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Guidelines for Collaborative Supply Chain System Design and Operation

Author

Listed:
  • John A. Muckstadt

    (Cornell University)

  • David H. Murray

    (College of William & Mary)

  • James A. Rappold

    (University of Wisconsin)

  • Dwight E. Collins

    (Aspen Technology)

Abstract

Over the past decade, firms have adopted supply chain management as a critical element of their corporate strategies. Despite these efforts, it is our observation that many firms do not realize the anticipated benefits of constructing collaborative operating relationships with supply chain partners. Our purpose in this paper is to establish a set of guiding principles for the effective design and execution of supply chain systems. These principles suggest why, what, and how collaborative relationships should be constructed. While constructing and operating a competitive supply chain is the primary objective of supply chain management, we have observed several impediments to achieving this goal. First, demand uncertainty is so substantial in most supply chain environments that if it is not adequately addressed, it can severely degrade the anticipated performance of the supply chain as measured in terms of unit cost, speed, quality, and responsiveness to changing conditions. Second, supply chains with poor physical characteristics that operate with long and variable response times cannot take full advantage of collaborative relationships due to their inability to respond to changes in the environment. Third, firms with poor information infrastructures lack the capabilities necessary to acquire, store, manipulate, and transmit data effectively and quickly. Fourth, business processes are often not designed properly, both intra- and inter-organizationally, to adapt to evolving supply chain conditions. Finally, decision support systems and operating policies that guide day-to-day operating decisions may not be adequately designed to contend with supply chain uncertainty. We also suggest that the strategic and tactical modeling paradigms employed in supply chain decision support systems are inadequate in many operational environments because of the manner in which uncertainty is treated. Furthermore, collaborative relationships that focus on reducing the uncertainty in operating environments by employing improved information systems and business processes will result in more efficient allocation of key resources, faster response times to market forces, and more reliable supply chain performance; however, these collaborative arrangements by themselves cannot compensate for fundamentally flawed and operationally ineffective manufacturing and distribution environments.

Suggested Citation

  • John A. Muckstadt & David H. Murray & James A. Rappold & Dwight E. Collins, 2001. "Guidelines for Collaborative Supply Chain System Design and Operation," Information Systems Frontiers, Springer, vol. 3(4), pages 427-453, December.
  • Handle: RePEc:spr:infosf:v:3:y:2001:i:4:d:10.1023_a:1012824820895
    DOI: 10.1023/A:1012824820895
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    References listed on IDEAS

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    1. Fangruo Chen, 1998. "Echelon Reorder Points, Installation Reorder Points, and the Value of Centralized Demand Information," Management Science, INFORMS, vol. 44(12-Part-2), pages 221-234, December.
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    Cited by:

    1. Taiwo Adetiloye, 2021. "Collaboration Planning of Stakeholders for Sustainable City Logistics Operations," Papers 2107.14049, arXiv.org.
    2. Oladapo Taiwo & Rejoice Worlasi Zotoo, 2021. "Collaboration within a Supply Chain and Corprate Wellness of Digital TV Firms in Rivers State," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 5(6), pages 405-412, June.
    3. Han, Jeong Hugh & Wang, Yingli & Naim, Mohamed, 2017. "Reconceptualization of information technology flexibility for supply chain management: An empirical study," International Journal of Production Economics, Elsevier, vol. 187(C), pages 196-215.
    4. Gary L. Lilien & Arvind Rangaswamy & Gerrit H. Van Bruggen & Katrin Starke, 2004. "DSS Effectiveness in Marketing Resource Allocation Decisions: Reality vs. Perception," Information Systems Research, INFORMS, vol. 15(3), pages 216-235, September.
    5. Riemer, Kai, 2008. "E-Commerce und Supply-Chain-Management: Maßnahmen und Instrumente zur Verbesserung der Koordination in Lieferketten," Working Papers 53, University of Münster, Competence Center Internet Economy and Hybrid Systems, European Research Center for Information Systems (ERCIS).
    6. Weili Han & Yun Gu & Wei Wang & Yin Zhang & Yuliang Yin & Junyu Wang & Li-Rong Zheng, 2015. "The design of an electronic pedigree system for food safety," Information Systems Frontiers, Springer, vol. 17(2), pages 275-287, April.
    7. Sachin Modgil & Rohit Kumar Singh & Shivam Gupta & Denis Dennehy, 2024. "A Confirmation Bias View on Social Media Induced Polarisation During Covid-19," Information Systems Frontiers, Springer, vol. 26(2), pages 417-441, April.
    8. Fatin Amrina A. Rashid & Hawa Hishamuddin & Nizaroyani Saibani & Mohd Radzi Abu Mansor & Zambri Harun, 2022. "A Review of Supply Chain Uncertainty Management in the End-of-Life Vehicle Industry," Sustainability, MDPI, vol. 14(19), pages 1-28, October.
    9. Muckstadt, John A. & Klein, Michael G. & Jackson, Peter L. & Gougelet, Robert M. & Hupert, Nathaniel, 2023. "Efficient and effective large-scale vaccine distribution," International Journal of Production Economics, Elsevier, vol. 262(C).
    10. ur Rehman, Attique & Shakeel Sadiq Jajja, Muhammad & Farooq, Sami, 2022. "Manufacturing planning and control driven supply chain risk management: A dynamic capability perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    11. Yamada, Tadashi & Imai, Koji & Nakamura, Takamasa & Taniguchi, Eiichi, 2011. "A supply chain-transport supernetwork equilibrium model with the behaviour of freight carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 887-907.

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