Effect of in-stream ads on viewer’s attitude to purchase—The moderating role of viewer’s control
Vol 8, Issue 8, 2024
VIEWS - 124 (Abstract) 104 (PDF)
Abstract
Research in the field of online advertising has focused on the effect of in-stream ads on viewers’ attitudes and intentions to purchase. However, little is known regarding the crucial role of viewer’s control in terms of the ‘skip ad option’ towards the attitude to purchase. This research aims to investigate the effect of in-stream ads on viewers’ attitudes to purchasing with the moderating role of viewer control. Primary data was collected from respondents of Vehari district of Pakistan through a questionnaire based on 5 points Likert scale. 370 questionnaires were incorporated after excluding the questionnaires having missing values. Structural equation modelling was used through SmartPLS-3 software in testing the hypotheses. The findings reveal that, in-stream (emotional, informational, and entertaining) ads have positive impact on viewers’ attitudes, and viewers’ control moderates the relationship between in-stream ads and viewers’ attitudes towards the ads. Further, viewers’ attitude toward the ads has a significant positive impact on viewers’ intention to purchase. To the best of our knowledge this is one of the first studies that examines the effect of in-stream ads on viewers’ attitudes to purchasing with the moderating role of viewer control in the context of a developing country, like Pakistan.
Keywords
Full Text:
PDFReferences
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918. https://doi.org/10.1037/0033-2909.84.5.888
Alhabash, S., McAlister, A. R., Quilliam, E. T., et al. (2012). Between “Likes” and “Shares”: Effects of Emotional Appeal and Virality of Social Marketing Messages on Facebook. Cyberpsychology, Behavior, and Social Networking, 16(3), 175–182. https://doi.org/10.1089/cyber.2012.0265
AlNuaimi, B. K., Khan, M., & Ajmal, M. M. (2021). The role of big data analytics capabilities in greening e-procurement: A higher order PLS-SEM analysis. Technological Forecasting and Social Change, 169, 120808. https://doi.org/10.1016/j.techfore.2021.120808
Altuna, O. K., & Konuk, F. A. (2009). Understanding consumer attitudes toward mobile advertising and its impact on consumers behavioral intentions: a crossmarket comparison of united states and Turkish consumers. International Journal of Mobile Marketing, 4(2).
Anderson, S. P., & Coate, S. (2005). Market provision of broadcasting: A welfare analysis. The review of Economic studies, 72(4), 947–972. https://doi.org/10.1111/0034-6527.00357
Aslam, W., Batool, M., & Haq, Z. U. (2016). Attitudes and behaviors of the mobile phones users towards SMS advertising: A study in an emerging economy. Journal of Management Sciences, 3(1), 63–80. https://doi.org/10.20547/jms.2014.1603105
Banerjee, S., & Chua, A. Y. (2019). Identifying the antecedents of posts’ popularity on Facebook Fan Pages. Journal of Brand Management, 26(6), 621–633. https://doi.org/10.1057/s41262-019-00157-7
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to casual modeling: personal computer use as an Illustration. Technal. Stud., 2(2).
Batra, R. (1986). Affective advertising: Role, processes, and measurement. The Role of Affect in Consumer Behavior, 53–85.
Belanche, D., Flavián, C., & Pérez-Rueda, A. (2017). Understanding interactive online advertising: Congruence and product involvement in highly and lowly arousing, skippable video ads. Journal of Interactive Marketing, 37, 75–88. https://doi.org/10.1016/j.intmar.2016.06.004
Cho, C. H. (2004). Why do people avoid advertising on the internet? Journal of Advertising, 33(4), 89–97. https://doi.org/10.1080/00913367.2004.10639175
Chungviwatanant, T., Prasongsukarn, K., & Chungviwatanant, S. (2016). A study of factors that affect consumer’s attitude toward a “skippable in-stream ad” on YouTube. AU-GSB e-Journal, 9(1), 83–83.
Dash, G., & Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173, 121092. https://doi.org/10.1016/j.techfore.2021.121092
Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. Journal of Personality and Social Psychology, 44(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113
Ducoffe, R. H. (1996). Advertising value and advertising on the web. Journal of Advertising Research, 36(5), 21.
