Sustainable Work and Comparing the Impact of Organizational Trust on Work Engagement Among Office and Production Workers in the Korean Food Manufacturing Industry

Abstract

Organizational performance can be enhanced by adopting sustainable work policies. This study examined the relationship between psychological factors such as organizational trust, job satisfaction, well-being, and work engagement among workers in the Korean food industry. This study utilized the Korean Working Conditions Survey (KWCS) data, and a total of 472 workers were selected as subjects for the research, comprising 185 office workers and 287 production workers. Regression analysis was conducted by comparing office and production workers to test the relationship between psychological factors and to identify causal relationships through a mediation model. The results of hypothesis testing via regression analysis indicated that organizational trust is proportionally related to job satisfaction (p < 0.001), well-being (p < 0.001), and engagement (p < 0.001), while work engagement is proportionally related to job satisfaction (p < 0.001) and well-being (p < 0.001). In particular, in the regression equation analyzing organizational trust (T) and job satisfaction (y), as organizational trust increases, the rate of increase in job satisfaction of office workers (y = 1.131 + 0.610T) is greater than that of production workers (y = 1.131 + 0.557T). On the other hand, the initial level of work engagement (y) of office workers is higher than that of production workers in the regression equations concerning organizational trust (T) and work engagement (y = 1.753 + 0.516T vs. y = 1.634 + 0.516T), as well as well-being (W) and work engagement (y = 2.648 + 0.345W vs. y = 2.512 + 0.345W). According to mediation models, work engagement was directly affected by organizational trust and indirectly affected by job satisfaction or well-being, and office workers exhibited higher work engagement than production workers. The findings of this study emphasize the need for customized enhancements to working hours, work organization, and the work environment for production workers to ensure sustainable employment.

1. Introduction

1.1. Purpose of Study

Sustainability includes environmental, social, and economic systems, and it promotes long-term work activities [1]. It is crucial to eliminate barriers that hinder workers’ employment and retention in order to achieve sustainable work. Consequently, it is important to improve living and working environments that foster engagement and support continuous employment [2]. Working conditions in the workplace can be classified into physical factors and psychological factors [3]. These factors should be considered in the workplace to enable employees to work sustainably, regardless of their physical limitations or job roles [3,4]. Organizational performance can be enhanced by adopting sustainable corporate responsibility policies, such as improving working conditions and addressing human rights issues [5]. This study focuses on the psychological interactions of organizational members.

Food manufacturing encompasses industrial activities that transform products from agriculture, forestry, and fisheries into food and animal feed for both humans and animals [6]. The Korean food industry is characterized by longer working hours than other industries [7]. In addition, production workers are frequently exposed to hot/cold temperatures and noise in the physical work environment [8], and their wages are lower than those of office workers [9]. In particular, production workers in the food industry are more female and older than office workers, and their wages and working conditions are also poor [10,11]. Therefore, conducting a comparative study on psychological factors of workers in the food industry is meaningful, where the working conditions of production and office employees differ significantly.

Work engagement is characterized by a strong commitment and intense focus on one’s work [12], leading to elevated levels of creativity, job performance, and productivity [13,14]. Previous research on work engagement has focused on bank managers [15], social workers [16], and remote work [17], but has predominantly targeted office workers. Understanding the factors that affect work engagement is of great interest to office and production workers concerning work performance and employee welfare [18,19]. Therefore, it is essential to analyze the factors affecting work engagement and their relationship between office and production workers. However, there has been a lack of research comparing and analyzing the relationship between office workers and production workers in the food industry, as well as a lack of attempts to connect it to sustainable work practices.

Employees’ organizational trust is linked to job satisfaction and well-being, and it helps reduce turnover intentions and enhance work engagement [20]. This study aims to analyze the influence of organizational trust on work engagement among employees in the Korean food industry. This study also seeks to establish a causal model that links organizational trust, job satisfaction, and well-being to work engagement. Furthermore, this study compares how the relationship differs between office and production workers using regression equations. These research findings are essential for understanding the traits of production and office workers and are crucial for helping older workers secure new jobs or adapt to new roles, which is necessary for sustainable employment.

1.2. Theoretical Background

1.2.1. Organizational Trust

Organizational trust refers to the belief that members of the organization have regarding their employers, roles, and relationships within the organization [21]. Leadership-focused sustainability planning in the food business has a positive impact on organizational trust and performance [22]. Furthermore, higher levels of organizational trust can reduce turnover tendencies and enhance job satisfaction, communication efficiency, and work performance [23].

