The Effect of Job Stress of Beauty Industry Employees on Turnover Intention

Abstract

Purpose: Employees in the beauty industry, where emotional labor is essential, are exhausted due to stress from excessive working hours and low pay, and ultimately consider changing jobs. This study analyzed the structural relationship of turnover intention according to job stress of beauty industry employees. We tried to present implications by verifying the methods necessary for conflict management in the beauty industry from an empirical point of view. Research design, data and methodology: This study selected 518 workers in the beauty industry as a sample. Frequency analysis, validity and reliability analysis, factor analysis, correlation analysis, and regression analysis were performed using SPSS (Statistical Package for Social Science) WIN23.0. Results: The moderating effect of work experience, a moderating variable, was found to be significant in the effect of job stress of beauty industry employees following changes in the employment environment on the dependent variable, turnover intention. Conclusion: This study revealed that changes in the employment environment negatively affect the job stress of beauty workers. To reduce the job stress of employees in the beauty industry, a systematic response at the organizational level will be necessary. In addition, it is expected that it will help establish differentiated strategies such as compensation system, service training, and service management to reduce job stress.

1. Introduction

The domestic beauty industry is a new growth business that is growing rapidly due to well-being-oriented consumption trends and personal desire for beauty and health as income increases and living standards improve (Hong, 2011). According to Sharon Ann, a beauty analyst at WGSN, a global trend analysis company in the UK, the secret to the success of K-beauty is the fusion of cutting-edge technology and science, with the power drawn from Korea's culture and heritage and the rapid evolution of new innovative technologies to meet beauty needs. It was said that it was to quickly grasp the consumer's lifestyle (Heo, 2022).

In the beauty industry, smarties and personalized beauty items or services are emerging that combine new concepts of information and communication technology that are more advanced than in customized service trends. Employees in the beauty industry are responding to consumers' desire for higher expectations and higher service. In addition, a lot of time is invested for a changed management paradigm to acquire new knowledge and diverse skills. They experience mental stress from the weighted task of flexibly adjusting the process through the observation and utilization of demand forecasting data. (Kwon & Park, 2011; Song, 2012). Human resources are a key factor in generating organizational benefits and ensure all of the organizational creative resources (Callea et al., 2016; Villajos et al., 2019; Nguyen, 2020; Wright et al., 2003).

The beauty industry is a labor-intensive service industry that relies heavily on human resources (Oh, 2009; Jeon & Yoon, 2021). Employees in the beauty industry, who are classified as emotional workers, spare no effort to acquire new technologies and knowledge to provide beauty services that meet the needs of demanding customers (Jung, 2016). Since beauty services are provided through direct face-to-face contact with customers, mental stress from relationships with customers is high (Yoon, 2010). Beauty industry employees are suffering from various stresses such as late work, heavy work, and low wages. Continuous exposure to these stresses harms physical and mental health. It also negatively affects the quality of beauty services and customer satisfaction (Ko, 2007).

Looking at the research on job stress and job performance, it was reported that the higher the job stress, the more negative the work efficiency and job ability, and the lower the work performance (Ju, 2010). In addition, it was said that the higher the stress caused by the role and relationship of workers and the inadequacy of compensation, the lower the work performance (Lee, 2014). As such, job stress can lead to low productivity of workers, so managing workers' stress is very important (Kim, 2018). Worker's job stress includes satisfaction with work in the workplace, his/her role problems, remuneration problems, relationships with colleagues, heavy burden on work, repeatability, and monotony of work, etc. Various factors are involved (Cooper et al., 1995; Burke & Richardsen, 1990; Hellerstech & Jeffery, 1990; Chang et al., 1997). Factors necessary for employee management are not supported within the organization, accelerating the turnover rate of employees.

The beauty service industry has a very high turnover rate of employees compared to other industries. In companies, fostering and utilizing talent is very important and systematic management is required. Efficient human resource management is important to continue to grow and develop the beauty service industry (Lee, 2010). As the number of workers has increased due to the rapid growth and expansion of the beauty industry, effective and efficient human resource management is needed at the corporate and national economy level (Kwak, 2021). This study aims to examine the effect of job stress on turnover intention through empirical analysis for employees working in the beauty industry. By presenting solutions to increase job satisfaction and organizational commitment of employees in the beauty service industry, this study would like to present implications for the systematic management of human resources in the beauty industry.

