Big data-enabled large-scale group decision making for circular economy: An emerging market context

Abstract

This study is focused on presenting a unique landscape for big data-enabled circular economy that involves stakeholders as important decision makers. This research is designed based on five case studies from emerging markets with a focus on circular models to propose a framework for large scale decision making. In these cases, different linear economy problems are addressed that further utilizes the integration of big data and large-scale group decision making by stakeholders to achieve circularity. The findings of our study indicate a four-step design (enabling technologies, business significance, deriving value, and circular goals) to implement the 10R's of the circular economy through emerging technologies such as big data and related mobile applications along with cloud-based platforms. The study highlights how cases from emerging markets can be useful for other firms and ecosystems, ranging from e-commerce to manufacturing, that employ large number of decision makers with the aim of creating a circular economy. At the end, the study presents theoretical and practical implications along with the scope for future research.