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Manuscript ID : 537154 Visit : 164 Page: 57 - 72

Article Type: Original Research

Outsourcing Reverse Logistics: Evaluating Strategic Decision Factors using Novel Combined SWOT and Grey AHP Approach

Subject Areas : Industrial Management

Mohsen Zareinejad 1

1 - Young Researchers and Elite club, Islamic Azad University Shiraz branch. Department of Industrial Engineering, Tehran North branch, Islamic Azad University, Tehran

Received: 2015-11-02 Accepted : 2016-08-18 Published : 2016-08-25

Keywords:

Abstract :

According to the increasing importance of competitive advantages in recent years, the importance of reverse logistics has doubled. Because of the complexity of reverse logistics system (RL) and also focus on the core business, then the organizations are acted to RL outsource. Therefore, the mistake in the assessment of the most important factors in RL decision leads to failure of RL outsources. The present study was paid to identify and evaluate the most important factors of reverse logistics outsourcing strategic in Dena industry manufacturing company in 2013. In this research, the analysis of strengths, weaknesses, opportunities, and threats (SWOT) was used to identify strategic factors of RL outsourcing. On the other hand, in order to measure the important qualitative factors SWOT analysis was applied of the developed grey analytical hierarchy process (GAHP). However, application of grey data in the assessment of linguistic variables, in fact, was a way to deal with uncertainty. The model validate was examined in a case study which was indicated the high reliability of the hybrid model. The results showed that in terms of decision-makers’ point of view, risk sharing in RL outsourcing decision was much more important than cost reduction factor.

References:


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  33. Park J.,Kim J. (2005). The impact of IS sourcing type on service quality and maintenance efforts”, Information & Management, 42(2), 261-274.
    34.
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  50. Xia, D., Chen, B., (2011). A comprehensive decision-making model for risk management of supply chain. Expert Systems with Applications, 38, 4957–4966.
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  52. Zahedi, F. (1986). The analytic hierarchy process - A survey of the method and its applications. Interfaces, 16 (4), 96-108.
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_||_

