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Original Articles

Segmenting sport video gamers by motivation: a cluster analysis

基于动机的运动视频游戏玩家(SVGs)细分: 聚类分析

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Pages 92-108 | Received 16 Aug 2011, Accepted 09 Sep 2012, Published online: 16 Jan 2013
 

Abstract

Using the Uses and Gratifications paradigm, the present study examines motives for playing sport video games (SVG). Based on motivations, this study identifies segments of SVG users using a cluster analysis, and then explores potential similarities and differences between segments based upon demographic and behavioral variables. With a sample of 378 SVG users from four popular video game websites, the cluster analysis yielded two distinct clusters: Fun seekers and Fantasy seekers. Results indicated that the members of each cluster seek various gratifications from SVG use. Each cluster also was further distinguished based upon gender, marital status, and media consumption behaviors. Implications are discussed relative to virtual sport experience in the mediated environment and its corresponding marketing strategies.

在运动爱好者中运动视频游戏玩家越来越多,理解他们的动机对体育营销者来说非常重要。清楚了解媒体行为有助于经理们选择有效的影响沟通工具。而且清晰识别运动视频游戏玩家的动机对体育组织发展适当的营销战略也是必须的。但是众多体育组织很少注意到运动视频游戏玩家市场对体育迷基础的意义。本研究的目的有两个。首先,用聚类分析技术识别运动视频游戏玩家的子群体,其次,描述他们的特征,人口统计特征和行为特点。为完成这一目标,本研究采用使用满足模型作为理论框架,该理论认为观众不仅清楚自己的需要,也知道如何选择合适的媒介来满足自己的心理需求(Papacharissi & Rubin, 2000; Ruggiero, 2000)。

运动视频游戏玩家通过四个在线游戏网站填写问卷,388个被试参加了研究,372个例子被采用。在线调查分为三个部分: 运动视频游戏玩家动机问题、体育媒介行为和人口统计学特征。问卷采用前人的研究(Kim & Ross, 2006; Milne & MacDonald, 1999)。采用AMOS 18进行确定性因子分析来鉴别合适的测量。共采用七个维度进行细分,两种聚类方法结合使用:等级聚类和非等级聚类。最终用SPSS 18.0进行卡方检验和一元方差分析检验各类之间的人口统计特征和行为特征的区别。

结果显示: 主要的参与者是男性(89.2%)和单身(70.4%), 以及教育水平较高人士。18–29岁之间占74.6%。确定性因子分析显示七因子动机模型拟合数据效果良好: χ2 = 963.02, df = 254, p < .001; CFI = .90; NNFI = .89; IFI = .90; RMSEA = .07; and SRMR = .05; 七个因子信度和效度都满足。两个聚类的结果也适合大多数运动视频游戏玩家,一个聚类包括了62.7%,另一个包括了37.33%。比较七个因子平均得分可见,显著差别体现在知识应用和幻想维度。分类之后做卡方检验, 看看两个聚类的人口统计变量是否有显著差异。结果显示, 在性别(χ2(1) = 22.34, p = .000)、婚姻状况(χ2(1) = 6.70, p = .035)上差异显著。ANOVA结果显示: 纸媒体和电子媒体差异显著。

本研究的理论和实践意义在于。找乐是娱乐的主要动机,投入、寻找快乐和逃避现实也是主要的。似乎运动视频游戏玩家更倾向于追求运动的乐趣并且应用他们的知识和经验在虚拟比赛中。从营销角度来看,心理和行为特征的识别可以用来开展有效的营销沟通战略。

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