Cited by 24Digital Marketing and Social MediaDiverse Aspects of Tourism ResearchConsumer Behavior and Marketing Influence

Traveler segmentation through Instagram Fashion Influencers. Mirror Tourist as a new segment consumer group

Open access
Sánchez-Amboage, Eva, Castellanos-García, Pablo, Crespo-Pereira, Verónica·2024·Journal of Retailing and Consumer Services

Abstract

Influencer marketing is an increasingly significant research topic, but there is a research gap when it comes to utilizing data from social media influencers' online community to identify novel consumer groups through market segmentation. To achieve this, a case study of 50 Instagram Fashion Influencers (IFIs) worldwide was carried out. Through a step-by-step analysis of market segmentation, the research obtained data from over 74 million followers of selected influencers, and through a logit analysis, ultimately identified a previously undiscovered type of tourist consumer: the Mirror Tourist (MT). The MT itself adds to the realm of lifestyle research, an intersection between tourism and fashion, by representing a distinctive category of Instagram user. This user is specifically interested in tourism-related content shared by the IFIs they follow. This creates a variety of opportunities to showcase businesses and tourist destinations through fashion influencers, as well as to formulate marketing strategies. Furthermore, this research brings substantial value to the literature on influencer marketing and tourism segmentation, as it represents the first study that focuses on segmentation through IFIs' followers.

Integrity signals

Registry

Crossref · 10.1016/j.jretconser.2024.103735

Cites

80 of 80 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Tourists who are highly influenced by an influencer's recommendation of a specific destination have their decision to visit directly linked to seeing an influencer's post, vlog, or story about a destination.

    “Destination Selection Intentions Tourists who are highly influenced by an influencer's recommendation of a specific destination.Their decision to visit is directly linked to seeing an influencer's post, vlog, or story about a destination”

Cites

Flagged first, then by citations

1 of the 81 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Sánchez-Amboage, E., Castellanos-García, P., & Crespo-Pereira, V.
Affiliations
Universidade da Coruña (ES)
Corresponding author
Sánchez-Amboage, Eva
Venue
Journal of Retailing and Consumer Services
Publisher
Elsevier BV
Published
2024-05
Volume
78
Pages
103735
ISSN
0969-6989 (ISSN-L)
OpenAlex
W4391589685
Cited by
21
References
81
Citations by year
2026: 7 · 2025: 12 · 2024: 2
FWCI
15.13
Type
journal article
Language
en
Open access
Locations
  • Journal of Retailing and Consumer Services (publishedVersion, cc-by-nc)
  • RePEc: Research Papers in Economics (submittedVersion)
  • RUC (Universidade Da Coruña) (submittedVersion, cc-by-nc)
Topics
  • Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
  • Social Sciences › Sociology and Political Science › Diverse Aspects of Tourism Research
  • Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
Keywords
influencer marketing, tourist segmentation, social media followers, tourism promotion

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review