Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 9, No. 1, 2023 229 The Mediator Role of Job Satisfaction (JS) Among the Relationship Between Electronic Human Resource Management (E ‐ HRM), Employee Performance (EP), and Organizational Commitment (OC)in Family‐Owned Small Middle Enterprises (SMEs)in China Yong See Chen, Chao Liu*, Lou Song Graduate School of Business (GSB), SEGi University, Malaysia * Corresponding author: Chao Liu (Email: 525473574@qq.com) Abstract: Purpose – This study explores the relationship between IVs [Electronic Human Resource Management (E - HRM) and Employee Performance (EP)], MV: Job Satisfaction (JS) and Organizational Commitment (OC) is the focus in the context among Small and Medium-sized (SEMs)Family Enterprises in China. Design/methodology/approach – 150 samples can be collected from Small and Medium-sized (SEMs) Family Enterprises in China by utilizing the convenience sampling method. And analyzing method in this study, the quantitative method can be selected by adopting IBMSPASS and PLS-SEM. Findings – Both E-HRM (β=0.380, p<0.01) and EP (β=0.545, p<0.01) have a significant positive impact on Job Satisfaction (JS). Job Satisfaction (JS) is an important factor affecting Organizational Commitment (OC). Job Satisfaction (JS) was included in the proposed model as an intermediary variable. Research limitations/implications – the moderating role of JS in the relationship between IVs (E - HRM, EP) and OC was studied using quantitative methods. The research background and research data are limited to small and medium-sized family enterprises and employees in China. Originality/value – By studying the relationship between IVs (E - HRM and EP), MV (JS), and OC, this paper will help to better understand how different E - HRM and EP affect JS, and how JS affects employees For corporate OC's. With the increasing market competition and rising labor costs in China, improving employees' OC for enterprises may be an important means to cope with future competition. Keywords: Electronic Human Resource Management, Employee Performance, Job satisfaction, Organizational commitment. 1. Introduction In response to the declining economy and fierce market competition after COVID-19, a large number of Chinese family businesses have focused their business development strategies on the market and customers (Zhang, Williams, Li, & Liu, 2022). However, the market for small and medium- sized family enterprises in China cannot be obtained solely by focusing on the strategic positioning of the enterprise. Small and medium-sized family businesses that want to achieve sustainable development often need to focus on the management and development of internal employees in order to contribute to the innovation and development of the company (Phonthanukitithaworn, Srisathan, Ketkaew, & Naruetharadhol, 2023). This means that the value and creative ability of the market and customers can only be obtained by stimulating and relying on the autonomous participation of employees within the enterprise (Su, Sun, & Zhao, 2022). However, there are very few small and medium-sized family enterprises with such capabilities in China (Hooi, 2022). Many private family entrepreneurs believe that the market value of Chinese companies and the opportunities and development of the market are the most important things rather than the company's customers and market creativity (Kogut & Mejri, 2022). This means that human resources within the company are not regarded as a kind of Utilization and beneficial value, but a cost and burden. This view is rooted in the management strategies of a large number of small and medium-sized family enterprises in China (Vahdat, 2022). Most of the small and medium-sized family enterprises in China are influenced by the traditional family concept of the Chinese, and they often establish family enterprises with family members as the core (Huang & Ichikohji, 2022). Opportunities for business development. Non-family employees are also dissatisfied because of the differentiation from family employees, and ultimately cannot serve the company wholeheartedly, which will make employees' organizational commitment to the company or the company's organizational commitment to employees very low(Febrianti & Jufri, 2022). A large number of non-family core employees leave because they cannot enjoy the same fair and open working environment as family core members and cannot establish a benign psychological contract with the company. Make it impossible for the enterprise to develop better (Phonthanukitithaworn et al., 2023). Small and medium-sized family businesses often hope that the introduction of digital information can make the internal process of the enterprise open and fair, but the introduction process of Electronic Human Resource Management Use (E- HRM) is too complicated, the operation of the process is complicated, and the linkage with the internal data of the enterprise is poor, resulting in employees (Li, Wei, & Guo, 2022). Dissatisfied with using such a system and not being able to effectively reduce the workload. At the same time, due to the long-term accumulation of dissatisfaction, employees will inevitably leave the company without a good organizational commitment. It makes the enterprise have problems in the value development of employees (Li et al., 230 2022). Because the employees of small and medium-sized family enterprises often cannot get the same attention as the employees of family enterprises, employees