Quality & Quantity

, Volume 46, Issue 4, pp 1077–1095 | Cite as

An application of co-word analysis and bibliometric maps for detecting the most highlighting themes in the consumer behaviour research from a longitudinal perspective

  • Francisco Muñoz-Leiva
  • María Isabel Viedma-del-Jesús
  • Juan Sánchez-Fernández
  • Antonio Gabriel López-Herrera
Article

Abstract

This article presents an application of a bibliometric and visual study of the research carried out on a social science subfield, concretely the consumer behaviour research (CBR), from a longitudinal perspective (period 1966–2008). The study combines performance analysis and science mapping for detecting and visualizing conceptual subdomains. Quantitative and qualitative measures are used in order to identify the most prominent themes. Quantitative data are used to put together very related concepts (themes or clusters of topics), while qualitative indicators (as those based on citations) are used to measure the quality and/or impact of the detected themes. The study also uses bibliometric maps to show in a visual way the associations between the main concepts treated by the CBR community. The maps provide insight into the structure of the CBR, visualize the division of the field into several subfields, and indicate the relationships between these subfields. Co-word analysis is the bibliometric technique used to identify the main themes. All this allows us to quantify and visualize the thematic evolution of the CBR. It also helps to both experts and novices to understand the current state of the art of the CBR and to predict where future research could lead.

Keywords

Bibliometric study Conceptual evolution Emerging trends Co-Word analysis Consumer behaviour research Information and communications technology 

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Francisco Muñoz-Leiva
    • 1
  • María Isabel Viedma-del-Jesús
    • 1
  • Juan Sánchez-Fernández
    • 1
  • Antonio Gabriel López-Herrera
    • 2
  1. 1.Department of Marketing and Market Research, Facultad de Ciencias Económicas y EmpresarialesUniversity of GranadaGranadaSpain
  2. 2.Department of Computer Science and Artificial Intelligence, CITIC-UGR (Research Center on Information and Communications Technology)University of GranadaGranadaSpain

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