Research On The Optimization And Selection Of Closed-Loop Supply Chain In Investing Big Data Technology Considering Different Recovery Channels

In the era of digital economy,the whole life cycle of products is shortened with the increasing speed and breadth of their circulation.The emergence of a large number of waste products makes the traditional data engine unable to provide immediate reverse logistics data value in the massive supply chain data,so the problem of closed-loop supply chain recycling and reuse is fundamentally "information opaque".The key to achieving sustainable production management in the current environment is to break down the information barriers between supply chain members on product dynamic information heterogeneity and independence.Based on the needs of manufacturing production,the emergence of big data technology mainly provides real-time monitoring,dynamic scheduling and planning for the whole manufacturing process through functions such as data ingestion,analysis,visualization,equipment application,etc.,so as to achieve the goal of improving economic performance and environmental performance.However,at this stage,the research of closed-loop supply chain mainly focuses on the structural issues of recycling channel selection,input recovery rate and recycling price under the complex digital market,which directly affect the operational decision-making of recycling quantity,and there is relatively little research on the use of big data technology to drive accurate recycling and remanufacturing in the supply chain,and the competitive advantage relationship between retailers and third-party data service providers in the information trading market is rarely discussed.In addition,the development of the post-information market makes it uncertain for manufacturing enterprises to choose the most favorable recycling channel in the original supply relationship.Therefore,based on the different choices of single recycling channels for the original supply chain relationship,it is of important theoretical and practical significance to study the choice of manufacturers’ big data technology investment models,which provides a new thinking direction for maximizing profits of closed-loop supply chain members in the information age.The main issues studied in this paper are the choice of different recycling channels by manufacturers of recycling and remanufacturing based on the original supply relationship and the investment cooperation behavior of big data technology.On the basis of the existing research,assuming that the new products produced by manufacturers are always sold by retailers,and at the same time,the selection of big data technology subjects is focused on under the two channels of direct and indirect recycling,and the big data technology input subjects are extended from traditional manufacturers to retailers and emerging third-party data service providers in the modern market,and three choices are assumed: manufacturers invest in big data technology by themselves(scenario I and scenario IV.),manufacturers encourage retailers to invest in big data technology(scenario II and scenario V.),Manufacturers outsource investments in big data technology to third-party data service providers(Scenarios III and VI).The Stackelberg master-slave game is used to find the optimal solution of the model in each case.Firstly,the vertical big data technology investment mode under fixed recycling channels is compared,and the impact of different big data investment entities on recycling and remanufacturing,product transaction price,and profit of all parties is analyzed separately,and then the big data investment market under different recycling channels is compared and analyzed,and finally the optimal selection strategy of manufacturers as the leading manufacturers for big data investment is obtained,and the dominant position of retailers and third-party data service providers in the big data investment market is discussed.Through the analysis and combing of the article is available(1)for any recycling channel,When the cost advantage coefficient of the third-party data service provider is less than 0.5,the manufacturer will tend to cooperate with the third-party data service provider;(2)for the comparison of the investment advantage system between external members,it is found that compared with the clear dividing line of 0.5 of the cost advantage coefficient of the third-party data service provider,the cost advantage coefficient of the retailer is dynamic and greater than 0.5,which indicates that the price sensitivity of the product makes the cost optimal coefficient more inclusive than that of the third-party data provider in the first stage of big data investment;(3)when the manufacturer determines the big data investment object For self-investment or outsourcing to a third-party data service provider,depending on the final payment of the recovery unit price to the consumer,which recovery cost is low,the manufacturer will be willing to choose this recovery channel,and in the case of retailer investment in big data,only when the retailer’s recovery unit price is significantly smaller than it is easy to occupy the advantage space of the third-party data service provider;(4)When manufacturers are in a situation where external big data investment members have a common advantage,retailers under the direct recycling channel are more than indirect recycling channels.The management implications of this article mainly include(1)In the digital aftermarket,manufacturers of different recycling channels should seize the dividends brought by big data,reduce internal investment in big data technology,and fully encourage external members to participate in investment in big data technology;(2)On the one hand,the existing recycling price mechanism determines that manufacturers choose different recycling channels,on the other hand,when the recovery cost of manufacturing enterprises does not have obvious advantages compared with retailers,enterprises should observe the changes in consumers’ sensitivity to the price of products in real time,and choose direct recycling channels to recover products that can be recovered by big data investment.(3)In addition,compared with retailers with a certain consumer data base and market share in the information market,third-party data service providers can only be eliminated if they continuously improve the cost advantage of big data technology.