Ensuring the objectivity of the technology for forecasting business process indicators in the field of e-commerce

Authors

DOI:

https://doi.org/10.15587/2706-5448.2025.326211

Keywords:

forecasting, e-commerce, integration of results, business management, anomaly detection, neural networks, decision optimization

Abstract

The object of research is the technology of forecasting business process indicators in the field of e-commerce. These technologies were investigated to identify ways to increase their objectivity.

In the process of research, an analysis of input data was performed, time horizons were determined and expected results were formulated. Data normalization was carried out using the minmax method, anomaly detection was based on the standard deviation criterion. The choice of the forecasting method included the use of factual, expert and combined methods. Data processing was performed using the K-means and DBSCAN algorithms. Forecast formation was carried out using retrospective methods with the adjustment of indicators and activation functions. Monitoring and adjustment of forecasts was implemented through the MAPE, RMSE, MAE metrics and error analysis. The accuracy of forecasts was assessed by comparing methods by metrics in different scenarios, which ensured the adaptability of the model to a changing business environment. The proposed approaches integrate modern digital tools: big data analysis, automation of forecasting methods, anomaly processing, scenario approach and neural networks.

The objectivity of the technology for forecasting business process indicators in the field of e-commerce ensures increased forecast accuracy, adaptability to a changing market environment, and expands the possibilities for making strategic management decisions. This contributes to increasing the competitiveness of enterprises, their ability to quickly respond to changes in the market situation and improve management processes.

Due to increased objectivity of forecasting, enterprises can quickly respond to market changes and optimize resource use. The integration of modern data processing tools and multifactor metrics guarantees the accuracy of forecasts and takes into account complex relationships.

This creates a basis for strategic planning, ensures sustainable development of enterprises in the digital economy and allows for increased management efficiency in a dynamic market. The results of the study demonstrate that the adjusted technology for forecasting business process indicators in the field of e-commerce contributes to making informed management decisions focused on long-term effectiveness.

Author Biographies

Oleksii Fedorchak, Lviv Polytechnic National University

PhD

Department of Entrepreneurship and Environmental Goods Expertise

Yaroslava Moskvyak, Lviv Polytechnic National University

PhD, Associate Professor

Department of Tourism

Anatolii Kucher, Lviv Polytechnic National University

Doctor of Economic Sciences, Senior Researcher, Professor

Department of Management of Organizations

Sviatoslav Kniaz, Lviv Polytechnic National University

Doctor of Economic Sciences, Professor, Director of Institute

Viacheslav Chornovil Institute of Sustainable Development

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Ensuring the objectivity of the technology for forecasting business process indicators in the field of e-commerce

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Published

2025-04-09

How to Cite

Fedorchak, O., Moskvyak, Y., Kucher, A., & Kniaz, S. (2025). Ensuring the objectivity of the technology for forecasting business process indicators in the field of e-commerce. Technology Audit and Production Reserves, 2(4(82), 14–23. https://doi.org/10.15587/2706-5448.2025.326211

Issue

Vol. 2 No. 4(82) (2025): Economics of enterprises. Macroeconomics

Section

Economics and Enterprise Management

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Copyright (c) 2025 Oleksii Fedorchak, Yaroslava Moskvyak, Anatolii Kucher, Sviatoslav Kniaz

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