A dynamic risk assessment modeling based on fuzzy ANP for safety management systems
Abstract
Risk assessment in large organizations with extensive operational domains has been a challenging issue. Employing an efficient method along with realistic pair comparisons, applying subjective inferences of organization experts, and purging the intrinsic ambiguity of inferences, are not reflected in current airlines' safety management. Traditional two-dimensional risk assessment for risk management of safety hazards, however, is no longer sufficient to comply with this complexity. A new model for risk management and a novel formula for risk index calculation, based on a fuzzy approach, are presented in this study. In this new model, unlike in the traditional approach, the latent aftermath of safety reports, especially those which affect the continuity of the business, is also taken into account. In this model, along with the definition of a new structure for risk management, risk analysis should be restructured. To that end, a two-dimensional classic risk formula was replaced with three-dimensional (nonlinear) exponential ones, considering “the impact on the business” as a source of risk and hazard. For measuring the safety risk using the Fuzzy hierarchical evaluation method, considering experts' opinions, three criteria in four different operational fields were developed. This method employs a Fuzzy ANP to help quantify judgments, make qualitative judgments in the traditional method, and weigh the priority of elements contributing to risk. Also, it provides a tool for top-level as well as expert level management to monitor safety more precisely, monitor the safety level within their departments or organizations, set quantitative safety goals and provide feedback for improvement as well as find the most critical areas with the least cost. In this study, an airline has been selected as a case study for the risk assessment of reports based on the new model.
Keyword : fuzzy, ANP, safety risk assessment, impact on business, aviation
How to Cite
Rezaei, M., & Borjalilu, N. (2018). A dynamic risk assessment modeling based on fuzzy ANP for safety management systems. Aviation, 22(4), 143-155. https://doi.org/10.3846/aviation.2018.6983
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Acur, N., & Englyst, L. (2006). Assessment of strategy formulation: how to ensure quality in process and outcome. Operation and Production Management, 26(1), 69-91. https://doi.org/10.1108/01443570610637021
Adams, E. (1976). Accident causation and the management systems. Professional Safety Journal, 21
(10), 26-29.
Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their fundation. European Journal of Operational Research, 235(1), 1-13. https://doi.org/10.1016/j.ejor.2015.12.023
Bird, F. E., & Loftus, R. G. (1976). Loss control management. Loganville, Ga: Institute Press.
Cacciabue, P. C., Cassani, M., Licata, V., Oddone, I., & Ottomaniello, A. (2015). A practical approach to assess risk in aviation domains for safety management systems. Journal of Cognition, Technology & Work, 17(2), 249-267. https://doi.org/10.1007/s10111-014-0294-y
Dargi, A., Anjomshoae, A., Galankashi, M. R., Memari, A., & Tap, M. B. M. (2014). Supplier selection: A fuzzy-ANP approach. Procedia Computer Science, 31, 691-700. https://doi.org/10.1016/j.procs.2014.05.317
Deng, F., Wang, C., & Liang, X. (2017). Fuzzy Comprehensive Evaluation Model for Flight Safety Evaluation Research Based on an Empowerment Combination. In Proceedings of the Tenth International Conference on Management Science and Engineering Management (pp. 1479-1491). Singapore: Springer. https://doi.org/10.1007/978-981-10-1837-4_120
Di Bona, G., Silvestri, A., & De Felice, F. (2016). An analytical model to measure the effectiveness of safety management systems: Global Safety Improve Risk Assessment (G-SIRA) method.
Journal of Failure Analysis and Prevention, 16(6), 1024-1037. https://doi.org/10.1007/s11668-016-0185-z
Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2017). A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria. Journal of Air Transport Management, 63, 45-60. https://doi.org/10.1016/j.jairtraman.2017.05.008
Griffin, T. G. C. (2010). The flight of information: New approaches for investigating aviation accident causation (PhD Thesis). School of Engineering and Design, Brunel University.
