INTRODUCTION
Research background and problem statement
Small and medium-sized enterprises (SMEs) play a crucial role in global economies, representing a significant portion of businesses In Europe, SMEs comprise 99.7% of all enterprises, with 57% being one-person businesses, 34% micro enterprises, 7.7% small enterprises, and only 1% medium enterprises, while large companies account for just 0.27% (Agnès, 2010) In China, SMEs represent 99.9% of firms, contributing to 84% of total employment and 71% of sales (Qimiao, 2003) Similarly, in Vietnam, SMEs make up approximately 97% of the 448,393 companies, driving employment growth and contributing 60% to the GDP, with a capital investment of 6 million billion VND (General Statistics Office, 2012; VCCI, 2012).
Small and medium-sized enterprises (SMEs) encounter significant challenges in human resources, particularly due to an increasing demand for skilled personnel and a shortage of qualified management staff This lack of suitable candidates hinders the growth and development of these businesses A notable issue in SMEs is the unclear distinction between administrative tasks and human resource functions; often, administration handles recruitment, despite these being two separate HR roles within the organization.
In 2003, it was noted that small and medium-sized enterprises (SMEs) struggle to compete with larger organizations in attracting qualified employees due to a lack of clear retention policies A survey conducted by recruitment firm Jobs Factory, which included over 4,500 students, identified Apple, Singapore Airlines, Google, 3M, and DBS Bank as the top five employers of choice in the private sector These multinational companies (MNCs) are favored by job seekers not only for their well-known brand names but also for their perceived stability and global presence.
Recent surveys indicate that the younger generation values work-life balance, viewing larger companies as more flexible and receptive to employee suggestions In contrast, small and medium-sized enterprises (SMEs) are frequently perceived as lacking transparency, exhibiting authoritarian management styles, and displaying less professionalism Additionally, it is common for the leadership of SMEs to prioritize familial connections over professional qualifications when forming their inner circles.
Employee retention poses a significant challenge for businesses in Vietnam, making it a critical topic for human resource managers Vietnamese employees are increasingly focused on advancing their careers, seeking better positions, more challenging roles, and higher salaries According to a 2010 survey by Navigos Group, a leading executive recruitment provider, 63.8% of respondents from 168 companies in Vietnam identified employee retention as the top human resource challenge The survey emphasized the importance of placing the right individuals in suitable roles and ensuring their growth within the company, highlighting that employee retention remains a demanding task for HR professionals.
The Towers Watson (2011) engagement indicator survey highlights a competitive talent landscape in Vietnam, where employers are actively implementing employee engagement programs to retain talent The survey reveals that employee engagement levels in Vietnam are stable at 78%, surpassing the Asia Pacific average of 74% However, the intent of Vietnamese employees to remain with their current employers is lower at 54%, compared to 61% in the broader Asia Pacific region This indicates that the competition for talent in Vietnam is more intense, with employees facing a greater likelihood of seeking new opportunities.
Organizational commitment is increasingly vital for human resource managers and employers, especially in small and medium-sized enterprises (SMEs) in Vietnam Understanding the key factors that influence employee commitment is essential, as many workers view their positions in SMEs as temporary and lack long-term plans Additionally, employees in these organizations often rely heavily on leadership for direction To foster a sustainable workforce, employers in Vietnamese SMEs must develop strategic action plans that enhance employee engagement and address the factors impacting organizational commitment and retention of key staff in Ho Chi Minh City.
Research objectives
This thesis will explore theories and prior research on the factors influencing employee organizational commitment within small and medium-sized enterprises (SMEs) Additionally, the study aims to identify the key elements affecting the retention of essential employees and assess the extent to which these factors impact both organizational commitment and employee retention in SMEs.
Research scope
The research was conducted in Ho Chi Minh City, Vietnam's commercial and financial hub, known for its central role in economic and industrial activities This city serves as a "silicon valley" for various sectors, including culture, education, and sports, and is home to the largest concentration of small and medium enterprises in the country.
This study focuses on small and medium sized enterprises in the area of Ho ChiMinh City.
Significance of the study
Ho Chi Minh City (HCMC) stands as Vietnam's largest trading, financial, and service hub, experiencing both significant successes and challenges According to the Ho Chi Minh City Department of Planning and Investment, over 26,000 companies ceased operations in the first half of 2012, largely due to difficulties in retaining talented employees Recognizing the critical role of key personnel, this research emphasizes the importance of employee retention strategies in small and medium-sized enterprises (SMEs) within HCMC.
