Turnover Risk Research Articles

Abstract This study investigates the trade-off between perceived productivity gains and career concerns under consideration of new ways of management control in corporate coworking, where teams are deployed to coworking spaces to foster innovation. Employing a methodological triangulation, we combine a principal-agent-based mathematical model with a qualitative multi-case study of eight corporate coworking teams, drawing on 31 semi-structured interviews with employees and employers. Our findings show that teams in coworking spaces perceive productivity gains driven by increased motivation, creativity, and team collaboration facilitated by physical proximity and co-discipline. At the same time, these environments lower barriers for external career networking, thereby increasing the perceived risk of employee turnover. To navigate this trade-off, employers must adjust traditional management control mechanisms to fit the corporate coworking context. In addition to personnel selection and incremental output monitoring, cultural control, role modeling, and fostering an intrapreneurial mindset emerge as key levers to affect the employees’ behavior respectively. By integrating theoretical modeling with empirical evidence, this study contributes to the literature on management control and extends the emerging discourse on corporate coworking. For practitioners, it offers actionable insights into selecting suitable employees for coworking environments and balancing autonomy with appropriate control. Ultimately, our work highlights the nuanced dynamics of corporate coworking and provides strategies to leverage its innovation potential while mitigating career-related mobility risks.

BackgroundSexual harassment experienced by nurses in the workplace is a serious occupational health hazard that undermines their physical and psychological well-being, reduces job satisfaction, and thereby increases the risk of turnover and burnout.MethodsBetween December 2024 and January 2025, a total of 500 nurses from five hospitals in China were recruited for the study. The Chinese version of the nurse sexual harassment scale underwent cross-cultural adaptation and psychometric evaluation in accordance with the Beaton guidelines and the COSMIN checklist. The psychometric properties, including content validity, structural validity, internal consistency, test-retest reliability, and measurement error.ResultsThe Chinese version of the nurse sexual harassment scale is composed of 14 items divided into two dimensions: latent sexual harassment and manifest sexual harassment. The scale demonstrated a scale-level content validity index of 0.972, with item-level content validity index values ranging from 0.8 to 1.00. Exploratory factor analysis identified two factors that accounted for 77.785% of the total variance, while confirmatory factor analysis confirmed a good fit for the two-factor model. The overall Cronbach’s alpha of scale was 0.956, a test-retest reliability of 0.847, and the Cronbach’s alpha of latent and manifest sexual harassment dimensions were 0.931 and 0.972, respectively. Furthermore, the smallest detectable change was 2.321, and the scale demonstrated satisfactory responsiveness.ConclusionsThe Chinese version of the nurse sexual harassment scale displays strong validity and reliability, making it an effective tool for assessing nurses’ experiences of sexual harassment within the Chinese cultural context.

BackgroundIn high-pressure environments such as intensive care units (ICUs), newly graduated nurses often experience heightened transition shock during role adaptation, which increases the risk of burnout and turnover. Consequently, facilitating a smooth transition for nurses during their ICU rotations is a persistent challenge for nursing managers and educators.AimThe purpose is to explore the dilemmas and strategies perceived by resident training nurses during their ICU rotation work.MethodsA qualitative study was conducted. Nineteen resident training nurses who rotated in the ICU were recruited. Face-to-face interviews, semi-structured interviews, and content analysis were utilized to analyze the data.ResultsFour key themes were identified: (1) Experiencing Overwhelming Work Tasks; (2) Experiencing a Fast-Paced Working Pattern; (3) Experiencing a Strained Working Atmosphere; and (4) Experiencing a Generalized Teaching Program. The subthemes of each theme reflect the unique nature of ICU work as perceived by the rotating nurses, corresponding to their perceptions of specific work dilemmas and the strategies they have derived.ConclusionsThe resident training nurses experienced a complex journey of disorientation and adaptation during their ICU rotation. This can be attributed to overwhelming work tasks, fast-paced work patterns, strained work atmospheres, and generalized teaching programs. Nursing managers and educators need to optimize the teaching system for resident training nurses rotated in the ICU and enhance the humanistic care mechanisms for nurses at the organizational level.

