Impacts of Bandwagon Effect and Product Type in Instagram Native Advertising on Generation Z Consumer’s Behavior
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Abstract
The objective of this study was to investigate the impact of bandwagon effect and product type in Instagram native advertising on consumer behavior (i.e., ad intrusiveness, attitude towards the ad, attitude towards the brand, purchase intention and intention to share). A 2x2 between subjects, factorial design was employed to collect data from 129 undergraduate students, who were Generation Z, in Thailand. The results showcase a statistically significant difference for intention to share between the low and high bandwagon effect treatments, with the high bandwagon one showing a higher mean score. Further, the results exhibit a statistically significant difference for purchase intention between the utilitarian product (notebook computer) and hedonic product (perfume), with the hedonic product showing a higher mean score. No interaction effect between bandwagon effect and product type was found in this study. Next to the generation of high bandwagon cues in form of likes and comments being a key aspect for impacting Thai Generation Z consumer’s behavioral intentions, this research also highlights the importance of ad-media congruence for native advertising on social media platforms.
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Ai, P., Li, W., & Ding, A. (2020). Powerful little numbers: How bandwagon cues influence consumer purchase intention for online content. Retrieved from https://advance.sagepub.com/articles/Powerful_Little_Numbers_How_Bandwagon_Cues_Influence_Consumer_Purchase_Intention_for_Online_Content/11912406/files/21882564.pdf
Alvarez, B. A., & Casielles, R. V. (2005). Consumer evaluations of sales promotion: The effect on brand choice. European Journal of Marketing, 39, 54-70.
Anantharaman, R., Prashar, S., & Vijay, T. S. (2022) Uncovering the role of consumer trust and bandwagon effect influencing purchase intention: an empirical investigation in social commerce platforms. Journal of Strategic Marketing, 1-21.
Baron, R. A., & Byrne, D. (1987). Social psychology: Understanding human interaction. (5th ed.). Boston, MA: Allyn & Bacon.
Borgave, S., & Chaudhari, J. S. (2010). Adolescents’ preferences and attitudes towards perfumes in India. Journal of Policy and Organizational Management, 1(2), 1-8.
Calder, B. J., & Malthouse, E. C. (2008). Media engagement and advertising effectiveness. Kellogg on advertising and media. Hoboken, NJ: Wiley.
Campbell, M.C., & Kirmani, A. (2000) Consumer’s use of persuasion knowledge: The effects of accessibility and cognitive capacity on perceptions of an influence of agent. Journal of Consumer Research, 27, 69-83.
Campbell, C., & Marks, L. J. (2015). Good native advertising isn’t a secret. Business Horizons, 58(6), 599-606.
Chaiken, S. (1980). Heuristic and systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39(5), 752-766.
Chaiken, S. (1987). The heuristic model of persuasion. In M. P. Zanna, J. M. Olson, & C. P. Herman (Eds.), Social influence: The Ontario symposium (Vol. 5, pp. 3–39). Mahwah, NJ: Lawrence Erlbaum Associates.
Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. Journal of Personality and Social Psychology, 66, 460-460.
Chen, T., & Lee, H. M. (2014). Why do we share? The impact of viral videos dramatized to sell: How microfilm advertising works. Journal of Advertising Research, 54(3), 292-303.
Darrel, D. M. (1987). Comparative advertising: The influence of attitude-toward-the- ad on brand evaluation. Journal of Advertising, 16(4), 43-49.
Degenhard, J. (2021, July 20). Forecast of the number of Instagram users in Thailand from 2017 to 2025. Retrieved from https://www.statista.com/forecasts/1138778/instagram-users-in-thailand
de Vries, E. L. (2019). When more likes is not better: The consequences of high and low likes-to- followers ratios for perceived account credibility and social media marketing effectiveness. Marketing Letters, 30, 275-291.
Dhar, R., & Wertenbroch, K. (2000). Consumer choice between hedonic and utilitarian goods. Journal of Marketing Research, 37(1), 60-71.
Edwards, S. M., Li, H., & Lee, J.H. (2002). Forced exposure and psychological reactance: Antecedents and consequences of the perceived intrusiveness of pop-up ads. Journal of Advertising, 31(3), 83-95.
Egan, J. (2015). Marketing communications (2nd ed.). Thousand Oaks, CA: Sage.
Fill, C. (2011). Essentials of marketing communications. Hoboken, NJ: Prentice-Hall.
Friestad, M., & Wright, P. (1994). The Persuasion Knowledge Model: How people cope with persuasion attempts. Journal of Consumer Research, 21(1), 1-31.
Fulgoni, G., & Lipsman, A. (2014). Digital game changers: How social media will help usher in the era of mobile and multi-platform campaign-effectiveness measurement. Journal of Advertising Research, 54(1), 11-16.
Gardner, M. P. (1985). Does attitude toward the ad affect brand attitude under a brand evaluation set? Journal of Marketing Research, 22(2), 192-198.
Go, E., Jung, E., & Wu, M. (2014). The effects of source cues on online news perception. Computers in Human Behavior, 38, 358-367.
