Twinamatsiko Jasonn

Koneru Lakshmaiah Education Foundation University e-mail: twinamjason@gmail.com

Anu Mary Ealias https://orcid.org/0000-0002-5001-5724 Koneru Lakshmaiah Education Foundation University

e-mail: anumaryealias@gmail.com

Examining the impact of non-monetary factors on voluntary employee turnover in the construction industry

Badanie wpływu czynników niepieniężnych na dobrowolną rotację pracowników

w sektorze budowlanym

https://doi.org/10.25312/ziwgib.806

Abstract

The construction sector is vital to economic growth but faces high employee turnover. This study explored key non-monetary factors (NMFs) influencing voluntary turnover among Ugandan construction workers. A literature-based list of NMFs was as- sessed through a survey of 110 workers. Data analysis iden- tified ten major NMFs, with training and career development, work-life balance, work overload and stress, decision-making involvement, job security, and leadership style as the most im- pactful. These findings highlight the need for targeted strategies to improve retention. The study provides valuable insights and a foundation for future research into additional factors affecting turnover.

Keywords: voluntary employee turnover, non-monetary factors, workforce retention

Streszczenie

Sektor budowlany ma kluczowe znaczenie dla wzrostu gospo- darczego, ale boryka się z wysoką rotacją pracowników. W ni- niejszym artykule zbadano kluczowe czynniki niepieniężne (NMF) wpływające na dobrowolną rotację wśród ugandyjskich pracowników budowlanych. Oparta na literaturze lista NMF została oceniona w ankiecie przeprowadzonej wśród 110 pra- cowników. Analiza danych pozwoliła zidentyfikować dziesięć głównych czynników pozapłacowych, z których największe znaczenie miały szkolenia i rozwój kariery, równowaga między życiem zawodowym a prywatnym, przeciążenie pracą i stres, zaangażowanie w podejmowanie decyzji, bezpieczeństwo pracy i styl przywództwa. Wyniki te podkreślają potrzebę ukie- runkowanych strategii mających na celu poprawę rotacji i pra- cowników. Badanie dostarcza cennych spostrzeżeń i podstaw do przyszłych badań nad dodatkowymi czynnikami wpływający- mi na rotację.

Słowa kluczowe: dobrowolna rotacja pracowników, czynniki niepieniężne, zatrzymanie pracowników

Introduction

The construction industry in Uganda has experienced significant growth over the past decade, driven primarily by rapid population growth that has increased the de- mand for housing and infrastructure (Katende, Alinaitwe, Tindiwensi, 2011). How- ever, this sector continues to face challenges that hinder its productivity and overall development. Two notable challenges include a shortage of skilled employees and high employee turnover rates (Holt, Love, Jawahar Nesan, 2000). Employee turn- over is often described as separations, which can be classified into voluntary separ- ations (quits) initiated by employees and involuntary separations (layoffs and dis- charges) initiated by employers (Job openings and labor turnover, 2024). The rate of voluntary quits serves as an indicator of workers’ willingness or ability to leave their jobs, posing a significant challenge for organizations. Voluntary quits are par- ticularly problematic as they lead to substantial organizational costs, including ex- penses related to hiring replacements, training new hires, and managing administra- tive adjustments. These costs impact not only individuals but also work units and the organization as a whole, emphasizing the need to investigate the factors contrib- uting to employee turnover (Hom, Griffeth, 1995; Elçi et al., 2012). In October 2024 alone, the construction industry reported a voluntary turnover rate of approximately 149,000 employees (Job openings and labor turnover, 2024). High staff attrition undermines investments in employee development, exacerbating challenges for em- ployers who already allocate significant resources to workforce training. This trend is not unique to Uganda but presents a notable obstacle to growth in its construction sector (Ssekamatte, 2010).

To address this issue, many construction companies have begun conducting root cause analysis (RCA) surveys to identify the underlying factors contributing to vol- untary turnover (Ssekamatte, 2010). RCA involves diagnosing the fundamental caus- es of problems to propose specific, actionable solutions (Han, 2024; Landau, 2024). This approach enables organizations to identify contributing factors, develop correc- tive strategies, and promote continuous improvement in business processes. Several studies have explored the causes of voluntary employee turnover in construction and other industries (Bilau et al., 2015; Li et al., 2022). For instance, Bilau et al. iden- tified triggers such as job dissatisfaction, inadequate salary, role conflict, role am- biguity, excessive workload, poor training, lack of fringe benefits, and alternative employment opportunities as critical contributors to voluntary turnover in Nigeria (Bilau et al., 2015). Similarly, Aregay highlighted factors such as job dissatisfaction, the absence of shared goals, inability to elicit employee commitment, unrealistic ex- pectations, and the allure of better-paying opportunities elsewhere (Aregay, 2021). In Uganda, numerous studies have concentrated on the effects of remuneration and promotion on turnover intentions, with some findings indicating that even well-com- pensated employees in public institutions exhibit high turnover rates (Stelson, 2021). Meyer et al. argued that resignation is not solely the result of cost-benefit analyses of labour market conditions but rather a complex interplay of individual and orga- nizational processes (Meyer et al., 2024). Researchers used Mobley’s model (1977) to illustrate how dissatisfaction at work leads employees to evaluate alternative op- portunities despite incomplete labour market information. Additionally, the ‘unfold- ing model’ by Lee and Mitchell suggests that resignations often stem from signifi- cant organizational shocks, such as conflicts with management or misalignment with organizational values (Meyer et al, 2024; Lee, Mitchell, 1994). High turnover rates are also linked to job-related concerns such as work exhaustion, delayed salaries, and the denial of bonuses or fringe benefits – challenges exacerbated by unstable regional economic conditions and weak workplace legislation (Li et al., 2022; Khan, Khan, Soomro, 2020; Nauman, Zheng, Ahmad, 2021). These circumstances increase employees’ perceptions of psychological contract breaches, which, in turn, elevate turnover intentions.

