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Capturing value from decentralized supply chain with third party reverse logistics

Tanai, Yertai
http://orcid.org/0000-0002-0431-9137
http://rave.ohiolink.edu/etdc/view?acc_num=kent1478815289859572

Abstract Details

2016, PHD, Kent State University, College of Business and Entrepreneurship, Ambassador Crawford / Department of Management and Information Systems.
As competition in the global market continues to grow and customers are becoming more environmentally as well as cost conscious, recent trends in retail practices attest to the attention and resources devoted to the returns in supply chains. Topping the list is the economic incentive to reap as much value as possible from returns. With the growth of an internet consumer base, vigorous competition and the advance of online sales regardless of product type, size and locations, many firms provide generous return policies. This has caused a significant increase in the volume of reverse flows and therefore great potential for value recovery from returns. According to the National Retail Federation, the value of merchandise returned amounted to $260.5 billion in 2015. Hence, ways of improving the performance of a supply chain through effectively and efficiently closing the loop have received considerable attention both from academic researchers and industry practitioners over the past two decades. One way to recoup returns value as quickly as possible is to decentralize reverse logistics functions to third party reverse logistics providers (3PRLP). Outsourcing to a 3PRLP allows a firm to gain a state-of-the-art reverse logistics program immediately thereby avoiding the capital investment and start up delay required to implement an in-house RL program. This dissertation proposes two models of a Closed-Loop Supply Chain (CLSC) with independent 3PRLP for returns processing. The first model presents a CLSC where demand is generated by a stochastic process. A fraction of the units that are initially sold are returned by the consumers for a full refund in every period. We model the forward flow interaction between the supplier, the retailer and 3PRLP by a widely accepted control policy that is lot size-reorder point inventory policy, which is detailed by the Markov process. We further propose a queuing network to capture reverse flow activities of the 3PRLP, which consists of customer decision delay and each of the 3PRLP activities. We characterize the expected profits for both firms and derive the effects of key parameters through set of numerical examples. The results of optimization based on numerical examples indicate that both firms' benefits from processing returns increase with an increasing returns rate. This is due to fact that the retailer captures more profits through selling processed returns at the price of new product. The 3PRLP unambiguously earns more profit from increasing product returns since the fee from processing returns is sole source of revenue. Furthermore, the directions of effects of changes in the holding cost are similar for both the retailer and 3PRLP. However, the magnitude of effects of the same parameter are quite opposite. Interestingly, the retailer’s profit appears to be more sensitive to the holding cost than that of the 3PRLP’s profit. The second model analyzes coordination issues between a retailer and a 3PRLP to manage product returns. We formulate the returns processing capacity of a 3PRLP as a two-input production function where there is only one variable input. Crucially, this implies that the 3PRLP's short run marginal cost is strictly increasing. This key feature of the 3PRLP's short run cost function motivates two supply chain interaction scenarios. In an uncoordinated supply chain, the retailer acts as a market leader who makes a take-it-or-leave-it fee and quantity of returns offers to the 3PRLP. With increasing marginal cost of returns processing and retailer market power, the quantity of returns processed is inefficiently low due to a standard monopsony argument. In a coordinated supply chain, the retailer and the 3PRLP jointly decide on the returns quantity to be processed in order to maximize the total profit for the supply chain. An appealing approach to model how the benefit to coordination is shared between the two firms is Nash bargaining. Accordingly, we characterize the Nash bargaining solution with asymmetric bargaining powers, assuming that the disagreement payoffs are given by the uncoordinated supply chain profit levels. The underlying model is one where the retailer and the 3PRLP negotiate the quantity of returns and the per unit fee, while both recognize that if they fail to reach an agreement, the retailer is poised to make a unilateral offer as in the uncoordinated case.
Alfred Guiffrida (Committee Chair)
Butje Eddy Patuwo (Committee Co-Chair)
Emmanuel Dechenaux (Committee Member)
90 p.
Business Administration
Closed-loop supply chain; third party reverse logistics providers; supply chain coordination; consumer returns; Nash bargaining

Recommended Citations

Citations

  • Tanai, Y. (2016). Capturing value from decentralized supply chain with third party reverse logistics [Doctoral dissertation, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1478815289859572

    APA Style (7th edition)

  • Tanai, Yertai. Capturing value from decentralized supply chain with third party reverse logistics. 2016. Kent State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1478815289859572.

    MLA Style (8th edition)

  • Tanai, Yertai. "Capturing value from decentralized supply chain with third party reverse logistics." Doctoral dissertation, Kent State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=kent1478815289859572

    Chicago Manual of Style (17th edition)

kent1478815289859572
712
© 2016, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.