will also show a kind of aimless work behavior, which will cause the Employee Performance(EP) to fail to create more value for the enterprise, so that the enterprise organizational commitment to employees will be negatively affected, and eventually no healthy organizational commitment can be produced with employees (Yuan, Chen, Yang, Chow, & Hsu, 2022). Similarly, non-family employees are dissatisfied and unwilling to contribute their core competencies due to the fact that family enterprises are divided into family core enterprises and non-family employees in the organization (Pimentel & Pereira, 2022). In the end, the performance of employees cannot meet the requirements of the enterprise, resulting in the enterprise's dissatisfaction with employees. Organizational commitment cannot be maintained in the long term (Vuong, Tushar, & Hossain, 2022). Due to the wide scope of research on human resources, this paper will conduct research on the organizational commitment of non-family employees in family enterprises. Through the research and introduction of Electronic Human Resource Management use (E-HRM), Employee Performance (EP) is used as an independent variable and employee Job Satisfaction (JS) is used as an intermediary variable. The model that ultimately affects corporate Organizational Commitment (OC) as a dependable variable conducts data collection and research on Chinese family SMEs, and makes theoretical and practical suggestions for how Chinese family SMEs can improve corporate organizational commitment and thus improve the efficiency of human resource management in Chinese family enterprises. 2. Literature Review and Hypothesis Development In this section, the related variables by conducting in previous studies can be described, including two independent variables Employee Performance (EP) and (Electronica Human Resource Management use) E - HRM use, mediator variable as Job Satisfaction (JS) and Organizational Commitment (OC) as dependable variable. Mover, the relationship between each variables described and tested in previous studies can be discussed and described in this section. Finally, by the relationship between each variables re- organize a model to test and discuss organizational commitment in family-owned SMEs in China. 2.1. The relationship between E - HRM use and Job satisfaction (JS) Marler and Parry (2016) stated that e - HRM use can be viewed as electronic resources by utilization of platform in a set of configurations of computer hardware and software for performing Human Resource Management (HRM) policies, practices and services in more effectiveness. Such better consequences by creating information and communicating with each other’s within organizational boundaries and by capturing data among the level of individual and group through the traditional way in management of coordinating and controlling. Moreover, as Bondarouk, Parry, and Furtmueller (2017) pointed out in terms of the improvement on organizational effectiveness, the organizations or companies could introduce and adopt advanced and appropriate Information Technology (IT) for performing best practices, polices and services in HRM. Many studies in terms of the content of the effect of e-HRM use on job satisfaction explain that job satisfaction within the organizations or companies can be transformed by e-HRM use. In this case, the problem in term of job satisfaction affected by the effect of e-HRM use can be explained by introduced the Job Characteristics Model(JCM). Hackman and Oldham (1975) indicated that improved intrinsic motivation can be carried out by employees during facing a task that is important, identifiable, autonomous, diversity of possessed skill and providing feedback. Most jobs from any particular field with potential motivation are able to be contributed by the five job characteristics. Three psychological states can be explained and concluded by these job characteristics regard individual employees, including work with meaningfulness, work performance with responsibility and knowledge in the reflection of actual performance of work activities. Internal work with high level motivation and high satisfaction in generally can be viewed as positive outcomes individually which can be generated or produced by these three critical psychological states and other factors such as knowledge and skill, growth by the demand in strength, and contest satisfaction all can moderate such three critical psychological states. Piñero et al. (2016) indicated that the positive effect of job satisfaction on the other can be enhanced by information technology use and the positive effect of job characteristics which include diversity skills, autonomy and feedback also can be forced by information technology use. Piñero et al. (2016) considered two hypothesis views or points related to effect that individual employees can be impacted by information technology. Initially, technology with automatic function can be existed and performed. Enriching elements among jobs are able to be stripped off by use of the automatic technology. In this case, employees’ motivation within organizations or companies can be reduced by employee dissatisfaction and alienation developed by deskilling jobs in such automatic technology. Additionally, information technology that enriches jobs by releasing people from jobs with dull and dry as well as eliminating monotony is able to be advanced and implemented within organizations or companies, by which job satisfaction