Using the FCB grid to understand privacy concerns in social media advertising

References

• Abu, Z., M. Hala, Z.M. Obeidat, M.T. Alshurideh, M. Abuhashesh, M. Maqableh, and R. Masa’deh. 2021. Corporate social responsibility and patronage intentions: The mediating effect of brand credibility. Journal of Marketing Communications 27, no. 5: 510–33.
   Google Scholar
• Ahluwalia, R., and Z. Gürhan-Canli. 2000. The effects of extensions on the family brand name: An accessibility-diagnosticity perspective. Journal of Consumer Research 27, no. 3: 371–81.
   Web of Science ®Google Scholar
• Aiolfi, S., S. Bellini, and D. Pellegrini. 2021. Data-driven digital advertising: Benefits and risks of online behavioral advertising. International Journal of Retail & Distribution Management 49, no. 7: 1089–110.
   Web of Science ®Google Scholar
• Anand, B.N, and R. Shachar. 2009. Targeted advertising as a signal. Quantitative Marketing and Economics 7, no. 3: 237–66.
   Web of Science ®Google Scholar
• Ang, L., and M. Eisend. 2018. Single versus multiple measurement of attitudes: A meta-analysis of advertising studies validates the single-item measure approach. Journal of Advertising Research 58, no. 2: 218–27.
   Web of Science ®Google Scholar
• Anton, A.I., J.B. Earp, and J.D. Young. 2010. How internet users’ privacy concerns have evolved since 2002. IEEE Security & Privacy Magazine 8, no. 1: 21–7.
   Web of Science ®Google Scholar
• Bang, H., and B.W. Wojdynski. 2016. Tracking users’ visual attention and responses to personalized advertising based on task cognitive demand. Computers in Human Behavior 55, no. PB: 867–76.
   Web of Science ®Google Scholar
• Bergkvist, L., and J.R. Rossiter. 2007. The predictive validity of multiple-item versus single-item measures of the same constructs. Journal of Marketing Research 44, no. 2: 175–84.
   Web of Science ®Google Scholar
• Bettman, J.R., M.F. Luce, and J.W. Payne. 1998. Constructive consumer choice processes. Journal of Consumer Research 25, no. 3: 187–217.
   Web of Science ®Google Scholar
• Biel, A.L, and C.A. Bridgwater. 1990. Attributes of likable television commericals. Journal of Advertising Research 30, no. 3: 38–44.
   Web of Science ®Google Scholar
• Boerman, S.C., S. Kruikemeier, and F.J. Zuiderveen Borgesius. 2017. Online behavioral advertising: A literature review and research agenda. Journal of Advertising 46, no. 3: 363–76.
   Web of Science ®Google Scholar
• Bower, A.B. 2001. Highly attractive models in advertising and the women who loathe them: The implications of negative affect for spokesperson effectiveness. Journal of Advertising 30, no. 3: 51–63.
   Web of Science ®Google Scholar
• Buchholz, L.M, and R.E. Smith. 1991. The role of consumer involvement in determining cognitive response to broadcast advertising. Journal of Advertising 20, no. 1: 4–17.
   Web of Science ®Google Scholar
• Carlsson Hauff, J., and J. Nilsson. 2023. Individual costs and societal benefits: The privacy calculus of contact-tracing apps. Journal of Consumer Marketing 40, no. 2: 171–80.
   Web of Science ®Google Scholar
• Chang, C. 2007. Diagnostic advertising content and individual differences: Testing a resource-matching perspective with a Taiwanese sample. Journal of Advertising 36, no. 3: 75–84.
   Web of Science ®Google Scholar
• Cheong, H.J, and Y. Cheong. 2021. Updating the foote, cone & belding grid: Revisiting the product classifications of the FCB grid for online shopping and contemporary consumers’ decision making. Journal of Advertising Research 61, no. 1: 12–29.
   Web of Science ®Google Scholar
• Choi, H., H.J. Yoon, H.-J. Paek, and L.N. Reid. 2012. Thinking and feeling’ products and ‘utilitarian and value-expressive’ appeals in contemporary TV advertising: A content analytic test of functional matching and the FCB model. Journal of Marketing Communications 18, no. 2: 91–111.
