The Impact Factor of Influencers - Modeling a new indicator for the tourism sector

Caroline Beltran (), Melissa Coumelongue, Miriam Scaglione () and Rodolfo Baggio
Additional contact information
Caroline Beltran: UA - Université d'Angers, GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement, Esthua Faculté de Tourisme, Culture et Hospitalité
Melissa Coumelongue: UPVD - Université de Perpignan Via Domitia, CRESEM - Centre de Recherche sur les Sociétés et Environnements en Méditerranées - UPVD - Université de Perpignan Via Domitia, IAE Perpignan - Institut d'Administration des Entreprises - Perpignan - UPVD - Université de Perpignan Via Domitia

Post-Print from HAL

Abstract: Social media and influencers play a crucial role in inspiring tourists and shaping travel decision-making processes. Empirical evidence suggests that the likelihood of planning a trip based on User-Generated Content (UGC)—that is, content created by individuals rather than organizations—is approximately 48%, as such content is perceived as more trustworthy and authentic than brand-generated content. Influencer marketing, widely recognized as a dominant paradigm on social media, is considered one of the approaches most likely to shape the future of social media marketing (Vrontis et al., 2021). Current influencer campaign performance metrics primarily rely on indicators such as views, publication reach, and engagement rates. This article proposes an alternative framework for measuring influencer marketing campaigns based on network analysis techniques. Using data collected from three influencer marketing campaigns conducted on tourist destinations through Instagram, this study develops an algorithm-based composite indicator, referred to as the Impact Factor, designed to assess an individual's influence by combining measures of credibility (authority score) and visibility (hub score). Based on the cases examined, our approach enables the mapping of influence networks, the assessment of relationship quality within influencer campaigns in addition to their quantitative reach, and the identification of the most influential individuals best suited for digital marketing campaigns.

Keywords: Network Analysis Techniques; Visibility; Perceived Credibility; Impact Factor; Influencer Marketing (search for similar items in EconPapers)
Date: 2025-08
References: Add references at CitEc
Citations:

Published in 74th AIEST Conference, AIEST, Aug 2025, Paris, France

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:hal:journl:hal-05646858

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().