Exploring barriers to smart and sustainable circular economy: The case of an automotive eco-cluster

Investigating the sustainable development goals derived due to adoption of circular economy practices.

Industries are moving towards maintaining sustainable production and consumption considering reverse logistics by maximizing the value creation of the end-of-life products and streamlining the busi...

Industry 4.0 model for integrated circular economy-reverse logistics network

Cooperate or compete? A strategic analysis of formal and informal electric vehicle battery recyclers under government intervention

ABSTRACT This special volume explores topics related to green and sustainable supply chain management (GSSCM) in platform economies. This article aims to provide an overview by dividing these topics into six groups: (1) platform-based GSSCM, (2) technological innovations supporting GSSCM in the platform economy, (3) data-driven sustainable development of the supply chain, (4) influencing factors of supply chain management (SCM), (5) coping with disruptions in SCM, and (6) data-driven medical SCM. Considering the urgency of action required for environmental pollution, the most important research contributions are sustainable development and influencing factors of SCM in a platform economy. Some authors have explored implementation barriers, distribution channel choice, collaboration and lean management, water shortages, and remanufacturing as key aspects of GSSCM. Others have discussed aspects of sustainable development, such as waste discharge prediction, efficiency evaluation, sustainability indexes, and collaborative logistics networks, while others have investigated the factors influencing SCM, such as green management, stakeholder motives, cause marketing, online consumer reviews, and public concerns. Their findings can serve as a reference for policymakers and business decision makers to promote GSSCM practices. However, many additional challenges must be overcome to successfully implement GSSCM.

Green and sustainable supply chain management in the platform economy

In reducing waste and protecting natural resources benefits in a circular economy platform, performing remanufacturing tasks are complex, as it may be associated with costs such as investment, setu...

Optimal number of remanufacturing in a circular economy platform

Product identification approach has become a crucial issue for the inventory monitoring process. Because of the enhanced product spectrum and many shipment points, it is quite likely to send incorrect orders to the customer erroneously. With the help of this proposed model, particular troubles during product shipment could be solved. In this study, it is aimed to not only delivery right product to the right consumers but also ensures Kanban system inside the facility by performing product identification procedure. Within the scope of this study, a technology - industry integrated system has been designed by using convolutional neural network architecture. Keywords : Convolutional Neural Network, Deep Learning, Product Identification

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Elif Cesur

Papers

Optimal number of remanufacturing in a circular economy platform

Product Identification System Design Based on Deep Learning