Econometric modelling and forecasting of the impact of external factors on trading enterprise activities: an empirical study of Ukraine

Abstract This article aims to enhance the quantitative methodological approaches used to analyse the impact of external factors, such as economic, social, political and technological influences, on the activities of trading enterprises. This will be achieved by constructing regression models that can be used to inform planning and forecasting activities. The article employs qualitative and quantitative methods to study phenomena and processes, specifically: PEST analysis was employed to determine and generalise the theoretical foundations of the qualitative analysis of the impact of the external environment, while time series were utilised to study trends in the development of individual macroeconomic indicators. Structural and typological groupings were employed to compile primary information characterising the economic, social, political and technological factors of the external environment. Correlation–regression analysis, SWOT analysis and PEST analysis were utilised to forecast and evaluate the impact of external environmental factors on the activities of trading enterprises, and graphical techniques were employed to visualise the impact of external environmental factors on the turnover of trading enterprises. The study’s information base is open statistical data from the State Statistics Committee of Ukraine for 2002–2022. To form the correlation–regression models, data from over 102,000 Ukrainian trading enterprises involved in wholesale and retail trade were used. This study has resulted in the development of quantitative methodological approaches for analysing the impact of external factors on the turnover of wholesale and retail enterprises. The proposed approach is based on constructing regression models to show the relationship between selected performance indicators and key external factors. Implementing the author’s methodology for the strategic analysis of the external environment involves forming a system of analytical indicators that characterise these factors, based on open statistical information. After studying trends in factor indicators in the four most important areas of the external environment (economic, social, political and technological), regression models were constructed to show the dependence of selected performance indicators that characterise the results of wholesale and retail trade enterprises. Using correlation coefficients, the most significant factors impacting the turnover of wholesale and retail trade enterprises were identified. These models can be used to plan development trends in the trade sector in response to changes in certain macroeconomic factors. Unlike existing methodological approaches to assessing the strength of external factors based on scoring, which are widely used in strategic analysis, the developed models allow for a quantitative assessment of their impact on the volume of goods turnover.