in the organizations or companies can be perfected or improved by eliminating repetitive tasks or missions from dull and dry work in the utilization of such information technology. Job satisfaction levels within organizations or companies can be impacted to produce with negative consequences, although implementing e-HRM enable organizations or companies to improve cost effectiveness for administrative processes by the reduction of costs and automation. Meanwhile, job satisfaction will be impacted by the level in difficulty of implementing e - HRM applications, which means the more difficult in the implementation e - HRM, the lower job satisfaction within organizations or companies. Maret et al. (2007) and Sykes, Venkatesh, and Johnson (2014) indicated that job satisfaction levels can be dropped by the consequence that decreasing motivation from the challenge of obtaining information technology abilities as viewed a difficulty by sense of employees. Work habits among employees also can be impacted by implementing electronic HRM applications so that job satisfaction within organizations or companies either dropping or improving. 231 Maret et al. (2007) and Sykes et al. (2014) articulated that the problem that decreasing job satisfaction within organizations or companies can be produced by an increasing number of works with additional stress caused from obtaining new routines and practices. Thus, this study provides a hypothesis question as below: Ha1: E - HRM use effect on Job Satisfaction (JS) positively. 2.2. The relationship between Employee Performance (EP) and Job Satisfaction (JS) As Latifah, Suhendra, and Mufidah (2023) integrate past studies regard the relationship between Employee Performance (EP) and Job Satisfaction (JS), the relationship between Employee Performance (EP) and Job Satisfaction (JS) can be revealed by James A Roberts and Meredith E David (2020) to indicated that performance within organizations or companies can be impacted by Job Satisfaction(JS) significantly and trusts from top management can impact on Job Satisfaction(JS) directly. Meanwhile, satisfied salary, opportunities of career promotion even environments with conducive work elements can be more benefit or impact on Job Satisfaction (JS) strongly, so that performance can be influenced by Job Satisfaction (JS) positively (Sembiring & Meo, 2020). However, Shahzad et al. (2018) indicated that performance also can be set with in negative consequence from Job Satisfaction(JS) by introducing and utilizing the Minnesota satisfaction questionnaire form Weiss (1967). James A. Roberts and Meredith E. David (2020) in the study indicated that there has been a proposed sequential model in mediating effect between Job Satisfaction (JS) and job performance. Attitudes can be viewed more important and preceded than behaviors in marketing, which can be held as axiom universally. Ajzen and Fishbein (1975) indicated that behavior can be viewed as a function of behavioral intentions and behavior also can be viewed as a function of attitude a subjective norm, which can be explained from the Theory of Reasoned Action. If an attitude object can be predisposed toward by people with a favorable sense, the predispositions that consistent with behaviors can be performed or engaged by the intention of people. As above points of the relationship between Job Satisfaction(JS) and performance can be mentioned and analyzed, higher levels of performance can be associated with Job Satisfaction(JS) positively within organizations or companies. Judge, Thoresen, Bono, and Patton (2001) articulated that the 0.3 of correlation can explain the relationship between Job Satisfaction (JS) and job performance by 54, 471 of sample size in 301 studies with a large -scale meta -analysis. At the same time, James A Roberts and Meredith E David (2020) indicated that job performance and better development in work effort can be caused by satisfaction from employees’ top management who provide their employees with more trusts. Additionally, the conclusion of the relationship between Job Satisfaction(JS) and job performance from past studies such as Bouckenooghe, Raja, and Butt (2013) indicate that the function of Job Satisfaction can facilitate job performance within organizations or companies. By conclusion with all above studies, the hypothesis question on the relationship between Job Satisfaction (JS) and performance can be provided below: Ha2: Employee Performance (EP) effect on Job Satisfaction (JS) positively. 2.3. The relationship between Job Satisfaction (JS) and Organizational Commitment (OC) Zhao et al. (2020) indicated that organizational commitment is a relationship between employees and organizations or companies, and such relationship, called organizational commitment can be influenced by the performance of employees behavior tightly. Jaros (2007) points out that the most prevalent definition of commitment found in HRM research is an attachment to or identification with the organizations. Hanaysha (2016) in the relationship between the attachment and employee behavior and performance indicate there can be a stronger relationship among attachment, employee behavior and performance, in other word, employee behavior and performance can be impacted or correlated with substantial effect by such an attachment. In this case, organizational commitment can be concluded that the organizations or companies have to be stayed with employees, which can be viewed as a sentiment by