Key employees are essential members of an organization who possess unique qualifications, including their tenure and significance to the company In addition to the standard expectations of regular employees, these key individuals have heightened needs that must be addressed to ensure their satisfaction and retention Meeting these specific demands is crucial for maintaining a motivated and committed workforce.
Research structure
The study consists of five main parts:
Introduction: Research background, problem statement, research purposes, scope of study and significances of the study
This chapter presents a literature review that defines key concepts relevant to the study, including small and medium enterprises, key employees, and the importance of key employee retention It also examines previous research on training and career opportunities, job characteristics, work/life balance policies, organizational commitment, and employee retention Additionally, this chapter will introduce the proposed research hypotheses.
This chapter outlines the research process, detailing the methodologies involved in designing questionnaires, measuring variables, drafting the questionnaire, conducting a pilot study, and collecting data Additionally, it covers the approaches to data analysis employed in the study.
Data analysis: Collected data will be analyzed in this chapter.
Conclusion, implications and limitation: This is the result of the study distribution of study for theory and applied, the limitation of the study and suggest to later study
Summary
This chapter outlines the study's background, articulates the problem statement, and defines the research objectives It also reviews the theoretical framework and delineates the scope and structure of the research.
LITERATURE REVIEW 2.1Introduction
Summary
This study examines the key factors influencing organizational commitment and the retention of essential employees in Ho Chi Minh City, specifically highlighting the importance of training and career opportunities, job characteristics, and work/life policies.
RESEARCH METHODOLOGY
Summary
A survey was conducted in Ho Chi Minh City, utilizing a convenience sampling method to gather data The targeted participants were employees from small and medium-sized enterprises in the area, ensuring that respondents were not company owners but rather individuals working within these organizations.
To ensure statistical significance, it is crucial to have an adequately sized sample According to Hair et al (2009), the minimum sample size for effective statistical analysis should be at least five times the number of variables, with a minimum threshold of 100 participants Thus, the sample size must meet the criteria of n ≥ 100 and n ≥ 5k, where k represents the number of variables.
The model in this research included five factors with twenty six variables, therefore the necessary sample size should be: 26 * 5 = 130 observations.
In Exploratory Factor Analysis (EFA), it is generally recommended to have a minimum sample size of at least five times the number of variables being analyzed, with a total sample size exceeding 100 (Hair et al., 2009) Therefore, for this study, the minimum required sample size for EFA is 130 observations, calculated as n = 5*26.
To implement standard multiple regression analysis, Nunnally & Burnstein (as cited in Nguyen, 2011) emphasized that the sample size must fully meet: n> 50 + 8m ( m in this case is the number of independent variables)
There were three independent variables in this study So, the minimum sample size required to run the multiple regression in this research should be: n > 50 + 8 * 3 74 observations.
In conclusion, with twenty-six variables and three independent variables, this study needed at least 130 observation for running EFA and multiple regression.
The data collection process for this research was conducted in Ho Chi Minh City and comprised two phases: qualitative and quantitative The survey questionnaire was initially developed in English and then translated into Vietnamese During the qualitative phase, the Vietnamese version was pretested through direct and in-depth interviews over three weeks with five individuals, including colleagues and friends, to ensure clarity and understanding of the scale This process aimed to confirm that the final questions effectively measured the observed variables before the main survey The interviews began by defining the study's objectives and involved presenting the draft questionnaire to assess comprehension The researcher sought to determine the appropriateness of the measurement scales for the Vietnamese context, particularly in Ho Chi Minh City Insights gathered from these interviews were crucial for evaluating the influence of independent factors—such as training, career opportunities, job characteristics, and work/life policies—on organizational commitment and employees' intent to stay in small and medium-sized enterprises in the region Feedback from interviewees was collected to refine the questionnaire's measurement scales.
In-depth and direct interview – Qualitative Research
Cronbach’s Alph Main Survey – Quantitative Research
(Test reliability and validity of measurement scale)
Multiple Regression and Simple Regression Analysis
Based on respondent feedback, the English content of the survey questionnaire was retained, while minor adjustments were made to the Vietnamese content to enhance clarity for the participants (see Appendix 1).
After finalizing the survey questionnaire, a comprehensive official survey was conducted throughout Ho Chi Minh City The qualitative phase has been detailed previously, and we now shift our focus to the quantitative phase, as illustrated in Figure 3.1 below.