1.2.2. Job Satisfaction

Job satisfaction refers to the degree of contentment that employees feel about their jobs, reflecting their emotional state regarding job-related factors. A key factor impacting job satisfaction is organizational trust. The level of organizational trust in employees influences job satisfaction [24]. Research indicates that organizational trust is positively associated with higher job satisfaction among nurse practitioners [25], doctors, nurses, and other healthcare professionals [26]. The poor working conditions and long working hours experienced by food manufacturing production workers can reduce job satisfaction. However, there has been a lack of research comparing the relationship between psychological factors in production and office work [27]. Therefore, the following hypothesis regarding job satisfaction is formulated.

Hypothesis 1 (H1): 

Organizational trust affects job satisfaction, and there is a difference between office and production workers.

1.2.3. Well-Being

Employee well-being is a level of happiness encompassing thoughts, perceptions, emotions, and experiences at work [28]. The well-being of employees significantly influences their performance and the organization’s overall productivity [29,30]. One major factor influencing workers’ well-being in the workplace is organizational trust [31]. Organizational trust significantly impacts the psychological well-being of medical workers [18] and correlates with the well-being of nurses [32]. Production workers in the Korean food manufacturing industry are typically employed by small businesses. This often results in less investment in upgrading, negatively impacting their overall well-being. Thus, the following hypothesis is formulated regarding well-being.

Hypothesis 2 (H2): 

Organizational trust influences well-being, and differences exist between office and production workers.

1.2.4. Work Engagement

Workers’ work engagement positively influences their creativity, job performance, and productivity levels [33]. Organizational trust enhances employee work engagement and reduces psychosocial risks [34]. A study of seven commercial banks and four pharmaceutical companies found a strong correlation between organizational trust and job engagement [35]. Additionally, healthcare workers’ organizational trust and support positively affected their job engagement [36]. Therefore, the following hypothesis is derived.

Hypothesis 3 (H3): 

Organizational trust affects work engagement, with differences between office workers and production workers.

Job satisfaction has a significant impact on work engagement [37]. As job satisfaction among bank managers increases, work engagement also rises [15]. Similarly, for business consultants, positive emotions and feelings at work impact work engagement [35]. Production workers in the Korean food manufacturing industry are typically employed by small businesses [11]. This often results in less investment in upgrading, negatively impacting their job satisfaction. Therefore, the following hypothesis is formulated.

Hypothesis 4 (H4): 

Job satisfaction influences work engagement, with differences between office workers and production workers.

Previous research has demonstrated that well-being influences work engagement. For social workers, a decline in psychological well-being is associated with reduced work engagement [16]. Additionally, a positive correlation exists between teachers’ well-being and their work engagement [38]. Comparing production and office workers in the Korean food manufacturing industry will provide basic data for establishing customized measures for production workers. Therefore, this study aims to analyze whether there are differences in the correlation between the psychological factors of production and office workers. Thus, the following hypothesis is formulated regarding work engagement.

Hypothesis 5 (H5): 

Well-being impacts work engagement, with differences between office workers and production workers.

1.2.5. Hypothesis Testing and Mediation Model

This study performs hypothesis testing using a regression analysis model. The mediation model proposed by Edwards and Lambert refers to a framework that thoroughly analyzes moderating and mediating effects within a single model [39]. By employing a model that simultaneously considers both moderating and mediating effects, the interactions and influences among variables can be examined comprehensively through various pathways. Yang and Jeong used a mediation model to analyze the causal relationship regarding job satisfaction among public sector workers [40]. This study employs the mediation model to thoroughly examine how organizational trust (T), job satisfaction (J), and well-being (W) influence work engagement and to establish the causal relationship. Furthermore, the indicator variable Z determines whether a distinction exists between office workers and production workers in the regression equation. The indicator variable Z denotes a variable that converts categorical variables to 0 and 1, thus expressing them numerically. By transforming categorical variables into dummy variables and analyzing them, the impact of a specific category on the dependent variable with the base category can be interpreted.

2. Materials and Methods

2.1. Data Collection and Subjects

This study used the Korean Working Conditions Survey (KWCS) data, which is publicly available [41]. The 6th KWCS was conducted nationwide over a six-month period, from 5 October 2020 to 4 April 2021, and the working conditions of 50,538 workers were surveyed using a stratified sampling method targeting the Korean workforce. Among 50,538 respondents, all workers corresponding to the food industry code of the Korean Standard Industrial Classification [7] were selected as subjects. In addition, office workers and production workers were classified according to the Korean Standard Classification of Occupations [42]. Food manufacturing workers were selected as research subjects based solely on industry and job indices from the raw data, without any control variables. Any data with missing values in the research variables were eliminated.

