Factors Driving Virtual Running Event Participation: A CHAID Segmentation Approach

Virtual running events (VREs) have emerged as participatory events and are projected to be a legitimate future segment in the sport event industry. This paper considers the most suitable market segment(s) with future intentions to partake in VREs. A Chi-Squared Automatic Interaction Detector (CHAID) algorithm, scarcely used to segment sport consumer markets, was applied based on various motivational factors that may drive VRE participation. Data were collected from 1,017 individuals who had participated in a VRE. Ten distinct market segments with varying intentions to partake in VREs were identified, uncovering at least six viable future VRE segments. Hedonia, perceived psycho-social risk, perceived price and VRE benefits were the strongest predictors of VRE participation intentions. The CHAID analysis allowed a detailed description of the relative importance of the characteristics within each segment, confirming the benefit of using this sophisticated technique to develop targeted marketing strategies.

Authors

Institutions

Publication Details

Journal
Sport Marketing Quarterly
Published
2024-12-01
DOI
https://doi.org/10.32731/smq.334.122024.06
Citations
2
Primary Topic
Sport and Mega-Event Impacts
Type
article
Field-Weighted Citation Impact
2.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Factors Driving Virtual Running Event Participation: A CHAID Segmentation Approach

Yolanda Jordaan, Du Preez, Bianca Frost
2 citations
Sport Marketing Quarterly
Sport and Mega-Event Impacts
2.26
article

Factors Driving Virtual Running Event Participation: A CHAID Segmentation Approach

Yolanda Jordaan, Du Preez, Bianca Frost
article en
2 citations

Abstract

Virtual running events (VREs) have emerged as participatory events and are projected to be a legitimate future segment in the sport event industry. This paper considers the most suitable market segment(s) with future intentions to partake in VREs. A Chi-Squared Automatic Interaction Detector (CHAID) algorithm, scarcely used to segment sport consumer markets, was applied based on various motivational factors that may drive VRE participation. Data were collected from 1,017 individuals who had participated in a VRE. Ten distinct market segments with varying intentions to partake in VREs were identified, uncovering at least six viable future VRE segments. Hedonia, perceived psycho-social risk, perceived price and VRE benefits were the strongest predictors of VRE participation intentions. The CHAID analysis allowed a detailed description of the relative importance of the characteristics within each segment, confirming the benefit of using this sophisticated technique to develop targeted marketing strategies.

Sport Marketing QuarterlyVol. 33(4)
Université de Tours (FR), Consumer Product Testing Company (United States) (US), American Marketing Association (US)
Openalex Percentile: Top 9%
Sport and Mega-Event Impacts
2.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.