   Google Scholar
• Choi, S.M, and N.J. Rifon. 2002. Antecedents and consequences of web advertising credibility. Journal of Interactive Advertising 3, no. 1: 12–24.
   Google Scholar
• Clore, G.L., N. Schwarz, and M. Conway. 1994. Affective causes and consequences of social information processing. In Handbook of social cognition: Basic processes; applications, 2nd ed. 1–2 vols., 323–417. Hillsdale, NJ, US: Lawrence Erlbaum Associates.
   Google Scholar
• de Groot, J.I.M. 2022. The personalization paradox in Facebook advertising: The mediating effect of relevance on the personalization–brand attitude relationship and the moderating effect of intrusiveness. Journal of Interactive Advertising 22, no. 1: 57–74.
   Google Scholar
• De Keyzer, F., G. van Noort, and S. Kruikemeier. 2022. Going too far? How consumers respond to personalized advertising from different sources. Journal of Electronic Commerce Research 23, no. 3: 138–59.
   Web of Science ®Google Scholar
• De Keyzer, F., N. Dens, and P. De Pelsmacker. 2015. Is this for me? How consumers respond to personalized advertising on social network sites. Journal of Interactive Advertising 15, no. 2: 124–34.
   Google Scholar
• De Keyzer, F., N. Dens, and P. De Pelsmacker. 2022. How and when personalized advertising leads to brand attitude, click, and WOM intention. Journal of Advertising 51, no. 1: 39–56.
   Web of Science ®Google Scholar
• De Pelsmacker, P., J. van den Bergh, and P. Anckaert. 1998. "Irritation, product type, consumer characteristics and advertising effectiveness." Paper presented at the marketing research and practice: Proceedings of the EMAC Conference: Track 4: Marketing management and communication, vol. 27, pp. 13–32.
   Google Scholar
• Doorn, J. V, and J.C. Hoekstra. 2013. Customization of online advertising: The role of intrusiveness. Marketing Letters 24, no. 4: 339–51.
   Web of Science ®Google Scholar
• Ewoldsen, D.R, and N. Rhodes. 2019. Media priming and accessibility. Media Effects 83–99.
   Google Scholar
• Feldman, J.M, and J.G. Lynch. 1988. Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. Journal of Applied Psychology 73, no. 3: 421–35.
   Web of Science ®Google Scholar
• Forgas, J.P. 1994. The role of emotion in social judgments: An introductory review and an affect infusion model (AIM). European Journal of Social Psychology 24, no. 1: 1–24.
   Web of Science ®Google Scholar
• Forgas, J.P. 1995. Mood and judgment: The affect infusion model (AIM). Psychological Bulletin 117, no. 1: 39–66.
   PubMed Web of Science ®Google Scholar
• Forgas, J.P, and G.H. Bower. 1987. Mood effects on person-perception judgments. Journal of Personality and Social Psychology 53, no. 1: 53–60.
   PubMed Web of Science ®Google Scholar
• Geuens, M., P. De Pelsmacker, and T. Faseur. 2011. Emotional advertising: Revisiting the role of product category. Journal of Business Research 64, no. 4: 418–26.
   Web of Science ®Google Scholar
• Haley, E., and M. Pittman. 2022. Remembering the FCB grid: Thinking, feeling, and involvement in the age of social media. Journal of Advertising 51, no. 3: 323–35.
   Web of Science ®Google Scholar
• Ham, C.-D. 2017. Exploring how consumers cope with online behavioral advertising. International Journal of Advertising 36, no. 4: 632–58.
   Web of Science ®Google Scholar
• Hargittai, E., and A. Marwick. 2016. What can I really do?” Explaining the privacy paradox with online apathy. International Journal of Communication 10: 21.
   Web of Science ®Google Scholar
• Hayes, A.F. 2018. Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation. Communication Monographs 85, no. 1: 4–40.
   Web of Science ®Google Scholar
• Hayes, J.L., N.H. Brinson, G.J. Bott, and C.M. Moeller. 2021. The influence of consumer–brand relationship on the personalized advertising privacy calculus in social media. Journal of Interactive Marketing 55, no. August: 16–30.