Hensel, K., & Deis, M. H. (2010). Using social media to increase advertising and improve marketing. The Entrepreneurial Executive, 15, 87-97.
Hirschman, E. C. (1980). Attributes of attributes and layers of meaning. Advances in Consumer Research, 7, 7-12.
Holbrook, M., & Batra, R. (1987). Assessing the role of emotions as mediators of consumer responses to advertising. Journal of Consumer Research, 14(3), 404-420.
Interactive Advertising Bureau. (2019, May 09). The native advertising playbook 2.0. Retrieved from https://www.iab.com/insights/iab-native-advertising-playbook-2-0/
Järvinen, J., Ohtonen, R., & Karjaluoto, H. (2016). Consumer acceptance and use of Instagram. 2016 49th HI International Conference on System Sciences (HICSS), 2227-2236.
Johnson, E. K., & Hong, S. C. (2020). Instagramming social presence: A test of social presence theory and heuristic cues on Instagram sponsored posts. International Journal of Business Communication. https://doi.org/10.1177/2329488420944462
Katz, D. (1960). The functional approach to the study of attitudes. Public Opinion Quarterly, 24, 163–204.
Kim, J., Lee, J., & Chung, Y. J. (2017). Product type and spokespersons in native advertising--The role of congruency and acceptance. Journal of Interactive Advertising, 17(2), 109-123.
Kim, J. W. (2018). They liked and shared: Effects of social media virality metrics on perceptions of message influence and behavioral intentions. Computers in Human Behavior, 84, 153-161.
Kim, M., Lee, J. K., & Lee, K. Y. (2019). Interplay of content type and product type in the consumer response to native advertising on social media. Asian Journal of Communication, 29(6), 464-482.
Kitchen, P. J., Brignell, J., Lit, T., & Jones, G. S. (2004). The emergence of IMC: A theoretical perspective. Journal of Advertising Research, 44(1), 19–30.
Kotler, P., & Armstrong, G. (2021). Principles of marketing (18th ed.). Harlow, UK: Pearson.
Kotler, P., Keller, K. L., & Chernev, A. (2021). Marketing management (16th ed.). Boston, MA: Pearson.
Lee, J., Kim, S., & Ham, C. D. (2016). A double-edged sword? Predicting consumers’ attitudes toward and sharing intention of native advertising on social media. American Behavioral Scientist. 60(12), 1425-1441.
Lee, J. Y., & Sundar, S. S. (2013). To tweet or to retweet? That is the question for health professionals on Twitter. Health Communication, 28(5), 509-524.
Lee-Won, R. J., Abo, M. M., Na, K., & White, T. N. (2016). More than numbers: Effects of social media virality metrics on intention to help unknown others in the context of bone marrow donation. Cyberpsychology, Behavior, and Social Networking, 19(6), 404-411.
Lehto, M. R., Nah, F. F.-H., & Yi, J. S. (2012). Decision-making models, decision support, and problem solving. In G. Salvendy (Ed.), Handbook of human factors and ergonomics (4th ed., pp. 192-242). Hoboken, NJ: John Wiley & Sons.
Li, H., Edwards, S. M., & Lee, J. H. (2002). Measuring the intrusiveness of advertisements: Scale development and validation. Journal of Advertising, 31(2), 37-47.
Li, R., Vafeiadis, M., Xiao, A., & Yang, G. (2020). The role of corporate credibility and bandwagon cues in sponsored social media advertising. Corporate Communications: An International Journal, 25(3), 495-513.
Li, R., & Sundar, S.S. (2018). Can interactive media attenuate psychological reactance? A study of the role played by user commenting and audience metrics in promoting persuasion. Paper presented at the 68th Annual Conference of International Communication Association, Prague.
Liao, C., To, P. L., Wong, Y. C., Palvia, P., & Kakhki, M. D. (2016). The impact of presentation mode and product type on online impulse buying decisions. Journal of Electronic Commerce Research, 17(2), 153-168.
Linaschke, J. (2011). Getting the most from Instagram. Berkeley, CA: Peachpit Press.
Liu, H., Wu, L., & Li, X. (2019). Social media envy: How experience sharing on social networking sites drives millennials’ aspirational tourism consumption. Journal of Travel Research, 58(3), 355-369.
Lu, L. C., Chang, W. P., & Chang, H. H. (2014). Consumer attitudes toward blogger’s sponsored recommendations and purchase intention: The effect of sponsorship type, product type, and brand awareness. Computers in Human Behavior, 34, 258-266.
Maclnnis, D. J., Moorman, C., & Jaworski, B. J. (1991). Enhancing and measuring consumers’ motivation, opportunity, and ability to process brand information from ads. Journal of Marketing, 55(4), 32-53.
Mittal, B., & Lee, M. S. (1989). A causal model of consumer involvement. Journal of Economic Psychology, 10(3), 363-389.
Moutinho, L. (1987). Consumer behavior in tourism. European Journal of Marketing, 21(10), 5-44.
