IDEAS home Printed from https://ideas.repec.org/a/lrc/larijb/v8y2018i3p1-11.html
   My bibliography  Save this article

Safety stock determination of uncertain demand and mutually dependent variables

Author

Listed:
  • Sharfuddin Lisan

    (Bangladesh Institute of Human Resource Management (BIHRM) –Supply Chain Department, Dhaka, Bangladesh.)

Abstract

Safety stock is that point, where the user finds a comfort zone between overstock and understock situation. It is is deï¬ ned as the buffer inventory have to be kept to deal with differences between supply and demand. There are different variables to be considered while determining safety stock. In this writing there is an effort to establish a model that include direct and indirect cost related to inventory. The inclusion of Ordering cost, holding cost, Product price, Time, Demand, Demand Variation, Lead time, Mean lead time, Errors in Forecasting, Deviation of lead time etc. are used in this model. This model works economic order quantity, regression, and forecasting error calculation to estimate safety stock while reducing human judgment error in the calculation.

Suggested Citation

  • Sharfuddin Lisan, 2018. "Safety stock determination of uncertain demand and mutually dependent variables," International Journal of Business and Social Research, LAR Center Press, vol. 8(3), pages 1-11, March.
    • Handle: RePEc:lrc:larijb:v:8:y:2018:i:3:p:1-11
    as

    Download full text from publisher

    File URL: https://thejournalofbusiness.org/index.php/site/article/view/1095/679
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Samuel Karlin, 1960. "Dynamic Inventory Policy with Varying Stochastic Demands," Management Science, INFORMS, vol. 6(3), pages 231-258, April.
    2. Katy S. Azoury, 1985. "Bayes Solution to Dynamic Inventory Models Under Unknown Demand Distribution," Management Science, INFORMS, vol. 31(9), pages 1150-1160, September.
    3. Janssen, Elleke & Strijbosch, Leo & Brekelmans, Ruud, 2009. "Assessing the effects of using demand parameters estimates in inventory control and improving the performance using a correction function," International Journal of Production Economics, Elsevier, vol. 118(1), pages 34-42, March.
    4. Gary D. Eppen & R. Kipp Martin, 1988. "Determining Safety Stock in the Presence of Stochastic Lead Time and Demand," Management Science, INFORMS, vol. 34(11), pages 1380-1390, November.
    5. Li Chen, 2010. "Bounds and Heuristics for Optimal Bayesian Inventory Control with Unobserved Lost Sales," Operations Research, INFORMS, vol. 58(2), pages 396-413, April.
    6. Matthew Rosenshine & Duncan Obee, 1976. "Analysis of a Standing Order Inventory System with Emergency Orders," Operations Research, INFORMS, vol. 24(6), pages 1143-1155, December.
    7. Zeynep Müge Avsar & Melike Baykal‐Gürsoy, 2002. "Inventory control under substitutable demand: A stochastic game application," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(4), pages 359-375, June.
    8. Beutel, Anna-Lena & Minner, Stefan, 2012. "Safety stock planning under causal demand forecasting," International Journal of Production Economics, Elsevier, vol. 140(2), pages 637-645.
    9. Howard J. Weiss, 1980. "Optimal Ordering Policies for Continuous Review Perishable Inventory Models," Operations Research, INFORMS, vol. 28(2), pages 365-374, April.
    10. Martin A. Lariviere & Evan L. Porteus, 1999. "Stalking Information: Bayesian Inventory Management with Unobserved Lost Sales," Management Science, INFORMS, vol. 45(3), pages 346-363, March.
    11. Dr. Murat çuhadar & Iclal Cogurcu & Ceyda Kukrer, 2014. "Modelling and Forecasting Cruise Tourism Demand to Izmir by Different Artificial Neural Network Architectures," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(3), pages 12-28, March.
    12. Strijbosch, L. W. G. & Moors, J. J. A., 2005. "The impact of unknown demand parameters on (R,S)-inventory control performance," European Journal of Operational Research, Elsevier, vol. 162(3), pages 805-815, May.
    13. Dr. Murat çuhadar & Iclal Cogurcu & Ceyda Kukrer, 2014. "Modelling and Forecasting Cruise Tourism Demand to Izmir by Different Artificial Neural Network Architectures," International Journal of Business and Social Research, LAR Center Press, vol. 4(3), pages 12-28, March.
    14. Donald L. Iglehart, 1964. "The Dynamic Inventory Problem with Unknown Demand Distribution," Management Science, INFORMS, vol. 10(3), pages 429-440, April.
    15. Chiang, Chi & Gutierrez, Genaro J., 1996. "A periodic review inventory system with two supply modes," European Journal of Operational Research, Elsevier, vol. 94(3), pages 527-547, November.
    16. Avinadav, Tal & Herbon, Avi & Spiegel, Uriel, 2013. "Optimal inventory policy for a perishable item with demand function sensitive to price and time," International Journal of Production Economics, Elsevier, vol. 144(2), pages 497-506.
    17. Patrik Alfredsson & Jos Verrijdt, 1999. "Modeling Emergency Supply Flexibility in a Two-Echelon Inventory System," Management Science, INFORMS, vol. 45(10), pages 1416-1431, October.
    18. Steven Nahmias & David Perry & Wolfgang Stadje, 2004. "Perishable inventory systems with variable input and demand rates," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 60(1), pages 155-162, September.
    Full references (including those not matched with items on IDEAS)