articulated from Meyer, Allen, and Gellatly (1990). Moreover, organizational commitment can explain that the level of that employees identifying with and involving in a particular organization or company(Gill-Simmen, MacInnis, Eisingerich, & Whan Park, 2018). Organizational commitment can be described that employees’ values should be consistence with the goal of organizations or companies, and they are prefer to perform missions or tasks within organizations or companies as well as the representing of organizations or companies by the employees can make their efforts as a demonstration(Meyer, Stanley, Herscovitch, & Topolnytsky, 2002). Khajuria and Khan (2022) states that learning and success within organizations or companies can be improved because organizational commitment can be impacted to be boosted. Culpepper (2000) indicated that organizational commitment can be usually performed for doing research by the utilization of Meyer and Allen’s (1991) three - component model, which can be characterized in the model of affective commitment, the model of continuance commitment, the model of normative commitment. Organizations or companies can be attached by employee’s emotion, this can be viewed as a perception of affiliation that can be described by the model of affective commitment to the organizations or companies from Meyer and Allen’s (1991) three - component model. Affective commitment with higher level can enhance employees to be prefer to stay with their organizations or companies over long period, and they are desire to enjoy their career for their employer’s long time. Continuance commitment can be interpreted that organizations or companies can enable their employees to be kept in the continuance of doing their jobs in the organizations or companies but not leave because dismission among employees in the organizations or companies need to be focused on higher costs for doing so. Pahos and Galanaki (2019) indicated that continuance commitment with higher level that employees can show is tend to enhance employees to stay long time but not leave due to the expensive cost that employees cannot afford in quitting the organizations or companies. Mercurio (2015) provided normative commitment with the 232 definition, which can be interpret that the organizations or companies can be stayed or remained with employees with obligation. Meanwhile, Khajuria and Khan (2022) indicated that the greater normative commitment can enhance employees’ cognition in a duty or responsibility in performing or doing job for their employer. In this case, the explanation in the reason why organizational commitment can be supported and in favor by managers based on the several reasons from previous Human Resource Management literature. Mercurio (2015) indicated that organizational commitment can impact on staff with high productivity, and the organizational commitment also can influence on the risk that undesired employee turnover can be occurred. Pahos and Galanaki (2019) also points out that better performance in organizational commitment should be acquired due to the consequence of organizational commitment can bring many benefits to organizations or companies, such as lower worker churn and higher-level workforce stability. Lamba and Choudhary (2013) states that organizations or companies have to make employees to be felt satisfied in emotional and physical way, which can enhance the employees with the better emotion and physic to be translated to be a devoted employee, and the devoted employee can be a foundation of an environment with positive attitude in working for disseminating the devotion that a devoted employee produces to organizations or companies for the colleagues. Markovits, Davis, Fay, and Dick (2010) stated that many results in the relationship between Job Satisfaction (JS) and organizational commitment from previous studies can be identified and performed as positive effect. Because organizational commitment can explain or be involve in a attitude that employees are favorable to be faced to organizations or companies but not to their own job or work, Job Satisfaction (JS) can be viewed as an extension of organizational commitment. According to a meta-analysis of 7.218 research papers conducted by Durukan et al. (2022), there is statistically significant correlation between the total effect size of job satisfaction and organization commitment. The ability of job satisfaction to positively influence organization commitment is greater. It's important to understand how the broad adoption of remote e-working in COVID-19 and the rise of hybrid work arrangements in corporations may affect the relationship between job satisfaction and organizational commitment. Thus, we put forth the following theories: Ha3: Job Satisfaction (JS) effect on Organizational Commitment (OC) positively 2.4. The mediation effect of Job Satisfaction among the relationship between IVs (employee performance, E - HRM use) and Organizational Commitment (OC) Previous studies, such as Maret et al. (2007) and Sykes et al. (2014) on the relationship between E - HRM and Job satisfaction all indicated that there is a positive relationship between E - HRM and Job Satisfaction. Job satisfaction levels within organizations or companies can be impacted to produce with positive consequences because implementing e- HRM enable organizations or companies to improve cost effectiveness for administrative processes by the reduction of costs and automation. The relationship between