   Web of Science ®Google Scholar
• Heckler, S.E, and T.L. Childers. 1992. The role of expectancy and relevancy in memory for verbal and visual information: What is incongruency? Journal of Consumer Research 18, no. 4: 475–92.
   Web of Science ®Google Scholar
• Helberger, N., J. Huh, G. Milne, J. Strycharz, and H. Sundaram. 2020. Macro and exogenous factors in computational advertising: Key issues and new research directions. Journal of Advertising 49, no. 4: 377–93.
   Web of Science ®Google Scholar
• Homburg, C., N. Koschate, and W.D. Hoyer. 2006. The role of cognition and affect in the formation of customer satisfaction: A dynamic perspective. Journal of Marketing 70, no. 3: 21–31.
   Web of Science ®Google Scholar
• Howard, D.J, and R.A. Kerin. 2004. The effects of personalized product recommendations on advertisement response rates: The ‘try this. It works!’ technique. Journal of Consumer Psychology 14, no. 3: 271–9.
   Web of Science ®Google Scholar
• Hoy, M.G, and G. Milne. 2010. Gender differences in privacy-related measures for young adult Facebook users. Journal of Interactive Advertising 10, no. 2: 28–45.
   Google Scholar
• Huang, S.-L, and Y.-H. Lin. 2022. Exploring consumer online purchase and search behavior: An FCB grid perspective. Asia Pacific Management Review 27, no. 4: 245–56.
   Web of Science ®Google Scholar
• Huettl, V., and H. Gierl. 2012. Visual art in advertising: The effects of utilitarian vs. Hedonic product positioning and price information. Marketing Letters 23, no. 3: 893–904.
   Web of Science ®Google Scholar
• Huh, J., and E.C. Malthouse. 2020. Advancing computational advertising: Conceptualization of the field and future directions. Journal of Advertising 49, no. 4: 367–76.
   Web of Science ®Google Scholar
• Hussain, S., T.C. Melewar, C.V. Priporas, and P. Foroudi. 2020a. Examining the effects of advertising credibility on brand credibility, corporate credibility and corporate image: A qualitative approach. Qualitative Market Research: An International Journal 23, no. 4: 549–73.
   Web of Science ®Google Scholar
• Hussain, S., T.C. Melewar, P. Constantinos-Vasilios, F. Pantea, and D. Charles. 2020b. Examining the effects of celebrity trust on advertising credibility, brand credibility and corporate credibility. Journal of Business Research 109: 472–88.
   Web of Science ®Google Scholar
• Jo, S. 2004. Effect of content type on impact: Editorial vs. advertising. Public Relations Review 30, no. 4: 503–12.
   Web of Science ®Google Scholar
• Johar, J.S, and M.J. Sirgy. 1991. Value-expressive versus utilitarian advertising appeals: When and why to use which appeal. Journal of Advertising 20, no. 3: 23–33.
   Web of Science ®Google Scholar
• John, L.K., T. Kim, and K. Barasz. 2018. "Ads That Don’t Overstep" Harvard Business Review. https://hbr.org/2018/01/ads-that-dont-overstep
   Google Scholar
• Jung, A.-R. 2017. The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior 70, no. May: 303–9.
   Web of Science ®Google Scholar
• Katz, Daniel. 1960. The functional approach to the study of attitudes. Public opinion quarterly 24, no. 2: 163–204.
   Google Scholar
• Kehr, F., T. Kowatsch, D. Wentzel, and E. Fleisch. 2015. Blissfully ignorant: The effects of general privacy concerns, general institutional trust, and affect in the privacy calculus: Privacy calculus: Dispositions and affect. Information Systems Journal 25, no. 6: 607–35.
   Web of Science ®Google Scholar
• Kempf, D.S. 1999. Attitude formation from product trial: Distinct roles of cognition and affect for hedonic and functional products. Psychology and Marketing 16, no. 1: 35–50.
   Web of Science ®Google Scholar
• Kim, D.H., Y.H. Sung, S.Y. Lee, D. Choi, and Y. Sung. 2016. Are you on timeline or news feed? The roles of Facebook pages and construal level in increasing ad effectiveness. Computers in Human Behavior 57, no. April: 312–20.
