Pricing and production decisions in a dual-channel closed-loop supply chain with (re)manufacturing

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Highlights

  • A closed-loop SC with a manufacturer’s direct and indirect channels is modelled.

  • Competitions between new and remanufactured products and channels are considered.

  • Conditions under which the manufacturer engages in remanufacturing are identified.

  • Optimal production and pricing strategies for the manufacturer/retailer are derived.

  • Introducing the remanufactured product does not always reduce the retailer’s profit.

Abstract

The development of information technologies and e-commerce has allowed many companies to set up online platforms to sell their products in dual-channel supply chain (SC) networks. The double competition between new and remanufactured products within channels and across competing channels affects manufacturer and retailer pricing decisions. However, the current state of the literature shows a gap in the modelling and analysis of a dual-channel SC with both cross-channel competition and channel costs. To fill this gap, this paper develops a model for a CLSC in which the manufacturer sells new products through a retail channel and also directly through its online channel. The manufacturer may also sell remanufactured products in its online direct channel if it decides to produce them. The results indicate that: (i) the manufacturer’s production and optimal pricing strategies depend on both production and channel selling costs; (ii) remanufacturing is not considered by the manufacturer when the unit manufacturing cost is sufficiently low and the retailer’s channel cost is sufficiently high; (iii) the introduction of remanufacturing hurts the retailer’s profit only when the unit manufacturing cost is sufficiently high; and (iv) selling the new product online mitigates the effect of remanufacturing on the retailer, and thus a high customer’s acceptance of the remanufactured product can benefit the retailer.

Introduction

In the past decade, supply chain (SC) managers have started to focus on product returns management and recovery policy due to the increasingly large number of returns and their negative impact on the environment (Bhatia and Rajiv, 2019). The National Retail Federation reported in 2018 that the total value of returns in the United States amounted to around 10% of the sales in the retail industry, namely 369 billion USD (Shang et al., 2018). The annual cost for US companies to deal with the returns was more than 35 billion USD (Hasanov et al., 2019). For online retailers, the return rate was more than 18% (Hua et al., 2016) and this number reached 74% for fashion products (Vlachos and Dekker, 2003). Therefore, dealing with these returns becomes a major concern for both retailers and manufacturers.

Remanufacturing has been shown to be a feasible and practical approach to deal with returns for companies (Liu et al., 2018b, Sitcharangsie et al., 2019, Chen et al., 2019). Remanufacturing can recover the value of used products and decrease the usage of raw materials and energy (Jung and Hwang, 2011). In South Korea, the remanufacturing industry accounted for around 700 million USD in 2015, a 16% increase from 2010 (Kang et al., 2018). In the United States, nearly 73,000 companies in different industries, such as computer components, smartphones, and engines, operated a remanufacturing business (Shi et al., 2011). Armstrong World Industries, a ceiling tile company, produces its tiles with more than 80% of recycled materials and reports a significant decrease in the emission of greenhouse gas and materials (Bhatia and Rajiv, 2019). Xerox Corporation has engaged in remanufacturing printers and saved about $6 million USD in production cost from 2008 to 2009 (Liu et al., 2018a). Similar operations can also be seen at Apple Inc., Caterpillar Inc., and John Deere Corporations (Niranjan, 2017).

Although remanufacturing has many economic benefits, cannibalization between remanufactured and new products constitutes a significant concern for manufacturers. As a lower-priced substitution, the purchase of a remanufactured product potentially cannibalizes the sales of a new product, and may reduce the profit of the manufacturer (Yenipazarli, 2016). Therefore, it is important for manufacturers to carefully design their production and sale strategies when both types of products are manufactured.