  1. Andersson, D. and Norrman, A. (2002). Procurement of logistics services a minutes work or a multi year project, European Journal of Purchasing and Supply Management, 8 (3), 14.
    2.
  2. Arianejad, M., Malek, A. M., Dabaghi, A., Alizade, A. (2008). Provide a technique to performance evaluation of the strategic plans. 4th International conference on Strategic Management. Tehran, 2008.
    3.
  3. Bahli, B., Rivard.S, (2005). Validating measures of information technology outsourcing risk factor. Omega, 33(2), 175-187.
    4.
  4. Bailey W., Masson R., Raeside R. (2002). Outsourcing in Edinburgh and the Lothians. European Journal of Purchasing & Supply Management, 8, 83-95.
    5.
  5. Boer, L., Gaytan, J. and Arroyo, P. (2006). A satisficing model of outsourcing’’, Supply Chain Management: An International Journal, 11(5), 444-55.
    6.
  6. Daugherty, P. J., Autry, C. W., & Ellinger, A. E. (2001). Reverse logistics: The relationship between resource commitment and program performance. Journal of Business Logistics, 22(1), 107– 123.
    7.
  7. Deng, J. L. (1982). Control problems of Grey Systems. Systems and Control Letters 5(2), 288-294.
    8.
  8. Gay, C., & Essinger, J. (2000). Inside outsourcing. Naperville, IL: Nicholas Brealey.
    9.
  9. Gilley, K. M., & Rasheed, A. (2000). Making more by doing less: an analysis of outsourcing and its effects on firm performance. Journal of management,26 (4), 763-790.
    10.
  10. Görener, A., Toker, K.,  Uluçay, K., (2012). Application of Combined SWOT and AHP: A Case Study for a Manufacturing Firm. 8th International Strategic Management Conference,Procedia - Social and Behavioral Sciences58 (12), 1525–1534.
    11.
  11. Gunasekaran, A., Patel, C. and Tirtiroglu, E. (2001), ‘‘Performance measures and metrics in a supply chain environment’’, International Journal of Operations & Production Management,. 21 (1/2), 71-87.
    12.
  12. Helms, M. M., & Nixon, J. (2010). Exploring SWOT analysis–where are we now? A review of academic research from the last decade. Journal of Strategy and Management, 3(3), 215-251.
    13.
  13. Hendrik, J., Matthias, Z., Marco, F. and Joachim, K. (2006). Performance evaluation as an influence factor for the determination of profit shares of competence cells in nonhierarchical regional production networks’’, Robotics and Computer-Integrated Manufacturing,. 22, 526-535.
    14.
  14. Ho, W., Emrouznejad, A., He, T., Man Lee, C. K., (2012). Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach. Expert Systems with Applications, 39(12), 10841–10850.
    15.
  15. Huang, Z. Y.,  Zhao, Q. L. (2012). A Study on the Selection of Logistics Outsourcing Service Provider Based on Analytical Hierarchy Process. Advanced Materials Research, 479-481, 76-80.
    16.
  16. IDG, Retrieved from http://www.kennedyinfo.com.
    17.
  17. Kannan, G., Palaniappan, M., Zhu, Q., Kannan, D. (2011). Analysis of third party reverse logistics provider using interpretive structural modeling. International Journal of Production Economics, 140. 204-211.
    18.
  18. Kannan, G., Shaligram, P., Sasikumar, P. (2009). A hybrid approach using ISM and Fuzzy TOPSIS for the selection of reverse logistics provider. Resources, Conservation and Recycling 54, 28–36
    19.
  19. King, A. M., Burgess, S. C., Ijomah, W., & McMahon, C. A. (2006). Reducing waste: repair, recondition, remanufacture or recycle? Sustainable Development, 14 (4), 257–267.
    20.
  20. Kumar, A., Bhatia, N., and Kaur, M. (2009). A new approach for solving fuzzy maximal flow problems. “Lecture Notes in Computer Science”. Springer-Verlag; Berlin, Heidelberg, 5908: 278-286.
    21.
  21. Kwang, J.K., Jeong, I.J., Park, J.C., Park, Y.J., Kim, C.G. and Kim, T.H. (2007), ‘‘The impact of network service performance on customer satisfaction and loyalty: high-speed internet service case in Korea’’, Expert Systems with Applications. 32, 822-31.
    22.
  22. Lacity, M. C., & Willcocks, L. (2000). Global information technology outsourcing: In search of business advantage. John Wiley & Sons, Inc.
    23.
  23. Langley, C.J., Allen, O.R. and Tyndall, O.R. (2002). Third Party Logistics Study 2002: Results and Findings of the Seventh Annual Study, Council of Logistics Management, Chicago, IL.
    24.
  24. Lee, S. (2010). Global outsourcing: A different approach to an understanding of sport labor migration. Global Business Review, 11, 153–165.
    25.
  25. Lee, S., & Walsh, P. (2011). SWOT and AHP hybrid model for sport marketing outsourcing using a case of intercollegiate sport. Sport Management Review, 14(4), 361-369.
    26.
  26. Levery, M. (2005). Motivating maintenance craftsmen–do we know what we’re doing?. IEE’s Engineering Management magazine, 1-21.
