IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v145y2006i1p35-4910.1007-s10479-006-0026-7.html
   My bibliography  Save this article

DEA models for supply chain efficiency evaluation

Author

Listed:
  • Liang Liang
  • Feng Yang
  • Wade Cook
  • Joe Zhu

Abstract

An appropriate performance measurement system is an important requirement for the effective management of a supply chain. Two hurdles are present in measuring the performance of a supply chain and its members. One is the existence of multiple measures that characterize the performance of chain members, and for which data must be acquired; the other is the existence of conflicts between the members of the chain with respect to specific measures. Conventional data envelopment analysis (DEA) cannot be employed directly to measure the performance of supply chain and its members, because of the existence of the intermediate measures connecting the supply chain members. In this paper it is shown that a supply chain can be deemed as efficient while its members may be inefficient in DEA-terms. The current study develops several DEA-based approaches for characterizing and measuring supply chain efficiency when intermediate measures are incorporated into the performance evaluation. The models are illustrated in a seller-buyer supply chain context, when the relationship between the seller and buyer is treated first as one of leader-follower, and second as one that is cooperative. In the leader-follower structure, the leader is first evaluated, and then the follower is evaluated using information related to the leader's efficiency. In the cooperative structure, the joint efficiency which is modelled as the average of the seller's and buyer's efficiency scores is maximized, and both supply chain members are evaluated simultaneously. Non-linear programming problems are developed to solve these new supply chain efficiency models. It is shown that these DEA-based non-linear programs can be treated as parametric linear programming problems, and best solutions can be obtained via a heuristic technique. The approaches are demonstrated with a numerical example. Copyright Springer Science+Business Media, LLC 2006