The convenience of online transaction and efficient delivery service attract customers to shopping in online stores. In 2019, retailing e-commerce sales were more than 3.5 trillion US dollars and was forecasted to be around 7 trillion by 2022 (Clement, 2019). This huge market has motivated manufacturers to develop direct online channels to meet more segments of customers (Radhi and Zhang, 2018), to save channel-developing cost and to obtain the latest market information Yang et al. (2018). Many companies such as Dell, Apple, and Sony sell their products through their online platforms (Giri et al., 2017). For example, Apple and Philips sell only new products in their retailer channels and both remanufactured and new products through their websites (online channels) (Yang et al., 2019, Borenich et al., 2020). However, the introduction of the new channel can cause conflict between the traditional and new channels, which is a negative effect and can decrease profits of all members of the SC (Giri et al., 2017).

To mitigate the channel conflict and cannibalization from the remanufactured product, it is necessary for the manufacturer to employ the appropriate price strategies for the products sold through different channels. Chiang et al. (2003) show that the retailer can benefit from the manufacturer’s direct channel due to the decrease in the wholesale price and the increase in the volume of sales. Fruchter and Tapiero (2005) find that a manufacturer should set the same product prices in both channels. Dan et al. (2012) demonstrate that the optimal pricing strategies of all members in the SC are influenced by the retailer’s service quality, while Huang et al. (2012) show that the customer’s preference for the online channel is a key factor in deciding the optimal prices.

An extensive literature review reveals that the optimal pricing and production strategies for the competing remanufactured and new products sold in the competing retail and online channels in a SC have not been fully investigated. Most papers in the literature, such as Gan et al. (2017) and He et al. (2019), only focus on the competition between new and remanufactured products in separate channels (cross-channel product competition). But in the common market, a double competition between new and remanufactured products within channels (intrachannel competition) and across competing channels (crosschannel competition) takes place simultaneously. For example, Apple Inc. sells new products in both the offline and online channels and the remanufactured products in its online channel also (https://www.apple.com/ca/). A similar case is also observed for Lenovo Inc.(https://www.lenovo.com/ca) and Samsung Inc. (https://www.samsung.com/us), who sell both their new and remanufactured products through the online channel. Moreover, the channel selling costs are ignored in most papers in the literature such as Gan et al., 2017, Batarfi et al., 2017, He et al., 2019. However, channel costs are essential parameters to differentiate the online and the retail channel on the cost aspect. Thus, the impact of these costs on the manufacturer’s optimal pricing and production strategy, and the retailer’s pricing decisions should be investigated. To fill the above research gaps, the proposed model investigates the optimal pricing and production strategies for a manufacturer selling its new product through a retailer and its direct online channel, and may sell remanufactured products through its online channel, with consideration given to both the production costs and the channel selling costs. The following questions are addressed in this paper.

  • What pricing and production strategies should the manufacturer and retailer implement in the cases with and without remanufacturing?

  • Under what conditions should the manufacturer carry out remanufacturing?

  • How does the manufacturer’s remanufacturing decision affect the retailer’s retail price, demand, and profit?

  • How will the customer’s acceptance levels for the remanufactured product and the online channel, the production and channel costs, and the proportion of high-quality returns impact the manufacturer’s optimal pricing and production strategy, and the retailer’s pricing strategy?

To answer these questions, a two-period model is developed to determine the optimal pricing and production strategies for both remanufactured and new products. It is shown that optimal pricing decisions of the manufacturer and the retailer, and the optimal production strategy of the manufacturer depend on both the channel selling cost and production cost of the new product. Numerical experiments are carried out to provide additional insights by testing the impact of the customer’s acceptance level of the remanufactured product, the customer’s acceptance level of the online channel, and the proportion of high-quality returns on the optimal decisions of the manufacturer and the retailer.

Our research indicates that there are key thresholds for the unit manufacturing cost of the new product and the retail channel cost, respectively. The manufacturer is not willing to engage in remanufacturing if the unit manufacturing cost for the new product is lower than a certain threshold. Moreover, the retailer’s channel selling cost does not affect the manufacturer’s remanufacturing decision when there are sufficient returns. When there are not enough returns, the manufacturer engages in remanufacturing if the retail channel cost is higher than a certain threshold. Furthermore, the retailer suffers a profit loss due to the introduction of the remanufactured products only when the manufacturer needs to use all returns for remanufacturing. The sensitivity analysis also shows that the customer’s acceptance level for the remanufactured product has no impact on the retailer’s profit when this acceptance level is lower than a threshold and the increase in the proportion of high-quality returns leads to an increase in the manufacturer’s profit and a decrease in the retailer’s profit when the manufacturer uses all returns for remanufacturing. The values of these key thresholds are determined and presented along with the optimal pricing and production strategies.