Finally, after excluding respondents with missing values for the study variables, 472 workers were selected as subjects for the research, including 185 office workers (39.2%) and 287 production workers (60.8%). The gender distribution by occupation group showed that the ratio of males in office work was 48.6%, while females comprised 51.4%. In production work, the ratio of males was 39.7%, and females were 60.3%. However, there was no significant gender difference between occupation groups (Chi-square = 3.653, p = 0.056). The age distribution revealed that 75.7% of office workers were under 50 years old, while 24.3% were over 50 years old. In contrast, 43.2% of production workers were under 50 years old, and 56.8% were over 50 years old. The proportion of elderly workers was higher among production workers (Chi-square = 54.964, p < 0.001). The high proportion of elderly workers in the age distribution of production workers reflects the sample size that corresponds to the age distribution in the Korean food industry workforce.

2.2. Research Variables

The research variables included occupational groups, organizational trust, well-being, job satisfaction, and work engagement selected from the KWCS and the European Working Conditions Surveys (EWCS) [43] questionnaire.

Table 1. Research variables of this study.

Variable	Variable Abbreviation: Description	Observed Score
Job	Z: Office worker or production worker	0: Office worker, 1: Production worker
Organizational trust	T1: Employees are appreciated when they have done a good job	1: Strongly disagree, 2: Tend to disagree, 3: Neither agree nor disagree, 4: Tend to agree, 5: Strongly agree
	T2: The management trusts the employees to do their work well
	T3: Conflicts are resolved in a fair way
	T4: The work is distributed fairly
	T5: There is good cooperation between you and your colleagues
	T6: In general, employees trust management
Well-being	W1: I have felt cheerful and in good spirits	0: At no time, 1: Some of the time, 2: Less than half of the time, 3: Most than half of the time, 4: Most of the time, 5: All of the time
	W2: I have felt calm and relaxed
	W3: I have felt active and vigorous
	W4: I woke up feeling fresh and rested
	W5: My daily life has been filled with things that interest me
Job satisfaction	J1: Considering all my efforts and achievements in my job, I feel I get paid appropriately	1: Strongly disagree, 2: Tend to disagree, 3: Neither agree nor disagree, 4: Tend to agree, 5: Strongly agree
	J2: My job offers good prospects for career advancement
	J3: I receive the recognition I deserve for my work
	J4: The organization I work for motivates me to perform at my best
	J5: I feel very competitive with others when it comes to work
	J6: I might lose my job in the next 6 months
	J7: Even if I quit my current job or lose my job, I will easily be able to find a job that pays similar wages
Work engagement	E1: At my work I feel full of energy	1: Never, 2: Rarely, 3: Sometimes, 4: Most of the time, 5: Always
	E2: I am enthusiastic about my job
	E3: Time flies when I am working

displays the research variables, their descriptions, and scales. The occupational groups were classified into office and production workers.

In Table 1, organizational trust consisted of six items, each utilizing a 5-point Likert scale. Each subject’s organizational trust value is calculated as the average of six items’ scores, with a higher score representing greater organizational trust. Well-being is assessed using a 6-point scale comprising five items. The average of the five items’ scores represented the value of well-being, with a higher score indicating better well-being. Job satisfaction was measured by a 5-point scale with 7 items. Each subject’s job satisfaction value is calculated as the average of 7 items’ scores, and a higher score indicates higher job satisfaction. Work engagement was evaluated on a 5-point scale using three items. The average of three items’ scores was defined as the work engagement value, and a higher score represents higher work engagement.

2.3. Reliability Analysis

Table 2. Results of reliability analysis of variables using Cronbach’s Alpha.

Latent Variable	Initial Items	Removed Question Item	Final Items	Cronbach’s Alpha
Organizational trust	6		6	0.883
Job satisfaction	7	J5, J6, J7	4	0.795
Well-being	5		5	0.909
Work engagement	3		3	0.778

presents the final reliability analysis results for subjective survey variables. In Table 2, Cronbach’s alpha value for organizational trust was 0.883, considered satisfactory, while well-being (0.909) and work engagement (0.778) were also deemed acceptable. Items J5, J6, and J7 from job satisfaction were removed, resulting in a Cronbach’s alpha value of 0.795, which is satisfactory. The job satisfaction value of each subject was corrected as an average of four items, not excluded.

2.4. Regression Analysis for Hypothesis Testing and Mediation Model

In this study, a regression equation represents a linear proportional relationship in the form of a first-order function between a dependent variable and an independent variable.

Table 3. Regression analysis using indicator variable, Z.