job satisfaction and employee performance by previous studies , such as Bouckenooghe et al. (2013), Maret et al. (2007) and Sykes et al. (2014) indicated that the function of Job Satisfaction can facilitate job performance within organizations or companies. Job satisfaction levels can be dropped by the consequence that decreasing motivation from the challenge of obtaining information technology abilities as viewed a difficulty by sense of employees. Work habits among employees also can be impacted by implementing electronic HRM applications so that job satisfaction within organizations or companies either dropping or improving. In terms of the relationship between job satisfaction and organizational commitment, previous studies such as Durukan et al. (2022), Lamba and Choudhary (2013) and Markovits et al. (2010) indicated that organizations or companies have to make employees to be felt satisfied in emotional and physical way, which can enhance the employees with the better emotion and physic to be translated to be a devoted employee, and the devoted employee can be a foundation of an environment with positive attitude in working for disseminating the devotion that a devoted employee produces to organizations or companies for the colleagues. In this case to be known that many results in the relationship between Job Satisfaction (JS) and organizational commitment from previous studies can be identified and performed as positive effect. Thus, the current study has already discussed the relationship between E - HRM and Job Satisfaction (JS), the relationship between Employee Performance (EP) and Job Satisfaction (JS), the relationship between Job Satisfaction (JS) and Organizational Commitment (OC). According to such discussing in the relationship between variables to be known, Job Satisfaction (JS) can be influenced by E - HRM and Employee Performance (EP), and then Job Satisfaction (JS) also can impact on Organizational Commitment (OC). In this case, Job Satisfaction actual can be mediator among the relationship between IVs (E - HRM and JP) and DV(OC), so as the hypothesis questions can be showed below: Ha4: Job Satisfaction (JS) mediate the relationship between IVs (employee performance, E - HRM use) and Organizational Commitment (OC) 3. Methodology The context and sample: The number of small and medium-sized family businesses in China has reached 48.42 million by the end of 2021. Small and medium-sized family businesses in China are involved in various industries, such as production and processing, retail, e-commerce and foreign trade. Among them, small and medium-sized family enterprises are also the largest foreign trade business entity in China, contributing more than 58.2% to the growth of foreign trade. The number of employees of small and medium-sized family businesses accounts for 80% of the total number of employees. In 2021, the total number of individuals employed by small and medium-sized family businesses in China will reach 400 million, an increase of more than 200 million over the past ten years. Therefore, in order to improve the organizational commitment of Chinese small and medium- sized family enterprises to employees, this research will pass through a Chinese family-owned enterprise. The management team of Ningxia Dafeng Environmental Protection Technology Co., Ltd. uses the China Federation of Small and Medium-sized Family Enterprises to distribute questionnaires to employees of Chinese small and medium-sized family enterprises. and data collection. 233 Moreover, the selected companies in China with Electronic Human Resource Management (E - HRM) can be targeted and picked. Through the China Federation of Small and Medium Family Enterprises, the questionnaires are distributed to the employees of the participating Chinese small and medium family enterprises, and finally the questionnaires are finally collected through the China Federation of Small and Medium Family Enterprises. From October to December 2022, a total of 150 questionnaires will be distributed, and after the first questionnaire survey period, a total of 80 questionnaires will be collected. In order to ensure the completeness of data collection, 150 questionnaires were distributed again from January to March 2023. After the second questionnaire distribution survey period, a total of 70 complete questionnaires were collected. By not comparing the response rates of the two questionnaires, it can be known that the response rate of the questionnaire in 2022 is 53%, and the response rate of the questionnaire in 2023 has reached 47%. The data collection in this research process all ensured the privacy of the respondents, and they have the right to determine whether they want to be surveyed. Finally, both two period of investigation in the collection in questionnaires can be total number in 150 compared with the utilization of G - power, a software of determining sample size that can assured the total sample size in 89. At the same time, considering the invalid collected questionnaires, that is why the total sample size and the number of distributing questionnaires should be 150. Measurement of Variables: This study provides a questionnaire that including four sections for covering the variables, which can be described as Electronic Human Resource Management use (E - HRM) as IV1, Employee Performance (EP) as IV2. Job Satisfaction (JS) as MV and Organizational Commitment (OC) as DV. All the variables in the scale can be measured by adopting