Work design, employee well-being, and retention intention: A case study of China's young workforce

China's growing workforce of young employees has propelled its economy towards becoming a global power. However, with evolving workplace difficulties and uncertainties, the rate of employee turnover is also rising, which affects every department in companies, in addition to impacting costs and finances. This study explored the influences of five core job characteristics, work relationships, and work conditions on young Chinese employees' retention intentions, mediated by employee well-being. Using a quantitative cross-sectional approach, 804 responses were obtained from young Chinese workers. We also employed partial least squares structural equation modeling to analyze and forecast the extent of the impact of this study's independent variables. The empirical findings revealed that job autonomy, skill variety, task significance, feedback, work relationships, and work conditions indirectly influenced the retention intentions of young workers in China, with employee well-being acting as a mediator. However, the impact of task identity on employee well-being and retention intentions was insignificant. Our study contributes to the literature on employee retention intentions by demonstrating the importance of young employees' perceptions of work design-related aspects and extending the application of the job characteristics model.

A diary study on the moderating role of leader-member exchange on the relationship between job characteristics, job satisfaction, and emotional exhaustion

Job characteristics play an essential role for the well-being of employees. When job characteristics are unfavorable, the experienced exchange relationship with one’s supervisor (i.e., leader-member exchange, LMX) may become relevant to weaken negative consequences. We conducted a diary study over ten consecutive working days with 112 academics. Based on conservation of resources theory, we assumed that daily LMX constitutes a resource for employees that moderates the link between job characteristics (job control and time pressure) and job satisfaction as well as emotional exhaustion. Additionally, we proposed lagged-effects of morning job characteristics and LMX on next-day morning job satisfaction and emotional exhaustion. Findings from hierarchical linear modeling (HLM) demonstrated that on the day-level higher perceived levels of job control in the morning were associated with higher perceived job satisfaction and lower perceived emotional exhaustion in the afternoon. The experience of increased time pressure in the morning was negatively related to perceived day-level afternoon job satisfaction and positively to perceived day-level afternoon emotional exhaustion. Within one day, perceived LMX moderated the relationship between perceived job control and perceived job satisfaction in the afternoon. We only found lagged effects of the interaction between afternoon job control and afternoon LMX on next-day morning job satisfaction. We discuss daily LMX as a resource for employees both within one day and from day-to day, along with future research directions on the buffering role of LMX.

Enhancing operations management through smart sensors: measuring and improving well-being, interaction and performance of logistics workers

Purpose

The purpose of the research is to conduct an exploratory investigation of the material handling activities of an Italian logistics hub. Wearable sensors and other smart tools were used for collecting human and environmental features during working activities. These factors were correlated with workers' performance and well-being.

Design/methodology/approach

Human and environmental factors play an important role in operations management activities since they significantly influence employees' performance, well-being and safety. Surprisingly, empirical studies about the impact of such aspects on logistics operations are still very limited. Trying to fill this gap, the research empirically explores human and environmental factors affecting the performance of logistics workers exploiting smart tools.

Findings

Results suggest that human attitudes, interactions, emotions and environmental conditions remarkably influence workers' performance and well-being, however, showing different relationships depending on individual characteristics of each worker.

Practical implications

The authors' research opens up new avenues for profiling employees and adopting an individualized human resource management, providing managers with an operational system capable to potentially check and improve workers' well-being and performance.

Originality/value

The originality of the study comes from the in-depth exploration of human and environmental factors using body-worn sensors during work activities, by recording individual, collaborative and environmental data in real-time. To the best of the authors' knowledge, the current paper is the first time that such a detailed analysis has been carried out in real-world logistics operations.

Shared Leadership, Unshared Burdens: How Shared Leadership Structure Schema Lowers Individual Enjoyment Without Increasing Performance

Despite the growing popularity of shared leadership, there is little research on how beliefs about the benefits of shared leadership—a shared leadership structure schema (LSS)—affect individual outcomes. We address this by integrating adaptive leadership and conservation of resources theories. We apply adaptive leadership theory to hypothesize that a shared LSS leads individuals to support shared leadership by interacting more frequently and taking on interpersonal responsibility, especially when low peer engagement signals a leadership void that shared LSS members try to fill. However, adaptive leadership theory does not discuss how the tendencies motivated by shared LSS impacts members’ outcome. Therefore, we apply conservation of resources theory to hypothesize that taking on interpersonal responsibility makes frequent interactions more stressful, thereby harming individual enjoyment. Further, the demands of interpersonal responsibility reduce members’ ability to process the information acquired in interactions, which negates interaction frequency’s usual performance benefits. Together, these theories suggest that, especially when peer engagement is low, shared LSS has a negative indirect effect on enjoyment and an attenuating effect on performance through interaction frequency due to shared LSS members taking on interpersonal responsibility. We test our model using five waves of multisource data on student consulting teams. Our results extend understanding of shared LSS’s consequences to the individual level and highlight potential costs of supporting shared leadership.