Background and Motivation
In November 2006, with the WTO accession of Vietnam, all businesses in the country have to face both opportunities and challenges, including higher education sector
Professor Tran Hong Quan, the former Minister of Education in Vietnam, emphasized that joining the WTO requires Vietnam to embrace international markets and welcome the influx of global trade, including in the education sector This shift highlights the service-oriented nature of Vietnamese higher education.
The Vietnamese education system faces both opportunities and challenges, particularly in enhancing educational quality through competition Assoc Prof Dr Bien Van Minh highlights that the current state of Vietnamese education is low, with many weaknesses in the macro environment Addressing these challenges, especially in human resources, is crucial for universities to thrive in a competitive market With the rapid expansion of institutions and the emergence of new international universities, the demand for qualified staff is increasing, leading to fierce competition among universities for talent High staff turnover poses significant challenges, as retaining skilled employees is critical for sustainable development As higher education becomes more service-oriented, the role of university staff is essential for maintaining educational quality This issue of staff retention motivates my research focus, applying MBA knowledge to enhance practices at International University (IU).
International University, a member of Vietnam National University in Ho Chi Minh City, is Vietnam's first international public university, established in 2003 With its own legal status, seal, and account, IU is authorized to award degrees from undergraduate to postgraduate levels Currently employing 81 full-time staff, the university recognizes the critical need to address staff turnover to effectively compete and prevent brain drain in a challenging educational environment.
The author selects International University as a case study due to its significantly high staff turnover rate compared to other public universities in Ho Chi Minh City, Vietnam, where the turnover rate averages between 3-5% annually—two to three times lower than that of International University This research aims to identify the factors contributing to this elevated turnover, with the hope of fostering the university's development and serving as a foundation for future studies by the author.
Research Purpose, Objectives and Questions
The main purpose of this project is to find out the factors influencing on the staff turnover rate at IU, with the three following objectives:
1 Explore the current status of staff turnover rate at IU
2 Identify the impact of high staff turnover to the education quality
3 Find out the factors influencing on the staff turnover intention of IU
To achieving those three objectives, there are four research questions that this study examines They are:
1 What is the average staff turnover rate at universities in Vietnam?
2 What is the staff turnover rate at IU?
3 What are the impacts of high staff turnover to the education quality?
4 What are the factors that influence on the staff turnover intention at IU?
Research Scope and Limitations
This project focuses on the factors that influencing on the staff turnover rate at IU The research subjects are all staff working full-time at IU
Due to time constraints, the author was unable to address all recommendations from the study Nonetheless, the primary goal is to investigate the causes of high staff turnover at IU, aiming to lay the groundwork for future research on this issue.
Definition of Terms
In human resources, turnover refers to the rate at which employees are hired and leave an organization, often described as "how long employees typically remain" or "the flow of personnel through the revolving door."
Employee turnover refers to the rate at which permanent employees leave a company within a specific timeframe, calculated against the total number of active permanent employees at the end of the previous period.
Staff of IU: The staffs mentioned in this project are all the officials working at
Turnover intention means the subjective perception of the organizational member to quite the current job for other opportunity (Hsien-Che Lee & Tsai-Hua Chuang, n.d.).
Literature Review
Turnover and High Turnover Rate
Labour turnover, as defined by Argyle (cited in Gerald L & Simon, 2004), refers to the movement of employees in and out of an organization This phenomenon has been a longstanding concern for organizations across various sectors, as noted by Gerald L & Simon (2004), highlighting its significance in workforce management and organizational stability.
William King (2009) defined turnover rate as the proportion of employees leaving a company or industry within a specific timeframe He noted that a high turnover rate indicates that workers are more likely to leave their jobs compared to employees in similar companies within the same industry.
Turnover is defined as the rate at which a company or industry experiences employee gains and losses A high turnover rate indicates that employees tend to have shorter tenures compared to their counterparts in similar companies within the same industry.
At a recent workshop titled "Turnover and the Roadmap of Success for Employees," hosted by the Club of Directors of Human Resources (CPO) in Vietnam, numerous HR managers highlighted that a typical organization experiences a "brain-drain" rate of around 5-7% However, if this rate exceeds 10%, it is crucial for the organization to conduct a thorough review.
This article compares the staff turnover rate at IU with that of various public universities in Vietnam, highlighting IU's notably high turnover rate.
Comparison between the Average Staff Turnover Rate at IU and Public
2.2.1 The staff turnover rate at some public universities in vietnam
Table 2-1 Turnover Rates of A Number of Public Universities in Vietnam from 2008 to
2010 University of Social Sciences and Humanities, HCMC 3 4 3
University of Social Sciences and Humanities, Hanoi 4 3 3
University of Natural Science, HCMC 2 3 2.5
University of Natural Science, Hanoi 4 4 3
Ho Chi Minh University of Medicine 4 5 5
Ho Chi Minh City University of Economics 3 5 4
Ho Chi Minh City University of Pedagogy 5 4 4
University of Technical Education Ho Chi Minh City 3 2 3
Ho Chi Minh City University of Agriculture and
Ho Chi Minh City University of Information
Ho Chi Minh City University of Medicine and
(Source: Personnel Administration Offices, Human resources division of universities)
A personal investigation by the author reveals that data from the Offices of Personnel Administration at various public universities in Vietnam indicates an annual staff turnover rate of 3-5% Human resource managers consider these turnover rates to be acceptable.