The present study is concerned with the critical challenges confronting Ukrainian small and medium-sized enterprises (SMEs) in personnel management in the context of economic instability and wartime conditions. Conventional human resources instruments, such as interviews and the evaluation of résumés, have been shown to be deficient in accurately assessing candidates' behavioural, cognitive and emotional compatibility. This has resulted in elevated levels of employee turnover and protracted periods of vacant positions being filled. In order to address the aforementioned shortcomings, the article proposes a novel integrated human resources (HR) management approach that combines Thomas International psychometric testing (namely, Personal Profile Analysis (PPA), General Intelligence Assessment (GIA), High Potential Trait Indicator (HPTI), and Trait Emotional Intelligence Questionnaire (TEIQue)) with the principle-oriented framework of PMBOK® 7 and advanced AI-driven analytics. A thorough analysis of openly published Western case studies, including those from Everything Office, Johnsons Workwear, and Ice River Springs, reveals significant outcomes: up to a 50% reduction in employee turnover, a 30% decrease in vacancy time-to-fill, and an 18–22% increase in team productivity following the implementation of this three-component model. Utilising these findings, the study proposes an adaptive HR model customised for crisis environments. This model personalises motivational strategies based on employees' behavioural, cognitive and emotional profiles, accelerates onboarding processes, and enhances organisational resilience in unpredictable conditions. The scientific novelty of the present study lies in the synthesis of psychometrics, project management principles, and artificial intelligence into a cohesive HR management system, offering quantitative diagnostics of employee engagement and stress resilience. This is of particular relevance for Ukrainian businesses during wartime and post-crisis recovery. Practical recommendations are provided for the phased integration of psychometric testing, PMBOK-aligned HR processes, and AI-driven monitoring into Ukrainian SMEs, with the objective of optimising recruitment, retention, and employee development. These include the establishment of ethical testing protocols, the benchmarking of job roles, and the implementation of quarterly AI analytics to predict turnover risks. The implementation of these measures is intended to foster sustainable business operations in challenging contexts.

Background Despite recent policy initiatives promoting disability employment, employees with disabilities in Japan often face considerable adaptation challenges during the early stages of their careers. Issues such as role ambiguity, low self-efficacy, and difficulties with emotional regulation can heighten stress levels and increase turnover risk, particularly within highly regulated employment settings. Objective This study aimed to identify and categorize workplace adaptation challenges experienced by employees with disabilities during their first five years of employment in Japanese special-purpose subsidiaries. Methods Semi-structured interviews were conducted with six employees with psychiatric, developmental, intellectual, or visual disabilities. Data were thematically analyzed to uncover key adaptation challenges, guided by organizational socialization, supportive relationship, and self-efficacy theories. Findings were then interpreted through Schlossberg's 4S model (Situation, Self, Support, Strategy) to propose evidence-based support strategies. Results Eleven distinct adaptation challenges emerged, classified as either organizational socialization issues (e.g., reality shock, unclear expectations) or disability-specific issues (e.g., reduced self-efficacy, emotional stress). These challenges negatively affected participants’ psychological well-being and underscored the need for individualized support measures. Conclusions The 4S model provided a valuable framework for understanding early workplace adaptation and designing targeted interventions. Findings highlight the importance of structured onboarding, mentoring, and inclusive HR practices to promote retention, mental health, and long-term employment sustainability for employees with disabilities.

ABSTRACT Using Conservation of Resources theory, this study investigates the intricate relationships between hotel employees’ emotional labour, well-being (mindfulness, job satisfaction, quality-of-life), and turnover intentions. A survey of 393 Korean hotel staff revealed that coping methods, proactive customer service, and service recovery work positively influence mindfulness and job satisfaction. Emotional regulation had negative effects. Comparative analyses uncovered key differences between low and high turnover risk groups. The findings emphasise the importance of cultivating a supportive work environment and the central role of job satisfaction in enhancing overall employee well-being. The study offers valuable insights for hotel managers to promote staff welfare and retention.

