Social responsibility is a key element in meeting the needs of the context in which an organization operates. In the healthcare sector, attention to this concept has involved studying internal aspects, as well as the contribution to its implementation in the management of processes and practices of the organization's agents. In order to analyze the relationship between social responsibility and hospital culture, a mixed study was conducted in two phases. First, a focused ethnography was implemented, followed by a systematic review study. The results showed a poor conceptual development of the category, the importance of organizational ethics, the values in the regulation exerted by hospital culture on social responsibility, and the need for the dual nature of social responsibility in terms of its design as an instrument or strategy of the organization. It is concluded that achieving a better operationalization of social responsibility is necessary for its reproduction in the hospital culture, as such responsibility must be promoted as an individual practice based on a solid worldview, and from this achievement, consolidated as a set of identifiable actions. Thus, quality must be a crossing in the design and description of the dimensions and indicators of social responsibility and an organizational value.

The patient flow, referring to the movement of patients through a healthcare institution, is essential for resource optimization, performance enhancement, and satisfaction level elevation within hospitals. The diagnosis of this flow is pivotal as it allows the identification of primary management inefficiencies. This research introduces a methodology structured in five stages for diagnosing patient trajectory management, integrating strategic and operational perspectives. After its implementation in a General Surgery service of a second-level hospital, its applicability was validated. The key deficiencies detected were grouped into essential variables for patient flow management. This methodology offers a holistic approach for healthcare administrators to evaluate the patient's journey within the hospital setting comprehensively.

The study focused on the management control of sustainability related to transportation in historic centers, given its influence on the social development of these areas. The primary purpose was to establish a system of indicators to monitor transportation sustainability in such centers. Techniques such as literature review, surveys, direct observation, expert consultations, and brainstorming were employed to achieve this. Various thematic models were analyzed, supported by software tools such as Microsoft Office Excel 2010, Microsoft Office Visio 2010, and EndNote X7. As a result of this research, twenty indicators were identified, meticulously described, and categorized under three sustainability perspectives: social, economic, and environmental. These indicators, derived from strategic objectives, are essential to assess the effects of transportation in historic centers and to facilitate prompt interventions that mitigate negative impacts, thereby improving the quality of life and urban sustainability

Supply chains play a critical role in the functioning of the global economy. The integration of information systems and emerging technologies, such as artificial intelligence and the Internet of Things, improves visibility, decision making and responsiveness throughout the supply chain. The objective of the research is to analyze research trends on the implementation of artificial intelligence to supply chain management. The research paradigm was quantitative, based on a descriptive, retrospective and bibliometric study, in the SCOPUS database, during the period from 2019 to 2024, without language restriction. The trend of research was positive and towards increase with a maximum peak in the year 2023 of 214 researches, research articles in the area of computer science predominated. The top producing country was the United Kingdom with 127 research papers and four lines of scientific research were identified around the implementation of artificial intelligence in supply chain management. In the business environment, the ability of supply chains to adapt to change is crucial; their management includes planning and coordination, logistics process management and customer relationship management. The integration of information systems and emerging technologies, such as artificial intelligence, has had a great impact on the improvement of all the processes involved in management.

Logistics has a significant impact on gentrification processes, as it facilitates the transformation of urban areas by improving connectivity and access to essential services, can lead to the arrival of large commercial chains and the modernization of local services, which transforms the cultural identity of the community and exacerbates social tensions between new and old inhabitants. The objective is to analyze the scientific production related to the impacts of logistics on gentrification processes. A quantitative type of research was developed, based on a retrospective and descriptive study, with a bibliometric approach, in the SCOPUS database during the period from 1987 to 2024, without language restriction. The behavior of the research was heterogeneous, with a predominance of research articles with 39 in the area of social sciences. The most productive country was the United States with research that directly influences the transformation of urban areas and the dynamics of the housing market. Two lines of scientific research related to residential segregation and its effects on the health of Caucasian adults and gentrification and its effects on the housing market in urban areas were identified. Logistics significantly impacts urban gentrification processes by improving connectivity and access to essential services, attracting new, higher-income residents and transforming the community's cultural identity, which poses challenges in terms of equity and social sustainability

Artificial intelligence is revolutionizing hospital management by optimizing critical processes to improve operational efficiency. The automation of administrative tasks allows reducing errors and streamlining the flow of patients and work, which translates into lower costs and better use of hospital resources. The objective is to analyze research related to the optimization of hospital processes based on artificial intelligence. The research paradigm was qualitative-quantitative, the focus of this research was based on a bibliometric analysis, which was complemented with a documentary review in databases of high international and Latin American impact in the period from 2010 to 2024. The trend of the research was towards an increase, where research in the area of medicine and computer sciences predominated. A keyword co-occurrence and citation analysis were carried out to identify possible lines of research. It was identified that monitoring and predictive analytics technologies based on artificial intelligence enable proactive management of patients' health, preventing complications and optimizing resource allocation. These tools also facilitate the personalization of care, adjusting treatments according to the specific needs of each patient. The implementation of artificial intelligence in hospital processes is a crucial tool for improving operational efficiency and reducing costs through the automation of administrative tasks, resulting in a smoother and more effective operation