The main survey utilized quantitative research methods to gather data for testing the research hypotheses Respondents completed a self-administered questionnaire primarily using a five-point Likert scale ranging from "strongly disagree" (1) to "strongly agree" (5) The questionnaire was predominantly distributed online via a Google Survey Tool link, although paper versions were provided in certain cases Participants received the questionnaire link through email and social media platforms, such as Facebook, and were given one week to respond To enhance participation, a reminder email or message was sent three days later, thanking those who completed the survey Data collection occurred over a period of one and a half months, encompassing both weekdays and weekends.
In accordance with the requirements outlined in section 3.1, a minimum sample size of 130 was necessary for data analysis For this survey, a total of 350 questionnaires were distributed, with 300 sent via email to students at the International School of Business, as well as to the author’s colleagues, friends, and business partners Additionally, 50 paper questionnaires were delivered to the researcher’s friends and business customers, while another 50 were shared through a Google Survey link on Facebook Ultimately, 307 responses were collected, resulting in a response rate of approximately 76.65%.
Out of the initial responses, only 206 were deemed suitable for data processing A total of 101 responses were discarded, including 72 questionnaires from company owners or shareholders, and 29 invalid questionnaires where respondents selected the same option for all questions Ultimately, 206 questionnaires were utilized as valid data for the research.
In comparison with the required minimum sample size, this number is totally meet the demand.
The measurement of the factor is founded and developed by many researchers:
Training and Career Opportunities: Training adequacy, promotional chance This measurement was developed by Blau (1989), Cammann at al., (1979), Hausknecht at al., (2002), Jones et al (2001), Warr at al., (1979).
Measurement of Training and Career Opportunities (TRA)
TRA1 - People are properly orientated and trained upon joining this organization. TRA2 - This organization does provide regular opportunities for personal and career development.
TRA3 - The organization has career development activities to help an employee identify/improve abilities, goals, strengths, & weaknesses.
TRA4 – My chances for being promoted are good.
TRA5 – There are enough career opportunities for me in this organization.
Job characteristics, as conceptualized by Hackman and Oldham in their theory from 1975-1976, provide a comprehensive framework for understanding job context variables Their research utilized the Job Diagnostic Survey, which includes two key items for each dimension, specifically focusing on skill variety and job autonomy.
Measurement of Job Characteristics (JOB)
JOB1 - The job requires me to use a number of complex or high level skills.
JOB2 - The job denies me any chance to use my personal initiative of judgment in carrying out the work.
JOB3 - The job is simple and repetitive.
JOB4 – The job gives me considerable opportunity for independence and freedom in how I do the work.
Work/life policies are essential for addressing employee needs and reducing the impact of work-family conflicts Developed by Pare and colleagues in 2001, these policies incorporate questions designed to assess and improve the balance between professional and personal responsibilities The framework builds on previous research by Honeycutt and Rosen (1997) and Kopelman et al (1983), highlighting the importance of creating supportive work environments.
Measurement of Work/Life Policies (POL)
POL1 – I often feel like there is too much work to do.
POL2 – My work schedule is often in conflict with my personal life.
POL3 – My job affects my roles as a spouse /or a parent.
POL4 – My job has negative effects on my personal life.
Organizational Commitment: That measures the feedback of employees for the company's affection, it founded from Meyer & Allen (1997); Porter at al., (1974) with 5 items and Janet (2004) developed to 9 items.
Measurement of Organizational Commitment (COM)
COM1- I feel a strong sense of belonging to this organization.
COM2- I could just as well working for a different organization if the type of work was similar. job performance.
COM5- My values and this organization’s values are very similar.
COM6- There is little to be gained by sticking with this organization
COM7- I am willing to put in a great deal more effort than normally expected to help this organization be successful.
COM8- I am proud to tell others that I am part of this organization.
COM9- I really care about the future of this organization.
Employee intention to stay refers to the measurement of trends regarding whether employees choose to remain with or leave an organization This concept is based on four key items developed by researchers including Cammann et al (1979), Dalessio et al (1986), Lambert et al (2001), Mathieu & Zajac (1990), and Seashore et al (1982).
Measurement of intent to stay of employees (INT)
INT 1- I plan to work at my present job for as long as possible.
INT 2- I will most certainly look for a new job in the near future.
INT 3- I plan to stay in this job for at least two to three years.
INT 4- I would hate to quit this job.
The completed questionnaire in English version and Vietnamese version were presented in Appendices 2 and 3.
The survey consists of three sections, with Part A designed to identify key employees through four specific questions Employees will be classified as key based on their fulfillment of certain established criteria.
