research methodology employee retention project

A Study on Employee Retention as a Tool for Improving Organizational Effectiveness

International Journal of Management, Technology, and Social Sciences (IJMTS), 6(2), 121-132. ISSN: 2581-6012. 2021

12 Pages Posted: 11 Dec 2021

Nethravathi P. S.

Srinivas University

P. S. Aithal

Poornaprajna College

Gayathri Babu J.

Shree Devi Institute of Technology, Mangaluru, 574142, India

Sonia Soans

University of Technology and Applied Sciences

Honey Jayaraj

Date Written: September 30, 2021

Background/Purpose: Human sources are those who make the group of workers of a company. It's also recognized via manpower, skills, labour, employees, etc. Human Resource department of a business enterprise performs human useful resource control. It entails various elements of the employment consisting of compliance with labour regulation and employment standards, management of worker benefits, and various other sports related to recruitment and choice of the employee. Worker retention is regarding the efforts with the aid of which employers try and retain the personnel in their team of workers. Retention turns into the strategies in place of the final results. Preserving the worker for long duration of time is known as retention. Retention strategies of the organization need to have the capacity to attract and hold their staff. Organizational effectiveness refers to a company's ability to achieve the goals it sets out to achieve. It's far the performance of the organization, group or an organization to fulfill its goal. Six Sigma is a methodology that makes a specialty of improving the overall efficiency of a business process. Objective: This work is carried out at Dinesh Foods, Kannur. Dinesh foods are a subsidiary unit of Kerala Dinesh Beedi Workers Co-op Society. The objective of this study is to observe and to recognize how worker retention facilitates in growing the organizational effectiveness of Dinesh Foods. It additionally assists to investigate diverse retention techniques followed and also the employee turnover within the unit. This work investigates the worker retention is a device for increasing the organizational effectiveness. Design/Methodology/Approach: For the purpose of study the data was collected through primary and secondary source. Questionnaire was distributed among the workers for collecting necessary data for the study, financial statement of the company to study about the financial stability of the organisation and annual report of the company. Findings/Results: This research is done to find out whether the employee retention in the organisation helps in improving the organisational effectiveness. Varies conditions applied for the hypothesis and it can be proved that the employee retention is a tool for increasing the organisational effectiveness. Based on the analysis, findings and suggestions Dinesh Foods, Kannur can give more concentration towards retaining the employees in the organisation as it is important in any organization. Conclusion: This study focusses on whether employee retention is a tool for improving the organisational effectiveness. It is found that the employee retention is a tool for improving organisational effectiveness and employee retention helps in increasing the productivity.

Keywords: Human Resource, Organizational effectiveness, Business Enterprise, Employee Retention, Financial Stability.

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An employee retention model using organizational network analysis for voluntary turnover

Sundus younis.

1 University of Engineering and Technology (UET), Taxila, Pakistan

2 Chifley Business School, Torrens University, Adelaide, SA Australia

Fiona M. Chatteur

3 Billy Blue College of Design, Torrens University, Sydney, NSW Australia

Contemporary research of employee social network analysis has grown far beyond the conventional wisdom of network and turnover theory; however, what is missing is a comprehensive review highlighting new perspectives and network constructs from a retention viewpoint. Since turnover is a concurrent component of retention, the analysis of the factors of quit propensity can result in a pre-emptive strategy for retention. This paper aims to capture the current state of the field and proposes a conceptual model for retention by exploring network position, centrality measures, network type, and the snowball effect. We identified 30 papers exploring voluntary turnover in social network constructs. Findings show that central network position is not always associated with negative turnover. Eigenvector, structural holes, and K-shell also prove to be a strong predictor of turnover. The snowball turnover of employees in similar network positions is pronounced in scenarios where employee sentiment is negative with poor group efficacy, entrepreneurship, and group values. This paper focuses on several themes to coalesce different determinants of an organizational network to demonstrate how social network theory has evolved to predict employee turnover. The resulting conceptual model suggests how to identify star performers and propose retention strategies.

Introduction

In today’s business environment, employees are considered to be the key intellectual asset (Albrecht et al. 2015 ); attracting and retaining them are crucial for knowledge-intensive industries (Deery and Jago 2015 ; Joo et al. 2015 ). However, voluntary exit of these employees takes a huge toll on the organizational success of a company. Since turnover is a concurrent component of retention (Holtom et al. 2008 ; Li et al. 2016 ; Mobley 1977 ), by analyzing the factors contributing toward quit propensity, a pre-emptive strategy to retain employees for a longer duration can be devised. Traditional approaches of human resource management (HRM) for turnover and retention have primarily focused on individual-level predictors such as job stress, unequal treatment, inadequate pay, or alternate job opportunities (Hom et al. 2017 ). However, there are other factors involved such as organizational networks (ON) or employee social networks which have a great impact on an employee’s turnover decision. Literature suggests that the structural characteristics of these organizational networks such as network density, group cohesiveness, and network centrality are hypothesized to influence an employee’s turnover intent (Gao et al. 2019 ; Ho et al. 2006 ). The main focus of this review paper revolves around how the structural attributes of the organizational networks have shaped an employee’s turnover decision in the past and at present to demonstrate how the network theory has evolved, based on the identified network constructs formulate an employee retention conceptual model.

Network literature reveals that the contemporary research of organizational network analysis of employees has grown far beyond the conventional wisdom of network and turnover theory introducing new perspectives and new constructs (Ballinger et al. 2016 ; Gopalakrishnan et al. 2013 ). However, as the field is growing, the change has not yet been properly encompassed in any recent systematic review to reflect how network theory has progressed with respect to turnover. There is a need to organize what has been done and identify themes accordingly so that new theory can be built upon the old.

Upon investigating the past studies, most of the earlier network research states that the more social connections an employee has or more central they are in their professional network, more contented and more embedded they will feel in the organization, which leads to their reduced turnover (Feeley and Barnett 1997 ; Feeley et al. 2010 ). However, a thorough analysis of the literature suggests that it does not hold true in every situation; there are other factors involved such as social support, energetic activation, role of brokers, individual performance, etc. This “more is better” approach has been highlighted in many earlier systematic reviews; however, despite of the advancements in this field of study, no single review has gone far beyond the mantra “more is better.” There is a gap in the literature. To address this issue, a comprehensive review is required to identify all the factors associated with network constructs and turnover in order to conceptualize a diagram for employee retention.

In recent empirical studies, the network position of employees is examined with completely new perspectives such as psychological contract breach (PCB) and energetic activation (Heffernan and Rochford 2017 ; Parker and Gerbasi 2016 ; Qu et al. 2019 ). New network measures such as eigenvector centrality , k-shell scores, and structural holes are introduced to predict employee turnover (Ballinger et al. 2016 ; Renneboog and Zhao 2019 ; Yuan et al. 2016 ), which challenge the traditional concepts of social network theory.

Historically, most social network research has focused on how the network structure and an individual’s network position affects their turnover decision (Freeman 1979 ). However, an employee’s turnover intent also depends on the type of network and the snowball effect of influential employees (Hayes et al. 2006 ; Gopalakrishnan et al. 2013 ). Previous studies have so far failed to coalesce different determinants of an organizational network for predicting voluntary turnover from a retention perspective.

There does not appear to be a systematic review that investigates the complete dynamics of organizational networks for employee turnover to enhance retention by considering the favorable and unfavorable work circumstances, nor is there a conceptual model that assists HRM in determining those at risk of resigning, with a view to mitigating these risks. By understanding the new viewpoints of social network parameters at a deeper level, human resource management (HRM) can mitigate voluntary turnover of employees and devise new strategies to enhance employee retention for adopting a better knowledge management (KM) system.

The aim of this paper is to integrate all the latest developments of relational determinants of turnover which have been overlooked in the past and present a comprehensive review highlighting the new perspectives and the network constructs being investigated by the modern researchers as opposed to the conventional wisdom of network and turnover theory and propose a new retention model.

In order to achieve this, a systematic literature review has been undertaken examining four essential network components: network position, centrality measures, types of network, and snowball effect of turnover. This approach follows Jo and Ellingson’s ( 2019 ) multidisciplinary methodology of relational turnover who categorized their research on

(i) behavioral, (ii) structural, and (iii) the psychological feature of social relationships. Building on Jo & Ellingson’s relational perspective, this review incorporates the structural characteristics by investigating network position and centrality measures, behavioral characteristics by exploring types of network and psychological features by examining the snowball effect of employee voluntary turnover. This paper focuses on several themes to coalesce different parameters of an organizational network to demonstrate how social network theory has evolved to predict employee turnover and based on the findings propose a new employee retention model. In this model, we analyze the relationship between four different network parameters and turnover to assess the impact of new network constructs and to clarify the mechanism through which the new network perspectives (favorable and unfavorable scenarios) and network position are associated with employee’s intention to quit. Furthermore, in our conceptual model we identify the star performers of the organizations and suggest their retention strategies (Fig. ​ (Fig.2). 2 ). The main objectives of this review are:

An employee retention conceptual model for management decision-making

(RO1) To document recent developments in the complex heterogeneous social networks and turnover studies.

(RO2) To determine how favorable and unfavorable work circumstances influence different structural positions and network measures which contribute toward predicting employee turnover.

(RO3) To examine the existing organizational networks and the snowball effect of employee turnover on their peers.