Suggested Citation

  • Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
    • Handle: RePEc:spr:annopr:v:145:y:2006:i:1:p:35-49:10.1007/s10479-006-0026-7
    DOI: 10.1007/s10479-006-0026-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-006-0026-7
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-006-0026-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Porter, Michael E, 1974. "Consumer Behavior, Retailer Power and Market Performance in Consumer Goods Industries," The Review of Economics and Statistics, MIT Press, vol. 56(4), pages 419-436, November.
    2. Zhimin Huang, 2000. "Franchising cooperation through chance cross‐constrained games," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(8), pages 669-685, December.
    3. Hau L. Lee & Corey Billington, 1993. "Material Management in Decentralized Supply Chains," Operations Research, INFORMS, vol. 41(5), pages 835-847, October.
    4. Li, Susan X. & Huang, Zhimin & Ashley, Allan, 1996. "Improving buyer-seller system cooperation through inventory control," International Journal of Production Economics, Elsevier, vol. 43(1), pages 37-46, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peretzke, Julia & Sandhaus, Gregor, 2017. "Einsatzpotentiale von Cognitive Computing zur Unterstützung der Entscheidungsfindung im Supply Chain Management," ild Schriftenreihe 53, FOM Hochschule für Oekonomie & Management, Institut für Logistik- & Dienstleistungsmanagement (ild).
    2. Krolikowski, Marcin W. & Adhikari, Hari P. & Malm, James & Sah, Nilesh B., 2017. "Inter-firm linkages and M&A returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 135-146.
    3. Henri Barki & Alain Pinsonneault, 2005. "A Model of Organizational Integration, Implementation Effort, and Performance," Organization Science, INFORMS, vol. 16(2), pages 165-179, April.
    4. Cai, Ya-Jun & Chen, Yue & Siqin, Tana & Choi, Tsan-Ming & Chung, Sai-Ho, 2019. "Pay upfront or pay later? Fixed royal payment in sustainable fashion brand franchising," International Journal of Production Economics, Elsevier, vol. 214(C), pages 95-105.
    5. Valérie Moatti & Pierre Dussauge, 2005. "L’influence du mode de développement sur les avantages liés à la taille : une étude empirique dans le secteur de la grande distribution au niveau mondial," Revue Finance Contrôle Stratégie, revues.org, vol. 8(3), pages 145-176, September.
    6. Chan K. Hahn & Edward A. Duplaga & Janet L. Hartley, 2000. "Supply-Chain Synchronization: Lessons from Hyundai Motor Company," Interfaces, INFORMS, vol. 30(4), pages 32-45, August.
    7. Kevin H. Shang & Jing-Sheng Song, 2006. "A Closed-Form Approximation for Serial Inventory Systems and Its Application to System Design," Manufacturing & Service Operations Management, INFORMS, vol. 8(4), pages 394-406, September.
    8. Feng Yang & Dexiang Wu & Liang Liang & Gongbing Bi & Desheng Wu, 2011. "Supply chain DEA: production possibility set and performance evaluation model," Annals of Operations Research, Springer, vol. 185(1), pages 195-211, May.
    9. Hiroko Nakamura & Shinji Suzuki & Tomobe Hironori & Yuya Kajikawa & Ichiro Sakata, 2011. "Citation lag analysis in supply chain research," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 221-232, May.
    10. Alptekinoglu, Aydin & Tang, Christopher S., 2005. "A model for analyzing multi-channel distribution systems," European Journal of Operational Research, Elsevier, vol. 163(3), pages 802-824, June.
    11. Guissoni, Leandro Angotti & Consoli, Matheus Alberto & Rodrigues, Jonny Mateus, 2013. "Gerenciamento por categorias em pequenos supermercados compensa o esforço?," RAE - Revista de Administração de Empresas, FGV-EAESP Escola de Administração de Empresas de São Paulo (Brazil), vol. 53(6), November.
    12. Perona, Marco & Cigolini, Roberto & Adani, Mattia & Biondi, Roberto & Guzzetti, Stefano & Jenna, Ruggero & Chessa, Mario & Agellara, Stefano, 2001. "The integrated management of logistic chains in the white goods industry. A field research in Italy," International Journal of Production Economics, Elsevier, vol. 69(2), pages 227-238, January.
    13. Peidro, David & Mula, Josefa & Jiménez, Mariano & del Mar Botella, Ma, 2010. "A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment," European Journal of Operational Research, Elsevier, vol. 205(1), pages 65-80, August.
    14. Zhu, Minghao & Yeung, Andy C.L. & Zhou, Honggeng, 2021. "Diversify or concentrate: The impact of customer concentration on corporate social responsibility," International Journal of Production Economics, Elsevier, vol. 240(C).
    15. Alex Bangash & Ramesh Bollapragada & Rachelle Klein & Narayan Raman & Herbert B. Shulman & Donald R. Smith, 2004. "Inventory Requirements Planning at Lucent Technologies," Interfaces, INFORMS, vol. 34(5), pages 342-352, October.
    16. Son, Joong Y. & Sheu, Chwen, 2008. "The impact of replenishment policy deviations in a decentralized supply chain," International Journal of Production Economics, Elsevier, vol. 113(2), pages 785-804, June.
    17. Parsa, H. G., 1999. "Interaction of Strategy Implementation and Power Perceptions in Franchise Systems: An Empirical Investigation," Journal of Business Research, Elsevier, vol. 45(2), pages 173-185, June.
    18. Lau, Amy Hing Ling & Lau, Hon-Shiang & Wang, Jian-Cai, 2007. "Pricing and volume discounting for a dominant retailer with uncertain manufacturing cost information," European Journal of Operational Research, Elsevier, vol. 183(2), pages 848-870, December.
    19. Cotterill, Ron, 1980. "Changing Structure of Mass Media Markets: relevance for Policy Initiatives on Advertising in the Food System," Staff Paper Series 200623, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    20. Vinayak Deshpande & Morris A. Cohen & Karen Donohue, 2003. "An Empirical Study of Service Differentiation for Weapon System Service Parts," Operations Research, INFORMS, vol. 51(4), pages 518-530, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:145:y:2006:i:1:p:35-49:10.1007/s10479-006-0026-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.