Hollnagel, E., Woods, D. D., & Leveson, N. (2007). Resilience engineering: Concepts and precepts. Aldershot, UK: Ashgate Publishing, Ltd.
International Air Transport Association.Acur, N., & Englyst, L. (2006). Assessment of strategy formulation: how to ensure quality in process and outcome. Operation and Production Management, 26(1), 69-91. https://doi.org/10.1108/01443570610637021
Adams, E. (1976). Accident causation and the management systems. Professional Safety Journal, 21(10), 26-29.
Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their fundation. European Journal of Operational Research, 235(1), 1-13. https://doi.org/10.1016/j.ejor.2015.12.023
Bird, F. E., & Loftus, R. G. (1976) Loss control management. Loganville, Ga: Institute Press.
Cacciabue, P. C., Cassani, M., Licata, V., Oddone, I., & Ottomaniello, A. (2015). A practical approach to assess risk in aviation domains for safety anagement systems. Journal of Cognition, Technology & Work, 17(2), 249-267. https://doi.org/10.1007/s10111-014-0294-y
Dargi, A., Anjomshoae, A., Galankashi, M. R., Memari, A., & Tap, M. B. M. (2014). Supplier selection: A fuzzy-ANP approach. Procedia Computer Science, 31, 691-700. https://doi.org/10.1016/j.procs.2014.05.317
Deng, F., Wang, C., & Liang, X. (2017). Fuzzy Comprehensive Evaluation Model for Flight Safety Evaluation Research Based on an Empowerment Combination. In Proceedings of the Tenth International Conference on Management Science and Engineering Management (pp. 1479-1491). Singapore: Springer. https://doi.org/10.1007/978-981-10-1837-4_120
Di Bona, G., Silvestri, A., & De Felice, F. (2016). An analytical model to measure the effectiveness of safety management systems: Global Safety Improve Risk Assessment (G-SIRA)
method. Journal of Failure Analysis and Prevention, 16(6), 1024-1037. https://doi.org/10.1007/s11668-016-0185-z
Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2017). A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria. Journal of Air Transport Management, 63, 45-60. https://doi.org/10.1016/j.jairtraman.2017.05.008
Griffin, T. G. C. (2010). The flight of information: New approaches for investigating aviation accident causation (PhD Thesis). School of Engineering and Design, Brunel University.
Hollnagel, E., Woods, D. D., & Leveson, N. (2007). Resilience engineering: Concepts and precepts. Aldershot, UK: Ashgate Publishing, Ltd.
International Air Transport Association. (2017). Safety report 2016 (53rd ed.). [Electtronic Version]. Retrieved from www.iata.org
International Civil Aviation Organization. (2013a). Safety Management Manual (SMM) (Doc 9859 AN/474). Retrieved from https://www.icao.int/safety/SafetyManagement/Documents/Doc.9859.3rd%20Edition.alltext.en.pdf
International Civil Aviation Organization. (2013b). Safety Management, Annex 19 to the Convention on International Civil Aviation. Montreal: ICAO.Janic, M. (2000). An assessment of risk and safety in civil aviation. Journal of Air Transport Management, 6(1), 43-50. https://doi.org/10.1016/S0969-6997(99)00021-6
Johnson, W. G. (1975). MORT: The management oversight and risk tree. Journal of Safety Research, 7(1), 4-15.
Kontogiannis, T., Malakis, S., & McDonald, N. (2017). Integrating operational and risk information with system risk models in air traffic control. Cognition, Technology & Work, 19(2-3), 345-361. https://doi.org/10.1007/s10111-017-0409-3
Leveson, N. (2005). Risk analysis of NASA independent technical authority. Cambridge, MA: MIT press.
Leveson, N. (2011). Engineering a safer world. In Aeronautics and astronautics. Cambridge, MA, SAD: MIT press.