(RO4) To illustrate how HRM can make use of these social network parameters to mitigate voluntary turnover and enhance retention by presenting a conceptual model emanating from the gap in literature.

Based on the research objectives of this study, this systematic review will help answer these research questions:

RQ1: What new themes around social network in turnover studies are being examined by contemporary researchers in terms of structural position and network centrality?

RQ2: What new constructs are being investigated?

RQ3: What are the dynamics of contemporary network theory versus the conventional wisdom of network studies?

RQ4: What are the gaps in the previous research and how they can be addressed in the future?

RQ5: Does a systematic review of social network turnover studies lead to conceptual model that inform management decision-making for enhancing employee retention?

The next section discusses the research method. Results of the study are presented in Sect.  3 . The application of SNA on turnover is explained in Sect.  4 based on different trends identified. This is followed by a detailed comparative analysis. The conceptual model is presented in Sect.  5 . The overall discussion, conclusion, and future work are discussed in Sects.  6 and 7 .

Research method

We adopted Kitchenham’s ( 2004 ) review protocol for conducting this study by first planning, organizing and then reporting the results. Using this procedure, we identified the need for carrying out this review, followed by the review protocol and presenting the results and analysis of the study. Arising from the analysis, we have developed a new conceptual model for employee retention, which synthesizes the findings of this study.

Review protocol

For extracting and analyzing the most relevant research papers for our study, a review protocol was developed, which defined the focus for the literature search and systematic review inclusion criteria. This section discusses the review protocol in detail.

Focus of our review

Our review of the application of social network analysis (SNA) for employee turnover was influenced by the importance of retaining high-quality employees for organizations (Deery and Jago 2015 ; Joo et al. 2015 ). Since turnover is a concurrent component of retention, employee retention will only be possible if organizations know the reasons why employees leave in the first place. In this regard, SNA has emerged as an important analytical tool to examine the employee interdependencies based on structural configuration of networks (Burt 2000 ; Kwon 2017 ; Yuan 2019 ), to extract useful meaning and forecast various outcomes such as turnover and thereby enhance retention. This review contributes toward the voluntary turnover and retention theory by exploring various determinants used in SNA.

Literature search

Multiple databases were searched to identify research articles and conference papers which fulfill our review criteria such as: Science Direct, IEEE Xplore, PsycINFO, Business Source, ProQuest, Scopus, and Institute for Scientific Information’s Web of Science. Many past studies have focused on employee turnover and SNA; however, for the present study only papers from the past 20 years, state-of-the-art and major contributions in this field have been discussed. We used a Boolean search strategy to explore the database using the following keywords:

• (Employee voluntary turnover OR turnover intent OR quit OR resign OR leave OR exit) AND
• (Social network analysis OR organizational network analysis OR social relationships OR social network OR workplace networks OR network analysis OR employee network OR employee relations OR network ties OR employee social networks)

Duplicate articles were identified and deleted at each iteration of the database search, and they were removed again during full-text review. We also removed any such article which was clearly unrelated to ‘SNA and employee voluntary turnover.’ The abstracts and body of the articles were also examined to identify whether social networks were used as a construct.

Further manual review was conducted to explore the bibliographies and the references. The reference sections of the selected studies were parsed to identify more relevant studies on SNA and turnover. To further refine the scope of the review, systematic reviews on turnover and SNA published in the past were examined to extract as many relevant articles from the reference section as possible for a thorough analysis.

Systematic review criteria

A research paper was eligible for this systematic review if it fulfilled the following inclusion criteria:

• Social network analysis tools and techniques were used
• Voluntary turnover or turnover intention was analyzed
• Employee turnover was discussed specifically
• The study was published in the English language
• Full text was available
• Literature was published in last 20 years (January 1999–December 2020)

This time period was chosen because this was when the application of SNA started gaining popularity in industry.

Any research paper was excluded if:

• SNA was used as a reference term, but a social network analysis was not conducted
• The principal focus of study was turnover, but SNA techniques were not applied
• Social network measures and strategies were not clearly mentioned
• The study included customer turnover instead of employee turnover
• The study included involuntary turnover by the employer or forced resignations
• The research paper itself was a review

The selected research papers were further scrutinized as follows:

• Titles and abstracts were individually reviewed
• The full manuscript was read to review the results

Study selection

The database keyword search returned a total number of 11,744 research articles. Articles not related to voluntary turnover were eliminated. Only peer-reviewed articles were considered which reduced the research results to 2300. A close study of the titles and abstracts of the identified research papers revealed 89 studies matching the review criteria, which were subject to a full text review. Following the inclusion protocol, 30 studies were considered for this comprehensive review. The identified research papers were then further scrutinized (Fig.  1 ).

Study selection protocol

Our qualitative synthesis of the literature resulted in 30 articles representing a diverse application of SNA on voluntary turnover. The most common topics discussed in past papers varied from CEO turnover, network contagion, intended, actual turnover, etc. Most of the papers ( n  = 19) were published from 2013 to 2019; remaining papers were published in earlier years (1 in 2000–2003, 5 in 2004–2007 and 5 in 2008–2012). Detailed results of this study are presented in Table ​ Table1 1 based on different categories.

Study description, sample, methodology, and network characteristics from applied SNA on turnover in the review ( N  = 30)

Most of the research papers were based in USA ( n  = 15). China was the second most dominant focus of study ( n  = 5). Few of the articles conducted their research in global firms of different regions. The remaining studies examined social networks and voluntary turnover in other countries such as (1 in Pakistan, 1 in Ireland, 1 in Netherland, 1 in Korea, and 1 in England).

Application of SNA for employee turnover

Four trends were observed when organizing the studies which were selected for this review, namely network position, centrality measures, types of networks, and snowball effect of turnover. These trends are the building blocks for carrying out an organizational network analysis (Scott 2000 ). Literature suggests that any network study essentially constitutes these network parameters, without which SNA cannot be executed. Categorizing these parameters as an individual trend helped to analyze how these individual constructs have evolved over time from conventional to contemporary research and investigate how each of these parameters influence employee turnover.

Trend one—network position

Network position is one of the fundamental concepts of SNA which provides many opportunities and constraints for the employees (Freeman 1979 ; Scott 2000 ). The structural network position of the employees is important as it can inform an individual’s decisions taken at work, such as his decision to resign or turnover intent.

The most widely investigated network positions are central , peripheral and knowledge brokers . These network positions are not dependent on the hierarchical status of the employees, rather employees at any hierarchy can benefit from their strategic positions (Burt 2005 ). Conventionally, centrally located employees are hypothesized to have quick access to peer support and other valuable resources, as a result they feel more contented, perform better, and are less likely to leave, whereas employees on the periphery have limited access to information, feel less connected toward the organization and the probability of quitting increases. Feeley ( 2000 ), Kwon ( 2017 ) and Yuan ( 2019 ), supported this argument by investigating peripheral and marginal employees in the context of the solidarity and instrumental ties. Their model suggested that employees in peripheral network positions and marginal identity are more likely to quit, whereas central employees have lower probability of turnover. These findings are also consistent with Mossholder et al. ( 2005 ).

However, recent research reveals that being in a central network position is not sufficient for a reduced turnover; there are many other factors involved, such as social support, energetic activation, performance, etc. While examining CEO turnover in the labor market, Liu ( 2014 ) found that a highly central CEO with many network ties who is a poor performer will further expand his social connectedness for exploring outside job options and will have a higher turnover probability as compared to a less central CEO. Feeley et al. ( 2010 ) hypothesized that social support plays a moderating role between network position and turnover; employees more central in the network have a better coping mechanism for job stress when they have social support from their peers. Vardaman et al. ( 2015 ) explored another aspect of network centrality and turnover by discussing the possibility of translating an employee’s intention to leave into an actual turnover suggesting that when an employee is contemplating turnover, his decision is attenuated by network centrality.

Another interesting study on energetic activation and turnover from a relational perspective was undertaken by Parker and Gerbasi ( 2016 ). Energetic activation is derived from human energy which leads to enthusiasm at work (Cross et al 2003 ; Quinn et al. 2012 ; Owens et al. 2016 ). Parker and Gerbasi ( 2016 ) argued that an employee central in his network is less likely to be dismissed from his position when his coworkers perceive him to be energizing.

Similar to the social network concept of the West, “guanxi,” a term coined for social interaction of employees in China is also gaining popularity (Law et al. 2000 ; Leung and Wong 2001 ; Wong et al. 2001 ). ‘Guanxi’ is more deeply embedded in Chinese culture as compared to the Western concept of social networks (Bian 1994 ). By investigating the network positions in guanxi networks, Hom and Xiao ( 2011 ) demonstrated that dense social networks devoid of structural holes or brokers reduce the employee turnover rate, which supports Burt’s ( 1992 ) theory of structural holes and also consistent with findings of (Feeley and Barnett 1997 ; Shaw et al. 2005 ).

A thorough analysis of literature also revealed that network positions can also determine the influence of the specific nodes on rest of the network. Ranking the core nodes of the network based on their influence is also gaining popularity. Central nodes tend to be more influential than the peripheral nodes (Yuan 2019 ). The turnover decision of influential nodes stimulates others in the network to do the same.

