Factores explicativos del éxito competitivo. Un estudio empírico en la pyme

[ES] Identificar el origen de la competitividad, a pesar de ser un tema controvertido, es algo a lo que investigadores, consultores y directivos dedican grandes esfuerzos. El hecho de que la mayoría de los estudios dirijan su atención hacia niveles macroeconómicos o se centren en la gran empresa nos lleva en este trabajo a identificar, basándonos en la literatura, los factores de éxito competitivo específicos de las pyme. A continuación, tras analizar cómo medir el éxito competitivo, se realiza un estudio empírico con una muestra de 473 pyme de la Región de Murcia para determinar cuáles son los factores explicativos de su éxito. Los resultados del estudio confirman parcialmente los recogidos en la literatura. Del trabajo se extraen interesantes conclusiones tanto relativas a cuáles son los factores explicativos del éxito en las pyme como de cara a la realización de nuevas investigaciones sobre este tema.

Morals in business organizations: an approach based on strategic value and strength for business management

[EN] In the last decades, the topic of business ethics has attracted great interest at the academic and professional levels. Nowadays business ethics is being increasingly implemented as a necessary discipline in universities’ study plans on business management. Moreover, its importance is also evident according to the worldwide increase of organizations and/or institutions that have implemented ethics systems. However, some approaches thoroughly do not consider the importance and the need of an ethical behaviour and are still guiding the actions and the way of thinking of many academics and professionals led to consider that the only responsibility of business is limited just to profit maximization.

New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination

Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.

Fiabilidad de diferentes pruebas que se utilizan para evaluar el riesgo de lesión del miembro inferior en mujeres deportistas

233 p. : il. + anexo (247 p.)

Neurolinguistic measure of typological effects in multilingual transfer: introducing an ERP methodology

This article has two main objectives. First, we offer an introduction to the subfield of generative third language (L3) acquisition. Concerned primarily with modeling initial stages transfer of morphosyntax, one goal of this program is to show how initial stages L3 data make significant contributions toward a better understanding of how the mind represents language and how (cognitive) economy constrains acquisition processes more generally. Our second objective is to argue for and demonstrate how this subfield will benefit from a neuro/psycholinguistic methodological approach, such as event-related potential experiments, to complement the claims currently made on the basis of exclusively behavioral experiments. Palabras clave

Cosmological constrains on fast transition Unified Dark Matter models

In this work we show the results obtained applying a Unified Dark Matter (UDM) model with a fast transition to a set of cosmological data. Two different functions to model the transition are tested, and the feasibility of both models is explored using CMB shift data from Planck [1], Galaxy Clustering data from [2] and [3], and Union2.1 SNe Ia [4]. These new models are also statistically compared with the ACDM and quiessence models using Bayes factor through evidence. Bayesian inference does not discard the UDM models in favor of ACDM.