Five Likert Point: 1- Strongly disagree, 2- Disagree, 3-Neutral, 4-agree, 5-Strongly agree. E - HRM use scale: Ruel, Bondarouk, and Van der Velde (2007) and Wahyudi and Park (2014) have created and developed this scale for doing research in E - HRM. The scale can be consisted of two items: 1.0 I have the necessary knowledge to use E-HRM systems; 2.0 Use of e-HRM systems do not require a lot of mental effort; which can measure IV1: E - HRM in this study. Meanwhile, the Cronobach’s alpha of the scale in the statistic can be found in 0.8 more than 0.7. Employee performance (EP) scale: Goodman and Svyantek (1999) has created and developed this scale for doing research in Employee Performance (EP). The scale can be consisted of four items: 1. The e-HRM systems are clear and understandable; 2. I help other employees with their work when the work load increases; 3. I assist others with their duties; 4. I make innovative suggestions to improve the overall quality of the department; which can measure IV2: Employee Performance (EP) in this study. At the same time, the Cronobach’s alpha of the scale in the statistic can be found in 0.8 more than 0.7. Job Satisfaction (JS) scale: The scale for doing research in Job Satisfaction (JS) has been created and developed by Warr (1998), which utilized five items to measure the MV: Job Satisfaction(JS) in this study. The items in measurement with 0.729 more than 0.7 of Cronobach’s alpha includes: 1. The physical conditions in which you work; 2. Relation between you and your immediate manager; 3. The job security; 4. Freedom to choose your own working methods; 5. The recognition you get for good work. Organizational Commitment (OC) scale: The scale for doing research in Organizational Commitment (OC) has been created and developed by Meyer and Allen (1991), which utilized five items to measure the DV: Organizational Commitment (OC) in this study. The items in measurement with 0.753 more than 0.7 of Cronobach’s alpha includes: 1. I really feel as if the organization’s problems are my own problems; 2. The organization has a great deal of personal meaning for me; 3. I have a strong sense of belonging to my organization; 4. I feel like‘part of the family’ at my organization; 5. I believe that a person must be loyal to his or her organization; 6. I feel that I owe the organization quite a bit because of what it has done for me. The Instrument for the study: Import the collected relevant data into the tool used in this study, namely IBMSPASS. The relevant analysis of data sources was carried out. By using the test of reliability and validity in IBMSPSS, each item of the scale used in this study was tested. The test basis was proposed by (Hair, Risher, Sarstedt, & Ringle, 2019). The test value of reliability and validity should be greater than 0.7. At the same time, in order to test the hypothesis of this study Whether it is established, and then import the relevant data that passed the reliability and validity test into the SMART-PLS-SEM software for structural analysis, respectively need to test the reliability and validity of the facet, whether the VIF passes and the final model test is the path coefficient, Significance and R-squared. 4. Data and Analysis Demographic present: The data of this research is mainly collected through the team of Ningxia Dafeng Environmental Protection Technology Co., Ltd. contacting the China Federation of Small and Medium Family Enterprises for this research. The main distribution of data sample collection is shown in the figure. A total of 150 questionnaires were collected this time, of which employees working in family businesses accounted for 96.7%, with a total of 147 questionnaires. Employees working in non-family businesses accounted for 3.3%, with a total of 5 jobs. In the gender classification of data collection sources, males accounted for 51.3%, with a total of 78 records. Data from female workers accounted for 48.7%, a total of 74 pieces. The main sources of data collected according to different ages are: employees aged 18-30 accounted for 48%, a total of 73; employees aged 31-50 accounted for 38.8%, a total of 59, and employees older than 50 accounted for 13.2, 62 copies in total. Among them, the largest source of data is mainly employees aged 18-30, followed by employees aged 31-50. The collected data also comes from employees with different years of work experience: 40.8% of employees with less than two years of work experience, a total of 48; 31.6% of employees with 2-6 years of work experience, a total of 48; more than six years of work experience employees accounted for 27.6%, a total of 42 copies. Among them, the largest source of data is employees with less than two years of work experience, followed by employees with 2-6 years of work experience. The source of the data this time also comes from employees working in small and medium-sized family businesses in different industries. The number of responses to the questionnaires in the agricultural industry accounted for 26.3%, with a total of 40 responses; the response to the questionnaires in the processing industry accounted for 234 40.8%, with a total of 62 responses; The number of responses to the questionnaires in the service industry accounted for 32.9%, with a total of 50 responses. Among them, the largest sources of data are the processing industry and the service industry. The data sources this time also come from employees working in small and medium-sized family businesses in different