This study aims to identify the main characteristics of the activities concentrating on R & D and innovation in the industrial sector of high and medium-high technology, and also the main differences with regard to non technological sectors. In order to do so we use data on 1540 manufacturing companies in Spain in two subgroups according to the National Classification of Economic Activities (CNAE). The data correspond to the values of 44 variables organised into 5 blocks of activity that have to do with R & D and innovation. The study includes an exploratory-descriptive analysis with the aim of providing information, and evidence of the outstanding characteristics of sectors with more technological components compared with other industrial manufacturing sectors. Although the study refers to Spanish companies, a large proportion of the results are easily transferrable to similar socioeconomic environments.

This work seeks to provide a new multi-criteria approach to assess IT Governance (ITG) in the area of Strategic Alignment. The complete methodological development process is described. The evaluation model uses Fuzzy Analytic Hierarchy Process (FAHP) and it is targeted to IT processes, more specifically to the COBIT© IT maturity levels, domains and processes, thus providing a differentiated analysis of importance for each item. Its relevance is related to addressing isolated and individual evaluation criteria that are normally practiced in audits of processes. The model allows generating information that extends the guarantees of compliance and corporate governance from different organizations. This research demonstrates that the combined use of multi-criteria decision methodologies and soft computing proves to be particularly suitable for Strategic Alignment such as the focal area of COBIT. The model was applied in a big retail Brazilian company.

Different theories of organization and management are based on implicit images or metaphors. Nevertheless, a quantitative approach is needed to minimize human subjectivity or bias on metaphors studies. Hence, this paper analyzed the presence of metaphors and clustered them using fuzzy data mining techniques in a sample of 61 Brazilian companies that operate in the state of Rio Grande do Sul. For this purpose the results of a questionnaire answered by 198 employees of companies in the sample were analyzed by R free software. The results show that it is difficult to find a clear image in most organizations. In most cases characteristics of different images or metaphors are observed, so soft computing techniques are particularly appropriate for this type of analysis. However, according to these results, it is noted that the most present image in the organizations studied is that of "organisms" and the least present image is that of a "political system" and of an "instrument of domination".

This paper presents a document representation strategy and a bio-inspired algorithm to cluster multilingual collections of documents in the field of economics and business. The proposed approach allows the user to identify groups of related economics documents written in Spanish and English using techniques inspired on clustering and sorting behaviours observed in some types of ants. In order to obtain a language independent vector representation of each document two multilingual resources are used: an economic glossary and a thesaurus. Each document is represented using four feature vectors: words, proper names, economic terms in the glossary and thesaurus descriptors. The proper name identification, word extraction and lemmatization are performed using specific tools. The tf-idf scheme is used to measure the importance of each feature in the document, and a convex linear combination of angular separations between feature vectors is used as similarity measure of documents. The paper shows experimental results of the application of the proposed algorithm in a Spanish-English corpus of research papers in economics and management areas. The results demonstrate the usefulness and effectiveness of the ant clustering algorithm and the proposed representation scheme.

Este artículo presenta una estrategia de representación documental y un algoritmo bioinspirado para realizar procesos de agrupamiento en colecciones multilingües de documentos en las áreas de la economía y la empresa. El enfoque propuesto permite al usuario identificar grupos de documentos económicos relacionados escritos en español o inglés usando técnicas inspiradas en comportamientos de organización y agrupamiento de objetos observados en algunos tipos de hormigas. Para conseguir una representación vectorial de cada documento independiente del idioma, se han utilizado dos recursos lingüísticos: un glosario económico y un tesauro. Cada documento es representado usando cuatro vectores de rasgos: palabras, nombres propios, términos económicos del glosario y descriptores del tesauro. La identificación de los nombres propios y la extracción y lematización de palabras se realizan usando herramientas específicas. El esquema tf-idf es utilizado para medir la importancia de cada rasgo en el documento, y se utiliza una combinación lineal convexa de separaciones angulares de los vectores de rasgos como medida de similitud de documentos. El trabajo muestra resultados experimentales de aplicación del algoritmo propuesto sobre un corpus español-inglés de documentos científicos de áreas económica y de gestión empresarial. Los resultados demuestran la utilidad y efectividad de las técnicas de ant clustering y del esquema de representación propuesto.