2.2.2 The staff turnover rate at IU
Table 2-2 Total Number Employed and Leavers over Year 2004 to 2010
Year Total number employed Total number of leavers
(Source: Personnel Administration Office, Human resources division, International
Table 2-3 Percentage of Staff Turnover Rate over Year 2004 to 2010
Year Percentage of staff turnover rate (%)
In order to obtain the data presented in Table 2-3, the author utilized a formula developed by Grant McKenzie, a consultant specializing in leadership, team-building, and communication skills.
Average turnover rate = Total number of leavers over period x 100/ Average total number employed over period
Table 2-3 shows that the university now has a high staff turnover rate through each year (more than 10%)
Thus, generally speaking, most universities in Vietnam has a staff turnover rate of less than 5% whereas at IU this turnover rate can be 10% or even higher during recent five years
High employee turnover can indicate underlying issues within an organization's policies, as noted by William King (2009) If a company fails to address this, it risks losing valuable employees to competitors and incurs high costs related to recruitment and training Currently, IU employs 81 full-time staff members and must take significant steps to effectively compete and thrive in its environment A critical focus for the university is to reduce staff turnover, which is essential for preventing brain drain and enhancing the quality of education.
The Impacts of High Staff Turnover to the Education Quality
High turnover in educational institutions has a detrimental effect on the quality of education, as highlighted by Ima Jackson-Obot (2010) According to Professor Nguyen Xuan Thu from RMIT University, a university's educational quality is recognized when all operational aspects, including management and student services, adhere to standard quality benchmarks, as endorsed by the International Network of Quality Assurance Agencies in Higher Education (INQAAHE) The Ministry of Education and Training in Vietnam further emphasizes that higher education quality aligns with the university's objectives and requires comprehensive guidelines, policies, and management structures to maintain and enhance educational standards Professor Carter McNamara notes that effective performance management is crucial for organizations, including universities, to achieve their missions efficiently A survey by SHRI Research Center (2010) indicates that high turnover rates pose significant challenges to productivity and quality, adversely affecting university performance across various critical dimensions.
Employee turnover significantly impacts organizations by increasing costs and decreasing productivity The importance of retaining employees and the expenses associated with their departure are well-documented in literature Turnover costs vary depending on job complexity, with numerous studies indicating that a lack of employee continuity leads to substantial expenses related to the induction, operation, and training of new hires.
Research by Lochhead and Stephens (2004) highlights that employee turnover incurs significant costs, including the challenges of recruiting, selecting, and training new staff, as well as the loss of workplace-specific skills that can take years to develop Schlesinger and Heskett (1991) further categorize these costs into direct and indirect expenses; direct costs encompass leaving, replacement, and transition costs, while indirect costs involve decreased productivity, lowered performance, excessive overtime, and diminished employee morale.
William G Bliss in “Cost of Employee Turnover” also listed the costs of turnover as following:
Costs Due to a Person Leaving
Employee turnover poses significant challenges for organizations due to the high costs associated with recruiting and training new staff to fill vacancies As noted by Eunmi Chang (1999), turnover costs encompass opportunity costs, expenses related to reselecting and retraining employees, and a potential decline in the morale of remaining team members.
Employee turnover significantly impacts organizational productivity and efficiency High turnover rates present challenges that can hinder overall performance According to research by Hughes & Finlayson (as cited in Rana et al., 2009), the cost of losing a high-performing employee can be particularly detrimental, leading to substantial losses in both performance and productivity for the organization.
Staff turnover is a natural occurrence in any organization, but excessive turnover can significantly hinder productivity and threaten growth Experts emphasize that having a stable core of experienced employees is crucial for an organization's success, as their familiarity with the job and the company contributes to overall efficiency and effectiveness.
High employee turnover in higher educational institutions significantly impacts academic and research activities, as knowledgeable and skilled human resources are vital assets The departure of an employee not only results in the loss of tacit knowledge but also diminishes social capital (Iqtidar Ali Shah et al., 2010) Furthermore, researchers Adedoyin, Asaolu, and David Elumilade highlight that elevated staff turnover jeopardizes the achievement of research and development goals, innovation for efficiency, and the overall performance and credibility of organizations, including universities.
High employee turnover rates can significantly hinder an organization's ability to maintain essential daily operations, as noted by Shelley Moore in “The Effects of Employee Turnover.” This challenge extends beyond merely having enough staff; it can lead to overworked and frustrated employees, ultimately resulting in dissatisfied customers, such as students or lecturers in a university setting Furthermore, the hiring process for new staff is time-consuming, and new employees often require additional time to acclimate to their roles, particularly in complex positions.
High turnover rates can significantly impact university morale, as noted by Eunmi Chang (1999), who argues that turnover reflects a breakdown in the relationship between employees and the organization This decline in morale can lead to a snowball effect, as highlighted by Gerald L Barlow in "Putting a Price on Staff Turnover," where low staff morale negatively affects productivity and increases turnover rates Conversely, improving staff morale by reducing turnover can enhance productivity in both quality and output.
High employee turnover leads to the loss of essential skills, experience, and corporate memory, significantly impacting a business's productivity, profitability, and service quality For universities, this turnover can diminish quality standards and lower morale, as former employees may spread negative perceptions, damaging the institution's reputation as an employer Consequently, this can hinder the recruitment of quality staff, exacerbating turnover issues Additionally, existing employees may struggle to perform well if they are preoccupied with job security concerns and the need to train new hires Ultimately, fostering a happy and motivated workforce is crucial, as it enhances loyalty and drives organizational success.
The performance of a university is a crucial factor in evaluating its educational quality High employee turnover raises concerns as it leads to staff discontinuity, resulting in instability and inconsistency in care This instability can adversely affect the university's operations and management.