Model	y	Independent Variable	Regression Model
Hypothesis Testing	Job satisfaction	Z, T, T×Z	$H1:y=({\alpha }_{11}+{\alpha }_{12}$$Z)+{(\beta }_{11}+{\beta }_{12}Z)\times T$
	Well-being	Z, T, T×Z	$H2:y=({\alpha }_{21}+{\alpha }_{22}$$Z)+{(\beta }_{21}+{\beta }_{22}Z)\times T$
	Work engagement	Z, T, T×Z	$H3:y=({\alpha }_{31}+{\alpha }_{32}$$Z)+{(\beta }_{31}+{\beta }_{32}Z)\times T$
	Work engagement	Z, J, J×Z	$H4:y=({\alpha }_{41}+{\alpha }_{42}$$Z)+{(\beta }_{41}+{\beta }_{42}Z)\times J$
	Work engagement	Z, W, W×Z	$H5:y=({\alpha }_{51}+{\alpha }_{52}$$Z)+{(\beta }_{51}+{\beta }_{52}Z)\times W$
Mediation Model 1	Job satisfaction	Z, T, T×Z	$y=({\gamma }_{11}+{\gamma }_{12}$$Z)+({\delta }_{11}+{\delta }_{12}Z)\times T$
	Work engagement	Z, T, J, T×Z, J×Z	$y=({\gamma }_{21}+{\gamma }_{22}$$Z)+({\delta }_{21}+{\delta }_{22}Z)\times T+({\theta }_{21}+{\theta }_{22}Z)\times J$
Mediation Model 2	Well-being	Z, T, T×Z	$y=({\gamma }_{31}+{\gamma }_{32}$$Z)+({\delta }_{31}+{\delta }_{32}Z)\times T$
	Work engagement	Z, T, W, T×Z, W×Z	$y=({\gamma }_{41}+{\gamma }_{42}$$Z)+({\delta }_{41}+{\delta }_{42}Z)\times T+({\theta }_{41}+{\theta }_{42}Z)\times W$
Mediation Model 3	Job satisfaction	Z, T, T×Z	$y=({\gamma }_{51}+{\gamma }_{52}$$Z)+({\delta }_{51}+{\delta }_{52}Z)\times T$
	Well-being	Z, T, T×Z	$y=({\gamma }_{61}+{\gamma }_{62}$$Z)+({\delta }_{61}+{\delta }_{62}Z)\times T$
	Work engagement	Z, T, J, W, T×Z, J×Z, W×Z	$y=({\gamma }_{71}+{\gamma }_{72}$$Z)+({\delta }_{71}+{\delta }_{72}Z)\times T+({\theta }_{71}+{\theta }_{72}Z)\times J+({\omega }_{72}+{\omega }_{72}Z)\times W$

Note: Z = 0 for office workers or 1 for production workers; T = Organizational trust; J = Job satisfaction; W = Well-being.

shows the established hypotheses and the corresponding mediation models derived from them. The model with a high R² value in the regression equation has better explanatory power. In the hypothesis test for the regression model of the dependent variable (y), if the p-value is less than 0.05, the null hypothesis is accepted. Furthermore, the significance of the coefficients for the independent variables and dummy variables (Z) was tested using the stepwise regression method, removing insignificant variables from the regression equation.

In Table 2, ${(\alpha }_{i1}$+${\alpha }_{i2}Z)$ represents the intercept of the regression equation and ${\alpha }_{i2}$ indicates whether the initial values of the office (Z = 0) and production work (Z = 1) are different [40]. Among regression coefficients, ${\alpha }_{i2}$ indicates whether the initial values of the office (Z = 0) and production work (Z = 1) differ [36,37]. The slope coefficient $({\beta }_{i2}+{\beta }_{i2}Z)$ of the regression equation determines whether the independent variables have a positive or negative impact on the dependent variable [36,37]. Thus, when the Z-related coefficients, ${\alpha }_{i2}$ and ${\beta }_{i2}$ are all removed from the regression equation, there is no difference in the relationship between office and production workers.

Edwards and Lambert’s Mediation Model [39] incorporates various independent variables to determine the effects of work engagement. This study examines whether a causal relationship exists through three work engagement models, utilizing direct factors such as organizational trust and indirect factors like job satisfaction and well-being. This study also aims to identify whether there is a difference in the direct and mediation effects between office workers and production workers by incorporating a dummy variable (Z) in the regression equation of the mediation model. That is, when the Z-related coefficients, α_i2, β_i2, γ_i2, δ_i2, θ_i2, and ω_i2, are all removed from the regression equation, there is no difference in the relationship between office work and production. The regression model was evaluated at a significance level of 0.05 and implemented using SPSS version 27.0.

