Green Competitiveness Forecasting as an Instrument for Sustainable Business Transformation
Open Access
- 29 June 2024
- journal article
- Published by WSB University in Forum Scientiae Oeconomia
- Vol. 12 (2) , 8-20
Abstract
Modern conditions for transforming the business environment in the context of implementing sustainable development goals, decarbonising the economy, and ensuring climate neutrality determine the need to implement effective measures at the level of individual enterprises. External challenges determine the urgency of strengthening enterprises' green competitive advantages and forming an integral level of green competitiveness. The paper offers a methodological basis for the long-term forecasting of enterprises' green competitiveness levels. The key object of the research is a set of companies representing the machine building, agriculture, and food industries, as strategic branches of Ukraine’s economy. The period of 2020–2028 was chosen as the interval for foresight. The application of autoregressive integrated ARIMA modelling by means of the non-linear least squares method made it possible to determine transformation vectors, marketing determinants, and target orientations for increasing the integral level of green competitiveness. The assessment of the results showed that the leading enterprises in the optimistic scenario are PJSC "SVF Agrotron" (agro-industrial complex), where the predictive value of green competitiveness is 0.84; PJSC "Wimm-Bill-Dunn Ukraine" (food industry), for which the predictive value is 0.73; and PJSC "Motor Sich" (mechanical engineering), for which the predictive value of green competitiveness is 0.74. The results of the evaluation revealed the leading enterprises according to the optimistic scenario for the agro-industrial complex, food industry, and mechanical engineering. The research substantiates the claim that the priorities of the strategy for increasing the level of green competitiveness and the relevant determinants of its implementation should be determined considering the transformation scenarios of its level.Keywords
This publication has 58 references indexed in Scilit:
- Understanding the nonlinear effect of digital technology development on CO 2 reductionSustainable Development, 2024
- A novel approach for forecasting PM2.5 pollution in Delhi using CATALYSTEnvironmental Monitoring and Assessment, 2023
- A comparative study of statistical and machine learning models on carbon dioxide emissions prediction of ChinaEnvironmental Science and Pollution Research, 2023
- Assessing the current and future effects of Covid-19 on energy related-CO2 emissions in the United States using seasonal fractional grey modelEnergy Strategy Reviews, 2023
- Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysisApplied Energy, 2023
- Analyzing the relationship between digitalization and energy sustainability: A comprehensive ISM-MICMAC and DEMATEL approachExpert Systems with Applications, 2023
- Public Sector Leadership as a Core Prerequisite for National Security Resistance to COVID-192023
- Economic analysis of the initial investment for intermediary introduction of compressed natural gas in RomaniaEnergy for Sustainable Development, 2023
- A multi-model forecasting approach for solid waste generation by integrating demographic and socioeconomic factors: a case study of Prayagraj, IndiaEnvironmental Monitoring and Assessment, 2023
- A primer on model selection using the Akaike Information CriterionInfectious Disease Modelling, 2020