Optimal price and service decisions for sharing platform and coordination between manufacturer and platform with recycling

https://doi.org/10.1016/j.cie.2020.106586Get rights and content

Highlights

  • Both manufacturer and sharing platform prefer to recycling supply chain as long as cost can be saved.

  • Cooperation is better than non-cooperation in profit and service.

  • Non-cooperative profit accounts for 3/4 of the profit in cooperative case.

  • The cost savings from remanufacturing will be evenly distributed to manufacturer and platform.

  • Manufacturer will increase or decrease wholesale price by the same amount as subsidy according to plus or minus sign.

Abstract

In this paper, a supply chain with a manufacturer and an Internet sharing platform who leases products to customers is considered. We solve the optimization problem in two structures, namely, without and with recycling. In basic structure, manufacturer produces new products and sells them to the platform. Then platform leases products to customers with per-use price and service level. Since platform keeps the ownership of products, reverse logistics from platform to manufacturer is explored. In both cases, cooperative and noncooperative relationships between manufacturer and platform are discussed. The results show cooperation is better than non-cooperation in profit and service aspects. Total profit in non-cooperative case accounts for 3/4 of the total profit in cooperative case, among which manufacturer’s profit is 1/2 and platform’s profit is 1/4. We also investigate the coordination policy between manufacturer and platform in noncooperative case via the recycling subsidy and find that subsidy affects the wholesale price merely. An example is given to illustrate values and sensitivity analyses are performed theoretically and numerically.

Introduction

Recent years have witnessed the Internet sharing platforms that provide direct or indirect service to customers, such as 3D Hubs for 3D printing, Airbnb for apartments, Velib for bikes, Uber for cars, MachineryLink for farm equipment. Taylor (2018) divided these platforms into three types: product sharing platform, on-demand service platform and freelancing platform. Product sharing platform is characterized by the sharing of the right to use, and helps customers access to assets renting, such as apartments, bikes (Benjaafar, Kong, Li, & Courcoubetis, 2018). The new economic pattern integrates and allocates scattered manufacturing resources and capacities around each link of the manufacturing process and maximizes the production efficiency of the manufacturing industry.

Though bike sharing system (e.g., Velib) runs successfully, large number of scrapped bikes witness the poor management of the Internet operator. Platform involves in trouble dealing with damaged bikes on the streets. Furthermore, famous enterprises Caterpillar has established three major remanufacturing centers in US, UK and China. Xerox saved 40–65% manufacturing costs by recycling the components and materials of used products (Savaskan, Bhattacharya, & Van Wassenhove, 2004). Motivated by this, we pay special attention to inverse logistics.

This paper considers the supply chain consisting of one manufacturer and one Internet operator and compares the optimal wholesale price, lease or per-use price and service level in two different structures, namely without and with recycling. In the first case, the manufacturer produces new products and sells them to the operator, while he recycles and remanufactures secondhand products as well in the second case. In both cases, platform provides customers leasing service with per-use price and service level. Considering that the manufacturer and platform operator could belong to the same enterprise, or they are independent, we establish the cooperative and noncooperative models.

It is worth noting that recycle flow brings up an important issue, namely how to coordinate between manufacturer and platform. On the one hand, since the recycled products with residual value belongs to platform, manufacturer who acts as collector are supposed to pay subsidy to platform. On the other hand, the manufacturer spends cost to recycle and help platform release environmental pressure from government, and s/he expects to get subsidy from platform.

Considering the motivation and supply chain structures, the questions raised in this paper include:

  • 1.

    Under what conditions will both members choose the recycling supply chain? That is, what is the difference of optimal solution with or without recycling?

  • 2.

    Whether cooperation is better than non-cooperation? That is, what are the optimal profits of both members in different situations?

  • 3.

    How to coordinate between manufacturer and platform in non-cooperative case? That is, how to make decision on recycle subsidy and how does it affect the optimal solution?

