The purpose of this study is to extract key sustainability attributes specific to the textile supply chains by conducting an adaptive choice-based conjoint (ACBC) analysis identifying the utility scores of these attributes and evaluating supply chain performances of Turkish textile small and medium-sized enterprises (SMEs) by Priority Observed from the Presumption of Gaussian Attitude of Alternatives (PrOPPAGA) technique in terms of sub-attributes with a case study and assigning these SMEs sustainability performance scores so that they can understand their position in the competitive market.
The methodology of this research is (1) extracting the important attributes affecting the textile SMEs’ sustainability performance, (2) conducting a dynamic survey via Lighthouse Studio software of the textile SME representatives to define importance degrees (i.e. utility scores) of each textile sustainability performance sub-attributes by conducting ACBC analysis including hierarchical Bayesian (HB) regression, (3) considering these utility scores as the weight of each sub-attribute, (4) evaluating case study participant Turkish textile SMEs by involvement of the company authorities, and (5) ranking and grouping the SMEs and identifying their positions in the market.
The findings of this study emphasize the importance of carbon footprint, water usage, waste management, labor practices, community engagement, training, cost efficiency and other sub-attributes such as Extended Producer Responsibility, recycling, upcycling, transparency, traceability and eco-friendly packaging in textile supply chains. Moreover, the Turkish textile SMEs are assessed and grouped in terms of sustainability measures and positioned in the market.
The outputs of this research provide valuable insights into sustainable practices and offers a comprehensive framework to enhance textile supply chain sustainability (SCS). Besides, this research contributes to the literature by proposing a novel approach integrating ACBC and PrOPPAGA as a performance evaluation framework.