This study aims to identify non-monetary factors (NMFs) driving voluntary

employee turnover in Uganda’s construction industry and to examine their impact on turnover intentions. Specifically, this research seeks to address the question: What are the primary non-monetary factors influencing employee turnover in Ugan- da’s construction sector? By identifying these factors and their influence, construc- tion companies can develop targeted interventions to improve employee retention, engagement, and productivity. To achieve this objective, the study commenced with a comprehensive literature review to identify factors contributing to high turn- over rates in the construction industry. A survey questionnaire was then developed and sent out to numerous construction employees to collect insights into how these

factors influence their turnover intentions. The findings aim to offer actionable rec- ommendations for lowering turnover rates and enhancing organizational success through improved workforce management.

Literature review

A comprehensive literature review was conducted to identify the primary factors in- fluencing voluntary turnover among construction workers as documented in prior studies. The review employed systematic searches using recognized academic data- bases and relevant keywords such as “construction employee turnover”, “voluntary turnover in construction”, and “non-monetary factors influencing employee turn- over in the construction industry”. Additionally, the process of cross-referencing, which involves examining the reference lists of identified studies to locate further relevant works, was utilized. This approach was subjectively guided by a research team to ensure methodological rigor in the selection process. The team employed criteria such as relevance to the research objectives, methodological soundness, and citation impact to identify and prioritize studies, thereby enhancing the credibility of the review. The analysis highlighted a range of non-monetary factors that are com- monly associated with voluntary turnover in construction settings, which can serve as a basis for providing actionable recommendations to industry stakeholders.

Several studies have explored the underlying causes of voluntary turnover, ex- amining its implications on organizational performance within construction projects. Moderate levels of turnover have been shown to contribute positively to organiza- tional outcomes by introducing new talent that brings fresh perspectives, innovative ideas, and diverse skills to the workforce. For instance, the recruitment of individ- uals with specialized expertise or unique problem-solving approaches can enhance team capabilities and adaptability. However, excessive turnover imposes significant costs and adversely impacts organizational efficiency, productivity, and competitive- ness (Meier, Hicklin, 2007). High turnover rates can diminish employee productivity, increase recruitment costs, erode morale, and reduce overall financial stability, often leading to lost sales and compromised organizational reputation (Lanchaster, 2024; Lepak, 2024). An organization perceived as having a revolving-door culture may face substantial challenges in attracting top talent (Lanchaster, 2024).

Personal demographic attributes, such as age, gender, education level, marital status, years of experience, individual abilities, and sense of responsibility, have been identified as influencing factors. Organizational characteristics including cor- porate culture, policies, benefits, growth prospects, size, salary structures, oppor- tunities for promotion, training, employee involvement, work attitudes, and orga- nizational justice also play pivotal roles (Zhang, 2016; Abdolmaleki et al. 2024). External social and economic factors, such as labour market conditions, job avail- ability, transportation, housing, education, healthcare facilities, cost of living and

overall life quality, further contribute to turnover trends (Zhang, 2016; Abdolmale- ki et al., 2024).

Role ambiguity, characterized by unclear job expectations, insufficient guid- ance, and inconsistent performance evaluations, has been reported as a significant stressor leading to increased turnover rates (Ait Alla, Rajâa, 2019). For example, in the construction industry, a project manager might be uncertain about their au- thority in allocating resources or prioritizing tasks, leading to misaligned goals and team inefficiencies. Employees experiencing inadequate recognition often feel un- dervalued, neglected, and disregarded, which fosters turnover intentions (Dahl, 2010; Elstad, Vabø, 2021; Jinisha, Safa, Basima Parveen, 2023). Perceptions of job insecu- rity and associated threats further exacerbate psychological and emotional exhaus- tion, thereby accelerating turnover (Chih et al., 2016; Abolade, 2018). Work-related stressors, such as high workloads and long hours of working which negatively affect work-life balance, have been consistently identified as major contributors to turnover in the construction industry (Leung, Yu, Chong, 2016; Galea, Powell, Loosemore, 2020). Employees dissatisfied with their personal lives or lacking a quality work-life balance often exhibit higher turnover intentions and diminished career satisfaction (Kabir, Tirno, Kabir, 2018; Lestari, Margaretha, 2021).

Leadership and teamwork also significantly influence turnover. Zaheer et al. un- derscore the importance of leadership style and effective teamwork in fostering a harmonious work environment (Zaheer et al., 2019). Effective leadership promotes synergistic teamwork, thereby enhancing employee satisfaction and reducing turn- over intentions (Boies, Fiset, Gill, 2015; Putri, Renwarin, 2023). Conversely, percep- tions of exploitative organizational relationships and poor internal communication contribute to employee dissatisfaction, fuelling turnover rates (Saniewski, McGuna- gle, 2011; Livne-Ofer, Coyle-Shapiro, Pearce, 2019). Clear communication and em- ployee involvement in decision-making processes are critical to mitigating turnover by ensuring employees feel valued and engaged (Saniewski, McGunagle, 2011). Ca- reer advancement opportunities and professional development have also been shown to significantly impact turnover intentions (Goh Jiaying, Muda, 2023). Employees with limited prospects for career growth or skill enhancement are more inclined to quit their organizations in quest of better opportunities (Abdolmaleki et al., 2024). Upon synthesizing the findings, ten key NMFs were identified as the most in- fluential drivers of voluntary turnover among construction employees: work-related stressors, role ambiguity, inadequate recognition, perceptions of job insecurity, lack of work-life balance, leadership and teamwork issues, exploitative organizational re- lationships, limited career advancement opportunities, ineffective communication, and external socioeconomic pressures. These factors were chosen based on their

prevalence in the reviewed literature.

NMFs in employee turnover

The NMFs contributing to employee turnover are explored through a comprehensive analysis. The fishbone diagram visually represents these factors (fig. 1), categorizing them into key areas such as work environment, job satisfaction, work-life balance, interpersonal relationships, organizational culture, and career development. Each cat- egory highlights specific issues that can lead to employee dissatisfaction and turn- over. Additionally, the accompanying table 1 provides a detailed description of each factor, its impact on organizational performance, and implications for mitigation. Together, these tools offer a holistic view of the challenges faced by employees and provide actionable insights for organizations to improve retention and foster a more stable workforce.

Fig. 1. Fishbone diagram illustrating non-monetary factors contributing to employee turnover

Source: own study based on literature research.

Tab. 1. Identified non-monetary factors influencing organizational performance and employee retention

Source: own study based on literature research.