Lin, R. H. (2009). An integrated FANP–MOLP for supplier evaluation and order allocation. Applied Mathematical Modelling, 33(6), 2730-2736. https://doi.org/10.1016/j.apm.2008.08.021
Lind,S., Nenonen,S., & Kivistö-Rahnasto, J. (2008). Safety risk assessment in industrial, maintenance. Journal of Quality in Maintenance Engineering, 14(2), 205-217. https://doi.org/10.1108/13552510810877692
Maseleno, A., Hasan, M. M., Tuah, N., & Tabbu, C. R. (2015). Fuzzy logic and mathematical theory of evidence to detect the risk of disease spreading of Highly Pathogenic Avian Influenza H5N1. Procedia Computer Science, 57, 348-357. https://doi.org/10.1016/j.procs.2015.07.349
Netjasov, F., & Janić, M. (2008, June 1-4). A review of the research on risk and safety modelling in civil aviation. In Third International Conference on Research in Air Transportation, Fairfax, Virginia, USA (pp. 169-176). Retrieved from http://www.icrat.org/icrat/3rd-international-conference/icrat2008_proceedingscomplete.pdf
Noriyati, R. D., Rozaaq, W., Musyafa, A., & Soepriyanto, A. (2015). Hazard & operability study and determining safety integrity level on sulfur furnace unit: A case study in fertilizer industry. Procedia Manufacturing, 4, 231-236. https://doi.org/10.1016/j.promfg.2015.11.036
Oldhama, K., Stantonb, J., Bilderbecka, M., & Spinettoa, J. (2017). Case study of a voluntary aviation safety and environmental accreditation programme. Safety Science, 96, 41-51. https://doi.org/10.1016/j.ssci.2017.02.015
Panagopoulos, I., Atkin, C. J., & Sikora, I. (2017). Developing a performance indicators lean-sigma framework for measuring aviation system’s safety performance. Transportation Research Procedia, 22, 35-44. https://doi.org/10.1016/j.trpro.2017.03.005
Perrow, C. (1999). Normal accidents: living with high-risk technologies. New Jersey: Princeton University Press.
Pillay, M. (2015). Accident causation, prevention and safety management: a review of the state-of-the-art. Procedia Manufacturing, 3, 1838-1845. https://doi.org/10.1016/j.promfg.2015.07.224
Ramkumar, M. (2016). A modified ANP and fuzzy inference system based approach for risk assessment of in-house and third party e-procurement systems. Strategic Outsourcing: An International Journal, 9(2), 159-188. https://doi.org/10.1108/SO-12-2015-0030
Ramkumar, M., Schoenherr, T., & Jenamani, M. (2016). Risk assessment of outsourcing e-procurement services: integrating SWOT analysis with a modified ANP-based fuzzy inference system. Production Planning & Control, 27(14), 1171-1190. https://doi.org/10.1080/09537287.2016.1190877
Rasmussen, J. (1997). Risk management in a dynamic society: a modelling problem. Safety Science, 27(2-3), 183-213. https://doi.org/10.1016/S0925-7535(97)00052-0
Reason, J. (1998). Managing the risk of organizational accidents. Burlington, USA: Ashgate Publishing Company. Sikora, I. (2015). Risk assessment, modelling and proactive safety management system in aviation: a literature review. In Proceedings of Conference on Transportation Systems with International Participation. Retreived from http://openaccess.city.ac.uk/16320/1/Sikora_KoREMA_2015_v_2_0.pdf
Stanton, N. A. (2008). Modelling command and control. London: Taylor & Francis Group.