Objective: The purpose of this study was to examine the impact of professional identity on clinical nurses' job embeddedness and the role of organizational climate and compassion fatigue in this relationship.Background: Nurses' job embeddedness has been a focus of attention in nursing, with lower levels of job embeddedness diminishing nurses' sense of commitment and belonging to their profession, increasing the risk of turnover, and affecting teamwork and continuity of care, thereby adversely affecting quality of care and patient safety. Therefore, improving the level of job embeddedness of nurses is important for stabilizing the nursing workforce and optimizing the quality of nursing services.Methods: This study used a convenience sampling method to conduct a cross-sectional survey from July to October 2024 among 661 clinical nurses in three general hospitals in Henan Province. The survey instruments included the Nurse Professional Identity Scale, Organizational Climate Scale, Compassion Fatigue Scale, and Job Embeddedness Scale. The participants were certified, formally employed nurses capable of independently performing clinical duties and who voluntarily agreed to participate. Nurses who withdrew during the study, were unable to complete the survey due to special circumstances, or submitted incomplete questionnaires were excluded. Data analysis was conducted using SPSS 25.0, while AMOS 26.0 was used for model construction and mediation path analysis.Results: The nurses' job embeddedness score was 21.93 ± 6.09, professional identity was a significant positive predictor of their job embeddedness (r = −0.437, p < 0.01), and organizational climate and compassion fatigue were chained mediators in their professional identity and job embeddedness (β = 0.034, p < 0.01). The mediator model showed a good fit.Conclusions: Clinical nurses' professional identity is significantly positively correlated with their job embeddedness, and organizational climate and compassion fatigue play a chain mediating role between the two. Therefore, hospital administrators should pay attention to nurses' professional identity and take organizational climate and compassion fatigue as entry points to develop a series of targeted measures to enhance their job embeddedness.

Promoting internal employees to managerial positions (internal sourcing) is a popular employee retention tactic. Although some research indicates that internal sourcing reduces voluntary turnover, conflicting evidence suggests that internal sourcing strategies make employees more difficult to retain in strong job markets (i.e., when job opportunities are plentiful relative to job seekers) because promotions increase an employee's external marketability. The onset of the COVID-19 pandemic-a global exogenous shock that triggered an event chain characterized by a weak job market followed by a historically strong one-provided a unique opportunity to test these competing perspectives. Drawing upon event system theory and the unfolding model of turnover, we argue that internal sourcing creates positive perceptions among employees about their employer, making them less inclined to seek external opportunities during periods of heightened employee mobility. Specifically, we predict that internally sourced employees perceive lower levels of employment threat and higher levels of organizational support than those hired externally, which mitigates their turnover risk in strong job markets. We tested these predictions in two studies: a longitudinal field study involving 11,072 restaurant managers who were newly promoted or hired into their roles in the years surrounding the onset of the COVID-19 pandemic and the strong job market that followed and an experiment designed to mirror the field study conditions, in which we examined the psychological mechanisms underlying this phenomenon. Collectively, the results of our studies support our predictions, offering valuable insights into the effects of internal versus external sourcing on employee retention. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Employee turnover remains a critical challenge, particularly in high-pressure industries such as luxury fashion. This literature review investigates the influence of organizational commitment and work stress on turnover intention, with job satisfaction acting as a mediating variable. The study aims to synthesize recent empirical findings to identify consistent patterns and gaps in the relationship among these variables. A systematic review was conducted using 11 peer-reviewed journal articles published within the last ten years, selected from credible academic databases including Scopus, Google Scholar, and Emerald Insight. Articles were chosen based on their relevance, methodological rigor, and empirical focus on the key constructs. The analysis reveals that high work stress significantly increases turnover intention, while job satisfaction and organizational commitment reduce it. Moreover, job satisfaction plays a mediating role by buffering the adverse effects of stress and reinforcing commitment. The findings emphasize that organizations should strengthen employees’ emotional attachment and satisfaction to reduce turnover risks, particularly among younger generations facing high job demands. These insights provide strategic input for human resource management in designing effective retention programs and creating supportive work environments, especially within dynamic and competitive sectors.