   Web of Science ®Google Scholar
• Kim, H., and J. Huh. 2017. Perceived relevance and privacy concern regarding online behavioral advertising (OBA) and their role in consumer responses. Journal of Current Issues & Research in Advertising 38, no. 1: 92–105.
   Google Scholar
• Kim, S., E. Haley, and G.-Y. Koo. 2009. Comparison of the paths from consumer involvement types to ad responses between corporate advertising and product advertising. Journal of Advertising 38, no. 3: 67–80.
   Web of Science ®Google Scholar
• Kirmani, A., and A.R. Rao. 2000. No pain, no gain: A critical review of the literature on signaling unobservable product quality. Journal of Marketing 64, no. 2: 66–79.
   Web of Science ®Google Scholar
• Koufaris, M. 2002. Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research 13, no. 2: 205–23.
   Web of Science ®Google Scholar
• Laurent, G., and J.-N. Kapferer. 1985. Measuring consumer involvement profiles. Journal of Marketing Research 22, no. 1: 41–53.
   Web of Science ®Google Scholar
• Lee, H., and C.-H. Cho. 2020. Digital advertising: Present and future prospects. International Journal of Advertising 39, no. 3: 332–41.
   Web of Science ®Google Scholar
• Leon, P.G., J. Cranshaw, L.F. Cranor, J. Graves, M. Hastak, B. Ur, and G. Xu. 2012. “What do online behavioral advertising privacy disclosures communicate to users?” Paper presented at the Proceedings of the 2012 ACM Workshop on Privacy in the Electronic Society, 19–30. WPES ‘12. New York, NY, USA: Association for Computing Machinery.
   Google Scholar
• Li, C. 2016. When does web-based personalization really work? The distinction between actual personalization and perceived personalization. Computers in Human Behavior 54, no. January: 25–33.
   Web of Science ®Google Scholar
• Li, H., X. Luo, J. Zhang, and H. Xu. 2017. Resolving the privacy paradox: Toward a cognitive appraisal and emotion approach to online privacy behaviors. Information & Management 54, no. 8: 1012–22.
   Web of Science ®Google Scholar
• Li, Y., J. Yao, and J. Chen. 2021. The negative effect of scarcity cues on consumer purchase decisions in the hospitality industry during the COVID-19 pandemic. International Journal of Hospitality Management 94, no. April: 102815.
   Web of Science ®Google Scholar
• Libert, Timothy. 2015. Privacy implications of health information seeking on the web. Communications of the ACM 58, no. 3: 68–77.
   Google Scholar
• Lynch, J.G., Jr., H. Marmorstein, and M.F. Weigold. 1988. Choices from sets including remembered brands: Use of recalled attributes and prior overall evaluations. Journal of Consumer Research 15, no. 2: 169–84.
   Web of Science ®Google Scholar
• Malär, L., H. Krohmer, W.D. Hoyer, and B. Nyffenegger. 2011. Emotional brand attachment and brand personality: The relative importance of the actual and the ideal self. Journal of Marketing 75, no. 4: 35–52.
   Web of Science ®Google Scholar
• Martin, K. 2018. The penalty for privacy violations: How privacy violations impact trust online. Journal of Business Research 82: 103–16.
   Web of Science ®Google Scholar
• McLean, G., and K. Osei-Frimpong. 2019. Hey alexa … examine the variables influencing the use of artificial intelligent in-Home voice assistants. Computers in Human Behavior 99, no. October: 28–37.
   Web of Science ®Google Scholar
• Maslowska, E., E.G. Smit, and B. van den Putte. 2013. Assessing the cross-cultural applicability of tailored advertising: A comparative study between The Netherlands and Poland. International Journal of Advertising 32, no. 4: 487–511.
   Web of Science ®Google Scholar
• Miltgen, C.L., A.-S. Cases, and C.A. Russell. 2019. Consumers’ responses to Facebook advertising across PCs and mobile phones: A model for assessing the drivers of approach and avoidance of Facebook ads. Journal of Advertising Research 59, no. 4: 414–32.