2. Literature Review

2.1. Changes in the Employment Environment

The change in the employment environment is labor flexibility, which has developed into a labor flexibility paradigm in terms of economic aspects of production technology and complex job performance needs and social environment changes in job design due to changes in worker needs (Lee et al., 2013). As the demand and supply system of the labor force changes, it is moving from supplier-centered to consumer-centered. Due to the flexibility strategy, the working environment is changing quantitatively and qualitatively (Hinrichs & Jessoula, 2012; Wonyongjae & Takjinguk, 2017).

Organizations can choose outsourcing, layoffs, and honorary retirement as management strategies along with legal deregulation for quantitative reduction. This situation led to a change in the perception of the employment environment for both managers and employees (Kim, 2013). It is useful to increase the flexibility of manpower management, but it increases job instability to employees and experiences lethargic and depressed emotions. This negatively affects job burnout, job stress, turnover intention, etc. (Kim & Lee, 2019). Layoffs are the termination of employment relations as a group in terms of promoting quantitative flexibility in employment. Amid the risk of market instability and economic crisis, it is the most common way for companies to improve profitability and reconsider management efficiency (Lee et al., 2001).

Layoffs can affect employees under the stress of job insecurity, but in the capitalist economic environment, they can also be a management method for corporate survival strategies (Park, 2017; Jeon et al., 2012). The increase in uncertainty about the organization caused by the reduction and change of the organization due to the increase in layoffs causes employees to experience changes in their roles and organizational changes. This directly or indirectly affects the attitudes and behaviors of employees, so it becomes a factor that increases job stress (Vakola & Nikolaus, 2005; Won & Tak, 2017; Lee et al., 2013).

2.2. Job Stress of Beauty Industry Employees

Job stress is defined as the interaction between job performers and job-related factors that make it difficult to perform normal jobs or change psychological and physical conditions due to factors related to an individual's job (Behr & Newman, 1978; Hunter & Thatcher, 2007; Na & Choi, 2018). Job stress is the stress that occurs in all processes perceived by members performing their duties (Hunter & Thatcher, 2007). The more complicated the job environment and job content become, the more serious the problem becomes. Pressure felt by members due to dangerous work conditions and environments experienced in the course of job performance, difficult jobs, heavy work, interpersonal conflicts, job instability, irrational/authoritative organizational culture, irrational compensation, conflicts, and disharmony between job areas, etc., can be expressed as a trigger for discomfort, conflict, and tension (Kim. 2010; Kim. 2020).

Stress was used by Walter Cannon in the 1920s and was thought to be a disorder of homeostasis (Jeon, 1993). Stress was defined as a specific relationship between the individual and the environment that threatens the stability of the individual beyond the resources of the employee (Lazarus & Folkman, 1984). It is said that it is an adaptation process to external situations when faced with inhibitions and opportunities related to the results that are perceived to be both uncertain and important (Robins et al., 1994). Stress can be divided into two categories: negative stress, which indicates an individual's discomfort and harmful condition, and stress, which helps and positively affects an individual's growth (Lee, 2014).

Job stressors are caused in various ways depending on the job type or job environment. It plays various roles according to individual and situational conditions, and the results of job stress vary (Beehr & Newman, 1978; Parker & DeCotis, 1983). Job stress is said to be a negative influence on the mental or physical body that an individual feels from the outside (Ahn, 2003). It is said that it is a negative emotional state caused by inconsistency between an individual's work ability and job needs (Oh, 2017). Due to the prolonged global pandemic situation and domestic and foreign economic crises, large-scale restructuring, layoffs, employment instability, and labor flexibility, the resulting increase in job stress and negative problems are intensifying (Kim, 2021).