This paper reviews artificial intelligence approaches to predicting the risks of employee turnover and managing strategies designed to retain them. The purpose of the current study is to carry out a systematic review and practical assessment of existing algorithms used as early warnings for personnel turnover in corporate environments and to recommend ways through which the derived models could be incorporated into HR management processes. The relevance of this work is determined by organizations’ enormous costs associated with replacing specialists, the rapid growth of the HR analytics market, and the need to shift from a reactive turnover management model to a proactive talent-retention system. The novelty of the research lies in the comprehensive comparison of classical statistical methods (logistic regression, CoxRF) and modern machine learning algorithms (XGBoost, LSTM-RNN, Bidirectional-TCN, graph neural networks) on both proprietary and open datasets, as well as in the incorporation of interpretability criteria (SHAP, LIME), organizational and ethical barriers, MLOps requirements, and EU regulatory standards into the architecture of predictive HR systems. The findings demonstrate that basic statistical models provide a rapid start and clear interpretability on small samples; however, as data volumes grow, gradient boosting emerges as the “gold standard,” and recurrent and convolutional networks become preferable for analyzing temporal communications. Graph neural networks improve flight-risk detection quality by accounting for social connections, while interpretability tools enable the translation of a score into a concrete retention plan. The key takeaway is the need for an integrated approach: starting from detailed data prep and cleanup, building a cross-functional team, setting up an MLOps loop, designing solutions ethically, training end-users, and monitoring success metrics regularly. This paper will be helpful to HR directors, people analytics specialists, AI-in-HR project managers, as well as academic researchers in the field of human capital management.

ABSTRACT This is one of the first studies to examine self-care and burnout scores among social work college students after the National Association of Social Workers (NASW) mandated that social workers practice self-care. A total of 117 social work college students participated in an online survey on self-care practices using a demographic questionnaire, the Self-Care Behavioral Inventory, and the Maslach Burnout Inventory. The results revealed high rates of burnout among college students in social work and highlighted the increased risk of turnover in the social work profession. Specifically, students who engaged in more self-care practices had lower burnout scores and sometimes reported practicing self-care. Surprisingly, over 40% of students reported high-level burnout on the emotional exhaustion subscale and 69% reported high-level burnout on the depersonalization subscale. Emotional exhaustion is considered the primary element of burnout, and this subscale alone should serve as a strong indicator of burnout. Despite NASW’s ethical mandate for social workers to practice self-care, this study revealed that social work students entering the profession do not prioritize self-care practices. As social work students are future practitioners, these findings highlight the need for social work programs to include a course exclusively dedicated to self-care.

Orientation: Voluntary employee turnover, particularly among Generation Z employees, is a growing concern due to their higher mobility and evolving workplace expectations. Understanding how these employees evaluate the value of current versus alternative job opportunities is crucial for improving turnover prediction and management. Research purpose: This study aimed to develop and validate the Alternative Job Net Value (AJNV) scale, a tool designed to measure the perceived net utility of present jobs versus job alternatives among Generation Z employees. Motivation for the study: Existing turnover models lack precise measurements of how employees assess their current positions against external opportunities. Addressing this gap is essential for organisations aiming to predict and reduce voluntary turnover among Generation Z. Research approach/design and method: Using an explanatory mixed-methods design, the study began with qualitative interviews to identify key factors influencing turnover, leading to the creation of an initial 28-item scale. The scale was refined through validity assessments and factor analyses. The final AJNV scale includes two subscales measuring the expected utility of the present job and job alternatives. Main findings: The AJNV scale showed strong construct validity and reliability for the present job subscale and moderate reliability for job alternatives. It captures factors such as career development, rewards, and organisational policies that influence turnover intentions among Generation Z. Practical/managerial implications: The AJNV scale offers organisations a diagnostic tool to assess turnover risk by comparing employees’ perceived value of current and alternative jobs, aiding retention strategies. Contribution/value-add: This study contributes to turnover research by providing a psychometrically robust tool for measuring job alternatives’ comparative value.

Abstract Workplace exclusion – often subtle and difficult to detect – significantly contributes to employee disengagement and turnover, costing US organizations over $1 trillion annually. This study examines how exclusionary behaviors (EBs) influence turnover intentions (TOIs) through disruption of psychological needs, using Rock’s SCARF model (Status, Certainty, Autonomy, Relatedness, Fairness) and self-determination theory. A two-wave survey of full-time US employees (N = 277) assessed EB, SCARF-based need satisfaction, and TOI. Partial least squares structural equation modeling revealed that EB significantly undermines all five SCARF domains, but only fairness and status mediated the EB–TOI link. Certainty, autonomy, and relatedness did not have significant effects. These findings suggest turnover risk intensifies when employees feel unfairly treated or socially devalued, rather than merely disempowered or disconnected. The study advances theoretical integration between SCARF and SDT and offers practical guidance for managers seeking to reduce attrition by fostering inclusive, respectful, and psychologically safe workplace environments.