Historically, network position is most frequently investigated as having a direct association with turnover; however, recent literature shows that network position sometimes serves as a moderating variable as well. Based on the classic theory of network position (Brass and Burkhardt 1993 ; Burt 1992 ; Powell et al. 1996 ), a new aspect of psychological contract breach (PCB) based on higher network position and turnover was examined by Heffernan and Rochford ( 2017 ). Investigating the social networks of officers in the Irish Defense force, the researchers found that network position also serves as a moderating factor between a PCB and turnover, these results conform with the work done by Ho et al., ( 2006 ) and Burt ( 2000 ).

Contrary to the general belief in literature regarding central employees having the lowest turnover intent, recent studies show that this theory may not hold true for every situation. In scenarios when a company’s stock is expected to crash, the most central directors of the organization tend to protect their reputation rather than supporting their organization in difficult times and resign before the company stock crashes. The informational advantage is exploited in case of restatements and lawsuits to protect their own prestige (Qu et al. 2019 ).

Overall, the literature review yielded contradictory results with regard to network position and turnover. On the one hand, a central network position greatly reduces an employee’s probability of turnover; on the other hand, it also promotes employee turnover intent when circumstances are not favorable either for the employee or for the employer. Gao et al. ( 2019 ) argue that exploring the relational aspect of employee’s network centrality is inevitable for analyzing the determinants of voluntary turnover.

An analytical summary of trend one is outlined in Table ​ Table2 2 .

Analytical summary of turnover based on network position

Trend two—centrality measures

Social network analysis relies on different centrality measures in order to understand organizational network characteristics (Bonacich 1972 ; Seidman 1983 and Freeman 1979 ). Although every SNA study employs different centrality measures for analyzing organizational networks which may seem to be a repetitive pattern, this study investigates which centrality measures are most frequently used in turnover studies and how employee turnover can be predicted. The SNA measures identify the most critical nodes of the network by highlighting a unique aspect of network nodes such as degree centrality, closeness and betweenness . Despite each of these centralities measuring a different interaction pattern of an individual, these measures indicate a unique prominence of an individual in the network (Wasserman and Faust 1994 ). The studies which have used these centrality measures to predict voluntary turnover are discussed below.

In the majority of network studies (e.g., Cross et al. 2002 and Soltis et al. 2013 ), degree centrality , in-degree, and out-degree have been most widely investigated from a turnover perspective. Results of earlier research reveal that a higher degree centrality was a negative predictor of turnover. Mossholder et al. ( 2005 ) hypothesized that employees with a higher in-degree are more attached to their organization, reducing the likelihood of turnover, confirming the previous findings of Feeley ( 2000 ) and Burt ( 2001 ). However, findings of Liu ( 2014 ) negate this argument, hypothesizing that a higher degree centrality provides the employees with ease of access to outside job information which leads to a higher turnover.

Apart from degree centrality, there are other SNA measures which are used in current network studies of turnover such as K-shell scores. K-shell is a centrality measure which is used for identifying the core and peripheral individuals of the network (Seidman 1983 ). It is increasingly argued that the K-shell scores prove to be a strong predictor of turnover as compared to degree, closeness and betweenness. Adopting this network construct, Yuan et al. ( 2016 ) measured the actual action network and online social network of employees using in-degree and K-shell scores. The findings proved that employees with higher in-degree value in action networks have a higher promotion probability and they are less likely to leave, while employees with low K-shell value in action and online social networks have a higher probability to resign.

Earlier network studies have highlighted the impact of network centralities on turnover (Maertz and Griffeth 2004 ; Feeley et al. 2008 ; Soltis et al. 2013 ). Ballinger et al. ( 2016 ) employed a different approach to network centrality. They investigated voluntary turnover by utilizing social capital , eigenvector centrality , in-degree centrality and structural holes . Their findings indicate that incoming eigenvector centrality has a negative relationship with intention to quit, and job hierarchy moderates the negative relationship between structural hole and turnover. Adler and Kwon ( 2002 ) also supports this argument.

Prior research addresses closeness network centrality to be negatively associated with turnover (Wasserman and Faust 1994 ). The higher the closeness centrality, the more strongly the employee is embedded within the organization. However, as opposed to this argument, the recent research shows that a higher closeness centrality may result in a higher employee turnover in four situations: (i) strong ties outside the organization; (ii) an upcoming lawsuit against the organization; (iii) employees already seeking new job opportunities; and (iv) employees shifting their task responsibilities to their peers.

Renneboog and Zhao ( 2019 ) investigated director turnover in the labor market by measuring the closeness centralities of directors. They demonstrated that directors with higher closeness centrality have a higher probability of turnover which is consistent with the existing literature on the ‘strength of weak ties’ (Granovetter 1973 ) and brokers’ theory (Burt 2005 ). Similar results were found by (Qu et al. 2019 ); however, their argument was based on the fact that increased turnover was subject to having fear of the potential company crashes in near future. Gloor et al. ( 2017 ) investigated the communication patterns of managers based on e-mail exchange. E-mail is a good data source for exploring different relational aspects of employees at their workplace (George et al. 2014 ; Sharaff and Nagwani 2015 ; Wen et al. 2019 ). The author analyzed the closeness centrality pattern of managers who resigned and found that five months prior to resignation, managers suddenly increased the frequency of communication with others at work in terms of a higher centrality in closeness, degree, and betweenness oscillation, which suggests managers attempting to allocate their tasks to others.

Up until now, betweenness was also considered to be negatively related to turnover. However, employees who are not efficient and are not highly productive tend to have a higher turnover probability. Liu ( 2014 ) supports this argument by demonstrating that a poor performing CEO despite having a higher betweenness network measure will eventually resign.

An analytical summary of trend two is mentioned in Table ​ Table3 3 .

Analytical summary of turnover based on network centrality

Trend three—types of networks

There are many different types of networks which exist in organizations such as advice-seeking; advice-giving; friendship; work-related; and avoidance networks. These networks are quite complex and reflect varying interdependency of employees on each other (Mossholder et al. 2005 ; Parker and Gerbasi 2016 ; Scott 2000 ).

Kitts and Trowbridge ( 2007 ) examined the turnover of recruit and founder colleague networks. They argued that tie strength or cohesiveness of colleague networks in the current workplace increases with the voluntary turnover of employees, extending Harrison and Carroll’s ( 2002 ) model of employee cohesiveness in organizational networks. Moynihan and Pandey ( 2008 ) examined how intra-organizational networks shape an individual’s decision to leave. They hypothesized that employees who form strong intra-organizational ties and Person–organization fit (P–O) tend to stay longer in the organization and employees having strong ties outside the organization tend to leave early. Their findings were consistent with Elfenbein and O’Reilly’s ( 2007 ) research.

Similar results were obtained by Feeley et al. ( 2008 ), who studied turnover in a friendship network in a fast-food restaurant. In-degree and out-degree centrality scores were measured by using UCINET [VI] software as stated in Borgatti et al. ( 2002 ). Data analysis revealed that turnover variance was strongly correlated with friendship networks.

Maertz and Griffeth ( 2004 ) conducted important social network research on an advice network and an employee’s intention to quit. They hypothesized that distributive justice, defined as perceived fairness of reward among employees, plays a mediating role between advice-giving ties and intention to quit. Employees who are frequently approached for advice by their colleagues feel they are burdened and their intention to quit increases if their efforts are not recognized and rewarded accordingly (see Table ​ Table4 4 ).

Analytical summary of turnover based on workplace networks

Extending the work done by Feeley et al. ( 2008 ) on friendship networks and turnover, Vardaman et al. ( 2018 ) examined the simmelian ties of organizational identification in a family-owned firm. The findings suggested that non-family employees’ turnover rate is reduced when they have higher centrality in the friendship network of family employees as compared to non-family employees. This argument of organizational identification is also supported in other research (Ashforth and Schinoff 2016 ; Mitchell et al. 2001 ).

Another aspect of relational ties in the workplace was explored by Haq et al. ( 2017 ) who examined interpersonal dislikes and conflicting ties. They found that dislike among colleagues at a workplace is positively related to turnover intention while conflicting ties do not have a significant impact on turnover intention. Since workplace social networks are not only limited to professional, advice and friendship relations, they are multifaceted, comprising of positive and negative ties (Everett and Borgatti 2014 ; Labianca 2014 ). Positive ties arise from mutual trust, friendliness and feeling of belongingness, whereas dislike, avoidance, and conflict give rise to negative ties (Labianca and Brass 2006 ; Haq et al. 2017 ).

From a network theory perspective, turnover was considered a consequence of network structure until now (Feeley and Barnett 1997 ; Wasserman and Faust 1994 ). Contrary to this approach, Troster et al. ( 2018 ) proposed a model which illustrates that an employee’s thoughts of quitting changes network ties. They theorized that friendship and advice networks are continuously being shaped by thoughts of quitting. Results suggested that employees who have a higher intention to quit have a tendency to drop old ties and create new ones in advice networks, but their friendship ties remain the same. A number of other studies (Brass et al. 2004 ; Parker and Gerbasi 2016 ) have found similar results regarding changing network ties with time.

An analytical summary of trend three is mentioned in Table ​ Table4 4 .

Trend four—snowball effect of network position

When an influential employee leaves an organization, the decision may have a reciprocal effect on his colleagues. Krackhardt and Porter ( 1986 ) state that turnover in a workplace is not a random phenomenon; it occurs in groups. In an empirical research, Hayes et al. ( 2006 ) argued that probability of cluster leaving among the top hierarchy increased many fold when the CEO resigns. Ballinger et al. ( 2010 ) also demonstrated that when a team leader who has strong cordial relations with his team members quits, his peers and subordinates are more likely to leave. Their decision stems from fear of not having similar friendly ties with the successor team lead.