3. Results

3.1. Correlation Coefficients Between Workers’ Subjective Scores

Table 4. Correlation coefficients among workers’ subjective scores.

		Job Satisfaction	Well-Being	Work Engagement
Total (N = 472)	Organizational trust	0.554 *	0.391 *	0.484 *
	Job satisfaction		0.369 *	0.483 *
	Well-being			0.552 *
Office worker (N = 185)	Organizational trust	0.580 *	0.399 *	0.503 *
	Job satisfaction		0.310 *	0.468 *
	Well-being			0.526 *
Production worker (N = 287)	Organizational trust	0.530 *	0.383 *	0.464 *
	Job satisfaction		0.404 *	0.472 *
	Well-being			0.566 *

* Significant at 0.01.

presents the correlation coefficients among organizational trust, job satisfaction, well-being, and work engagement for office and production workers. In analyzing both groups, work engagement displayed a high correlation coefficient with well-being at 0.552, followed by organizational trust at 0.484 and job satisfaction at 0.483. The work engagement of office workers demonstrated a positive proportional relationship in the following order: well-being (0.526), organizational trust (0.503), and job satisfaction (0.468). In contrast, the work engagement of production workers exhibited a positive proportional relationship in this order: well-being (0.566), job satisfaction (0.472), and organizational trust (0.464). These results suggest that for office workers, organizational trust significantly impacts well-being and work engagement more than for production workers. Conversely, for production workers, job satisfaction has a more significant effect on both well-being and work engagement.

3.2. Results of Hypothesis Testing

Table 5. Regression analysis on hypothesis model.

Hypothesis	y	Independent Variable	Regression Model	${\mathit{R}}^2$	Model Validity
H1	Job satisfaction	Z, T, T×Z	y = 1.131 + 0.610T − 0.053 T×Z	0.329	p < 0.001 **
H2	Well-being	Z, T, T×Z	y = 0.370 + 0.671T	0.153	p < 0.001 **
H3	Work engagement	Z, T, T×Z	y = 1.753 + 0.516T − 0.119Z	0.243	p < 0.001 **
H4	Work engagement	Z, J, J×Z	y = 1.958 + 0.488J	0.233	p < 0.001 **
H5	Work engagement	Z, W, W×Z	y = 2.648 + 0.345W − 0.136Z	0.315	p < 0.001 **

Note: ** Significant at 0.05, Z = Job group (0 = office worker and 1 = production worker); T = Organizational trust; J = Job satisfaction; and W = Well-being.

presents the results of the hypothesis test using a regression model. In the regression equation examining the effect of organizational trust on job satisfaction (H1), the R² value was 0.329. Similarly, the R² values for well-being (H2) were 0.153. The R² of the regression equation for work engagement was the highest for well-being (H5) at 0.315, followed by organizational trust (H3) at 0.243 and job satisfaction (H4) at 0.233. This indicates that the regression equation for work engagement is best explained by well-being (H5).

In Table 5, the regression equation (H1) shows that as organizational trust increases, job satisfaction also rises (p < 0.001). The relationship between organizational trust (T) and job satisfaction (y) differed for office workers (y = 1.131 + 0.610T) and production workers (y = 1.131 + 0.557T). This indicates that organizational trust significantly affects office workers’ job satisfaction more than production workers. The regression equation (H2) presents that as organizational trust increased, the well-being index also rose (p < 0.001). No differences were observed in the relationship between office workers and production workers. The regression equation (H3) indicates that as organizational trust (T) increases, work engagement (y) also rises (p < 0.001). There is a difference in the intercept between office workers (y = 1.753 + 0.516T) and production workers (y = 1.634 + 0.516T). The regression equation (H4) shows that as job satisfaction increased, work engagement also rose (p < 0.001). There was no difference in the relationship between office workers and production workers. The regression equation (H5) indicates that as the well-being (W) index rises, work engagement (y) also increases (p < 0.001). There is a difference in the intercept in the relationship between office workers (y = 2.648 + 0.345W) and production workers (y = 2.512 + 0.345W).

In summary, Table 5 shows that all five hypotheses were accepted. Also, results suggest that even when organizational trust increases, office workers’ job satisfaction rises more than that of production workers. They also indicate that office workers experience higher work engagement than production workers, even at the same level of organizational trust or well-being.

3.3. Mediation Model 1: Relationships Between Organizational Trust and Job Satisfaction on Work Engagement

Figure 1 and

Table 6. Regression analysis on mediation model 1.

