IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v145y2006i1p15-3410.1007-s10479-006-0023-x.html
   My bibliography  Save this article

The efficiency of joint decision making in buyer-supplier relationships

Author

Listed:
  • Markus Biehl
  • Wade Cook
  • David Johnston

Abstract

This paper examines the effectiveness of joint decision making within 87 pairs of buyer-supplier relationships in manufacturing. Joint decision making is an important attribute of a more cooperative supply chain relationship that may ultimately result in a better performance. Efficiency is modeled as a multiple criteria problem using Data Envelopment Analysis (DEA). Inputs of five kinds of joint decision making activity are examined relative to two measures of output based on the assessment of the buying firm. Three contingent constructs (product customization and innovation, media richness of the communication between buyer and supplier, and continuity in the relationship) are then examined for their impact on the relative performance of each pair. The implications for the management of supply chain relationships and benchmarking of best practice are then discussed. Copyright Springer Science+Business Media, LLC 2006

Suggested Citation

  • Markus Biehl & Wade Cook & David Johnston, 2006. "The efficiency of joint decision making in buyer-supplier relationships," Annals of Operations Research, Springer, vol. 145(1), pages 15-34, July.
    • Handle: RePEc:spr:annopr:v:145:y:2006:i:1:p:15-34:10.1007/s10479-006-0023-x
    DOI: 10.1007/s10479-006-0023-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-006-0023-x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-006-0023-x?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. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    3. Jeffrey H. Dyer, 1997. "Effective interim collaboration: how firms minimize transaction costs and maximise transaction value," Strategic Management Journal, Wiley Blackwell, vol. 18(7), pages 535-556, August.
    4. Hartley, Janet L. & Choi, Thomas Y., 1996. "Supplier development: Customers as a catalyst of process change," Business Horizons, Elsevier, vol. 39(4), pages 37-44.
    5. Kleinsorge, Ilene K. & Schary, Philip B. & Tanner, Ray D., 1992. "Data Envelopment Analysis for monitoring customer-supplier relationships," Journal of Accounting and Public Policy, Elsevier, vol. 11(4), pages 357-372.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thuzar Linn & Broos Maenhout, 2019. "The impact of environmental uncertainty on the performance of the rice supply chain in the Ayeyarwaddy Region, Myanmar," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 7(1), pages 1-29, December.
    2. Zhongbao Zhou & Mei Wang & Hui Ding & Chaoqun Ma & Wenbin Liu, 2013. "Further study of production possibility set and performance evaluation model in supply chain DEA," Annals of Operations Research, Springer, vol. 206(1), pages 585-592, July.
    3. Yen Sheng Tsai & Wei-Hsi Hung, 2023. "A low-cost intelligent tracking system for clothing manufacturers," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 473-491, February.
    4. Ming-Miin Yu & Bo Hsiao, 2016. "Measuring the technology gap and logistics performance of individual countries by using a meta-DEA--AR model," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(1), pages 98-120, January.
    5. Oliveira, Fernando S. & Ruiz, Carlos & Conejo, Antonio J., 2013. "Contract design and supply chain coordination in the electricity industry," European Journal of Operational Research, Elsevier, vol. 227(3), pages 527-537.
    6. Ke Ma & Lichuan Wang & Yan Chen, 2017. "A Collaborative Cloud Service Platform for Realizing Sustainable Make-To-Order Apparel Supply Chain," Sustainability, MDPI, vol. 10(1), pages 1-21, December.
    7. Chunguang Bai & Joseph Sarkis, 2016. "Supplier development investment strategies: a game theoretic evaluation," Annals of Operations Research, Springer, vol. 240(2), pages 583-615, May.

    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. Talluri, Srinivas & Narasimhan, Ram, 2004. "A methodology for strategic sourcing," European Journal of Operational Research, Elsevier, vol. 154(1), pages 236-250, April.
    2. Mohammad Izadikhah & Reza Farzipoor Saen & Razieh Roostaee, 2018. "How to assess sustainability of suppliers in the presence of volume discount and negative data in data envelopment analysis?," Annals of Operations Research, Springer, vol. 269(1), pages 241-267, October.
    3. Ganji, S.S. & Tirkolaee, Erfan Babaee & Jahed, Rasul, 2024. "Evaluating the performance of intercity road freight transport: Double-frontier parallel network cross-efficiency model," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    4. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, March.
    5. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    6. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    7. Ahmad, Usman, 2011. "Financial Reforms and Banking Efficiency: Case of Pakistan," MPRA Paper 34220, University Library of Munich, Germany.
    8. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.
    9. António Afonso & Ana Patricia Montes & José M. Domínguez, 2024. "Measuring Tax Burden Efficiency in OECD Countries: An International Comparison," CESifo Working Paper Series 11333, CESifo.
    10. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.
    11. Chai, Naijie & Zhou, Wenliang & Hu, Xinlei, 2022. "Safety evaluation of urban rail transit operation considering uncertainty and risk preference: A case study in China," Transport Policy, Elsevier, vol. 125(C), pages 267-288.
    12. Ravelojaona, Paola, 2019. "On constant elasticity of substitution – Constant elasticity of transformation Directional Distance Functions," European Journal of Operational Research, Elsevier, vol. 272(2), pages 780-791.
    13. Hu, Jin-Li & Wang, Shih-Chuan & Yeh, Fang-Yu, 2006. "Total-factor water efficiency of regions in China," Resources Policy, Elsevier, vol. 31(4), pages 217-230, December.
    14. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    15. Keh, Hean Tat & Chu, Singfat, 2003. "Retail productivity and scale economies at the firm level: a DEA approach," Omega, Elsevier, vol. 31(2), pages 75-82, April.
    16. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    17. da Silva, Aneirson Francisco & Miranda, Rafael de Carvalho & Marins, Fernando Augusto Silva & Dias, Erica Ximenes, 2024. "A new multiple criteria data envelopment analysis with variable return to scale: Applying bi-dimensional representation and super-efficiency analysis," European Journal of Operational Research, Elsevier, vol. 314(1), pages 308-322.
    18. Atkinson, Scott E. & Tsionas, Mike G., 2021. "Generalized estimation of productivity with multiple bad outputs: The importance of materials balance constraints," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1165-1186.
    19. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    20. Simona Alfiero & Laura Broccardo & Massimo Cane & Alfredo Esposito, 2018. "High Performance Through Innovation Process Management in SMEs. Evidence from the Italian wine sector," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(3), pages 87-110.

    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:15-34:10.1007/s10479-006-0023-x. 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.