Methodology

Survey design for employee turnover

A survey was meticulously crafted to examine the impact of NMFs on employee turnover within the Ugandan construction industry. The objective was to gain a com- prehensive understanding of how these factors influence turnover rates, providing actionable insights for construction management. The survey was divided into two sections: first section gathered demographic information about the participants, in- cluding age, years of experience, academic qualifications, marital status, and gen- der. The second section employed a Likert scale to assess participants’ perceptions of their career experiences, focusing on various non-monetary factors influencing their job satisfaction and turnover intentions.

The survey was constructed using Google Forms to facilitate efficient data collec- tion and distribution. The survey link was shared with Ugandan construction workers through an online platform, ensuring accessibility across diverse professional levels. Participation in the survey was entirely voluntary, and stringent measures were taken to ensure the quality and reliability of responses. The data was subjected to a filtering process to verify that responses were complete and of high quality, focusing on data from construction professionals who could offer relevant insights into the topic. In to- tal, over 200 construction employees were approached, with 110 completing the sur- vey and providing comprehensive responses. Although the response rate (55%) was lower than anticipated, this is not uncommon in construction industry research, as similar studies have faced comparable challenges in achieving high response rates (Abowitz, Toole, 2009; Bröchner, Badenfelt, 2011). Despite a relatively low response rate, the sample size was deemed adequate for drawing valid and meaningful con- clusions, consistent with the sample size recommendations for qualitative research in construction studies (Fellows, Liu, 2021). The survey respondents comprised a di- verse group, including lab technicians, engineers, and a small number of managers. The participants exhibited a wide range of professional experience, with an average of seven years spent in the construction sector. This variation in experience levels en- riched the data, providing a broad perspective on the impact of non-monetary factors across different job roles.

Descriptive statistical analysis was utilized to analyse the gathered data. Measures such as mean, median, and pivot tables were utilized to offer a detailed interpretation of the responses, particularly in relation to how NMFs contributed to employee turn- over from the perspective of construction professionals. Descriptive statistics, such as these, are commonly used in organizational studies to distil key insights from large datasets, ensuring that complex patterns and trends are adequately understood (Meier, Hicklin, 2007). Inferential statistical analysis was used to ensure that there is statistically significant evidence that supports the findings from the descriptive anal- ysis. To determine this, regression co-efficient test was performed using the SPSS

software. The most favourable opinion was found to be the extreme on the Likert scale; in this instance the most positive opinion was 5 which denotes highly effective. According to earlier research, many survey respondents may choose the mid-point ranking for a number of reasons, such as confusion or ignorance of the subject mat- ter. Utilizing inferential analysis reduces uncertainty and guarantees that results may be applied to a broader population.

It is crucial to note that the survey was designed with an emphasis on validity, ensuring both content and construct validity. To minimize bias and ensure the re- search captured relevant non-monetary factors, some factors were drawn from ex- isting literature on employee turnover (Zhang, 2016; Lepak, 2024). This approach was critical in enhancing the robustness of the survey design. Furthermore, to ensure content validity, the initial set of survey questions underwent review and verifica- tion by a third-party expert specializing in employee turnover and the construction industry. This pilot testing phase allowed for the refinement of questions before dis- tribution, ultimately improving clarity and precision of the survey (Karakhan et al., 2024). Feedback from this pilot testing phase was incorporated to make necessary adjustments to the wording and structure of the questionnaire, strengthening its over- all validity and relevance.

Results and discussion

Table 2 presents demographic information of the survey participants in Uganda’s construction industry, offering insights into the workforce composition. The anal- ysis aimed to identify NMFs driving voluntary employee turnover and to examine their impact on turnover intentions. The results, summarized in pivot charts, provide a comprehensive overview of the demographic characteristics of the 110 participants. The majority of participants are male (65.45%), reflecting the traditional gender dis- tribution in the construction sector, which is often male-dominated due to physical demands of the job. However, the presence of female participants (34.55%) indicates a positive trend towards gender diversity. The age distribution shows that the work- force is relatively young, with a mean age of 30.9 years. Specifically, 55.45% are aged between 21–30 years and 36.36% between 31–40 years. This suggests that the industry attracts younger individuals who may be seeking career growth and de- velopment opportunities.

The marital status data reveals that 54.55% of participants are single, while 45.45% are married. This balance suggests that both single and married individuals find opportunities in the construction industry, though their job satisfaction and turn- over intentions may differ based on personal responsibilities. Education qualifica- tions indicate a highly educated workforce, with 52.73% holding a bachelor’s degree and 37.27% a master’s degree. This high level of education is essential for techni- cal and managerial roles in construction. The total work experience data shows that 41.82% have 1–5 years of experience, indicating a relatively high turnover rate or

a young workforce still gaining experience. The average tenure in an organization is

2.8 years, with most employees staying for about 2–3 years, suggesting challenges in long-term retention. Comprehending these demographics facilitates the tailoring of retention approaches to address unique needs and concerns of the workforce.

Tab. 2. Demographic information of survey participants

Source: compilation based on own research.

Table 3 presents mean ratings of various NMFs that influence voluntary employee turnover in Uganda’s construction industry. These factors were assessed based on par- ticipants’ responses, providing insights into their levels of satisfaction and the impact on turnover intentions. The mean ratings range from 2.44 to 4.17, indicating varying degrees of concern among employees.

Training and career development opportunities received the lowest mean rating of 2.44, highlighting significant dissatisfaction among employees. This suggests that many participants felt their previous organizations did not provide adequate training and development opportunities, which are crucial for professional advancement and job satisfaction. The lack of such opportunities can lead to employees feeling un- dervalued and unmotivated, increasing their likelihood of seeking employment else- where. This finding aligns with previous research indicating that insufficient training and career development are major drivers of voluntary turnover.

Work-life balance also received a low mean rating of 2.65, indicating that em- ployees struggled to strike a good balance between their personal and professional lives. This imbalance can lead to job dissatisfaction, burnout, and ultimately, high- er turnover rates. Work overload/stress had a high mean rating of 4.08, reflecting significant concerns about excessive workloads and stress levels. High stress and workload can deplete employees’ energy and negatively impact their job perfor- mance and well-being, further contributing to turnover intentions. Job security (mean rating of 3.91) and decision-making involvement (mean rating of 3.34) were also notable concerns, suggesting that employees value stability and participation in deci- sion-making processes. Ensuring job security and involving employees in decisions can enhance their sense of belonging and commitment to the organization.