2 Work for that company over than 6 months.
4 Support company’s organizational culture and vision.
This section includes screening questions that respondents must answer before proceeding with the main survey If a participant answers "No" to any of the four initial questions, it indicates they do not meet the criteria for this survey and will be disqualified from continuing.
PART B: Demographic Profile is in this part: These data help the author understand about interviewees and know deeply research objective.
Part C focuses on key employee perceptions, utilizing a five-point Likert scale ranging from Strongly Disagree to Strongly Agree This section assesses employee attitudes towards their company, highlighting aspects such as training and career opportunities, job characteristics, and work/life policies.
DATA ANALYSIS
Respondent’s Demographics
The writer employed SPSS to analyze the demographic data of survey respondents, aiming to provide an overview of the individuals who submitted valid responses The findings from the demographic analysis are presented in Table 4.1, which highlights several key insights.
1- The correspondents are key employees from various industries such as 19.9% for engineering, 15.5% for trading, 20.9% for banking, 34.5% for import and export, and the rest 9.2% for other fields.
2- In terms of occupation, there were 83 salespersons, 60 officers, 21 managers, 18 engineers, and 24 persons from other occupation, who made the survey.
3- The key employees who answered the survey are most of bachelor degree (84%), the rest part are 4.4% for college and 11.7% for upper bachelor degree.
4- Among the respondents, there were 106 men and 100 women In addition, the percentage of single accounted for 62.1%, and 37.9% is married.
Frequency Percent Valid Percent Cumulative
5- The age of employees who joined the survey, ranged from under 30 to 50 With under 30, it accounted for 61.6% From 31 to 40 were 26.7%, and the rest 11.7% for the age from 41 to 51.
Reliability Analysis
A crucial aspect of data analysis is ensuring the reliability of measurement scales used to assess research hypotheses To achieve this, a reliability test must be conducted for each definition within the measurement scale Cronbach's Alpha serves as a key indicator of internal consistency, helping to identify and eliminate unstandardized items For a measurement scale to be deemed reliable, Cronbach's Alpha should be at least 0.6, as recommended by Nunnally & Bernstein (cited in Nguyen, 2011).
The Corrected Item – Total Correlation is a vital metric in reliability testing, indicating that an item is likely to be well correlated with other scale items if its correlation exceeds 0.3 (Nunnally & Burnstein, as cited in Nguyen, 2011) Conversely, if an item's corrected item – total correlation falls below 0.3, it is essential to reevaluate that item, with modifications or deletions recommended as necessary.
The author presented the results of reliability test of each item of the research model in the Table 4.2 below.
Variable Scale Mean if Scale Variance Corrected Item- Alpha
Item Deleted Item Item Deleted Correlationif Total Deletedif
Training and Career Opportunities (TRA): Alpha = 0.792
Work/Life Policies (POL): Alpha = 0.787
Intent to Stay (INT) Alpha = 0.803
During the reliability testing of the TRA scale, TRA5 was excluded due to its low corrected item-total correlation of 0.26, which is below the acceptable threshold of 0.30 Following the removal of TRA5, the reliability test was conducted again for the TRA scale.
The results presented in Table 4.2 indicate that Cronbach’s alpha values for job characteristics, organizational commitment, and intent to stay were notably high, exceeding 0.8, demonstrating strong reliability While the alpha values for training and career opportunities, as well as work/life policies, were slightly lower, they still surpassed the minimum acceptance threshold Additionally, the Corrected Item-Total Correlation values for all items across the five measurement scales of the survey were significantly substantial.
In summary, all five measurement scales demonstrated reliability in assessing the research concept, with Cronbach's alpha values exceeding 0.6 Additionally, the corrected item-total correlations for all dimensions surpassed the acceptable threshold of 0.3 Consequently, it can be concluded that all scales meet the necessary criteria for reliability.
The next step would be the test the validity of the measurement scale by doing exploratory factor analysis (EFA).
Exploratory Factor Analysis
Exploratory Factor Analysis (EFA) was utilized to validate measurement scales by simplifying interrelated measures and examining the relationships among interval variables (Leech et al., 2005) This analysis allowed the author to identify how various items cluster together In this study, Varimax rotation was applied to EFA to highlight scale items with low loading on the construct For an item to be deemed valid, its loading factor needed to be at least 0.5, and the Eigen value had to exceed 1.0.
The KMO value of 0.875, exceeding the recommended threshold of 0.7 (Leech et al., 2005), indicates that there are sufficient items to effectively measure each construct Additionally, the significance value being below 5% demonstrates a strong correlation among the variables Consequently, it can be concluded that the data is appropriate for factor analysis.