Dependent Variable (y)	Independent Variable	Regression Model	${\mathit{R}}^2$	Model Validity
Job satisfaction	Z, T, T×Z	y = 1.131 + 0.610T − 0.053T×Z	0.329	p < 0.001 **
Work engagement	Z, T, J, T×Z, J×Z	y = 1.314 + 0.338T + 0.313J	0.301	p < 0.001 **

Note: ** Significant at 0.05, Z = Job group (0 = office worker and 1 = production worker); T = Organizational trust; J = Job satisfaction.

present the results of regression analysis for mediation model 1, which has the dependent variable, work engagement (E); the independent variable, organizational trust (T); and the mediator variable, job satisfaction (J). In Figure 1, coefficients represent the slope of the regression equation. Figure 1 and Table 6 show that work engagement is directly influenced by organizational trust and indirectly influenced by job satisfaction, suggesting a causal relationship.

In Table 6, job satisfaction (y) rises with increasing organizational trust (T). Moreover, office workers (y = 1.131 + 0.610T) are more influenced by organizational trust than production workers (y = 1.131 + 0.557T). This implies that even when organizational trust increases, job satisfaction among office workers rises more than that of production workers.

The regression equation for work engagement (y) indicated that work engagement rises as organizational trust (T) and job satisfaction (J) increase (y = 1.314 + 0.338T + 0.313J). Furthermore, the impact of organizational trust (0.338) was more significant than that of job satisfaction (0.313). The work engagement in the mediation model was directly influenced by organizational trust and indirectly influenced by job satisfaction. Furthermore, the mediating effect of job satisfaction was more substantial for office workers (0.191) than for production workers (0.174). This implies that within the causal relationship between organizational trust and job satisfaction related to work engagement, office workers exhibit a greater increase in work engagement than production workers at equivalent levels of organizational trust and job satisfaction.

3.4. Model 2: Relationships Between Organizational Trust and Well-Being on Work Engagement

Figure 2 provides a summary of the analysis results for mediation model 2, which examines the relationships among the dependent variable work engagement (E), the independent variable organizational trust (T), and the mediator variable well-being (W). Additionally,

Table 7. Regression analysis on mediation model 2.

Dependent Variable (y)	Independent Variable	Regression Model	${\mathit{R}}^2$	Model Validity
Well-being	Z, T, W×Z	y = 0.370 + 0.671T	0.153	p < 0.001 **
Work engagement	Z, T, W, T×Z, W×Z	y = 1.647 + 0.336T + 0.269W − 0.111Z	0.396	p < 0.001 **

Note: ** Significant at 0.05, Z = Job group (0 = office worker and 1 = production worker); T = Organizational trust; W = Well-being.

presents the regression analysis results for this mediation model. In Figure 2, coefficients represent the slope of the regression equation. Figure 2 and Table 7 indicate that a causal model linking organizational trust, well-being, and work engagement is adopted. Table 7 illustrates that the well-being index (y) rises as organizational trust (T) increases. However, there is no difference in the relationship between office and production workers (y = 0.370 + 0.671T).

In examining the regression equation of organizational trust (T) and the well-being index (W) on work engagement (y), it was observed that as both organizational trust and the well-being index increase, work engagement also rises. The mediating effect of well-being was 0.180. In Table 7, the impact of organizational trust (0.336) was greater than that of the well-being index (0.269), as represented by the equation y = 1.647 + 0.336T + 0.269W − 0.111Z. A difference in the intercept was noted in the relationship equation between office (y = 1.647 + 0.336T + 0.269W) and production workers (y = 1.536 + 0.336T + 0.269W). This implies that office workers exhibit greater work engagement than production workers, even when the levels of organizational trust and well-being are identical.

3.5. Model 3: Relationships Between Organizational Trust, Job Satisfaction, and Well-Being on Work Engagement

Figure 3 and

Table 8. Regression analysis on mediation model 3.

Dependent Variable (y)	Independent Variable	Regression Model	${\mathit{R}}^2$	Model Validity
Job satisfaction	Z, T, T×Z	y = 1.131 + 0.610T − 0.053 T×Z	0.329	p < 0.001 **
Well-being	Z, T, T×Z	y = 0.370 + 0.671T	0.153	p < 0.001 **
Work engagement	Z, T, J, W, T×Z, J×Z, W×Z	y = 1.317 + 0.225T + 0.227J + 0.244W	0.423	p < 0.001 **

Note: ** Significant at 0.05, Z = Job group (0 = office worker and 1 = production worker); T = Organizational trust; J = Job satisfaction; and W = Well-being.

present the regression analysis results for mediation model 3, which has the dependent variable, work engagement (E); the mediating variables, job satisfaction (J) and well-being (W); and the independent variable, organizational trust (T). Table 8 indicates that a causal model linking organizational trust, well-being, job satisfaction, and work engagement is adopted.

