Tilburg University

About: Tilburg University is a education organization based out in Tilburg, Noord-Brabant, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 5550 authors who have published 22330 publications receiving 791335 citations.

Daily work contexts and resistance to organisational change : the role of leader-member exchange, development climate, and change process characteristics.

Abstract: In the last decade, researchers have started to investigate the psychological processes that are involved in employees’ experiences of organisational change. The present study examined how characteristics of the daily work context related to employees’ resistance to change through aspects of the change process. The results supported the research model, showing that the relationships of leader–member exchange and perceived development climate with employees’ resistance to a merger were fully mediated by three change process characteristics (i.e. information, participation, and trust in management). In addition, two individual-level characteristics (i.e. openness to job changes, and organisational tenure) showed significant relationships with resistance to change. Employees’ role breadth self-efficacy was not related to resistance. Together, the results suggest a number of ways in which organisations can increase the effectiveness of their change efforts. Au cours de la derniere decennie, les chercheurs ont commenceaetudier les processus psychologiques a l’œvre dans les experiences des employes lors d’un changement organisationnel. La presente etude examine la facon dont les caracteristiques d’un contexte de travail quotidien sont en lien avec la resistance au changement des salaries a travers certains aspects du processus de changement. Les resultats confirment le modele de recherche en montrant que les relations de LMX (Leader–Member Exchange) et du climat de developpement percu avec la resistance des salaries a une fusion etaient totalement mediees par trois caracteristiques processuelles de changement (l’information, la participation et la confiance dans la direction). De plus, les caracteristiques individuelles (ouverture aux changements de travail et titularisation au sein de l’organisation) sont significativement liees a la resistance au changement. L’efficacite de l’ampleur du role des salaries n’est pas liee a la resistance. Ensemble, ces resultats ouvrent quelques voies que les organisations peuvent utiliser pour augmenter l’efficacite de leurs efforts de changement.

Social Differentiation in Musical Taste Patterns

Abstract: In this article, we investigate patterns of musical taste using a large sample from the Dutch population. It is found that members from higher-status groups tend to be more omnivorous (that is, they like more different musical genres) than those from lower-status groups, which is in line with Peterson's (1992; Peterson & Simkus 1992) hypothesis. The actual difference is, however, rather small and occurs only with regard to the number of genres that respondents like at least "more or less," not with regard to their favorite genres. In order to discover the combinatorial logic by which musical genres are clustered into specific taste patterns, a factor model is estimated. The results indicate that musical genres can be structured on the basis of three basic "discourses" (highbrow, pop, folk). The so-called omnivores comprise a specific fraction of the higher-status groups known as the new middle class, whose tastes combine a set of genres related to all these discourses.

Computational generation of referring expressions: A survey

Abstract: This article offers a survey of computational research on referring expression generation (REG). It introduces the REG problem and describes early work in this area, discussing what basic assumptions lie behind it, and showing how its remit has widened in recent years. We discuss computational frameworks underlying REG, and demonstrate a recent trend that seeks to link REG algorithms with well-established Knowledge Representation techniques. Considerable attention is given to recent efforts at evaluating REG algorithms and the lessons that they allow us to learn. The article concludes with a discussion of the way forward in REG, focusing on references in larger and more realistic settings.