Hospital supply chains are responsible for several economic inefficiencies, negative environmental impacts, and social concerns. However, a lack of research on sustainable supply chain management specific to this sector is identified. Existing studies do not analyze supply chain management practices in an integrated and detailed manner, and do not consider all sustainable performance dimensions. To address these gaps, this paper presents a systematic literature review and develops a framework for identifying the supply chain management practices that may contribute to sustainable performance in hospitals. The proposed framework is composed of 12 categories of management practices, which include strategic management and leadership, supplier management, purchasing, warehousing and inventory, transportation and distribution, information and technology, energy, water, food, hospital design, waste, and customer relationship management. On the other side, performance categories include economic, environmental, and social factors. Moreover, illustrative effects of practices on performance are discussed. The novelty of this document lies in its focus on hospital settings, as well as on its comprehensiveness regarding the operationalization of practices and performance dimensions. In addition, a future research agenda is provided, which emphasizes the need for improved research generalizability, empirical validation, integrative addressing, and deeper analysis of relationships between practices and performance.

El objetivo de este artículo es predecir el rendimiento académico de estudiantes de educación superior, a partir de diversos factores influyentes usando técnicas de inteligencia artificial (clasificadores). El estudio de tales factores, aunque ha sido ampliamente analizado desde enfoques cuantitativos y cualitativos, aun presenta oportunidades de investigación usando herramientas que provee la inteligencia artificial, particularmente en la predicción del rendimiento académico. Con los factores definidos (educacionales, familiares, socioeconómicos, de hábitos y costumbres, entre otros), se diseñó una metodología que permite entrenar un sistema capaz de clasificar a priori a un nuevo estudiante, en una de las cinco categorías predeterminadas de rendimiento académico. Esta clasificación permite a una institución educativa identificar con anticipación estudiantes con problemas potenciales de rendimiento académico. A partir de ello, se pueden desplegar acciones de acompañamiento y mitigación inmediatas. La metodología fue aplicada a una muestra de estudiantes de una universidad pública en Colombia, obteniendo un nivel de aciertos del 91.7%.

Purpose: Assessment of manufacturing systems provides a baseline for manufacturing strategy (MS) formulation. The purpose of this paper is to develop and propose a maturity assessment model for manufacturing systems (MAMMS). The MAMMS provides a maturity index, in order to establish manufacturing system performance on five possible levels: preinfantile, infantile, industry average, adult, and world class manufacturing.Design/methodology/approach: Three main steps were taken: MAMMS design; maturity-level assessment in two companies; and MAMMS validation. Based on an action-research process, several research tools, such as surveys, expert panels, and immersion in two manufacturing companies, were used.Findings: By integrating 79 variables into a maturity index, the maturity level for two manufacturing companies was obtained. Considering three main components (competitive priorities, manufacturing levers, and manufacturing’s strategic role), the analyzed companies showed a performance at the average industry level. According to participants, the MAMMS is a valuable tool to support decision making in MS.Practical implications: Empirical evidence supports the relevance of the proposed MAMMS and its practical usefulness. In particular, the maturity index identifies strengths and weaknesses in the manufacturing system, providing a baseline from which to deploy MS.Originality/value: The literature review shows a lack of contributions regarding maturity models, particularly, the non-existence of maturity assessment models for manufacturing systems. The proposed MAMMS is a valuable tool to support decision making in MS. Also, this paper contributes to understanding the action-research paradigm, for further research in operations management.

Purpose: From the green supply chain management (GSCM) approach, the purpose of this paper is to propose a green index as a benchmarking tool to assess environmental performance in manufacturing companies. The index involves 10 green practices and 46 performance dimensions, which were identified by way of an exhaustive literature review. Design/methodology/approach: The GSCM index was designed as follows: survey design; experts group selection; relationship identification and green practice weighting (DEMATEL method); and GSCM index construction. The proposed GSCM index was validated at a set of ten Colombian manufacturing companies, which belong to different industrial subsectors. Findings: The structural relationships between both green practices and performance dimensions (cause group vs effect group) were determined. Consequently, a set of green practices and performance dimensions on which managers must focus their environmental efforts (cause group), in order to positively affect the system as a whole, was identified. The environmental performance of a set of manufacturing companies was established. Practical implications: As a decision support tool, the GSCM index provides a baseline for the deployment of environmental improvement plans. It also permits the comparison of environmental performance between companies from different industrial sectors. Further, it can be used to monitor internal operations and collaboration programs in each echelon of the supply chain. Originality/value: This publication contributes to the field of environmental performance measurement by introducing a new index, from the GSCM perspective. In contrast with the existing green indicators, the proposed index is the first to consider causal relationships between green practices and between their performance dimensions.

El presente artículo presenta los principales resultados de un análisis bibliométrico basado en 432 publicaciones (periodo 2011-2016), tomadas de bases de datos relevantes, sobre el tema de la logística humanitaria. La logística humanitaria se ha convertido en un área de investigación fértil debido a su importancia estratégica para gobiernos, comunidades y empresas. Este campo de estudio emergió como consecuencia de las debilidades logísticas para enfrentar grandes desastres tales como el tsunami del Océano Índico (2004) y el huracán Katrina (2005), entre otros. Como tema de investigación, la logística humanitaria se proyecta como uno de los de mayor crecimiento en los próximos diez años. Aunque algunos trabajos previos han abordado este tópico desde la perspectiva de la revisión de literatura, la mayoría se centran en un análisis de contenido desde una perspectiva cualitativa y, en consecuencia, el uso de enfoques bibliométricos es escaso. En este trabajo se exponen las principales tendencias bibliométricas y se identifican algunos vacíos de conocimiento desde cinco perspectivas de análisis.

En este artículo se realiza un estudio sobre las principales variables que afectan el abandono estudiantil. Se predice el comportamiento del abandono estudiantil (variable dependiente) usando 25 variables independientes agrupadas en 5 categorías: personales, económicas, sociales, familiares y académicas. Estas fueron muestreadas sobre una población de 410 estudiantes. Mediante un análisis estadístico multivariado, se seleccionaron aquellas más influyentes para estructurar un archivo que fue analizado por el algoritmo J48 de la plataforma Weka. Los resultados muestran que, con una efectividad superior al 80%, las variables más influyentes en el abandono estudiantil son: pedagogía de los profesores, sentimiento de frustración, importancia del programa, expectativas insatisfechas, motivación del programa y procrastinación. Variables como promedio académico y edad de ingreso parecen no tener mayor relevancia. Se concluye que los resultados aportan información útil para el despliegue de estrategias universitarias orientadas a reducir el abandono estudiantil.