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Diffusion of green products in industry 4.0: Reverse logistics issues during design of inventory and production planning system

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  • Dev, Navin K.
  • Shankar, Ravi
  • Swami, Sanjeev

Abstract

Under the paradigm of Industry 4.0, the present research attempts to model the reverse logistics and examine how product diffusion dynamics in the market affect the economic and environmental performances of an inventory and production planning (I&PP) system. We use the classic Bass (1969) model of diffusion of innovation to capture the returns of a single-generation of a product under the proposed architecture of systematical deployment of information-sharing strategies and I&PP policies under the notions of Industry 4.0 components. The key feature of Industry 4.0 characterized by virtualization of factory operations is captured using the simulation model. For the analysis, using the Taguchi experimental design framework, we present valuable managerial insights. Our findings suggest the relevant adoption patterns based on the combination of information-sharing and I&PP policies for the tradeoff between environmental and economic performance. An extensive sensitivity analysis shows the robustness of the model. Further, the managerial decisions on the environmental and economic performance measures reveal that in spite of the presence of Industry 4.0 technology capabilities, a close attention should be paid to operational parameters and their related costs when socially influenced green product adoption with the parameters such as size of end-user market and collection investment are governing the returns of the product to the reverse logistics system. Accordingly, the model exhibits a real-time decision support tool for the sustainable reverse logistics system in Industry 4.0 environment at large.

Suggested Citation

  • Dev, Navin K. & Shankar, Ravi & Swami, Sanjeev, 2020. "Diffusion of green products in industry 4.0: Reverse logistics issues during design of inventory and production planning system," International Journal of Production Economics, Elsevier, vol. 223(C).
  • Handle: RePEc:eee:proeco:v:223:y:2020:i:c:s0925527319303408
    DOI: 10.1016/j.ijpe.2019.107519
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