IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v227y2020ics0925527320300761.html
   My bibliography  Save this article

Data driven supply allocation to individual customers considering forecast bias

Author

Listed:
  • Seitz, Alexander
  • Grunow, Martin
  • Akkerman, Renzo

Abstract

We propose a data-driven allocation planning approach, which is designed for use in advanced planning systems as they are widely used in industrial environments. The approach exploits increasingly available data on individual customers and products by allocating supply on a highly granular level at high planning frequencies. It counteracts rationing gaming by customers, which we assume to be the reason for demand forecast biases.

Suggested Citation

  • Seitz, Alexander & Grunow, Martin & Akkerman, Renzo, 2020. "Data driven supply allocation to individual customers considering forecast bias," International Journal of Production Economics, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:proeco:v:227:y:2020:i:c:s0925527320300761
    DOI: 10.1016/j.ijpe.2020.107683
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527320300761
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2020.107683?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. Chevalier, Philippe & Lamas, Alejandro & Lu, Liang & Mlinar, Tanja, 2015. "Revenue management for operations with urgent orders," European Journal of Operational Research, Elsevier, vol. 240(2), pages 476-487.
    2. Chiang, David Ming-Huang & Wu, Andy Wei-Di, 2011. "Discrete-order admission ATP model with joint effect of margin and order size in a MTO environment," International Journal of Production Economics, Elsevier, vol. 133(2), pages 761-775, October.
    3. Kloos, Konstantin & Pibernik, Richard, 2020. "Allocation planning under service-level contracts," European Journal of Operational Research, Elsevier, vol. 280(1), pages 203-218.
    4. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect"," Management Science, INFORMS, vol. 50(12_supple), pages 1887-1893, December.
    5. Lars Mönch & Reha Uzsoy & John W. Fowler, 2018. "A survey of semiconductor supply chain models part III: master planning, production planning, and demand fulfilment," International Journal of Production Research, Taylor & Francis Journals, vol. 56(13), pages 4565-4584, July.
    6. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 50(12_supple), pages 1875-1886, December.
    7. Christoph Kilger & Herbert Meyr, 2015. "Demand Fulfilment and ATP," Springer Texts in Business and Economics, in: Hartmut Stadtler & Christoph Kilger & Herbert Meyr (ed.), Supply Chain Management and Advanced Planning, edition 5, chapter 9, pages 177-194, Springer.
    8. Jörg Thomas Dickersbach, 2009. "Supply Chain Management with SAP APO¿," Springer Books, Springer, number 978-3-540-92942-0, December.
    9. Liu, Shudong & Song, Miao & Tan, Kok Choon & Zhang, Changyong, 2015. "Multi-class dynamic inventory rationing with stochastic demands and backordering," European Journal of Operational Research, Elsevier, vol. 244(1), pages 153-163.
    10. Alexander Seitz & Martin Grunow, 2017. "Increasing accuracy and robustness of order promises," International Journal of Production Research, Taylor & Francis Journals, vol. 55(3), pages 656-670, February.
    11. Zhenying Zhao & Michael Ball & Masahiro Kotake, 2005. "Optimization-Based Available-To-Promise with Multi-Stage Resource Availability," Annals of Operations Research, Springer, vol. 135(1), pages 65-85, March.
    12. Tsai, Kune-muh & Wang, Shan-chi, 2009. "Multi-site available-to-promise modeling for assemble-to-order manufacturing: An illustration on TFT-LCD manufacturing," International Journal of Production Economics, Elsevier, vol. 117(1), pages 174-184, January.
    13. Herbert Meyr, 2009. "Customer segmentation, allocation planning and order promising in make-to-stock production," Springer Books, in: Herbert Meyr & Hans-Otto Günther (ed.), Supply Chain Planning, pages 117-144, Springer.
    14. Venkatadri, Uday & Srinivasan, Ashok & Montreuil, Benoit & Saraswat, Ashish, 2006. "Optimization-based decision support for order promising in supply chain networks," International Journal of Production Economics, Elsevier, vol. 103(1), pages 117-130, September.
    15. Alarcón, F. & Alemany, M.M.E. & Ortiz, A., 2009. "Conceptual framework for the characterization of the order promising process in a collaborative selling network context," International Journal of Production Economics, Elsevier, vol. 120(1), pages 100-114, July.
    16. İsmail Bakal & Nesim Erkip & Refik Güllü, 2011. "Value of supplier’s capacity information in a two-echelon supply chain," Annals of Operations Research, Springer, vol. 191(1), pages 115-135, November.
    17. Thomas R. Ervolina & Markus Ettl & Young M. Lee & Daniel J. Peters, 2009. "Managing product availability in an assemble-to-order supply chain with multiple customer segments," Springer Books, in: Herbert Meyr & Hans-Otto Günther (ed.), Supply Chain Planning, pages 145-168, Springer.
    18. Baptiste Lebreton, 2015. "Integrated Campaign Planning, Scheduling and Order Confirmation in the Specialty Chemicals Industry," Springer Texts in Business and Economics, in: Hartmut Stadtler & Christoph Kilger & Herbert Meyr (ed.), Supply Chain Management and Advanced Planning, edition 5, chapter 26, pages 475-485, Springer.
    19. Long Gao & Susan H. Xu & Michael O. Ball, 2012. "Managing an Available-to-Promise Assembly System with Dynamic Short-Term Pseudo-Order Forecast," Management Science, INFORMS, vol. 58(4), pages 770-790, April.
    20. Pibernik, Richard, 2005. "Advanced available-to-promise: Classification, selected methods and requirements for operations and inventory management," International Journal of Production Economics, Elsevier, vol. 93(1), pages 239-252, January.
    21. Meyr, H., 2009. "Customer Segmentation, Allocation Planning and Order Promising in Make-to-Stock Production," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 36061, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    22. Richard Pibernik & Prashant Yadav, 2009. "Inventory reservation and real-time order promising in a Make-to-Stock system," Springer Books, in: Herbert Meyr & Hans-Otto Günther (ed.), Supply Chain Planning, pages 169-195, Springer.
    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. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).

