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Circular dairy supply chain management through Internet of Things-enabled technologies.

Yigit KazancogluMelisa Ozbiltekin-PalaMuruvvet Deniz SezerAnil KumarSunil Luthra
Published in: Environmental science and pollution research international (2022)
Internet of Things-enabled technologies help to collect data and make it understandable, especially in supply chain processes, thus minimizing the problems that may arise in supply chains. It is extremely important to support this process with Internet of Things-enabled technologies, especially in supply chains that are vulnerable to disruptions such as the dairy supply chain. Moreover, dairy supply chains are the type of supply chains where the most waste is generated; evaluating this waste is very beneficial to the circular economy. Therefore, monitoring data in dairy supply chains and using Internet of Things-enabled technologies prevent losses; it is critical to have Internet of Things-enabled circular dairy supply chains in operation. The aim of this study is to determine the success factors of Internet of Things-enabled circular dairy supply chains based on the various stages of these chains; we hope to match each dairy supply chain stage with a success factor of Internet of Things-enabled technology and determine a ranking for these factors. Hence, six success factors of Internet of Things-enabled circular supply chains are weighted for each stage of the chain; Internet of Things-enabled digital technologies are then matched with each stage of the chain, and the success factor is determined. The ranking of factors can then be drawn up through the integration of Step Wise Weight Assessment Ratio Analysis (SWARA) and Technique for Order Preference Similar to Ideal Solution (TOPSIS). The outcome of this study will provide managers and policy makers with insights into Internet of Things-enabled circular dairy supply chains.
Keyphrases
  • health information
  • healthcare
  • magnetic resonance
  • body mass index
  • physical activity
  • heavy metals
  • machine learning
  • computed tomography
  • big data
  • electronic health record
  • deep learning
  • weight gain