Hsiu-Chia Ko
ABSTRACT
Nowadays, advertising on Facebook has grown into a highly popular marketing channel, resulting in how advertisements can capture users' attention becomes a vital issue for practitioners and researchers. This study aims to use the Social Learning Theory as a theoretical foundation to investigate how the social-feature factor, perceived herd behavior on Facebook advertisement, may serve as the external observational learning sources and how personal instant gratification need learned from impulse consumption may serve as the internal reinforcement learning sources. Moreover, how both learning sources tempt consumers' impulse buying tendency was also examined. The results showed that the numbers of "Like," "Share," and "Comment" on the advertisement of Facebook might become an effective observational learning source that triggers users to follow and imitate others' advertisement viewing behaviors. The results also indicated that instant gratification feeling learned from previous impulse buying can be a reinforcement learning source that becomes a durational inner stimulus of impulsive consumption. Moreover, this study further revealed that both perceived herd behavior and instant gratification would lead users to generate reactions of perceived usefulness and perceived enjoyment toward advertisements on Facebook News Feed, which in turn intensify their impulse buying tendency. Notably, both perceived herd behavior and instant gratification have greater influences on perceived usefulness than on perceived enjoyment, and perceived usefulness also has a greater influence on impulse buying tendency. Finally, the implications of the results were discussed.
- Ali, S. W., & Sudan, S. 2018. Influence of cultural factors on impulse buying tendency: A study of Indian consumers. Vision: The Journal of Business Perspective, 22, 1, 68--77.Google Scholar
Cross Ref
- Amos, C., Holmes, G. R., & Keneson, W. C. 2014. A metaanalysis of consumer impulse buying. Journal of Retailing and Consumer Services, 21, 2, 86--97.Google ScholarCross Ref
- Bandura, A. 1971. Social learning theory. NY: General Learning Cooperation.Google Scholar
- Bandura, A. 1986. A social foundations of thought and action. Englewood Cliffs: Prentice Hall.Google Scholar
- Bandura, A. 2001. Social cognitive theory of mass communication. Mediapsychology, 3, 265--299.Google Scholar
- Bayley, G., & Nancarrow, C. 1998. Impulse purchasing: A qualitative exploration of the phenomenon. Qualitative Market Research: An International Journal, 1, 2, 99--114.Google ScholarCross Ref
- Chan, T. K. H., Cheung, C. M. K., & Lee, Z. W. Y. 2017. The state of online impulse buying research: A literature analysis. Information & Management, 54, 2, 204--217. Google ScholarDigital Library
- Chen, Y., Wang, Q., & Xie, J. 2011. Online social interactions: A natural experiment on word of mouth versus observational learning. Journal of Marketing Research, 48, 2, 238--254.Google ScholarCross Ref
- Cheung, C. M. K., Liu, I. L. B., & Lee, M. K. O. 2015. How online social interactions influence customer information contribution behavior in online social shopping communities: A social learning theory perspective. Journal of the Association for Information Science and Technology, 66, 12, 2511--2521. Google ScholarDigital Library
- Chu, S.-C., & Sung, Y. 2015. Using a consumer socialization framework to understand electronic word-of-mouth (eWOM) group membership among brand followers on Twitter. Electronic Commerce Research and Applications, 14, 4, 251--260. Google ScholarDigital Library
- Fornell, C., &Larcker, D. F. 1981. Evaluating structural equations with unobservable variables and measurement error. Journal of Marketing Research, 18, 1, 39--50.Google ScholarCross Ref
- Jones, M. A., Reynolds, K. E., Weun, S., & Beatty, S. E. 2013. The product-specific nature of impulse buying tendency. Journal of Business Research, 56, 7, 505--511.Google ScholarCross Ref
- Koufaris, M. 2002. Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13, 2, 205--223. Google ScholarDigital Library
- Lee, J., & Hong, I. B. 2016. Predicting positive user responses to social media advertising: The roles of emotional appeal, informativeness, and creativity. International Journal of Information Management, 36, 3, 360--373. Google ScholarDigital Library
- Liu, Y., Li, H., & Hu, F. 2013. Website attributes in urging online impulse purchase: An empirical investigation on consumer perceptions. Decision Support Systems, 55, 829--837.Google ScholarCross Ref
- Madhavaram, Rao, S., & Laverie, D. A. 2004. Exploring impulse purchasing on the Internet. Advances in Consumer Research, 34, 1, 59--66.Google Scholar
- Parboteeah, D. V., Valacich, J. S., & Wells, J. D. 2009. The influence of website characteristics on a consumer's urge to buy impulsively. Information Systems Research, 20, 1, 60--78 Google ScholarDigital Library
- Park, J., & Lennon, S. J. 2006. Psychological and environmental antecedents of impulse buying tendency in the multichannel shopping context. Journal of Consumer Marketing, 23, 2, 56--66.Google ScholarCross Ref
- Slickdeals. 2018. Slickdeals shares new survey data showing Americans spend $324,000 on impulse buys in their lifetime.Google Scholar
- Smart PLS 2.0_M3 Beta, H., 2005, http://www.smartpls.com.Google Scholar
- Sun, T., & Wu, G. 2011. Trait predictors of online impulsive buying tendency: A hierarchical approach. Journal of Marketing Theory and Practice, 19, 3, 337--346.Google ScholarCross Ref
- Chen, J. V., Su, B.-C., & Widjaja A. E. 2016. Facebook C2C social commerce: A study of online impulse buying. Decision Support Systems, 83, 1, 57--69. Google ScholarDigital Library
- Wang, X., Yu, C., & Wei, Y. 2012. Using a consumer socialization framework to understand electronic word-of-mouth (eWOM) group membership among brand followers on Twitter. Journal of Interactive Marketing, 26, 4, 198--208.Google ScholarCross Ref
- Wu, Y.-W., Huang, C.-F., & Weng, K.-H. 2014. A study of an architecture design learning process based on social learning, course teaching, interaction, and analogical thinking. Mathematical Problems In Engineering, 2014, 1--8.Google Scholar
- Xiang, L., Zheng, X., Lee, M. K. O., & Zhao, D. 2016. Exploring consumers' impulse buying behavior on social commerce platform: The role of parasocial interaction. International Journal of Information Management, 36, 3, 333--347. Google ScholarDigital Library
- Zhang, K. Z. K., Hu, B., & Zhao, S. J. 2014. How online social interactions affect consumers' impulse purchase on group shopping websites? In Pacific Asia Conference on Information Systems (PACIS).Google Scholar
Index Terms
- Exploring the factors driving impulse buying tendency on advertisements of Facebook: a social learning theory perspective
Recommendations
Exploring the Effects of Browsing Motivations on Planned Impulse Buying in Facebook Transaction Groups
ICIEB '21: Proceedings of the 2021 2nd International Conference on Internet and E-BusinessIn recent years, the topical specificity of Facebook buy and sell groups has made it easier to attract consumers with a common need or interest in a particular topic to come together. With this feature, Facebook buy and sell groups have also become one ...
Exploring consumers' impulse buying behavior on social commerce platform
Task-related features affect perceived usefulness.Mood-related features affect perceived enjoyment.Social-relevant features determine users' parasocial interaction (PSI).PSI affects impulse buying tendency.Perceived enjoyment and impulse buying tendency ...
The driving forces of Facebook social commerce
Trust is viewed as a crucial factor in social commerce due to the prominent role and significant amount of peer-generated contents. The current study aims to investigate the relationship between trust in social commerce and customers' purchase ...
Comments