2024-03-28T14:41:32Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1092912022-02-08T07:16:59Zcom_10261_37com_10261_4col_10261_290
2015-01-13T09:23:39Z
urn:hdl:10261/109291
Bayesian network analysis of safety culture and organizational culture in a nuclear power plant
García-Herrero, Susana
Mariscal Saldaña, Miguel Ángel
Gutiérrez, José M.
Toca-Otero, Antonio
Bayesian networks
Organizational culture inventory
Nuclear industry
Organizational culture
Safety culture
Many high-hazard industries around the world have explicitly recognized the critical role that human, management and organizational risk factors play in major accidents. The findings of accident investigations and risk assessments demonstrate a growing recognition that the cultural context of work practices may influence safety just as much as technology.The objective of this paper is to establish a relationship between the concepts of safety culture and organizational culture in a Nuclear Power Plant (NPP). This study permits the identification and quantification of the possible mechanisms for improving the safety culture in the NPP acting on organizational culture. It therefore provides a methodology to identify potential strategies for safety improvement.Probabilistic (Bayesian) Networks (BNs) have been used to determine the relationships between the organizational culture and safety culture in a quantitative form. To this aim, we considered data from a survey conducted of every employee at a Spanish NPP. The resulting data-driven models allow us to establish the probabilistic relationship among organizational culture factors, including the 12 OCI (Organizational Culture Inventory) scales, that have an influence on safety culture. The study yielded a ranking of organizational cultures that can be used to improve safety culture in a NPP. © 2012 Elsevier Ltd.
2015-01-13T09:23:39Z
2015-01-13T09:23:39Z
2013
2015-01-13T09:23:39Z
artículo
Safety Science 53: 82-95 (2013)
http://hdl.handle.net/10261/109291
10.1016/j.ssci.2012.09.004
eng
closedAccess
Elsevier