Interactions among Cognitive Factors Affecting Unsafe Behavior: Integrative Fuzzy DEMATEL ISM Approach

The prevention of industrial accidents is not completely practical by implementing safety programs unless focusing on protecting vulnerable workers. The unsafe behavior cognitive factors (UBCFs) are essential determinants contributing to human failure. This study aimed at eliciting the most important UBCFs, along with investigating hierarchical cause-effect interactions among them. A qualitative approach using metasynthesis was utilized to extract all essential UBCFs among industrial workplaces. Afterward, the relationships between UBCFs were recognized using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method and rated by an expert panel. Also, a hierarchical model was developed based on the final matrix of DEMATEL by employing the interpretive structural modeling (ISM) method. Ten criteria were extracted as UBCFs through the metasynthesis method. The threshold value was set as 0.175 in DEMATEL following experts’ ideas. Inadequacy of persons’ resilience and habitual rule ignorance were recognized as the most important predictive UBCFs. The developed model was tested through a case study in a petrochemical company. The results of the study can be used to help industrial managers and HSE practitioners to consider workers’ capabilities either cognitively or physically when designing the required tasks to reduce unsafe behaviors. Also, the findings of the study are applicable for other researchers to prioritize the most important factors affecting unsafe behavior in different workplaces.

[1]  Matthew R. Hallowell,et al.  Construction-Safety Best Practices and Relationships to Safety Performance , 2013 .

[2]  Antonio Padovano,et al.  Modeling workers’ behavior: A human factors taxonomy and a fuzzy analysis in the case of industrial accidents , 2019, International Journal of Industrial Ergonomics.

[3]  S. Downe,et al.  Meta-synthesis method for qualitative research: a literature review. , 2005, Journal of advanced nursing.

[4]  Bonaventura H.W. Hadikusumo,et al.  Structural equation model of integrated safety intervention practices affecting the safety behaviour of workers in the construction industry , 2017 .

[5]  Rakesh Kumar,et al.  An integrated framework of interpretive structural modeling and graph theory matrix approach to fix the agility index of an automobile manufacturing organization , 2017, Int. J. Syst. Assur. Eng. Manag..

[6]  Qinggui Cao,et al.  Research on the influencing factors in coal mine production safety based on the combination of DEMATEL and ISM , 2018 .

[7]  Erik Hollnagel,et al.  The Phenotype of Erroneous Actions , 1993, Int. J. Man Mach. Stud..

[8]  Frank A. Felder,et al.  Analysis of barriers to development in landfill communities using interpretive structural modeling , 2011 .

[9]  Ronald Iammartino,et al.  Evaluation of preconditions affecting symptomatic human error in general aviation and air carrier aviation accidents , 2018, Reliab. Eng. Syst. Saf..

[10]  Mehdi Jahangiri,et al.  A Novel Fuzzy Bayesian Network-HFACS (FBN-HFACS) model for analyzing Human and Organization Factors (HOFs) in process accidents , 2019 .

[11]  Mehdi Shamizanjani,et al.  Meta-synthesis of big data impacts on information systems development , 2017 .

[12]  Marko Čepin.  Importance of human contribution within the human reliability analysis (IJS-HRA) , 2008 .

[13]  Faisal Khan,et al.  A hybrid model for human factor analysis in process accidents: FBN-HFACS , 2019, Journal of Loss Prevention in the Process Industries.

[14]  Michael Rutter,et al.  Resilience as a dynamic concept , 2012, Development and Psychopathology.

[15]  Min-chih Hsieh,et al.  Application of HFACS, fuzzy TOPSIS, and AHP for identifying important human error factors in emergency departments in Taiwan , 2018, International Journal of Industrial Ergonomics.

[16]  Abdul Hameed,et al.  A risk-based shutdown inspection and maintenance interval estimation considering human error , 2016 .

[17]  Javad Jassbi,et al.  A Fuzzy DEMATEL framework for modeling cause and effect relationships of strategy map , 2011, Expert Syst. Appl..

[18]  John F. Murphy,et al.  Black swans, white swans, and 50 shades of grey: Remembering the lessons learned from catastrophic process safety incidents , 2014 .

[19]  Carlo Andolfo,et al.  A Probabilistic Accident Prediction Model for Construction Sites , 2015 .

[20]  Lia Buarque de Macedo Guimarães,et al.  An algorithm for classifying error types of front-line workers based on the SRK framework , 2008 .

[21]  Nancy G. Leveson,et al.  Applying systems thinking to analyze and learn from events , 2010 .

