From conventional group decision making to large-scale group decision making: What are the challenges and how to meet them in big data era? A state-of-the-art survey

TLDR: The challenges of large-scale group decision making are summarized and a state-of-the-art survey of main achievements in this field is presented to provide existing research gaps and future directions that require further consideration.

Abstract: The arrival of Big Data era has brought large, complex, and growing data generated from numerous sources. Due to the power in felicitous decision making based on diverse and large data, Big Data can be used in distinct disciplines, especially in social Big Data such as e-commerce, e-marketplaces and social media platforms. As a result, the large-scale group decision making, in which a large number of decision-makers take part in the decision-making process, has become a much-talked-about topic in decision science. Because of the characteristics of social Big Data, much more information in large-scale group decision making will arise than conventional group decision making. Information is a key factor that influences the performance of decision-makers. Therefore, how to manage the challenges from conventional group decision making to large-scale group decision making is a critical and interesting research topic. Up to now, many studies have been published to tackle these challenges. The objective of this study is to summarize the challenges and present a state-of-the-art survey of main achievements in this field. We also provide existing research gaps and future directions that require further consideration. It is hoped that our study could give insights for scholars and practitioners along the developments and promising research of large-scale group decision making.