http://scholars.ntou.edu.tw/handle/123456789/211 2026-04-24T10:00:39Z http://scholars.ntou.edu.tw/handle/123456789/26531 標題: Optimizing Sustainable Electronics Supply Chains Under Carbon Taxation and Fuzzy Demand: A Multi-Goal Programming Approach 作者: Chung, Kuang-Yen; Chiu, Rong-Her 摘要: The sustainable transformation of electronics supply chains (ESCs) increasingly relies on effective green supply chain planning under carbon pricing and demand uncertainty. However, prior studies often lack an integrated framework that jointly considers carbon taxation, green technology investment, and profitability-environment trade-offs in forward and reverse supply chains. To address this gap, this study proposes a fuzzy multi-goal optimization model using linear goal programming under progressive carbon taxation. The model incorporates fuzzy demand (triangular fuzzy numbers), carbon emissions, carbon taxes, and green investment costs and is converted into a solvable linear form via a defuzzification-based procedure to simultaneously achieve multiple aspiration levels for economic and environmental objectives. A real-world ESC case validates the model. The results show that carbon taxation and green investments can reduce emissions while maintaining profitability, with total cost and emission sensitivity of +/- 10-20% across different policies and demand uncertainty settings. The findings support adaptive, policy-aware planning by guiding green investment intensity and forward-reverse logistics decisions to balance cost efficiency and emissions reduction and provide actionable insights for managers facing progressive carbon pricing regulations. 2026-01-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/26497 標題: Unveiling a Data-Driven Circular Business Strategy Framework in a Digital Supply Chain: A Strategic Roadmapping for the Semiconductor Industry 作者: Kurrahman, Taufik; Tsai, Feng Ming; Lim, Ming K.; Sethanan, Kanchana; Tseng, Ming-Lang 摘要: Unveiling a data-driven circular business strategy (CBS) framework in a digital supply chain is needed to develop a data-driven analysis owing to the necessity of reconstructing the attributes involved and concentrating on matching the operational and environmental technology together. The semiconductor industry encounters the challenge of integrating top management commitment and collaboration with digital manufacturing and production, which aligns with waste and resource management as well as operations efficiency. To achieve this challenge, this study utilizes a hybrid method using content, bibliographic, and cluster analyses, the entropy weighted method (EWM) and the fuzzy Delphi method (FDM), to validate the data-driven CBS in a digital supply chain. Furthermore, the fuzzy synthetic evaluation-decision-making trial and evaluation laboratory (FSE-DEMATEL) developed strategic data-driven circular business roadmapping. Hence, this study constructed a hierarchical structure and identified valid prioritized main attributes to support CBS in a digital supply chain. The findings indicate that digital integration capability, green innovation, waste repurposing, decision support systems, and machine learning applications can be used to enhance CBS in digital supply chains and contribute to data-driven practical guidance by using strategic roadmapping for the industry. 2025-01-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/26494 標題: Sustainable dynamic pricing, advertising, and replenishment strategies under emissions constraints and time-varying demand 作者: Liu, Je-Hung; Dye, Chung-Yuan; Yang, Chih-Te 摘要: This study investigates how a profit-maximizing firm can jointly optimize its pricing, advertising efforts, and inventory replenishment strategies over a finite planning horizon under the cap-and-price regulatory framework. Our theoretical results demonstrate that cap-and-price regulation enables governments to effectively control emissions, offering an effective policy tool to balance economic development and environmental protection. Numerical examples reveal that goodwill and regulatory parameters significantly influence a firm's behavior. More frequent replenishment allows firms to fine-tune pricing and advertising strategies at the cost of higher replenishment and emission-related expenses. We alsofind that Cap-and-Trade yields the highest profit and moderate emissions, benefiting from trading flexibility and balanced incentives. In contrast, firms adopt aggressive strategies without regulation, producing the highest emissions and lowest profits. Furthermore, as carbon penalties internalize emission costs, firms may face higher operating costs, leading to rising prices or reduced advertising efforts. Such responses can affect brand image and weaken customer loyalty, underscoring the importance of integrated and adaptive decision-making in regulated markets. The proposed model offers valuable insights for high-emission sectors, supporting integrated decisions under environmental constraints. Finally, we conclude the study with insights derived from the theoretical analysis and numerical experiments and suggest directions for future research. 2025-01-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/26424 標題: Circular economy challenges under uncertainty in the Indonesian fashion industry: A causal hierarchical model 作者: Bui, Tat-Dat; Rosiana, Rita; Tsai, Feng-Ming; Chiu, Anthony S. F.; Tseng, Ming-Lang 摘要: This study provides insights into the circular economy challenges in the Indonesian fashion industry and builds a hierarchical model under causality relations among the proposed challenges' attributes. However, the Indonesian fashion industry imposes many challenges in addressing environmental and social concerns. This study aims to assess the partition challenges of the fashion industry to establish a new approach to developing a hierarchical model. A hybrid methodology is proposed. (1) The fuzzy Delphi method is used to establish a valid set of circular economy challenges; (2) the fuzzy decision-making test and evaluation laboratory are used to assess the causal relationships among the different attributes to determine the challenges; and (3) the analytic network process can assess hierarchical interdependencies among the attributes. The results show that waste management barriers and standard and regulation challenges are the main causal attributes. The challenges in the Indonesian fashion industry include inadequate waste management infrastructure, a lack of regulatory pressure on waste management, unstandardized circular economy measurements and the high dependability on third-party waste pickers. 2025-01-01T00:00:00Z