Research on Collaborative Management Strategies of Closed-Loop Supply Chain under the Influence of Big-Data Marketing and Reference Price Effect

Abstract

This paper integrates the Internet service platform with big-data marketing into the dynamic closed-loop supply chain system as an independent game subject. Considering the reference price effect of consumers, this work constructs differential games among manufacturer, retailer and Internet service platform under three business models of independent, collaborative production and collaborative marketing. Using Bellman’s continuous dynamic programming theory, this work obtains the optimal feedback strategies of price and big-data marketing effort, brand goodwill, return rate of used products and corporate profits under the three business models. Comparing the three scenarios and analyzing the sensitivity of key exogenous parameters, it can be found that the involvement of Internet service platform has a crucial impact on the sustainable profitability of supply chain enterprises. Considering the reference price effect of consumers, enterprises should adopt different strategic alliances in different periods, which can also gain new development momentum in the context of data-driven marketing, achieve the improvement of the triple-bottom line of closed-loop supply chain and even reach a win-win situation for supply chain enterprises.

A Bibliometric Review of Two Decades’ Research on Closed-Loop Supply Chain: 2001-2020

“…With the development of information technology and the availability of data, big data analytics are employed by more companies in their supply chains. In the work of Ma and Hu [109], the Internet service platform with big-data marketing was integrated into the dynamic CLSC system, which served as an independent game subject. Meanwhile, sharing and learning of information is also critical in determining the efficiency and the benefit of supply chain [110].…”

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

“…Liu and Yi [21] studied the pricing and coordination strategy of products under the precision marketing of BDT. Internet service platforms utilize Big Data marketing to increase the collecting rates of used products, which in turn enhances environmental sustainability [22,33]. From the product information itself, Kai et al [32] divided the information system of the product life cycle into static data and dynamic data, indicating that breaking the information bottleneck can obtain decision support for the recovery of recycling and remanufacturing value.…”

Strategic Analysis of the Recycler considering Consumer Behavior Based on E‐Platform Recycling

“…With the emergence of Internet platforms in the reverse supply chain, several scholars have studied the pricing decisions under this recycling model [26,28,36,37]. However, related studies have mainly focused on qualitative analysis or single-channel recycling and mostly have been conducted on (re)manufacturers and retailers.…”