.6902.8404.6204.7014.3014.2993.4544.4663.6783.295
* p < 0.05, ** p < 0.01 (2-tailed).
Table 4. Results of regression analysis.
Table 4. Results of regression analysis.
Depression
Model 1Model 2Model 3Model 4Model 5Model 6
Gender0.0430.0480.0610.0660.0590.055
(0.706)(0.886)(0.986)(1.060)(1.145)(0.902)
Age−0.039−0.041−0.053−0.056−0.078−0.064
(−0.606)(−0.726)(−0.825)(−0.878)(−1.158)(−1.006)
Level of education−0.119 **−0.121 **−0.128 *−0.124 *−0.135 *−0.126 *
(−2.128)(−2.221)(−2.064)(−2.001)(−2.073)(−2.063)
Job position0.0360.0360.0390.0430.0500.043
(0.624)(0.628)(0.630)(0.697)(0.763)(0.702)
Work experience0.0040.0140.0180.0160.0210.019
(0.601)(0.862)(0.911)(0.897)(0.908)(0.883)
Number of
employees		0.0730.1070.0820.1040.0800.041
(1.265)(1.537)(1.165)(1.478)(1.134)(1.241)
ESG complexity0.143 *0.143 *0.140 *0.153 *0.157 *0.139 *
(2.019)(2.021)(2.038)(2.187)(2.170)(2.058)
ESG uncertainty0.197 **0.198 **0.170 *0.165 *0.229 **0.162 *
(2.722)(2.723)(2.403)(2.336)(3.138)(2.321)
Job crafting −0.354 ***−0.338 ***−0.346 ***−0.306 ***−0.353 ***
(−4.748)(−4.981)(−5.526)(−4.493)(−5.714)
Relationship conflict 0.301 ***0.297 ***0.295 ***0.331 ***0.327 ***
(4.995)(4.765)(4.760)(4.659)(5.258)
ESG complexity ×
Job crafting		 −0.309 **
(−3.139)
ESG uncertainty ×
Job crafting		 −0.388 **
(−4.360)
ESG complexity ×
Relationship conflict		 0.253 *
(2.867)
ESG uncertainty ×
Relationship conflict		 0.147 *
(2.465)
R20.4810.5520.5510.5530.5660.569
Adjusted R20.2310.3030.3040.3060.3280.324
∆R2 0.0710.0700.0720.0850.088
F7.623 ***9.644 ***9.764 ***9.911 ***10.623 ***10.761 ***
(1) * p < 0.05, ** p < 0.01, *** p < 0.001; (2) Numbers are standardized regression coefficients. Numbers in parentheses are t statistics.
Table 5. Additional analyses and robustness test.
Table 5. Additional analyses and robustness test.
Depression
Model 1Model 2Model 3Model 4Model 5Model 6
Gender0.0940.0810.0820.0810.0790.083
(1.453)(1.526)(1.547)(1.529)(1.502)(1.575)
Age−0.182 *−0.109 †−0.112 †−0.110 †−0.107 †−0.106 †
(−2.319)(−1.670)(−1.699)(−1.672)(−1.631)(−1.613)
Level of education−0.073−0.028−0.029−0.029−0.026−0.028
(−1.228)(−0.572)(−0.584)(−0.579)(−0.527)(−0.572)
Job position0.0240.0180.0190.0170.0220.015
(0.340)(0.303)(0.332)(0.285)(0.376)(0.264)
Work experience0.032−0.009−0.005−0.009−0.009−0.009
(0.424)(−0.150)(−0.085)(−0.154)(−0.154)(−0.143)
Number of
employees		−0.039−0.039−0.042−0.039−0.043−0.038
(−0.662)(−0.812)(−0.867)(−0.808)−0.883)(−0.782)
ESG complexity0.203 **0.190 ***0.195 ***0.190 ***0.197 ***0.179 **
(3.106)(3.491)(3.549)(3.491)(3.597)(3.257)
ESG uncertainty0.176 **0.221 **0.221 **0.218 **0.210 **0.228 ***
(2.193)(3.411)(3.400)(3.395)(3.199)(3.544)
Job crafting −0.097 *−0.103 *−0.094 *−0.102 *−0.104 **
(−1.910)(−1.995)(−1.960)(−1.985)(−2.027)
Relationship conflict 0.523 ***0.524 ***0.523 ***0.525 ***0.523 ***
(10.786)(10.789)(10.767)(10.813)(10.807)
ESG complexity ×
Job crafting		 −0.331 **
(−2.668)
ESG uncertainty ×
Job crafting		 −0.339 ***
(−3.180)
ESG complexity ×
Relationship conflict		 0.446 ***
(4.981)
ESG uncertainty ×
Relationship conflict		 0.464 ***
(4.378)
R20.3610.6360.6370.6380.6390.636
Adjusted R20.1750.3820.3830.3840.3860.384
∆R2 0.2750.2760.2770.2780.275
F14.025 ***17.800 ***17.863 ***17.942 ***18.085 ***19.642 ***
(1) † p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001; (2) Numbers are standardized regression coefficients. Numbers in parentheses are t statistics.
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Han, G.-R.; Lee, J.-E. Does ESG Affect Mental Health of Employees? Focusing on the Moderating Effects of Job Crafting and Relationship Conflict. Sustainability 2024, 16, 6076. https://doi.org/10.3390/su16146076

AMA Style

Han G-R, Lee J-E. Does ESG Affect Mental Health of Employees? Focusing on the Moderating Effects of Job Crafting and Relationship Conflict. Sustainability. 2024; 16(14):6076. https://doi.org/10.3390/su16146076

Chicago/Turabian Style

Han, Ga-Rog, and Jae-Eun Lee. 2024. "Does ESG Affect Mental Health of Employees? Focusing on the Moderating Effects of Job Crafting and Relationship Conflict" Sustainability 16, no. 14: 6076. https://doi.org/10.3390/su16146076

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