Key drivers of trucking safety climate from the perspective of leader-member exchange: Bayesian network predictive modeling approach

Yueng hsiang Huang, Yimin He, Jin Lee, Changya Hu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Purpose: Safety climate, which is defined as workers’ shared perceptions of organizational policies, procedures, and practices as they relate to the true or relative value and importance of safety within an organization, is one of the best indicators of organizational safety outcomes. This study identifies key drivers of safety climate from the perspective of leader-member exchange (LMX). LMX is a theory describing the nature and processes of social interactions between a supervisor and a subordinate. This study examines the impact of individual drivers and combinations of drivers on safety climate through Bayesian Network simulations to predict practices which most effectively improve safety climate in the trucking industry. Method: Survey data were collected from 5083 truck drivers in a large U.S. trucking company. Bayesian Network analysis was used to identify key drivers (factors) of safety climate and the best joint strategies for improvement. The impact of the drivers on safety climate was assessed and the simulation identified their potential impact independently and in concert with other drivers. Results: The results from Bayesian Network analyses showed that the effects of LMX on organization- and group-level safety climate were conditionally dependent on four other drivers including psychological ownership, supervisory integrity, situation awareness, and safety communication. Among the five contributing factors, supervisory integrity and LMX had the strongest independent effects on organization- and group-level safety climate. Moreover, the results indicated that the best two joint strategies for promoting organizational (company/top management level) safety climate were LMX and psychological ownership as well as LMX and situation awareness, whereas the best two joint strategies for improving group (workgroup/supervisor level) safety climate were joint optimization of LMX and safety communication as well as LMX and psychological ownership. Implications: Based on the study results, the strategies that may have the most potential to improve trucking safety climate are: enhancing leaders' ability to engage in high-quality exchanges (e.g., caring about employees), developing training to encourage employees/leaders to deliver on promises, and providing employees with more autonomy to enhance their ownership.

Original languageEnglish (US)
Article number105850
JournalAccident Analysis and Prevention
Volume150
DOIs
StatePublished - Feb 2021

Keywords

  • Bayesian network analysis
  • Leader-member exchange
  • Safety climate

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health

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