Stoop, J., & Dekker, S. (2010). Limitations of ‘Swiss Cheese’ models and the need for a systems approach. In Proceedings of the 41 st Annual International Seminar “Investigating ASIA in
Mind–Accurate, Speedy, Independent and Authentic” (pp. 52-59). Retreived from https://www.isasi.org/Documents/library/Seminar-Proceedings/Proceedings-2010.pdf
Tsay, C. Y. J., Kuo, C. C., Chao, C. J., Drury, C. G., & Hsiao, Y. L. (2014, June). Safety culture evaluation in China Airlines: a preliminary study. In International Conference on Engineering
Psychology and Cognitive Ergonomics (pp. 387-397). Cham: Springer. https://doi.org/10.1007/978-3-319-07515-0_39
Tuzkaya, U. R., & Önüt, S. (2008). A fuzzy analytic network process based approach to transportation-mode selection between Turkey and Germany: A case study. Information Sciences, 178(15), 3133-3146. https://doi.org/10.1016/j.ins.2008.03.015
Wang, L., & Sun, R. (2012). The development of a new safety culture evaluation index system. Procedia Engineering, 43, 331-337. https://doi.org/10.1016/j.proeng.2012.08.057
Weaver, D. (1971). Symptoms of operational error. Professional Safety Journal, 104
(2), 39-42.
Wichapa, N., & Khokhajaikiat, P. (2017). Solving multi-objective facility location problem using the fuzzy analytical hierarchy process and goal programming: a case study on infectious waste disposal centers. Operations Research Perspectives, 4, 39-48. https://doi.org/10.1016/j.orp.2017.03.002
Wise, B. (2016). Safety risk management principles from the Federal Aviation Administration. In Resident’s Handbook of Medical Quality and Safety (pp. 17-20). Cham: Springer. https://doi.org/10.1007/978-3-319-24190-6_3
Xianfeng, L., & Shengguo, H. (2012). Airport safety risk evaluation based on modification of quantitative safety management model. Procedia Engineering, 43, 238-244. https://doi.org/10.1016/j.proeng.2012.08.041
Xueyan, S., Mingliang, Q., & Mingang, G. (2012). Safety risk analysis in flight operations quality assurance. Systems Engineering Procedia, 5, 81-86. https://doi.org/10.1016/j.sepro.2012.04.013
Yüksel, İ., & Dağdeviren, M. (2010). Using the fuzzy analytic network process (ANP) for Balanced Scorecard (BSC): A case study for a manufacturing firm. Expert Systems with Applications, 37(2), 1270-1278. https://doi.org/10.1016/j.eswa.2009.06.002
Zadeh, L. A. (1965). Information and control. Fuzzy Sets, 8(3), 338-353.
Zhao, X., Hwang, B. G., & Gao, Y. (2016). A fuzzy synthetic evaluation approach for risk assessment: a case of Singapore’s green projects. Journal of Cleaner Production, 115, 203-213. https://doi.org/10.1016/j.jclepro.2015.11.042
Zhao, Z., Liu, L., & Liu, F. (2008, October). Airport internal safety risk assessment using fuzzy hierarchy process approach. In International Symposium on Computational Intelligence and Design, 2008. ISCID’08. (Vol. 1, pp. 170-173). IEEE. https://doi.org/10.1109/ISCID.2008.144
Zhou, C., & Hu, D. (2012). Research on inducement to accident/incident of civil aviation in southwest of china based on grey incidence analysis. Procedia Engineering, 45, 942-949. https://doi.org/10.1016/j.proeng.2012.08.263
Adams, E. (1976). Accident causation and the management systems. Professional Safety Journal, 21
(10), 26-29.
Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their fundation. European Journal of Operational Research, 235(1), 1-13. https://doi.org/10.1016/j.ejor.2015.12.023
Bird, F. E., & Loftus, R. G. (1976). Loss control management. Loganville, Ga: Institute Press.
Cacciabue, P. C., Cassani, M., Licata, V., Oddone, I., & Ottomaniello, A. (2015). A practical approach to assess risk in aviation domains for safety management systems. Journal of Cognition, Technology & Work, 17(2), 249-267. https://doi.org/10.1007/s10111-014-0294-y
Dargi, A., Anjomshoae, A., Galankashi, M. R., Memari, A., & Tap, M. B. M. (2014). Supplier selection: A fuzzy-ANP approach. Procedia Computer Science, 31, 691-700. https://doi.org/10.1016/j.procs.2014.05.317
Deng, F., Wang, C., & Liang, X. (2017). Fuzzy Comprehensive Evaluation Model for Flight Safety Evaluation Research Based on an Empowerment Combination. In Proceedings of the Tenth International Conference on Management Science and Engineering Management (pp. 1479-1491). Singapore: Springer. https://doi.org/10.1007/978-981-10-1837-4_120
Di Bona, G., Silvestri, A., & De Felice, F. (2016). An analytical model to measure the effectiveness of safety management systems: Global Safety Improve Risk Assessment (G-SIRA) method.
