Financial modeling trends for production companies in the context of Industry 4.0

  • Received January 18, 2021;
    Accepted March 2, 2021;
    Published March 18, 2021
  • Author(s)
  • DOI
  • Article Info
    Volume 18 2021, Issue #1, pp. 270-284
  • Cited by
    13 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

Over the years, technological progress has accelerated highly, and the speed, flexibility, human error reduction, and the ability to manage the process in real time have become more critical and required production companies to adapt production and business models according to the needs. The demand for real-time decision support systems adapted to these raising business needs is continuously growing. Nevertheless, businesses usually face challenges in identifying new indicators, data sources, and appropriate financial modeling methods to analyze them. This paper aims to define and summarize the main financial/economic forecasting methods for production companies in the context of Industry 4.0. Main findings show forecasting accuracy of up to 96% when combining economic and demand information, optimal forecasting period from 10 months to five years, more frequent use of soft indicators in forecasting, the relationship between company’s size and production planning. Four groups of indicators used in financial modeling, such as (I) production-related, (II) customers’ and demand-oriented, (III) industry-specific, and (IV) media information indicators, were separated. The analysis forms a suggestion for decision-makers to pay more attention to the forecasting object identification, indicators’ selection peculiarities, data collection possibilities, and the choice of appropriate methods of financial modeling.

This work was partly supported by Project No. 0121U100470 “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy”.

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    • Figure A1. The most relevant literature analysis findings
    • Figure A2. Industry 4.0 financial/economic forecasting models and indicators by analyzed authors
    • Conceptualization
      Inga Kartanaitė, Rytis Krušinskas
    • Data curation
      Inga Kartanaitė
    • Formal Analysis
      Inga Kartanaitė
    • Investigation
      Inga Kartanaitė
    • Methodology
      Inga Kartanaitė
    • Validation
      Inga Kartanaitė, Oleksandr Kubatko, Rytis Krušinskas
    • Visualization
      Inga Kartanaitė
    • Writing – original draft
      Inga Kartanaitė, Rytis Krušinskas
    • Writing – review & editing
      Inga Kartanaitė, Bohdan Kovalov, Oleksandr Kubatko, Rytis Krušinskas
    • Funding acquisition
      Bohdan Kovalov, Oleksandr Kubatko
    • Resources
      Bohdan Kovalov, Oleksandr Kubatko
    • Software
      Bohdan Kovalov
    • Project administration
      Rytis Krušinskas
    • Supervision
      Rytis Krušinskas