1. Introduction
Employee retention is becoming a major concern in organizational management. In this fierce global business competition, the shortfall of the workforce in many industrial economies has required employers to show their ability to keep employees working for their organizations to maintain business competitive advantages [
1]. However, Burke and Ng [
2] acknowledged a growing number of employees do not want to have a traditional career within one organization, possibly because they have a greater choice in pursuing careers across an increasing number of companies [
1]. Therefore, today workers seem to be more opportunistic of work opportunities and less loyal than their counterparts in the past. High employee turnover rates have been unsurprisingly witnessed in the oil and gas [
3], travel [
4], and construction industries [
5]. Companies may face substantial risks of losing confidential information to competitors since skilled employees can take a lot of know-how with them. In such a case, losing employees does not solely mean a loss of human investment but also business survival.
The construction industry plays a vital role in all national economies that employ a large proportion of employees in the labor market [
6]. As a large number of employees is required for business operation, losing such employees may lead to significant losses for recruiting and training. The review of the literature [
5] highlighted that a high labor turnover rate negatively influences organizational productivity and performance since most of the resource utilization is heavily dependent on the workforce. Employee retention then becomes necessarily important in construction firms [
5].
Unlike other industries, construction is a project-oriented [
7] and highly fragmented industry [
8]. Construction projects are naturally complex and are subject to a multitude of random internal (i.e., human resources) and external factors (i.e., political and economic factors) [
9]. Moreover, construction projects are commonly located in dispersed locations and performed independently by a unique collection of project teams. Consequently, construction workers have to change their working locations frequently. Researchers showed that workers in the construction industry normally suffer from high rates of mental health problems [
10] and on-site accidents [
11] but not all of them are offered sufficient health insurance [
12]. Moreover, construction projects are becoming more complex and challenging [
13]. Therefore, it is highly possible that employees will search for another job which provides them better work conditions.
Acknowledging the negative effects of high labor turnover rates in construction businesses, this research focuses on analyzing the determinants that influence employee retention. Basically, job satisfaction and organizational commitment increase the intention to stay of the employees and then reduce the turnover rate within organizations [
1,
14,
15]. Specifically, Currivan [
14] confirmed that workplace structure and individual characteristics-related factors affect employee satisfaction, organizational commitment, and then employee retention. To improve employee satisfaction and organizational commitment, specific factors have been identified such as improving the job environment, giving fair and competitive compensation packages, providing clear employee development plans and career growth opportunities [
5,
12,
16,
17,
18]. Although several factors may affect the level of employee retention within construction firms, the improvement of employee retention requires careful consideration of scarce organizational resources with an emphasis on the most important determinants. The identification and prioritization of employee retention determinants are heavily affected by the research context and remained a problem for decision-makers in organizations.
As stated by Coetzee and Stoltz [
19], Kim [
20], and Yamamoto [
21], the assessment and evaluation of employee retention contains multi-level and multi-factor features, so such difficulties can be considered as multiple criteria decision-making (MCDM). Among numerous MCDM methods, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) has been widely employed in previous studies with satisfactory results [
22,
23,
24,
25]. Therefore, this research applies TOPSIS to evaluate the importance weights of evaluation criteria. Previous studies noticed the different advantages of TOPSIS in the evaluation of multi-level and multi-factor features. Wang and Chang [
26] highlighted the concept of TOPSIS permits the pursuit of best alternatives for each criterion shown in a simple mathematical form. Moreover, Dandage et al. [
27] argued TOPSIS logic is rational and understandable with straightforward computation processes. Normally, decision-makers have to deal with uncertain problems under complex circumstances. These issues are understandable because the natural language to express judgment and opinion is normally uncertain, subjective, or vague [
26]. Subjectivity, uncertainty, and ambiguity usually exist in the evaluation of the employee retention process and were not easily solved until the development of Zadeh’s fuzzy sets theory [
28]. Hence, the use of TOPSIS under a fuzzy environment is reasonable to achieve the research objectives.