Meta-analysis of one of the studies revealed that employees with similar designations also have a significant impact on turnover, creating a snowball effect (Lorrain and White 1971 ). Results from a quadratic assignment procedure (QAP) test performed on a dataset acquired from three different fast-food restaurants were significant, with P  < 0.004. Findings suggested that employees who are perceived to be in equivalent roles at workplace tend to stay together or quit in clusters (see Table ​ Table5). 5 ). Literature suggests that embeddedness and closeness of social networks play a key role in cluster leaving (Felps et al. 2009 ; Mossholder et al. 2005 ). When many employees in a common project occupying similar job hierarchy resign, it creates a ripple effect and the probability of turnover for the rest of the team is also higher.

Analytical summary of snowball effect on turnover

Feeley and Barnett ( 1997 ) refined the snowball effect analysis in cluster leaving by stating that employees with strong communication ties to those who resigned increased their likelihood of quitting irrespective of their job hierarchy. Similar results were observed by Gopalakrishnan et al. ( 2013 ) who examined turnover in project affiliated groups in a technology-based firm. They found that individuals whose network included more people who had left the organization were also more likely to quit. Similar results were observed by Wang et al. ( 2016 ) who studied contagion turnover.

Apart from turnover of influential employees and equivalent job roles, there are other factors involved for cluster leaving. Wang et al. ( 2017 ) extended the concept of collective turnover in organizations based on casual network mapping and found that negative sentiments, cognitive contagion, group efficacy, an enthusiasm for entrepreneurship and similar group values stimulate translocated mutual turnovers in organizations (see Table ​ Table5). 5 ). Few other studies have also highlighted entrepreneurship, cognitive sense-making, and group efficacy as triggers for collective turnovers (Biraglia and Kadile 2016 ; Li et al. 2010 ; Zomeren et al. 2004 ).

An analytical summary of trend four is mentioned in Table ​ Table5 5 .

Measurement opportunities

Most network studies on turnover have adopted a cross-sectional approach for data collection. While this methodology may be quick and easy to conduct, it fails to capture the continuous evolving nature of social relationships, which is a major drawback. Social networks are rarely static and keep on evolving with time, based on employees’ specific circumstances (Zhao et al. 2018 ). Future research could incorporate a cross-sectional approach along with longitudinal studies for a better validity of results, building a more viable framework for predicting turnover based on social network parameters.

Our findings indicate that most studies used a whole network approach to investigate the network position of employees. This method gives the overall picture of organizational networks, but it has its limitations. To capture whole network data, all individuals must be included in the survey—which is difficult. Whole network data do not explain the opportunities and constraints of individual employees. To get a closer look of organizational data structure, future research can study the whole network first and then extract ego networks from it (Hanneman and Riddle 2005 ). This method is ideal for observing the whole network along with multiple ego networks for analyzing individual behavioral patterns.

Other centrality measures such as power , PageRank , Katz centrality , cross-clique centrality, and reach are not frequently used in turnover research. These new network constructs can measure the most prominent nodes by categorizing specific employee characteristics such as high potential employees, mentors, entrepreneurs, etc. by assigning relative scores and thus give a more comprehensive picture of the network. Future research is needed to answer research questions such as: what is the turnover intent of the most prominent nodes (based on the SNA measure and specific employee characteristics) of the network? Or what will be the impact of turnover of these prominent nodes on the rest of the nodes? To understand how prominent nodes stimulate turnover, we need to consider all the above network measures side by side. Since these SNA measures indicate the importance of an individual in their own unique way, by incorporating these measures together, turnover research can be broadened to a greater extent.

Examining past research on network studies, two methodological findings become evident. Firstly, most of the studies adopt a questionnaire approach for analyzing networks. Survey/questionnaire methods have their pros and cons, individuals may give politically correct replies, many questions go unanswered, capture unconscientious responses, and so on. A more robust approach is to study actual networks. Analyzing multiple communication platforms such as e-mail exchange, call detail records, digital recordings of virtual meetings will give more accurate network insights. Secondly, much of the research has focused on turnover intent rather than actual turnover. Turnover intent may not always translate into the actual turnover of individuals. For reliability, we encourage future studies to correlate results of turnover intent with actual turnover.

Individuals who are prominent because of their influence and talent are the most significant in any social network. Such employees are usually the key players who drive performance in organizations. In the majority of past studies, the snowball effect is measured in terms of employees in general. Categorizing and predicting turnover of these employees based on their intellect, or influence (e.g., influencers and high potential employees) measured in terms of centrality and then analyzing the impact on cluster leaving would be more beneficial. This method of coalescing employee characteristics with network measures will further refine turnover theory. The results of such an analysis can be used not only to identify the key players for any organization but also highlight the influence of their decision on the entire network.

Way forward—conceptual model

A thorough investigation of previous studies reveals that a retention model has never been discussed within social network context. Based on our review on SNA and employee turnover studies and the gaps identified, we suggest a conceptual model of employee retention which comprises of the following elements as depicted in Fig.  2 . The retention model is developed by integrating the shortcoming of all the four trends investigated in this review, namely network position, centrality measures, network type, and the snowball effect. In addition to this, the model also suggests identifying the star employees of the organization and employees with negative megaphoning based on their respective network measures to predict their turnover intent. Combining all the aforementioned constructs resulted in an employee retention conceptual model. The top management decision makers of any organization can make use of this retention model to reduce communication boundaries between different employee networks, promote informal networks, enhance employee performance by encouraging smart networks, introduce a healthy working environment, and thus mitigate voluntary turnover and enhance retention.

The detailed description of the all elements of the conceptual model is mentioned below.

Firstly, for network position , the model suggests considering ‘favorable’ and ‘unfavorable circumstances’ for the employees. The analytical summary of network position from the past studies suggests that different network positions have a varying impact on turnover based on the external circumstances. Future studies can make use of this conceptual model to enhance retention by taking into account the varying nature of organizational networks, along with favorable and unfavorable work conditions (Fig.  2 ).

Secondly, for network type, the conceptual model considers investigating the multiplex heterogonous networks of advice, friendship, work, and common projects simultaneously. Since organizational networks are usually quite complex and mostly intertwined with each other, examining the heterogeneous networks provides a deeper understanding of the superimposed networks of workplace. Contrary to this, the majority of the networks in the past were investigated from a simplex viewpoint in which networks were examined in isolation which was not very practical. To cater for this insufficiency, our conceptual model suggests using heterogeneous networks in future.

Thirdly, for network measure, our retention model suggests that for better reliability of results and cross validation, multiple centrality measures should be computed instead of relying upon a single SNA measure which limits the result outcome. This consideration was missing in earlier studies. The conceptual model also enlists the old and new centrality measures used in network turnover studies.

Fourthly, star individuals should be identified based on their SNA measurement and specific personality traits. Through this method, we can categorize employees on a deeper level instead of only identifying focal and peripheral employees which are already discussed in literature multiple times. Fifthly, after identifying the star performers, their turnover should be predicted, followed by analyzing the snowball effect on other employees. Since every star performer might generate a unique quit propensity, their turnover decision will either stimulate cluster leaving or promote cluster staying; thus, by predicting the snowball effect, collective employee turnover can be reduced.

An extension to this model could be to identify those individuals with negative communication pattern, who impede firm performance. Literature suggests that not every individual contributes equally toward promoting a healthy working environment; there may be some employees whose behavior is detrimental to other employees’ wellbeing or whose actions are harmful to organizational reputation (Lee and Kim 2020 ; Silvia and Alessandra 2018 ). Identifying employees with negative megaphoning in parallel to the star performers will help to retain the individuals most beneficial to the organization and get rid of the black sheep. By adopting the conceptual model presented in Fig.  2 of this study, managers can identify the key employees who are at risk of quitting and possibly mitigate their voluntary turnover. Such an effort will aid in creating a productive and healthy working environment.

Discussion and conclusion

To our knowledge, this systematic review is the first to analyze different network construct of SNA for formulating an employee retention conceptual model for HRM, GM, and KM practices. The aim of this study was to identify the knowledge gaps by examining the major recent contributions on the application of SNA on employee turnover. Thirty articles were identified after an extensive literature search, suggesting that this area of research is still underexplored, with great potential for future studies. We found a diverse range of factors constituting favorable and unfavorable work conditions influencing social network parameters and employee turnover.

Four trends emerged when examining employee turnover in organizations, namely network position , network centrality , types of networks, and the snowball effect of turnover. We found that different centrality measures of SNA can help identify individuals who are focal in their network, lie on the periphery and are brokers. Research indicates that whichever network position an employee occupies in an organization either positively or negatively correlates with their turnover decision. As opposed to the established concept of the past that central employees tend to have lower turnover propensity, we found many articles negating this concept based on the argument that unfavorable conditions can stimulate a highly connected central employee to quit. Social support, energetic activation, and individual performance influence the turnover decision of central employees. The same was observed for network centralities when an employee with higher degree centrality does not always have a reduced turnover, unlike the traditional concept of network centrality. Many studies supported the earlier concept of network position and network centrality, but overall, the findings were contradictory suggesting more elaborate research is required in this area.