The Factors That Influence On the Staff Turnover Rate
It seems that the relationship between supervisors and employees, also called
“employment relationship”, is one of the most important aspects which might cause the high staff turnover
A good supervisor must possess strong leadership skills and treat all employees fairly to prevent dissatisfaction, which often arises from conflicts or differing work values According to Lau Wan Ling, Elaine (2007), increased supervisory support correlates with a reduced intention of employees to leave their jobs.
In his 2006 article "Employee Turnover," Gregorio Billikopf highlights that poor worker-management relations are a significant factor in employee turnover Key issues include a lack of compatibility with herd managers and the perception that supervisors lack effective communication skills in providing directives.
Debrah (as cited in Brian Whitaker, 2010) agrees with Gregorio on the detrimental impact of poor interpersonal skills and inflexibility in supervisors, which can quickly lead to employee turnover Research indicates that the quality of relationships between supervisors and employees is crucial for fostering employee commitment Moreover, employees who lack confidence in their immediate supervisors are significantly more likely to leave the organization voluntarily.
Researchers Adedoyin Olusola Ologunde, Asaolu, and David Oladapo Elumilade highlight that poor management of work-life quality and lack of employee engagement lead to issues such as absenteeism, punctuality problems, accidents, low morale, and high labor turnover They emphasize that effective supervision is crucial for retaining employees and mitigating these negative outcomes.
Research by Naresh, Pawan, and Chong (n.d.) involving 131 employees from four companies revealed a significant link between supervisor satisfaction and turnover intention among workers in the retail and food and beverage sectors.
We believe that the relationship will hold for other jobs and industries too Thus, we develop the hypothesis as below:
H1: The relationship between Supervisors and staff has an effect on the staff turnover intention at IU
A survey conducted on Human Resource Planning & Control for the Energy Industry in Libya revealed that many respondents attribute high job turnover to substandard working conditions Key issues identified include inadequate facilities such as poor lighting, insufficient furniture, lack of restrooms, and inadequate health and safety provisions These unsatisfactory conditions lead employees to be unwilling to endure the inconveniences for an extended period.
Three researchers, Adedoyin Olusola Ologunde, Asaolu, and David Oladapo Elumilade, emphasize that working conditions significantly impact employee turnover They argue that a manager's failure to ensure fair working conditions can result in industrial unrest, strikes, and prolonged negotiations, all of which adversely affect productivity and increase labor turnover.
Researchers Rana, Tariq Mehmood, Salaria M Rashid, Herani Gobind M., and Amin Mohammad (2009) emphasize that poor working conditions significantly contribute to high employee turnover rates in organizations.
Based on the literature review and the opinions in the in-depth interview, we develop the hypothesis as below:
H2: Working conditions have an effect on the staff turnover intention at IU
Theorists assert that employees are an organization's most valuable asset, emphasizing that investing in their training and development, recognizing their performance, and engaging them in the decision-making process can significantly boost their motivation and overall performance.
Leigh Branham (2005) identifies a key factor influencing employee turnover as the lack of growth and advancement opportunities This issue is often exacerbated by barriers between departments, training that is limited to current job roles, and insufficient support for employees in establishing their career goals.
Max Messmer, chairman and CEO of Robert Half International, aligns with Branham's perspective, stating that employees are more inclined to remain with a company that invests in their training and development.
Employees require guidance and support to navigate unfamiliar roles, and a lack of training programs can hinder their performance and confidence When companies fail to invest adequately in employee training and development, it can lead to frustration, prompting workers to seek better opportunities with organizations that offer greater investment in their growth.
Brian Whitaker (2010) noted that managers often hesitate to invest in employee training due to concerns about competitors enticing trained staff away Nevertheless, research indicates that employees who do not receive training tend to switch jobs more frequently.
In his article "Reasons why high staff turnover can occur," Andrew Michaels, with two decades of experience across various businesses, highlights poor training as a significant factor contributing to high staff turnover He emphasizes that inadequate training can be incredibly demotivating for employees, as most require proper guidance to succeed in their roles Despite this, many managers continue to overlook the importance of effective training programs, leading to increased employee dissatisfaction and turnover.
In conclusion, inadequate training and development can lead employees to consider leaving their jobs Based on this premise, we propose the following hypothesis:
H3: The Training and development policy have an effect on the staff turnover intention at IU
Turnover Intention
Table 2-5 Definition of Turnover Intention
Year Author Definition of Turnover Intention
1973 Porter & Steers Retreating behavior from job dissatisfaction
1975 Kraut The best anticipation for turnover
1975 Fishbein & Ajzen The best measurement to presume the worker’s turnover behavior
1978 Mobely Idea of leaving the current organization or post
1982 Bluedorn It is differ from actual turnover behavior which is influenced by more external element
1993 Tett & Meyer Perception of a series of retreating cognitions
(Source: Hsien-Che Lee, Tsai-Hua Chuang, The Impact of Leadership Styles on Job
Stress and Turnover Intention – Taiwan Insurance Industry As an Example)
Research indicates that turnover intention, i.e., thinking about leaving one's job, is the best and most immediate predictor of turnover (Tresvil G Pack, Ronna Turner, Richard T Roessler, & Judith Robertson, 2007)
Research by Naresh, Pawan, and Chong highlights that turnover intention is frequently examined in studies on employee turnover Shore and Martin emphasize its relevance as a dependent variable due to its strong correlation with actual turnover rates Additionally, Bluedorn and James L Price advocate for using turnover intention over actual turnover, citing the challenges in predicting turnover due to various external factors influencing employee behavior.