The above discussions show that construction firms face unique difficulties in improving the employee retention rate, which may be different from the other business sectors. Thus, it is imperative to investigate the determinants that influence employee retention in construction firms. In making its case, this study focuses on ranking determinants of employee retention of construction employees in the context of the South Korean construction industry based on their effect on two dimensions, namely, job satisfaction and organizational commitment. First, the determinants of employee retention in construction firms are identified through a review of the literature and discussions with construction employees. Second, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) is employed to rank the identified determinants. The findings of this research will provide construction firms with the prioritization of determinants of employee retention; thus, supporting the improvement of the employee retention rate to maintain business competitiveness.
The rest of the paper is organized as follows: the next section presents the literature on employee retention, determinants of employee retention, and the current status of the South Korean construction industry. This is followed by the presentation of the research methodology in
Section 3. Subsequently,
Section 4 shows the analysis of fuzzy TOPSIS to rank the determinants of employee retention. Finally,
Section 5 discusses the research findings, limitations, and proposes future research directions to enhance the understanding and knowledge of employee retention.
4. Ranking Determinants Using Fuzzy TOPSIS
Results collected from the interview stage enabled the authors to form the survey questionnaire, which intended prioritizing the importance of each determinant according to two dimensions, namely, job satisfaction and organizational commitment.
Fuzzy TOPSIS was employed to analyze the collected data. It is worth noticing that in this research, the alternatives are eight employee retention determinants and the criteria are job satisfaction and organizational commitment. The following steps should be noted. This section is divided by subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn.
4.1. Step One
Introducing the membership function of the alternatives and criteria. In this paper, the linguistic terms and their corresponding membership functions of the alternatives and criteria are illustrated in
Table 1.
4.2. Step Two
Assigning linguistic terms to the alternatives and criteria. Seventy-two respondents in different South Korean contractors agreed to participate in the questionnaire survey.
Table 2 presents the information of these respondents.
The list of employee retention determinants and dimensions was provided to the respondents. They were asked to assign the linguistic terms to the given criteria and alternatives.
4.3. Step Three
Constructing the aggregated fuzzy weights for the criteria and alternatives. The collected assessments of linguistic terms of criteria and alternatives were then translated into membership functions presented in
Table 1. The outputs were used to calculate the aggregated fuzzy weights for the criteria and alternatives. First, the aggregated fuzzy weights for the criteria is defined as follows:
where:
is the weight of jth criterion
The fuzzy decision matrix of the criteria (
) is presented as follow:
Second, the aggregated fuzzy weights for the alternatives is defined as follow:
where:
is the aggregated fuzzy rating
of
criteria within each alternative.
The fuzzy decision matrix of the alternatives (
) is presented as follow:
The aggregated fuzzy weights of criteria and ratings of alternatives are computed and presented in
Table 3 and
Table 4.
4.4. Step Four
Calculating the normalized fuzzy decision matrix. The normalized fuzzy decision matrix for alternatives is calculated by the following formulation and illustrated in
Table 5:
where:
For example, the normalized decision matrix of alternatives employee income in criteria job satisfaction is computed as:
4.5. Step Five
Generating the weighted normalized matrix. The weighted normalized matrix was then identified as follow:
where:
For example, the weighted normalized matrix of alternatives employee income in criteria job satisfaction is computed as:
Table 6 illustrates the weighted normalized matrix.
4.6. Step Six
Determining the distance of each alternative from FPISs and FNISs. The fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS) are generated as follow:
The distance of each alternative from FPISs and FNISs are then computed and presented in
Table 7 as follows:
where: d(..) refers to the distance between two triangular fuzzy numbers
and
, calculated by the following formula:
Taking alternatives employee income in criteria job satisfaction as an example:
4.7. Step Seven
Determining the closeness coefficient
and ranking the alternatives. The alternatives are prioritized based on the values of
. The alternative that has the highest
value is the most important option. The closeness coefficient
of each alternative is defined and calculated (
Table 8) as follows:
For example, the ranking of alternative employee income is calculated as:
The results of fuzzy TOPSIS analysis revealed that personal characteristics are the most critical factor that affects employee retention in South Korean construction firms. This was followed by personal development, promotion opportunities, and work-life balance, respectively. Meanwhile, company images and development, work environment, employee welfare, and employee income were the least affecting factors towards employee retention.