Dukes, A., Liu, Q., & Shuai, J. (2018). Interactive advertising: The case of skippable ads. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3169629
Duroy, D., Sabbagh, O., Baudel, A., & Lejoyeux, M. (2018). Compulsive buying in Paris psychology students: Assessment of DSM-5 personality trait domains. Psychiatry research, 267, 182–186. https://doi.org/10.1016/j.psychres.2018.06.015
Edell, J. A., & Burke, M. C. (1987). The power of feelings in understanding advertising effects. Journal of consumer research, 14(3), 421–433. https://doi.org/10.1086/209124
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
Escalas, J. E., & Stern, B. B. (2003). Sympathy and empathy: Emotional responses to advertising dramas. Journal of consumer research, 29(4), 566–578. https://doi.org/10.1086/346251
Fishbein, M. (1979). A theory of reasoned action: Some applications and implications. Nebraska Symposium on Motivation, 27, 65–116.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382. https://doi.org/10.2307/3150980
Fung, R., & Lee, M. (1999). EC-trust (trust in electronic commerce): exploring the antecedent factors. AMCIS 1999 Proceedings, 179.
Gerbasi, M. E., & Prentice, D. A. (2013). The self-and other-interest inventory. Journal of Personality and Social Psychology, 105(3), 495–514. https://doi.org/10.1037/a0033483
Golan, G. J., & Zaidner, L. (2008). Creative strategies in viral advertising: An application of Taylor’s six-segment message strategy wheel. Journal of computer-mediated communication, 13(4), 959–972. https://doi.org/10.1111/j.1083-6101.2008.00426.x
Goodrich, K., Schiller, S. Z., & Galletta, D. (2015). Consumer reactions to intrusiveness of online-video advertisements: do length, informativeness, and humor help (or hinder) marketing outcomes? Journal of advertising research, 55(1), 37–50. https://doi.org/10.2501/jar-55-1-037-050
Grant, P., Botha, E., & Kietzmann, J. (2015). Branded flash mobs: Moving toward a deeper understanding of consumers’ responses to video advertising. Journal of Interactive Advertising, 15(1), 28–42. https://doi.org/10.1080/15252019.2015.1013229
Haghirian, P., & Dickinger, A. (2005). Identifying success factors of mobile marketing. ACR Asia-Pacific Advances.
Haghirian, P., & Madlberger, M. (2005). Consumer attitude toward advertising via mobile devices-An empirical investigation among Austrian users. ECIS 2005 Proceedings, 44.
Haghirian, P., Madlberger, M., & Tanuskova, A. (2005). Increasing advertising value of mobile marketing-an empirical study of antecedents. In: Proceedings of the 38th annual Hawaii international conference on system sciences.
Hair, J., Anderson, R., Babin, B., & Black, W. (2010). Multivariate data analysis: A global perspective: Pearson Upper Saddle River. Pearson.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139–152. https://doi.org/10.2753/mtp1069-6679190202
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
Hegner, S. M., Kusse, D. C., & Pruyn, A. T. (2016). Watch it! The influence of forced pre-roll video ads on consumer perceptions. In: Advances in Advertising Research. Springer. pp. 63–73.
Hofacker, C. F., & Belanche, D. (2016). Eight social media challenges for marketing managers. Spanish Journal of Marketing-ESIC, 20(2), 73–80. https://doi.org/10.1016/j.sjme.2016.07.003
Holbrook, M. B., & O’Shaughnessy, J. (1984). The role of emotion in advertising. Psychology & Marketing, 1(2), 45–64. https://doi.org/10.1002/mar.4220010206
Hsu, C., Chang, K., & Chen, M. (2012). Flow Experience and Internet Shopping Behavior: Investigating the Moderating Effect of Consumer Characteristics. Systems Research and Behavioral Science, 29(3), 317–332. https://doi.org/10.1002/sres.1101
Hui, M. K., & Toffoli, R. (2002). Perceived control and consumer attribution for the service encounter. Journal of Applied Social Psychology, 32(9), 1825–1844. https://doi.org/10.1111/j.1559-1816.2002.tb00261.x
Hwang, J., Yoon, Y. S., & Park, N. H. (2011). Structural effects of cognitive and affective reponses to web advertisements, website and brand attitudes, and purchase intentions: The case of casual-dining restaurants. International Journal of Hospitality Management, 30(4), 897–907. https://doi.org/10.1016/j.ijhm.2011.01.011
Hwang, Y., & Jeong, S. H. (2019). Editorial content in native advertising: How do brand placement and content quality affect native-advertising effectiveness? Journal of advertising research, 59(2), 208–218. https://doi.org/10.2501/jar-2018-019