Bedeian (as cited in Eunmi Chang, 1999) emphasized that while turnover and turnover intention are often measured separately, turnover intention serves as a crucial cognitive factor that directly influences employee turnover Mylene Perez (2008) noted that actual turnover is likely to rise in tandem with increasing turnover intention, while career factors become irrelevant when turnover intention is controlled (Eunmi Chang, 1999) These findings underscore the significance of turnover intention in understanding individual turnover behavior.
Thus, in this study, the author also considered turnover intention the dependent variable.
Research Methodology
Research Framework
The research has been conducted through 2 main periods: (1) Interviewing to build a complete questionnaire, (2) Quantitative research to collect and analyze survey data
In addition to conducting in-depth interviews, we synthesized key factors influencing staff turnover at IU based on the literature review in Chapter 2, leading to the development of a research framework illustrated in Figure 3-1.
The staff turnover at IU is influenced by seven key independent factor groups, which are analyzed in relation to the dependent variable representing staff turnover This relationship is essential for formulating and testing hypotheses, with seven specific hypotheses established to explore the connections between these two groups.
Hypothesis H1: The relationship between Supervisors and staff has an effect on the staff turnover intention at IU
Hypothesis H2: Working conditions have an effect on the staff turnover intention at IU
Hypothesis H3: The Training and development policy have an effect on the staff turnover intention at IU
Hypothesis H4: The Promotion policy has an effect on the staff turnover intention at IU
Hypothesis H5: Job stress has an effect on the staff turnover intention at IU
Hypothesis H6: The Salary policy has an effect on the staff turnover intention at
Hypothesis H7: The Benefit policy has an effect on the staff turnover intention at
Research Process
The process of research consists of these following steps, and presented in figure 3-2:
Define research matter: high staff turnover rate of
Design Research framework and questionnaire
Research methods
This study employed both qualitative and quantitative methods, beginning with in-depth interviews of two Rectors and three Heads of Personnel Administration to inform the development of a survey questionnaire Subsequently, a quantitative survey was conducted with a sample size of 81 participants This mixed-methods approach combined primary data from interviews, capturing attitudes and ideas, with survey data reflecting opinions Following data analysis, additional interviews were conducted to gain deeper insights into the results Secondary data were also collected from relevant studies, articles, journals, reports, and websites to enhance the research.
Interviews serve as primary sources of information, as noted by Vinh (2006) Building on this concept, Mohd H R Joarder and Mohamad Yazam Sharif (2011) describe in-depth interviews as a qualitative method that provides a comprehensive understanding of a situation and facilitates the exploration of intriguing topics for future research.
This project aims to investigate the factors affecting staff turnover at IU by conducting in-depth interviews with key personnel The interviewees include a Rector and four Heads of Personnel Administration Offices from universities in Ho Chi Minh City, referred to as interviewee A, B, C, D, and E These interviews took place in the interviewees' offices throughout October, gathering valuable insights and opinions on the topic.
In 2010, interviews lasting approximately 30 minutes were conducted to explore staff turnover in universities At the outset, the interviewer outlined the research objectives, sought consent from participants, and expressed gratitude for their involvement The interviewees were then prompted to discuss in detail the factors they believed contributed to employee turnover Due to the sensitive nature of the topic, participants declined permission for tape recording.
Through the investigation on the opinions of the above interviewees from the universities about basic elements affecting the staff turnover in a university, the researcher collected results as following:
Most interviewees, except Interviewee E, believe that low salaries are a significant factor contributing to employee turnover at their universities They assert that many staff members leave due to dissatisfaction with their pay Interviewees A, B, C, and D noted that younger employees, particularly recent graduates, often seek university positions primarily for experience, leaving for higher-paying opportunities shortly after Although Interviewee E acknowledged that salary dissatisfaction drives staff away, she pointed out that her university's salaries are competitive compared to others However, she criticized the salary policy for being based on education level and years of service rather than individual capability, which fails to motivate staff and encourage long-term commitment to the organization.
The relationship between supervisors and employees significantly influences staff turnover Interviewees A and B highlighted that when employees feel disrespected or undervalued by their supervisors, it can lead to serious conflicts, prompting them to leave the university swiftly.
Three interviewees, A, D, and E, identified work-related stress as a major factor contributing to staff turnover Interviewee A noted that employees struggle to maintain a balance between work and personal life, often leading to fatigue and eventual resignation when stress becomes unbearable Similarly, interviewees B and C highlighted that their colleagues experience significant pressure and heavy workloads, particularly those responsible for critical tasks requiring advanced skills This difficulty in delegating responsibilities to less experienced staff exacerbates stress levels, prompting employees to leave the university.
Interviewees C and D highlighted the impact of working conditions on employee turnover at universities Interviewee D noted that her university's facilities fail to meet staff needs, while Interviewee C reported dissatisfaction among her colleagues regarding outdated and inconvenient equipment compared to other institutions Ultimately, both interviewees agreed that inadequate working conditions could significantly contribute to staff turnover intentions.
Interviewee B highlighted the significance of training and development, noting that many employees cited insufficient training in their exit interviews as a reason for leaving Additionally, Interviewee E pointed out that the promotion policy at her university contributes to employee dissatisfaction; when staff perceive limited opportunities for advancement, they are more likely to seek better job prospects elsewhere.