Other factors such as role ambiguity (mean rating of 4.17), recognition (mean rating of 3.19), communication gap (mean rating of 3.53), teamwork (mean rating of 3.73), and leadership style (mean rating of 3.34) also play significant roles in in- fluencing turnover intentions. High role ambiguity suggests that employees may not have a clear comprehension of their duties and obligations, leading to confusion and frustration. Recognition and effective communication are essential for employee morale and engagement, while teamwork and supportive leadership styles create a healthy work environment. Addressing these factors can help construction compa- nies create a more supportive and inclusive workplace, reducing voluntary turnover and enhancing employee retention.

Tab. 3. Mean ratings of non-monetary factors

Source: compilation based on own research.

Figure 2a bar chart illustrates the participants’ perceptions of role ambiguity and other NMFs influencing voluntary employee turnover in their previous organizations. The mean rating of 4.17 indicates a high level of clarity regarding roles and respon- sibilities, which suggests that most employees had a clear understanding of their du- ties. This clarity is crucial as it reduces confusion and frustration, enabling employees to perform efficiently, contribute effectively, and experience greater job satisfaction. However, other non-monetary factors such as work-life balance, career develop- ment opportunities, and leadership also played critical roles in influencing turnover decisions. For instance, regarding work-life balance, 26.36% strongly agreed and 19.09% agreed that their organization provided an adequate balance, yet a significant 33.64% disagreed and 17.27% strongly disagreed, revealing that many employees felt overburdened or unable to manage work and non-work activities effectively. This imbalance can lead to stress, burnout, and eventual dissatisfaction. Similarly, percep- tions of career growth opportunities showed a divided response, with only 18.18% strongly agreeing and 35.45% agreeing, while 29.09% disagreed and 17.27% strong- ly disagreed, indicating that limited career advancement prospects were a significant concern for many employees. When employees perceive a lack of growth or stag- nation in their roles, it often prompts them to seek better opportunities elsewhere. Lastly, leadership emerged as a critical factor, as 30.91% strongly agreed and 27.27% agreed with the statement, “People usually don’t quit jobs; they usually quit bosses”. This indicates that employees place significant importance on their relationship with their managers. Poor leadership, lack of recognition, or a negative work environment

created by bosses can erode trust and morale, pushing employees to leave despite other favourable conditions. These insights highlight that while role clarity provides a foundation for satisfaction, unresolved challenges in work-life balance, career progression, and leadership practices remain major drivers of voluntary turnover, requiring organizations to address these concerns holistically to increase retention. The results of this survey indicated that all of the factors selected for examination are perceived as critical in accelerating voluntary turnover intentions of Ugandan con- struction employees.

Figure 2b bar chart illustrates the frequency of recognition received by employ- ees in their previous organizations and highlights additional NMFs influencing vol- untary employee turnover. The mean rating of 3.19 for recognition suggests a mod- erate level, where 35.45% of employees reported “always” receiving recognition, while 38.18% indicated “often”, and smaller proportions experienced it “sometimes” (18.18%) or “rarely” or “never”. Recognition is critical to employee motivation and engagement, as it reinforces a sense of value and appreciation for their contri- butions. However, inconsistent recognition practices can leave employees feeling undervalued, negatively impacting morale and increasing turnover risk. Similarly, only 30% of participants felt they “always” participated in decision-making process- es, while 37.27% reported doing so “often” and 20% “sometimes”, indicating a gap in involving employees in organizational decisions. This lack of involvement can lead to disengagement and reduced loyalty, as employees may feel their perspectives are not valued. Furthermore, 34.55% of employees “always” experienced work-re- lated stress, and 43.64% reported it “often”, pointing to significant workplace stress levels that could contribute to dissatisfaction and attrition if not addressed through better support systems. Additionally, only 34.55% of participants indicated that their organization “always” provided adequate training and development opportu- nities, while another 34.55% felt it occurred “often”, leaving a notable proportion who experienced it only “sometimes” or “rarely”. Limited opportunities for growth and skill development can cause frustration and stagnation, prompting employees to seek external opportunities. Collectively, these findings underscore the impor- tance of regular recognition, stress management, employee involvement, and robust training programs to improve job satisfaction, engagement, and retention while re- ducing voluntary turnover. Overall, the survey results categorize these factors into those of greater concern and those of moderate concern, providing insights into the perceived influence and impact of these NMFs on voluntary employee turnover in- tentions in the Ugandan construction industry. This categorization does not necessar- ily mean that factors of moderate concern do not have significant influence on em- ployee turnover intentions; it simply means that they are perceived to be slightly less influencing from the perception of employees. It should be reiterated that all anal- ysed factors were found to be significantly expediting employee turnover intentions. Figure 2c bar chart highlights the extent to which job security influenced em- ployees’ decisions to leave their organizations, with a mean rating of 3.91, indicating

a relatively high level of concern. The chart shows that 40% of participants reported job security had a “strong influence” on their decision, while 29.09% indicated it had a “moderate influence”, and smaller proportions cited “slight influence”, “no influ- ence”, or “not applicable”. This demonstrates that job insecurity is a significant fac- tor driving voluntary turnover. An insecure job environment often generates anxiety, uncertainty, and dissatisfaction among employees, reducing their trust in the organi- zation and prompting them to seek more stable employment opportunities elsewhere. Such conditions may arise from frequent layoffs, unclear organizational strategies, or unpredictable work conditions. To address this issue, organizations need to fo- cus on creating a sense of stability and trust by fostering transparent communication, outlining long-term goals, and implementing employment practices that ensure sta- bility. By prioritizing job security, employers can reduce anxiety, enhance employee loyalty, and retain their most valuable talent, thus contributing to organizational success. Over 55% and 36% of our participants lie within the age range of 21–30 and 31–40 years respectively. Generation Y, Millennials (1981–2000) are reported to exhibit a short-term attachment or commitment towards their work organizations. They have a preference towards working with clear expectations, with a significant number expecting job security as their top priority (Pipe, Madadi, 2015). Perceptions of job instability and uncertainty about the future of work can decrease job satisfac- tion (Abolade, 2018; Gunawan et al., 2024) like in the case where over 70% of our participants confirmed that job security increased their turnover intent, then influ- enced and led to actual turnover.