[22]  E. Fontela,et al.  Using interpretive structural modelling in strategic decision‐making groups , 2005 .

[23]  R. Kant,et al.  Knowledge management barriers: An interpretive structural modeling approach , 2007, 2007 IEEE International Conference on Industrial Engineering and Engineering Management.

[24]  Waldemar Karwowski,et al.  The effect of cognitive demands and perceived quality of work life on human performance in manufacturing environments. , 2009 .

[25]  Vikram Garaniya,et al.  An integrated method for human error probability assessment during the maintenance of offshore facilities , 2015 .

[26]  Michel Godet,et al.  Introduction to la prospective: Seven key ideas and one scenario method☆ , 1986 .

[27]  Lela V. Zimmer,et al.  Qualitative meta-synthesis: a question of dialoguing with texts. , 2006, Journal of advanced nursing.

[28]  Kathryn Mearns,et al.  Stress, Fatigue, Situation Awareness and Safety in Offshore Drilling Crews , 2013 .

[29]  Tamera L. McKinniss,et al.  The moderation of conscientiousness by cognitive ability when predicting workplace safety behavior , 2009 .

[30]  Kehinde Adewale Adesina,et al.  Learning from Fire Accident at Bouali Sina Petrochemical Complex Plant , 2019, Journal of Failure Analysis and Prevention.

[31]  Patrick X.W. Zou,et al.  Skills for managing safety risk, implementing safety task, and developing positive safety climate in construction project , 2013 .

[32]  Mohit Kumar,et al.  A Novel Weakest t-Norm based Fuzzy Importance Measure for Fuzzy Fault Tree Analysis of Combustion Engineering Reactor Protection System , 2019, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[33]  Hasse Nordlöf,et al.  Safety culture and reasons for risk-taking at a large steel-manufacturing company : Investigating the worker perspective , 2015 .

[34]  Z. Rahman,et al.  Brand Experience Anatomy in Hotels: An Interpretive Structural Modeling Approach , 2017 .

[35]  Valerie F Reyna,et al.  Explaining Contradictory Relations Between Risk Perception and Risk Taking , 2008, Psychological science.

[36]  Lee T. Ostrom,et al.  Occupational Ergonomics: Practical Approach, A , 2016 .

[37]  Michelle Ann Toppazzini,et al.  Making workplaces safer: The influence of organisational climate and individual differences on safety behaviour , 2017, Heliyon.

[38]  G. Dixit,et al.  An analysis of barriers affecting the implementation of e-waste management practices in India: A novel ISM-DEMATEL approach , 2018 .

[39]  Patrick L. Yorio,et al.  The role of risk avoidance and locus of control in workers' near miss experiences: Implications for improving safety management systems. , 2019, Journal of loss prevention in the process industries.

[40]  Matthew L. Bolton,et al.  Properties for formally assessing the performance level of human-human collaborative procedures with miscommunications and erroneous human behavior ☆ , 2016 .

[41]  Stephen C. Theophilus,et al.  Human factors analysis and classification system for the oil and gas industry (HFACS-OGI) , 2017, Reliab. Eng. Syst. Saf..

[42]  Mica R. Endsley,et al.  Measurement of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[43]  M Sandelowski,et al.  Qualitative Metasynthesis : Issues and Techniques , 1997 .

[44]  Hedieh Shakeri,et al.  Analysis of factors affecting project communications with a hybrid DEMATEL-ISM approach (A case study in Iran) , 2020, Heliyon.

[45]  Pasupulati Venkata Chalapathi,et al.  Factors Influencing Implementation of OHSAS 18001 in Indian Construction Organizations: Interpretive Structural Modeling Approach , 2015, Safety and health at work.

[46]  J. Reason.  Human error: models and management , 2000, BMJ : British Medical Journal.

[47]  Minjun Peng,et al.  The digital simulation and fuzzy evaluation to reduce the likelihood of unsafe behavior in nuclear decommissioning , 2018, Annals of Nuclear Energy.

[48]  Rakesh D. Raut,et al.  To identify the critical success factors of sustainable supply chain management practices in the context of oil and gas industries: ISM approach , 2017 .

[49]  A. Choobineh,et al.  Individual cognitive factors affecting unsafe acts among Iranian industrial workers: An integrative meta-synthesis interpretive structural modeling (ISM) approach , 2019 .

[50]  Mohit Kumar,et al.  A Novel Weakest t-norm based Fuzzy Fault Tree Analysis Through Qualitative Data Processing and Its Application in System Reliability Evaluation , 2018, J. Intell. Syst..