The impact of extreme levels of electronic word-of-mouth volume on suspicion and choice intention

  • Inna Dickmänken (Student)

Student thesis: Master's Thesis

Abstract

Online product reviews have become a relevant information source and sales driver in the online purchase decision process. Being aware of the positive effects, many online sellers engage in measures to increase their amount of highly-rated reviews. Consequently, the instrument of reviews itself and fake reviews in particular became highly relevant for researchers, who put effort into understanding the effects of electronic word of mouth (eWOM) – especially its metrics of valence, the review’s star rating, and volume, the number of reviews – on variables such as purchase intention, perceived and suspicion. The author elaborates on existing research and uncovers that until now no attention has been devoted to the possible effects of extreme values of review volume, although prevailing, e.g., on Amazon. This thesis attempts to fill the identified research gap by proposing consumers use a heuristic approach to interpret the meaning of these metrics. By means of an experiment, the author analyses whether extreme values of review volume in the beginning of the purchase decision process, namely consideration set formation, work as a suspicious cue that implies suspicion and deters consumers from adding a product to their consideration set. The results reveal that an extreme volume does not lead to consumer suspicion, only valence does. Further, it was shown that this resulting feeling of suspicion weakens choice intention while an extreme volume has no impact on choice intention. This thesis is a first contribution to fill the research gap of extreme values of volume.
Date of Award26 Apr 2021
Original languageEnglish
Awarding Institution
  • Universidade Católica Portuguesa
SupervisorAna Filipa Almeida (Supervisor)

Keywords

  • E-WOM
  • E-WOM volume
  • E-WOM valence
  • Online reviews
  • Product reviews
  • Fake reviews
  • Heuristics
  • Purchase decision making process

Designation

  • Mestrado em Gestão e Administração de Empresas

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