Figure 2d bar chart illustrates employees’ perceptions of the leadership style of their previous supervisors or managers, which significantly impacts work-life balance and overall job satisfaction. A supportive leadership style, identified by 37.27% of respondents, fosters a positive work environment, helping employees manage work demands effectively and maintain a healthier work-life balance. How- ever, 28.18% described their managers as “authoritative”, and 21.82% felt their leadership was “micromanaging”, both of which can restrict employees’ autonomy and lead to stress and dissatisfaction. Additionally, an “uninvolved” leadership style, though reported by a smaller percentage, reflects a lack of guidance and support, potentially exacerbating challenges related to workload management and personal well-being. The mean rating of 2.65 for work-life balance highlights these leader- ship deficiencies and underscores their influence on employee burnout, stress, and turnover. Organizations should promote supportive leadership practices, such as open communication, delegation, and flexibility, to create a work culture that values employee well-being. By doing so, employers can address issues related to work- life balance enhancing employee satisfaction and reducing voluntary turnover. Over 60% argued and confirmed saying “People usually don’t quit jobs, they usually quit bosses” is true. A research survey conducted by Sara Korolevich revealed that 82% of American workers claimed they would potentially quit their jobs because of a bad manager (Korolevich, 2025) which highly relates with our findings. Bad

leadership styles such as authoritative and micromanaging can discourage the work- force, damage employee engagement and productivity, and lower morale to the point where people leave the organization (Unveiling the Truth…, 2025).

The chart in figure 2e highlights significant levels of work overload and stress experienced by employees, as evidenced by a mean rating of 4.08. This elevat- ed score underscores the pervasive challenge of excessive workloads which can have far-reaching negative impact on workers’ well-being, productivity and job sat- isfaction. High levels of stress are often associated with burnout, decreased morale, and diminished performance, all of which contribute to increased turnover inten- tions. Employees struggling to manage overwhelming demands may seek alternative employment opportunities that offer more balanced workloads and supportive en- vironments. To mitigate these challenges, organizations must prioritize assessing and redistributing workloads to ensure fairness and feasibility. Implementing stress management programs, such as wellness initiatives, counselling services, and flexi- ble scheduling, can further help employees cope with stress. Additionally, fostering a culture of support and open communication allows employees to voice concerns and access resources needed to maintain their health and performance. By addressing work overload and stress effectively, organizations can enhance workers’ satisfac- tion, lower turnover, and increase overall organizational resilience. Over 80% of our participants experienced work overload/stress in their previous workplaces. This may have caused reduced employees’ job involvement, energy depletion, and neg- ative behaviour. Additionally, work overload/stress brings about an increase in psychological withdrawal and turnover intentions (Eatough et al., 2011; Leung, Yu, Chong, 2016; Wen et al., 2020; Fathima, Umarani, 2022).

The chart in figure 2f presents employees’ perspectives on their involvement in decision-making processes, with a mean rating of 3.34. This moderate rating re- flects a mixed perception, indicating that while some employees felt engaged in de- cision-making, others perceived a lack of inclusion. Employee involvement in deci- sions, especially those directly affecting their roles, is critical for fostering a sense of ownership, accountability, and belonging within the organization. When employ- ees are excluded from these processes, it can lead to feelings of disengagement and undervaluation, contributing to higher turnover intentions. To address this, organiza- tions should adopt participative management practices that promote inclusivity and empower employees to contribute their perspectives. Strategies such as regular feed- back sessions, open forums, and collaborative planning can help ensure employees feel heard and valued. Additionally, transparent communication regarding organi- zational decisions enhances trust and strengthens the employer-employee relation- ship. By prioritizing employee involvement in decision-making, organizations can improve engagement, satisfaction, and overall retention. Only 37% of our partici- pants experienced satisfaction with the employee involvement in decision-making processes in their previous workplaces, which highlights a significant gap in foster- ing inclusion and belonging.

I

a)

I felt there was an adequate/enough healthy balance between the work and non-work activities

I was satisfied with the career growth opportunities at your previous organization

Frommy past experience, I believe/feel the saying

„People usually don't quit jobs, they usually quit

bosses" is true

O 1O 20 30 40 SO 60 70 80

-

b)

I had a elear understanding of my roles and

responsibilities in my previous organization

How often did you receive recognition for your

work?

How often did you participate in decision-making

processes at your workplace?

ometimes I experienced work-related stress in my

previous organization

y previous organization provided adequate training and development opportunities

1111

%

o 10 20 30 40 SO 60 70 80 90 100

lways ■ Often ■ Sometimes ■ Rarely ■ Never

c)

o what extent did job security influence your decision to leave the organization?

ot applicable ■ No influence ■ Slight influence ■ Moderate influence ■ Strong influence

Fig. 2. Analysis of non-monetary factors influencing voluntary employee turnover (a) Role

ambiguity (b) Recognition (c) Job security (d) Work-life balance (e) Work overload/stress

(f) Decision making involvement

Source: compilation based on own research.

Regarding the inferential statistical findings in table 4a, the reliability analysis using Cronbach’s Alpha yielded a coefficient of 0.735 for the 17-item scale. This suggests that the scale has acceptable internal consistency, meaning that the items are measuring the same underlying construct with a reasonable degree of reliabili- ty. The model in table 4b explains 60.1% of the variance in the dependent variable, which is a good level of explanatory power. This suggests a moderately strong rela- tionship between the predictors and the outcome variable. However, the Adjusted R Square of 0.532 suggests that some predictors may not be strong contributors, and model refinement may improve its predictive ability. The regression model in ta- ble 5 identifies key predictors that significantly impact PE17. The predictors PE3 (B = 0.183, p = 0.021), PE5 (B = -0.135, p = 0.010), PE6 (B = 0.177, p = 0.013),

PE8 (B = 0.234, p = 0.009), and PE10 (B = 0.175, p = 0.014) are the key variables influencing PE17 since (p < 0.05).