   Web of Science ®Google Scholar
• Morimoto, M. 2021. Privacy concerns about personalized advertising across multiple social media platforms in Japan: The relationship with information control and persuasion knowledge. International Journal of Advertising 40, no. 3: 431–51.
   Web of Science ®Google Scholar
• Morrison, D.G, and D.C. Schmittlein. 1991. How many forecasters do you really have? Mahalanobis provides the intuition for the surprising Clemen and Winkler result. Operations Research 39, no. 3: 519–23.
   Web of Science ®Google Scholar
• Okazaki, S. 2004. How do Japanese consumers perceive wireless ads? A multivariate analysis. International Journal of Advertising 23, no. 4: 429–54.
   Google Scholar
• Park, S.-Y., M. Cho, and S. Kim. 2021. The effect of CSR expectancy violation: Value from expectancy violation theory and confirmation bias. Journal of Marketing Communications 27, no. 4: 365–88.
   Google Scholar
• Percy, L., and R.J. Donovan. 1991. A better advertising planning grid. Journal of Advertising Research 31, no. 5: 11–21.
   Web of Science ®Google Scholar
• Park, C.W, and S.M. Young. 1986. Consumer response to television commercials: The impact of involvement and background music on brand attitude formation. Journal of Marketing Research 23, no. 1: 11–24.
   Web of Science ®Google Scholar
• Pitardi, V., and H.R. Marriott. 2021. Alexa, she’s not human but… unveiling the drivers of consumers’ trust in voice-based artificial intelligence. Psychology & Marketing 38, no. 4: 626–42.
   Web of Science ®Google Scholar
• Pittman, M., and A. Abell. 2021. More trust in fewer followers: Diverging effects of popularity metrics and green orientation social media influencers. Journal of Interactive Marketing 56: 70–82.
   Web of Science ®Google Scholar
• Pittman, M., and E. Haley. 2022. Cognitive load and social media advertising. Journal of Interactive Advertising 23, no. 1: 33–54.
   Google Scholar
• Puzakova, M., and P. Aggarwal. 2018. “Brands as rivals: Consumer pursuit of distinctiveness and the role of brand anthropomorphism.” edited by Eileen fischer and JoAndrea Hoegg. Journal of Consumer Research 45, no. 4: 869–88.
   Web of Science ®Google Scholar
• Qin, X., and Z. Jiang. 2019. The impact of AI on the advertising process: The Chinese experience. Journal of Advertising 48, no. 4: 338–46.
   Web of Science ®Google Scholar
• Raghunathan, R., and J.R. Irwin. 2001. Walking the hedonic product treadmill: Default contrast and mood-based assimilation in judgments of predicted happiness with a target product. Journal of Consumer Research 28, no. 3: 355–68.
   Web of Science ®Google Scholar
• Ratchford, B.T. 1987. New insights about the FCB grid. Journal of Advertising Research 27, no. 4: 24–38.
   Web of Science ®Google Scholar
• Reich, B.J, and M. Pittman. 2020. An appeal to intimacy: Consumer response to platform-appeal fit on social media. Journal of Consumer Psychology 30, no. 4: 660–70.
   Web of Science ®Google Scholar
• Rocklage, M.D, and R.H. Fazio. 2020. The enhancing versus backfiring effects of positive emotion in consumer reviews. Journal of Marketing Research 57, no. 2: 332–52.
   Web of Science ®Google Scholar
• Roskos-Ewoldsen, D.R, and R.H. Fazio. 1992. The accessibility of source likability as a determinant of persuasion. Personality and Social Psychology Bulletin 18, no. 1: 19–25.
   Web of Science ®Google Scholar
• Rossiter, J.R. 2002. The C-OAR-SE procedure for scale development in marketing. International Journal of Research in Marketing 19, no. 4: 305–35.
   Web of Science ®Google Scholar
• Schwarz, N., H. Bless, and G. Bohner. 1991. Mood and persuasion: Affective states influence the processing of persuasive communications. In Advances in experimental social psychology, ed. Mark P. Zanna, vol. 24, 161–99. Academic Press.
   Google Scholar
• Shavitt, S. 1990. The role of attitude objects in attitude functions. Journal of Experimental Social Psychology 26, no. 2: 124–48.