Stress, if accumulated and sustained over a long period of time, not only negatively affects an individual's mental and physical health, but also negatively affects work and organizational performance (Law & Song, 2004). Several studies on job stress in service-related industries have shown that job stress has a negative effect on variables such as burnout, job satisfaction, and turnover intention (Kwak et al., 2010; Lee & Lim, 2017; Ashforth & Humphery, 1993; Bakker & Demerouti, 2007). The beauty service industry, which focuses on hospitality services, is a job with high work stress for employees. Research on job stress affecting service quality and job performance will be important in that it seeks efficient ways to reduce job stress and job burnout in terms of improving organizational productivity (Park et al., 2018).

2.3. Turnover Intention of Employees in the Beauty Service Industry

Turnover refers to the disconnection of the employment relationship between the organization and employees and is the act of members leaving the organization and leaving the outside. In other words, it means terminating the relationship with the organization by leaving the organization where you worked, not a temporary absence or departure (Mobley, 1982). Turnover refers to a somewhat coercive disconnection due to organizational manpower adjustment, or a state in which employees terminate their employment contracts on their own (Kim & Hong, 2019; Zopiatis et al., 2014).

Turnover intention is an individual's psychological state that affects from thoughts about turnaround to turnaround (Iverson, 1999; Shin et al., 2010; Price & Mueller, 1981). Turnover intention generally means judging by considering the idea of moving a company based on one's voluntary will and psychological response in certain situations, the willingness to change jobs, and the possibility of leaving the organization at a certain point in the future (Kwon & Park, 2015). Turnover intention does not represent the result of the behavior of turnover but refers to a psychological state that may appear as a turnover behavior in the future. Therefore, turnover intention can be understood as an individual's level of will regarding turnover. In terms of the loss of existing skilled labor, turnover can lead to productivity degradation, such as lower corporate skills and quality, higher personnel management costs, and further damage problems such as information leakage (Lee & Shin, 2012; Lee & Kim, 2012). Employee turnover may create an atmosphere of turnover for other workers in the organization. It can also be a factor that has a negative effect on turnover, such as efforts to explore new organizations and inducing stress. (Dalton et al.,1980; Mor Barak et al., 2001).

In terms of job security, minimizing the turnover rate can be a strategy for efficient management of a company. In addition, it is necessary to identify the causes of turnover such as working environment, working hours, annual salary, welfare environment, etc. The organization should establish alternatives and strategies to reduce the turnover rate and maximize personnel management efficiency to implement stable manpower management and management. (Porter et al., 1974; Price & Mueller, 1986; Park & Kim, 2017).

3. Research Methods and Materials

3.1. Research Models and Hypotheses

Based on the results of previous studies, this research hypothesis was reflected in the research model by analyzing the causal relationship related to job stress due to changes in the employment environment. Figure 1 shows the research model of this study.

Figure 1: Research Model

3.2. Composition of Measurement Tools

The questionnaire used as a measurement tool of this study consisted of 44 questions including demographic characteristics, changes in the employment environment, job stress, turnover intention, and work experience. The detailed configuration is as follows. Changes in organizational structure, increase of non-regular workers, and generalization of layoffs, which are factors of employment environment change, are 15 questions in total, and 5 questions in workload, tension in work, work stress, processing time unfinished, work situational pressure. Turnover intention consisted of 10 questions. Demographic characteristics (gender, age, educational background, marriage, income) consisted of 5 questions, and working characteristics consisted of 9 questions.

3.3. Data Collection and Analysis

Data collection and analysis of this study was carried out in accordance with the following procedure. In this study, to collect the most reliable data, a self-written survey was conducted on beauty workers in the Seoul metropolitan area of Korea from August 15 to September 10, 2022, carefully considering the setting of each research topic. A total of 600 questionnaires were distributed and 556 copies were collected, and 518 copies were used as final analysis data, excluding 38 copies with unfaithful responses. The statistical processing of the data collected by the data analysis method was analyzed using the Statistical Package for Social Science (SPSS) WIN23.0 statistical package program through data coding and data cleanup.

First, frequency analysis was performed to identify the general characteristics of the sample. Second, to analyze the validity and reliability of the measurement tool, the validity of the factors composed for each variable was verified. To understand the structure of factors, we performed exploratory factor analysis, one of the multivariate statistical techniques, followed by reliability analysis.

