Purpose: The institutional context in which family firms operate influences their behaviour and performance, yet literature reviews seldom analyse family firms on a regional basis. To fill this gap, this review aims to present research on family entrepreneurship in the transition economies of the Visegrád countries (V4). In this particular group of European economies, the current formal institutions have largely evolved along Western European lines. However, the transformation of informal institutions appears to be still in its infancy.Design/methodology/approach: In order to identify the most representative authors, the methodologies used, the main research topics and to establish a future research agenda, the authors selected, through a systematic process, 112 papers from the Web of Science up to the year 2022. The authors performed a bibliographic analysis using clustering algorithms, complemented by a traditional literature review.Findings: The performance of family firms in transition economies has been the subject of very little research. The results allowed the authors to identify four main areas of research: governance, innovation, sustainability, competitive advantage and considering the influence of the region's characteristics on family business behaviour.Originality/value: Studies from transition economies can contribute to a broader understanding of family firms in terms of the impact of the institutional environment (especially the influence of sociological changes and specific historical experiences of family members) on their long-term planning, socioemotional wealth (SEW) protection and ethics. In light of recent events, research from the region may also contribute to the understanding of how and to what extent “familiness” influences crisis management or socially responsible behaviour in family firms.

Family enterprises are considered to be one of the oldest and still dominant forms of business organisations. However, their innovation activity is an emerging area of research, especially in the Central and Eastern European region. The aim of our study is to address this research gap by investigating, with the help of statistical tools, the relationship between the familiness of the firms, their innovation activity, and their export activity on representative samples of Hungarian SMEs in the years 2017, 2020, and 2022. Our results suggest that the innovation activity of exporting Hungarian SMEs is more significant than that of non-exporting SMEs. However, the relationship between familiness and innovation activity is not uniform in the three analyzed years, and the relationship between familiness and export activity is not significant. The findings of this study, that firms’ innovation and exporting activities can be mutually reinforcing, can be used by policymakers, curriculum developers in business education, and entrepreneurs. One of the main limitations of our research is that the 2020 and 2022 surveys were conducted after the first wave of the COVID-19 pandemic and the shock of the Russian–Ukrainian war, respectively; thus, the decisions of the firms could have been influenced by the unpredictability of the external environment.

Entrepreneurship is deeply rooted in tradition and culture in many countries; however, transitional market economies in Central and Eastern Europe (CEE) underwent 40–45 years of socialism, which disrupted these traditions by collectivising private property. Education is recognised as a key tool for regional development and restoring entrepreneurial knowledge and skills, potentially enhancing entrepreneurial intentions within society. This paper investigates the impact of entrepreneurial education on entrepreneurial activity in transitional CEE countries. Pearson’s correlation analysis was conducted using a combined national-level dataset from the Annual Population Survey (APS) and the National Expert Survey of the Global Entrepreneurship Monitor (GEM) spanning 2021–2023. Results reveal inconsistent findings across the years. In 2021 and 2022, there was a significant moderate correlation between total early-stage entrepreneurial activity (TEA) and an indicator of entrepreneurial education at primary and secondary levels in CEE countries. In contrast, no such relationship was observed in other regions. In 2023, however, no significant correlations were identified for any country group. These results highlight the temporal variability of education’s influence on entrepreneurship in transitional economies.

Digitalisation presents a significant challenge for small- and medium-sized enterprises (SMEs), as they generally lack the required competencies and qualifications for a digital transformation. However, crises such as the COVID-19 pandemic have highlighted how digitalisation can improve SME efficiency and unlock new markets. This paper aims to contribute to the empirical literature by analysing the factors influencing Hungarian entrepreneurs' activities and attitudes towards digitalisation during the COVID-19 pandemic. The results are based on the quantitative analyses of Hungarian datasets of the Global Entrepreneurship Monitor (GEM) spanning 2021 to 2023, complemented by figures from a representative survey of SMEs in 2022. Our findings show that while nearly all SMEs utilise digital devices, adopting more advanced solutions remains low. Although the pandemic somewhat accelerated the digitalisation efforts, most entrepreneurs do not expect to use more digital solutions in the next six months. There is no consistent correlation between digitalisation and entrepreneurial motives, as the cluster analyses did not provide homogenous groups of entrepreneurs in the years analysed, so we can conclude that digitalisation efforts may be even among them. Thus, to overcome the challenge of digitalisation, policymakers should incentivise entrepreneurs to improve their digital skills and implement digital solutions.

Entrepreneurship and Sustainability Issues is a peer-reviewed journal which publishes original research papers and case studies

In our study, we examined the characteristics of nascent entrepreneurs using the 2021 Global Entrepreneurship Monitor national representative data in Hungary. We examined our topic based on Arenius and Minitti’s four-category theory framework. In our research, we examined system-level feature sets with four machine learning modeling algorithms: multivariate adaptive regression spline (MARS), support vector machine (SVM), random forest (RF), and AdaBoost. Our results show that each machine algorithm can predict nascent entrepreneurs with over 90% adaptive cruise control (ACC) accuracy. Furthermore, the adaptation of the categories of variables based on the theory of Arenius and Minitti provides an appropriate framework for obtaining reliable predictions. Based on our results, it can be concluded that perceptual factors have different importance and weight along the optimal models, and if we include further reliability measures in the model validation, we cannot pinpoint only one algorithm that can adequately identify nascent entrepreneurs. Accurate forecasting requires a careful and predictor-level analysis of the algorithms’ models, which also includes the systemic relationship between the affecting factors. An important but unexpected result of our study is that we identified that Hungarian NEs have very specific previous entrepreneurial and business ownership experience; thus, they can be defined not as a beginner but as a novice enterprise.