This paper presents a framework for reverse logistics aimed at managing reusable items within supplier-buyer relationships to promote sustainability and reduce environmental impact. In this model, the supplier produces and inspects items, shipping only perfect items to buyers, while recycling or disposing of imperfect ones. Returned items from consumers are categorized as either reusable or damaged at a collection center. The concept of a circular economy encourages the return and refilling of reusable items, while damaged items are recycled. Additionally, the model incorporates carbon emissions considerations across production, storage, transportation, and landfilling, emphasizing the importance of environmental factors. To evaluate the sustainability and economic efficiency of the supply chain network, both Stackelberg and Nash equilibrium strategies are employed. The paper provides a mathematical framework based on lemmas to analyze the impact of the network and promote sustainable supply chain practices. In this cycle, consumers use the items and eventually discard them. To support a zero-waste policy, the supplier labels the bottles with barcodes to identify used items upon collection. The supplier has two different rates at which they purchase used bottles from consumers. Refilled bottles are sent back for reuse, while damaged bottles are either repurposed as raw materials or disposed of. The research paper aims to develop a mathematical model that determines the buyer's cycle time and the number of deliveries from the supplier to the buyer, ensuring that the buyer's demand is met without shortages.

Textile industry involves a lengthy process from upstream to downstream, making supply chain integration crucial for enhancing firm performance. This study explores various factors that can boost supply chain integration and company performance in Indonesia's textile sector, including strategic agility, innovation capability, and technology adoption. The research is grounded in resource-based-view and market-based-view theories, suggesting that companies can optimize their resources and collaborate effectively with supply chain partners to enhance industry performance. Additionally, the study considers environmental turbulence as a moderating variable. Utilizing a quantitative approach with judgmental sampling, the research collected data through a structured questionnaire, resulting in 270 valid responses. The data was analyzed using the partial least squares structural equation modeling (PLS-SEM) method with SmartPLS 4.0 software. Findings indicate that strategic agility, innovation capability, and technology adoption significantly influence firm performance through supply chain integration, while environmental turbulence notably moderates the relationship between innovation capability and supply chain integration on firm performance. The study recommends that textile companies prioritize agility, strategic innovation, and technology adoption to enhance their integration with supply chain partners. It underscores the critical role of supply chain integration in improving company performance and the impact of environmental turbulence as a moderating factor.

In today's dynamic and uncertain environments, effective decision-making processes are essential for navigating complex challenges. This paper proposes an innovative approach utilizing Fermatean fuzzy sets to enhance decision-making within heterogeneous group dynamics. Through a systematic mathematical framework, our method integrates expert preferences to find out the comparative weight of decision attribute, leveraging both Fermatean fuzzy sets and entropy calculations. Furthermore, we introduce a novel technique to assess the significance of individual experts' opinions, accounting for specific contextual factors. By synthesizing performance ratings, criteria weights, and expert inputs, our approach offers a comprehensive decision-making model. We introduce the concept of the proximity coefficient to address existing methodological limitations, enhancing the accuracy of decision outcomes. To validate our methodology, we apply it to a practical scenario involving warehouse location selection. Additionally, analysis of sensitivity is conducted to evaluate the robustness of our method across diverse scenarios, demonstrating its efficacy in uncertain environments. This research contributes to advancing decision-making practices in complex and uncertain contexts, offering a valuable tool for addressing real-world challenges.

In today's dynamic and uncertain environments, effective decision-making processes are essential for navigating complex challenges. This paper proposes an innovative approach utilizing Fermatean fuzzy sets to enhance decision-making within heterogeneous group dynamics. Through a systematic mathematical framework, our method integrates expert preferences to find out the comparative weight of decision attribue, leveraging both Fermatean fuzzy sets and entropy calculations. Furthermore, we introduce a novel technique to assess the significance of individual experts' opinions, accounting for specific contextual factors. By synthesizing performance ratings, criteria weights, and expert inputs, our approach offers a comprehensive decision-making model. We introduce the concept of the proximity coefficient to address existing methodological limitations, enhancing the accuracy of decision outcomes. To validate our methodology, we apply it to a practical scenario involving warehouse location selection. Additionally, analysis of sensitivity is conducted to evaluate the robustness of our method across diverse scenarios, demonstrating its efficacy in uncertain environments. This research contributes to advancing decision-making practices in complex and uncertain contexts, offering a valuable tool for addressing real-world challenges.

The new economic context has brought new challenges to the supply chain and has increased the complexity of its processes. The digitalization; as one of these challenges, is a rapidly evolving paradigm that transforms supply chains by integrating data and communication technologies to optimize operations, enhance sustainability, and improve overall performance. Digital twin technology emerged as one of the most promising digital tools that offer an innovative approach to supply chain management. However, the adoption of digital twins in the supply chain is still in its early stages. Previous research papers presented limited overviews of the applications of digital twin technology in supply chain systems that need to be extended, as it is inevitably a work in progress. In this matter, we conducted a systematic literature review built upon 31 articles to determine the applications of supply chain digital twins (SCDT). This study is divided into three core themes; the first is a comprehensive review of the paradigm of digital supply chain with a focus on digital twin technology and its primary features. The second theme presents an analysis of the 31 papers where we explore the different purposes of SCDTs and their integration. in the third theme by using VOSviewer to conduct a network analysis. We aim; through this paper, to contribute significantly to the supply chain management field by summarizing and analyzing existing research and developments in the applications of digital twins in the different areas of supply chains.