In addition, feasibility indicators were confirmed through exploratory factor analysis. As an analysis method to simplify the contents, numerous variables were grouped with highly correlated variables to see if variables measuring the same concept were grouped into the same factor. In particular, the number of factors was reduced, and information loss was minimized through the Principal Components Analysis method. Factor rotation was used to secure mutual independence among factors. The Varimax method, which is a right-angle rotation method that maintains the angle between the axes of each factor at 90°, was used.

Through reliability analysis, it was verified whether the concept to be measured for measurement items classified by factors was consistently and accurately measured through the response of the survey respondents. The internal consistency of measurement items through Cronbach's Alpha was investigated. In this study, it was verified under the significance levels p<0.05, p<0.01, and p<0.001.

4. Results and Discussion

4.1. Demographic characteristics of the sample

Considering the convenience and effectiveness of this study, an empirical survey was conducted focusing on Seoul and Gyeonggi-do, which are close to the metropolitan area. The survey was conducted focusing on beauty industry workers.

The results of frequency analysis conducted to find out the demographic characteristics of the survey subjects in this study are as follows shown as a Table 1.

Table 1: Characteristics of Population Statistics (N=518)

* p<0.05 ** p<0.01 *** p<0.001

As for the size of the shop, 299 people (57.8%) in private shops 20-30, 112 people (21.7%) in private shops 10-20, 55 people (10.6%) 20-30 franchises, 51 people (9.9%) 30-40 franchises. The number of employees was 259 (50.1%) of 5 or less, 149 (28.8%) of 6 to 10 or less, 69 (13.3%) of 11 to 15 or less, and 40 (7.7%) of 16 or more. As for shop locations, 261 people (50.5%) in apartment complexes and residential areas, 162 people (31.3%) in downtown areas, 79 other people (15.3%), and 15 people (2.9%) in shopping malls and department stores.

The working period was 191 (36.9%) for less than 1 year, 140 (27.0%) for less than 1 to 5 years, 85 (16.4%) for less than 5 to 10 years, 69 (13.3%) for more than 15 years, and 33 (6.4%) for less than 10 to 15 years. The positions were 201 directors (38.8%), 127 designers (24.5%), 90 managers (17.4%), 69 beginners (13.3%) and 31 interns (6.0%). Working hours were 254 (49.0%) under 8-10 hours, 189 (36.5%) under 8 hours, 48 (9.3%) under 10-12 hours, and 27 (5.2%) over 12 hours.

The number of holidays was 202 (39.0%) more than 8 times, 160 (30.9%) less than 4 times, 96 (18.5%) five times, 35 (6.8%) six times, and 25 (4.8%) seven times. The salaries were 208 (40.2%) directors, 139 (26.8%) 100% incentives, 76 (14.7%) monthly salaries, 69 (13.3%) basic salaries + incentives, and 26 (5.0%) hourly wages. In the field of work, 307 people (59.3%), 127 people (24.5%), 45 people (8.7%) for perfume, 31 people (6.0%) for nails, and 8 people (1.5%) for makeup were found. The gender was 461 women (89.0%) and 57 men (11.0%). The age was 192 (37.1%) under the age of 40 to 50, 117 (22.6%) under the age of 20 to 30, 111 (21.4%) over the age of 50, 93 (18.0%) under the age of 30 to 40, and 5 (1.0%) under the age of 19. The academic background was 188 high school graduates (36.3%), 140 college graduates (27.0%), 105 college graduates (20.3%), and 85 graduate students (16.4%) or higher. There were 259 married (50.0%), 234 unmarried (45.2%), and 25 others (divorce, separation, and separation) (4.8%). Monthly income was 178 people (34.4%) under 3~4 million won, 172 people (33.2%) under 2~3 million won, 100 people (19.3%) over 4 million won, 61 people (11.8%) under 1~2 million won, and 7 people (1.4%) under 1 million won shown as a Table 1.