Tab. 4(a) Reliability Statistics

Tab. 4b. Model Summary

a Predictors: (Constant), PE16, PE15, PE8, PE1, PE4, PE5, PE7, PE10, PE13, PE6, PE11, PE12, PE3, PE9, PE2, PE14

Tab. 5. Regression Coefficientsa

Source: compilation based on own research.

Collectively, these results emphasize the need for companies to establish com- prehensive training programs, promote a culture of development, and actuate their employees to reduce turnover intentions. Work-life balance, work overload/stress, decision-making involvement, and job security showed mean ratings of great con- cern, which means they play an influential role in accelerating voluntary turnover intentions of construction employees. A poor work-life balance, evident with over 60% of our participants having experienced this in their previous workplaces, is a menace to a healthy equilibrium between work and personal life, which can lead to extra job dissatisfaction and increased turnover rates.

Although influencing factors such as teamwork, communication gaps, recogni- tion, and role ambiguity were found with mean ratings of moderate concern, these mean ratings still indicate a negative impact on job satisfaction, hence contributing to voluntary employee turnover intentions. By addressing these areas, construction companies can establish a more supportive and inclusive work environment where all employees can flourish and give their all. The study findings can assist construction companies to develop targeted interventions to improve employee retention, engage- ment, and productivity. The subsequent discussion delves into a more comprehensive analysis of the survey findings, examining the implications and providing a profound understanding of the results. Some of the most remarkable findings from the pivot charts are the factors with mean ratings of greater concern that included training and career development, with over 65% of our participants expressing their dissatisfac- tion, which directly agrees with Karakhan et al. This research reported employees with insufficient knowledge and skills related to their work indicated a higher in- tention to quit voluntarily (Karakhan et al., 2024). Additionally, more research also concluded that construction employees’ need for training and career advancement is a major factor in their decision to quit (Holt, Love, Jawahar Nesan, 2000). Therefore, construction companies should establish comprehensive training programs and pro- mote a culture of training and professional advancement to actuate their employees, hence reducing turnover intentions.

Conclusion

This study aimed to identify primary non-monetary factors driving voluntary employee turnover in Uganda’s construction industry and to examine their influence on employ- ees’ intentions to leave. To achieve this objective, the research began with an extensive review of existing literature to uncover the key contributors to high turnover rates with- in the sector. These factors were categorized into crucial domains, including the work environment (e.g., poor management, lack of resources, unsafe conditions), job sat- isfaction (e.g., monotonous tasks, lack of recognition, limited growth opportunities), work-life balance (e.g., inflexible schedules, long hours of working, high stress lev- els), interpersonal relationships (e.g., conflicts with colleagues, poor team dynamics, lack of support), organizational culture (e.g., misalignment with values, lack of inclu- sivity, poor communication), and career development (e.g., limited training programs, lack of mentorship, stagnant career progression).

The findings from both the descriptive and inferential analyses of the study re- veal that these factors significantly influence turnover intentions among employees in Uganda’s construction industry. Specifically, training and career development, work-life balance, work overload/stress, involvement in decision-making, job secu- rity, and leadership style were identified as the most influential factors driving turn- over. The impact of these factors was shown to outweigh that of other factors such

as teamwork, communication gaps, recognition, and role ambiguity. The insights gained from this study are intended to provide actionable strategies for reducing em- ployee turnover and fostering organizational success through improved workforce management practices.

To address these pressing concerns, construction companies can implement tar- geted interventions aimed at enhancing employee retention, engagement, and pro- ductivity. Recommendations include adopting 360-degree feedback mechanisms, im- plementing comprehensive training programs tailored to industry needs, encouraging flexible work schedules, promoting employee well-being initiatives, and actively monitoring workloads to prevent burnout. Organizations should also foster partici- pative decision-making models to create a sense of inclusiveness and transparency, ensure job stability to build trust and loyalty, and emphasize ethical leadership prac- tices. Additionally, introducing employee appreciation programs, public recognition initiatives, and performance-based rewards can reinforce employees’ sense of value and commitment. By addressing these critical areas, construction firms can signifi- cantly reduce turnover rates and build a more motivated and productive workforce.

This study offers insightful information about the role of NMFs in employee turnover within Uganda’s construction industry. However, it is important to acknowl- edge certain limitations. First, the non-monetary factors analysed in this research are not exhaustive, and additional factors may also significantly influence employee turnover. Future studies could explore these overlooked factors and further assess their impact on turnover in the construction sector within Uganda.

Another limitation lies in the sample size, which consisted of 110 participants. While this sample size is adequate for drawing meaningful conclusions, it may not fully represent diverse perspectives of all employees in the construction sector. Ad- ditionally, the survey was administered through an online platform, which may have introduced selection bias, as not all construction workers have equal access to or familiarity with online tools. This potential bias may limit the findings’ applicability to the broader population of construction workers.

Moreover, this study focused on skilled professionals such as lab technicians, en- gineers, and managers, while views of other key stakeholders, such as executives and clients, were not included. To enhance the scope and applicability of future research, it is recommended to involve larger, more diverse samples and adopt a mixed-meth- od approach. This would enable a deeper understanding of how non-monetary factors influence not only employees but also other critical stakeholders in the construction industry. Such an approach would improve the generalizability and comprehensive- ness of the findings across a wider population.

References

Abdolmaleki G., Naismith N., Ghodrati N., Poshdar M., Babaeian Jelodar M. (2024), An analysis of the literature on construction employee turnover: Drivers, consequences, and future direction, “Construction Management and Econo- mics”, vol. 42(9), pp. 822–846, https://doi.org/10.1080/01446193.2024.233

7084

Abolade D.A. (2018), Impact of employees’ job insecurity and employee turnover on organisational performance in private and public sector organisations, “Studies in Business and Economics”, vol. 13(1), pp. 5–19, https://doi. org/10.2478/SBE-2018-0016

Abowitz D.A., Toole T.M. (2009), Mixed method research: Fundamental issues of design, validity, and reliability in construction research, “Journal of Con- struction Engineering and Management”, vol. 136(1), pp. 108–116, https:// doi.org/10.1061/(ASCE)CO.1943-7862.0000026

Ait Alla A., Rajâa O. (2019), A review of the literature on employee turnover, “Ame- rican International Journal of Social Science”, vol. 8(3), pp. 49–54, https:// doi.org/10.30845/aijss.v8n3p4

Aregay A. (2021), An assessment of the causes and effects of employees’ turnover: The case of Defence Construction Enterprise, unpublished master’s thesis, St. Mary’s University, Ethiopia.