Interviewee D highlighted that inadequate benefits are a significant factor driving staff to leave the university While some employees do not voice concerns about their salaries, recognizing the difficulty in changing them, they express dissatisfaction with the university's benefits policy, particularly regarding bonuses during national occasions and overtime allowances.
In summary, after collecting the ideas, the study modifies variables for the questionnaire They are 7 factors that may have effects on the staff turnover of the university:
The survey aimed to investigate the factors influencing staff turnover at International University by assessing staff satisfaction across seven key areas Questionnaires were distributed to all full-time employees, who were informed about the study's purpose, ensuring confidentiality of their names and contact details.
The researcher distributed survey forms directly to each staff member, accompanied by an explanation of the study These forms were either handed out by the author herself or by her acquaintances The collected data was then entered into a database for further analysis.
The follow-up interviews aim to provide a deeper understanding of the findings from data analysis regarding staff turnover The interviews will include insights from one staff member with two years of experience at IU and three former employees who worked there for about a year before leaving By gathering their perspectives, the author seeks to enrich the understanding of the significant factors influencing staff turnover, in relation to the initial research results.
Designing the Questions
The questions for the in-depth interview were designed to find out what factors affect on the staff turnover at universities
The questionnaire was designed with two parts as below:
The initial section focused on collecting general information from participants through multiple-choice questions that assess their demographics, specifically targeting the age of the respondents.
(2) The gender of the respondent; (3) The year of working of the respondent; (4) The education level of the respondents; and (5) The monthly income of the respondent
The second part of the study aimed to assess satisfaction across seven key factors, utilizing a questionnaire developed from a thorough literature review To effectively measure the satisfaction levels of IU staff, a 5-point Likert scale was implemented, ranging from strongly disagree (1) to strongly agree (5) (Hair et al., 2003) Table 3-1 provides references for the items included in the developed questionnaire.
Table 3-1 The Questionnaire Constructs with References
Hieu (2007), Public Service Secretariat (2007/08), , Stanton & Crossley (2000) manager cares about staff’s feeing about work work with current manager is convenient supervisors assigns work fairly supervisor’s repertoire of skills Job stress
Iqtidar Ali Shah, Zainab fakhr, M Shakil Ahmad, Khalid Zaman (2010), Hieu
(2007), Public Service Secretariat (2007/08), job responsibilities relationship with others overload work stress at work, tired to enjoy family life
Physical aspects of the work environment
Public Service Secretariat (2007/08) proper equipments and facilitations health and safety responsibility for protecting personal health and safety in the work place
The Public Service Secretariat (2007/08) emphasizes the importance of providing appropriate and adequate training courses to enhance job performance By conducting skill development programs, the Secretariat supports work-related learning and development, facilitating staff access to continuing education opportunities.
Promotion Thanchanok Suksri (2003) aware of the university’s conditions for promotion
Working styles and characteristics of work capable, skillful and efficient staffs will certainly get promotion
Salary Minnesota satisfaction salary is compensated with
The salary policy motivates staff at work get salary raise when performing well Benefits Stanton & Crossley (2000) good benefits
IU’s sponsored money for further study of their staff social insurance and health insurance is well performed prize money Turnover
Michigan Organizational Assessment questionnaire ; Cummann et al (1979)
As soon as I can find a better job will I quit at this organization
You will probably look for a job at a different company in the next year
You often think about quitting my job
There were seven groups of questions developed in the questionnaire:
Group 1 (questions 1-4): aim to know about the perception of the staff towards their supervisors
Group 2 (questions 5-7): aim to know perception of the staff towards the working environment of the IU
Group 3 (questions 8-12): aim to know perception of the staff towards the training and development policy of the IU
Group 4 (questions 13-15): aim to know perception of the staff towards the promotion policy of the IU
Group 5 (questions 16-19): aim to know perception of the staff towards the job stress when working at the IU
Group 6 (questions 20-22): aim to know perception of the staff towards the salary policy of the IU
Group 7 (questions 23-26): aim to know perception of the staff towards the benefit policy of the IU
After being designed, the questionnaires were sent to three academic experts: one senior manager in IU and two Doctors of School of Business Administration in
IU so that they evaluate the structure and validity of the content
Some items in the questionnaires were revised for better clarity when the designers received feedbacks from those experts
The researchers raised questions based on the research results such as “What”,
“Why”, “How” about the factors affecting the decision to leave the University of the participants.
Validity and Reliability
To ensure the reliability and validity of the questionnaires, the study employed Cronbach’s Alpha test using SPSS 15.0 software According to Hair, Babin, Money, and Samouel (as cited in Vinh, 2006 and Hoa, 2009), a Cronbach’s Alpha value greater than 0.7 is deemed “acceptable.” Consequently, if the results meet this threshold, the reliability of the questions will be confirmed, as illustrated in Table 3.
The researcher made the experts’ validity by asking two academic research experts, one in IU and one in another university
Table 3-2 Reliability of the Questionnaire (Detail in the Attachment)
Physical aspects of the work environment b3 961 c1 960 c2 960 c3 960 c4 960
Table 3-2 indicates that the Cronbach’s Alpha values for each sub-factor and the overall value exceed 0.7, confirming the reliability of all questionnaire items With a total of 76 questionnaires collected, the data was coded and analyzed using SPSS 15.0 software, with detailed findings to be discussed in Chapter 4.
Sampling Design
Through a private connection facilitated by the Director of the Institute for Human Resource Training and Development, the author successfully conducted interviews with a university Rector in Ho Chi Minh City and four Heads of Personnel Administration offices.
