The purpose of this research is to predict the influence of YouTube advertising on consumers purchase intention in India. Based on the Ducoffe’s web advertising model, this research developed a hypothetical model by combining hedonic motivation with entertainment, informativeness, credibility, incentives and irritation. A survey was conducted among 562 Gen ‘Z’ respondents in India and the data was analysed using structural equation modelling. The results indicate that informativeness, credibility, entertainment and hedonic motivation were reported as the predictors to consumers purchase intention. It was further observed that incentives and irritation were not the significant predictors to consumers purchase intention in the Indian context. The main implications of the study show that marketers and advertisers should focus on the hedonic motivation and incentives to enhance purchase intention.
AakerD. A., & BruzzoneD. E. (1981). Viewer perceptions of prime-time television advertising. Journal of Advertising Research, 21(5), 15–23.
2.
AjzenI. (1991). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211.
3.
AlalwanA. A. (2018). Investigating the impact of social media advertising features on customer purchase intention. International Journal of Information Management, 42, 65–77.
4.
AlalwanA. A., RanaN. P., DwivediY. K., & AlgharabatR. (2017). Social media in marketing: A review and analysis of the existing literature. Telematics and Informatics, 34(7), 1177–1190.
5.
Ana Gajić (2022). Advertising statistics. https://99firms.com/blog/advertising-statistics/#gref
6.
AndersonJ. C., & GerbingD. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
7.
AslamB., & KarjaluotoH. (2017). Digital advertising around paid spaces, E-advertising industry’s revenue engine: A review and research agenda. Telematics and Informatics, 34(8), 1650–1662.
8.
BaabdullahA. M. (2018). Consumer adoption of Mobile Social Network Games (M-SNGs) in Saudi Arabia: The role of social influence, hedonic motivation and trust. Technology in Society, 53, 91–102.
9.
BaronR. M., & KennyD. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.
BenoitI. D., & MillerE. G. (2019). When does creativity matter: The impact of consumption motive and claim set-size. Journal of Consumer Marketing, 36(4), 449–460.
12.
BoomsmaA. (1987). The robustness of maximum likelihood estimation in structural equation models. Cambridge University Press.
13.
BorahP., FowlerE., & RidoutT. N. (2018). Television vs. YouTube: Political advertising in the 2012 presidential election. Journal of Information Technology & Politics, 15(3), 230–244.
14.
BrackettL. K., & CarrB. N. (2001). Cyberspace advertising vs. other media: Consumer vs. mature student attitudes. Journal of Advertising Research, 41(5), 23–32.
ByrneB.M. (2010). Structural equation modeling using AMOS: Basic concepts, applications and programming(2nd ed.). Taylor & Francis Group.
17.
ChinW. W., & ToddP. A. (1995). On the use, usefulness, and ease of use of structural equation modelling in MIS research: A note of caution. MIS Quarterly, 19(2), 237–246.
18.
ChoC. H., & CheonH. J. (2004). Why do people avoid advertising on the internet?Journal of Advertising, 33(4), 89–97.
19.
CroesE., & BartelsJ. (2021). Young adults’ motivations for following social influencers and their relationship to identification and buying behavior. Computers in Human Behavior, 124, 1–10.
20.
DehghaniM., NiakiM. K., RamezaniI., & SaliR. (2016). Evaluating the influence of YouTube advertising for attraction of young customers. Computers in Human Behavior, 59, 165–172.
21.
DehghaniM., & TumerM. (2015). A research on effectiveness of Facebook advertising on enhancing purchase intention of consumers. Computers in Human Behavior, 49, 597–600.
22.
DeyD. K., & SrivastavaA. (2017). Impulse buying intentions of young consumers from a hedonic shopping perspective. Journal of Indian Business Research, 9(4), 266–282.
23.
DjafarovaE., & KramerK. (2020). Is YouTube advertising effective: Context of travel industry?Athens Journal of Tourism, 7(3), 117–132.