This paper differs from previous studies on inverse logistics which starts from customers. We point out that the recycle flow in this paper is from platform operator to manufacturers since platform keeps the ownership of products. It makes our paper superior to the commonly discussed inverse logistics in several aspects. Firstly, recycle process is independent of customers, which means literatures discussing the efforts to encourage customers to return products back are unnecessary. Collector merely negotiates with platform operator who supports recycle due to the cost-saving and environment issues. Secondly, the quantity of collected products is almost one hundred percent percent compared with recycling from customers among whom they are unwilling to return products back. Thirdly, customers do not differentiate between new and remanufactured products as long as the leased products work smoothly. This feature helps avoid assuming that they have identical market acceptance (Zheng et al., 2018). This fact is different from that remanufactured products will compete with new products (Wu, 2012, Tao et al., 2018). Consequently, platform prefers to remanufactured products if they are more economical than new products.

This paper differs from previous studies on model as well. Firstly, we introduce daily loss rate of product that implies the quantity of products that can be leased is not fixed. Secondly, we characterize the proportion of recycled product that can be used for remanufacturing as a parameter, and explore its influence by simulation. It is assumed to be 100% in most literature. Lastly, the subsidy is studied to coordinate between manufacturer and platform. That is to say, subsidy will answer two questions. One is that who should bear recycling cost, and the other one is that who can benefit from cost-savings.

Main findings in this paper are threefold. Firstly, when the cost used to produce a new product is higher than that of recycling and reproducing a secondhand product, the two members will take the remanufacturing policy. Secondly, service and profit in cooperative case are better than that in non-cooperative case. Total profit in the non-cooperative case is only 3/4 of the total profit in the cooperative case, of which the manufacturer is 1/2 and the operator is 1/4. Thirdly, in noncooperative case, recycled subsidy which indicates the coordination between the manufacturer and platform operator affects wholesale price merely. Namely, manufacturer will increase or decrease wholesale price by the same amount as subsidy. And the cost savings due to remanufacturing are evenly distributed between platform and manufacturer.

The reminder of this paper is organised as follows. Section 2 gives literature review related to our study. In Section 3, we formulate the problem and describe the profit functions of the manufacturer and the operator. Then, models in different cases are established. Analyses and simulations are shown in Section 5. At last, there is a brief summary including directions for further research.

Section snippets

Literature review

The research relates to three main streams of literature: one is the price and service strategy; second stream explores leasing mode, and another one is remanufactured products.

Problem formulation

This study is inspired by bike-sharing system, and is applicable to other leasing industry. The actual supply chain existing presently is comprised of a manufacturer that produces new products from raw materials and a platform operator that leases the products to customers. The supply chain is depicted in Fig. 1(a). Superscript A is used to denote supply chain without recycling. Since the sharing industry is on the rise, inexperienced platform operator does poorly on managing off-line.

Models

In this section, we established cooperative and non-cooperative models in supply chain A and B. Then the optimal solution problem in both cases are solved.

Analysis and simulation

We now explore further properties or economic implications associated with the cooperative and non-cooperative models. We focus on comparisons between the optimal solutions for two supply chains and coordination between manufacture and platform operator in non-cooperative model. Then parameters’ sensitivity analysis are given to provide more insights by means of numerical simulations.

Conclusions

In this paper, we consider a supply chain with one manufacturer that both produces new products and recycles, remanufactures secondhand products and one Internet operator who leases the two kinds of products to customers. We solve the problems in two options: cooperative or noncooperative, with or without recycling and remanufacturing. Compared with cooperative model, noncooperative model gains 34 unit of the total profit, among which 12 unit is the manufacturer’s profit and 14 unit owns to the

CRediT authorship contribution statement

Xuejie Ren: Conceptualization, Methodology, Software, Investigation, Writing - original draft, Data curation. Michael Herty: Formal analysis, Writing - review & editing, Visualization. Lindu Zhao: Supervision, Investigation, Writing - review & editing, Project administration, Funding acquisition.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (no. 71661147004); the Key R&D Plans of Jiangsu Province, China (No. BE2017156); the Fundamental Research Funds for the Central Universities (no. KYCX18_0196), Postgraduate Research & Practice Innovation Program of Jiangsu Province (no. KYCX18_0196); and the China Scholarship Council.

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