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Clustering Esports Gameplay Consumers via Game Experiences
This study focuses on “game experiences” in the context of esports gameplay consumption and aims to identify adequate consumer groups based on their esports experience including perceptions of gameplay, watching, and purchasing hardware. The purpose of this study is to identify adequate consumer gro...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245691/ https://www.ncbi.nlm.nih.gov/pubmed/34222860 http://dx.doi.org/10.3389/fspor.2021.669999 |
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author | Jang, Wooyoung William Byon, Kevin K. Pecoraro, Jennifer Tsuji, Yosuke |
author_facet | Jang, Wooyoung William Byon, Kevin K. Pecoraro, Jennifer Tsuji, Yosuke |
author_sort | Jang, Wooyoung William |
collection | PubMed |
description | This study focuses on “game experiences” in the context of esports gameplay consumption and aims to identify adequate consumer groups based on their esports experience including perceptions of gameplay, watching, and purchasing hardware. The purpose of this study is to identify adequate consumer groups through consumer segmentation. Based on the literature review, a matrix of esports gameplay was proposed based on high/low esports gameplay, viewing esports, and hardware enthusiasm. Four esports gameplay consumer groups are proposed (all-around gamer, conventional player, observer, recreational gamer) based on their prior esports experiences (esports gameplay, viewing esports content via media, and hardware enthusiasm). A total of 699 usable observations were initially collected by the online survey. Eventually, 508 observations were retained (127 for each group) for multivariate analysis of variance and subsequent univariate tests. The findings indicated the four esports gameplay consumer groups were empirically supported. Furthermore, this study found similarities and differences for each group based on the six antecedents of esports gameplay intention. The findings indicated hedonic motivation and price value might be considered general factors that may be applied to all esports consumers. Contrarily, the findings indicated that social influence, habit, effort expectancy, and flow might be suitable for tailored marketing strategies targeting esports consumer groups. Theoretically, the suggested esports experience will contribute to the growing body of knowledge aimed at understanding esports consumers' behavior through the consistent clustering of behavioral prior experience. Practically, the proposed esports consumers' clustering will contribute to more efficient marketing, with spending on more targeted marketing leading to effectively reaching the right people. |
format | Online Article Text |
id | pubmed-8245691 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82456912021-07-02 Clustering Esports Gameplay Consumers via Game Experiences Jang, Wooyoung William Byon, Kevin K. Pecoraro, Jennifer Tsuji, Yosuke Front Sports Act Living Sports and Active Living This study focuses on “game experiences” in the context of esports gameplay consumption and aims to identify adequate consumer groups based on their esports experience including perceptions of gameplay, watching, and purchasing hardware. The purpose of this study is to identify adequate consumer groups through consumer segmentation. Based on the literature review, a matrix of esports gameplay was proposed based on high/low esports gameplay, viewing esports, and hardware enthusiasm. Four esports gameplay consumer groups are proposed (all-around gamer, conventional player, observer, recreational gamer) based on their prior esports experiences (esports gameplay, viewing esports content via media, and hardware enthusiasm). A total of 699 usable observations were initially collected by the online survey. Eventually, 508 observations were retained (127 for each group) for multivariate analysis of variance and subsequent univariate tests. The findings indicated the four esports gameplay consumer groups were empirically supported. Furthermore, this study found similarities and differences for each group based on the six antecedents of esports gameplay intention. The findings indicated hedonic motivation and price value might be considered general factors that may be applied to all esports consumers. Contrarily, the findings indicated that social influence, habit, effort expectancy, and flow might be suitable for tailored marketing strategies targeting esports consumer groups. Theoretically, the suggested esports experience will contribute to the growing body of knowledge aimed at understanding esports consumers' behavior through the consistent clustering of behavioral prior experience. Practically, the proposed esports consumers' clustering will contribute to more efficient marketing, with spending on more targeted marketing leading to effectively reaching the right people. Frontiers Media S.A. 2021-06-17 /pmc/articles/PMC8245691/ /pubmed/34222860 http://dx.doi.org/10.3389/fspor.2021.669999 Text en Copyright © 2021 Jang, Byon, Pecoraro and Tsuji. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Sports and Active Living Jang, Wooyoung William Byon, Kevin K. Pecoraro, Jennifer Tsuji, Yosuke Clustering Esports Gameplay Consumers via Game Experiences |
title | Clustering Esports Gameplay Consumers via Game Experiences |
title_full | Clustering Esports Gameplay Consumers via Game Experiences |
title_fullStr | Clustering Esports Gameplay Consumers via Game Experiences |
title_full_unstemmed | Clustering Esports Gameplay Consumers via Game Experiences |
title_short | Clustering Esports Gameplay Consumers via Game Experiences |
title_sort | clustering esports gameplay consumers via game experiences |
topic | Sports and Active Living |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245691/ https://www.ncbi.nlm.nih.gov/pubmed/34222860 http://dx.doi.org/10.3389/fspor.2021.669999 |
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