departments. The information and technology department accounted for 49.3% of the questionnaire responses, a total of 75; the financial department accounted for 28.9% of the questionnaire responses, a total of 44 The proportion of responses to the questionnaires from the administrative department was 21.7%, with a total of 33 questionnaires. The data comes from the Information Technology Department and the Finance Department. Finally, the source of the data this time also comes from employees working in small and medium-sized family businesses in different positions. Non-management employees accounted for 51.3% of the questionnaire responses, a total of 78; management questionnaire responses accounted for 48.7% , a total of 74 copies. Among them, the largest sources of data are non-management and management. Descriptive Analysis: This article first examines the validity and reliability, and uses IBM SPASS to measure the reliability and validity of all items in this research. After passing the reliability and validity and testing the structural model. According to Bland and Altman (1997), the reliability and validity greater than 0.7 indicate that the scale has good reliability and validity. Through this IBMSPASS test, the reliability and validity of this research are 0.959 corresponding to the items of 17 scales and the KMO of 0.958 (Napitupulu, Kadar, & Jati, 2017). Dimensional Reliability and Validity: Measurement model testing is actually convergent validity and discriminant validity testing. Convergent validity means that test indicators measuring the same underlying trait (construct) fall on the same common factor. As Hair et al. (2019) indicated that if the average variance extraction (AVE) value of each factor is greater than 0.50, and the CR value of all concepts is greater than 0.80, the criterion of convergent validity is met. In this study, the below table shows Composite reliability, CR for each variables(E - HRM, EP, JS, OC) are all more than 0.8, and the AVE of each variables(E - HRM, EP, JS, OC) are greater than 0.5. So, the criterion of convergent validity can be met by the results in this study. Loading Factors for Each Variables of Items: The results in the table below show that according to Hair et al. (2019), the loads of all items are greater than 0.60, and the loads of each variable item are: Electronic Human Resource Management (E - HRM): 0.829 to 0.873, Employee Performance (EP): 0.784 to 0.82, Job Satisfaction (JS): 0.799 to 0.85, Organizational Commitment (OC): 0.824 to 0.857. The above values are significantly greater than the standard value of 0.60. In this case, the items in this study also pass the factor loading test. Discriminant Validity: Discriminant validity refers to the degree of item differences between variables, which can be measured by correlation analysis and the square root of AVE. The following table shows that the square root of AVE exceeds the correlation coefficient of the variables in the model. In order to further test the discriminant validity, different variables show a set of index values to measure whether the discriminant validity of the relationship between different variables is too high (>0.90) or too low (<0.10). The figure below shows that the highest correlation value between variables is 0.885 【between Job Satisfaction (JS) and Organizational Commitment (OC)】. Therefore, the discriminant validity of the measurement model meets the requirements (Hair et al., 2019). Testing by VIF: Multicollinearity test. In order to assess the problem of multicollinearity, the author calculated the variance inflation factor (Variance Inflation Factor, VIF), which ranges from 1.62 to 2.776. As shown in the figure below, the VIF of this study is significantly smaller than the threshold value of 5. Therefore, there is no variable collinearity problem and passed the multicollinearity test (O’brien, 2007). Model Testing for Hypothesis Questions: As shown in the table below, both E-HRM (β=0.380, p<0.01) and EP (β=0.545, p<0.01) have a significant positive impact on Job Satisfaction (JS). At the same time, according to the path coefficient and p value, it can be concluded that JS (β=0.885,, R square in 0.768> 0.7, p<0.01) has a significant positive impact on OC (R square is 0.783, which can be more than 0.7 ). From the structure and data, it can be concluded that Electronic Human Resource Management (E - HRM) is the most important influencing factor of Job Satisfaction (JS), followed by Employee Performance (EP). At the same time, according to the structural data, Job Satisfaction (JS) is an important factor affecting Organizational Commitment (OC) (Hair et al., 2019). Therefore, it is assumed that Ha1, Ha2, and Ha3 are all established. Finally, according to the significant positive effects of E-HRM and EP on JS, and the significant positive effect of JS on OC, it can be concluded that Ha4 is established. Job Satisfaction (JS) was included in the proposed model as an intermediary variable. The results show that Job Satisfaction (JS) (β=0.012 5, p>0.05, R square is more than 0.7) has a significant positive impact on Organizational Commitment (OC) (Hair et al., 2019). The use of survey data in this study may lead to response bias, and future research can overcome this shortcoming by adding observation groups and interviewing team managers in the sample through targeted methods. In addition, important factors outside the model may not be included in the research framework, and future research can explore other potentially relevant factors, such as cultural background, social atmosphere, and individual quality. 