A persuasive-based latent class segmentation analysis of luxury brand websites

Estrella Díaz (), David Martín-Consuegra () and Hooman Estelami ()
Additional contact information
Estrella Díaz: University of Castilla-La Mancha
David Martín-Consuegra: University of Castilla-La Mancha
Hooman Estelami: Graduate School of Business

Electronic Commerce Research, 2016, vol. 16, issue 3, No 5, 424 pages

Abstract: Abstract Based on the development of the use of websites by brands, the purpose of this paper is to identify and describe different groups of luxury brands bearing in mind the persuasiveness of their websites (informativeness, usability, credibility, inspiration, involvement and reciprocity). The data for this study were collected from 197 luxury websites through content analysis methodology. Then, latent class cluster analysis was employed to identify the segments obtained in this study. The results confirm the existence of three segments of luxury brands according to website persuasiveness: “exclusive websites”, “transparent and accessible websites” and “old-fashioned websites”. This study helps luxury brand managers to evaluate the degree of persuasiveness of each group, determines how attractive the websites in each group are and suggests the measures necessary to improve their websites.

Keywords: Content analysis; Websites; Persuasiveness; Luxury brands; Latent class segmentation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10660-016-9212-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:elcore:v:16:y:2016:i:3:d:10.1007_s10660-016-9212-0

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10660

DOI: 10.1007/s10660-016-9212-0

Access Statistics for this article

Electronic Commerce Research is currently edited by James Westland

More articles in Electronic Commerce Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().