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http://dx.doi.org/10.5143/JESK.2018.37.3.387

Identification and Organization of Factors Influencing Team Decision Making by Analyzing Accidents in Complex Systems  

Jung, Won-Jun (Chonnam National University, Department of Industrial Engineering)
Ham, Dong-Han (Chonnam National University, Department of Industrial Engineering)
Publication Information
Journal of the Ergonomics Society of Korea / v.37, no.3, 2018 , pp. 387-401 More about this Journal
Abstract
Objective: The purpose of this study is to identify and organize factors that can be influential in the performance of team decision making (TDM) through analyzing previous accidents in complex systems. Background: In the operation of complex socio-technical systems, it is increasingly important to enhance the performance of teamwork, particularly TDM. For this it is necessary to identify a set of factors influencing TDM. However, there is still a lack of studies that investigate TDM impact factors and propose a way of organizing them meaningfully. Method: We examined 989 accidents in the three work domains (nuclear power plants, railway systems, and aviation industry). Of those, 258 accidents were considered as cases in which human errors were involved. Again, a more detailed analysis of them revealed 35 accidents to which TDM performance was critical. Based on the analysis of those 35 accidents, we identified 88 TDM impact factors and classified them into 13 groups. Results: Seventy-two factors influencing TDM were identified and categorized into 13 groups that are meaningful to more comprehensive study of TDM process. Conclusion: We derived 88 factors that could influence the performance of TDM through accident analysis in the three work domains and classified them into 13 groups as well. Application: The identified TDM impact factors can be a useful input data for assessing team reliability in complex systems and offer a theoretical basis for understanding TDM more comprehensively.
Keywords
Team decision making; Team performance; Teamwork; Performance shaping factors; Accident analysis;
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