As shown in Table 8, job satisfaction (y) increases with rising organizational trust (T). Furthermore, a difference exists between the job satisfaction of office workers (y = 1.131 + 0.610T) and production workers (y = 1.131 + 0.557T). This indicates that as organizational trust increases, job satisfaction among office workers is more pronounced than that among production workers. Additionally, the regression equation for well-being (y) indicated that as organizational trust (T) increased, the well-being index also rose. However, no difference was found in the relationship between office and production workers (y = 0.370 + 0.671T).

The regression equation for work engagement (y) reveals that work engagement increases with higher levels of organizational trust (T), job satisfaction (J), and well-being (W). It shows that these factors influence work engagement in the following order: well-being (0.244), job satisfaction (0.227), and organizational trust (0.225). Notably, there is no distinction in the relationship between office and production workers (y = 1.137 + 0.225T + 0.227J + 0.244W).

In summary, work engagement (y) was directly influenced by organizational trust (T) and indirectly impacted by the mediating variables job satisfaction (J) and well-being (W). The mediation effect was more pronounced on well-being than on job satisfaction. The mediation effect of well-being was 0.164, and the mediation effect of job satisfaction was higher among office workers (0.138) than production workers (0.126). These results mean that office workers show higher work engagement than production workers, even when the levels of organizational trust, well-being, and job satisfaction are the same.

4. Discussion

This study examined the relationship between psychological factors such as organizational trust, job satisfaction, well-being, and work engagement among workers in the food industry. The hypothesis testing results of this study indicate that organizational trust positively affects job satisfaction, well-being, and work participation. Additionally, job satisfaction and well-being were found to positively affect work engagement. What is unique about the results of this study is that it tests whether there is a difference in the relationship between office workers and production workers through a regression equation model using dummy variables. In the regression equation analyzing organizational trust and job satisfaction, the slope for office workers was greater than that for production workers. This indicates that when organizational trust increases, the rate of increase in job satisfaction of office workers outpaces that of production workers. On the other hand, in the regression equation for organizational trust and work engagement or the regression equation for well-being and work engagement, there was a difference in the intercept. This suggests that the initial level of work engagement for office workers is higher than that of production workers, and this gap is sustained. The results of the hypothesis test indicate that production workers have lower levels of job satisfaction and well-being compared to office workers. In the food industry, production workers are often older and female and often face challenges such as shift work, exposure to extreme temperatures, and physical strain from handling heavy objects [44,45,46]. Therefore, older or female workers experience problems such as musculoskeletal pain and work-family conflict, which may lower job satisfaction and well-being [47,48].

This study analyzed the causal relationship between psychological factors using a mediation model. In mediation model 1, a causal relationship was identified among organizational trust, job satisfaction, and work engagement. Also, in mediation model 2, a causal relationship was established between organizational trust, well-being, and work engagement. It was also discovered that model 3 of the causal relationships involving organizational trust, job satisfaction, well-being, and work engagement was established. In summary, work engagement is directly influenced by organizational trust and is indirectly influenced by job satisfaction and well-being, establishing a causal relationship. Additionally, the causal model demonstrated that well-being had a stronger mediation effect than job satisfaction. At the same time, the causal model indicated that office workers exhibited higher work engagement than production workers.

The findings of this study indicate that enhancing organizational trust, job satisfaction, and well-being can lead to improved work engagement among food manufacturing workers. Previous studies showed that factors influencing organizational trust, job satisfaction, and well-being include supervisor support, decision-making autonomy, health status, wages, work-family conflict, sleep-related issues, and musculoskeletal pain [36,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65].

Table 9. Correlation coefficients on organizational trust, job satisfaction, and well-being.

