Use of modern analytical models for forecasting the results of innovation implementation on the overall economic productivity of enterprises - Pokolenko, V.; Khomenko , O.; Kedrenovskyi, S.; Ovsyanyk, M.; Siedinkin, O. (Ways to Improve Construction Efficiency, 2023)
In the conditions of the modern economy, characterized by high competition and rapid technological changes, enterprises are forced to seek new ways to enhance the effectiveness of their operations. One of the key elements of this process is innovation. Innovative activities include the development and implementation of new technologies, products, and management methods aimed at achieving competitive advantages. However, the implementation of innovations is a complex and risky process that requires careful planning and forecasting. In this context, the need for modern analytical models to forecast innovation results and their impact on the overall economic productivity of the enterprise is increasing. Innovative solutions can significantly affect all aspects of an enterprise’s activity, including production processes, financial stability, and market position. Effective management of innovation processes allows not only to increase productivity but also to create conditions for the long-term growth of the company. However, innovation implementation is always accompanied by certain risks, as results may differ from expectations due to market uncertainty or technical difficulties. This creates the need for scientifically grounded forecasting methods that allow assessing potential development scenarios and reducing risks. Analytical forecasting models allow enterprises to evaluate various aspects of innovation activity and their possible consequences for economic productivity. Such models can include regression analysis, scenario analysis, risk assessment methods, and multifactorial analysis methods. They enable businesses to objectively evaluate the potential benefits of innovations, develop strategies to minimize risks, and forecast economic results based on various assumptions and market development scenarios. The implementation of analytical forecasting models is particularly relevant for enterprises operating in high-tech industries or markets where constant innovation changes occur. This enables them to remain competitive, respond quickly to market changes, and optimize resource utilization. Analytical models also help enterprises better understand which innovations have the greatest potential for creating added value and focus on areas that ensure the highest profitability.