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Numerical analysis of a nonlinear (S, s) inventory control policy under a quantity adjustment economy including explanations from a linear model

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  • Kazuhisa Taniguchi

Abstract

This paper is a sequel to the nonlinear inventory control economy reported in Taniguchi (Significance of nonlinearity and many goods models. In: Shiozawa Y, Morioka M, Taniguchi K (eds) Microfoundations of evolutionary economics. Springer, 2019a). The (S, s) inventory control policy is very simple and has been proved to be optimal from the perspective of cost. However, like an island floating in the vast ocean, it operates as an isolated entity from the surrounding economic activities. In contrast, the quantity adjustment economy presupposes enterprises whose production activities are loosely connected and interdependent in a production network. Therefore, we embedded these optimal and isolated (S, s) policy enterprises into the mesh of interdependent enterprises within a quantity adjustment economy and tried to operate them within the following economic environment. Specifically, we examined a scenario where production is restricted due to a shortage of raw materials, making it impossible to meet all demands. In this situation, can the (S, s) policy enterprises sustain their economic activities, and what are the consequences for the economy as a whole? As a result, if the goods are distributed proportionally to the demand, within the scope of this simulation, the (S, s) policy enterprises are able to continue operating without suffering a halt in economic activity due to a shortage of raw materials within a relatively wide range of parameters. In addition, from the original (S, s) policy, we devised an extended-(S, s) policy that is more resistant to fluctuations in exogenous change, and we examined its characteristics. Furthermore, clearer and more comprehensible supplementary explanations were provided for the linear pseudo(S, s) policy model explained in Taniguchi (2019). This also deepens our understanding of the varying consequences of having differences in the numbers of the kinds of goods.

Suggested Citation

  • Kazuhisa Taniguchi, 2023. "Numerical analysis of a nonlinear (S, s) inventory control policy under a quantity adjustment economy including explanations from a linear model," Evolutionary and Institutional Economics Review, Springer, vol. 20(2), pages 401-424, September.
    • Handle: RePEc:spr:eaiere:v:20:y:2023:i:2:d:10.1007_s40844-023-00266-8
    DOI: 10.1007/s40844-023-00266-8
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    References listed on IDEAS

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    1. repec:bla:kyklos:v:33:y:1980:i:2:p:219-29 is not listed on IDEAS
    2. Joan Robinson, 1980. "Time In Economic Theory," Kyklos, Wiley Blackwell, vol. 33(2), pages 219-229, May.
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    Cited by:

    1. Kazuhiro Kurose & Hiroshi Nishi, 2023. "Special issue: microfoundation of evolutionary economics and its application," Evolutionary and Institutional Economics Review, Springer, vol. 20(2), pages 321-328, September.
    2. Kazuhiro Kurose & Hiroshi Nishi, 2024. "Special issue: microfoundation of evolutionary economics and its application: part 2," Evolutionary and Institutional Economics Review, Springer, vol. 21(2), pages 301-303, September.

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    More about this item

    Keywords

    Quantity adjustment; Nonlinear; Inventory control; Production; Input–Output; Simulation modeling;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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