Table 4.3 KMO and Bartlett’s Test of Independent Variables
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .875
The cumulative of the three factors was 65.30 percent of variance (see Appendix
D, Table D1) It meant that more than a half of variance could be explained by these three factors.
The rotated component matrix, as illustrated in Table 4.4, reveals that all items exhibit a factor loading exceeding 0.5 The analysis identified three independent variables, with all 12 items successfully categorized into three components, each demonstrating high loadings Furthermore, the items within the same dimension remained consistently grouped after rotation.
Table 4.4 Rotated Component Matrix of Independent Variables
The KMO value was notably high at 0.893, exceeding the accepted threshold of 0.7, indicating sufficient items to measure each dimension effectively Additionally, the significance value was less than 5%, confirming that the correlation matrix was significant and that the variables were indeed correlated.
Table 4.5 KMO and Bartlett’s Test of Dependent Variables
Kaiser-Meyer-Olkin Measure of Sampling
According to the data presented in Appendix D Table D2, two factors were identified, accounting for a cumulative variance of 54.93 percent This indicates that these two factors collectively explain over half of the total variance.
Table 4.6 Rotated Component Matrix of Dependent Variables
COM8 0.764 COM2 0.735 COM6 0.708 COM9 0.691 COM4 0.688 COM3 0.686 COM5 0.678 COM7 0.625 COM1 0.532
Table 4.6 presents a total of thirteen dependent variable items categorized into two components All loading factors exceeded 0.5, indicating that items within the same dimension were effectively grouped after rotation This suggests that the items are clearly defined and well-structured.
Regression analysis was the next step after testing reliability and validity of collected data in order to investigate the relationship among the factors in the research model Multiple regression would be used in this part to test the hypotheses from 1 to 3, in which training and career opportunities, job characteristics, and work and life policy were considered as the independent variables and organization commitment was seen as the dependent variable In order to executing multiple regression, it was necessary for the variables to meet some important assumptions:
Assumption 1: The residuals were independent.
Assumption 2: The linear relationship between independent variables and dependent variable appeared.
Assumption 3: The residual was distributed normally.
Assumption 4: No multicollinearity among independent variables
These four assumptions above were developed by Leech et al., (2005)
To validate the assumption, we concentrated on the Durbin-Watson value, which ideally falls between 0 and 4, with a value of 2 indicating independent residuals In our analysis, the Durbin-Watson value was 1.980, suggesting that the residuals were indeed independent and thus satisfying the first assumption.
To evaluate assumption 2, the shape of the overall regression plot is analyzed A curvilinear shape in the plot indicates that the predictors are not linearly related to the dependent variable As demonstrated in Appendix E, this assumption is effectively validated.
The residual scatter plot chart provides evidence for the assumption of normally distributed residuals If the dots in the chart are widely scattered, it indicates that the data meets this assumption As illustrated in Appendix E, Figure E2, the results confirm this conclusion.
Before conducting multiple regression analysis, it is crucial to test for multicollinearity, which occurs when there are high inter-correlations among independent variables (Leech et al., 2005).
Multicollinearity arises when two or more predictors share overlapping information, potentially skewing analysis results To evaluate this issue, a correlation matrix is utilized to identify the relationships between the variables.
Description TRA JOB POL COM
The Pearson test results from the correlation matrix indicated values below 0.8, with significant values less than 5% among the predictors, suggesting a reduced likelihood of multicollinearity Additionally, the Variance Inflation Factor (VIF) was utilized to further validate this assumption, with comprehensive details provided in Table 4.10.
In short, the data satisfied all of the assumptions Therefore, we could run the multiple regression analysis now.
Results of multiple regression analysis
To conduct multiple regression analysis, the author employed the enter method, which allows for the simultaneous input of all three predictors to assess their collective impact on the dependent variable.
Table 4.8 Model Summary of multiple regression analysis
Square Std Error of the Estimate
1 651 a 424 416 47185 a Predictors: (Constant), TRA, POL, JOB b Dependent Variable: COM
The model summary displayed the multiple correlation coefficient (R) was 0.651 ,
R square was 0.424 and adjusted R square was 0.416, indicating that 41,16% of the variance in organizational commitment could be predicted from three independent variables It meant that the model was fit.
Table 4.9 ANOVA of multiple regression
Squares df Mean Square F Sig.
Total 78.139 205 a Dependent Variable: COM b Predictors: (Constant), TRA, POL, JOB
The value of F was 49.656 and sig < 0.05 showed that the combination of three independent variables significantly (P
