Grupos estratégicos en el sector hotelero español: diferencias de desempeño intra e intergrupo

El mundo es cada vez más pequeño debido a los avances tecnológicos y a la mayor experiencia de los directivos hoteleros y de los turistas, lo que provoca que la rivalidad entre destinos en el sector turístico sea cada vez mayor. Ante esta situación, este estudio se centra en el sector hotelero español y aplica los grupos estratégicos para determinar de qué forma compiten los hoteles y cómo influyen sus comportamientos estratégicos en su desempeño. Asimismo, se ofrecen acciones para mejorar el desempeño de un hotel en función del grupo estratégico al que pertenezca. La relevancia de este estudio radica en que clarifica la complejidad estratégica a la que están sometidos los directivos de los hoteles y les sirve de guía para la toma de decisiones estratégicas.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.

Modernizing Secure OLAP Applications with a Model-Driven Approach

The majority of the organizations store their historical business information in data warehouses which are queried to make strategic decisions by using online analytical processing (OLAP) tools. This information has to be correctly assured against unauthorized accesses, but nevertheless there are a great amount of legacy OLAP applications that have been developed without considering security aspects or these have been incorporated once the system was implemented. This work defines a reverse engineering process that allows us to obtain the conceptual model corresponding to a legacy OLAP application, and also analyses and represents the security aspects that could have established. This process has been aligned with a model-driven architecture for developing secure OLAP applications by defining the transformations needed to automatically apply it. Once the conceptual model has been extracted, it can be easily modified and improved with security, and automatically transformed to generate the new implementation.