The rapid pace of change and uncertainty brought about by the digital revolution are reshaping business models. This study investigates the impact of this transformation on entrepreneurial activity in the Eurozone, specifically examining the role of technology and innovation. Digitalization presents both advantages and disadvantages: while it creates new economic sectors and jobs, it also leads to job displacement in sectors susceptible to automation. This study focuses on the opportunities generated by this transformation, particularly for self-employed entrepreneurs. The literature highlights the transformation of the entrepreneurial process by digital technologies, the rise of new economic sectors based on concepts like AI and robotics, and the impact of digitalization on consumer behavior and business models. The study hypothesizes that the digital revolution creates opportunities across all economic sectors.

The literature review explores the existing scholarship on digital entrepreneurship, contrasting it with traditional entrepreneurship. Key differences highlighted include marketing techniques and the nature of products and services. The role of information technology as a facilitator and mediator in entrepreneurs' operations is emphasized. Studies examining the transformation of entrepreneurial activity by digitalization and the opportunities generated by digital innovation are reviewed. The review also examines the necessary skills for digital entrepreneurs, the processes of business model change in dynamic environments, and the impact of digitalization on access to finance and value creation. The role of digitalization in improving customer service and the relationships between entrepreneurs, customers, and digital platforms are also considered.

The study employs panel data for Euro area countries (excluding Malta, Greece, and Ireland due to incomplete data) from 2009 to 2020. The choice of the Eurozone allows for analysis focusing on factors beyond monetary policy. A panel data methodology is used, combining cross-sectional and time-series data to account for country heterogeneity. The model is represented as: y_it = a_i + βX_it + u_it, where 'i' represents the country and 't' the year. The dependent variables are entrepreneurial activity density (total and self-employed without employees). Independent variables include: change in GDP, unemployment rate, bank credit to GDP ratio, industrial robot density, private and public sector R&D investment, and employment in science and technology-intensive sectors. Fixed effects panel data models with robust standard deviations (HAC) were used, given the Hausman test results.

The results, presented in two models (total companies and self-employed), show that the relative change in GDP positively and significantly influences entrepreneurial activity. The unemployment rate and bank credit/GDP ratio were not statistically significant, suggesting that entrepreneurship in the Eurozone, particularly related to digital factors, is opportunity-driven rather than necessity-driven. Crucially, industrial robot density shows a significant positive relationship with both total and self-employed entrepreneurial activity, supporting the hypothesis that automation creates opportunities. Conversely, private sector R&D investment had a significant negative effect, possibly because internal innovation reduces the need for external entrepreneurial activity. Public R&D investment and employment in science and technology sectors showed no significant relationship with entrepreneurial activity. These findings suggest that high-skilled individuals in technology sectors may not be incentivized to start businesses if suitable employment is available.

The findings suggest that the digital revolution, specifically the rise of robotics, creates substantial entrepreneurial opportunities in the Eurozone. This contrasts with the negative correlation found between private sector R&D investment and entrepreneurial activity. The non-significant impact of public R&D investment and employment in science and technology highlights the need for policy interventions to effectively translate technological advancements into entrepreneurial pursuits. The study's findings challenge the assumption that high unemployment and access to credit are the primary drivers of entrepreneurship in the context of digital transformation. The opportunity-driven nature of entrepreneurship in this domain is emphasized.

This study demonstrates the positive impact of robot density on entrepreneurial activity, particularly for self-employed entrepreneurs in the Eurozone. However, private sector R&D investment showed a negative correlation, indicating a need to incentivize entrepreneurship alongside innovation within companies. Public policy interventions should focus on fostering a favorable environment for digital innovation and AI, and promoting intrapreneurship within firms. Further research should explore the direct impact of specific digital technologies (e.g., blockchain, AI) and the influence of robot density on customer service and consumer experience.

The study's limitations include the exclusion of countries with incomplete data and the potential for omitted variable bias. The analysis primarily focuses on aggregate data and does not delve into the nuances of individual entrepreneurial experiences. Future research could address these limitations through more granular data and qualitative studies to gain a deeper understanding of the interplay between digital transformation and entrepreneurship.