BEHAVIOURAL TARGETING, PERCEPTION OF INTERNET USERS AND CLICK-THROUGH INTENTIONS: IMPLICATIONS FOR DIGITAL ENTREPRENEURS IN NIGERIA
Keywords:
Ads Based On Users’ Interest, Ads Intrusiveness, Behavioural Targeting, Click-Through Intention, Perception
Abstract
This study assessed the effect of adverts (Ads) based on users’ interest, Ads intrusiveness on the perception of behavioural targeting and click-through intention. The study further examined how the perception of behavioural targeting mediates the interaction between Ads based on users’ interest, Ads intrusiveness and click-through intentions. The study was a descriptive survey, and the approach was deductive. The study collected primary data from a sample of 376 internet users in Nigeria using a cloud-based questionnaire. The data obtained were analysed using descriptive and inferential statistical tools. Partial least square structural equation modelling (PLS-SEM) was used to test the hypotheses. Findings showed that Ads based on users’ interest and Ads intrusiveness predict click-through intentions and the perception of behavioural targeting. Perception of behavioural targeting mediated the interaction between Ads based on users’ interests and click-through intentions. Overall, the study concluded that Ads based on users’ interest and Ads intrusiveness influences the perception of behavioural targeting, which affects click-through intention. Hence the study recommended that digital entrepreneurs carefully design, manage and control the Ads contents they direct to customers. Digital entrepreneurs should exercise caution in implementing their behavioural targeting strategy so as not to breach an acceptable threshold.
JEL Classification Codes: M13, M31, M37.
References
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Kaspar, K., Weber, S. L., & Wilbers, A. (2019). Personally relevant online advertisements: effects of demographic targeting on visual attention and brand evaluation. PloS ONE, 14(2), 1–18.
Kenny, D., & Marshall, J. F. (2000). Contextual marketing: the real business of the internet. Harvard Business Review, 78(6), 119–125.
Kline, R. B. (2011). Principles and practice of structural equation modeling. Guilford Press.
Kondalkar, V. G. (2007). Organizational behaviour. New Age International Publishers.
Koskinen, S. (2017). Targeted social media advertising and consumer decision making in online buying behaviour. Oulu business school.
Kumar, K., & Patel, A. (2014). A research paper on measuring effectiveness of online behavioural advertisements. International Journal of Scientific Research and Management (IJSRM), 2(12), 1825–1832.
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Moreno, A. M., & Casillas, J. C. (2008). Entrepreneurial orientation and growth of SMEs: a causal model (pp. 507–528). Baylor University.
Olayiwola, A. . (2007). Procedures in educational research. Hanjim Publications.
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Pickens, J. (2005). Attitudes and perceptions of individuals. In N. Borkowski (Ed.), Organizational Behavior in Health Care (pp. 43–76). Jones and Bartlett Publishers.
Ringle, C. M., Sarstedt, M., Mitchell, R., & Siegfried, P. G. (2018). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 1–27. https://doi.org/10.1080/09585192.2017.1416655
Schedwin, J. (2008). Behavioural targeting: issues involving the Microsoft-aquantive and google-doubleclick mergers, and the current and proposed solutions to those issues. Journal of Law and Policy for the Information Society, 4(3), 710–730.
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict.
Smit, E. G., Noort, G. Van, & Voorveld, H. A. M. (2014). Understanding online behavioural advertising: user knowledge, privacy concerns and online coping behaviour in Europe. Computers in Human Behavior, 32, 15–22. https://doi.org/10.1016/j.chb.2013.11.008
Soares, M. C., & Perin, M. G. (2019). Entrepreneurial orientation and firm performance: An updated meta-analysis. RAUSP Management Journal. https://doi.org/10.1108/RAUSP-01-2019-0014
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Varnali, K. (2019). Online behavioural advertising: An integrative review. Journal of Marketing Communications, 00(00), 1–22. https://doi.org/10.1080/13527266.2019.1630664
Wiese, M., Akareem, H. S., & Wiese, M. (2020). Determining perceptions, attitudes and behaviour towards social network site advertising in a three-country context social network site advertising in a three-country context. Journal of Marketing Management, 00(00), 1–36. https://doi.org/10.1080/0267257X.2020.1751242
Yan, J., Liu, N., Wang, G., Zhang, W., Jiang, Y., & Chen, Z. (2009). How much can behavioural targeting help online advertising? In Proceedings of the 18th International Conference on World Wide Web, WWW ’09, 261–270.
