Role of organizational factors affecting worker safety behavior: a Bayesian Belief Network Approach

被引:19
|
作者
Hadikusumo, Bonaventura H. W. [1 ]
Jitwasinkul, Bhanupong [1 ]
Memon, Abdul Qayoom [1 ]
机构
[1] Asian Inst Technol, Sch Engn & Technol, POB 4, Klongluang 12120, Pathumthani, Thailand
来源
3RD INTERNATIONAL CONFERENCE ON SUSTAINABLE CIVIL ENGINEERING STRUCTURES AND CONSTRUCTION MATERIALS - SUSTAINABLE STRUCTURES FOR FUTURE GENERATIONS | 2017年 / 171卷
关键词
Organizational factors; Worker behavior; Bayesian belief network; PLANNED BEHAVIOR; EMPOWERMENT; ATTITUDES; CULTURE; MODEL;
D O I
10.1016/j.proeng.2017.01.319
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Several investigations on major occupational accidents are demonstrating interest in role of organizational factors. Investigations and evidences manifest that "the root causes involved more than technical or human failures" [1]. Thus, focusing on organizational factors is an important issue in safety as a means of mitigating accident in the workplace. First step for assessing the influence of organizational factors is to identify the relevant organization factors. Out of 22 factors identified from literature review, seven important factors were finalized for Thailand construction industry: communication, culture, management commitment, leadership, organization learning, empowerment, and reward system. At final phase, Bayesian Belief Network was used for handling the complex causality and providing the strategies to enhance the safety work behaviors. According to first alternative, 73.3% of safety work behavior was reached by manipulating management commitment, participation, learning and leadership nodes simultaneously. The second alternative accomplished about 74.6% of safety work behavior when the leadership, management commitment, participation and intention node were assigned to favorable state. For the third alternative, 77.7% of safe work behavior could be obtained by controlling leadership, management commitment, participation and perceived behavioral control node. (C) 2017 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:131 / 139
页数:9
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