Abstract: Rapid economic development and rapid population growth have exacerbated environmental pollution and resource shortage. Many manufacturing enterprises have begun to incorporate closed-loop supply chain into their development system. There are many interference factors in the closed-loop supply chain. Enterprise decision-makers must face the impact of these factors and make timely decisions. Improper handling may affect the reputation of enterprises. Today is in the information age, and having valuable information is conducive to enterprise decision-making and planning. Therefore, big data service providers came into being. There are various types of big data service providers, including big data service providers that provide technology-based services and big data service providers that provide data resources. Big data services have been widely used. Enterprises can choose big data service types according to their own needs, such as product recommendation, marketing assistance and recycling assistance. When the closed-loop supply chain is faced with multiple factors and the participation of big data service providers, the supply chain member strategy becomes the key. The impact of the participation of big data service providers on enterprises deserves further study. In the closed-loop supply chain, considering the involvement of a big data service provider and the recovery rate affected by various factors such as goodwill and time. This paper studies the equilibrium strategies of supply chain members under three situations of no big data service provider participation, a big data service provider providing assistance recovery and marketing service respectively, and makes a comparative analysis. This paper describes the dynamic change of recovery rate through Ito process, and analyzes the influence of big data service fee sharing ratio and the sensitivity coefficient of goodwill to recovery rate on supply chain members. The results show that: the recovery rate of used products, decisions and profits of closed-loop supply chain members can reach the expected value in a short time, and fluctuate around the expected value due to the interference of random factors; the retailer is more aware of market changes and profit; the participation of a big data service provider can improve the recovery rate and the recycling effort level of the manufacturer and the profit of closed-loop supply chain members in some way. When the external environment has more constraints and restrictions on the recycling of waste products, under the same big data service level, assisting marketing is more conducive to the improvement of recycling effort and profit than assisting recycling. The enlightenment is as follows: (1)Although the recovery rate and the decision variables and profits of supply chain members can reach the expected value in a short time, they are still in a fluctuating state due to the interference of random factors. Especially in the era of the Internet, the rapid spread of information has exacerbated the volatility of random factors. Enterprises should pay more attention to the changes in the external environment and adjust their strategies in time; (2)As retailers perceive and respond to the market more quickly, manufacturers should maintain a good cooperative relationship with retailers, share business information, jointly discuss the sharing ratio of big data service costs, reduce the negative impact of uncertainty, and enhance the level of pricing, recovery efforts and profit stability; (3)In the era of big data, enterprises should have the ability to mine valuable information from massive data. Enterprises can consider whether they need the assistance of big data service providers. When selecting the type of big data service, they should consider the overall environment, including the external environment, such as the policies of the government and other third-party institutions, the industrial environment, the economic situation and the internal environment, such as the enterprise strategy and their own capabilities, It is conducive to the sustainable development of enterprises and the environment. The study considered all sold offline. However, with the development of the Internet, many enterprises have started the online and offline dual-channel sales model. Therefore, it will be the focus of future research to consider dual-channel sales and the participation of big data service providers in the closed-loop supply chain.

Key words: a big data service provider, closed-loop supply chain, ito process, goodwill

摘要： 在闭环供应链中考虑了大数据服务商参与和受企业声誉、时间等多种因素影响的回收率,研究了无大数据服务商参与、大数据服务商协助回收和营销三种情形下供应链成员的均衡策略,并进行了对比分析。通过伊藤过程对动态变化的回收率进行了刻画,分析了大数据服务费分担比例和回收率对企业声誉敏感参数对供应链成员的影响。研究表明:废旧产品的回收率、制造商的回收努力水平、零售商的零售价格和两者的利润能够在较短时间内达到期望值,受随机因素干扰在期望值附近波动;零售商对市场变化以及自身利润的感知速度更快;大数据服务商的参与能够提高废旧产品的回收率、制造商的回收努力水平和闭环供应链成员的利润。相同的大数据服务水平下,外部环境对废旧产品回收的限制约束大于激励时,协助营销相较于协助回收对回收努力水平以及制造商和零售商利润的提升更有利。

关键词: 大数据服务商, 闭环供应链, 伊藤过程, 声誉