RESUMEN: La realidad y la literatura científica de la empresa social han ido adquiriendo mayor relevancia durante los últimos años en España, aunque no ha llegado a equipararse a los niveles de otros países europeos, en los cuales el concepto goza de un mayor reconocimiento y desarrollo. Si bien se pueden identificar ejemplos de empresas sociales en nuestro país desde el siglo XV, no es hasta hace una década cuando se ha acuñado el concepto de manera más generalizada.Nuestro objetivo es identificar los modelos de empresa social existentes en España sobre cada uno de los enfoques considerados en la literatura específica de empresa social.Partiendo de la metodología y el trabajo desarrollado dentro del proyecto ICSEM (equipo español), estableceremos una clasificación de los distintos modelos de empresas sociales, utilizando como referencia las fronteras conceptuales de cuatro realidades socioeconómicas presentes en España: la economía social, el Tercer Sector de Acción Social, la economía solidaria y el Emprendimiento Social.Como resultado más relevante obtenemos una nueva perspectiva de análisis de las empresas sociales, contribuyendo así al debate actual de delimitación del concepto y realidad de la empresa social, en España en particular, y en la esfera académica en general.

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In order to analyse, manage, and compare social projects we need, among other things, to be able to measure their impact. One of the methodologies currently used to measure and manage social impact is Social Return on Investment (SROI). However, not all the results calculated by the SROI method are directly attributable to the project, and, therefore, to determine the real impact it is necessary to filter out the changes that the project has not produced. Filter coefficients perform this function. However, the theoretical logic on which the chain is constructed that converts the outputs into impacts is ambiguous. In this study, we will analyse twenty-five real cases where SROI was used to measure social projects. We will identify the difficulties of isolating and measuring impacts by performing a comparative study of the procedures that entities develop to calculate the filters. This allows us to calculate the impacts from the outputs. We will then propose the improvements needed to overcome these shortcomings.

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Given that the creation of successful interactions and collaboration networks develops into sustainable and successful social entrepreneurial organisations, learning communities can serve as an ideal environment to train students in social entrepreneurship. This paper describes massive open online learning communities as an appropriate methodology for the distance teaching of social entrepreneurship and how the students on a massive online open course in social entrepreneurship commit to the learning community generated in this virtual environment. Data from a pioneer social entrepreneurship massive open online learning communities were analysed using three statistical methodologies. The analysis demonstrates that a student's commitment to the distance learning community is directly related to his degree of participation, the rewards received, his correspondence with the other students and recognition from the other members of the community.