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Original Articles

Issues in reverse supply chain, part III: classification and simple analysis

P. Sasikumar Department of Production Engineering, National Institute of Technology, Tiruchirappalli, India

G. Kannan Operations and Supply Chain Management, Department of Business and Economics, University of Southern Denmark, DenmarkCorrespondence[email protected]

Abstract

Due to growing environmental concern and increasing awareness among customers, reverse supply chain (RSC) has received much attention among researchers and practitioners. Therefore it is necessary to provide a comprehensive list of references for other researchers (or readers), who are interested in RSC research to help stimulate further interest. In this paper, we present classification schemes and a simple analysis for the reverse supply chain. This literature review was mainly based on journal articles but also included web based documents, conference materials, working papers, etc. A total of 543 articles were reviewed, of which 506 were published between 1967 and 2008 from 100 reputed international journals. Based on the literature review carried out and the nature of research observed in RSC, we have introduced two classification schemes to systematically organise the published articles. The first classification scheme is based on the content related issues on RSC and the second one is based on the solution methodology followed by the researchers. These classification schemes indicate that there is considerable research potential for RSC. The results also show that there is strong growth in RSC research.

Keywords:

1. Introduction

Reverse supply chain has received considerable attention from researchers and practitioners due to the potential for value recovery from used products. Research on RSC has been growing since the 1960s. In view of this growing interest the existing literature on RSC, published in various scientific journals and conference proceedings, was analysed and a classification was made based on the content issues. Figure provides a framework for the classification scheme based on the content related issues. In addition, the tools and techniques used in the RSC field are mapped along with content classification. Reverse logistics is practiced in many industries like automobiles, aircraft, steel industry, electronic industry, pharmaceuticals, tyre industry, chemical industry, paper industry, electrical and home appliances, etc.

The specific objectives of this paper are:

to suggest a classification of available literature on the basis of content‐related issues;
to identify different solution methodologies used in the RSC context;
mapping of tools and techniques related to content classification;
based on the above, to suggest future directions for researchers who are interested in mathematical modelling and decision‐making in this field.

The paper is organised as follows: after a brief introduction, the details of the research methodology are presented in Section 2. In Section 3, the existing literature has been classified in to a number of areas and sub‐areas based on reverse logistics issues. Mapping of tools and techniques, along with the content classification, is presented in Section 4. Finally, Section 5 closes the paper by offering conclusions and some suggestions for future research.

Objectives and format

This paper is the third and final of three reviews by the authors that consider issues in reverse supply chain management. In addition to the environmental regulation, product recovery and inventory management issues of Part I and reverse distribution issues of Part II, a simple analysis and classification of reverse supply chains are addressed in the present paper. The specific objectives of this paper are: (1) to suggest a classification on the basis of content related issues in reverse supply chain; (2) to identify the different solution methodologies used in a reverse supply chain context; (3) to map the tools and techniques used with content classification; (4) to suggest future directions for those researchers who are interested in mathematical modelling and decision‐making in this field. The paper is organised as follows: after a brief introduction, the details of the research methodology are presented in Section 2. In Section 3, the existing literature has been classified based on content issues in RSC. Mapping of tools and techniques along with the content classification are presented in Section 4. Finally, Section 5 closes the paper by offering conclusions and some suggestions for future research.

2. Research methodology

We believe that academics and practitioners equally use published articles most often for acquiring additional knowledge and disseminating new findings that contribute at the highest level of research. A literature survey of 543 articles published in various international journals, conference proceedings and working papers up to 2008 was employed as the research methodology. During the period: 1967 to 2008, 506 articles on RSC appeared in 100 international journals and the remaining 37 articles were from various conference proceedings and working papers submitted to the journal category. This study may suggest/bring to light some unexplored research problems for future researchers in this field. The literature search was based on the following descriptors: ‘reverse logistics’, ‘closed loop supply chain’, ‘green supply chain management’, ‘end‐of‐life product recovery’, ‘recycling’, ‘remanufacturing’, ‘reuse’, ‘waste management’, and ‘multi‐criteria decision‐making in reverse logistics’. Here, our aim is to consolidate the available literature on RSC and to present a classification based on the problem‐related issues. In addition to classifying the literature on RSC, the tools and techniques used to model and analyse various RSC activities are also presented. This will be useful to those researchers who are interested in modelling and analysis in this field. As we stated earlier, our aim was to analyse those articles that directly related to RSC. By keeping this in mind, we carried out a literature review and Table shows the distribution of articles in the various journals from 1967 to 2008. Since many authors (Flesichmann et al. Citation1997, Moyer and Gupta Citation1997, Carter and Ellram Citation1998, Gungor and Gupta Citation1999, Guide et al. Citation1999a, Dowlatshahi Citation2000, Fleischmann et al. Citation2000, Guide Citation2000, Guide et al. Citation2000b) presented the literature review articles on RSC prior to the year of 2000, we consider the period 1990 to 2000 as a single group.

Table 1. Distribution of articles by journal in the period 1967–2007 (30 articles in the year 2008).

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From Table , it is can be seen that there is a proliferation of papers published during 2007 and 2008 and this reflects the growth in new RSC‐related research. Table also shows that the primary publication outlets for RSC research are International Journal of Production Research; International Journal of Production Economics; European Journal of Operational Research; Computers & Industrial Engineering; International Journal of Physical Distribution & Logistics Management; Computers & Operations Research; Omega; Resources, Conservation and Recycling; Journal of Cleaner Production; Interfaces; OR Spectrum; Journal of Operations Management; Journal of the Operational Research Society; California Management Review; collectively publishing about 65.29% of the total articles. The large number of articles in the International Journal of Production Economics is partially the result of the publication of a special issue on Sustainable Supply Chain management in the year 2008, an event in itself indicative of the growing relevance of the topic in RSC research.

