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.

This study examines the determinants of stunting prevention among toddlers in fishing families residing in the coastal areas of Bengkulu City. Utilizing a mixed-method approach, the research combined survey data from 70 respondents and in-depth interviews with 11 informants. Findings indicate that health behavior and genetic factors from health status, alongside education level and occupation from socioeconomic status, play pivotal roles in stunting prevention. Consumption patterns, particularly the consistent provision of animal protein and vegetables in daily meals, significantly contribute to the absence of stunting cases in the studied population. However, limited fruit intake persists due to economic barriers. The study underscores the necessity of integrated strategies, including nutrition education, enhanced access to nutritious foods, and economic support for fishing families, to sustain stunting prevention in coastal communities.

The advent of Artificial Intelligence (AI) has transformed Learning Management Systems (LMSs), enabled personalized adaptation and facilitated distance education. This study employs a bibliometric analysis based on PRISMA-2020 to examine the integration of AI in LMSs from an educational perspective. Despite the rapid progress observed in this field, the literature reveals gaps in the effectiveness and acceptance of virtual assistants in educational contexts. Therefore, the objective of this study is to examine research trends on the use of AI in LMSs. The results indicate a quadratic polynomial growth of 99.42%, with the years 2021 and 2015 representing the most significant growth. Thematic references include authors such as Li J and Cavus N, the journal Lecture Notes in Computer Science, and countries such as China and India. The thematic evolution can be observed from topics such as regression analysis to LMS and e-learning. The terms e-learning, ontology, and ant colony optimization are highlighted in the thematic clusters. A temporal analysis reveals that suggestions such as a Cartesian plane and a league table offer a detailed view of the evolution of key terms. This analysis reveals that emerging and growing words such as Learning Style and Learning Management Systems are worthy of further investigation. The development of a future research agenda emerges as a key need to address gaps.

With the rapid development of artificial intelligence (AI) technology, its application in the field of auditing has gained increasing attention. This paper explores the application of AI technology in audit risk assessment and control (ARAC), aiming to improve audit efficiency and effectiveness. First, the paper introduces the basic concepts of AI technology and its application background in the auditing field. Then, it provides a detailed analysis of the specific applications of AI technology in audit risk assessment and control, including data analysis, risk prediction, automated auditing, continuous monitoring, intelligent decision support, and compliance checks. Finally, the paper discusses the challenges and opportunities of AI technology in audit risk assessment and control, as well as future research directions.