The most pre-dominant network measures used in literature were degre e (in-degree, out-degree), closeness , betweenness , k-shell scores, and eigenvector centrality, and the most frequently studied networks were friendship and advice networks.

Turnover is not a random phenomenon; it occurs in groups—creating a snowball effect. This is especially true when a CEO or an influential employee resigns. Contagion turnovers were also observed in instances of group efficacy, common projects, equivalent job roles, entrepreneurship, and negative sentiments toward organization.

The majority of studies focused on how social networks instigate the thought process of employee turnover, but some have hypothesized that turnover intention of employees shape up their friendship and advice networks in the future (Gloor et al. 2017 ; Troster et al. 2018 ). Finally, the studies in this review convincingly demonstrate turnover theory is more nuanced with regards to the relational aspect of employees.

Previous research has primarily focused on determinants of turnover within a social network context, whereas no attention has been given to developing an employee retention model. While it may signify an elusive distinction in representing an important organizational aspect, developing a retention model, however, opens new prospects for better management of human resources. The focus shifts from the argument “will they go” to “will they stay” which offers more potential benefit for organizational decision-making. To fill this gap in literature, our research proposes a conceptual model that maps employees’ social network parameters to enable managers to identify the most productive employees of the organization and mitigate their intention to quit by considering the favorable and unfavorable work conditions. Since not all employees are equally valuable, identifying and retaining the best talent will prove to be fruitful for maintaining a competitive advantage for the organizations.

Limitations and future work

A detailed literature search was carried out based on the inclusion criteria to gather as many relevant articles as possible, but not every study in this field may have been identified. The study selection method to identify only those research papers that employed SNA techniques for analyzing voluntary turnover may have excluded those papers which did conduct SNA but did not include the keywords in the title or abstract of the studies. The principal contribution of this systematic review lies in identifying knowledge gaps in present studies and in the formulation of a new conceptual diagram for employee retention for future scholars and to highlight current avenues where SNA is applicable.

From this review, we found that the centrality measures most often used were closeness and betweenness, which are significant, but still do not capture many other variables known to turnover intention such as PageRank , power, and reach centralities. Future researchers should integrate a wider range of centrality measures for turnover.

The majority of the studies used the questionnaire approach for data collection (Mossholder et al. 2005 ; Labianca 2014 ), but this approach might introduce bias in the results because of the sensitivity of information used in SNA (e.g., who goes to whom for advice or who avoids whom at workplace). This review found only two studies in which actual interaction and e-mail communication of employees was analyzed for predicting turnover (Gloor et al. 2017 ; Yuan et al. 2016 ). There are other data collection methods for mapping actual social interaction of employees at workplaces, such as resource generator and position generator using data from call records, video conferences, or text messages. Future scholars could explore other modes of communication between employees for acquiring confidential data by obtaining prior permission from the employer and the employee.

Most of the studies in our review used the quantitative method of SNA, however, it will be beneficial for later studies if they also consider a mixed methods approach along with visual mapping of interaction patterns to get detailed insights into workplace relationships. We also suggest that future practitioners apply SNA techniques more deeply to specifically predict turnover of those employees who are more beneficial to the organization in terms of performance in addition to general turnover.

Although SNA has been applied in different organizations to study employees’ behavioral patterns, no study encompasses employee retention strategies. Future studies might take this into consideration. Since social network analysis has added another dimension to theory, based on the gaps identified in this review it will be worthwhile to further incorporate reasons to quit into an employee retention model.

In one of the studies, Vardaman et al. ( 2012 ) investigated networks and organizational change reactions; future studies can explore the same by integrating the effects of social networks on turnover during change. It will be an interesting aspect to investigate in future.

Furthermore, owing to the negative impact of current pandemic Covid-19 on the business acumen and organizations, where businesses have been redefined in different parameters, there is a need to explore this aspect in future studies. Stemming from the Covid-19 regime when majority of the workforce had to shift from controlled office environment to ‘work from home,’ employee turnover has become even a bigger challenge for the companies since they had limited control on the employee work environment. The future researchers should also cater for the new ‘remote working conditions’ of the employees while carrying out SNA.

Author contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by SY and AA. The first draft of the manuscript was written by SY, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Conceptualization was performed by SY, AA, FMC; methodology by SY, AA; formal analysis and investigation by SY; writing—original draft preparation—by SY; writing—review and editing—by FMC, SY; supervision by AA.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. No funds, grants, or other support was received. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Declarations

The authors declare that there is no conflict of interest. This research did not involve primary research involving human participation; therefore, issues of informed consent and ethics do not apply. Data used in this research have been derived from previously published peer-reviewed papers.

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ABSTRACT The study is about the finding the factors affecting effectiveness of retention strategy in government agencies, the case study of Tanzania National Roads Agency (TANROADs) in MOROGORO The study intend ended to investigate issues that lead TANROADS employees to quit the job and to assess the strategy for retaining employee at TANROADS, to Determine the challenges facing TANROADS management in retaining their employees and to suggest solutions for effective strategy and role of human resource officer in retaining employee of TANROADS The researchers used literature review thus includes theoretical framework, general survey of information and studies by various scholars about the same problem. The researcher also use the case study design and methods used to collect data involved questionnaires, interviews and documentary reviews. In research design a researcher used two sampling techniques which involved simple random sampling (used to get information from ordinary or lower employees) and purposive or judgmental sampling (used to draw information from the top management). The researcher then found the existence of effective retention strategy at TANROADS; also the researcher tries to show the response of employees on reasons for them to quit the job at TANROADS, retention strategy implemented at TANROADS, also researcher found the challenges facing TANROADS management in retaining employees, and obtain some possible solution for the challenges and role of human resource officer in retaining employees at TANROADS. The researcher finally concluded by provide recommendations to be implemented by management of TANROADS chapter five stipulate, the recommendation as proposed suggestions will be the solutions to ensure more effective retention strategy at TANROADS and the whole government Agencies in general.

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• Published: 27 September 2024

Securing human resources for Japan’s aging population: a mixed methods study of job satisfaction and well-being among Southeast Asian long-term care workers in Japan

• Niaya Harper Igarashi 1 ,
• Junko Kiriya 1 ,
• Rogie Royce Carandang 1 , 2 ,
• Ken Ing Cherng Ong 1 , 3 ,
• Akira Shibanuma 1 &
• Masamine Jimba 1  

BMC Health Services Research volume  24 , Article number:  1134 ( 2024 ) Cite this article

Metrics details

Japan is one of the countries experiencing a “super-aged society.” The government has looked to Southeast Asia for recruiting workers to fill the demand for long-term care (LTC) workers. However, migrant LTC workers have faced many job-related stressors. This study aimed to examine the factors associated with job satisfaction and subjective well-being among Filipino, Indonesian, and Vietnamese LTC workers in Japan and explore the specific factors behind what makes them satisfied in their jobs.

A convergent mixed methods study was conducted. The workers were recruited through snowball and convenience sampling and completed a self-administered questionnaire for the quantitative part. The association of the work environment with the workers’ job satisfaction and subjective well-being were analyzed using multiple linear regression analysis. An interpretive phenomenological approach was used to conduct in-depth interviews of the workers, which were analyzed using a deductive and inductive approach for the qualitative part. Quantitative and qualitative results were integrated and interpreted to expand on the findings with new insights.

In the final analysis, 122 workers were included (20 Filipino, 43 Indonesian, and 59 Vietnamese). In the quantitative part, having the necessary tools/equipment (Unstandardized Coefficient [B] = 16.1, 95% Confidence Interval [CI] = 6.8, 25.3) and support from work (B = 18.1, 95% CI = 8.6, 27.6) were associated with a higher level of job satisfaction. Having experienced harassment on the job was associated with a lower level of job satisfaction (B = -18.2, p  = 0.007, 95% CI = -28.5, -7.8). There is no strong evidence for the association with subjective well-being. In the qualitative part, prominent themes emerged related to cultural sensitivity and an inadequate knowledge of caring for older adults living with dementia. The integrated findings suggested inadequate and unequal Japanese language training across the facilities. Moreover, the importance of human relations in the workplace emerged, with some workers desiring a deeper connection with their Japanese coworkers.

Conclusions

A supportive and culturally sensitive work environment may bring about more motivated employees and increase employee retention from migrant LTC workers. Government and facilities should consider policies supporting a culturally sensitive work environment and more equitable Japanese language training across all facilities.

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Introduction

Today, people are living longer, and the population aged 60 and over is growing faster than all other age groups. By 2030, 1 in 6 people worldwide will be 60 or older [ 1 ]. Japan is experiencing what is known as a “super-aged society,” with 30% of its population already aged 60 and above, making it the country with the largest proportion of this age group in the world [ 2 ].

The shift in the aging demographics and changes in the structure of family households in Japan has created many challenges in securing the human resources to care for older adults [ 3 ]. Due to geographical constraints, work demands, or raising children, many families can no longer care for an aging family member, thus resulting in a substantial growth in the need for long-term care and an increased demand for long-term care (LTC) workers [ 4 , 5 ]. Like many other high-income countries, Japan has a labor shortage of LTC workers. As the population grows older in Japan, the Ministry of Health, Labour and Welfare (MHLW) estimates that by 2040, there will be a need for 2.8 million LTC workers, leaving an additional 690,000 LTC workers needed to fill the labor gap [ 6 ].