The article systematizes contemporary approaches to integrating neural networks and artificial-intelligence (AI) tools across all core human-resource management (HR) processes. Drawing on BCG industry reports and specialized studies, it demonstrates that neural networks accelerate recruitment through automatic résumé screening, candidate ranking and round-the-clock chatbot support, thereby reducing recruiter workload by up to ten percent and shortening average vacancy-closure time by roughly forty percent. The paper outlines analytical models that predict turnover risk and help design personalized career trajectories. Adaptation functions include automatic generation of check-lists, early detection of burnout signs and development of individual learning programmes. Confidentiality challenges are analysed, notably potential data leaks and model “hallucinations” that necessitate multi-level fact-checking. The practical value of hybrid architectures that combine on-premise and cloud neural networks to balance security and cost efficiency is underlined. Separate attention is given to the growth of prompt-engineering skills among HR professionals, enabling precise task formulation and mitigating legal risks. Examples are provided of chatbots conducting brief preliminary interviews and clarifying candidate expectations. The article notes that analytical modules can aggregate employee feedback and generate dynamic mood reports at the team level. The authors emphasize that successful AI integration requires continuous data-quality monitoring and regular algorithm updates. The findings confirm the high efficiency and future relevance of neural-network integration into HR processes, provided that information-security requirements and ethical standards are strictly observed.

An increasing body of research has explored the impact of job demands and resources on employee wellbeing and performance; however, empirical evidence remains limited regarding how these factors operate in non-Western contexts. Addressing this gap, the present study examines blue-collar (70.7%) and white-collar (29.3%) workers in Türkiye, investigating the effects of job demands (quantitative, cognitive, emotional) and job resources (leader support, co-worker support, trust) on emotional exhaustion, job satisfaction, organizational commitment, and intention to leave. A total of 563 employees from three large production companies in Türkiye voluntarily participated in this study. Data were collected using the Turkish version of the Copenhagen Psychosocial Questionnaire (COPSOQ-III) for all constructs, except for intention to leave, which was assessed using the Michigan Organizational Assessment Questionnaire (MOAQ). The proposed relationships were analyzed through multi-group structural equation modeling (MG-SEM). Job demands significantly increased emotional exhaustion in both blue- and white-collar workers. However, while emotional exhaustion did not diminish organizational commitment among blue-collar workers, job satisfaction emerged as a key determinant in reducing their turnover intentions. In contrast, for white-collar workers, emotional exhaustion weakened organizational commitment, ultimately leading to higher turnover intentions. Moreover, job resources enhanced job satisfaction and indirectly reduced turnover intentions for blue-collar workers, whereas these resources did not significantly predict job satisfaction among white-collar workers. These findings underscore the importance of tailoring workplace strategies to different occupational groups in a non-Western setting. Strengthening job resources-particularly trust, leader support, and co-worker support-can enhance job satisfaction and reduce turnover risk among blue-collar workers. Conversely, for white-collar workers, mitigating job demands and managing emotional exhaustion are crucial for sustaining organizational commitment. This study contributes to the cross-cultural understanding of job demands and resources, highlighting their differential impact on blue- and white-collar workers in Türkiye.

ABSTRACT We examine whether executives are more likely to avoid reporting failures when turnover risk is higher. Consistent with accountability falling on executives with direct responsibility, we document the turnover rate for CAOs is highest after a restatement, followed by CFOs and CEOs. Further, we find higher turnover following a restatement for female executives when their workplace is more susceptible to gender biases. Next, we consider how higher turnover risk, due to the executive’s role and gender, influence reporting failures. We find a reduction in restatement likelihood associated with female CAOs in workplaces that are more susceptible to gender biases. Conversely, we find no evidence of an association between gender and restatements when the workplace is less susceptible to gender biases. Accordingly, our situation-based evidence suggests innate female risk aversion is not a complete explanation for reporting differences across gender. Data Availability: All data used in the study are publicly available. JEL Classifications: J01; J16; M12; M14; M41; O16.