Ali, F., Gon, W. K., & Ryu, K. (2016). The effect of physical environment on passenger delight and satisfaction: Moderating effect of national identity. Tourism Management, 57, 213–224. https://doi.org/10.1016/j.tourman.2016.06.004
Alnahdi, S., Maged, A., & Alkayid, K. (2014). The effectiveness of online advertising via the behavioural targeting mechanism. The Business and Management Review, 5(1), 23–31.
Bayer, E., Srinivasan, S., Riedl, E. J., & Skiera, B. (2020). The impact of online display advertising and paid search advertising relative to offline advertising on firm performance and firm value. International Journal of Research in Marketing, 37, 789–804. https://doi.org/10.1016/j.ijresmar.2020.02.002
Beales, H. (2011). The value of behavioural targeting. Network Advertising Initiative (NAI).
Benitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020). How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research. Information & Management, 57(2), 1–16. https://doi.org/10.1016/j.im.2019.05.003
Boerman, S. C., Kruikemeier, S., & Borgesius, F. J. Z. (2017). Online behavioural advertising: a literature review and research agenda. Journal of Advertising, 46(3), 364–376. https://doi.org/10.1080/00913367.2017.1339368
Breznitz, D., & Palermo, V. (2013). Big data, big profits? Understanding the role of targeting technologies as part of a mixed online advertisement strategy (No.311).
Carrascosa, J. M., Cuevas, R., Mikians, J., Erramilli, V., & Laoutaris, N. (2015). I always feel like somebody’s watching me: measuring online behavioural advertising. CoNEXT 15 Proceedings of the 11th ACM Conference on Emerging Networking Experiments and Technologies, 1–13.
Dai, F. (2012). A model of network marketing business entrepreneurial performance. University of Technology, Sydney.
Dai, F., Teo, S., & Wang, K. Y. (1995). Identifying and measuring motivational factors in conducting network marketing business by Chinese immigrants (pp. 1–23). University of Technology, Sydney.
Dai, F., Teo, S., & Wang, K. Y. (2007). Performance of entrepreneurial Chinese immigrants in network marketing organisations (pp. 1–20). University of Technology, Sydney.
Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297–316.
Ducoffe, R. H. (1995). How consumers assess the value of advertising. Journal of Current Issues and Research in Advertising, 17(1), 1–18.
Dwyer, C. (2011). The effect of behavioural targeting on trust in E-commerce (pp. 1–28). https://doi.org/http://ssrn.com/abstract=1801366
Ebrahim, R. S. (2013). A Study of Brand Preference: An Experiential View. Brunel University, London.
Fachryto, T., & Achyar, A. (2018). Effect of online behavioural advertising implementation on attitude toward Ad and purchase intention in Indonesian e-marketplace. Sriwijaya International Journal of Dynamic Economics and Business, 2(2), 123–138.
Farahat, A., & Bailey, M. (2012). How effective is targeted advertising? International World Wide Web Conference, 111–120.
Fish, W. (2010). Philosophy of Perception: A Contemporary Introduction. Routledge.
Garson, G. D. (2016). Partial least squares: Regression and structural equation models (2016 Eds). Statistical Associates Publishing.
Gauzente, C. (2009). The intention to click on sponsored links-an analysis of the moderating role of prior knowledge. Actes Du 25th Congre’s International de l’AFM-Londres, 14 et 15 Mai 2009, 1–18.
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2013). A primer on partial least squares structural equation modelling (PLS-SEM). Sage Publications.
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. https://doi.org/10.1108/EBR-11-2018-0203
Hariharan, V. G., Talukdar, D., & Kwon, C. (2015). Optimal targeting of advertisement for new products with multiple consumer segments. International Journal of Research Marketing, 32, 263–271. https://doi.org/10.2139/ssrn.2555682
Helberger, N., Huh, J., Milne, G., Strycharz, J., & Sundaram, H. (2020). Macro and exogenous factors in computational advertising: Key issues and new research directions. Journal of Advertising, 49(4), 377–393. https://doi.org/10.1080/00913367.2020.1811179
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
Jain, D. C. (2019). Mastering partial least squares structural equation modeling (PLS-SEM) with SmartPLS in 38hours. iUniverse.
Kalra, S., Kondepudi, M., & Sridharan, A. (2016). Consumer attitude towards network marketing in a global scenario. Intercontinental Journal of Marketing Research Review, 4(12), 9–14.
