Analysis and Evaluation of Sustainable Economic Development Components in the Supply Chain Using the Best–Worst Approach
Keywords:
Sustainable economic development, sustainable supply chain, multi-criteria decision-making, best–worst method, fuzzy analysisAbstract
This study aims to analyze and prioritize the indicators of sustainable economic development in the supply chain of Iranian manufacturing industries using the fuzzy Best–Worst Method (BWM). This applied and descriptive–analytical research involved experts from academia and industry in the fields of industrial management and supply chain. Forty-one economic indicators of sustainable development were identified through literature review. Data were collected via a fuzzy survey and normalized through defuzzification. The final weights were obtained using the BWM model in Lingo software, and the inconsistency rate was calculated to ensure data reliability. Results showed that indicators such as production rate (W1), demand (W25), and the percentage of need for a green production system (W30) had the highest weights, indicating their crucial role in achieving economic sustainability in the supply chain. Conversely, indicators such as production start-up cost (W4) and maintenance cost per product unit (W11) had the lowest weights. The inconsistency rate was 0.0619, confirming the model’s high validity and reliability. By providing a localized and quantitative model for prioritizing economic sustainability components, this study offers a practical framework for managers and policymakers to enhance strategic decision-making focused on productivity, demand management, and green production technologies. The proposed model can serve as a foundation for future research and sustainable decision frameworks in various industrial sectors.
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