5. Conclusion The results of this study confirmed that the independent variable Electronic Human Resource Management (E - HRM), and the independent variable Employee Performance (EP) have a significant positive impact on Job Satisfaction (JS), at the same time, Job Satisfaction (JS) has a significant positive impact on Organizational Commitment (OC ) has a significant positive impact, and because in the same research model framework, the data also confirmed that Job Satisfaction (JS) has a mediating role between Organizational Commitment (OC) and IVs (E - HRM and EP). Therefore, in order to improve the Organizational Commitment (OC) of employees to the enterprise or organization, small and medium-sized family enterprises in China need to formulate and introduce systems and policies to improve Job Satisfaction (JS), and pay more attention to the introduction of new human resource system technology and expansion It is not necessary to invest a lot of manpower 235 and financial resources in order to innovate the main scope of Electronic Human Resource Management(E - HRM) and optimize the layout of Electronic Human Resource Management(E - HRM) facilities. Electronic Human Resource Management (E - HRM) was confirmed to have a statistically significant positive correlation with Job Satisfaction (JS). Only the introduction of new technology systems can allow more corporate employees to participate in family business activities through the process of E-HRM implementation, thereby improving the efficiency and boundaries of employees using new technologies for the daily work of small and medium-sized furniture companies in China, thereby Improve employees' Job Satisfaction (JS) and then increase employees' Organizational Commitment (OC) to the enterprise. The results of this study show that top management's commitment and support for the introduction of E-HRM, together with the provided innovative sharing facilities, can not only promote non-family employees' interest in participating in the company's daily experience, but also make family core employees feel motivated by top management. The coercive measures of employers share the work of non- family employees, so that non-family employees have a sense of fairness, increase Job Satisfaction (JS), and further promote employees' Organizational Commitment (OC) to the enterprise. Employee Performance (EP) was confirmed to have a significant positive correlation with Job Satisfaction (JS). Only employees with a positive working attitude and Employee Performance (EP) can maximize their potential to make a certain contribution to the company and create a more positive Employee Performance atmosphere. Then such a positive Employee Performance (EP) can enable non-family employees and family employees working in small and medium-sized family enterprises in China to contribute to the company's goals, so that non-family employees can see that family employees are just like themselves By contributing your own strength, you can improve the internal Job Satisfaction (JS) of the enterprise, and then increase the Organizational Commitment (OC) of employees to the enterprise. In summary, studying the relationship between IVs (E - HRM and EP), MV (JS) and OC is the focus of this paper. On a theoretical level, this study develops and tests a conceptual model that reveals the mediating role played by JS in the relationship between IVs (E - HRM, EP) and OC. The practical significance of this study is to suggest that those Chinese small and medium-sized family enterprises that want to improve the OC of employees to the enterprise should pay more attention to the introduction of E-HRM, the expansion of the scope of E-HRM subjects, and the optimization of the layout of E-HRM facilities. Focus on how to deter employees through coercive means. Therefore, by studying the relationship between IVs (E - HRM and EP), MV (JS) and OC, this paper will help to better understand how different E - HRM and EP affect JS, and how JS affects employees For corporate OC's. With the increasing market competition and rising labor costs in China, improving employees' OC for enterprises may be an important means to cope with future competition. The limitation of this study is that the moderating role of JS in the relationship between IVs (E - HRM, EP) and OC was studied using quantitative methods. The research background and research data are limited to small and medium-sized family enterprises and employees in China. In the future, scholars or researchers can try to add and expand the influencing variables of JS, such as Organizational Culture (OC). Also for this research framework, more influencing variables can be put forward for combined research on E-HRM. The use of survey data in this study may lead to response bias, and future research can overcome this shortcoming by adding observation groups and interviewing team managers in the sample through targeted methods. In addition, important factors outside the model may not be included in the research framework, and future research can explore other potentially relevant factors, such as cultural background, social atmosphere, and individual quality. Acknowledgment We thank Liu Jian LI and Xu Jing ru. This work was supported in part by a grant from Ningxia Dafeng Environmental Protection Co. Ltd. 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