Kaspar, K., Weber, S. L., & Wilbers, A. (2019). Personally relevant online advertisements: effects of demographic targeting on visual attention and brand evaluation. PloS ONE, 14(2), 1–18.
Kenny, D., & Marshall, J. F. (2000). Contextual marketing: the real business of the internet. Harvard Business Review, 78(6), 119–125.
Kline, R. B. (2011). Principles and practice of structural equation modeling. Guilford Press.
Kondalkar, V. G. (2007). Organizational behaviour. New Age International Publishers.
Koskinen, S. (2017). Targeted social media advertising and consumer decision making in online buying behaviour. Oulu business school.
Kumar, K., & Patel, A. (2014). A research paper on measuring effectiveness of online behavioural advertisements. International Journal of Scientific Research and Management (IJSRM), 2(12), 1825–1832.
Lammers, R. (2020). Feeling targeted in a digital era: A study about the influence on online behavioural targeting on consumer attitudes. University of Twente.
Li, W., & Huang, Z. (2016). The research of influence factors of online behavioural advertising avoidance. American Journal of Industrial and Business Management, 6, 947–957. https://doi.org/10.4236/ajibm.2016.69092
Moreno, A. M., & Casillas, J. C. (2008). Entrepreneurial orientation and growth of SMEs: a causal model (pp. 507–528). Baylor University.
Olayiwola, A. . (2007). Procedures in educational research. Hanjim Publications.
Ozcelik, A. B., & Varnali, K. (2019). Effectiveness of online behavioural targeting: a psychological perspective. Electronic Commerce Research and Applications, 33, 1–12. https://doi.org/10.1016/j.elerap.2018.11.006
Pickens, J. (2005). Attitudes and perceptions of individuals. In N. Borkowski (Ed.), Organizational Behavior in Health Care (pp. 43–76). Jones and Bartlett Publishers.
Ringle, C. M., Sarstedt, M., Mitchell, R., & Siegfried, P. G. (2018). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 1–27. https://doi.org/10.1080/09585192.2017.1416655
Schedwin, J. (2008). Behavioural targeting: issues involving the Microsoft-aquantive and google-doubleclick mergers, and the current and proposed solutions to those issues. Journal of Law and Policy for the Information Society, 4(3), 710–730.
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict.
Smit, E. G., Noort, G. Van, & Voorveld, H. A. M. (2014). Understanding online behavioural advertising: user knowledge, privacy concerns and online coping behaviour in Europe. Computers in Human Behavior, 32, 15–22. https://doi.org/10.1016/j.chb.2013.11.008
Soares, M. C., & Perin, M. G. (2019). Entrepreneurial orientation and firm performance: An updated meta-analysis. RAUSP Management Journal. https://doi.org/10.1108/RAUSP-01-2019-0014
Statista. (2018). Number of internet users worldwide: 2005-2018.
Varnali, K. (2019). Online behavioural advertising: An integrative review. Journal of Marketing Communications, 00(00), 1–22. https://doi.org/10.1080/13527266.2019.1630664
Wiese, M., Akareem, H. S., & Wiese, M. (2020). Determining perceptions, attitudes and behaviour towards social network site advertising in a three-country context social network site advertising in a three-country context. Journal of Marketing Management, 00(00), 1–36. https://doi.org/10.1080/0267257X.2020.1751242
Yan, J., Liu, N., Wang, G., Zhang, W., Jiang, Y., & Chen, Z. (2009). How much can behavioural targeting help online advertising? In Proceedings of the 18th International Conference on World Wide Web, WWW ’09, 261–270.
Published
2022-04-29
How to Cite
Oladele, S., Adigun, O., Johnson, L. S., Oladele, F., & Ajani, J. (2022). BEHAVIOURAL TARGETING, PERCEPTION OF INTERNET USERS AND CLICK-THROUGH INTENTIONS: IMPLICATIONS FOR DIGITAL ENTREPRENEURS IN NIGERIA. International Journal of Marketing Research Innovation, 7(1), 1-11. https://doi.org/10.46281/ijmri.v7i1.1702
Section
Research Paper/Theoretical Paper/Review Paper/Short Communication Paper
Copyright (c) 2022 Seun Oladele, Oluwatimileyin Adigun, Laosebikan S. Johnson, Femi Oladele, John Ajani
This work is licensed under a Creative Commons Attribution 4.0 International License.
