An Intuitionistic fuzzy approach to modeling the drivers to promote Energy-Efficient textile Manufacturing: Implications for sustainable development

Abstract

The textile manufacturing sector plays a vital role in the economic growth of many emerging economies. Hence, achieving energy efficiency and sustainability is crucial for this sector to cope with the ongoing energy crisis, rising fuel prices, and economic inflation. Previous studies on energy efficiency focused on various industrial sectors. However, none focused on assessing the driving forces to encourage the energy-efficient textile manufacturing sector in emerging economies. This study, therefore, addresses the gap in existing studies by determining and evaluating the factors and their interrelationships that encourage energy-efficient textile manufacturing in a developing economy like Bangladesh. This study utilizes a novel hybrid Interval-Valued Type 2 Intuitionistic Fuzzy (IVT2IF) theory-based decision-making trial and evaluation laboratory (DEMATEL) framework. After expert validation, sixteen factors were analyzed in this study. The findings suggest “Implementing effective in-house energy management measures (F4)” to be the most eminent factor for promoting energy efficiency. Again, “Adopting renewable energy (F2)” was found to be the most important causal group factor, and “Adopting alternative waterless dyeing technology (F3)” was found to be the most affected effect group factor. This study is expected to aid industrial managers and policymakers in promoting energy efficiency in the textile manufacturing sector and thus contribute to the sustainable development of emerging economies like Bangladesh.

Keywords

• Energy efficiency
• Textile manufacturing
• Sustainable development
• Interval-valued type 2 intuitionistic fuzzy set theory
• DEMATEL