IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v156y2014icp208-213.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527314001935
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2014.06.010?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. Takahashi, Katsuhiko & Myreshka & Hirotani, Daisuke, 2005. "Comparing CONWIP, synchronized CONWIP, and Kanban in complex supply chains," International Journal of Production Economics, Elsevier, vol. 93(1), pages 25-40, January.
    2. Fan, Ti-Jun & Chang, Xiang-Yun & Gu, Chun-Hua & Yi, Jian-Jun & Deng, Sheng, 2014. "Benefits of RFID technology for reducing inventory shrinkage," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 659-665.
    3. Huang, Min & Wang, Dingwei & Ip, W. H., 1998. "Simulation study of CONWIP for a cold rolling plant," International Journal of Production Economics, Elsevier, vol. 54(3), pages 257-266, May.
    4. Ngai, Eric W.T. & Cheung, Bernard K.S. & Lam, S.S. & Ng, C.T., 2014. "RFID value in aircraft parts supply chains: A case study," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 330-339.
    5. Zhou, Wei & Piramuthu, Selwyn, 2013. "Remanufacturing with RFID item-level information: Optimization, waste reduction and quality improvement," International Journal of Production Economics, Elsevier, vol. 145(2), pages 647-657.
    6. Caridi, Maria & Moretto, Antonella & Perego, Alessandro & Tumino, Angela, 2014. "The benefits of supply chain visibility: A value assessment model," International Journal of Production Economics, Elsevier, vol. 151(C), pages 1-19.
    7. Segerstedt, Anders, 1996. "Formulas of MRP," International Journal of Production Economics, Elsevier, vol. 46(1), pages 127-136, December.
    8. Wong, W.K. & Guo, Z.X. & Leung, S.Y.S, 2014. "Intelligent multi-objective decision-making model with RFID technology for production planning," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 647-658.
    9. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
    10. Pettersen, Jan-Arne & Segerstedt, Anders, 2009. "Restricted work-in-process: A study of differences between Kanban and CONWIP," International Journal of Production Economics, Elsevier, vol. 118(1), pages 199-207, March.
    11. Radner, Roy, 1993. "The Organization of Decentralized Information Processing," Econometrica, Econometric Society, vol. 61(5), pages 1109-1146, September.
    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. Wang, Hui & Gong, Qiguo & Wang, Shouyang, 2017. "Information processing structures and decision making delays in MRP and JIT," International Journal of Production Economics, Elsevier, vol. 188(C), pages 41-49.
    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.

    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. Dai, Hongyan & Ge, Ling & Zhou, Weihua, 2015. "A design method for supply chain traceability systems with aligned interests," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 14-24.
    2. Guo, Z.X. & Ngai, E.W.T. & Yang, Can & Liang, Xuedong, 2015. "An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment," International Journal of Production Economics, Elsevier, vol. 159(C), pages 16-28.
    3. Ahmed Musa & Al-Amin Abba Dabo, 2016. "A Review of RFID in Supply Chain Management: 2000–2015," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 17(2), pages 189-228, June.
    4. Tao, Feng & Wang, Liang & Fan, Tijun & Yu, Hao, 2022. "RFID adoption strategy in a retailer-dominant supply chain with competing suppliers," European Journal of Operational Research, Elsevier, vol. 302(1), pages 117-129.
    5. Lei, Quansheng & Chen, Jian & Wei, Xingyu & Lu, Shan, 2015. "Supply chain coordination under asymmetric production cost information and inventory inaccuracy," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 204-218.
    6. Wang, Hui & Gong, Qiguo & Wang, Shouyang, 2017. "Information processing structures and decision making delays in MRP and JIT," International Journal of Production Economics, Elsevier, vol. 188(C), pages 41-49.
    7. Park, Chan-Woo & Lee, Hyo-Seong, 2013. "Performance evaluation of a multi-product CONWIP assembly system with correlated external demands," International Journal of Production Economics, Elsevier, vol. 144(1), pages 334-344.
    8. Onyeocha, Chukwunonyelum Emmanuel & Wang, Jiayi & Khoury, Joseph & Geraghty, John, 2015. "A comparison of HK-CONWIP and BK-CONWIP control strategies in a multi-product manufacturing system," Operations Research Perspectives, Elsevier, vol. 2(C), pages 137-149.
    9. Simonetto, Marco & Sgarbossa, Fabio & Battini, Daria & Govindan, Kannan, 2022. "Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda," International Journal of Production Economics, Elsevier, vol. 253(C).
    10. Daron Acemoglu & Philippe Aghion & Claire Lelarge & John Van Reenen & Fabrizio Zilibotti, 2007. "Technology, Information, and the Decentralization of the Firm," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1759-1799.
    11. Jean-Marc Bourgeon & Marie-Laure Breuillé, 2023. "Citizen preferences and the architecture of government," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 61(3), pages 537-585, October.
    12. DeCanio, Stephen J. & Watkins, William E., 1998. "Information processing and organizational structure," Journal of Economic Behavior & Organization, Elsevier, vol. 36(3), pages 275-294, August.
    13. Nicholas Bloom & Luis Garicano & Raffaella Sadun & John Van Reenen, 2014. "The Distinct Effects of Information Technology and Communication Technology on Firm Organization," Management Science, INFORMS, vol. 60(12), pages 2859-2885, December.
    14. , & , M. & ,, 2013. "Hierarchical cheap talk," Theoretical Economics, Econometric Society, vol. 8(1), January.
    15. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    16. Aaltonen, Aleksi Ville & Alaimo, Cristina & Kallinikos, Jannis, 2021. "The making of data commodities: data analytics as an embedded process," LSE Research Online Documents on Economics 110296, London School of Economics and Political Science, LSE Library.
    17. Lidong Wang & Cheryl Ann Alexander, 2015. "Big Data Driven Supply Chain Management and Business Administration," American Journal of Economics and Business Administration, Science Publications, vol. 7(2), pages 60-67, June.
    18. Kembro, Joakim & Näslund, Dag & Olhager, Jan, 2017. "Information sharing across multiple supply chain tiers: A Delphi study on antecedents," International Journal of Production Economics, Elsevier, vol. 193(C), pages 77-86.
    19. Zand, Fardad & Van Beers, Cees & Van Leeuwen, George, 2011. "Information technology, organizational change and firm productivity: A panel study of complementarity effects and clustering patterns in Manufacturing and Services," MPRA Paper 46469, University Library of Munich, Germany.
    20. Jeremy C. Stein, 2002. "Information Production and Capital Allocation: Decentralized versus Hierarchical Firms," Journal of Finance, American Finance Association, vol. 57(5), pages 1891-1921, October.

    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:eee:proeco:v:156:y:2014:i:c:p:208-213. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.