Journal of Failure Analysis and Prevention, 16(6), 1024-1037. https://doi.org/10.1007/s11668-016-0185-z
Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2017). A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria. Journal of Air Transport Management, 63, 45-60. https://doi.org/10.1016/j.jairtraman.2017.05.008
Griffin, T. G. C. (2010). The flight of information: New approaches for investigating aviation accident causation (PhD Thesis). School of Engineering and Design, Brunel University.
Hollnagel, E., Woods, D. D., & Leveson, N. (2007). Resilience engineering: Concepts and precepts. Aldershot, UK: Ashgate Publishing, Ltd.
International Air Transport Association.Acur, N., & Englyst, L. (2006). Assessment of strategy formulation: how to ensure quality in process and outcome. Operation and Production Management, 26(1), 69-91. https://doi.org/10.1108/01443570610637021
Adams, E. (1976). Accident causation and the management systems. Professional Safety Journal, 21(10), 26-29.
Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their fundation. European Journal of Operational Research, 235(1), 1-13. https://doi.org/10.1016/j.ejor.2015.12.023
Bird, F. E., & Loftus, R. G. (1976) Loss control management. Loganville, Ga: Institute Press.
Cacciabue, P. C., Cassani, M., Licata, V., Oddone, I., & Ottomaniello, A. (2015). A practical approach to assess risk in aviation domains for safety anagement systems. Journal of Cognition, Technology & Work, 17(2), 249-267. https://doi.org/10.1007/s10111-014-0294-y
Dargi, A., Anjomshoae, A., Galankashi, M. R., Memari, A., & Tap, M. B. M. (2014). Supplier selection: A fuzzy-ANP approach. Procedia Computer Science, 31, 691-700. https://doi.org/10.1016/j.procs.2014.05.317
Deng, F., Wang, C., & Liang, X. (2017). Fuzzy Comprehensive Evaluation Model for Flight Safety Evaluation Research Based on an Empowerment Combination. In Proceedings of the Tenth International Conference on Management Science and Engineering Management (pp. 1479-1491). Singapore: Springer. https://doi.org/10.1007/978-981-10-1837-4_120
Di Bona, G., Silvestri, A., & De Felice, F. (2016). An analytical model to measure the effectiveness of safety management systems: Global Safety Improve Risk Assessment (G-SIRA)
method. Journal of Failure Analysis and Prevention, 16(6), 1024-1037. https://doi.org/10.1007/s11668-016-0185-z
Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2017). A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria. Journal of Air Transport Management, 63, 45-60. https://doi.org/10.1016/j.jairtraman.2017.05.008
Griffin, T. G. C. (2010). The flight of information: New approaches for investigating aviation accident causation (PhD Thesis). School of Engineering and Design, Brunel University.
Hollnagel, E., Woods, D. D., & Leveson, N. (2007). Resilience engineering: Concepts and precepts. Aldershot, UK: Ashgate Publishing, Ltd.
International Air Transport Association. (2017). Safety report 2016 (53rd ed.). [Electtronic Version]. Retrieved from www.iata.org
International Civil Aviation Organization. (2013a). Safety Management Manual (SMM) (Doc 9859 AN/474). Retrieved from https://www.icao.int/safety/SafetyManagement/Documents/Doc.9859.3rd%20Edition.alltext.en.pdf
International Civil Aviation Organization. (2013b). Safety Management, Annex 19 to the Convention on International Civil Aviation. Montreal: ICAO.Janic, M. (2000). An assessment of risk and safety in civil aviation. Journal of Air Transport Management, 6(1), 43-50. https://doi.org/10.1016/S0969-6997(99)00021-6
Johnson, W. G. (1975). MORT: The management oversight and risk tree. Journal of Safety Research, 7(1), 4-15.
