INVESTIGATION OF ANTECEDENTS AND CONSEQUENCES OF USEFULNESS IN ONLINE TRAVEL COMMUNITIES: THE MODERATING ROLE OF DECISION MAKING STAGE

被引:1
作者
Ranga, Bindu [1 ]
Singh, Ranbir [2 ]
Ranga, Indu [3 ]
机构
[1] Lovely Profess Univ, Sch Hotel Management & Tourism, Phagwara, Punjab, India
[2] Cent Univ Haryana, Dept Tourism & Hotel Management, Jaat, Haryana, India
[3] Christ Univ, Dept Tourism Management, Bangalore, India
来源
ADVANCES IN HOSPITALITY AND TOURISM RESEARCH-AHTR | 2023年 / 11卷 / 04期
关键词
online travel community; user-generated content; perceived usefulness; travel decision making; Eloborate Likelihood Model; (ELM); WORD-OF-MOUTH; ELABORATION LIKELIHOOD MODEL; PERCEIVED USEFULNESS; TOURISM EXPERIENCES; SOURCE CREDIBILITY; SOCIAL MEDIA; ACCEPTANCE; ADOPTION; REVIEWS; QUALITY;
D O I
10.30519/ahtr.1053634
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study examines the perceived usefulness (PU) of online discourse and the decision-making behavior of users in Online Travel Communities (OTCs). Partial least squares structural equation modeling (PLS-SEM) was used on secondary data available in OTCs in the form of 852 threads to empirically test the proposed integrated model. The antecedents of the perceived usefulness of online travel communities were found to be the argument quality and credibility. These influence the PU of user-generated content significantly and are helpful in information adoption in OTCs. The PU of OTC discourse positively impacts travelers' information adoption and decision-making. The current study offers implications for OTCs and online service providers for enhancing the usefulness of user-generated content in OTCs and social media sites, leading to online information use and travel decision-making. Prior literature has explored the nature and magnitude of the influence of electronic word-of-mouth (eWOM) on information adoption and intention to use information for travel purchases from users' perspectives and has investigated the PU of third-party travel sites. This paper is an effort to examine PU and decision-making by analyzing the User-Generated-Content (UGC) posted by the actual users.
引用
收藏
页码:476 / 504
页数:29
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