A dark side of retargeting? How advertisements that follow users affect post-purchase consumer behavior: Evidence from the tourism industry in Saudi Arabia
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DOIhttp://dx.doi.org/10.21511/im.19(4).2023.19
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Article InfoVolume 19 2023, Issue #4, pp. 234-246
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Creative Commons Attribution 4.0 International License
This study aims to explore the complex effects of post-purchase retargeting ads on consumer behavior, with a focus on expectation confirmation, satisfaction, and repurchase intentions. Additionally, it examines the influence of time spent online on these effects. Anchored in expectation confirmation theory (ECT), the study analyzes responses from 396 Saudi Arabian e-tourism customers who encountered competitive retargeting ads after purchasing an e-tourism package. The analysis employs partial least squares structural equation modeling (PLS-SEM) and multigroup analysis (MGA) to test the hypotheses. A notable finding is the direct negative impact of retargeting ads on expectation confirmation: increased exposure to such ads post-purchase seems to diminish the perception that initial expectations of the product or service are being met. The negative effect of these ads also indirectly influences satisfaction and repurchase intentions. Furthermore, the MGA results indicate variations in this negative impact based on the time spent online. Specifically, the more time consumers spend online, the stronger the negative impact, leading to a significant decrease in satisfaction and repurchase intentions. These insights reveal the complex nature of post-purchase retargeting ads and underscore the importance of accounting for consumers’ online behavior. They offer valuable direction for marketers to refine retargeting strategies to better resonate with consumer expectations.
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JEL Classification (Paper profile tab)M31, M37, Z33, L83
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References42
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Tables8
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Figures1
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- Figure 1. Path diagram results
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- Table 1. Construct definitions and measurements
- Table 2. Reliability and validity criteria
- Table 3. HTMT ratios
- Table 4. Evaluation of common method bias
- Table 5. Path coefficients, bootstrap confidence intervals, and standardized root mean square residuals
- Table 6. R2, Q2, and PLS predict procedure
- Table 7. Steps 2 and 3 of the MICOM procedure
- Table 8. Multigroup comparison results
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- Aguirre, E., Mahr, D., Grewal, D., De Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34-49.
- Al-Zahrani, A. (2015). Toward digital citizenship: Examining factors affecting participation and involvement in the internet society among higher education students. International Education Studies, 8(12), 203-217.
- Baek, T. H., & Morimoto, M. (2012). Stay away from me. Journal of Advertising, 41(1), 59-76.
- Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370.
- Bleier, A., & Eisenbeiss, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390-409.
- Brislin, R. W. (1976). Comparative research methodology: Cross-cultural studies. International Journal of Psychology, 11(3), 215-229.
- Chen, J., & Stallaert, J. (2014). An economic analysis of online advertising using behavioral targeting. MIS Quarterly, 38(2), 429-449.
- Chen, S.-C., & Lin, C.-P. (2019). Understanding the effect of social media marketing activities: The mediation of social identification, perceived value, and satisfaction. Technological Forecasting and Social Change, 140, 22-32.
- Cooper, D. A., Yalcin, T., Nistor, C., Macrini, M., & Pehlivan, E. (2023). Privacy considerations for online advertising: A stakeholder’s perspective to programmatic advertising. Journal of Consumer Marketing, 40(2), 235-247.
- Do Valle, P. O., & Assaker, G. (2016). Using partial least squares structural equation modeling in tourism research: A review of past research and recommendations for future applications. Journal of Travel Research, 55(6), 695-708.
- Dubrovski, D. (2001). The role of customer satisfaction in achieving business excellence. Total Quality Management, 12(7-8), 920-925.
- Farman, L., Comello, M. L., & Edwards, J. R. (2020). Are consumers put off by retargeted ads on social media? Evidence for perceptions of marketing surveillance and decreased ad effectiveness. Journal of Broadcasting & Electronic Media, 64(2), 298-319.
- Fettahlıoglu, M., Cikmaz, G., & Ates, N. B. (2019). The effect of social media addiction and nomophobia on academic procrastination. International Journal of Social Humanities Sciences Research, 6(42), 2875-2896.
- Franke, G., & Sarstedt, M. (2019). Heuristics versus statistics in discriminant validity testing: A comparison of four procedures. Internet Research, 29(3), 430-447.
- Hair, F. J., Hult, M. G., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Cham: Springer International Publishing AG.
- Hair, J. F., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458.
- Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
- Henseler, J., Ringle, C.M., & Sinkovics, R.R. (2009). The use of partial least squares path modeling in international marketing. In R.R. Sinkovics & P.N. Ghauri (Eds.), New Challenges to International Marketing (pp. 277-319). Leeds: Emerald Group Publishing Limited.
- Jiang, Z., Chan, T., Che, H., & Wang, Y. (2021). Consumer search and purchase: An empirical investigation of retargeting based on consumer online behaviors. Marketing Science, 40(2), 219-240.
- Johnson, G. A., Lewis, R. A., & Nubbemeyer, E. I. (2017). Ghost ads: Improving the economics of measuring online ad effectiveness. Journal of Marketing Research, 54(6), 867-884.
- Kim, M., & Ohk, K. (2017). The bright side and dark side of retargeting advertising. Information, 20(5), 3073-3081.
- Kock, N. (2015). Common method bias in PLS-SEM. International Journal of E-Collaboration, 11(4), 1-10.
- Lambrecht, A., & Tucker, C. (2013). When does retargeting work? Information specificity in online advertising. Journal of Marketing Research, 50(5), 561-576.
- Latan, H., & Noonan, R. (2017). Partial least squares path modeling: Basic concepts, methodological issues and applications (1st ed.). Springer.
- Li, J., Luo, X., Lu, X., & Moriguchi, T. (2021). The double-edged effects of e-commerce cart retargeting: Does retargeting too early backfire? Journal of Marketing, 85(4), 123-140.
- Moralista, R. B., & Oducado, R. M. F. (2020). Faculty perception toward online education in a state college in the Philippines during the coronavirus disease 19 (COVID-19) pandemic. Universal Journal of Educational Research, 8(10), 4736-4742.
- Mutalik, N. R., Tejaswi, T. P., Moni, S., & Choudhari, S. B. (2018). A cross-sectional study on assessment of prevalence of Internet addiction and its correlates among professional college students. Open Journal of Psychiatry & Allied Sciences, 9(1), 20-25.
- Oliver, R. L. (1977). Effect of expectation and disconfirmation on postexposure product evaluations: An alternative interpretation. Journal of Applied Psychology, 62(4), 480-486.
- Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.
- Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of Retailing, 57(3), 25-48.
- Omar, A. M., & Atteya, N. (2020). The impact of digital marketing on consumer buying decision process in the Egyptian market. International Journal of Business and Management, 15(7), 120-132.
- Pinquart, M., Endres, D., Teige-Mocigemba, S., Panitz, C., & Schütz, A. C. (2021). Why expectations do or do not change after expectation violation: A comparison of seven models. Consciousness and Cognition, 89, 103086.
- Ringle, C., Da Silva, D., & Bido, D. (2014). Structural equation modeling with the SmartPLS. Revista Brasileira de Marketing, 13(2), 56-73.
- Sahni, N. S., Narayanan, S., & Kalyanam, K. (2019). An experimental investigation of the effects of retargeted advertising: The role of frequency and timing. Journal of Marketing Research, 56(3), 401-418.
- Semerádová, T., & Weinlich, P. (2023). The impact of cookie regime change on the effectiveness of automatic retargeting in advertising. Innovative Marketing, 19(2), 101-114.
- Shmueli, G., Sarstedt, M., Hair, J., Cheah, J., Ting, H., Vaithilingam, S., & Ringle, C. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322-2347.
- Van Doorn, J., & Hoekstra, J. C. (2013). Customization of online advertising: The role of intrusiveness. Marketing Letters, 24(4), 339-351.
- Villas-Boas, J. M., & Yao, Y. (J.). (2021). A dynamic model of optimal retargeting. Marketing Science, 40(3), 428-458.
- Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares: Concepts, methods and applications. Berlin: Springer.
- Zarouali, B., Ponnet, K., Walrave, M., & Poels, K. (2017). “Do you like cookies?” Adolescents’ skeptical processing of retargeted Facebook-ads and the moderating role of privacy concern and a textual debriefing. Computers in Human Behavior, 69, 157-165.
- Zhang, Y., Trusov, M., Stephen, A. T., & Jamal, Z. (2017). Online shopping and social media: Friends or foes? Journal of Marketing, 81(6), 24-41.
- Zhong, Z., Luo, J., & Zhang, M. (2015). Understanding antecedents of continuance intention in mobile travel booking service. International Journal of Business and Management, 10(9).