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Distribution Strategy Planning: A Comprehensive Probabilistic Approach for Unpredictable Environment

Author

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  • Theodor Petrik

    (Faculty of Social Sciences, Institute of Economic Studies, Charles University, Prague, Czechia)

Abstract

Uncertain future development presents a significant challenge during the distribution strategy planning process. Traditional planning approaches, reliant on creating potential scenarios and assigning probabilities, often struggle due to future developments´ inherent unpredictability, which can lead to suboptimal strategies if probabilities are inaccurately estimated. This paper introduces a novel method designed to navigate these uncertainties without rigid assumptions about the exact probability of each future scenario. This method aims to identify optimal strategies applicable across a wide range of situations by exploring the entire allowable probability space. The effectiveness of this approach is demonstrated by a case study of a real-world Czech company considering potential expansion. The optimal distribution stratégy is formulated and evaluated in the case study for six years, considering multiple potential development scenarios.

Suggested Citation

  • Theodor Petrik, 2024. "Distribution Strategy Planning: A Comprehensive Probabilistic Approach for Unpredictable Environment," Working Papers IES 2024/19, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2024.
    • Handle: RePEc:fau:wpaper:wp2024_19
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    File URL: https://ies.fsv.cuni.cz/en/distribution-strategy-planning-comprehensive-probabilistic-approach-unpredictable-environment
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    More about this item

    Keywords

    Decision-making under uncertainty; Economic efficiency; Transport Economics; Probabilistic Approach;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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