4.2. Reliability and Feasibility Analysis

4.2.1. Reliability of Change in Employment Environment, Job Stress, and Turnover Intention

Before evaluating the measurement model, reliability was verified by calculating the reliability coefficient (Cronbach's α) to verify the internal consistency of each research concept. Factor analysis results using Varimax rotation Items with low reliability were excluded from the analysis. As a method of measuring internal consistency, we intend to use the Cronbach's alpha (C⍺) coefficient. The Cronbach's alpha (C⍺) coefficient is generally 0.7 or more to ensure that the measured value is reliable. As a result of reliability analysis for the measurement items, the Cronbach's α coefficient for organizational change was 0.901, the Cronbach's α coefficient for the increase in non-regular workers was 0.850, the Cronbach's α coefficient for general layoffs was 0.859, the Cronbach's α coefficient for job stress was 0.877, and the Cronbach's α coefficient for turnover intention. was 0.956, which was found to be higher than the general standard of 0.6. Therefore, the reliability, which is the internal consistency of the overall response, was found to be at an appropriate level shown as a Table 2.

Table2: Reliability of Employment Environment Changes, Job stress, and Turnover Intention

* p<0.05 ** p<0.01 *** p<0.001

4.3. Factor Analysis: Rotated Component Matrix (KMO and Barrett)

4.3.1. Factor Analysis Results for Changes in the Employment Environment for Independent Variables

This is the result of factor analysis on the change in the employment environment of the empirical independent variable. It is shown in Table 3 A total of five factors were derived, and the total cumulative explanatory power was about 70.185%. The KMO was 0.906 and the Bartlett test was ²=13613698.508, which was identified as a significant model (p<0.05). Factor 1 was found to be an eigenvalue of 6.750, and the explanatory power was found to be 22.499%. Factor 2 was found to be an eigenvalue of 4.089, and the explanatory power was found to be 13.629%. Factor 3 was found to be an eigenvalue of 3.604, and the explanatory power was found to be 12.014%. Factor 4 was found to be an eigenvalue of 3.362, and the explanatory power was found to be 11.207%. Factor 5 was found to be an eigenvalue of 3.251, and the explanatory power was found to be 10.835% shown as a Table 3.

Table 3: Factor Analysis on Changes in the Employment Environment for Independent Variables

* p<0.05 ** p<0.01 *** p<0.001

4.3.2. Correlation Analysis of Change in Employment Environment, Job Stress, and Turnover Intention

As a result of correlation analysis, it was found that there was a significant correlation between all variables (p<0.05). In addition, the correlation between the independent variables is all significant, but the maximum correlation coefficient is 0.540, indicating that the level of multicollinearity that may appear in the regression analysis process is lower than 0.85. It is judged that such a problem will not occur shown as in Table 4.

Table 4: Correlation Analysis of Change in Employment Environment, Job Stress, and Turnover Intention

* p<0.05 ** p<0.01 *** p<0.001

4.4. Validation Of Research Hypotheses

4.4.1. Linear Regression Analysis on Changes in the Employment Environment and Job Stress

The degree to which the independent variable explained the dependent variable, 'job stress', was approximately 38.0% (R²= 0.380), and this regression model was found to be statistically significant (F=104.993, p<0.05). As a result of identifying variables in which independent variables have a significant effect on dependent variables, organizational structure change, increase in non-regular workers, and universal layoffs were found to have significant effects at the significance level of 0.05 (p<0.05). Changes in organizational structure, increase in non-regular workers, and generalization of layoffs have a positive (+) effect on the dependent variable, 'job stress'. As a result of identifying the size of the influence among the variables that affect the dependent variable, organizational structure change (t=12.344)> non-regular employment increase (t=5.931)> layoffs (t=3.639) in the order of generalization. In addition, as a result of identifying the problem of multicollinearity between independent variables, the VIF value was 1.117 to 1.236, which was less than 10, so it was judged not to be a big problem shown as a Table 5.