Bilau A.A., Ajagbe M.A., Sholanke A.B., Sani T.A. (2015), Impact of employee turno- ver in small and medium construction firms: A literature review, “Internatio- nal Journal of Engineering Research and Technology”, vol. 4(2), pp. 976–984.

Boies K., Fiset J., Gill H. (2015), Communication and trust are key: Unlocking the relationship between leadership and team performance and creativi- ty, “The Leadership Quarterly”, vol. 26(6), pp. 1080–1094, https://doi.or- g/10.1016/j.leaqua.2015.07.007

Bröchner J., Badenfelt U. (2011), Changes and change management in construction and IT projects, “Automation in Construction”, vol. 20(7), pp. 767–775, https://doi.org/10.1016/j.autcon.2011.01.001

Chih Y.-Y., Kiazad K., Zhou L., Capezio A., Li M., Restubog S.L.D. (2016), Investi- gating employee turnover in the construction industry: A psychological con- tract perspective, “Journal of Construction Engineering and Management”, vol. 142(6), article no. 04016018, https://doi.org/10.1061/(ASCE)CO.1943-

7862.0001101

Dahl H.M. (2010), An old map of state feminism and an insufficient recognition of care, “NORA – Nordic Journal of Feminist and Gender Research”, vol. 18(3), pp. 152–166, https://doi.org/10.1080/08038740.2010.498325

Eatough E.M., Chang C.H., Miloslavic S.A., Johnson R.E. (2011), Relationships

of role stressors with organizational citizenship behavior: A meta-analy-

sis, “Journal of Applied Psychology”, vol. 96(3), pp. 619–632, https://doi. org/10.1037/a0021887

Elçi M., Şener İ., Aksoy S., Alpkan L. (2012), The impact of ethical leadership and leadership effectiveness on employees’ turnover intention: The mediating role of work-related stress, “Procedia – Social and Behavioral Sciences”, vol. 58, pp. 289–297, https://doi.org/10.1016/j.sbspro.2012.09.1003

Elstad J.I., Vabø M. (2021), Lack of recognition at the societal level heightens turno- ver considerations among Nordic eldercare workers: A quantitative analysis of survey data, “BMC Health Services Research”, vol. 21(1), 1–10, https:// doi.org/10.1186/s12913-021-06734-4

Fathima M.H., Umarani C. (2022), A study on the impact of role stress on engineer intention to leave in Indian construction firms, “Scientific Reports”, vol. 12,

pp. 1–11. https://doi.org/10.1038/s41598-022-21730-2

Fellows R., Liu A. (2021), Research methods for construction (5th ed.), Hoboken: Wiley-Blackwell.

Galea N., Powell A., Loosemore M., Chappell L. (2020), The gendered dimensions of informal institutions in the Australian construction industry, “Gender, Work & Organization”, vol. 27(7), pp. 1214–1231, https://doi.org/10.1111/ gwao.12458

Goh Jiaying A., Muda A.L. (2023), The effect of career growth on employee turnover intention in Sarawak construction industry, “Journal of Cognitive Sciences and Human Development”, vol. 9(2), pp. 133–150, https://doi.org/10.33736/ JCSHD.5879.2023

Gunawan H., Pala R., Tijjang B., Razak M., Qur’ani B. (2024), Global challenges of the mining industry: Effect of job insecurity and reward on turnover in- tention through job satisfaction, “South African Journal of Human Resour- ce Management”, vol. 22, article no. 2555, https://doi.org/10.4102/sajhrm. v22i0.2555

Han E. (2024), Root cause analysis: What it is & how to perform one, https://online. hbs.edu/blog/post/root-cause-analysis [accessed: 29.05.2025].

Holt G.D., Love P.E.D., Jawahar Nesan L. (2000), Employee empowerment in con- struction: an implementation model for process improvement, “Team Perfor- mance Management”, vol. 6(3/4), pp. 47–51, https://doi. org/10.1108/13527590010343007

Hom P.W., Griffeth R.W. (1995), Employee turnover, Ohio: Cincinnati, South-We- stern College Publishing.

Jinisha K.P., Safa C.T., Basima Parveen T.P (2023), Employee retention analy- sis in construction industry.“ International Advanced Research Journal in Science, Engineering and Technology”, vol. 10, pp. 153–164, https://doi. org/10.17148/IARJSET.2023.10126

Job openings and labor turnover (2024), U.S. Bureau of Labor Statistics, https:// www.nj.gov/labor/labormarketinformation/assets/PDFs/JOLTS/JOLTS%20 Nov%202024%20final.pdf [accessed: 29.05.2025].

Kabir A.A., Tirno R.R., Kabir M.A.A. (2018), Impact of work-life balance on em- ployees’ turnover and turnover intentions: An empirical study on multinatio- nal corporations in Bangladesh, “Jahangirnagar University Journal of Ma- nagement Research”, vol. 1, pp. 15–32.

Karakhan A.A., Nnaji C.A., Alsaffar O., Jin Z. (2024), Strategies for employee empo- werment in construction: US industry outlook, “Practice Periodical on Struc- tural Design and Construction”, vol. 29(1), pp. 1–7, https://doi.org/10.1061/ PPSCFX.SCENG-1438

Katende J., Alinaitwe H., Tindiwensi D. (2011), A Study into the Factors Hindering Development of the Construction Industry in Uganda, [in:] Proceedings of the Second International Conference on Advances in Engineering and Technology, Diamond Scientific Publishing, Vilnius, pp. 332–338.

Khan N.A., Khan N.A., Soomro M.A. (2020), Influence of ethical leadership in ma- naging human resources in construction companies, “Journal of Construc- tion Engineering and Management”, vol. 146(2), pp. 1–12, https://doi. org/10.1061/(ASCE)CO.1943-7862.0001919

Korolevich S. (2025), Horrible bosses: A survey of the American workforce, https:// www.goodhire.com/resources/articles/horrible-bosses-survey/ [accessed: 29.05.2025].