In October 2010, five comprehensive interviews were conducted to investigate the factors influencing staff turnover at a university, specifically focusing on IU.
Based on population size choosing method examined by Robert V Krejcie & Daryle W Morgan (cited in Phi, 2009), the researcher chooses the research samples following the formula:
X 2 = the Figure value of chi – square for 1 degree of freedom at the desired confidence level (3.8411)
P = the population proportion (assumed to be 50 since this would provide the maximum sample size) d = the degree of accuracy expressed as a proportion (.50)
According to the sample size determination table by Robert V Krejcie and Daryle W Morgan (1970), the total staff at IU is 81, leading to a research population of 66 The author distributed 81 questionnaires to gather insights from all IU staff regarding the factors influencing their turnover Ultimately, 76 completed questionnaires were returned, resulting in a response rate of 93.82%.
76 full filled questionnaires for the study, the author will process them with SPSS software in 15.0 version This part will be presented clearly in chapter 4.
Data Collection
The questionnaires were sent to all the staff of IU through 2 ways:
- Sending directly to the staffs who are friends or have a close relationship with the author of the research
- Having the left questionnaires delivered to the other employee by the above staff
Then, the researcher collected the answers after 1 week
In this study, in-depth interviews were conducted with participants who declined to be recorded, resulting in all data being meticulously noted Each interview lasted approximately 30 minutes, and the collected content served as primary data for subsequent qualitative analysis.
The follow-up interview, lasting just 15 minutes, focused on the author's strong connections with four former IU staff members Due to these close relationships, the researchers arranged in-person meetings with three of the ex-employees at local coffee shops and conducted a phone interview with the fourth, meticulously recording the gathered information.
The analysis of data gathered from questionnaires will be conducted using SPSS Software, Version 15, to identify the factors influencing staff turnover at IU This will involve employing descriptive statistics, frequency tables, and reliability checks, along with factor analysis to evaluate the seven proposed hypotheses.
Exploratory Factor Analysis (EFA) is a statistical method used to examine the relationships between numerous variables and to interpret them through their common underlying factors This technique condenses information from a large set of original variables into fewer dimensions, or factors, while minimizing information loss (Hair et al., 1992).
Exploratory factor analysis (EFA) is a widely used statistical technique in the social sciences, as highlighted by Costello and Osborne (2005) Their research demonstrates various applications of EFA, including its role in identifying the types of services that should be provided to college students.
In "Understanding Factor Analysis," R.J Rummel (1970) explains that factor analysis is a valuable tool for exploring content areas, classifying or reducing data, defining relationships, and testing hypotheses related to dimensions of attitude, personality, social behavior, voting, and conflict The term "dimension" typically refers to a cluster of interrelated characteristics or behaviors, making factor analysis essential for empirically validating their existence.
This study investigates the influence of seven assumed factors on staff turnover intention at IU and assesses their impact levels The author employs exploratory factor analysis to examine the interrelationships among twenty-nine variables, ultimately condensing the information into a more manageable set of factors for further analysis to meet the thesis objectives.
In Exploratory Factor Analysis (EFA), Principal Component Analysis (PCA) serves as the primary extraction method, recognized for its ability to identify linear combinations of variables that capture the maximum variance This technique systematically removes the extracted variance and continues to seek subsequent linear combinations that account for the highest proportion of the remaining variance (Lester, 2006; Camelio & Heichelbech, 2009).
Research Results and Analysis
Descriptive Data Statistics
Description statistical analysis of data was used to know more about personal information of IU’s staff, the result of table shows statistical analysis descriptive figure in the survey
Table 4-1 The Sum of Coded Scales
1 a1 The manager cares how I really feel about my work
2 a2 I feel that it is convenient to work with my current manager
3 a3 My supervisor assigns work fairly
4 a4 I have confidence in my supervisor because of his/her repertoire of skills
B Physical aspects of the work environment
5 b1 I have proper equipments and facilitations at work
6 b2 The university is committed to ensure the health and safety of its employees
7 b3 I am aware of my role and responsibility for protecting my personal health and safety in the work place
8 c1 I get the training I need to do my job
9 c2 The university provides me with appropriate and adequate training courses
10 c3 IU emphasizes on skill development programs
11 c4 The university supports my work-related learning and development
12 c5 IU facilitates staffs to continuing education
13 d1 I know the university’s conditions for promotion
14 d2 Working styles and characteristics of work in my department are challenging and encouraging so that I can continuously learn new
No Code Items things through my work
15 d3 Staffs who are capable, skillful and efficient in the university will certainly get promotion
16 e1 My job responsibilities are not clear to me
17 e2 To satisfy some people at my job, I have to upset others
18 e3 It seems to me that I have more work at my job that I can handle
19 e4 I often get stress at work and that makes me too tired to enjoy family life
20 f1 My salary is compensated with my ability and responsibility
21 f2 The salary policy motivates me at work
22 f3 I will surely get salary raise if I perform well
23 g1 The university has good benefit
24 g2 I am satisfied with the IU’s sponsored money for further study of their staff
25 g3 The university performs social insurance and health insurance well
26 g4 I am satisfied with prize money from the university
27 h1 As soon as I can find a better job will I quit at this organization
28 h2 You will probably look for a job at a different company in the next year
29 h3 You often think about quitting my job
Table 4-2 Descriptive Statistics Analysis of Gender
In 76 questionnaires, the proportion of male and female are rather equal, including 104 men (52%) and 96 women (48%)
Table 4-3 Descriptive Statistics Analysis of Age
The data reveals that 64.5% of employees at IU are aged between 21 and 35, highlighting a predominantly young workforce primarily composed of recent university graduates entering the job market.
