Ángel Francisco Villarejo-Ramos

Searching for latent class segments in technological services

The focus in this article is on uncovering segments that describe mobile phone users and on investigating the nature of these segments to get some relevant information. We use a phased approach to reach this objective. First, two segmentation bases have been compared in order to select the best variables for the identification of groups. This is done using a latent class modelling approach. Second, two different segmentation techniques are examined looking for the best model fit. Finally, the model that achieves the best results is applied to the most significant segmentation variables with the purpose of uncovering segments that describe mobile phone users.

Modelling the Influence of eWOM on Loyalty Behaviour in Social Network Sites

Social network sites (SNS) have become part of the daily reality of Internet users in recent years. Firms have recognised the importance of electronic recommendation (eWOM: electronic word-of-mouth) and its influence on consumer decisions. They use SNS as a two-way communication with their current and potential customers. In this context, this chapter means to establish a modelling of causal relations analysing the effect of eWOM communication on the affective commitment developed by SNS users and its effect on the behaviour of loyalty. In this model proposed, the online reputation, the consumer’s satisfaction and the user’s social involvement in SNS are considered as antecedents. The model’s central variable proposed is eWOM communication. This is an efficient means of capturing and retaining customers, as it presents a high level of credibility to developing long-term value relationships as relational marketing suggests. The model proposed, the justification of the relationships and the measurement scales aim to understand, explain and predict how eWOM communication influences loyalty behaviour in users’ SNS.

Hedonic and Utilitarian Effects of the Adoption and Use of Social Commerce

The aim of this research is to contribute to the field of study which explores the consumer behaviour model in social commerce, introducing the social commerce concept as a new commercial formula.

A knowledge structures exploration on social network sites

This paper aims to describe a method for combining perceived community support, relationship quality and the extended technology acceptance model in the same empirically derived associative network. The research also examines the moderating role of accumulation of knowledge (based on beliefs and opinions) derived from social interactions.,The Pathfinder algorithm is a valid approach for determining network structures from relatedness data. Such a graphical representation provides managers with a comprehensible picture of how social behaviours relate to loyalty-based dimensions.,As the benefits of community participation and integration might be differently evaluated by new and long-term users, the research examines the associative network by levels of user familiarity. This study indeed contributes to the analysis of enduring social bonds with respect to individuals’ decision-making processes, as it provides details representing specific relationships between diverse concepts based on true-loyalty.,The application of Pathfinder to the study of online social services and user behaviour appears to have potential for unveiling the structures of social network sites members and designing successful strategies for prospective community managers.,This is the first study to the author’s knowledge that empirically tests a theory-grounded framework for integrating individual characteristics and relational driver and focuses on associative structures evidenced as a representation of the most salient loyalty-based concepts by also studying the moderating effects of familiarity.