Microfoundations of strategic management: Toward micro–macro research in the resource-based theory

Over the last few years, a new stream of research has emerged in the field of strategic management which focuses on the analysis of its microfoundations. This line of research analyzes strategic topics examining their foundations rooted in individual actions and interactions. The main purpose of this paper is to examine this emerging literature of microfoundations, indicating its usefulness and main characteristics. Through a systematic literature review, this paper contributes to the field by identifying the main areas studied, the benefits and potential of this approach, and some limitations and criticisms. Moreover, the paper studies how the integration of micro and macro aspects in strategy research may be carried out, examining several works that use a multilevel approach. Some methodological approaches that may help to effect this integration are indicated. These aspects will be analyzed in relation to the resource-based theory.

Impacto de las instalaciones sobre el desempeño del sector hotelero español

El sector hotelero, productor primario del sector turístico, tiene una gran relevancia para la economía española. Sin embargo, está inmerso en un entorno global y está sujeto a fuertes cambios. Por lo tanto, ante esta situación de incertidumbre, el sector hotelero debe identificar y analizar cuáles son sus fuentes de ventaja competitiva para mejorar su competitividad futura y adaptarse correctamente a los retos de su entorno. En este estudio, realizado desde la Teoría de Recursos, se argumenta la importancia de las instalaciones hoteleras y se ofrecen múltiples razones para que sean consideradas fuente de ventaja competitiva para mejorar la capacidad de competir de los hoteles. De esta forma, en esta investigación empírica, se realiza un estudio descriptivo del nivel de desarrollo de las instalaciones hoteleras y se demuestra que tienen un impacto significativo sobre el desempeño que alcanzan los hoteles de tres a cinco estrellas de toda España.

Diversity for Texts Builds in Language L(MT): Indexes Based in Theory of Information

If one has a distribution of words (SLUNs or CLUNS) in a text written in language L(MT), and is adjusted one of the mathematical expressions of distribution that exists in the mathematical literature, some parameter of the elected expression it can be considered as a measure of the diversity. But because the adjustment is not always perfect as usual measure; it is preferable to select an index that doesn't postulate a regularity of distribution expressible for a simple formula. The problem can be approachable statistically, without having special interest for the organization of the text. It can serve as index any monotonous function that has a minimum value when all their elements belong to the same class, that is to say, all the individuals belong to oneself symbol, and a maximum value when each element belongs to a different class, that is to say, each individual is of a different symbol. It should also gather certain conditions like they are: to be not very sensitive to the extension of the text and being invariant to certain number of operations of selection in the text. These operations can be theoretically random. The expressions that offer more advantages are those coming from the theory of the information of Shannon-Weaver. Based on them, the authors develop a theoretical study for indexes of diversity to be applied in texts built in modeling language L(MT), although anything impedes that they can be applied to texts written in natural languages.

Algorithm for the detection of outliers based on the theory of rough sets

Outliers are objects that show abnormal behavior with respect to their context or that have unexpected values in some of their parameters. In decision-making processes, information quality is of the utmost importance. In specific applications, an outlying data element may represent an important deviation in a production process or a damaged sensor. Therefore, the ability to detect these elements could make the difference between making a correct and an incorrect decision. This task is complicated by the large sizes of typical databases. Due to their importance in search processes in large volumes of data, researchers pay special attention to the development of efficient outlier detection techniques. This article presents a computationally efficient algorithm for the detection of outliers in large volumes of information. This proposal is based on an extension of the mathematical framework upon which the basic theory of detection of outliers, founded on Rough Set Theory, has been constructed. From this starting point, current problems are analyzed; a detection method is proposed, along with a computational algorithm that allows the performance of outlier detection tasks with an almost-linear complexity. To illustrate its viability, the results of the application of the outlier-detection algorithm to the concrete example of a large database are presented.