5. Discussion and Conclusions
It is noticeable that employee income ranked the lowest importance in comparison with the other determinants. As a developed country, South Korean workers are well-protected by the laws [
20]. In 2021, the minimum hourly wage has been set at
$7.23, increasing by 1.5% from 2020 [
67]. This minimum wage is applied to any worker in any business sector. Thus, a construction worker typically earns more than
$2,000 per month [
67]. On a national level, it is estimated a family of four can expect to spend an average of
$2,000 per month [
68]. As to Maslow’s needs hierarchy theory [
69], because this amount of money is sufficient for the basic needs (i.e., physiological needs), construction workers will value other aspects such as working conditions, social security insurance, and affiliation to an organization [
43]. Meanwhile, previous studies, focused on developing context, witnessed a critical role that employee income plays in employee retention [
15,
34,
35].
According to Maslow’s five basic needs [
69], when an employee has fulfilled a self-development opportunity (i.e., social needs), they may value a working environment that provides a high possibility of growth. In particular, they will expect to be participated in the organization’s decision-making process, thus showing their social status. At the highest level of Maslow’s needs hierarchy, employees demand that their personality is fit with their job characteristics and working environment to achieve self-actualization [
43]. Thus, it is understandable that personal characteristics became the most crucial factor that affects employee retention in the South Korean context. This finding is also supported by the statement of Ayodele et al. [
5] that personal (employee) characteristics are the most frequently mentioned factor associated with the individual workforce that affects workforce turnover in the construction sector.
Through reviewing the literature and discussions with construction professionals, this study identifies eight significant determinants of employee retention in the context of the South Korean construction industry. The fuzzy TOPSIS method is successfully employed to assess and prioritize eight determinants of employee retention in regards to two dimensions, job satisfaction, and organizational commitment. The findings highlight that personal characteristics are the most critical determinants of employee retention in South Korean construction firms, followed by personal development, promotion opportunities, and work-life balance, company image and development, work environment, employee welfare, and employee income, respectively. Additionally, the proposed framework presented in
Figure 1 is another finding of this study that proposes a comprehensive methodology in assessing determinants of employee retention. Finally, it results that fuzzy TOPSIS can be employed in human resources management multiple criteria decision-making problems with several advantages over other techniques of prioritization.
In terms of managerial implications, this paper contributes to human resources management by investigating the determinant of employee retention in South Korean construction firms. The analysis highlighted that South Korean construction firms should carefully examine employee characteristics before hiring and positioning important positions within their organizations to increase employee retention rates. Furthermore, they should provide their employees with sufficient training to satisfy employees’ demand for personal development. Specifically, South Korean construction firms are suggested to increase human capital investment through different employee training programs, such as safety (i.e., site supervisor safety training), technical training (i.e., Building Information Modelling), and soft skills (i.e., leadership, teamwork, and communication). Moreover, potential promotion opportunities should be also provided which plays a significant role in the achievement of sustainable employee retention in South Korean construction companies.
Although the research objectives were achieved, this research had the following limitations. First, this research only focused on the context of South Korean contractors. Thus, different business contexts, working environments, and cultural backgrounds may generate different findings. Second, while the list of determinants of employee retention was investigated from the careful literature review and validated by experienced experts, this research was unable to encompass all determinants pertaining to employee retention considering the uncertainties of the dynamic business environment. Consequently, future studies are encouraged to employ the methodology presented in this research to investigate the most relevant determinants of employee retention and assess the importance of these variables within different research contexts. Moreover, future studies should be implemented in the contexts of developing countries to compare the results of this research. The comparisons will provide comprehensive illustrations regarding the differences in human resources management practices between developed and developing countries.