Table 5: Linear Regression Analysis on Changes in Employment Environment and Job Stress

* p<0.05 ** p<0.01 *** p<0.001

4.4.2. Linear Regression Analysis on Changes in Employment Environment and Turnover Intention

The degree to which the independent variable explains the dependent variable "transfer intention" was found to be about 35.4% (R==0.354), and this regression model was found to be statistically significant (F9393.724, p<0.05). As a result of identifying the variables that the independent variable significantly affects the dependent variable, it was found that organizational structure change, non-regular workers increase, and layoff universalization had a significant effect at the significance level of 0.05 (p<0.05). Changes in organizational structure, increase in non-regular workers, and generalization of layoffs have a positive (+) effect on turnover intention, a dependent variable. As a result of identifying the size of the influence among the variables that affect the dependent variable, it was identified in the order of organizational structure change (t=9.061) > increase in non-regular workers (t=7.872) > generalization of layoffs (t=4.342). In addition, as a result of identifying the problem of multicollinearity between independent variables, the VIF value was 1.117 to 1.236, which was less than 10, so it was judged not to be a big problem shown as a Table 6.

Table 6: Linear Regression Analysis on Changes in Employment Environment and Turnover Intention

* p<0.05 ** p<0.01 *** p<0.001

4.4.3. Mediating Effect of Job Stress on Changes in the Employment Environment and Turnover Intention

As a result of regression analysis of the first-stage independent variable for the parameter, the explanatory power was 21.0%, and this regression model was found to be statistically significant (F=137.078, p<0.05). Changes in the employment environment, an independent variable, were found to have a significant positive (+) effect on job stress, which is a parameter (t=11.708, p<0.05). As a result of regression analysis of the two-stage independent variable for the dependent variable, the explanatory power was 24.9%, and this regression model was found to be statistically significant (F=170.899, p<0.05). It was found that the change in the employment environment, an independent variable, had a significant positive (+) effect on turnover intention, a dependent variable (t=13.073, p<0.05). As a result of regression analysis of the three-step independent variable and parameter for the dependent variable, the explanatory power was 25.5%, and this regression model was found to be statistically significant (F=88.349, p<0.05). The independent variable was found to have a significant positive (+) effect (t=10.678, p<0.05), and the parameter showed a significant positive (+) effect (t=2.146, p<0.05). In step 3, it was found that both the independent variable and the parameter had a significant effect on the dependent variable, and the parameter (β = 0.092) was less significant than the independent variable (β = 0.457), indicating that there was no mediating effect shown as a Table 7.

Table 7: The Mediating Effect of Job Stress on Employment Environment Change and Turnover Intention

* p<0.05 ** p<0.01 *** p<0.001

This is the result of performing the Sobel test to understand the size of the indirect effect and the flexibility of the effect. The effect size of the independent variable on the dependent variable through the parameter was 0.057, and it was found to be statistically significant (t-value=2.111, p<0.05) shown as a Table 8.

Table 8: The Mediating Effect of Job Stress on Employment Environment Change and Turnover Intention

* p<0.05 ** p<0.01 *** p<0.001

4.4.4. Working Experience Moderating Effects of Job Stress and Turnover Intention

The degree to which the first-stage independent variable explained the turnover intention, which is a dependent variable, was about 9.1%, and this regression model was statistically significant (F=51.424, p<0.05). As a result of introducing the adjustment variable 'working period' in step 2, the explanatory power increased by about 46.7%, and this increase in explanatory power was statistically significant (F=544.096, p<0.05). The working period was found to have a significant negative (-) effect on turnover intention (t=-23.326, p<0.05), and the conditional effect of the modulating variable was found to be significant. Finally, as a result of introducing the interaction variable between the independent variable and the control variable in step 3, the explanatory power increased by about 1.7%, and this increase in explanatory power was statistically significant (F=19.931, p<0.05). In addition, the interaction effect was found to be significant because the interaction variable had a significant positive (+) effect. Therefore, in the effect of job stress, an independent variable, on turnover intention, a dependent variable, the moderating effect of the working period, which is a moderating variable, was found to be significant ) shown as a Table 9.