Jain, G., Rakesh, S., & Chaturvedi, K. R. (2018). Online video advertisements’ effect on purchase intention: an exploratory study on youth. International Journal of E-Business Research (IJEBR), 14(2), 87–101. https://doi.org/10.4018/ijebr.2018040106
Jeon, Y. A., Son, H., Chung, A. D., & Drumwright, M. E. (2019). Temporal certainty and skippable in-stream commercials: Effects of ad length, timer, and skip-ad button on irritation and skipping behavior. Journal of Interactive Marketing, 47, 144–158. https://doi.org/10.1016/j.intmar.2019.02.005
Jewell, R. D., & Kidwell, B. (2005). The moderating effect of perceived control on motivation to engage in deliberative processing. Psychology & Marketing, 22(9), 751–769. https://doi.org/10.1002/mar.20083
Joa, C. Y., Kim, K., & Ha, L. (2018). What makes people watch online in-stream video advertisements? Journal of Interactive Advertising, 18(1), 1–14. https://doi.org/10.1080/15252019.2018.1437853
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, 303–309. https://doi.org/10.1016/j.chb.2017.01.008
Kaasinen, E. (2003). User needs for location-aware mobile services. Personal and Ubiquitous Computing, 7(1), 70–79. https://doi.org/10.1007/s00779-002-0214-7
Kalakota, R., Robinson, M., & Kalakota, D. R. (2002). M-business: The race to mobility. McGraw-Hill New York.
Kamran, Q., & Siddiqui, D. A. (2019). The Impact of Emotional Advertising on Consumer Buying Behavior for Home Appliance Products in Pakistan. Business and Management Horizons, 7(1), 23–48. https://doi.org/10.5296/bmh.v7i1.14410
Kononova, A., & Yuan, S. (2015). Double-dipping effect? How combining YouTube environmental PSAs with thematically congruent advertisements in different formats affects memory and attitudes. Journal of Interactive Advertising, 15(1), 2–15. https://doi.org/10.1080/15252019.2015.1009524
Krejcie, R., & Morgan, S. (1970). Sample size determination. Business Research Methods, 4(5), 34–36.
Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311–328. https://doi.org/10.1037/0022-3514.32.2.311
Laskey, H. A., Day, E., & Crask, M. R. (1989). Typology of main message strategies for television commercials. Journal of Advertising, 18(1), 36–41. https://doi.org/10.1080/00913367.1989.10673141
Lee, E. B., Lee, S. G., & Yang, C. G. (2017). The influences of advertisement attitude and brand attitude on purchase intention of smartphone advertising. Industrial Management & Data Systems, 117(6), 1011–1036. https://doi.org/10.1108/imds-06-2016-0229
Lee, J., & Hong, I. B. (2016). Predicting positive user responses to social media advertising: The roles of emotional appeal, informativeness, and creativity. International Journal of Information Management, 36(3), 360–373. https://doi.org/10.1016/j.ijinfomgt.2016.01.001
Li, Y., & Peng, Y. (2021). What Drives Gift-giving Intention in Live Streaming? The Perspectives of Emotional Attachment and Flow Experience. International Journal of Human-Computer Interaction, 37(14), 1317–1329. https://doi.org/10.1080/10447318.2021.1885224
Lin, H. C. S., Lee, N. C. A., & Lu, Y. C. (2021). The Mitigators of Ad Irritation and Avoidance of YouTube Skippable In-Stream Ads: An Empirical Study in Taiwan. Information, 12(9), 373. https://doi.org/10.3390/info12090373
Liu-Thompkins, Y. (2019). A decade of online advertising research: What we learned and what we need to know. Journal of Advertising, 48(1), 1–13. https://doi.org/10.1080/00913367.2018.1556138
Liu, S. S., & Stout, P. A. (1987). Effects of message modality and appeal on advertising acceptance. Psychology & Marketing, 4(3), 167–187. https://doi.org/10.1002/mar.4220040303
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/10.1177/002224298905300204
Ming, J., Jianqiu, Z., Bilal, M., et al. (2021). How social presence influences impulse buying behavior in live streaming commerce? The role of S-O-R theory. International Journal of Web Information Systems, 17(4), 300–320. https://doi.org/10.1108/ijwis-02-2021-0012
Mitchell, A. A. (1986). Some issues surrounding research on the effects of feeling advertisements. Advances in Consumer Research, 13, 623–628. https://doi.org/10.1086/209044
Mohammed, A. B., & Alkubise, M. (2012). How do online advertisements affects consumer purchasing intention: Empirical evidence from a developing country. European journal of business and management, 4(7), 208–218.
