Responses to anti-adblock filters: theoretical foundations, influential factors, and managerial implications
Abstract
Ad-supported websites face an increasing loss of monetizable ad impressions due to the rapid spread of adblockers, which allow users to get desired website content without unwanted advertising. As a countermeasure, many of these websites use anti-adblock filters, which detect adblock users and prevent their access to website content unless their adblockers are disabled. Users may certainly respond by disabling their adblockers but also by leaving the website or trying to bypass the anti-adblock filter. To better understand the choice among these responses, we propose a conceptual framework that combines psychological reactance theory along with uses and gratifications theory. We also hypothesize the influence of four user-related factors: (a) more positive (negative) attitudes toward online advertising encourage adblocker deactivation (website abandonment); (b) longer adblock usage experiences enable filter bypassing; (c) wider (narrower) scopes of online activities stimulate filter bypassing (website abandonment); and (d) greater online privacy concerns discourage adblocker deactivation. These hypotheses were supported by a survey conducted by the Spanish advertising industry, but the influence of breadth of online activities was negligible in practice. Our findings suggest the importance of improving attitudes toward online advertising, reducing online privacy concerns, and searching for alternative ways to monetize website visits.
First published online 29 October 2020
Keyword : anti-adblocking, advertising avoidance, online privacy, advertising management, psychological reactance, uses and gratifications theory
How to Cite
Redondo, I., & Aznar, G. (2021). Responses to anti-adblock filters: theoretical foundations, influential factors, and managerial implications. Journal of Business Economics and Management, 22(1), 42-60. https://doi.org/10.3846/jbem.2020.13698
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Youn, S., & Kim, S. (2019). Understanding ad avoidance on Facebook: Antecedents and outcomes of psychological reactance. Computers in Human Behavior, 98, 232–244. https://doi.org/10.1016/j.chb.2019.04.025
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Aseri, M., Dawande, M., Janakiraman, G., & Mookerjee, V. S. (2020). Ad-blockers: A blessing or a curse? Information Systems Research, 31(2), 627–646. https://doi.org/10.1287/isre.2019.0906
Bandura, A. (1978). Self-efficacy: Toward a unifying theory of behavioral change. Advances in Behavior Research and Therapy, 1(4), 139–161. https://doi.org/10.1016/0146-6402(78)90002-4
Bleier, A., & Eisenbeiss, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390–409. https://doi.org/10.1016/j.jretai.2015.04.001
Boerman, S. C., Kruikemeier, S., & Borgesius, F. J. Z. (2017). Online behavioral advertising: A literature review and research agenda. Journal of Advertising, 46(3), 363–376. https://doi.org/10.1080/00913367.2017.1339368
Brehm, S. S., & Brehm, J. W. (1981). Psychological reactance: A theory of freedom and control. Academic Press.
Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145–158. https://doi.org/10.2307/249749
Dinev, T., & Hart, P. (2004). Internet privacy concerns and their antecedents – measurement validity and a regression model. Behavior & Information Technology, 23(6), 413–422. https://doi.org/10.1080/01449290410001715723
Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer-Mediated Communication, 6(1), JCMC611. https://doi.org/10.1111/j.1083-6101.2000.tb00110.x
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. https://doi.org/10.1080/00913367.2002.10673678
EUR-Lex. (2016). Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC. https://eur-lex.europa.eu/eli/reg/2016/679/oj
Gordon, B. R., Jerath, K., Katona, Z., Narayanan, S., Shin, J., & Wilbur, K. C. (2020). Inefficiencies in digital advertising markets. Journal of Marketing. https://doi.org/10.1177/0022242920913236
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Pearson Education.
Ham, C.-D. (2017). Exploring how consumers cope with online behavioral advertising. International Journal of Advertising, 36(4), 632–658. https://doi.org/10.1080/02650487.2016.1239878
Hargittai, E., & Hinnant, A. (2008). Digital inequality: Differences in young adults’ use of the internet. Communication Research, 35(5), 602–621. https://doi.org/10.1177/0093650208321782
Helsper, E. J., & Eynon, R. (2013). Distinct skill pathways to digital engagement. European Journal of Communication, 28(6), 696–713. https://doi.org/10.1177/0267323113499113
Ji, P., & Fu, W. W. (2013). Love Internet, love online content: Predicting Internet affinity with information gratification and social gratifications. Internet Research, 23(4), 396–413. https://doi.org/10.1108/IntR-08-2012-0155
Lim, W. M., & Ting, D. H. (2012). E-shopping: An analysis of the uses and gratifications theory. Modern Applied Science, 6(5), 48–63. https://doi.org/10.5539/mas.v6n5p48
MacKenzie, S. B., & Lutz, R. J. (1989). An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. Journal of Marketing, 53(2), 48–65. https://doi.org/10.2307/1251413
Mazel, J., Garnier, R., & Fukuda, K. (2019). A comparison of web privacy protection techniques. Computer Communications, 144, 162–174. https://doi.org/10.1016/j.comcom.2019.04.005
Miyazaki, A. D. (2008). Online privacy and the disclosure of cookie use: Effects on consumer trust and anticipated patronage. Journal of Public Policy & Marketing, 27(1), 19–33. https://doi.org/10.1509/jppm.27.1.19
Novak, T. P., Hoffman, D. L., & Yung, Y.-F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22–42. https://doi.org/10.1287/mksc.19.1.22.15184
Palmgreen, P., Wenner, L. A., & Rosengren, K. E. (1985). Uses and gratifications research: The past ten years. In K. Rosengren, L. Wenner, & P. Palmgreen (Eds.), Media gratifications research: Current perspectives (pp. 11–37). Sage.