Table 9: The Effect of Work Experience on Job Stress and Turnover Intention

* p<0.05 ** p<0.01 *** p<0.001

4.5. Study Hypothesis Test Results and Discussion

This study analyzed the structural relationship between employment change, job stress, and turnover intention in depth and empirically. The findings provided evidence for the proposed hypothesis, but some were not supported. The study obtained the following results. First, because of analyzing the structural model, it was found that the change in the employment environment had a positive (+) effect on job stress. Changes in organizational structure, increase in non-regular workers, and generalization of layoffs have a positive (+) effect on the dependent variable, 'job stress'. The results showed that changes in the employment environment are factors that increase job stress. Second, it was found that changes in the employment environment had a positive (+) effect on turnover intention. Changes in organizational structure, increase in non-regular workers, and generalization of layoffs have a positive (+) effect on the dependent variable, 'turnover intention'. Research supports that higher job stress increases employee turnover intention. Third, independent variables were shown to have a significant positive (+) effect (t=10.678, p<0.05), The parameters showed a significant positive (+) effect (t=2.146, p<0.05).

It was found that job stress had a mediating effect on changes in the employment environment and turnover intention. Fourth, work experience was found to have a significant negative (-) effect on turnover intention (t=-23.326, p<0.05), and the conditional effect of the moderating variable was found to be significant. interaction variables had a significant positive (+) effect, so the interaction effect was found to be significant. Therefore, the moderating effect of the working period, the moderating variable, was found to be significant in the effect of the independent variable, job stress, on the dependent variable, turnover intention. Based on these results, the relationship between the variables proposed in this paper forms job stress and turnover intention, ultimately leading to high performance. This study empirically verified the effect of job stress on turnover intention due to changes in the employment environment of organizational members.

5. Conclusions

Due to the acceleration of technology and market competition developing in the era of the fourth industry, the business environment of companies has reconsidered the flexibility of labor to secure continuous management and competitiveness. (Askenazy & Galbis, 2007; Lee et al., 2012). The development of digital technology is an important issue that has a significant impact on the labor market and jobs. Factors that change the employment environment can be examined in terms of knowledge information and the advancement of digital technology due to the development of technology. These changes led to the arrival of a multi-functional job society with the characteristics of work as intellectual labor (Atchison, 1991).

The beauty service industry is competitive as a labor-intensive industry that is highly dependent on human resources and simultaneity of production and consumption. (Chae, 2019). In numerous previous studies on human management, securing excellent human resources is closely related to the improvement of management performance. (Wright et al., 2013). In accordance with the rapidly changing environment of the beauty industry, the consciousness structure and way of thinking of organization members are also diversifying. There is a limit to increasing the loyalty of members only with generalized logic. (Kim & Kim, 2021).

As a result of verifying the relationship between job stress and turnover intention of beauty industry employees, it was found that the path from job stress, a parameter, to members' turnover intention, had a significant effect. These analysis results showed that high job stress increases the intention to change jobs to other jobs. In the event of a turnover, replacement personnel are needed. As a result, costs such as training and adaptation time are incurred until replacement personnel are supported, which acts as a negative factor among employees. To solve this problem, it was found that systematic human resource management is needed for periodic job management, training management, promotion, and compensation.

The implications of this study are as follows. Identify the characteristics of beauty industry workers with high turnover rates and identify the relationship between job stress and turnover intention with the support of companies and organizations. Identifying the perception of changes in the employment environment of beauty industry employees as a cause of job stress, a variable of job demands, can be found in the study in that individual behavior and psychological attitude toward jobs directly affect turnover intention (Yoon et al., 2019; Kim & Shin, 2018). Beauty industry workers are exposed to an environment that is prone to emotional exhaustion due to job stress in that they respond to customer contact services. Companies' efforts to control and manage them affect management performance such as human resource management (HRM) and improvement of turnover (Kim, 2019; Kang, 2023). Despite the above implications, it has several limitations, so I would like to propose a research direction for follow-up research as follows.

This study investigated employees' perception of changes in the employment environment of the beauty industry in the COVID-19 situation, which is a period from August 15 to September 10, 2022. As a result, it is not clear whether the trend of change in the employment environment in the domestic beauty industry and social environmental factors have had a specific effect on the employment environment. Therefore, in-depth research needs to be conducted based on specific social environmental factors for future research.

Second, it is a limitation about investigation. The subjects of the study were limited to Seoul and parts of Gyeonggi-do. There is a limit to generalizing to the entire beauty industry in Korea. In future studies, it is believed that the limitations can be overcome if the target selection and investigation are conducted by expanding the domestic distribution area further.