Kontogiannis, T., Malakis, S., & McDonald, N. (2017). Integrating operational and risk information with system risk models in air traffic control. Cognition, Technology & Work, 19(2-3), 345-361. https://doi.org/10.1007/s10111-017-0409-3
Leveson, N. (2005). Risk analysis of NASA independent technical authority. Cambridge, MA: MIT press.
Leveson, N. (2011). Engineering a safer world. In Aeronautics and astronautics. Cambridge, MA, SAD: MIT press.
Lin, R. H. (2009). An integrated FANP–MOLP for supplier evaluation and order allocation. Applied Mathematical Modelling, 33(6), 2730-2736. https://doi.org/10.1016/j.apm.2008.08.021
Lind,S., Nenonen,S., & Kivistö-Rahnasto, J. (2008). Safety risk assessment in industrial, maintenance. Journal of Quality in Maintenance Engineering, 14(2), 205-217. https://doi.org/10.1108/13552510810877692
Maseleno, A., Hasan, M. M., Tuah, N., & Tabbu, C. R. (2015). Fuzzy logic and mathematical theory of evidence to detect the risk of disease spreading of Highly Pathogenic Avian Influenza H5N1. Procedia Computer Science, 57, 348-357. https://doi.org/10.1016/j.procs.2015.07.349
Netjasov, F., & Janić, M. (2008, June 1-4). A review of the research on risk and safety modelling in civil aviation. In Third International Conference on Research in Air Transportation, Fairfax, Virginia, USA (pp. 169-176). Retrieved from http://www.icrat.org/icrat/3rd-international-conference/icrat2008_proceedingscomplete.pdf
Noriyati, R. D., Rozaaq, W., Musyafa, A., & Soepriyanto, A. (2015). Hazard & operability study and determining safety integrity level on sulfur furnace unit: A case study in fertilizer industry. Procedia Manufacturing, 4, 231-236. https://doi.org/10.1016/j.promfg.2015.11.036
Oldhama, K., Stantonb, J., Bilderbecka, M., & Spinettoa, J. (2017). Case study of a voluntary aviation safety and environmental accreditation programme. Safety Science, 96, 41-51. https://doi.org/10.1016/j.ssci.2017.02.015
Panagopoulos, I., Atkin, C. J., & Sikora, I. (2017). Developing a performance indicators lean-sigma framework for measuring aviation system’s safety performance. Transportation Research Procedia, 22, 35-44. https://doi.org/10.1016/j.trpro.2017.03.005
Perrow, C. (1999). Normal accidents: living with high-risk technologies. New Jersey: Princeton University Press.
Pillay, M. (2015). Accident causation, prevention and safety management: a review of the state-of-the-art. Procedia Manufacturing, 3, 1838-1845. https://doi.org/10.1016/j.promfg.2015.07.224
Ramkumar, M. (2016). A modified ANP and fuzzy inference system based approach for risk assessment of in-house and third party e-procurement systems. Strategic Outsourcing: An International Journal, 9(2), 159-188. https://doi.org/10.1108/SO-12-2015-0030
Ramkumar, M., Schoenherr, T., & Jenamani, M. (2016). Risk assessment of outsourcing e-procurement services: integrating SWOT analysis with a modified ANP-based fuzzy inference system. Production Planning & Control, 27(14), 1171-1190. https://doi.org/10.1080/09537287.2016.1190877
Rasmussen, J. (1997). Risk management in a dynamic society: a modelling problem. Safety Science, 27(2-3), 183-213. https://doi.org/10.1016/S0925-7535(97)00052-0
Reason, J. (1998). Managing the risk of organizational accidents. Burlington, USA: Ashgate Publishing Company. Sikora, I. (2015). Risk assessment, modelling and proactive safety management system in aviation: a literature review. In Proceedings of Conference on Transportation Systems with International Participation. Retreived from http://openaccess.city.ac.uk/16320/1/Sikora_KoREMA_2015_v_2_0.pdf
Stanton, N. A. (2008). Modelling command and control. London: Taylor & Francis Group.
