Investment decision-making of closed-loop supply chain driven by big data technology

Abstract

<p style='text-indent:20px;'>In this paper, we put forward a data-driven supply chain consisting of a manufacturer, a retailer, and a third-party data service provider and explore the two stages of the manufacturer in making investment decisions. Given the convenience of recycling information sources, we divided the structure of the closed-loop supply chain into three investment models, including (1) the manufacturer concentrates on the two stages through big data technology; (2) the manufacturer can stimulate the retailer, who is close to reused products, to attend data collection activities; (3) the manufacturer subcontracts data collection activities to the third-party. The result shows that the manufacturer as the leader of Stackelberg will have alternative models in different situations. Specifically, the retailer is more inclusive than the third-party in the information market due to the positive influence of the price sensitivity coefficient, with the manufacturer always choosing to cooperate with the retailer when the cost advantages of big data investment are less than or equal to that of the third-party. In the event that the third-party data provider, seeing its cost advantage coefficient 0.5 times bigger than that of the retailer, will dominate the information market. Although the third-party has the upper hand, the information market will be shared by the retailer when the cost advantage coefficient of the former is two times bigger or more than that of the latter, with the share shinking with the advantage of the retailer. In addition, there is an interesting finding that the expanding cost advantage of the third-party will have a positive impact on the optimal profit of the manufacturer from two perspectives, including a direct rise in profit and a narrower range of dropping profit.</p>