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The intersection of the Internet of Things (IoT) and the circular economy (CE) creates a revolutionary opportunity to redefine economic sustainability and resilience. This review article explores the intricate interplay between IoT technologies and CE economics, investigating how the IoT transforms supply chain management, optimises resources, and revolutionises business models. IoT applications boost efficiency, reduce waste, and prolong product lifecycles through data analytics, real-time tracking, and automation. The integration of the IoT also fosters the emergence of inventive circular business models, such as product-as-a-service and sharing economies, offering economic benefits and novel market opportunities. This amalgamation with the IoT holds substantial implications for sustainability, advancing environmental stewardship and propelling economic growth within emerging CE marketplaces. This comprehensive review unfolds a roadmap for comprehending and implementing the pivotal components propelling the IoT's transformation toward CE economics, nurturing a sustainable and resilient future. Embracing IoT technologies, the authors embark on a journey transcending mere efficiency, heralding an era where economic progress harmonises with full environmental responsibility and the CE's promise. [ABSTRACT FROM AUTHOR]

Sustainable supply chain management (SSCM) is a tactical concern for managers seeking a longterm result. Different managers are attempting to apply SSCM in order to get a competitive advantage. One of the critical processes is the identification of strategy implementation hurdles, which has been a research focus. As a result, this paper identifies these obstacles and analyzes their interrelationships. A list of obstacles was initially established by a survey of the literature and expert judgment in the form of the fuzzy Delphi approach. Next, an investigation was designed to collect expert opinions on the interrelationships between these obstacles. The fuzzy DEMATEL (FDEMATEL) approach was employed for examining the causal linkages and interdependencies of these obstacles. Subsequently, the interpretative structural modeling (ISM) technique was utilized to create a classified structure and to identify the driving and dependent connections. A fuzzy MICMAC analysis was applied for categorizing the obstacles based on driving and dependent power. The results reveal that barriers, "cost of implementation sustainability (B1)", "lack of financial resources (B2)", "institutional complexity (B3)", "complexity in measuring and monitoring sustainability practices (B4)", "lack of effective regulations (B5)", "lack of a proper evaluation system for suppliers (B6)", "lack of sustainability knowledge (B7)", and "strategic and structural restraints (B8)", are the influence-forwarding obstacles. These obstacles influence "inadequate government support (B9)", "high investments for sustainability and less return-oninvestments (B10)", "old equipment and machinery (B11)", and "lack of management commitment (B12)", which are the greatest influences on SSCM practices. Identifying the important obstacles and their interdependences can help policymakers in the manufacturing sector minimize or overcome them, boosting the possibilities of effectively incorporating sustainable principles into these projects. [ABSTRACT FROM AUTHOR]

This study optimizes the sustainable implementation of light wood-framed buildings in the Nordic region using multi-criteria decision-making. Integrating prefabrication, transportation logistics, and multi-criteria decision-making (MCDM) methods enhances cost efficiency, time savings, and quality assurance. Significant international and local impact promotes sustainable construction practices. Strong promotion fosters industry-wide adoption. The presented framework enables stakeholders to make informed decisions, enhancing the efficiency and effectiveness of building implementation processes and fostering sustainable development in the construction industry. [ABSTRACT FROM AUTHOR]

Shopping center plays an important role in distribution system and marketing. These canters provide an appropriate atmosphere for customers; so that, the customers achieve the best service within a short time. However, there is an intense competition among shopping centers to attract more customers for increasing the profit. Therefore, a powerful model assists authorities in identifying the critical competitive aspects and directing their efforts toward performance improvement. However, a number of strategies have been developed to identify the most relevant components. The Delphi technique under intuitionistic fuzzy environment, called intuitionistic fuzzy Delphi method (IFDM) study, is a group-based technique that can simply formulate the uncertainty imposed by decision making circle. On the other hand, multi criteria decision making (MCDM) method such as analytical network process (ANP) is a mathematical tool for taking into account mutual relationships in order to rank a number of criteria. Nonetheless, the ANP is unable to account for the uncertainty involved in the decision-making process. Similarly, the intuitionistic fuzzy set (IFS) can express ambiguity and vagueness by utilizing the given scale. Because the IFS is robust in dealing with complexity and ambiguity, the IFS-GANP (an integrated model of the IFS and ANP methods under group decision) can result in a more specific description of the situation. As a result, the IFS-GANP approach outperforms both conventional ANP and fuzzy ANP. To demonstrate the model's feasibility, a case study rating the essential aspects impacting the attractiveness of retail centers is shown. The result demonstrates factor C31 (Location) with value of 0.202 plays the greatest role in attracting customers. [ABSTRACT FROM AUTHOR]

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