    27.
  27. Li, M., & Burden, W. (2005). Institutional control, perceived product attractiveness, and other related variables in affecting athletic administrations’ outsourcing decisions. International Journal of Sport Management, 5, 1–11.
    28.
  28. Lin,  Y. H., &  lee ,  P. C ., &  Ting , H. I. (2008).  dynamic  multi – attribute  decision  making  model  with  grey  number  evaluation.  Expert systems with application. 35 (4) ,  1638 – 1644 
    29.
  29. Meade, L., Joseph Sarkis. (2002). A conceptual model for selecting and evaluating third-party reverse logistics providers", Supply Chain Management: An International Journal, 7 (5), 283 – 295.
    30.
  30. Moore, R., E., (1996). Interval  analysis, Pentic – hall , Engle wood cliffs,  NJ, 8 – 13. 
    31.
  31. Ordoobadi, S. M., (2009). Outsourcing reverse logistics and remanufacturing functions: a conceptual strategic model", Management Research News, 32(9), 831 – 845.
    32.
  32. Pagell, M., Wu, Zh. and Nagesh, N.M. (2007). The supply chain implications of recycling’’, Business Horizon. 50, 133-43.
    33.
  33. Park J.,Kim J. (2005). The impact of IS sourcing type on service quality and maintenance efforts”, Information & Management, 42(2), 261-274.
    34.
  34. Peng, J., (2012). Selection of Logistics Outsourcing Service Suppliers Based on AHP. International Conference on Future Electrical Power and Energy System 2012, Energy Procedia 17(A), 595–601.
    35.
  35. Ravi, V., Shankar, R.M., Tiwari, K. (2005). Productivity improvement of a computer hardware supply chain. International Journal of Productivity and Performance Management 54 (4), 239–255.
    36.
  36. Reza, K., & Vassilis, S. M. (1988). Delphi hierarchy process (DHP): A methodology for priority setting derived from the delphi method and analytical hierarchy process. European Journal of Operational Research, 137, 347–354
    37.
  37. Rogers, D. S., & Tibben-Lembke, R. S. (1998). Going Backwards: Reverse Logistics Trends and Practices. University of Nevada, Reno, Center for Logistics Management.
    38.
  38. S. Senthil, B. Srirangacharyulu, A. Ramesh. (2014). A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics. Expert Systems with Applications 41, 50–58
    39.
  39. Saaty, T. (1980). The analytic hierarchy process, New York, McGraw-Hill.
    40.
  40. Saaty, T. (2005). Theory and applications of the analytic network process: Decision making with Benefits, Opportunities, Costs, and Risks, RWS publications.
    41.
  41. Saaty, T. (2010). Principia Mathematica Decernendi: Mathematical principles of decisionmaking, RWS publications Pittsburgh, PA, USA.
    42.
  42. Sahay, B.S. and Mohan, R. (2006). APL: an Indian perspective. International Journal of Physical Distribution & Logistics Management, 36(9),66-89.
    43.
  43. Scott, J. A., Ho, W.,  Dey, P. K., (2013). Strategic sourcing in the UK bioenergy industry. International Journal of Production Economics, 1 February 2013.
    44.
  44. Scott, W. (1995). Institutions and organizations. CA: Thousands Oaks.
    45.
  45. Senthil, S., Srirangacharyulu, B., & Ramesh, A. (2014). A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics. Expert Systems with Applications, 41(1), 50-58.
    46.
  46. Shrestha, A., Alavalapati, J., & Kalmbacher, R. (2004). Exploring the potential for silvopasture adoption in south-central Florida: An application of SWOT–AHP method. Agricultural Systems, 81, 185–199.
    47.
  47. Tavana, M., Zareinejad, M., Santos-Arteaga, F. J., & Kaviani, M. A. (2016). A conceptual analytic network model for evaluating and selecting third-party reverse logistics providers. The International Journal of Advanced Manufacturing Technology, 1-17. DOI: 10.1007/s00170-015-8208-6
    48.
  48. Third Party Logistics Providers Liability Risks, Retrieved from http://usa.marsh.com/NewsInsights/ThoughtLeadership/Articles/ID/670/Third-Party-Logistics-Providers-Liability-Risks.aspx, 02-Apr- 2007
    49.
  49. Van der Meer-Kooistra, J., & Vosselman, E. G. (2000). Management control of interfirm transactional relationships: the case of industrial renovation and maintenance. Accounting, organizations and society, 25(1), 51-77.
    50.
  50. Xia, D., Chen, B., (2011). A comprehensive decision-making model for risk management of supply chain. Expert Systems with Applications, 38, 4957–4966.
    51.
  51. Zareinejad, M., Javanmard, H. (2013). Evaluation and selection of a third-party reverse logistics provider using ANP and IFG-MCDM methodology. Life Sci J;10(6s):350-355.
    52.
  52. Zahedi, F. (1986). The analytic hierarchy process - A survey of the method and its applications. Interfaces, 16 (4), 96-108.
    53.

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