Korolevich S. (2025), Horrible bosses: A survey of the American workforce, https:// www.goodhire.com/resources/articles/horrible-bosses-survey/ [accessed: 29.05.2025].

Lanchaster L. (2024), Effects of high turnover among employees, https://stratus.hr/ resources/effects-of-high-employee-turnover [accessed: 29.05.2025].

Landu P. (2025), Root Cause Analysis: A Quick Guide, https://www.projectmanager. com/blog/root-cause-analysis-guide [accessed: 30.05.2025].

Lee T.W., Mitchell T.R. (1994), An alternative approach: The unfolding model of vo- luntary employee turnover, “Academy of Management Review”, vol. 19(1),

pp. 51–89, https://doi.org/10.5465/amr.1994.9410122008

Lepak S. (2024), Causes and effects of employee turnover [2025], https://matterapp. com/blog/causes-and-effects-employee-turnover [accessed: 29.05.2025].

Lestari D., Margaretha M. (2021), Work life balance, job engagement and turnover intention: Experience from Y generation employees, “Management Science Letters”, vol. 11, pp. 165–170, https://doi.org/10.5267/j.msl.2020.8.019

Leung M.-Y., Yu J., Chong M.L.A. (2016), Effects of stress and commitment on the performance of construction estimation participants in Hong Kong, “Journal of Construction Engineering and Management”, vol. 142(2),

pp. 1–10, https://doi.org/10.1061/(ASCE)CO.1943-7862.0001059

Li Y., Soomro M.A., Khan A.N., Han Y., Xue R. (2022), Impact of ethical leader- ship on employee turnover intentions in the construction industry, “Jour- nal of Construction Engineering and Management”, vol. 148(2), pp. 1–16, https://doi.org/10.1061/(ASCE)CO.1943-7862.0002303

Livne-Ofer E., Coyle-Shapiro J.A.M., Pearce J.L. (2019), Eyes wide open: Perceived exploitation and its consequences, “Academy of Management Journal”, vol. 62(6), pp. 1989–2018, https://doi.org/10.5465/amj.2017.1421

Meier K.J., Hicklin A. (2007), Employee turnover and organizational performance: Testing a hypothesis from classical public administration, “Journal of Public Administration Research and Theory”, vol. 18(4), pp. 573–590, https://doi. org/10.1093/jopart/mum028

Meyer V., Culié J.D., Philippe X., Sorreda T., Garcia J.F., Tessier L. (2024), ‘The great resignation’: The ambivalences of the liquid employee facing a consumerist work relationship, “European Management Journal”, https:// doi.org/10.1016/j.emj.2024.11.008

Nauman S., Zheng C., Ahmad R. (2021), Employee career outlook and turnover: Unleashing the roles of career adaptability and career satisfaction in in- ternational construction projects, “Journal of Construction Engineering and Management”, vol. 147(6), pp. 1–12, https://doi.org/10.1061/(ASCE) CO.1943-7862.0002150

Pipe C., Madadi V. (2015), Are we on the same jobsite? Expectations of millennial students vs. construction industry employees, https://papers.iafor.org/wp-con- tent/uploads/papers/ecss2015/ECSS2015_11468.pdf?utm_source=chatgpt. com [accessed: 2.07.2025].

Putri A.R., Renwarin J.M.J. (2023)., The effect of leadership and teamwork on em- ployee turnover and team performance, “Human Capital and Organization”, vol. 1(1), pp. 46–54, https://doi.org/10.58777/hco.v1i1.121

Saniewski L.L., McGunagle D. (2011), The impact of leadership on employee reten- tion “ProQuest Dissertations and Theses Global”, article no. 3462491.

Ssekamatte A. (2010), HR managers grapple with high turnover rate, https://www. monitor.co.ug/uganda/magazines/jobs-and-career/hr-managers-grapple- with-high-turnover-rate-1475898 [accessed: 29.05.2025].

Stelson A. (2021), Organization’s strategic orientation and intention to leave among staff: A case study of staff of National Housing and Construction Company Limited, Kampala, unpublished master’s thesis, Kyambogo University.

Unveiling the Truth: People Don’t Quit Jobs, They Quit Bosses (2025), https://well- hub.com/en-us/blog/talent-acquisition-and-retention/people-dont-quit-jobs- they-quit-bosses/ [accessed: 30.05.2025].

Wen B., Zhou X., Hu Y., Zhang X. (2020). Role stress and turnover intention of front- line hotel employees: The roles of burnout and service climate, “Frontiers in Psychology”, vol. 11, pp. 1–13, https://doi.org/10.3389/fpsyg.2020.00036

Zaheer S., Ginsburg L., Wong, H.J., Thomson K., Bain, L., Wulffhart, Z. (2019), Turnover intention of hospital staff in Ontario, Canada: Exploring the role of frontline supervisors, teamwork, and mindful organizing, “Human Re- sources for Health”, vol. 17, article no. 66, https://doi.org/10.1186/s12960- 019-0404-2

Zhang Y. (2016), A review of employee turnover influence factor and countermea- sure, “Journal of Human Resource and Sustainability Studies”, vol. 4(2),

pp. 85–91, https://doi.org/10.4236/jhrss.2016.42010

About the Author

Anu Mary Ealias – Assistant Professor at Koneru Lakshmaiah Education Foundation University (KL University) in Vijayawa- da, India, in the Department of Civil Engineering. Her research focuses on environmental engineering, particularly the synthe- sis and characterization of nanomaterials and their application in dye removal from textiles and wastewater treatment.

O autorce

Anu Mary Ealias – adiunktka w Koneru Lakshmaiah Educa- tion Foundation University (KL University) w Vijayawadzie, In- die, w Katedrze Inżynierii Lądowej. Jej badania koncentrują się na inżynierii środowiska, w szczególności na syntezie i charak- terystyce nanomateriałów oraz ich zastosowaniu w usuwaniu barwników z tekstyliów i oczyszczaniu ścieków.

Ten utwór jest dostępny na licencji Creative Commons Uznanie autorstwa-Na tych samych warunkach 4.0 Międzynarodowe.