COVID-19: a Kano model and AHP-based classification of preventive activities under Fuzzy environment

Abstract

PurposeThe aim of the present work is to develop a method to find the preventive measures for COVID-19 and their priorities. These preventive measures are prioritized according to the expert opinion.Design/methodology/approachAn integrated method using the Kano model and Fuzzy-AHP is used to achieve the study objectives. First, the preventive measures are identified according to the expert. Next, the Kano model is used to determine the different Kano categories for remedial activities that are identified by the World Health Organization (WHO) and other medical authorities. Finally, Fuzzy-AHP is applied to determine the weights of these activities and assign the priorities according to their impact.FindingsIt is observed that the activity Avoid Travelling is the most important classification or category with the highest weight as compared to the other activities and sub-activities. It is also noticed that the category packed food items get the lowest weight and is the least important classification or category. In this work, two different approaches, designed for different purposes, provide similar results and verify each other.Originality/valueResearch contributing to the classification and prioritization of preventive activities using Kano and Fuzzy-AHP methods is not available. In the critical time of COVID-19, when governments are obliged to deal with many infected patients and a high number of deaths, one can focus on different preventive activities according to their classification, weights and ranks.