4.1.3 Result of year of working
Table 4-4 Descriptive Statistics Analysis of Working Year
Looking at the table, we can find that most of the staffs have worked for
IU less than 1 year (50%) As we found out in Chapter 2, the staff turnover rate of IU is high through each year, so this result is entirely reasonable
Table 4-5 Descriptive Statistics Analysis of Education
According to statistics, 65.8% of the employees have university or post graduate degree and 34.2% have college or training degree The reason is that
IU is an international university, so it requires the level and knowledge for the job highly
Table 4-6 Descriptive Statistics Analysis of Monthly Income
Table 4-6 reveals that staff earning between 5 million VND and less than 7 million VND per month constitute the highest percentage at 48.7% Conversely, those with monthly incomes exceeding 7 million VND represent the lowest percentage This pattern indicates that staff income correlates with their educational qualifications and tenure at the university Consequently, it is logical that the majority of staff hold a university degree, while those with postgraduate degrees are in the minority.
Table 4-7 The Result of Quantitative Variable Descriptive
Deviation The manager cares how I really feel about my work 1 5 3.33 719
I feel that it is convenient to work with my current manager 2 5 3.45 755
My supervisor assigns work fairly 2 5 3.61 655
I have confidence in my supervisor because of his/her repertoire of skills 2 5 3.93 660
I have proper equipments and facilitations at work 3 5 4.09 696
The university is committed to ensure the health and safety of its employees 2 5 3.84 767
I am aware of my role and responsibility for protecting my personal health and safety in the work
I get the training I need to do my job 1 5 3.93 699 The university provides me with appropriate and adequate training courses 3 5 3.99 622
IU emphasizes on skill development programs 3 5 3.97 610
The university supports my work- related learning and development 3 5 4.61 591
IU facilitates staffs to continuing education 3 5 4.14 706
I know the university's conditions for promotion 2 5 4.75 545
Working styles and characteristics of work in my department are challenging and encouraging so that I can continuously learn new things through my work
Staffs who are capable, skillful and efficient in the university will certainly get promotion
My job responsibilities are not clear to me 1 5 4.04 916
To satisfy some people at my job, I have to upset others 1 5 3.91 1.098
It seems to me that I have more work at my job that I can handle 1 5 4.05 847
I often get stress at work and that makes me too tired to enjoy family life
My salary is compensated with my ability and responsibility 2 5 3.84 880
The salary policy motivates me at work 2 5 4.62 711
I will surely get salary raise if I perform well 2 5 4.59 769
The university has good benefit 2 5 3.93 699
I am satisfied with the IU's I am satisfied with the IU’s sponsored money for further study of the staff 3 5 4.14 706
The university performs social insurance and health insurance well 1 5 3.38 1.019
I am satisfied with prize money from the university 3 5 4.75 465
As soon as I can find a better job will
You will probably look for a job at a different company in the next year 2 5 3.84 731
You often think about quitting my job 2 5 3.99 808
Exploratory Factor Analysis
4.2.1 Test the reliabilities of variables
Chapter 3 demonstrates that the Cronbach's Alpha for all variables is 0.962, with each individual variable exceeding the acceptable threshold of 0.7, confirming the reliability of the questionnaire items for factor analysis.
4.2.2 Analyze to check hypotheses by exploratory factor analysis
In Exploratory Factor Analysis (EFA), the initial step involves assessing the data's suitability for factor analysis, as it is crucial for researchers to confirm that the data matrix exhibits adequate correlation to validate the use of this statistical method (Hoang Trong, 2006).
Hoang Trong (2006) utilized Bartlett’s test of sphericity to assess variable correlations, while the Kaiser-Meyer-Olkin (KMO) coefficient indicates the adequacy of these correlations for conducting Exploratory Factor Analysis (EFA) A significance level of less than 0.05 in Bartlett’s test, along with a KMO value between 0.5 and 1, confirms that factor analysis is appropriate and valid.
Factor loading is a crucial indicator in Exploratory Factor Analysis (EFA) as it helps interpret the significance of each variable in defining factors (Sara Faraji Jalal, 2007) It reflects the relative importance of each item to its corresponding factor (James Neill, 2010) According to Hair & CTG (1998), factor loadings are essential for ensuring the practical significance of EFA, with a recommended threshold of > 0.75 for sample sizes around 50.
Hair et al (as cited in Sara Faraji Jalal, 2007) suggest that researchers should avoid factor analysis with samples smaller than 50 observations, ideally using a sample size of 100 or more This study, however, includes a sample size of 76, which is derived from a total staff of 81 at IU According to the results presented in Table 4.13, five items—c4, b2, a4, f1, and g4—showed specific factor loadings.
< 0.75 (0.608, 0.651, 0.551, 0.657, and 0.540, respectively), all the left variables ensure the practical significance of the EFA with the factor loading > 0.75
When evaluating factor analysis, two key indicators to consider are Total Variance Explained and Eigenvalue A robust factor solution, as noted by James Neill (2010), is one that maximizes variance explanation with the least number of factors Hair et al (1998) suggest that the Total Variance Explained should be at least 50% Additionally, eigenvalues indicate the variation each factor accounts for in the total sample (HishamMB, 2008) A high ratio of explanatory importance among factors is indicated when eigenvalues exceed 1 (Hair et al.).