24.
DjafarovaE., & RushworthC. (2017). Exploring the credibility of online celebrities’ Instagram profiles in influencing the purchase decisions of young female users. Computers in Human Behavior, 68, 1–7.
25.
DucoffeR. H. (1995). How consumers assess the value of advertising. Journal of Current Issues & Research in Advertising, 17(1), 1–18.
26.
DucoffeR. H. (1996). Advertising value and advertising on the web. Journal of Advertising Research, 36(5), 21–32.
27.
FischerE., & ReuberA. R. (2011). Social interaction via new social media:(How) can interactions on Twitter affect effectual thinking and behavior?Journal of Business Venturing, 26(1), 1–18.
28.
FitrianiW. R., MulyonoA. B., HidayantoA. N., & MunajatQ. (2020). Reviewer’s communication style in YouTube product-review videos: Does it affect channel loyalty?. Heliyon, 6(9), 1–10.
29.
FornellC., & LarckerD. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
30.
HairJ. F., AndersonR. E., TathamR. L., & BlackW. C. (1998). Multivariate data analysis(5th ed.). Prentice Hall.
31.
HairJ. F., BlackW. C., BabinB. J., & AndersonR. E. (2018). Multivariate data analysis(8th ed.). Cengage Learning.
32.
HairJ. F., HultG. T. M., RingleC. M., SarstedtM., & ThieleK. O. (2017). Mirror, mirror on the wall: A comparative evaluation of composite-based structural equation modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632.
33.
HairJ. F., WilliamC. B., BarryJ. B., & RolphE. A. (2010). Multivariate data analysis. Prentice Hall.
34.
HashimN. H., Normalini, & SajaliN. (2018). The influence factors towards mobile advertising message content on consumer purchase intention. Global Business Review, 19(5), 1187–1206.
35.
HerrandoC., & Martín-De HoyosM. J. (2022). Influencer endorsement posts and their effects on advertising attitudes and purchase intentions. International Journal of Consumer Studies, 46(2), 2288–2299.
36.
HuL. T., & BentlerP. M. (1999). Cut-off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modelling: A Multidisciplinary Journal, 6(1), 1–55.
37.
HutaV., & WatermanA. S. (2014). Eudaimonia and its distinction from hedonia: Developing a classification and terminology for understanding conceptual and operational definitions. Journal of Happiness Studies, 15(6), 1425–1456.
38.
JaegerA. K., & WeberA. (2020). Can you believe it? The effects of benefit type versus construal level on advertisement credibility and purchase intention for organic food. Journal of Cleaner Production, 257, 1–12.
39.
JeonY. A., SonH., ChungA. D., & DrumwrightM. 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(1), 144–158.
40.
KaczmarekL. D. (2017). Eudaimonic motivation. Encyclopedia of personality and individual differences. Springer.
41.
KangH. J., ShinJ. H., & PontoK. (2020). How 3D virtual reality stores can shape consumer purchase decisions: The roles of informativeness and playfulness. Journal of Interactive Marketing, 49, 70–85.
42.
KhanM. L. (2017). Social media engagement: What motivates user participation and consumption on YouTube?Computers in Human Behavior, 66, 236–247.
43.
KimB. (2007). The antecedents of influence on the attitude toward mobile advertising. Advertising Research, 75(6), 51–75.
44.
KimY. B., YoonY., KimY., & LeeB. G. (2012). Strategy to maximise mobile advertising effect in smart environment: Focused on DuCoffe model and TAM. International Journal of Smart Home, 6(3), 9–16.
45.
KimY. J., & HanJ. (2014). Why smartphone advertising attracts customers: A model of Web advertising, flow, and personalisation. Computers in Human Behavior, 33, 256–269.
46.
KimY., & ParkH. (2017). Is there still a PR problem online? Exploring the effects of different sources and crisis response strategies in online crisis communication via social media. Corporate Reputation Review, 20(1), 76–104.