To mitigate the labor shortage of LTC workers, the Japanese government has implemented several policies for accepting migrant LTC workers. Since 2008, Japan has received nursing and LTC work candidates through the Economic Partnership Agreement (EPA) from Indonesia, the Philippines, and Vietnam [ 7 ]. The EPA permits candidates for LTC work to enter and stay in Japan for up to four years for training to obtain the national care worker certification. Upon receiving the qualification, candidates can live and work in Japan indefinitely. In contrast, candidates who are unsuccessful in passing the exam will be required to return to their home country [ 8 ].

However, there have been some challenges for the workers, such as passing the exam, which is in Japanese. The government has since made several modifications to the exam to make passing it more achievable for migrant workers. Several reforms have also been implemented to expand the systems through which migrant workers can come to Japan to work in LTC [ 9 , 10 ]. There are four systems for employing migrant LTC workers: through the EPA, graduating from a certified care worker training school and obtaining care worker qualification in Japan, through the Technical Intern Training program, and Specified Skilled Worker status of residence [ 11 ].

While passing the national care worker certification exam is one challenge, many workers have also reported negative experiences on the job. One study that surveyed 146 EPA nurse and LTC worker candidates from Indonesia, the Philippines, and Vietnam showed that dissatisfaction with their job was significantly associated with returning to their home country [ 12 ]. In other studies, migrant workers cited dissatisfaction with working conditions such as the long hours, physical health concerns, and coworker relationships, as well as stressors such as language barriers, workplace discrimination, and cultural differences [ 13 , 14 , 15 ].

The Range of Affect Theory (1976) is a job satisfaction model developed by Edwin A Locke. This theory proposes that an individual’s job satisfaction depends on the workers’ expectations from the job and if the expectations are met. Further, the theory states that how much the worker values any given part of the job (autonomy, coworker relationships, organizational culture, management practices, etc.) determines their satisfaction or dissatisfaction when expectations are met or not met [ 16 ].

With the growing demand for qualified migrant LTC workers in Japan, the government must study all aspects of the human resources shortage and turnover among migrant LTC workers. Previous literature on migrant LTC workers in Japan primarily focused on the stressors and dissatisfaction of the workers who were mainly part of the EPA system and working as nurses. Little research to date has investigated the factors associated with satisfied migrant LTC workers and the association between their work environment with their job satisfaction and well-being. By understanding what makes migrant LTC workers satisfied and happy in their jobs, new methods and strategies can be employed to modify the work environment, reduce employee turnover, and optimize retention among this group of workers. Figure  1 illustrates the conceptual framework used in this study.

Conceptual framework

This study had two objectives: to examine the factors associated with job satisfaction and subjective well-being among migrant LTC workers in Japan and to explore the factors behind what makes the workers satisfied with their jobs.

A convergent mixed methods study was conducted across all 47 prefectures (administrative regions) in Japan. The convergent mixed methods design was employed to meet the needs of the objectives and to be able to examine the situation of the workers from different angles and within the study’s timeline. The convergent design allowed quantitative and qualitative data to be collected in parallel but analyzed independently [ 17 ].

Quantitative study design and participants

Participants of this study included Filipino, Indonesian, and Vietnamese LTC workers who were either certified or trainees working in an LTC facility, excluding daycare centers and in-home care services. The workers were at least 20 years of age. This population was selected as it represents the three main countries from which the majority of migrant LTC workers are recruited and where Japan holds EPA Agreements.

A minimum sample size of 350 was calculated using OpenEpi software, taking the mean difference in job satisfaction from the bivariate analysis of a study on job satisfaction and associated factors among healthcare professionals in Ethiopia [ 18 ]. The significance level was 5%, with a statistical power of 80%.

The workers for this study were recruited by employing both a convenience sampling and snowball sampling method through social media groups and with the cooperation from non-governmental organizations (NGOs), LTC facilities, and supervising organizations that support migrant workers in Japan.

Variables and assessment

Exposure variables, work environment.

The work environment was assessed by asking the following “Yes” or “No” questions, “My workplace provides me with the necessary tools/equipment to perform my job,” “I have experienced harassment or discrimination in my workplace,” and “There are enough staff in my workplace to provide the necessary care for the users.” Social support at work was assessed by asking, “Is there someone at work to talk to about understanding a situation or any problems.”

Outcome variables

• Job satisfaction

The workers’ job satisfaction was measured using the Job Satisfaction Survey (JSS) developed by Paul Spector. Spector’s JSS was based on Locke’s (1976) job satisfaction theory [ 19 ]. The workers responded based on a 6-point Likert scale ranging from 1 “disagree very much” to 6 “agree very much” with scores ranging from 36 to 108 interpreted as “dissatisfied,” whereas scores of 144 to 216 interpreted as “satisfied” [ 20 ]. The questionnaire also consists of nine subscale domains (pay, promotion, supervision, fringe benefits, contingent rewards, operating conditions, coworkers, nature of work, and communication). The JSS has adequate reliability with Cronbach’s alpha score that averages 0.7 for all nine subscales, making it a reliable tool for evaluating job satisfaction [ 21 ]. The JSS has been translated into 27 languages and has been used in studies worldwide, demonstrating the instrument’s acceptability across cultures [ 22 ].

Subjective well-being

The WHO-5 Well-being Index (WHO-5) was used to measure the workers’ subjective well-being. Responses to this questionnaire are based on a 6-point Likert scale ranging from 0 “none of the time” to 5 “all of the time,” with a total score of 25 representing the “best imaginable well-being” while scores below 13 indicate “poor well-being”. The WHO-5 has been translated into over 30 languages and due to the diversity of its application, the WHO-5 instrument has shown to be successful across different regions of the world [ 23 ].

Translated and validated versions of previous studies’ JSS and WHO-5 questionnaires were used for Filipino and Vietnamese workers. There were no translated versions of the JSS or WHO-5 for Indonesian workers, so for this study, a forward–backward translation from English to Indonesian was performed by a researcher fluent in both languages and with a background in health science. The primary researcher conducted face and content validity and pre-testing on a sample of six Indonesian LTC workers to assess the understanding of each questionnaire for linguistic and cultural validation. Pre-tests were also conducted on a small sample of two Filipino and five Vietnamese workers before the start of the study. Cronbach’s alpha was calculated to check internal consistency, which came out to α = 0.93 for the JSS and α = 0.90 for the WHO-5.

Confounders

Potential confounders of this study are length of time living in Japan, Japanese language proficiency, being a certified care worker, number of years of LTC work, living situation, and work location.

Covariates of this study are background-related factors of the workers, which included age, sex, nationality, weekly working hours, and monthly income.

Data collection

A 58-item web-based, anonymous, self-administered questionnaire was created in the native language of the workers, Tagalog, Indonesian, and Vietnamese, and distributed online using the Google Forms platform. A paper-based questionnaire was also made available if needed. Quantitative data were collected from mid-May to mid-October 2021.

Data analysis

Descriptive statistics were used to summarize the characteristics of the workers. The mean scores of the JSS nine subscales were calculated to examine the specific job domains in which workers are satisfied or dissatisfied. One-way Analysis of Variance (ANOVA) was conducted to test the differences in the JSS subscale mean scores among the nationalities.

Multiple imputation was performed for variables with missing data. Multiple linear regression analyses were performed to identify the association of the work environment with job satisfaction and subjective well-being. The variance inflation factor (VIF) was calculated to check the multicollinearity, and values below 5, suggesting a moderate correlation, but not severe enough to warrant corrective measures, remained in the model [ 24 ]. The level of statistical significance was set at p  < 0.05. All analyses were performed using Stata/SE 16 (StataCorp, College Station, TX, USA).

Qualitative study design and participants

For the qualitative part of the study, an interpretive phenomenological approach was employed to explore further and interpret the workers’ perceived experiences at work and in life and identify the factors behind what makes them satisfied in their jobs. Eligible workers who completed the questionnaire were recruited from the quantitative part of the study. An estimated sample size of 20 eligible workers (10 "satisfied” and 10 “dissatisfied”) were purposively selected and screened before sending a formal invitation to collect and compare workers at both ends of the satisfaction spectrum. The nationality of the workers was also considered to include a balanced number of workers from all three nationalities included in the study.

In-depth interviews were conducted using a semi-structured approach with guided questions developed for this study. The primary researcher and an interpreter (research assistant speaking the local language of the worker) interviewed the workers on the Zoom online platform, where workers chose a convenient private location. Informed consent was taken verbally on the day of the interview before starting. The workers were given ID codes in place of their names during the Zoom interview to confirm their identity and stay anonymous. Questions asked in the interview were framed around their (1) background, (2) work environment, (3) social support, and (4) unique behaviors (Appendix A). Qualitative data were collected from August to mid-October 2021. Data saturation was checked and discussed after each interview.

All transcripts not in English or Japanese were translated by the interpreter and analyzed by the primary researcher using a deductive and inductive thematic approach in parallel with another researcher trained in qualitative interviewing. Each researcher independently coded the transcripts and met to discuss their codes, which were then grouped into more conceptual categories and themes. Lastly, to minimize researcher bias, themes included in the final analysis were mutually agreed upon through peer debriefing with a third external researcher. The Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist was completed for this study. MAXQDA 2020 (VERBI Software, 2019) qualitative data analysis software was used to manage and code the data.

