Este estudio se centra en identificar los factores que influyen en la percepción de la calidad del consumidor en restaurantes de servicio a mesa en el pueblo mágico Real del Monte, Hidalgo, México. La metodología se basa en dos perspectivas, en primer lugar, en el análisis de los factores más importantes de los resultados de una encuesta de 22 ítems por medio de redes neuronales artificiales aplicada a 320 comensales y, en segundo lugar, en la aplicación de entrevistas semiestructuradas a ocho comensales. Los hallazgos muestran que los aspectos fundamentales que influyen en la percepción de los consumidores son la capacidad del personal para responder preguntas, la música de fondo, así como la calidad y el sabor de los alimentos.

El Programa Jóvenes Construyendo el Futuro surge como una política para combatir el desempleo, subempleo y los bajos salarios en la población joven. El programa pretende capacitar y vincular a los jóvenes con el sector productivo, con la finalidad de que encuentren empleos estables y mejor remunerados. Algunos de los efectos potenciales de esta política pública podrían relacionarse con el crecimiento   económico e impactar en otros aspectos sociales (vivienda, salud, seguridad). Derivado de ello, el presente escrito tiene como objetivo realizar un análisis integral del programa, utilizando el modelo de etapas de Subirats, así como la definición de actores, recursos, reglas y componentes de la política pública y el modelo de Bardach, lo que permitirá efectuar algunas recomendaciones. Los hallazgos muestran que uno de los aspectos a mejorar en la implementación de este programa es el establecimiento de mecanismos de evaluación, por lo que se sugiere una modificación en las reglas de operación del programa, que incluyan los indicadores de evaluación de resultados, la focalización de beneficiarios, la creación de incentivos fiscales para los centros de trabajo participantes y una definición precisa de los planes de capacitación que potencien la vinculación con el sector productivo.

The COVID-19 pandemic has become a critical and disruptive event that has substantially changed the way people live and work. Although several studies have examined the effects of remote work on organizational outcomes and behaviors, only a few have inquired into how its opportune implementation impacts aggregate emotions over time. This chapter aims to conduct a sentiment analysis with public reactions on Twitter about telework during the pandemic period. The results showed fluctuations in emotional polarity, starting with a higher positive charge in the early pandemic scenarios that became weaker, and the negative polarity of emotions increased. Fear, sadness, and anger were the emotions that increased the most during the pandemic. Knowledge about people's sentiments about telework is important to complement organizational research and to complement the framework for the development of efficient telework implementation strategies.

The COVID-19 pandemic led to changes in consumer behavior, where social commerce played a relevant role. Through the theory of protection motivation as a theoretical basis, this chapter´s purpose is the analysis of consumer sentiment in the evolution of panic buying for which the authors identified the trend themes and some important influencers during the contingency. The results show that the leaders with the highest positive sentiment levels were the President of Taiwan and the Prime Minister of Australia. WHO was the influential account with the most negative sentiment during the pandemic. Relative to trending topics, the dataset with the highest positive sentiment is related to cleaning and disinfection products. The face mask data set had the highest negative sentiment and is the trending topic with the highest polarity. The trending topic on health foods, vitamins, and food supplements had the lowest polarity.

Public sector organizations are increasingly adopting artificial intelligence (AI). However, its implementation is creating controversy regarding its impact on the labor market (technological unemployment). The purpose of this chapter is to determine whether the idea that AI will replace human labor within the public sector is realistic, or it is too exaggerated. A systematic review of the literature and an analysis of cases in three different contexts were developed. The results show a framework that foresees positive future scenarios, and it is glimpsed that the relationship between humans and AI will be perfected over time to ensure that the benefits of this relationship are legitimate for public organizations.