Variable	Organizational Trust		Job Satisfaction		Well-Being
	Office Worker	Production Worker	Office Worker	Production Worker	Office Worker	Production Worker
Supervisor support	0.618 *	0.571 *	0.518 *	0.441 *	0.428 *	0.319 *
Decision latitude	0.316 *	0.155 *	0.376 *	0.271 *	0.266 *	0.145 *
Health status	0.289 *	0.156 *	0.172 *	0.142 *	0.353 *	0.255 *
Wage	0.051	0.126 *	0.170 *	0.175 *	0.087	0.101
Work-family conflict	−0.299 *	−0.157 *	−0.133	−0.179 *	−0.176 *	−0.179 *
Sleep-related problems	−0.239 *	−0.132 *	−0.258 *	−0.219 *	−0.349 *	−0.216 *
Musculoskeletal pain	−0.097	−0.076	−0.214 *	−0.115	−0.225 *	−0.203 *

* Significant at 0.05.

presents the analysis of the correlation coefficients among organizational trust, job satisfaction, well-being, and influential factors, categorized into office and production workers. Examining the characteristics of production workers in Table 9, organizational trust displayed a positive correlation with supervisor support (0.571), while showing a negative correlation with work-family conflict (−0.157). Furthermore, the job satisfaction of production workers demonstrated a positive correlation with supervisor support (0.441) and decision latitude (0.271), but a negative correlation with sleep-related problems (−0.219) and work-family conflict (−0.179). Additionally, well-being exhibited a positive correlation with supervisor support (0.441) and health status (0.255), yet a negative correlation with sleep-related problems (−0.216), musculoskeletal pain (−0.203), and work-family conflict (−0.179). These results suggest that work-family conflict, sleep-related problems, and musculoskeletal pain have a negative impact on the job satisfaction and well-being of production workers. This can also be linked to the issue of increasing the well-being and job satisfaction of women and older workers.

The results of this study suggest that customized enhancements are needed to ensure that food manufacturing workers can work safely, both psychologically and physically. First, this study indicates that the food industry needs policy considerations for sustainable work. Exposure to physical or psychosocial risks, as well as excessive working hours, has a negative impact on the implementation of sustainable work [64]. The trend in organization and production processes primarily focuses on intensifying work. However, if there is insufficient effort to adapt working conditions for older workers with declining physical and mental abilities, these workers may hesitate to continue working. In turn, employers may favor replacing older workers with younger, better-educated, and more skilled workers. However, women and elderly production workers, who constitute the majority of the food manufacturing industry, are likely to experience difficulties such as pain even under the same working conditions. Thus, it is necessary to implement human-centered design policies in workspaces, allowing women and older production workers to work regardless of their physical abilities. Second, this study indicates that production workers have lower psychological well-being than office workers. They frequently experience musculoskeletal pain and work-family conflict due to long hours and shift work. Enhancing the psychological factors for production workers is closely linked to personal dignity in the workplace, as it is a key aspect of sustainable work [2]. Therefore, comprehensive psychological strategies are essential to ensure sustainable work, including reduced working hours, human-centered work organization policies, and strategies to reduce exposure to physical and psychosocial risks [65].

This study has several limitations. First, although this study used the questionnaire on organizational trust, job satisfaction, well-being, and work engagement from the KWCS survey, the existence of response bias by industry and job type was not examined, so caution is required in interpreting the results. Second, while this study surveyed industrial occupations in the KWCS, the number of subjects in office and production jobs varied, so caution is necessary when extending the results to consider the characteristics of these groups. Third, while other factors, such as supervisor support and decision-making, influence work engagement, this study focused solely on organizational trust, job satisfaction, and well-being. Therefore, future research should develop an integrated model that includes additional influential factors beyond the three examined in this study. In the discussion, it was confirmed that there is a difference in the correlation coefficients between office and production workers concerning the factors that influence organizational trust, job satisfaction, and well-being. However, future research needs to conduct regression analysis to assess the extent of the influence of supervisor support, decision-making, and health status. Despite these limitations, this study is significant because it confirms that differences exist in the factors affecting work engagement between production and office workers. It also suggests that sustainable work policies, which consider the differences in job types, are necessary to enhance the work participation of both production and office workers.

5. Conclusions

This study showed that the organizational trust of food manufacturing workers was closely linked to job satisfaction, well-being, and work engagement. Additionally, this study suggests that work engagement is affected by job satisfaction or well-being. In particular, this study revealed notable differences in the relationships among psychological variables for office workers and production workers, analyzed through a regression equation model utilizing dummy variables. According to the regression equation analyzing organizational trust and job satisfaction, as organizational trust increases, the rate of increase in job satisfaction of office workers is greater than that of production workers. On the other hand, in the regression equations for organizational trust and work engagement, or for well-being and work engagement, the initial level of work engagement for office workers is higher than that of production workers.

The findings of this study indicate that tailored improvements are crucial for ensuring the safety of food manufacturing workers. This involves implementing human-centered design policies in the workplace, which will allow women and older production workers to perform their tasks effectively, regardless of their physical abilities. Furthermore, comprehensive psychological strategies, such as reducing working hours, implementing human-centered organizational policies, and minimizing exposure to physical and psychosocial risks, are essential to ensure sustainable work.