    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. Ben Ali, M. & D’Amours, S. & Gaudreault, J. & Carle, M-A., 2018. "Configuration and evaluation of an integrated demand management process using a space-filling design and Kriging metamodeling," Operations Research Perspectives, Elsevier, vol. 5(C), pages 45-58.
    2. Fleischmann, Moritz & Kloos, Konstantin & Nouri, Maryam & Pibernik, Richard, 2020. "Single-period stochastic demand fulfillment in customer hierarchies," European Journal of Operational Research, Elsevier, vol. 286(1), pages 250-266.
    3. Raul Oltra-Badenes & Hermenegildo Gil-Gomez & Jose M Merigo & Daniel Palacios-Marques, 2019. "Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-19, July.
    4. Konstantin Kloos & Richard Pibernik & Benedikt Schulte, 2019. "Allocation planning in sales hierarchies with stochastic demand and service-level targets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(4), pages 981-1024, December.
    5. Alexander Seitz & Hans Ehm & Renzo Akkerman & Sarah Osman, 2016. "A robust supply chain planning framework for revenue management in the semiconductor industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(6), pages 523-533, December.
    6. Gössinger, Ralf & Kalkowski, Sonja, 2015. "Robust order promising with anticipated customer response," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 529-542.
    7. Ojha, Divesh & Sahin, Funda & Shockley, Jeff & Sridharan, Sri V., 2019. "Is there a performance tradeoff in managing order fulfillment and the bullwhip effect in supply chains? The role of information sharing and information type," International Journal of Production Economics, Elsevier, vol. 208(C), pages 529-543.
    8. Vogel, Sebastian & Meyr, Herbert, 2015. "Decentral allocation planning in multi-stage customer hierarchies," European Journal of Operational Research, Elsevier, vol. 246(2), pages 462-470.
    9. Alexander Seitz & Martin Grunow, 2017. "Increasing accuracy and robustness of order promises," International Journal of Production Research, Taylor & Francis Journals, vol. 55(3), pages 656-670, February.
    10. Wang, Zhaodong & Wang, Xin & Ouyang, Yanfeng, 2015. "Bounded growth of the bullwhip effect under a class of nonlinear ordering policies," European Journal of Operational Research, Elsevier, vol. 247(1), pages 72-82.
    11. Zhang, Xiaolong & Burke, Gerard J., 2011. "Analysis of compound bullwhip effect causes," European Journal of Operational Research, Elsevier, vol. 210(3), pages 514-526, May.
    12. Foad Mahdavi Pajouh & Dahai Xing & Yingjue Zhou & Sharethram Hariharan & Balabhaskar Balasundaram & Tieming Liu & Ramesh Sharda, 2013. "A Specialty Steel Bar Company Uses Analytics to Determine Available-to-Promise Dates," Interfaces, INFORMS, vol. 43(6), pages 503-517, December.
    13. Darwish, M.A. & Odah, O.M., 2010. "Vendor managed inventory model for single-vendor multi-retailer supply chains," European Journal of Operational Research, Elsevier, vol. 204(3), pages 473-484, August.
    14. Chong, Alain Yee-Loong & Zhou, Li, 2014. "Demand chain management: Relationships between external antecedents, web-based integration and service innovation performance," International Journal of Production Economics, Elsevier, vol. 154(C), pages 48-58.
    15. Abhijit Baidya, 2019. "Stochastic supply chain, transportation models: implementations and benefits," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 432-476, June.
    16. Ding, Huiping & Guo, Baochun & Liu, Zhishuo, 2011. "Information sharing and profit allotment based on supply chain cooperation," International Journal of Production Economics, Elsevier, vol. 133(1), pages 70-79, September.
    17. Quante, R. & Fleischmann, M. & Meyr, H., 2009. "A Stochastic Dynamic Programming Approach to Revenue Management in a Make-to-Stock Production System," ERIM Report Series Research in Management ERS-2009-015-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    18. Pedro Domingos Antoniolli, 2016. "Information Technology Framework for Pharmaceutical Supply Chain Demand Management: a Brazilian Case Study," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 27-55, March.
    19. Patrick R. Burgess & Funlade T. Sunmola, 2022. "Exploring Attractive Quality Requirements for Short Food Supply Chain Digital Platforms," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(1), pages 1-24, January.
    20. Ying Rong & Lawrence V. Snyder & Zuo‐Jun Max Shen, 2017. "Bullwhip and reverse bullwhip effects under the rationing game," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(3), pages 203-216, April.

    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:227:y:2020:i:c:s0925527320300761. 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.