3. Classification based on reverse logistics issues

The literature available on RSC is reviewed here with a focus on environmental impact, product recovery, reverse distribution, inventory management and waste management issues. Outcome of the literature survey: a total of 543 papers published in various international journals, conference proceedings and working papers were collected and analysed. In this paper, the literature on RSC is classified into 10 categories: (A) Impact of environmental regulation; (B) Product recovery; (C) Common issues in product recovery; (D) Reverse distribution; (E) Inventory management; (F) Waste management; (G) Role of information technology; (H) Decision‐making models; (I) Literature review articles; and (J) General category. The details of the major classification scheme and the articles that come under each such classification are presented in Table . It can be seen that some articles may be presented in more than one classification. For examples, Ko and Evans (Citation2007) and Du and Evans (Citation2008) addressed the issues of both closed loop supply chain and third party logistics. Consequently, these articles are referred under both the closed loop supply chain and the third party reverse logistics classification. Many authors (Del Castillo and Cochran Citation1996, Barros et al. Citation1998, Boon et al. Citation2002, Kannan et al. Citation2009) have reported case studies on reverse logistics. Table summarises the products that have been taken back to perform the reverse logistics operations.

Table 2. Summary of references under the content classification and sub‐classification scheme of the literature.

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Table 3. Summary of references under product categories.

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4. Mapping of tools and techniques used

Rubio et al. (Citation2008) grouped the articles according to the topics of: management of the recovery and distribution of end‐of‐life products; production planning and inventory management; and supply chain management issues in reverse logistics. They also considered the methodologies of: case study; literature review; mathematical model; survey; and wholly theoretical for each classification to examine the correspondences between the topic and the methodology. The solution methodologies proposed in various RSC papers (Figure ) could be broadly grouped into mathematical programming method, heuristic method, simulation method, or multi‐criteria decision‐making (MCDM) method. Under the mathematical programming group, linear; non‐linear; integer and mixed integer programming models are widely used by researchers (Table ). The mathematical programming approach guarantees global convergence as long as problems are small. According to the general classification on heuristic methods, the review carried out on RSC research led us to classify the solution methodologies being followed so far in this research into: (1) simple (constructive) heuristic; (2) meta‐heuristic; and (3) artificial intelligence. Analytic hierarchy process (AHP) and fuzzy AHP are used as multi‐criteria decision‐making tools in most of the cases for the selection and analysis of reverse logistics providers. Here, our aim is to map the tools and techniques identified (Table ) with the classification based on the content issues.

Table 4. Mapping of tools and techniques used with content classification.

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5. Conclusion

In this paper, we have attempted to review and classify the content issues and solution methodologies used in RSC. Accordingly, an extensive literature review was conducted to review RSC research from various journals and web‐based articles that are possible outlets for this research. This resulted in identification of 543 articles related to RSC research, published between 1967 and 2008. Finally, we acknowledge that this review cannot be claimed to be exhaustive, but it does provide reasonable insights into the state‐of‐the‐art on RSC research. Thus, it is hoped that, this review will provide a source of reference for other researchers/readers interested toward RSC research, and help stimulate further interest. On the basis of this review, the following conclusions and recommendations are presented:

	From Table , it can be seen that a majority of case studies have dealt with electronic equipment, especially computers. However, there are still research opportunities for home appliances, information technology and the health care domain.
	All the multi‐objective programming models mentioned in Table are bi‐objective only. So, there is research scope for considering more than two objectives.
	From Table , it can be observed that Lieckens and Vandaele (Citation2007) have only used differential evolution algorithm for problem solving and no one has used non‐dominated sorting genetic algorithm (NSGA) in the reverse logistics field. In future, researchers can make use of these meta‐heuristics as a problem solving tool depending upon their own problem.
	Little work has been conducted in the context of information technology. Future researchers could make use of IT as a strategic tool for sharing the information in reverse logistics.
	From Table , it can be seen that there is a research potential to make use of VIKOR, PROMETHEE, ELECTRE, TOPSIS, SAW, etc., as multi‐criteria decision‐making tools for the analysis and selection of reverse logistics providers.
	Under the mathematical programming approach, only a few authors (Korugan and Gupta Citation1998, Toktay et al. Citation2000, Souza and Ketzenberg Citation2002, Lieckens and Vandaele Citation2007) have addressed queuing models.

Figure 1 Classification scheme based on content related issues.

Figure 2 Classification scheme based on solution methodology.

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Issues in reverse supply chain, part III: classification and simple analysis

Abstract

1. Introduction

Objectives and format

2. Research methodology

Table 1. Distribution of articles by journal in the period 1967–2007 (30 articles in the year 2008).

3. Classification based on reverse logistics issues

Table 2. Summary of references under the content classification and sub‐classification scheme of the literature.

Table 3. Summary of references under product categories.

4. Mapping of tools and techniques used

Table 4. Mapping of tools and techniques used with content classification.

5. Conclusion

Related Research Data

References

Information for

Open access

Opportunities

Help and information

Issues in reverse supply chain, part III: classification and simple analysis

Abstract

1. Introduction

Objectives and format

2. Research methodology

Table 1. Distribution of articles by journal in the period 1967–2007 (30 articles in the year 2008).

3. Classification based on reverse logistics issues

Table 2. Summary of references under the content classification and sub‐classification scheme of the literature.

Table 3. Summary of references under product categories.

4. Mapping of tools and techniques used

Table 4. Mapping of tools and techniques used with content classification.

5. Conclusion

Related Research Data

References

Reprints and Corporate Permissions

Academic Permissions

Related research

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