A multi-model approach for the extension of the use and gratification theory in video game streaming

满足 背景(考古学) 互动性 人气 解释力 计算机科学 独创性 心理学 多媒体 人机交互 社会心理学 古生物学 哲学 认识论 创造力 生物
作者
Xiaoyu Xu,Syed Muhammad Usman Tayyab,Qingdan Jia,Albert Huang
出处
期刊:Information Technology & People [Emerald Publishing Limited]
卷期号:38 (1): 137-179 被引量:8
标识
DOI:10.1108/itp-08-2021-0628
摘要

Purpose Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental elements, gratifications and user pre-existing attitudes in VGS, this paper presents the development of an extended model of uses and gratification theory (EUGT) for predicting users' behavior in novel technological context. Design/methodology/approach The proposed model was empirically tested in VGS context due to its popularity, interactivity and relevance. Data collected from 308 VGS users and structural equation modeling (SEM) was employed to assess the hypotheses. Multi-model comparison technique was used to assess the explanatory power of EUGT. Findings The findings confirmed three significant types elements in determining VGS viewers' engagement, including gratifications (e.g. involvement), environmental cues (e.g. medium appeal) and user predispositions (e.g. pre-existing attitudes). The results revealed that emerging technologies provide potential opportunities for new motives and gratifications, and highlighted the significant of pre-existing attitudes as a mediator in the gratification-uses link. Originality/value This study is one of its kind in tackling the criticism on UGT of considering media users too rational or active. The study achieved this objective by considering environmental impacts on user behavior which is largely ignored in recent UGT studies. Also, by incorporating users pre-existing attitudes into UGT framework, this study conceptualized and empirically verified the higher explanatory power of EUGT through a novel multi-modal approach in VGS. Compared to other rival models, EUGS provides a more robust explanation of users' behavior. The findings contribute to the literature of UGT, VGS and users' engagement.
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