Due to the digital transformation, organizations have incorporated technologies in all areas of the company, creating digital business ecosystems. These in turn, with the tools that compose it, influence the satisfaction of stakeholders and business performance. The objective of this research is to know how the digital business ecosystem affects customer and employee satisfaction and whether this satisfaction has an impact on business performance. To achieve this objective, a model is proposed to which a PLS technique is applied to a sample of 1319 Spanish SMEs. The results of this innovative study show, on the one hand, a positive relationship of the digital business ecosystem with the satisfaction of both stakeholders, and, on the other hand, and as the main contribution of this study, it has been found that employee satisfaction positively influences business performance. This research offers a novel model capable of relating how the satisfaction of both customers and employees in a digital environment improves business performance. It also contributes to the literature by widening the field of study and overcomes a new gap for SMEs.

Innovation has traditionally been related to unemployment because people are replaced by machines. By analyzing the different approaches in the literature, we focused on the relationship between innovation and employment with the aim of exploring whether the most innovative companies create more employment, or hope to create it, taking into account the company performance. For this purpose, we performed multivariate analysis, using the partials least squares (PLS) technique, to study the direct and indirect relationship between business innovation and employment through the economic and financial performance of the company, focusing on Spanish companies in the year 2022. The results obtained show that innovation has a positive effect on employment and on the performance of the company, and thus on the creation of employment. In conclusion, the administration should encourage business innovation to improve employment rates and company performance.

This study examines whether the mechanisms underlying entrepreneurial intention formation remain stable under conditions of extreme socio-economic disruption. Drawing on the Theory of Planned Behavior (TPB), we analyze the relationships between entrepreneurial education, attitudes, subjective norms, perceived behavioral control, and entrepreneurial intentions across two cohorts: pre-pandemic and during the Covid-19 pandemic. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) and multi-group analysis (MGA), we assess both direct relationships and contextual differences. Results confirm the robustness of the TPB framework. Attitudes and perceived behavioral control emerge as consistent predictors of intentions, while subjective norms exhibit a weaker effect. Entrepreneurial education shows a nuanced pattern, functioning as a predictor of attitudes, subjective norms, and perceived behavioral control only during the Covid-19 period, albeit with modest effect sizes. Multi-group analysis reveals structural stability, with most relationships remaining invariant. However, statistically significant differences are identified in the paths between entrepreneurial education and perceived behavioral control, and between subjective norms and entrepreneurial intentions; the strength of both diminishes during the pandemic. In conclusion, entrepreneurial intention formation demonstrates structural resilience. Rather than altering the cognitive model, the pandemic generates selective, modest adjustments, particularly regarding the translation of educational inputs into perceived feasibility and the role of social influence. This study contributes to the literature by integrating intention-based theory with a crisis-context perspective, providing empirical evidence on the stability of entrepreneurial cognition under heightened uncertainty.