47.
KlineP. (1994). An easy guide to factor analysis. Routledge.
48.
LeeJ., & HongI. 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.
49.
LendvaiM. B., KovácsI., BalázsB. F., & BekeJ. (2022). Health and environment conscious consumer attitudes: Generation Z segment personas according to the LOHAS Model. Social Sciences, 11(7), 1–18.
50.
LeongL. Y., HewT. S., OoiK. B., & LinB. (2019). Do electronic word-of-mouth and elaboration likelihood model influence hotel booking?Journal of Computer Information Systems, 59(2), 146–160.
51.
LinH., FanW., & ChauP. Y. (2014). Determinants of users’ continuance of social networking sites: A self-regulation perspective. Information & Management, 51(5), 595–603.
52.
LoganK., BrightL. F., & GangadharbatlaH. (2012). Facebook versus television: Advertising value perceptions among females. Journal of Research in Interactive Marketing, 6(3), 164–179.
53.
LópezM., SiciliaM., & VerleghP. W. (2021). How to motivate opinion leaders to spread e-WoM on social media: Monetary vs non-monetary incentives. Journal of Research in Interactive Marketing, 16(1), 154–171.
54.
LouC., ZhouX., HuangX., QiuC., & YuanM. (2022). Fostering consumer engagement during an omnipresent victim crisis: Understanding the role of values in pandemic-themed advertising. International Journal of Advertising, 1–26.
55.
MacCallumR. C., & AustinJ. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51(1), 201–226.
56.
MackenzieS. R. (1989). An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. Journal of Marketing, 53(4), 48–65.
57.
MaloneS., McCabeS., & SmithA. P. (2014). The role of hedonism in ethical tourism. Annals of Tourism Research, 44, 241–254.
58.
MansoorIqbal (2020). Business of apps. https://www.businessofapps.com/data/youtube-statistics/#1
59.
MardiaK. V. (1970). Measures of multivariate skewness and kurtosis with applications measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530.
Martín-ConsuegraD., DíazE., GómezM., & MolinaA. (2019). Examining consumer luxury brand-related behavior intentions in a social media context: The moderating role of hedonic and utilitarian motivations. Physiology & Behavior, 200, 104–110.
62.
MartinsJ., CostaC., OliveiraT., GonçalvesR., & BrancoF. (2019). How smartphone advertising influences consumers’ purchase intention. Journal of Business Research, 94, 378–387.
63.
MaseehH. I., JebarajakirthyC., PentecostR., AshaduzzamanM., ArliD., & WeavenS. (2021). A meta-analytic review of mobile advertising research. Journal of Business Research, 136, 33–51.
64.
MkikS., KhouilidM., & AomariA. (2017). Green advertising and environmentally consumption: The level of awareness and Moroccan costumer’s perception. IOSR Journal of Business and Management, 19(8), 1–11.
65.
MukherjeeK., & BanerjeeN. (2017). Effect of social networking advertisements on shaping consumers’ attitude. Global Business Review, 18(5), 1291–1306.
66.
NunnallyJ. C., & BernsteinI. H. (1994). Psychometric theory(3rd ed.). McGraw-Hill.
67.
OkazakiS. (2004). How do Japanese consumers perceive wireless ads? A multivariate analysis. International Journal of Advertising, 23(4), 429–454.
68.
OliverM. B., & RaneyA. A. (2011). Entertainment as pleasurable and meaningful: Identifying hedonic and eudaimonic motivations for entertainment consumption. Journal of Communication, 61(5), 984–1004.
69.
PavlouP. A., & StewartD. W. (2000). Measuring the effects and effectiveness of interactive advertising: A research agenda. Journal of Interactive Advertising, 1(1), 61–77.
70.
RezvaniZ., JanssonJ., & BengtssonM. (2018). Consumer motivations for sustainable consumption: The interaction of gain, normative and hedonic motivations on electric vehicle adoption. Business Strategy and the Environment, 27(8), 1272–1283.
