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Factors Influencing Shoppers’ Behavioral Intention to Purchase Smart Phones: Digital Transformation Through YouTube User Generated Content
Author(s)
Thirakulwanich, Anuphat
Date Issued
January 1, 2022
Type
Conference Paper
Abstract
This study explored the factors that influence shoppers’ behavioral intention to purchase smartphones based on User Generated Content on the YouTube platform. The study was underpinned by two critical theories which include; Extended Technology Acceptance Model (TAM) and Source Credibility Theory to understand how UGC on YouTube was applicable in influencing purchase decisions. The independent variables were UGC, perceived credibility, and perceived usefulness. The study adopted a quantitative descriptive survey research design. A questionnaire was used to collect data from a sample size of 442 YouTube users in Thailand and the data were analyzed using SEM. The findings revealed that user-generated content on YouTube has a positive effect on perceived credibility, perceived usefulness, and behavioral intention to purchase smartphones. It also showed that perceived usefulness and perceived credibility have a positive effect on behavioral intention to purchase smartphones. Ultimately, the study also found that UGC on YouTube has an indirect and significant effect on behavioral intention to purchase smartphones mediated for both perceived usefulness and perceived credibility. The study recommends that future studies should consider different social media platforms where UGC are available to test for consistency, and also incorporate a mixed method of research involving qualitative data that will allow respondents to provide clarifications for their decisions. A few imitations of the study could be highlighted. The first limitation is within the scope of the study, from the fact that the study’s focus was on one social media channel – YouTube. The study focused more on the user-generated content on YouTube and added two more variables (perceived credibility and perceived usefulness).
Citation
Communications in Computer and Information Science, 1619 CCIS, 35-50, 2022