This article explores the relationship between digitalization and business performance in European small- and medium-sized enterprises (SMEs) amidst the COVID-19 pandemic, which has intensified the need for SMEs to adopt digital technologies for enhanced competitiveness. Conducted through a comprehensive literature review, this study investigates the impact of digitalization on SME performance. Employing the statistical software EViews 12, the research utilizes an econometric analysis of panel data to examine the influence of digitalization on SME performance and validate the formulated hypotheses. The dataset comprises 135 observations collected over a five-year period from 27 European countries. A linear regression model is used to test the hypotheses, revealing the relationship between the independent and dependent variables. Model specifications are determined through various tests. This study’s findings demonstrate that the integration of digital technologies and digital intensity significantly drives digitalization in European SMEs, leading to positive impacts on performance. This article emphasizes the importance of digitalization in SMEs for process streamlining, productivity improvement, and enhanced customer experience, ultimately fostering business growth and development. These empirical findings provide valuable evidence for policymakers to prioritize the identification of appropriate measures for stimulating the integration of new digital tools into SME infrastructure and serve as a foundation for future research in this domain.

The current market situation shows that enterprises are still struggling to digitize their business through the integration of the Internet of Things (IoT), artificial intelligence (AI), cloud technologies and other more advanced technologies, but the fifth industrial revolution is knocking on the door. This article deals with the analysis and evaluation of the impact of Industry 5.0 on entrepreneurs. Industry 4.0 analysis provides results based on interviews with practitioners as well as sales representatives. The main part of the article focuses on the business situation, where the goal was to identify existing gaps along with opportunities and threats. This analysis also describes the best way how to transform in times of the next industrial revolution. Study addresses the approach of integrating human workers in the supply chain in cooperation with automated processes. The purpose of this study is to confirm or refute whether companies are ready for another industrial revolution.

The role and position of the manufacturing sector changes over time. Its importance in the sustainable growth of the economy, innovations, trade, reducing energy demand, and environmental problems is currently being shown again. The study underlines the significance and importance of the manufacturing sector in the economy of countries, and the generally applicable economic principles are explicitly examined in regard to the manufacturing sector. It examines whether selected economic indicators of the manufacturing sector in the region of the Visegrad Group countries can affect the level of average wages in the sector. Wages represent a key determinant of attractiveness, as well as the potential to increase the standards of living and the long-term sustainability of a given sector. The selected economic indicators for the period 2008–2019 concerning average wages in the manufacturing sector were: FDI Flow, GDP, labour productivity, employment, and the number of hours worked in the manufacturing sector. The source of secondary data was the OECD database. A multiple regression model was used and tested. The suitability of the proposed model was tested using the ANOVA method. A significant effect was shown in the case of two of the examined variables, namely the GDP and employment in the manufacturing sector. Based on the findings of the study, it can be assumed that the sectoral GDP can positively affect average wages in the sector and the level of employment in manufacturing can negatively affect them. The summary of implications and proposals indirectly supports the need to develop and introduce innovations, new technologies, automation, and robotization, as well as for further implementation and support of Industry 4.0 and 5.0.

Proposal of Performance Assessment by Integration of Two Management Tools

This article examines the impact of the macroenvironment on enterprises in euro-area countries over the period 2006–2020. Our study builds on important works and theories in the field of business, including the work of Kar and Özsahin. We employ the Panel Least Squares method to estimate the coefficient of selected variables. We identify political, institutional (government effectiveness index, regulatory quality index, rule of law, market capitalization of company, control of corruption, political stability and absence of violence) and financial (financial development index, gross domestic product, inflation rate, unemployment rate, public debt) determinants that can have an effect on entrepreneurship. The article aims to fill a gap in the existing literature by providing new insights from the Eurozone and updated data that were not included in previous literature reviews and studies. In this way, we contribute to expanding knowledge about the relationship between macroeconomic factors and entrepreneurial activities in this specific geographical area, considering the lack of current analyses. According to our results, there is a positive statistically significant relationship between entrepreneurship and gross domestic product per capita, regulatory quality index, and market capitalization of the company and a negative statistically significant relationship between entrepreneurship and rule of law, and public debt.

The purpose of this article is to point out the need to use software simulation tools in industrial practice to optimize the production process and assess the economic effectiveness of investment, including risk. The goal of the research is to find an optimal investment variant to ensure an increase in the production volume of at least 50% and to achieve the maximum economic efficiency of the investment, even considering the risk. The article presents a comprehensive approach that enables the achievement of the set research goal. The selection of the optimal version of the investment is carried out in three steps. Firstly, the versions of the investment variants are assessed from the production point of view using the program Tecnomatix Plant Simulation. Subsequently, the versions of the investment variants are assessed from an economic point of view and from a risk point of view. Economic efficiency is assessed using the financial criteria net present value (NPV), profitability index (PI), and discounted payback period (DPP), and risk analysis is carried out using Monte Carlo simulations. Finally, the accepted outputs are evaluated overall using a multi-criteria method, namely the method of partial order.