    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. Sharfuddin Lisan, 2018. "Safety stock determination of uncertain demand and mutually dependent variables," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 8(3), pages 1-11, March.
    2. Prak, Dennis & Teunter, Ruud & Syntetos, Aris, 2017. "On the calculation of safety stocks when demand is forecasted," European Journal of Operational Research, Elsevier, vol. 256(2), pages 454-461.
    3. Tomoaki Yamazaki & Keisuke Shida & Takashi Kanazawa, 2016. "An approach to establishing a method for calculating inventory," International Journal of Production Research, Taylor & Francis Journals, vol. 54(8), pages 2320-2331, April.
    4. Harun Avci & Kagan Gokbayrak & Emre Nadar, 2020. "Structural Results for Average‐Cost Inventory Models with Markov‐Modulated Demand and Partial Information," Production and Operations Management, Production and Operations Management Society, vol. 29(1), pages 156-173, January.
    5. Woonghee Tim Huh & Paat Rusmevichientong, 2009. "A Nonparametric Asymptotic Analysis of Inventory Planning with Censored Demand," Mathematics of Operations Research, INFORMS, vol. 34(1), pages 103-123, February.
    6. Mila Nambiar & David Simchi‐Levi & He Wang, 2021. "Dynamic Inventory Allocation with Demand Learning for Seasonal Goods," Production and Operations Management, Production and Operations Management Society, vol. 30(3), pages 750-765, March.
    7. Ghate, Archis, 2015. "Optimal minimum bids and inventory scrapping in sequential, single-unit, Vickrey auctions with demand learning," European Journal of Operational Research, Elsevier, vol. 245(2), pages 555-570.
    8. Glenn, David & Bisi, Arnab & Puterman, Martin L., 2004. "The Bayesian Newsvendors in Supply Chains with Unobserved Lost Sales," Working Papers 04-0110, University of Illinois at Urbana-Champaign, College of Business.
    9. Zhang, Jian & Zhang, Juliang & Hua, Guowei, 2016. "Multi-period inventory games with information update," International Journal of Production Economics, Elsevier, vol. 174(C), pages 119-127.
    10. Xiaomei Ding & Martin L. Puterman & Arnab Bisi, 2002. "The Censored Newsvendor and the Optimal Acquisition of Information," Operations Research, INFORMS, vol. 50(3), pages 517-527, June.
    11. Katy S. Azoury & Julia Miyaoka, 2009. "Optimal Policies and Approximations for a Bayesian Linear Regression Inventory Model," Management Science, INFORMS, vol. 55(5), pages 813-826, May.
    12. Li, Tianyun & Fang, Weiguo & Baykal-Gürsoy, Melike, 2021. "Two-stage inventory management with financing under demand updates," International Journal of Production Economics, Elsevier, vol. 232(C).
    13. Arnab Bisi & Maqbool Dada, 2007. "Dynamic learning, pricing, and ordering by a censored newsvendor," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(4), pages 448-461, June.
    14. Aditya Jain & Nils Rudi & Tong Wang, 2015. "Demand Estimation and Ordering Under Censoring: Stock-Out Timing Is (Almost) All You Need," Operations Research, INFORMS, vol. 63(1), pages 134-150, February.
    15. Prak, Dennis & Teunter, Ruud, 2019. "A general method for addressing forecasting uncertainty in inventory models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 224-238.
    16. Woonghee Tim Huh & Retsef Levi & Paat Rusmevichientong & James B. Orlin, 2011. "Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator," Operations Research, INFORMS, vol. 59(4), pages 929-941, August.
    17. Li Chen & Adam J.Mersereau & Zhe (Frank) Wang, 2017. "Optimal Merchandise Testing with Limited Inventory," Operations Research, INFORMS, vol. 65(4), pages 968-991, August.
    18. Yossi Aviv, 2003. "A Time-Series Framework for Supply-Chain Inventory Management," Operations Research, INFORMS, vol. 51(2), pages 210-227, April.
    19. Çağrı Haksöz & Sridhar Seshadri, 2004. "Monotone Forecasts," Operations Research, INFORMS, vol. 52(3), pages 478-486, June.
    20. Larson, C. Erik & Olson, Lars J. & Sharma, Sunil, 2001. "Optimal Inventory Policies when the Demand Distribution Is Not Known," Journal of Economic Theory, Elsevier, vol. 101(1), pages 281-300, November.

    More about this item

    Keywords

    Dependent Variables; Direct and Indirect Inventory Cost; Safety Stock; Uncertain Demand.;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • J29 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Other

    Statistics

    Access and download statistics

    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:lrc:larijb:v:8:y:2018:i:3:p:1-11. 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: Al Hossain (email available below). General contact details of provider: http://www.thejournalofbusiness.org .

    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.