1998) The "eigenvalue greater than 1" criterion is also a good rule of thumb for determining the number of factors
4.2.2.1 The first exploratory factor analysis
Table 4-8 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling
Table 4-9 Result of the Relationship between Components and Variables
Initial Eigenvalues Extraction Sums of Squared
Loadings Rotation Sums of Squared Loadings Component
Extraction Method: Principal Component Analysis
Table 4-10 Result of Component Loadings
Job stress Promotion Supervisors Salary c1 863 c2 835 c3 830 b1 733 g2 698 c5 687 c4 614 e1 844 e2 817 e4 780 e3 713 d2 848 d1 836 d3 775 b2 656 a1 855 a3 832 a2 791 a4 567 f3 833 f2 830 f1 617 g4 570
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization
According to the result of table 4-8, KMO = 0.859 (0.5=
50 % This result shows that five factors explain 78.132% of the variance in the items
Table 4-10 reveals that 26 observed variables belong in five factors in which three items b3, g3, g1 were removed from EFA because of the Factor Loading < 0.5
Following the results of the initial Exploratory Factor Analysis (EFA), we proceeded to conduct the final EFA The findings from this second EFA are presented in the tables below.
4.2.2.2 The second exploratory factor analysis
Table 4-11 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling
Table 4-12 Result for the Relationship between Components and Variables
Initial Eigenvalues Extraction Sums of Squared
Loadings Rotation Sums of Squared
Extraction Method: Principal Component Analysis
Table 4-13 Result of Component Loadings
Development Job stress Promotion Supervisors Salary c1 858 c2 839 c3 828 b1 740 g2 710 c5 707 c4 608 e1 858 e2 806 e4 804 e3 704 d2 858 d1 842 d3 786 b2 651 a1 872 a3 841 a2 789 a4 551 f3 826 f2 819 f1 657 g4 540
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization
According to the result of table 4-11, KMO = 0.862 (0.5= 0.5
The next step was to name the new five factors
Table 4-14 Factors Grouped and Named
Factors Variables Name of factors c1 c2 c3 b1 g2 c5
The EFA results indicate that five independent factors significantly influence turnover intention: training and development, job stress, promotion, supervisors, and salary Conversely, working conditions and benefits do not impact employee turnover intention at IU Consequently, we accept Hypotheses H1, H3, H4, H5, and H6, while rejecting Hypotheses H2 and H7.
In summary, after the factor analysis, the research model should be modified as the following figure:
Figure 3-3 Research Model Then based on the results achieved from the EFA, the researcher proceed other analyses to examine the impact level of the above five factors
Correlation and Regression Analysis on the Impact of the Five Factors on the
4.3.1 Correlation analysis with pearson coefficients
Table 4-15 Result of Linear Relationship between Variables
** Correlation is significant at the 0.01 level (2-tailed)
The table 4-15 shows that variable Y has correlations with variables Xi (i=1 ->
A correlation coefficient of R -> +1 signifies a strong positive linear relationship between turnover intention (variable Y) and five key factors: supervisors, promotion opportunities, training and development, job stress, and salary.
The analysis reveals that X1 exhibits the strongest correlation with Y (R = 0.705), followed by X2 with a correlation of R = 0.680, and X3 at R = 0.609 X4 shows a correlation of R = 0.558, while X5 has the weakest correlation at R = 0.536 The findings indicate that among the five factors assessed, "supervisors" significantly influences turnover intention, with promotion, training and development, and job stress following in decreasing order of impact, while salary has the least effect on turnover intention.
4.3.2 Linear correlation and regression analysis
Table 4-16 Result of Linear Relationship between Variables
Table 4-17 Result of Variables Entered
X1 Stepwise (Criteria: Probability-of-F-to-enter = 100).
X2 Stepwise (Criteria: Probability-of-F-to-enter = 100).
X4 Stepwise (Criteria: Probability-of-F-to-enter = 100). a Dependent Variable: Y
R Square Std Error of the
3 828(c) 686 673 3490 1.513 a Predictors: (Constant), X1 b Predictors: (Constant), X1, X2 c Predictors: (Constant), X1, X2, X4 d Dependent Variable: Y
The above table shows that the model of regression has Adjusted R Square
= 686 which can explain that about 68% of changes of Y (or turnover intention) is due to influences of 3 constants X1 (Supervisors), X2 (Promotion), and X3 (Job stress)
Table 4-19 The Result of ANOVA
Total 27.924 75 a Predictors: (Constant), X1 b Predictors: (Constant), X1, X2 c Predictors: (Constant), X1, X2, X4 d Dependent Variable: Y
Table 4-20 The Result for Coefficient of Three Variables
B Std Error Beta Tolerance VIF
Table 4-19 reveals that the significance levels of variables X1, X2, and X4 are below 0.05, indicating meaningful correlations among these three variables Consequently, X1, X2, and X3 were included in the regression model Upon analyzing the relationship between each variable and Y, it was found that all five variables influence Y However, the correlations of X3 and X5 with Y weakened in the regression context, leading to their exclusion from the model.
According to Trong and Ngoc (2008), a regression model is considered appropriate if the Tolerance coefficient exceeds 0.0001 and the Variance Inflation Factor (VIF) is less than 2 In Table 4-20, the Tolerance coefficients for the three variables are 702, 739, and 727, all greater than 0.0001, while the VIF values are 1.425, 1.354, and 1.375, all below 2 This indicates that the model meets the necessary criteria, confirming no multicollinearity among the independent variables.
Therefore there is an equation of regression as follows:
Or we can write it this way:
Turnover intention = -0.107 + 0.443 supervisors + 0.425 promotion + 0.133 job stress + e