Fadara, Taiwo Gbolarumi and Wong, Kuan Yew (2023) A decision support system for sustainable textile product assessment. Textile Research Journal, 93 (9-10). pp. 1971-1989. ISSN 0040-5175
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Official URL: http://dx.doi.org/10.1177/00405175221135167
Abstract
Given the significant scale of the textile industry, there has been rising global concern over the sustainability of this sector. Consumers’ satisfaction with textile materials plays a pivotal role in sustainable textile products in competitive markets. There have been limited studies on understanding customers preferences and the selection criteria for sustainable textile products in developing countries, where the uncertainties of demand and supply abound. The sustainability impact of textile products in developing countries has not been thoroughly investigated in previous studies. This study aims to examine sustainability criteria to evaluate the selection of sustainable textile products. Thus, using a case study of the textile industry in Nigeria, this paper provides a fuzzy decision support system to analyze the selection of sustainable textile products in the country's textile industry. The study employed an integrated fuzzy best-worst method and fuzzy inference systems to evaluate textile products. The fuzzy best-worst method was used to calculate the weight of each criterion while a fuzzy inference system was employed to select the best product. The proposed method was utilized in a real-world case study, and some managerial implications were determined. Based on three distinctive evaluative assessments, the proposed method was shown to be valid and robust.
Item Type: | Article |
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Uncontrolled Keywords: | fuzzy best-worst method, fuzzy environment, sustainability indicators, sustainable manufacturing, textile industry, textile products |
Subjects: | T Technology > TJ Mechanical engineering and machinery |
Divisions: | Mechanical Engineering |
ID Code: | 107413 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 11 Sep 2024 04:48 |
Last Modified: | 11 Sep 2024 04:48 |
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