71.
RodgersS., & ThorsonE. (2000). The interactive advertising model: How users perceive and process online ads. Journal of Interactive Advertising, 1(1), 41–60.
72.
RotzollK. B., & HaefnerJ. E. (1990). Advertising in contemporary society(2nd ed.). South-Western Publishing.
73.
SchlingerM. J. (1979). A profile of responses to commercials. Journal of Advertising Research, 19(2), 37–46.
74.
SchwartzS. H. (1994). Are there universal aspects in the structure and contents of human values?Journal of Social Issues, 50(4), 19–45.
75.
ShanmugavelN., & SolayanS. (2021). Impact of hedonic motivation and perceived moral obligation on green products purchase intention among centennials. Academy of Marketing Studies Journal, 25(3), 1–20.
76.
ShareefM. A., MukerjiB., AlryalatM. A. A., WrightA., & DwivediY. K. (2018). Advertisements on Facebook: Identifying the persuasive elements in the development of positive attitudes in consumers. Journal of Retailing and Consumer Services, 43, 258–268.
77.
SinghR. P., & BanerjeeN. (2018). Exploring the influence of celebrity credibility on brand attitude, advertisement attitude and purchase intention. Global Business Review, 19(6), 1622–1639.
78.
SundarS. S., & MaratheS. S. (2010). Personalisation versus customisation: The importance of agency, privacy, and power usage. Human Communication Research, 36(3), 298–322.
79.
TabachnickB. G., & FidellL. S. (2001). Using multivariate statistics. Allyn and Bacon.
80.
TaylorD. G., LewinJ. E., & StruttonD. (2011). Friends, fans, and followers: Do ads work on social networks? How gender and age shape receptivity. Journal of Advertising Research, 51(1), 258–275.
81.
TrivediJ. P. (2017). Do long format advertisements sell? Evidence from Indian consumers. Global Business Review, 18(3_suppl), S38–S51.
82.
TrivediJ. P., DeshmukhS., & KishoreA. (2020). Wooing the consumer in a six-second commercial! Measuring the efficacy of bumper advertisements on YouTube. International Journal of Electronic Marketing and Retailing, 11(3), 307–322.
83.
Van-Tien DaoW., Nhat Hanh LeA., Ming-Sung ChengJ., & Chao ChenD. (2014). Social media advertising value: The case of transitional economies in Southeast Asia. International Journal of Advertising, 33(2), 271–294.
84.
VarnaliK., YilmazC., & TokerA. (2012). Predictors of attitudinal and behavioral outcomes in mobile advertising: A field experiment. Electronic Commerce Research and Applications, 11(6), 570–581.
85.
VenkateshV., ThongJ. Y., & XuX. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
86.
WongC. H., TanG. W. H., TanB. I., & OoiK. B. (2015). Mobile advertising: The changing landscape of the advertising industry. Telematics and Informatics, 32(4), 720–734.
87.
WuS. (2006). The impact of feeling, judgment and attitude on purchase intention as online advertising performance measure. Journal of International Marketing & Marketing Research, 31(2), 89–108.
88.
XiaoM., WangR., & Chan-OlmstedS. (2018). Factors affecting YouTube influencer marketing credibility: A heuristic-systematic model. Journal of Media Business Studies, 15(3), 188–213.
89.
YangB., KimY., & YooC. (2013). The integrated mobile advertising model: The effects of technology- and emotion-based evaluations. Journal of Business Research, 66(9), 1345–1352.
90.
YangB. H., & KimY. C. (2008). Study on mutual causality model for mobile advertising effect: Convergence of advertising communication and mobile technology. Journal of Advertising, 19(3), 57–171.
91.
YangK. C., HuangC. H., YangC., & YangS. Y. (2017). Consumer attitudes toward online video advertisement: YouTube as a platform. Kybernetes, 46(5), 840–853.