Moller, A. C., Deci, E. L., & Ryan, R. M. (2006). Choice and ego-depletion: The moderating role of autonomy. Personality and Social Psychology Bulletin, 32(8), 1024–1036. https://doi.org/10.1177/0146167206288008
Mueller, R. O., & Hancock, G. R. (2018). Structural equation modeling. In: The reviewer’s guide to quantitative methods in the social sciences. Routledge. pp. 445–456.
Nauman Abbasi, M., Ramzan Sheikh, M., Saeed, R., & Imdadullah, M. (2014). Impact of Emotional Appeals on Youth Purchasing Behavior: Evidence from Pakistan. Pakistan Journal of Social Sciences (PJSS), 34(2).
Nwagwu, W. E., & Famiyesin, B. (2016). Acceptance of mobile advertising by consumers in public service institutions in Lagos, Nigeria. The Electronic Library, 34(2), 265–288. https://doi.org/10.1108/el-09-2014-0169
Oh, L. B., & Xu, H. (2003). Effects of multimedia on mobile consumer behavior: An empirical study of location-aware advertising. ICIS 2003 Proceedings, 56.
Okazaki, S., Molina, F. J., & Hirose, M. (2012). Mobile advertising avoidance: exploring the role of ubiquity. Electronic Markets, 22(3), 169–183. https://doi.org/10.1007/s12525-012-0087-1
Pashkevich, M., Dorai-Raj, S., Kellar, M., & Zigmond, D. (2012). Empowering online advertisements by empowering viewers with the right to choose: the relative effectiveness of skippable video advertisements on YouTube. Journal of advertising research, 52(4), 451–457. https://doi.org/10.2501/jar-52-4-451-457
Pelchen, L. (2024). Internet Usage Statistics in 2024. Available online: https://www.forbes.com/home-improvement/internet/internet-statistics/ (accessed on 7 March 2024).
Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In: Communication and persuasion. Springer. pp. 1–24.
Pollay, R. W., & Mittal, B. (1993). Here’s the beef: factors, determinants, and segments in consumer criticism of advertising. Journal of marketing, 57(3), 99–114. https://doi.org/10.1177/002224299305700307
Prestwich, A., Conner, M. T., Lawton, R. J., et al. (2012). Randomized controlled trial of collaborative implementation intentions targeting working adults’ physical activity. Health Psychology, 31(4), 486–495. https://doi.org/10.1037/a0027672
Puto, C. P., & Wells, W. D. (1984). Informational and transformational advertising: The differential effects of time. ACR North American Advances.
Puwandi, P. H., De, G. T., & Brasali, N. (2020). The factors affecting consumer response towards online video advertisement: YouTube as a platform. International Journal of Multicultural and Multireligious Understanding, 7(2), 486–495. https://doi.org/10.1037/a0027672
Ramadhani, S., Suroso, A. I., & Ratono, J. (2020). Consumer attitude, behavioral intention, and watching behavior of online video advertising on YouTube. Jurnal Aplikasi Manajemen, 18(3), 493–503. https://doi.org/10.21776/ub.jam.2020.018.03.09
Raney, A. A., Arpan, L. M., Pashupati, K., & Brill, D. A. (2003). At the movies, on the web: An investigation of the effects of entertaining and interactive web content on site and brand evaluations. Journal of Interactive Marketing, 17(4), 38–53. https://doi.org/10.1002/dir.10064
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
Sandvig, J. C., Bajwa, D., & Ross, S. C. (2011). Usage and perceptions of internet ad blockers: An exploratory study. Issues in Information Systems, 12(1), 59–69.
Sarstedt, M., Hair, J. F., Ringle, C. M., et al. (2016). Estimation issues with PLS and CBSEM: Where the bias lies! Journal of Business research, 69(10), 3998–4010. https://doi.org/10.1016/j.jbusres.2016.06.007
Shavitt, S., Lowrey, P., & Haefner, J. (1998). Public attitudes toward advertising: More favorable than you might think. Journal of advertising research, 38(4), 7–22.
Statista. (2023). Number of digital video viewers worldwide from 2019 to 2023. Available online: https://www.statista.com/statistics/1061017/digital-video-viewers-number-worldwide/ (accessed on 7 March 2024).
Statista. (2024a). Number of digital video viewers in the Asia Pacific region from 2019 to 2023. Available online: https://www.statista.com/statistics/658228/digital-video-viewers-in-apac/ (accessed on 7 March 2024).
