SWOT Framework Based on Fuzzy Logic, AHP, and Fuzzy TOPSIS for Sustainable Retail Second-hand Clothing in Liberia

Abstract

Abstract The fast-fashion business model is marred by high resource consumption and enormous emission of greenhouse gases. It is based on inaccurate forecasts, resulting in excess supply than demand. Globally, 85% of two-week-old garments end up as unfashionable or worn-out items that must be discarded as waste, disposed of for recycling, or donated to charities. With this colossal increase in textile waste, resource efficiency is one of the biggest challenges facing the fashion industry, which now calls for a swift implementation of a new sustainable business and consumption model to extend product life cycles. This demand for sustainable consumption encourages consumers to reuse, recycle and resell. The resell campaign known as second-hand clothing is a growing market worldwide. Current global forecasts predict a 185% increase over the next ten years, compared to FF, which will expand by just 20%. Africa is a top destination, with more than 80% of its population wearing SHCs. We contribute to this literature by assessing the significance of SHC trade in Liberia. We extend this assessment by developing a hybrid MCDM tool incorporating AHP, fuzzy logic, Ensemble, and TOPSIS to build a SWOT framework to identify criteria and sub-criteria for prioritizing SHC retailing in Liberia and Africa. Data for this study were gathered from a survey involving 100 SHC retailers from the Red-Light, Waterside, Duala, and Omega markets in Monrovia, Liberia. We identified several important factors in implementing sustainable SHC and recommended strategic directions towards their successful implementation.