This paper’s contribution to the literature is two-fold. Firstly, the optimal pricing and production strategies are explored for a SC in which remanufactured and new products are sold in a dual-channel by considering not only the channel competition (retail versus online), but also the product cannibalization/competition between the remanufactured and new products that are sold in the same channels and across channels. Hence, a two-fold product competition is considered: intrachannel and crosschannel. Secondly, our model differentiates not only the online channel and retail channel from the customer’s perspective by considering a discounted perceived value on the products sold in the online channel, but also the selling costs for the two channels (different channel operating costs), which is not explored in the literature. Our results show that the channel selling cost is the essential factor affecting the optimal pricing strategies of the manufacturer and the retailer and optimal production strategy of the manufacturer.

The rest of the paper is structured as follows. Section 2 presents the related literature review. In Sections 3 Problem description, 4 Optimal decisions, the two-period model is presented and the optimal pricing strategies of the manufacturer and retailer for the cases with and without remanufacturing are derived. The numerical experiments and the conclusion are presented in Sections 5 Numerical experiments, 6 Conclusion respectively. Proofs are presented in Appendix.

Section snippets

Literature review

In this section, we discuss the literature on the pricing strategy for the remanufactured and new products. Comprehensive reviews of this topic can be found in Kumar and Ramachandran (2016) and Guo et al. (2017). Kumar and Ramachandran (2016) reviews the issues affecting the manufacturer’s pricing decisions, which can be classified into three areas: product issues, SC issues, and formulation issues. Guo et al. (2017) focus on studies of the optimal pricing strategy for the manufacturer under

Problem description

Table 3 presents the notation used in the paper.

A CLSC with a manufacturer and a retailer is considered. The selling horizon is divided into two periods. In the first period, the manufacturer sells the new product only through both its online channel and the retail channel. In the second period, the manufacturer sells the new product through the retail channel and both the remanufactured and new products (Case B) or the new product only (Case N) through its online channel. The two cases, Case N

Optimal decisions

In this section, the optimal pricing strategies are derived for the manufacturer and the retailer in the Stackelberg game for both cases, s={N,B}.

Numerical experiments

In this section, numerical experiments are used to examine the impacts of the customer’s acceptance level for the remanufactured product (α), the customer’s acceptance level for the online channel (β), and the proportion of high-quality returns (δ), on the optimal prices, demands, and profits of the manufacturer and the retailer. The following parameter values are selected: cn=0.07, cp=0.04, q=0.6, ct=0.007, cm=0.008, cmt=0.008, α=0.81, β=0.85, and δ=0.4.

Conclusion

A two-period model for a CLSC with a manufacturer and a retailer to decide the optimal pricing and production strategies for remanufactured and new products is developed. Both competitions between the retailer’s store and the manufacturer’s online channel, and between the remanufactured and new products in the same and different channels are considered in the paper. Demands for both product types sold in the retailer’s and the manufacturer’s channels are derived based on the utility theory. The

CRediT authorship contribution statement

Zhuojun Liu: Conceptualization, Methodology, Software, Formal analysis, Investigation, Writing - original draft, Writing - review & editing. Jing Chen: Conceptualization, Methodology, Writing - review & editing, Supervision, Project administration, Funding acquisition. Claver Diallo: Conceptualization, Methodology, Writing - review & editing, Supervision, Project administration, Funding acquisition. Uday Venkatadri: Writing - review & editing, Supervision.

Acknowledgements

This work was supported by grants awarded by the Canadian Natural Science and Engineering Research Council, Canada to the second, third and fourth authors through the Discovery Grant Program. We also thank the Editors and the anonymous reviewers.

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