Dijital sürdürülebilirlik perspektifinden tekstil üretiminde bir BT yatırım değerlendirme çerçevesi

The textile industry, one of Türkiye's and the world's leading and most significant industries, is undergoing an intensive digitalization process driven by the need to enhance competitiveness through operational efficiency, social compliance, and sustainability requirements. This paper presents a comprehensive assessment framework to evaluate IT (Information Technologies) investments in textile production from a digital sustainability perspective. The framework structured around eight key criteria: technological infrastructure, cost, data security, strategic fit, organizational culture, management support, environmental impact, incentives and policies. Each main criterion is further broken down into sub-criteria to facilitate a systematic and detailed analysis. The evaluation applied on nine IT investment alternatives: Internet of Things (IoT), Digital Twin(DT), Enterprise Resource Planning ERP) Systems, Image Processing (IP), Energy Management Systems (EMS), Manufacturing Execution Systems (MES), Smart Logistics and Inventory Management (SL/IM), Block-chain (BC), and Augmented Reality and Virtual Reality Applications (AR/VR) across eight criteria and twenty-two sub-criteria. To address the uncertainties inherent in decision-making processes, Spherical Fuzzy Logic integrated with AHP and TOPSIS are employed. This hybrid approach combines expert opinions and industry insights, providing a robust and flexible prioritization process under complex, real-world conditions. Preliminary findings indicate that the proposed framework not only helps decision- makers in selecting the most suitable IT solutions for digital transformation but also supports sustainable development in the textile industry by balancing economic, environmental and social objectives. Although the primary focus is on Türkiye's textile industry, the adaptable nature of the framework supports its application in a variety of industries and international environments. Future research directions and potential limitations of the study are discussed, paving the way for further improvements and empirical validation.