Stochastic choice analysis of tourism destinations

The analysis of tourist destination choice, defined by intra-country administrative units and by product types “coastal/inland and village/city”, permits the characterisation of tourist flow behaviour, which is fundamental for public planning and business management. In this study, we analyse the determinant factors of tourist destination choice, proposing various research hypotheses relative to the impact of destination attributes and the personal characteristics of tourists. The methodology applied estimates Nested and Random Coefficients Multinomial Logit Models, which allow control over possible correlations among different destinations. The empirical application is realised in Spain on a sample of 3,781 individuals and allows us to conclude that prices, distance to the destination and personal motivations are determinants in destination choice.

Open business intelligence: on the importance of data quality awareness in user-friendly data mining

Citizens demand more and more data for making decisions in their daily life. Therefore, mechanisms that allow citizens to understand and analyze linked open data (LOD) in a user-friendly manner are highly required. To this aim, the concept of Open Business Intelligence (OpenBI) is introduced in this position paper. OpenBI facilitates non-expert users to (i) analyze and visualize LOD, thus generating actionable information by means of reporting, OLAP analysis, dashboards or data mining; and to (ii) share the new acquired information as LOD to be reused by anyone. One of the most challenging issues of OpenBI is related to data mining, since non-experts (as citizens) need guidance during preprocessing and application of mining algorithms due to the complexity of the mining process and the low quality of the data sources. This is even worst when dealing with LOD, not only because of the different kind of links among data, but also because of its high dimensionality. As a consequence, in this position paper we advocate that data mining for OpenBI requires data quality-aware mechanisms for guiding non-expert users in obtaining and sharing the most reliable knowledge from the available LOD.

COMENEGO (Corpus Multilingüe de Economía y Negocios): a metadiscursive analysis approach

This paper describes a stage in the COMENEGO project, which is creating comparable corpora of Business texts in order to distribute them among translation practitioners so that they can use this resource when translating economic, business or financial texts. This stage consists of discursive analysis of a pilot specialised corpus initially compiled in French and Spanish. Its textual resources are classified in different categories which need to be confirmed so that they can be useful when including them into the virtual platform which will allow users exploit the corpus and filter their searches according to their specific needs. The aim of this paper is to propose a discursive analysis approach based on the concept of ‘metadiscourse’ (Hyland, 2005).

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.

A Sociocybernetics Data Analysis Using Causality in Tourism Networks

The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Multi-Element Analysis of Spanish Date Palm (Phoenix dactylifera L.) by Inductively Coupled Plasma-Based Techniques. Discrimination Using Multivariate Statistical Analysis

The elemental analysis of Spanish palm dates by inductively coupled plasma atomic emission spectrometry and inductively coupled plasma mass spectrometry is reported for the first time. To complete the information about the mineral composition of the samples, C, H, and N are determined by elemental analysis. Dates from Israel, Tunisia, Saudi Arabia, Algeria and Iran have also been analyzed. The elemental composition have been used in multivariate statistical analysis to discriminate the dates according to its geographical origin. A total of 23 elements (As, Ba, C, Ca, Cd, Co, Cr, Cu, Fe, H, In, K, Li, Mg, Mn, N, Na, Ni, Pb, Se, Sr, V, and Zn) at concentrations from major to ultra-trace levels have been determined in 13 date samples (flesh and seeds). A careful inspection of the results indicate that Spanish samples show higher concentrations of Cd, Co, Cr, and Ni than the remaining ones. Multivariate statistical analysis of the obtained results, both in flesh and seed, indicate that the proposed approach can be successfully applied to discriminate the Spanish date samples from the rest of the samples tested.

The business of fashion in the nineteenth and twentieth centuries

Fashion is a complex social and cultural phenomenon with strong economic implications. Historical analysis reveals that the mechanisms of creating and spreading fashion have not remained constant, but have varied according to social structures, forms of producing and distributing apparel and social media, while the level of influence of fashion on society has increased in line with economic development. This special issue of Investigaciones de Historia Económica-Economic History Research is dedicated to fashion as an economic phenomenon in the contemporary period. The four articles which make it up show the plurality of the subject areas, sources and methodological approaches in the current research on this topic.

Application-Based Analysis of Register File Criticality for Reliability Assessment in Embedded Microprocessors

There is an increasing concern to reduce the cost and overheads during the development of reliable systems. Selective protection of most critical parts of the systems represents a viable solution to obtain a high level of reliability at a fraction of the cost. In particular to design a selective fault mitigation strategy for processor-based systems, it is mandatory to identify and prioritize the most vulnerable registers in the register file as best candidates to be protected (hardened). This paper presents an application-based metric to estimate the criticality of each register from the microprocessor register file in microprocessor-based systems. The proposed metric relies on the combination of three different criteria based on common features of executed applications. The applicability and accuracy of our proposal have been evaluated in a set of applications running in different microprocessors. Results show a significant improvement in accuracy compared to previous approaches and regardless of the underlying architecture.

Sensitivity Analysis in Convex Optimization through the Circatangent Derivative

The main goal of this paper is to analyse the sensitivity of a vector convex optimization problem according to variations in the right-hand side. We measure the quantitative behavior of a certain set of Pareto optimal points characterized to become minimum when the objective function is composed with a positive function. Its behavior is analysed quantitatively using the circatangent derivative for set-valued maps. Particularly, it is shown that the sensitivity is closely related to a Lagrange multiplier solution of a dual program.