High turnover intention among married female nurses at Fatmawati Hospital increases operational costs and risks compromising the quality of healthcare services. This study investigated the impact of work-family conflict (WFC) on turnover intention (TI), emphasizing the mediating role of psychological well-being (PWB). Using a mixed-methods approach, primary data were collected through structured questionnaires from married female nurses, while secondary data supported the theoretical framework. WFC was measured through two dimensions: work interference with family and family interference with work. PWB encompasses six dimensions, and TI was assessed based on six indicators related to job satisfaction and turnover intention. Data analysis using SPSS revealed that WFC negatively impacted PWB and positively impacted TI. In addition, higher psychological well-being reduced turnover intention and partially mediated the WFC–TI relationship. These findings highlight the importance of managing work-family conflict and improving nurses’ psychological well-being to reduce turnover risk. Limitations include a single hospital sample and cross-sectional design, and the need for larger longitudinal studies that can incorporate qualitative insights.

This study examines burnout reduction interventions for remote leaders, particularly in the context of COVID-19’s impact on work-life boundaries. Using a quasi-experimental design, online survey findings from remote employees were analyzed through the lens of Maslach Burnout Inventory (MBI) and Job Demands-Resource Theory (JD-R). Results indicate that Mindfulness Meditation and Strategic Subtraction are effective in reducing burnout. These findings offer practical insights for organizations seeking to improve employee well-being and mitigate turnover risks in remote work settings. Implications for leadership strategies and workplace policies are discussed to support sustainable remote work environments through practical interventions.

The article is devoted to analyzing the effectiveness of implementing CRM systems in the mass recruitment process and their impact on employee turnover. The focus is on the potential of digitalizing HR processes, optimizing recruitment stages, and reducing employer costs in the context of large-scale hiring. The study aims to identify key factors that contribute to lowering turnover rates and enhancing the efficiency of recruitment strategies through the integration of CRM solutions. The research employs a combination of quantitative and qualitative analysis, including surveys of HR specialists, recruiters, and HR managers, as well as semi-structured interviews with representatives of companies that have already implemented CRM in mass recruitment. The results of the analysis show a significant positive impact of CRM systems on recruiting. Using these systems reduces the time it takes to fill vacancies by 25–30%, improves the quality of communication with candidates, and increases staff retention by 10–14%. Case studies from companies such as IBM and Unilever show impressive results: IBM achieved a 45% reduction in turnover in critical positions and a 95% reduction in hiring time, while Unilever recorded a 16% reduction in turnover over three years. Digitalization facilitates deeper analysis of candidate behavior, personalized hiring strategies, and automation of onboarding processes, reducing early turnover by 30%. Integrating employee engagement analytics into CRM allows you to predict the risk of turnover with 78% accuracy and reduce turnover by 25–43%, saving up to $4,000 per hire. The findings emphasize that the implementation of CRM in mass recruiting is a strategic decision that not only optimizes costs but also increases process transparency, employer trust, and company competitiveness. It is recommended to integrate CRM with other HR systems, automate communications, and use analytical tools to create a sustainable system for attracting and retaining personnel in an unstable labor market.

The new phenomenon of quiet quitting where employees intentionally constrain their work effort to their contractual terms without overpromising has emerged as a critical challenge for modern human resource management. This review paper critically analyzes the conceptual underpinnings of employee engagement and disengagement and examines quiet quitting as a quiet resistance or strategic withdrawal in the post-pandemic workplace. Building on prevalent theories like the Job Demands-Resources model and psychological empowerment, the paper integrates empirical and theoretical research to determine antecedents, manifestations, and organizational outcomes of quiet quitting. The paper further describes how conventional HR practices need to transform to deal with the roots of disengagement, such as burnout, work-life conflict, and changing employee aspirations. Integrating findings from recent studies and case studies, this review provides actionable recommendations to HR practitioners to boost authentic engagement, promote well-being, and minimize turnover risks in an evolving work environment. This synthesis contributes timely and relevant knowledge to employee behavior dynamics understanding and responsive HR policy-making.