Modelling the Human Values Scale from Consumers Transactional Data Bases

The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study

Reliable entertainment: Spanish consumers' preferences regarding a film's country of origin

This article contributes to the study of cinema audiences in Europe by analyzing the actual behavior of Spanish moviegoers and their level of satisfaction. We modeled moviegoers’ choice of film by country of origin (U.S.A., Spain, and other countries) according to a set of determinants: (1) consumers’ interpretation of several sources of information, (2) motivations and (3) choice rules. We found three clear consumer stereotypes related to each type of film: (1) U.S.A. films were preferred by almost everyone (especially families and younger audiences); (2) Spanish films had audiences composed of middle-age and middle-class moviegoers; and (3) European productions were preferred by a social or intellectual elite. U.S.A. films dominate the Spanish market for the reason that they provide most of what moviegoers prefer, namely, familiar, reliable entertainment in Spanish; three characteristics that are not satisfied by Spanish and European films. Additionally, we discuss the implications for the European cultural policy