Stoop, J., & Dekker, S. (2010). Limitations of ‘Swiss Cheese’ models and the need for a systems approach. In Proceedings of the 41 st Annual International Seminar “Investigating ASIA in
Mind–Accurate, Speedy, Independent and Authentic” (pp. 52-59). Retreived from https://www.isasi.org/Documents/library/Seminar-Proceedings/Proceedings-2010.pdf
Tsay, C. Y. J., Kuo, C. C., Chao, C. J., Drury, C. G., & Hsiao, Y. L. (2014, June). Safety culture evaluation in China Airlines: a preliminary study. In International Conference on Engineering
Psychology and Cognitive Ergonomics (pp. 387-397). Cham: Springer. https://doi.org/10.1007/978-3-319-07515-0_39
Tuzkaya, U. R., & Önüt, S. (2008). A fuzzy analytic network process based approach to transportation-mode selection between Turkey and Germany: A case study. Information Sciences, 178(15), 3133-3146. https://doi.org/10.1016/j.ins.2008.03.015
Wang, L., & Sun, R. (2012). The development of a new safety culture evaluation index system. Procedia Engineering, 43, 331-337. https://doi.org/10.1016/j.proeng.2012.08.057
Weaver, D. (1971). Symptoms of operational error. Professional Safety Journal, 104
(2), 39-42.
Wichapa, N., & Khokhajaikiat, P. (2017). Solving multi-objective facility location problem using the fuzzy analytical hierarchy process and goal programming: a case study on infectious waste disposal centers. Operations Research Perspectives, 4, 39-48. https://doi.org/10.1016/j.orp.2017.03.002
Wise, B. (2016). Safety risk management principles from the Federal Aviation Administration. In Resident’s Handbook of Medical Quality and Safety (pp. 17-20). Cham: Springer. https://doi.org/10.1007/978-3-319-24190-6_3
Xianfeng, L., & Shengguo, H. (2012). Airport safety risk evaluation based on modification of quantitative safety management model. Procedia Engineering, 43, 238-244. https://doi.org/10.1016/j.proeng.2012.08.041
Xueyan, S., Mingliang, Q., & Mingang, G. (2012). Safety risk analysis in flight operations quality assurance. Systems Engineering Procedia, 5, 81-86. https://doi.org/10.1016/j.sepro.2012.04.013
Yüksel, İ., & Dağdeviren, M. (2010). Using the fuzzy analytic network process (ANP) for Balanced Scorecard (BSC): A case study for a manufacturing firm. Expert Systems with Applications, 37(2), 1270-1278. https://doi.org/10.1016/j.eswa.2009.06.002
Zadeh, L. A. (1965). Information and control. Fuzzy Sets, 8(3), 338-353.
Zhao, X., Hwang, B. G., & Gao, Y. (2016). A fuzzy synthetic evaluation approach for risk assessment: a case of Singapore’s green projects. Journal of Cleaner Production, 115, 203-213. https://doi.org/10.1016/j.jclepro.2015.11.042
Zhao, Z., Liu, L., & Liu, F. (2008, October). Airport internal safety risk assessment using fuzzy hierarchy process approach. In International Symposium on Computational Intelligence and Design, 2008. ISCID’08. (Vol. 1, pp. 170-173). IEEE. https://doi.org/10.1109/ISCID.2008.144
Zhou, C., & Hu, D. (2012). Research on inducement to accident/incident of civil aviation in southwest of china based on grey incidence analysis. Procedia Engineering, 45, 942-949. https://doi.org/10.1016/j.proeng.2012.08.263