Scholarlink

<p>Industries are working hard to rearrange their supply chains in order to build a waste reduction strategy that involves reusing and recycling waste in an efficient and affordable manner. According to the authors' knowledge, this is the first paper to investigate the relevance of reconfigurability enablers in the context of the agro-industrial waste supply chain (AIWSC) using bibliometric and co-citation analysis. An integrated framework with total interpretive structural modelling and cross-impact matrix multiplication (TISM-MICMAC) approach to categorize the enabling factors into a hierarchical structure and investigate their intricate relationships under the mentioned four drivers: digitalization, efficiency, resilience, and sustainability. In the current study introduced a new Integrated approach to measuring the reconfigurability of the supply chain mentioned AIWSC by measuring its enablers, defining its dimensions, and estimating how these dimensions relate to each other in order to determine the degree of reconfigurability. Furthermore, by combining the two methods, we developed our Comprehensive Relative Reconfigurability Index (CRRI), which evidences the fact that the AIWSC can quickly change its settings to align with the changing needs of the clients and the variations of the environment. The quantification provided a CRRI, and, supported by two separate evaluation processes, demonstrates that the AIWSC can quickly modify its configuration in response to changing client needs and environmental changes to generate a substantial score of 74.45%. This study highlights the importance of quantifying reconfigurability as a necessary step in improving the performance of the supply chain, especially under volatile and unpredictable conditions. In order to confirm the findings, we used a case study and sensitivity analysis; the findings explain the viability and effectiveness of the suggested methodology. The suggested solution technique can serve as a generic model for computational applications, and it aids as a decision-making tool to reconfigure the supply chains.</p> Graphical Abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Quantifying Reconfigurability in Supply Chains: A Comprehensive Analysis of Agro-industrial Waste Supply Chain

  • 期刊论文

  • 发表日期：

    2025年11月10日

查看全文
  • Veerababu Ramkaurthi,
  • Anupama Tiwari,
  • Rajeev agarwal,
  • Hasanul Fahmi Zuhri,
  • Ella Silvana Ginting

摘要

Industries are working hard to rearrange their supply chains in order to build a waste reduction strategy that involves reusing and recycling waste in an efficient and affordable manner. According to the authors' knowledge, this is the first paper to investigate the relevance of reconfigurability enablers in the context of the agro-industrial waste supply chain (AIWSC) using bibliometric and co-citation analysis. An integrated framework with total interpretive structural modelling and cross-impact matrix multiplication (TISM-MICMAC) approach to categorize the enabling factors into a hierarchical structure and investigate their intricate relationships under the mentioned four drivers: digitalization, efficiency, resilience, and sustainability. In the current study introduced a new Integrated approach to measuring the reconfigurability of the supply chain mentioned AIWSC by measuring its enablers, defining its dimensions, and estimating how these dimensions relate to each other in order to determine the degree of reconfigurability. Furthermore, by combining the two methods, we developed our Comprehensive Relative Reconfigurability Index (CRRI), which evidences the fact that the AIWSC can quickly change its settings to align with the changing needs of the clients and the variations of the environment. The quantification provided a CRRI, and, supported by two separate evaluation processes, demonstrates that the AIWSC can quickly modify its configuration in response to changing client needs and environmental changes to generate a substantial score of 74.45%. This study highlights the importance of quantifying reconfigurability as a necessary step in improving the performance of the supply chain, especially under volatile and unpredictable conditions. In order to confirm the findings, we used a case study and sensitivity analysis; the findings explain the viability and effectiveness of the suggested methodology. The suggested solution technique can serve as a generic model for computational applications, and it aids as a decision-making tool to reconfigure the supply chains.

Graphical Abstract