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Simulation Decomposition: New Approach For Better Simulation Analysis Of Multi-Variable Investment Projects

Author

Listed:
  • M. Kozlova

    (School of Business and Management, Lappeenranta University of Technology, Skinnarilankatu 34, 53850 Lappeenranta, Finland.)

  • M. Collan

    (School of Business and Management, Lappeenranta University of Technology, Skinnarilankatu 34, 53850 Lappeenranta, Finland.)

  • P. Luukka

    (School of Business and Management, Lappeenranta University of Technology, Skinnarilankatu 34, 53850 Lappeenranta, Finland.)

Abstract

This paper presents a new method to enhance simulation-based analysis of complex investments that contain multi-variable uncertainty. The method is called “simulation decomposition”. Typically the result of simulation-based investment analysis is in the form of histogram distributions - here we propose a method for first classifying the possible outcomes of selected uncertain variables into states and then using combinations of the created states in the decomposition of the simulated distribution into a number of sub-distributions. The sub-distributions that can be matched to state-combinations of the variables contain relevant actionable information that helps managers in decision-making with regards to the studied investments. A numerical illustration of a renewable energy investment is used to demonstrate the usability, the enhanced analytical power, and the intuitively understandable benefits that can be reached by using the simulation decomposition method. The proposed method is generally usable and can be utilized independent of the investment context.

Suggested Citation

  • M. Kozlova & M. Collan & P. Luukka, 2016. "Simulation Decomposition: New Approach For Better Simulation Analysis Of Multi-Variable Investment Projects," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 21(2), pages 3-18, November.
    • Handle: RePEc:fzy:fuzeco:v:21:y:2016:i:2:p:3-18
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    Citations

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    Cited by:

    1. Mariia Kozlova & Julian Scott Yeomans, 2022. "Monte Carlo Enhancement via Simulation Decomposition: A “Must-Have” Inclusion for Many Disciplines," INFORMS Transactions on Education, INFORMS, vol. 22(3), pages 147-159, May.
    2. Deviatkin, Ivan & Kozlova, Mariia & Yeomans, Julian Scott, 2021. "Simulation decomposition for environmental sustainability: Enhanced decision-making in carbon footprint analysis," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).

    More about this item

    Keywords

    corporate finance and governance; capital budgeting; simulation modeling; renewable resources and conservation;
    All these keywords.

    JEL classification:

    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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