Payne, G. A., Severn, J. J. H., & Dozier, D. M. (1988). Uses and gratifications motives as indicators of magazine readership. Journalism Quarterly, 65(4), 909–913. https://doi.org/10.1177/107769908806500411
Redondo, I., & Aznar, G. (2018). To use or not to use ad blockers? The roles of knowledge of ad blockers and attitude toward online advertising. Telematics and Informatics, 35(6), 1607–1616. https://doi.org/10.1016/j.tele.2018.04.008
Redondo, I., & Bernal, J. (2016). Product placement versus conventional advertising: The impact on brand choice of integrating promotional stimuli into movies. Journal of Promotion Management, 22(6), 773–791. https://doi.org/10.1080/10496491.2016.1214205
Redondo, I., & Charron, J.-P. (2013). The payment dilemma in movie and music downloads: An explanation through cognitive dissonance theory. Computers in Human Behavior, 29(5), 2037–2046. https://doi.org/10.1016/j.chb.2013.04.015
Rojas-Méndez, J. I., & Davies, G. (2005). Avoiding television advertising: Some explanations from time allocation theory. Journal of Advertising Research, 45(1), 34–48. https://doi.org/10.1017/S0021849905050154
Rubin, A. M. (1983). Television uses and gratifications: The interactions of viewing patterns and motivations. Journal of Broadcasting, 27(1), 37–51. https://doi.org/10.1080/08838158309386471
Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communication and Society, 3(1), 3–37. https://doi.org/10.1207/S15327825MCS0301_02
Shiller, B., Waldfogel, J., & Ryan, J. (2018). The effect of ad blocking on website traffic and quality. RAND Journal of Economics, 49(1), 43–63. https://doi.org/10.1111/1756-2171.12218
Smock, A. D., Ellison, N. B., Lampe, C., & Wohn, D. Y. (2011). Facebook as a toolkit: A uses and gratification approach to unbundling feature use. Computers in Human Behavior, 27(6), 2322–2329. https://doi.org/10.1016/j.chb.2011.07.011
Söllner, J., & Dost, F. (2019). Exploring the selective use of ad blockers and testing banner appeals to reduce ad blocking. Journal of Advertising, 48(3), 302–312. https://doi.org/10.1080/00913367.2019.1613699
Speck, P. S., & Elliott, M. T. (1997). Predictors of advertising avoidance in print and broadcast media. Journal of Advertising, 26(3), 61–76. https://doi.org/10.1080/00913367.1997.10673529
Stafford, M. R., & Stafford, T. F. (1996). Mechanical commercial avoidance: A uses and gratifications perspective. Journal of Current Issues & Research in Advertising, 18(2), 27–38. https://doi.org/10.1080/10641734.1996.10505049
Tucker, C. E. (2014). Social networks, personalized advertising, and privacy controls. Journal of Marketing Research, 51(5), 546–562. https://doi.org/10.1509/jmr.10.0355
Tudoran, A. A. (2019). Why do Internet consumers block ads? New evidence from consumer opinion mining and sentiment analysis. Internet Research, 29(1), 144–166. https://doi.org/10.1108/IntR-06-2017-0221
Wang, Y., & Sun, S. (2010). Assessing beliefs, attitudes, and behavioral responses toward online advertising in three countries. International Business Review, 19(4), 333–344. https://doi.org/10.1016/j.ibusrev.2010.01.004
Youn, S., & Kim, S. (2019). Understanding ad avoidance on Facebook: Antecedents and outcomes of psychological reactance. Computers in Human Behavior, 98, 232–244. https://doi.org/10.1016/j.chb.2019.04.025
Zhu, S., Iqbal, U., Wang, Z., Qian, Z., Shafiq, Z., & Chen, W. (2019). ShadowBlock: A lightweight and stealthy adblocking browser. In Proceedings of the 2019 World Wide Web Conference (pp. 2483–2493). ACM Press. https://doi.org/10.1145/3308558.3313558