Network analysis of well-being of managerial employees in the construction industry

被引:4
作者
Zhang, Yuanxin [1 ]
Li, Ying [1 ]
Xue, Xiaolong [1 ]
Dou, Yudan [2 ]
Zhang, Ruixue [3 ]
机构
[1] Guangzhou Univ, Sch Management, Guangzhou 510006, Peoples R China
[2] Dalian Univ Technol, Dept Construct Management, Dalian 116024, Peoples R China
[3] Liaoning Tech Univ, Sch Business Adm, Fuxin 12510, Peoples R China
基金
中国国家自然科学基金;
关键词
Subjective well-being; Network analysis; Factor network; LASSO; EBIC; WORK-FAMILY CONFLICT; JOB-SATISFACTION; WORKPLACE STRESS; MENTAL-HEALTH; PROFESSIONALS; MODEL; CENTRALITY; HAPPINESS; SAFETY; ENVIRONMENT;
D O I
10.1016/j.jobe.2023.108011
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The construction industry is notorious for the tremendous mental and physical stress employees bear, which is a significant contributor to talent shortages and brain drain. However, scholars mainly focus on the single sources of stress, anxiety, and depression for construction workers, lacking a systematic study of the subjective well-being of managerial employees. To address the academic shortfall, this study initially identified the influencing factors of employee well-being (EWB) in the construction industry, and defined them in seven aspects: occupational wellbeing, social well-being, income and welfare, health, safety and protection equipment, work environment, and the nature of work. Then, based on 511 sample data, the Gaussian graphical models, the Graphical Least Absolute Shrinkage and Selection Operator, and the Extended Bayesian Information Criteria methods were used to build a reliable network and to visualize the relationships between the factors. Finally, this study dissected the significant factors affecting EWB and their interrelationships based on network analysis. The study discovers that fair and adequate salary is the most crucial factor in terms of centrality, followed by sufficient salary for family and personal needs, as well as access to personal protective equipment. Job satisfaction and work-family balance sit at the center of the network, able to influence other factors most quickly. The contribution of this research is twofold: first, it deepens understanding of influencing factors to EWB through the introduction of a novel analytical technique-factor network analysis; and second, companies can then improve EWB, ultimately mitigating labor shortage and brain drain in the construction industry.
引用
收藏
页数:17
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