Integration

The data from the quantitative and qualitative parts were collected in parallel and analyzed independently. The results were then merged and interpreted. Significant findings that confirm the results in both parts or expand on the results by providing new insights were organized and presented as joint displays showing both quantitative and qualitative findings side-by-side. Meta-inferences were drawn to describe new findings obtained from the integration.

Quantitative part

In total, 124 workers completed the survey. After data cleaning, it was found that two entries were missing substantial data and were excluded from further analysis. The final analysis included 122 workers from 31 prefectures (Appendix B). The calculated estimated sample size in this study was not met due to challenges in recruiting participants during the COVID-19 pandemic, and given the time limitation, it was decided for the data collection to stop at 124 workers. However, the statistical power for each significant outcome variable in the regression analysis of this study was sufficient.

Sociodemographic characteristics of the workers

Table 1  shows the sociodemographic characteristics of the workers, 20 Filipino, 43 Indonesian, and 59 Vietnamese. Their mean age was 27.9 years (SD 6.1), and most were women (79.5% vs. 20.5%). Most workers (79.8%) had a monthly income of JPY 200,000 (USD 1,900) or less. 34.4% were employed through EPA, followed by Specified Skilled Worker (23.8%) and Technical Intern Trainee (21.3%). Concerning their Japanese language proficiency, 70.5% of the workers self-rated their Japanese speaking proficiency as working-level or greater.

Overview of the Job Satisfaction (JSS) and the WHO-5 subjective well-being (WHO-5) scores

Table 2 shows the JSS subscale mean scores for each of the nine subscale domains. The mean scores of the subscale domains: “nature of their work” (17.6), “communication” (17.1), “supervision” (17.0), and “coworkers” (16.7) all suggest a higher level of satisfaction. The results from ANOVA showed no significant differences among the nationalities (Appendix C). The WHO-5 mean scores were calculated at 12.9 points, indicating poor well-being. The Cronbach’s alpha of the JSS scale used for this study was α = 0.92 for Tagalog, α = 0.93 for Indonesian, and α = 0.91 for Vietnamese. The Cronbach’s alpha of the WHO-5 scale used for this study was α = 0.91 for Tagalog, α = 0.90 for Indonesian, and α = 0.93 for Vietnamese.

The association of the work environment with job satisfaction and subjective well-being

Table 3  shows the results of the multiple linear regression analysis for the association of the work environment with job satisfaction. Workers that reported having the necessary tools/equipment (Unstandardized Coefficient [B] = 16.1, p  = 0.007, 95% CI = 6.8, 25.3) and support from work (B = 18.1, p  = 0.006, 95% CI = 8.6, 27.6) were significantly associated with having a higher level of job satisfaction compared with workers who did not. Workers who have experienced harassment or discrimination at work (B = -18.2, p  = 0.007, 95% CI = -28.5, -7.8) were significantly associated with a lower level of job satisfaction compared with workers who have not.

Table 4  shows the results of the multiple linear regression analysis for the association of the work environment with subjective well-being. Although the WHO-5 mean scores were calculated at 12.9 points, indicating poor well-being, strong enough evidence for the association between work environment with subjective well-being was not found. However, based on the value of the coefficients and the confidence interval, the following variables could be potential factors contributing to subjective well-being. Being a certified care worker (B = 3.1, p  = 0.097, 95% CI = -0.8, 7.0), Filipino worker (B = 2.4, p  = 0.130, 95% CI = -1.1, 5.9), working 30 hours or less in a week (B = 2.3, p  = 0.089, 95% CI = -0.5, 5.1), and having support from family and friends (B = 2.1, p  = 0.101, 95% CI = -0.6,4.8) might be important factors that contribute to a higher level of subjective well-being.

Qualitative part

Out of the 76 contacted workers, 16 interviews were successfully arranged. Table 5  shows the sociodemographic characteristics of the workers who participated in the interviews: 2 Filipino, 8 Indonesian, and 6 Vietnamese, with a mean age of 28.3 years (SD 4.6).

Two main themes emerged from the qualitative findings: unique behaviors of the workers and positive factors of their work environment. Table  6 summarizes the themes, sub-themes, and descriptions from the findings.

Unique behaviors of the workers

Religious beliefs and practices.

Religion was mentioned by many of the workers from Indonesia and the Philippines. The workers talked about their religious practices, with several stating religion as a strong factor in their motivation for continuing their work and dealing with stressors related to work or daily life.

“Just staying motivated in that work because I’m a Christian, that is my motivation to do a job. And then even if the situation is very hard, so you need to be focused and you need to stay motivated in that job, because of our God.” ( Filipino, female, 30 s, works in Aichi)

Community participation

Some of the workers discussed their involvement in community activities. Community participation or volunteering has been associated with migrant workers feeling more connected to Japan [ 25 ].

“There are some Japanese people more like a mother figure that are around me who I know from the cultural center. There’s a space to meet and study Japanese and exchange culture and there are many older Japanese ladies that also visit and or work there and I often talk with them.”  (Indonesian, female, 20 s, works in Aichi)

Cultural adaptability

While many workers highlighted cultural differences as challenges within the workplace, some talked about having more of an ability to quickly adapt and integrate due to previous education or interest in Japanese culture and language.

“There are some points that I am accustomed to, and others are still shocking to me. Before coming to Japan, I was able to learn about Japanese culture and manner, so it was easy to get use to the differences.”  (Indonesian, female, 20 s, works in Aichi)

Knowledge of care for older adults (users) living with dementia

Workers who have been working in LTC for some years or who are certified in Japan mentioned being more familiar with the varying behaviors of dementia among older adults. In comparison, recently employed workers talked about their shock and challenges with how to care for the users in their facility who are living with dementia.

“There are some users that are suffering from dementia and there are many different stages so there can be users who can go on a rampage wanting to return back to their home… I was surprised, during my training there was no mention of this…I never thought [of it] until experiencing this at the facility.”  (Indonesia, female, 20 s, works in Aichi)

Positive factors of the work environment

Leadership and development opportunities.

Some workers spoke enthusiastically about leadership opportunities. Providing opportunities for the workers to be more involved in taking ownership of responsibilities other than their daily tasks can empower them to be more motivated. It may also create a more inclusive working environment for the migrant workers to feel equal to Japanese workers.

“There is a [training] program here, every month we discuss about an issue for example diseases infection prevention, how to improve quality of the patient’s condition…The training can develop into a career. I have worked already as a floor leader position and team leader.”  (Indonesian, male, 30 s, works in Tokyo)

Japanese language training

Although all the workers are required to meet a minimum intermediate level of Japanese language requirement [JLPT N3] for working as an LTC worker, the majority stated having insufficient language ability to perform their duties confidently and spoke about Japanese language being one of the significant challenges at work. Furthermore, many workers talked about the need for self-study or paying for lessons independently. In contrast, others mentioned that Japanese language support or even allowance for study time was provided within their facilities.

“My facility also facilitated me to learn Japanese, the sensei [language instructor] comes to my facility… Two hours, every week.”  (Indonesian, female, 20 s, works in Gifu)

“Before the exam [National care worker certification exam] they will give us 40 days, we can study at any day. We will still have to go to the facility, but it won’t be to work, but just to study, during that time.” (Vietnamese, female, 20 s, works in Tokyo)

Cultural sensitivity

When bringing other nationalities and cultures into the workplace, it is essential to have an awareness and understanding of the different cultures of the workers [ 26 ]. Those workers in facilities where the management understood the importance of accepting the workers’ cultural and religious practices shared how lucky they felt to work in such a facility.

“I discussed this [my religion] with the facility management prior to joining in the interview. I explained that it was necessary for me to pray five times a day and they were understanding about it…and are flexible with giving me time off for religious obligations as well. I am very appreciative of this.”  (Indonesian, male, 20 s, works in Gunma)

Social support

Coworker support has been associated with a more positive work environment, higher job satisfaction, and lower turnover intentions [ 27 ]. Additionally, it helps to build human relationships and skill sharing. For migrant workers, many are here in Japan alone, and some may have no other support system apart from support from their facility.

“The positive point for me, the director is easy-going; they support learning, study time, teachers, books, a lot. Plus, we’ve had a raise recently.”  (Vietnamese, female, 20 s, works in Tokyo)

Two new findings were brought to light after integrating the quantitative and qualitative data results. The first integrated finding in Table  7 shows that while Japanese language proficiency was not significantly associated with job satisfaction in the quantitative part, in the qualitative part, almost all the workers mentioned that speaking and or writing in Japanese remained a significant challenge for them.

The second integrated finding that emerged relates to workplace human relations. Based on the JSS total subscale mean scores in the quantitative findings, the workers were satisfied with the domains: “nature of their work” (17.6), “communication” (17.1), “supervision” (17.0), and “coworkers” (16.7). The results in Table 8  show comparable responses from the qualitative findings, where workers shared about their “friendly environment” and “helpful coworkers.” While most of the workers noted a high level of social support in the workplace, some also mentioned wanting a deeper connection with Japanese coworkers.

