关键词: 随机需求, 鲁棒优化, 直播供应链, 大数据投资, 协调

Abstract: Livestreaming sales are considered an effective combination of digital promotion and manufacturing, and more and more manufacturers have opened livestreaming sales channels. Compared with traditional online shopping, consumers are more likely to have unplanned and sudden impulsive consumption behaviors during livestreaming shopping, which makes it difficult to obtain the distribution information of market demand for live shopping. At the same time, the development of digital technology has enabled livestreaming sales to generate massive market demand and personalized preference data. These data, known as “oil”, have become important production factors for analyzing the characteristics of livestreaming sales behavior. Livestreaming retailers and data companies investing in big data can accurately analyze consumers’ heterogeneous needs, increase sales, and reduce production costs. However, it is difficult to estimate the costs and benefits of big data investment in the face of random demand, leading to a wait-and-see attitude towards big data investment. Therefore, this paper aims to address the following questions: (1)How do livestreaming supply chain members make decisions under random demand? (2)Can big data investment improve the livestreaming supply chain members and overall profits under random demand? (3)How to design a coordination contract to achieve perfect coordination of the three-echelon livestreaming supply chain including data company?
To solve these problems, this paper establishes a three-echelon supply chain game model composed of a live streaming retailer, a manufacturer and a data company, adopts the robust optimization method to study the impact of big data investment on supply chain decisions and profits under centralized and decentralized decision-making, and designs a profit-sharing-cost-sharing contract to achieve perfect coordination of live-streaming supply chain.
It is found that: (1)The overall profit of live streaming supply chain is positively correlated with the mean of random demand, but negatively correlated with the standard deviation of random demand. (2)If the total cost of big data investment meets certain conditions, both live streaming retailer and data company investing in big data can improve live streaming supply chain members and overall profits under random demand. (3)Whether or not big data is invested, the profit-sharing-cost-sharing joint contract can improve the profits of live-streaming supply chain members and the overall profits under random demand. In particular, data companies achieve perfect coordination of the live-streaming supply chain in the form of subsidies.
The contribution of this paper has three aspects. First, in view of the background, that is to say, livestreaming sales face random market demand, this paper discusses the new problem of big data investment decision and coordination of livestreaming supply chain, which makes up for the lack of random demand consideration and the lack of data companies as decision-making member consideration in current livestreaming supply chain studies. Second, it is found that the investment of big data by both live-streaming retailers and data companies can improve the members of the live streaming supply chain and the overall profits, and the profit-sharing-cost-sharing contract can realize the perfect coordination of the three-level live streaming supply chain. Third, different from the linear market demand modeling and solving method adopted in the prior research on decision-making and coordination of live-streaming supply chain, this paper adopts a new method of stochastic demand and robust optimization to solve the optimal decision-making and coordination problem of stochastic market demand of live-streaming supply chain, which cannot be solved by the modeling method of definite market demand.
The study gives the following management implications to the members of live-streaming supply chain: (1)Government can formulate relevant policies to encourage data firms and live-streaming retailers that have not yet invested in big data to invest in big data for sustainable development. (2)Government should guide supply chain members investing in big data to sign a profit-sharing and cost-sharing joint contract, to achieve the supply chain performance of centralized decision-making. (3)Supply chain members who sign the joint coordination contract should control the big data investment cost within an appropriate range according to their own cost-benefit rate.

Key words: random demand, robust optimization, livestreaming supply chain, big data investment, coordination