Outsourcing decisions in reverse logistics: Sustainable balanced scorecard and graph theoretic approach

Highlights

• Explored outsourcing attributes and alternatives in reverse logistics.

• Developed a sustainable balanced scorecard for the selection of attributes/sub-attributes.

• Proposed a graph theoretic approach to select the best alternative.

• A case of mobile manufacturing firm is discussed for the illustration of the approach.

Abstract

Reverse logistics has become an important issue for most of the organizations due to increased flow of product returns and growing concern for the environment, legislation, and corporate social responsibility. Reverse logistics activities include product collection, inspection and sorting, disposition (reuse, repair, remanufacture or recycle), and redistribution of products. One of the important decisions is whether such activities must be outsourced partly or all must be outsourced or nothing must be outsourced. The articles on the selection of third party reverse logistics service providers are abundant but the articles on outsourcing reverse logistics fully or partly are very limited. The proposed study develops a framework for outsourcing decisions in reverse logistics by using graph theoretic approach. The ability of graph theoretic approach to consider interdependencies and maintaining hierarchical relationship among attributes and sub-attributes makes it an attractive approach. The attributes and sub-attributes were selected by combining four traditional balanced scorecard perspectives i.e. stakeholder, internal business process, learning and growth, and finance with triple bottom line aspects of sustainability known as sustainable balanced scorecard. By considering sustainable balanced scorecard based attributes and sub-attributes, organizations can ensure their contribution toward sustainability even after outsourcing the reverse logistics activities. The proposed framework is illustrated by case example of a mobile manufacturing firm. Scenario based alternatives were developed and “outsourcing index” were calculated for all the alternatives by evaluating permanent function using graph theoretic approach. The best alternative was selected based on the “outsourcing index”. The proposed framework will help managers and practitioners in outsourcing reverse logistics decisions.

Introduction

The customer may return the products because of many known or unknown reasons such as defects or damages, or customer dissatisfaction (Barsky and Ellinger, 2001). Product returns are uncertain in terms of quantity, quality, and timing of returns; and they are difficult to manage in comparison to new products in forward logistics (Rogers and Tibben-Lembke, 1999). When worn out or obsolete products are remanufactured, “it's not uncommon for companies to realize higher margins on these remanufactured products than they do on new items” (Stock et al., 2002). Still, product returns are eminent in a competitive business environment and firms need to manage those returns effectively. One of the effective ways of dealing product returns efficiently is to adoption of reverse logistics system. Firms realized that the reverse logistics has a potential for being market differentiator through corporate social image and better customer satisfaction (Stock et al., 2002, Stock et al., 2006).

In Reverse logistics, the used or returned products are collected after their acquisition and inspected for sorting into the different categories. The next step is to disposition them for repair, remanufacturing, recycling, reuse or final disposal. Manufacturers may adopt reverse logistics by choice or by force but they have to decide whether performing the activities themselves or outsourcing to a third party (Martin et al., 2010). Kannan et al. (2012) observed that reverse logistics outsourcing may reduce costs as the third party can get the advantage of the economies of scale. Also, by outsourcing reverse logistics, firms can reduce their asset base, and deploy the capital released for other productive usage. Other advantages include low costs, less uncertainty, lower capital investment, more focussed on core competency, more flexibility, better customer responsiveness, and better excess to new technology (Kumari et al., 2015). However, some firms realized unexpected higher costs because of complexity, lack of flexibility, and other hidden problems with outsourced service providers (Tadelis, 2007). Therefore, it is important to make systematic analysis from various business perspectives before taking outsourcing decisions. In a literature review, Agrawal et al. (2015) emphasized on the need of developing a comprehensive decision making framework with respect to completely or partly outsourcing the reverse logistics activities.

Traditionally, organizations have considered the economic criteria like cost, investment, economies of scale; processing parameters like flexibility, capacity, capability; resource capacity; quality of service, core competency and other strategic, operational and tactical parameters for the outsourcing decisions. Although the concept of balanced scorecard (BSC) has been primarily designed for the measurement of the system performance, Authors have frequently utilized BSC perspectives as criteria for the selection of best outsourcing alternatives (Tjader et al., 2014, Ravi et al., 2005, Shaik and Kader, 2012). Merits of the BSC approach are to integrate strategic, operational, and financial attributes to consider the balanced key perspectives of the decision making. BSC approach allows managers to look at the business from four divergent important perspectives: customer, internal business, innovation and learning, and finance (Kaplan and Norton, 1992). However, this approach does not consider the important sustainable development of the organizations such as triple bottom line aspects of sustainability. Triple bottom line aspects include economic, environment, and social dimensions of the sustainability. It has been utilized by researchers for identification of criteria for various outsourcing decision making (Huang et al., 2012, Tuzkaya et al., 2009, Lu et al., 2007). However, it does not provide the holistic view of an organization. In order to have advantages of both the approaches, triple bottom line aspects of sustainability have been combined with BSC (known as sustainable balanced scorecard (SBSC)) for selecting the attributes and sub-attributes for the proposed study.

The proposed research is focused on exploring the various alternatives of outsourcing reverse logistics activities fully or partly and developing a decision making approach for selecting best alternative. Various multi criteria approaches including TOPSIS, AHP, ANP, and DEA, are available for such type problems. TOPSIS and AHP can be used if the attributes are independent, which is not the case with proposed problem. While ANP does not represent hierarchical relationship among attributes, DEA requires more computation and may be a poor discriminator of good and poor performers if the numbers of attributes are large (Rao and Padmanabhan, 2006). Graph Theory Approach (GTA) does not have such limitations. Therefore, GTA has been utilized for the selection of best outsourcing reverse logistic alternative based on “Outsourcing Index”. “Outsourcing Index” is the value of permanent function obtained through GTA for different alternatives. This study makes significant contribution to the very few available studies and also, the GTA is first time being used for such type of problem.

The remainder of the paper is organized as follows: Section 2 comprises a literature review on reverse logistics, outsourcing, and on SBSC. In Section 3, research methodology including GTA and step by step approach has been discussed for evaluation of “Outsourcing Index” for various alternatives. Subsequently, the proposed approach is validated through a case illustration of a mobile manufacturing firm in section 4. Results are also presented and discussed in section 4. Section 5 summarizes all the findings and concludes the study. Managerial implications along with future scope of the study are discussed in Section 6.