Noda, L., Kolosova, O., Levoshich, N., & Zatsarinnaya, Е. (2022). Going native: Prospects of native advertising development in the ASEAN and BRICS countries. Mind & Society, 1-14.
Park, C. W., & Moon, B. J. (2003). The relationship between product involvement and product knowledge: Moderating roles of product type and product knowledge type. Psychology & Marketing, 20(11), 977-997.
Pelletier, M. J., Krallman, A., Adams, F. G., & Hancock, T. (2020). One size doesn’t fit all: A uses and gratifications analysis of social media platforms. Journal of Research in Interactive Marketing, 14(2), 269-284.
Petty, R. E., Cacioppo, J. T., & Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of Consumer Research, 10(2). 135-146.
Probst, F., Grosswiele, F., & Pfleger, R. (2013). Who will lead and who will follow: Identifying influential users in online social networks: A critical review and future research directions. Business and Information Systems Engineering, 5(3), 179-193.
Ross, I. (1975). Perceived risk and consumer behavior: A critical review. In M. J. Schlinger (Ed.), Advances in Consumer Research (Vol. 2, pp. 1-20). Ann Abor, MI : Association for Consumer Research.
Santhadkolkarn, W., & Anantachart, S. (2017). Effects of model's beauty types in advertising and product types on consumer responses. Journal of Communication Arts, 35(2), 57-76.
Schiffman, L. G., & Wisenblit, J. (2019). Consumer behavior (12th ed., Global ed.). Harlow, UK: Pearson.
Shiv, B., & Fedorikhin, A. (1999). Heart and mind in conflict: The interplay of affect and cognition in consumer decision making. Journal of Consumer Research, 26(3), 278-292.
Smakova, J. (2017). Native Advertising on social media: The effect of heuristics on attitudes and purchase behavior. Unpublished master’s thesis. University of Amsterdam, The Netherlands.
Solomon, M. R. (2019). Consumer behavior: Buying, having, and being. (13th ed.). Harlow, UK: Pearson Prentice Hall.
Spears, N., & Singh, S. N. (2004). Measuring attitude toward the brand and purchase intentions. Journal of Current Issues and Research in Advertising, 26(2), 53-66.
Statista Research Department. (2021, November 23). Social media in Thailand: Statistics & facts. Retrieved March 12, 2022, from https://www.statista.com/topics/8194/social-media-in-thailand/#dossierKeyfigures
Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In M. J. Metzger, & A. J. Flanagin (Eds.). Digital media, youth, and credibility 73-100.
Sundar, S. S., Xu, Q., & Oeldorf-Hirsch, A. (2009). Authority vs. peer: How interface cues influence users. CHI'09 Extended Abstracts on human factors in computing systems, 4231-4236.
Tunshevavong, W. (2022). From online information seeking to native advertising exposure: Examining the Thai millennials on online information cues, ad click-through and brand awareness. Humanities, Arts and Social Sciences Studies, 22(1), 76-90.
Tutaj, K., & van Reijmersdal, E.A. (2012). Effects of online advertising format and persuasion knowledge on audience reactions. Journal of Marketing Communications, 18(1), 5-18.
Vijayasarathy, L. R. (2002). Product characteristics and internet shopping intentions. Internet Research, 12(5), 411–426.
Voss, K. E., Spangenberg, E. R., & Grohmann, B. (2003). Measuring the hedonic and utilitarian dimensions of consumer attitude. Journal of Marketing Research, 40(3), 310-320.
Wojdynski, B. W. (2016). Native advertising: Engagement, deception, and implications for theory. In R. Brown, V.K. Jones and B.M. Wang. (Eds.), The new advertising: branding, content and consumer relationships in a data-driven social media era (pp. 203-236). Westport, CT: Praeger/ABC Clio.
Wojdynski, B. W., & Evans, N. J. (2016). Going native: Effects of disclosure position and language on the recognition and evaluation of online native advertising. Journal of Advertising. 45(2), 157-168.
Wright, E., Khanfar, N. M., Harrington, C., & Kizer, L. E. (2010). The lasting effects of social media trends on advertising. Journal of Business & Economics Research, 8(11), 73-80.
Xu, Q. (2013). Social recommendation, source credibility, and recency effects of news cues in a social bookmarking website. Journalism and Mass Communication Quarterly, 90(4) 757-775.
Yang, J., & Jiang, M. (2021). Demystifying congruence effects in Instagram in-feed native ads: the role of media-based and self-based congruence. Journal of Research in Interactive Marketing, 15(4), 685-708. https://doi.org/10.1108/JRIM-03-2020-0048
Zaichkowsky, J. L. (1985) Measuring the involvement construct in marketing. Journal of Consumer Research, 12, 341–352.
Zhao, X., Yang, J., Xie, T., & Wang, Z. (2017). Examining advertising intrusiveness on Instagram: Hedonic and utilitarian attributes of brand and sponsored content. In T. Reichert (Ed), Proceedings of the 2017 Conference of the American Academy of Advertising (pp. 243-255). Athens, GA: University of Georgia.