Abstract
PurposeThe regular occurrence of natural disasters elevates the need for an effective method to measure organizational preparedness in responding to the adverse impact of disasters. In this context, this paper presents a new decision support model to assess organizational disaster preparedness using both subjective and objective disaster preparedness criteria in a multi-criteria decision-making context.Design/methodology/approachThe statistical variance method is integrated with the proximity value index (PVI) technique to determine priority scores in order to rank organizational disaster readiness.FindingsThe results of applying the integrated model developed herein enable decision-makers to make informed decisions for assigning priority ranking of organizational disaster preparedness in a simpler and more efficient way.Research limitations/implicationsHuman resource is the most impacting criterion affecting hospital preparedness in undertaking action to cure disaster victims.Practical implicationsThis paper offers an exemplar of a simple and efficient decision-making process considering the subjectivity associated with decision-making as well as the objectivity of data used for determining the priority ranking of organizational disaster preparedness.Originality/valueIntegrating statistical variance method with the PVI technique is novel and it has not been presented in previous studies. In fact, this study is the first to integrate both methods for selecting the priority ranking of organizational disaster preparedness.
Subject
Management Science and Operations Research,Safety Research
Reference59 articles.
1. Ahmad, S., Akber, A., Khan, Z.A. and Ali, M. (2021), “Selection of best dispatching rule for job sequencing using combined best–worst and proximity index value methods”, in Singari, R.M., Mathiyazhagan, K. and Kumar, H. (Eds), Advances in Manufacturing and Industrial Engineering. Lecture Notes in Mechanical Engineering, Springer, Singapore, doi: 10.1007/978-981-15-8542-5_68.
2. Integrating sustainability into supplier selection with analytical hierarchy process and improved grey relational analysis: a case of telecom industries;International Journal of Advanced Manufacturing Technology,2017
3. A decision support system for materials selection using proximity indexed value method;MaterialsToday: Proceedings,2022
4. Level of emergency and disaster preparedness of public hospitals in Northwest Ethiopia: a cross-sectional study;African Journal of Emergency Medicine,2022
5. Evaluation of hospital disaster preparedness by using multi criteria decision making: the case of Turkish hospitals;International Disaster Risk Reduction,2020