Operational Efficacy of 3PL in Reverse Logistics and Closed Loop Supply Chain: Service Quality Challenges in Emerging Markets

Operational Efficacy of 3PL in Reverse Logistics and Closed Loop Supply Chain: Service Quality Challenges in Emerging Markets

Manu Sharma, Jitendra Kumar
Copyright: © 2016 |Pages: 23
DOI: 10.4018/978-1-4666-9720-1.ch006
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Abstract

The paper presents an empirical research aims to establish service quality relationship between focal firm and 3PL operations and their performance in a reverse logistic and closed loop supply chain particularly in emerging economies like India and China. Seven Constructs has been formulated viz. Outsourcing contract between focal firm – 3PL; Supply Chain Integration; 3PL operational assessment; Service Quality; Return shipping; Lead-time; Reverse logistics cost. Five hypotheses were tested using Confirmatory Factor Analysis (CFA). The results shows the efficacy of reverse logistics determine the customer satisfaction, whereas the degree of supply chain integration between focal firm and 3PL. The research gives broad insight on the 3PL functionality in reverse logistics especially for consumer centric emerging market places.
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1. Introduction

Despite of being in the infant state, Reverse Supply Chain issues in the recent times has received serious attention from both corporate and researchers (Prahinski & Kocabasoglu, 2005; Rogher & Tibben-Lembke, 2001; Daugherty et al., 2001; Guide & Van, 2002; Vachon, Klassen & Johnson, 2001) . Conceptually, it is efficient and cost effective management of series of activities required retrieving a product from a customer, its redesigned and either dispose of it or recover value (Fleschmann et al., 2000; Du & Evas, 2008). Return flows classified into commercial returns, warranty returns, end-of-use returns reusable container returns, Dead On Arrival (DOA), in-transit damage (Du & Evans, 2006). Commercially, There are two major sources of returns:

  • 1.

    Returns from Original Equipment Manufacturers (OEM)’s business customers returns;

  • 2.

    Returns from end-users to retails stores (off line and/or online) (Rogers & Tibben-Lembke, 2001; Dowlatshahi, 2000).

Table 1 shows various Categories of Returns.

Table 1.
Categories of returns
Type of Return% ContributionTechnical Reason
Category A: OEM Business Customers Returns
Overstock Inventories at the end OEM’s Business customersOverall Contribution Accounts for 30-40% of returns (majorly from large retail stores/wholesalers/distributors).Overstock are inaccurate forecasting, fluctuating macro-economic indicators, inefficient Supply Chain Strategies
Order Error due to wrong item selection at the customerscontribute 3-5% of overall returnWrong interpretation about the product due to visual vs. reality
Damaged goodsContribute 3-4% of overall returnIn transit damages/ improper shelving
Order Cancellationcontribute 8-12% of overall returnChange in demand/ requirements
Obsolete and Excessive InventoriesContributes up to 45-55% of total returnsRapid changes in technology and competitive market strategies
Category B: Consumer Returns
True Defects6-15% of returnsCommercially unqualified
Perceived as Defectup to 30% returnsDue to damaged accessories
Variation in Prices3-5% of overall returnLong duration in order placement and order fulfilment
Mismatched expectations5-8% of returnsOverstated features and benefits in the advertisements, leads to fall short of customer’s expectation. The Higher the price of product, higher the return rate will be.
Missing parts of componentsUpton 3-4%Lack of quality packaging norms
Wrong size/Model/ PartsUpton 2-3.5%Procedural fault at Warehouse or Distribution Centre (DC)
Impulse Buying or Buyer ResponseUpton 2-3.5%Wrong forecasting
Recall and Warranty ReturnsUpton 4-5%Lacks of availability of forecasted information.

(Adopted from Lee & Lund, 2003).

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