This study aimed to examine the factors associated with the job satisfaction and the well-being among migrant LTC workers in Japan and to explore the unique behaviors of those workers who are satisfied in their jobs. Four main findings emerged from this study. First, it highlights the importance of cultural sensitivity among management and staff in the facilities as an important factor for many workers, particularly when it involves understanding religious practices. Second, having the necessary tools, equipment, and social support in the facility was positively associated with the level of job satisfaction; conversely, facing discrimination and harassment in the facility was negatively associated with the level of job satisfaction. Third, some of the workers felt that their knowledge and level of training in caring for older adults living with dementia was inadequate. Fourth, in the integrated findings, a divergent finding emerged that although the association of Japanese language level was not found statistically significant with the workers’ job satisfaction or well-being, Japanese language is an ongoing challenge for many of the workers, and that there are disproportionate levels of training across facilities. Furthermore, the importance of social support and human relations at work was confirmed in the integrated findings.

The importance of cultural sensitivity and acceptance of cultural practices in the workplace

In this study, religion was found to be an important factor for many of the workers. Many of the Muslim workers talked about the cultural barriers they have faced when it comes to their religious obligations of daily prayers. On the other hand, some of the Muslim workers expressed how “ lucky ” they felt to work for a facility that respected their culture and religious practices. Muslims are required by their faith to observe five daily prayers at set times, usually at dawn, mid-day, mid-afternoon, sunset, and nighttime. One study in Malaysia highlighted the impact that daily prayers had on Muslim workers’ motivation to work hard in their organizations [ 28 ]. Christian workers also spoke about religion as a motivating factor for dealing with daily stressors and for their resilience to continue even when work gets demanding.

Furthermore, the increase in migrant LTC workers from Southeast Asia brings a new cultural diversity to many of the facilities, with workers who hold different beliefs, values, and behaviors from the Japanese workers. Facility management should consider implementing cultural sensitivity practices in their facilities, as it has been found to be a strong predictor of job satisfaction and employee retention [ 29 , 30 ].

The association of the work environment with job satisfaction

Workers at facilities with the necessary tools/equipment and support from work were associated with a higher level of job satisfaction compared with workers who do not. Many of the workers interviewed in this study who expressed their satisfaction with their job also mentioned that they received support from their coworkers or supervisors in dealing with issues in their daily lives. It is beneficial for management and staff to have healthy interactions, such as sharing resources and information. Past studies have found a link between support from supervisors or coworkers and job satisfaction [ 31 , 32 , 33 ]. In the case of migrant LTC workers, most of the workers come to work in Japan alone, so they do not necessarily have the same level of support outside of work as their Japanese coworkers. This places even more importance on the level of support provided by the facility to the workers. The integrated findings in this study also highlighted how significant social support and human relations at work are for the workers, with many workers also expressing wanting to have a deeper connection with the Japanese workers in their facility.

Workers who have experienced harassment or discrimination at work were associated with a lower level of job satisfaction compared with workers who have not. Previous studies highlight the impact experiences of harassment and discrimination, such as being undervalued, ignored for promotion, and excessive discipline by supervisors, have on job satisfaction and well-being [ 34 , 35 , 36 ]. For example, one qualitative study on migrant care workers in Japan, which was used as the basis of this study, found discrimination as one of the stressors LTC workers face in Japan [ 15 ]. Migrant and minority workers are most at risk of harassment or discrimination on the job and suffer more adverse health outcomes in comparison to the majority demographic group of the country in which they are living [ 37 ]. The quantitative findings in this study support how among all the other factors how much facing harassment or discrimination at work negatively impacts the level of job satisfaction.

Inequalities in the level of training across long-term care facilities

Many workers spoke about the on-the-job training they receive at their facilities, which includes the physical care and support training required for daily work. Having the knowledge and understanding of caring for older adults living with dementia was one part of the job that some of the workers felt inept in handling. Workers who have been working longer in LTC in Japan had a better understanding of dementia. In contrast, workers who have recently started working spoke about the challenges they faced when caring for users in their facility living with dementia. This finding suggests that among migrant LTC workers, there is a need for more awareness, knowledge, and training on caring for older adults living with dementia. Based on 2020 projections, over the next 25 years in Japan, dementia in people older than 65 years is projected to exceed 25% nationwide [ 38 ].

It also emerged that some workers want to have a deeper connection with their coworkers. Language could be a potential barrier to forming a deeper connection. While the workers are expected to have a minimum level of Japanese language requirement, many expressed a lack of confidence in speaking and writing in Japanese at work. Some workers mentioned that their facilities provide free Japanese language training for them on-site. In contrast, others talked about having to supplement their Japanese language learning through their own financial means.

The integrated findings of this study suggest that the current amount of Japanese language support provided is insufficient. In the quantitative findings, although there was no significant association between Japanese language proficiency and job satisfaction, in the qualitative part, most of the workers discussed the challenges and barriers that remained with speaking and writing Japanese at work, with one worker stating difficulties with the Japanese language, “sometimes makes me want to quit”. This finding corroborates with past literature where it was found among migrant nurses and care workers that Japanese language, especially understanding kanji and writing incident reports in Japanese, remained difficult [ 39 , 40 ].

Ensuring equitable access to language training across facilities nationwide can enable workers to form a deeper connection with coworkers and establish a better relationship with the facility’s users. Moreover, given the pass rate of the national care worker certification exam for migrant workers, having the necessary Japanese language training to pass the exam and get certified is important for retaining migrant workers for the future.

Strengths and limitations

The mixed methods approach in this study utilized the strengths of both quantitative and qualitative findings. However, there were three limitations to address. First, only a small sample size was attained, and the estimated sample size for this study was not achieved, limiting the study’s representativeness and generalizability. This study was conducted during the peak of the COVID-19 pandemic, limiting the accessibility of workers at the time, however, having more authority through government agency with support for recruitment methods may have had a better response, in addition to having an incentive for the facility management to encourage the participation of their employees. Second, multiple imputation was used for the data missing at random, which can reduce the study’s statistical power. Therefore, a statistical power calculation was performed for the variables that showed significance and were all sufficient at over 80%. Third, most of the workers who participated in the interviews had a high level of satisfaction based on their JSS mean score, resulting in possible selection bias. There was an effort to reduce this bias in the beginning by purposively selecting workers who were both satisfied and dissatisfied to compare. However, those workers who were less satisfied were not as responsive, and many could not be interviewed.

Despite such limitations, this study benefits from several strengths. This study examines the experiences and positive factors of migrant LTC workers in Japan from all four government employment systems and across 31 out of 47 prefectures working in both urban and rural settings. The mixed methods design of this study further strengthens the findings. For instance, the qualitative interpretive approach allowed the primary researcher to examine the experiences of the workers from their perspective, which brought to light many significant findings that could not be seen in the quantitative part, such as the importance of cultural sensitivity and the need for more knowledge and training in caring for older adults living with dementia. Future research could explore the experiences and challenges of employing migrant LTC workers from the LTC facilities and management perspective.

With Japan’s aging population and labor shortage in long-term care, workers from Southeast Asia are an important pool of future human resources to hold the industry together. Therefore, policies and interventions should be implemented to promote cultural sensitivity training for all employees in LTC facilities while also allowing flexibility and accommodations for workers with specific religious or cultural obligations. Moreover, facilities and supervising organizations should focus on more education and training on caring for older adults living with dementia and Japanese language. Providing a culturally sensitive working environment and sufficient and equitable training and support are some of the ways to create a more encouraging workplace and improve employee retention.

Availability of data and materials

The datasets used and analyzed during this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to acknowledge the following organizations and researchers who provided their industry expertise and support for this study: Gaikokujin Gino Jisshu no Kai, Indonesian Community in Japan (ICJ), KALAKASAN Migrant Women Empowerment Center, Kokoro Medical, NPO Foreign Residence Support, Onodera User Run, Professor Akiko Asai, Professor Yuko Hirano, and SETIA Management. In addition, the authors would like to acknowledge, Kathleen Soriano, Truong Quy Quoc Bao, Do Dang An, Ahmad Junaedi, and Cindy Rahman Aisyah who assisted with the translation and interpretation during the data collection of this study. Appreciation should also go to all the long-term care workers from Indonesia, the Philippines, and Vietnam for their time and cooperation to participate in this study.

This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Niaya Harper Igarashi, Junko Kiriya, Rogie Royce Carandang, Ken Ing Cherng Ong, Akira Shibanuma & Masamine Jimba

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Contributions

NHI and JK together conceived the design, while JK supervised the study. NHI mobilized collaborators, implemented the study, and conducted data collection. NHI, AS, RRC analyzed and interpreted the data. KICO contributed as an external researcher for peer debriefing of the data analysis and interpretation. NHI drafted the manuscript. MJ reviewed and provided input for the finalization of the manuscript.

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Correspondence to Niaya Harper Igarashi .

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This study was approved by the Research Ethics Committee of The University of Tokyo (Reference Number: 2021023NI). Participation in this study was voluntary. Workers were notified of the objective and practical issues of the study, the right to withdraw or terminate from participating at any time, and the protection of privacy. Informed consent was obtained from all workers prior to conducting the study. The confidentiality of the workers was maintained, and the data collected for the quantitative and qualitative parts were securely stored on two USB drives and locked in a private desk. No information revealing the identity of any worker in this study shall be included during the dissemination of findings.

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Igarashi, N.H., Kiriya, J., Carandang, R.R. et al. Securing human resources for Japan’s aging population: a mixed methods study of job satisfaction and well-being among Southeast Asian long-term care workers in Japan. BMC Health Serv Res 24 , 1134 (2024). https://doi.org/10.1186/s12913-024-11572-1

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Received : 29 May 2024

Accepted : 10 September 2024

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DOI : https://doi.org/10.1186/s12913-024-11572-1

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