Abstract The aim of this research is to understand the relationship between sustainability and entrepreneurship of small tourism enterprises in an area of high environmental value (tourist environment) which has been threatened in different ways (e.g., COVID-19, tourist pressure, natural phenomena, pollution, etc.), considering the mediating effect of the values of the entrepreneur and the tourist environment. This is a quantitative study, using a multivariate second-order hierarchical component model. Partial least squares structural equation modelling was used for the analysis. The results indicate that sustainability alone is not sufficient for entrepreneurship. However, if sustainability is mediated by the values of the entrepreneur and the tourism environment, it does have a positive impact on entrepreneurship. Furthermore, these variables have a positive effect on entrepreneurship, therefore these values of the entrepreneur are revealed as a driver of a sustainable economic model. This work has significant implications for decision-making regarding the importance of sustainable entrepreneurship in an environmentally threatened coastal area. It is recommended that tourism companies invest in sustainable tourism actions to preserve the local environment because of its positive influence on stakeholders. This research fills a gap in the literature on the relationship between sustainability, entrepreneur values, environment and entrepreneurship. It highlights the importance of context-specific contingencies for sustainability and the impact of entrepreneurship. The study provides a novel framework for understanding the process of social change towards sustainable tourism led by the entrepreneur and his or her values. The study is limited to a very specific area of high ecological value, so we consider that it can be extrapolated to similar areas.

Abstract The aim of this paper is twofold. Firstly, to analyse the international behaviour of academic spin-offs to explore the internationalisation patterns followed by these companies, considering precocity, scale, and scope as the key dimensions of the internationalisation process. The second objective is to discern whether academic spin-offs that follow different patterns present distinctive characteristics. To test the hypotheses, a cluster analysis, a series of ANOVA analyses of variance and post hoc tests were performed on a sample of 161 Spanish academic spin-offs. Results show that 49% of these firms do not internationalise and that three patterns of internationalisation exist in academic spin-offs: true born global, sporadic born global, and born again global. On the other hand, the results also reveal distinctive antecedent factors among the different internationalisation patterns. Thus, international industrial networks and management team functional heterogeneity are more relevant in academic spin-offs that follow the true born global and the born again global patterns, while global technological competence is significant for all three internationalisation patterns, and international academic networks present minor importance for the internationalisation process developed by academic spin-offs.

Abstract The differences in Labour and Capital Productivity and Education in Europe were used to provide a comprehensive evaluation of the performance of technical efficiency of entrepreneurship activities and new firm creation. For this purpose, two distinct methodologies were used: a non-parametric Data Envelopment Analysis (DEA) and a parametric Stochastic Frontier Analysis (SFA). Firstly, to obtain the ranking for assessing entrepreneurship efficiency, two outputs (birth rate and total early-stage entrepreneurial activity) were combined, and four inputs (long-term unemployment rate, household disposable income ratio S80/S20; young people neither in employment nor in education or training and employment rate of recent graduates) were applied. In the second step, two estimators were used to examine the effect of capital productivity, labour productivity, non-qualified labour, and population share of education on the technical efficiency score of entrepreneurial outcomes. The estimators were the Tobit regression, including random effects and mixed effects models, and the quantile regression model. The results for technical efficiency in the first step reveal that during 2008–2014 and after this period, 2015–2019, the European countries of Lithuania, Estonia and the Netherlands present the highest efficiency scores according to the DEA-CRS model. Applying the SFA technique, Belgium, Germany, and Malta show the highest levels of inefficiency during both periods of financial crisis. The second stage results demonstrate that there was a negative and significant effect of capital productivity on the efficiency scores of entrepreneurial outcomes in the periods of financial crises. This statistical evidence mirrors the observed decrease in average EU investments in fixed capital, structural changes in the labour market, and structural changes in education level in the active and inactive population, particularly in countries with economic growth, during the sub-periods between 2008 and 2019 under consideration.