The development of the personal innovative competences in workers is of capital importance for the competitiveness of organizations, where the ability of the employees must respond in an innovative way to diverse situations that arise in specific contexts. Considering this, the question arises: How do innovative employees’ competences affect the sustainable development of Micro, Small and Medium Enterprises (MSMEs)? Therefore, the objective of this work is to present a multi-criteria method based on the Analytic Network Process (ANP), to relate innovative personal competences and the sustainable development of MSMEs. An instrument was applied to groups of experts from 31 Ecuadorian fruit-exporting MSMEs, to develop a multi-criteria decisional network that allowed identifying the innovative personal abilities that have the greatest impact on the sustainable development of these organizations. The results demonstrate the relevance of the elements of innovative personal competencies, with a cumulative participation of 39.15%, Sustainable Export Development with 32.18% and Improvements with 28.66%. It also presents three types of analysis: i) Global to establish the weight of each variable; ii) Influences, to establish solid cause-effect relationships between the variables and iii) Integrated. The most relevant innovative personal competences for sustainable development and improvements for exporting SMEs are teamwork, critical thinking, and creativity within the international context.

Foodborne diseases are a global health problem. Every year, millions of people die worldwide from these diseases. It has been determined that the high prevalence of these diseases is related to unfavorable socioeconomic conditions of the population. In this study, the relationship between foodborne diseases and socioeconomic conditions of the population was determined using principal component analysis as a multivariate statistical analysis technique. In this study, the socioeconomic variables of each Ecuador province and the prevalence of foodborne diseases (hepatitis A, salmonella, shigellosis and typhoid fever) during the years 2018 and 2019 were considered. The results show the relationship between foodborne diseases and the socioeconomic conditions of the population, as well as identifying regions more vulnerable to present high levels of prevalence of foodborne diseases, thus facilitating the implementation of social investment programs to reduce the prevalence of these diseases.

This study evaluates the effectiveness of measures aimed at reducing traffic violations, specifically focusing on wrong-way driving, at intersections in Loja, Ecuador. The high incidence of accidents at these intersections, often resulting from wrong-way driving and non-compliance with traffic regulations, underscores the critical need for effective strategies to enhance road safety. To address this issue, we adopted a multidisciplinary approach to assess the impact of two specific interventions: the implementation of official warnings and the presence of traffic officers at a selected intersection. Data collection involved recording instances of traffic violations, administering road safety surveys, and monitoring the implementation of these interventions. The post-implementation analysis sought to determine the effect of these measures on driver behavior and overall traffic safety. Our findings indicate that while the interventions succeeded in increasing awareness about traffic violations, they did not produce a significant reduction in undesirable driving behaviors. This suggests that, although the presence of warnings and traffic officers is beneficial in raising awareness, these measures alone may not be sufficient to effect substantial behavioral changes. The research provides valuable insights for the development of more comprehensive road safety strategies and emphasizes the need for further studies to explore and address the underlying causes of traffic violations.

Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.