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Information and decision-making delays in MRP, KANBAN, and CONWIP

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  • Gong, Qiguo
  • Yang, Yuru
  • Wang, Shouyang

Abstract

A production control system (PCS) can be considered an information-processing organization (IPO). The performance of different production control systems has been studied intensively. However, their decision-making efficiency has not drawn much attention. The amount of information in a production control system can lead to a delay in decision-making. This paper considers the effect of product position information on decision-making. We use information entropy to measure the amount of position information in products and find that there are different amounts of position information in MRP, KANBAN, and CONWIP. Then, we compare the decision-making time delay among the three production control systems across identical organizational structures for information processing. We conclude that the production control system with the smallest amount of information spends the least amount of time in decision-making.

Suggested Citation

  • Gong, Qiguo & Yang, Yuru & Wang, Shouyang, 2014. "Information and decision-making delays in MRP, KANBAN, and CONWIP," International Journal of Production Economics, Elsevier, vol. 156(C), pages 208-213.
    • Handle: RePEc:eee:proeco:v:156:y:2014:i:c:p:208-213
    DOI: 10.1016/j.ijpe.2014.06.010
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    References listed on IDEAS

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    Cited by:

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    2. Fan, Huan & Li, Gang & Sun, Hongyi & Cheng, T.C.E., 2017. "An information processing perspective on supply chain risk management: Antecedents, mechanism, and consequences," International Journal of Production Economics, Elsevier, vol. 185(C), pages 63-75.
    3. Ruiz-Hernández, Diego & Menezes, Mozart B.C. & Amrani, Aicha, 2019. "An information-content based measure of proliferation as a proxi for structural complexity," International Journal of Production Economics, Elsevier, vol. 212(C), pages 78-91.
    4. M. Thürer & Y. H. Pan & T. Qu & H. Luo & C. D. Li & G. Q. Huang, 2019. "Internet of Things (IoT) driven kanban system for reverse logistics: solid waste collection," Journal of Intelligent Manufacturing, Springer, vol. 30(7), pages 2621-2630, October.
    5. Plaza, Malgorzata & David, Iulian & Shirazi, Farid, 2018. "Management of inventory under market fluctuations the case of a Canadian high tech company," International Journal of Production Economics, Elsevier, vol. 205(C), pages 215-227.
    6. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    7. Jia, Fu & Blome, Constantin & Sun, Hui & Yang, Yang & Zhi, Bangdong, 2020. "Towards an integrated conceptual framework of supply chain finance: An information processing perspective," International Journal of Production Economics, Elsevier, vol. 219(C), pages 18-30.
    8. Nelson Duarte, 2018. "Systemy informatyczne w przemyśle: perspektywa dostawcy," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 49, pages 465-476.
    9. Na Li & Xiaohong Wang & Shaopeng Zhang, 2023. "Effects of digitization on enterprise growth performance: Mediating role of strategic change and moderating role of dynamic capability," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 1040-1053, March.
    10. María Mojarro-Magaña & Jesús Everardo Olguín-Tiznado & Jorge Luis García-Alcaraz & Claudia Camargo-Wilson & Juan Andrés López-Barreras & Rubén Jesús Pérez-López, 2018. "Impact of the Planning from the Kanban System on the Company’s Operating Benefits," Sustainability, MDPI, vol. 10(7), pages 1-24, July.

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