   Web of Science ®Google Scholar
• Shavitt, S., and M.R. Nelson. 2002. The role of attitude functions in persuasion and social judgment. In The persuasion handbook: Developments in theory and practice, ed. Dillard JP & Pfau M., 137–153.
   Google Scholar
• Sheinin, D.A., S. Varki, and C. Ashley. 2011. The differential effect of ad novelty and message usefulness on brand judgments. Journal of Advertising 40, no. 3: 5–18.
   Web of Science ®Google Scholar
• Sirgy, M.J., J.S. Johar, A.C. Samli, and C.B. Claiborne. 1991. Self-congruity versus functional congruity: Predictors of consumer behavior. Journal of the Academy of Marketing Science 19, no. 4: 363–75.
   Google Scholar
• Simmons, C.J., B.A. Bickart, and J.G. Lynch. Jr. 1993. Capturing and creating public opinion in survey research. Journal of Consumer Research 20, no. 2: 316–29.
   Web of Science ®Google Scholar
• Spiller, S.A., G.J. Fitzsimons, J.G. Lynch, and G.H. Mcclelland. 2013. Spotlights, floodlights, and the magic number zero: Simple effects tests in moderated regression. Journal of Marketing Research 50, no. 2: 277–88.
   Web of Science ®Google Scholar
• Sung, Y.H., D.H. Kim, D. Choi, and S.Y. Lee. 2020. Facebook ads not working in the same way: The effect of cultural orientation and message construals on consumer response to social media ads. Telematics and Informatics 52, no. September: 101427.
   Web of Science ®Google Scholar
• Taylor, C.R. 2013. Editorial: Customised communications. International Journal of Advertising 32, no. 4: 483–5.
   Web of Science ®Google Scholar
• Taylor, J.F., J. Ferguson, and P.S. Ellen. 2015. From trait to state: Understanding privacy concerns. Journal of Consumer Marketing 32, no. 2: 99–112.
   Web of Science ®Google Scholar
• Tucker, C.E. 2014. Social networks, personalized advertising, and privacy controls. Journal of Marketing Research 51, no. 5: 546–62.
   Web of Science ®Google Scholar
• Van den Broeck, E., B. Zarouali, and K. Poels. 2019. Chatbot advertising effectiveness: When does the message get through? Computers in Human Behavior 98, no. September: 150–7.
   Web of Science ®Google Scholar
• Voorveld, H.A. 2019. Brand communication in social media: A research agenda. Journal of Advertising 48, no. 1: 14–26.
   Web of Science ®Google Scholar
• Wang, H., M.K.O. Lee, and C. Wang. 1998. Consumer privacy concerns about internet marketing. Communications of the ACM 41, no. 3: 63–70. https://go.gale.com/ps/i.do?p=AONE&sw=w&issn=00010782&v=2.1&it=r&id=GALE%7CA20561633&sid=googleScholar&linkaccess=abs.
   Web of Science ®Google Scholar
• Warren, S.D, and L.D. Brandeis. 1890. The right to privacy. Harvard Law Review 4, no. 5: 193.
   Google Scholar
• Wyer, R.S., G.L. Clore, and L.M. Isbell. 1999. Affect and information processing. In Advances in experimental social psychology, ed. Mark P. Zanna, vol. 31, 1–77. Academic Press.
   Google Scholar
• Xua, X., T.-Y. Wub, and D.J. Atkinc. 2021. Effects of website credibility and brand trust on responses to online behavioral advertising. Journal of Communication Technology 4, no. 2: 32–57.
   Google Scholar
• Yi, C., Z. Jiang, and I. Benbasat. 2017. Designing for diagnosticity and serendipity: An investigation of social product-search mechanisms. Information Systems Research 28, no. 2: 413–29.
   Web of Science ®Google Scholar
• Yssel, J.C. 1996. Demonstrating the superiority of the FCB grid as a tool for students to write effective advertising strategy. Journal of Advertising Education 1, no. 1: 31–41.
   Google Scholar
• Zha, X., J. Li, and Y. Yan. 2015. Advertising value and credibility transfer: Attitude towards web advertising and online information acquisition. Behaviour & Information Technology 34, no. 5: 520–32.
   Web of Science ®Google Scholar