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Monte Carlo Simulation as a Demand Forecasting Tool

Author

Listed:
  • Bartosz Przysucha
  • Piotr Bednarczuk
  • Wlodzimierz Martyniuk
  • Ewa Golec
  • Michal Jasienski
  • Damian Pliszczuk

Abstract

Purpose: This article aims to evaluate the effectiveness of Monte Carlo simulation as a tool for demand forecasting. Design/Methodology/Approach: The study analyzes historical data on product sales, fits a theoretical distribution, and then applies Monte Carlo simulation to forecast demand for the next 15 days. Findings: The result of the research shows that Monte Carlo simulation can outperform more straightforward methods such as averaging, particularly in the presence of uncertainty or randomness Practical Implications: The study demonstrates how Monte Carlo simulation can improve demand forecasting accuracy, which is crucial for optimizing various business operations. Originality/Value: This study's novelty lies in demonstrating the practical application of Monte Carlo simulation for demand forecasting and comparing its performance against traditional methods.

Suggested Citation

  • Bartosz Przysucha & Piotr Bednarczuk & Wlodzimierz Martyniuk & Ewa Golec & Michal Jasienski & Damian Pliszczuk, 2024. "Monte Carlo Simulation as a Demand Forecasting Tool," European Research Studies Journal, European Research Studies Journal, vol. 0(Special A), pages 103-113.
    • Handle: RePEc:ers:journl:v:xxvii:y:2024:i:speciala:p:103-113
    as

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    References listed on IDEAS

    as
    1. Damian Pliszczuk & Piotr Lesiak & Krzysztof Zuk & Tomasz Cieplak, 2021. "Forecasting Sales in the Supply Chain Based on the LSTM Network: The Case of Furniture Industry," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 627-636.
    2. WILLIAM J. McCAUSLAND, 2009. "Random Consumer Demand," Economica, London School of Economics and Political Science, vol. 76(301), pages 89-107, February.
    3. repec:ers:journl:v:xxiv:y:2021:i:special2:p:627-636 is not listed on IDEAS
    4. Matthias F. Brauer, 2013. "The effects of short-term and long-term oriented managerial behavior on medium-term financial performance: longitudinal evidence from Europe," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(2), pages 386-402, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Monte Carlo simulation; demand forecasting; business operations; sales prediction; uncertainty management.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

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