A Study of the Effects of Job Stress on the Psychosocial Safety Behavior of Construction Workers: The Mediating Role of Psychological Resilience

Engineers often play vital roles in technical planning, designing, and operating projects, as well as implementing standard requirements in the physical sites. Although architectural designs may be similar in a construction project, the technical problems, including soil conditions, loading calculations, team combination, etc., often vary between projects. Although previous studies focus on the stress management of construction professionals, little research has been particularly conducted for the effects of stressors and stress of engineers on their organizational commitment. It is inevitable for engineers to experience different uncertainties, harsh working environments, and serious legal liabilities, while there is often no tolerance when it comes to deadlines and safety requirements. All this definitely puts great pressure on them and may subsequently affect their commitment to their organizations. The present study aimed to investigate the impact of stressors and stress on the commitment of engineers in the construction industry. A total of 146 respondents participated in a questionnaire survey, and various statistical analyses including a reliability test, correlation, and hierarchical multiple regressions were adopted for developing the optimized commitment models. The research results revealed that (1) Type A personality was a key factor, which had a significant positive effect on all the three organizational commitments of professional engineers in the construction industry; (2) poor office environment, job overload, and role ambiguity were positively associated with continuance and normative commitment, whereas poor site environment and lack of job autonomy were negatively linked with affective commitment; and (3) stress had a negative relationship with affective commitment; (4) however, there was no relationship between stress and continuance or normative commitment. In order to establish holistic organizational commitment strategies in the industry well, the current study indicates key stressors to upper management to help them efficiently manage complicated project teams in construction projects. In addition, it contributes the body of knowledge by developing an integrated commitment model for engineers. Finally, numerous recommendations are made, such as encouraging Type A personality behaviors, providing sufficient job autonomy, improving worksite conditions to enhance the organizational commitment of engineers, and reducing the adverse impacts of these stressors and stress.

Section: Introductionmentioning

confidence: 99%

Impact of Stressors/Stress on Organizational Commitment of Engineers in the Construction Industry

Leung,

Ahmed,

Chan

2024

A Study on the Cascade Evolution Mechanism of Construction Workers’ Unsafe Behavior Risk Factors

Luo,

Tang,

Zhou

et al. 2024

There are numerous risk factors across various dimensions that lead to unsafe behaviors among construction workers, and the interactions between these factors are complex and intertwined. Therefore, it is crucial to comprehensively explore the mechanisms of these risk factors across all dimensions to reduce the accident rate. This paper combines cascading failure and entropy flow models to construct a cascading trigger model for identifying key nodes and paths in a risk network. First, this paper identifies the risk factors in the individual, organizational, managerial, and environmental dimensions, dividing them into deep and surface factors. Based on this, a risk network is constructed, and cascading failure is introduced to simulate the dynamic evolution of risks. Then, the entropy flow model is introduced to quantify the risk flow in risk propagation. Finally, to address the uncertainty of risk occurrence, Visual Studio Code is used for coding, and a simulation platform is built using JavaScript. After conducting simulation experiments, the results are statistically analyzed. The results show that the key nodes of deep factors are mainly concentrated in the individual dimension (herd mentality, negative emotions, physical fatigue, fluke mindset), organizational dimension (poor cohesion, poor internal communication), and managerial dimension (abusive leadership style and insufficient/low-quality safety education and training); the surface factors are mainly the poor safety climate in the organizational dimension. The findings provide theoretical support for reducing the accident rate caused by unsafe worker behaviors, aiming to reduce accident risk losses by cutting off risk propagation paths.

A Systematic Review of the Evolution of the Concept of Resilience in the Construction Industry

Li,

Yu,

Deng

2024

Despite the growing importance of resilience in the construction sector, the existing literature often focuses on specific systems or functions without integrating a holistic view of resilience. Hence, there is a pressing need for comprehensive research that synthesizes these dimensions to provide a clearer framework for resilience in the construction industry. To find the inherent patterns and trends of resilience, we carried out research from the perspective of three elements defining resilience (the subject of resilience, the influencing factors, and the subject’s ability). In this systematic review, 70 articles were rigorously handpicked from Web of Science, Scopus, and authoritative journals and divided into 6 major categories and 24 subcategories for quantitative and temporal analyses. The evolution of resilience in the construction industry is investigated in this review, shifting from specific systems facing defined impacts to addressing the complexities of diverse and unpredictable disruptions within VUCA (volatile, uncertain, complex, and ambiguous) environments. As Industry 4.0 and digital transformation progress, the significance of functional resilience across various system levels becomes apparent, necessitating a reconstitution into structural, operational, and supply chain resilience. This study encourages the use of advanced methodologies like big data, AI, and high-level architecture (HLA) federated simulations to predict disruptions and optimize resilience strategies, thus providing a robust foundation for handling future uncertainties.