Statista. (2024b). Video Advertising, worldwide. Available online: https://www.statista.com/outlook/dmo/digital-advertising/video-advertising/worldwide (accessed on 7 March 2024).
Styśko-Kunkowska, M. A., & Borecka, D. (2010). Extraversion and evaluation of humorous advertisements. Psychological reports, 106(1), 44–48. https://doi.org/10.2466/pr0.106.1.44-48
Thananuraksakul, S. (2007). Factors influencing online shopping behavior intention: A study of Thai consumers. AU Journal of Management, 5(1), 41–46.
Tsang, M. M., Ho, S. C., & Liang, T. P. (2004). Consumer attitudes toward mobile advertising: An empirical study. International journal of electronic commerce, 8(3), 65–78. https://doi.org/10.1080/10864415.2004.11044301
Ul Haq, Z. (2012). Attitude toward SMS advertising: A survey with reference to Indian consumers. Journal of Internet Commerce, 11(4), 271–290. https://doi.org/10.1080/15332861.2012.729463
Ünal, S., Ercis, A., & Keser, E. (2011). Attitudes towards mobile advertising—A research to determine the differences between the attitudes of youth and adults. Procedia-Social and behavioral sciences, 24, 361–377. https://doi.org/10.1016/j.sbspro.2011.09.067
Wang, Y., & Sun, S. (2010). Examining the role of beliefs and attitudes in online advertising: A comparison between the USA and Romania. International Marketing Review, 27(1), 87–107. https://doi.org/10.1108/02651331011020410
Wang, Y., Sun, S., Lei, W., & Toncar, M. (2009). Examining beliefs and attitudes toward online advertising among Chinese consumers. Direct Marketing: An International Journal, 3(1), 52–66. https://doi.org/10.1108/17505930910945732
Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interactions. Computers in human behavior, 9(4), 411–426.
Wells, W. D. (1980). How Advertising Works, Needham. In: Harper and Steers Advertising. Inc., Chicago.
Wu, P. C., & Wang, Y. C. (2011). The influences of electronic word‐of‐mouth message appeal and message source credibility on brand attitude. Asia Pacific Journal of Marketing and Logistics, 23(4), 448–472. https://doi.org/10.1108/13555851111165020
Xie, T., Donthu, N., Lohtia, R., & Osmonbekov, T. (2004). Emotional appeal and incentive offering in banner advertisements. Journal of Interactive Advertising, 4(2), 30–37. https://doi.org/10.1080/15252019.2004.10722085
Xu, H., Oh, L. B., & Teo, H. H. (2009). Perceived effectiveness of text vs. multimedia location-based advertising messaging. International Journal of Mobile Communications, 7(2), 154–177. https://doi.org/10.1504/ijmc.2009.022440
Yadati, K., Katti, H., & Kankanhalli, M. (2013). CAVVA: Computational affective video-in-video advertising. IEEE Transactions on Multimedia, 16(1), 15–23. https://doi.org/10.1109/tmm.2013.2282128
Yang, K. C., Huang, C. H., Yang, C., & Yang, S. Y. (2017). Consumer attitudes toward online video advertisement: YouTube as a platform. Kybernetes, 46(5), 840–853. https://doi.org/10.1108/k-03-2016-0038
Ying, L., Korneliussen, T., & Grønhaug, K. (2009). The effect of ad value, ad placement and ad execution on the perceived intrusiveness of web advertisements. International Journal of Advertising, 28(4), 623–638. https://doi.org/10.2501/s0265048709200795
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
Zhang, H., Cao, X., Ho, J. K., & Chow, T. W. (2016). Object-level video advertising: an optimization framework. IEEE Transactions on Industrial Informatics, 13(2), 520–531. https://doi.org/10.1109/tii.2016.2605629
Zheng, S., Chen, J., Liao, J., et al. (2023). What motivates users’ viewing and purchasing behavior motivations in live streaming: A stream-streamer-viewer perspective. Journal of Retailing and Consumer Services, 72, 103240. https://doi.org/10.1016/j.jretconser.2022.103240
DOI: https://doi.org/10.24294/jipd.v8i8.5401
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Orangzab, Muhammad Ismail, Minhas Akbar, Vaclav Zubr, Syed Muntazir Mehdi, Asokan Vasudevan, Huimin Fan
License URL: https://creativecommons.org/licenses/by/4.0/
This site is licensed under a Creative Commons Attribution 4.0 International License.