The evolution of social media as an interactive technology has gathered wide acknowledgement in our daily lives. With the increasing number of active users and ease of use, marketing practitioners have been constantly using Web 2.0 based social media applications to advertise their products and conduct various marketing activities. The fundamental purpose of the study is to discover the antecedents that lead to the acceptance of social media as an effective advertising vehicle. Thus, the current study is the first to employ the technology acceptance model (TAM) to cognize consumers’ behavioural intention in the social media advertising context. The responses were acquired from 348 respondents deploying a self-administered questionnaire. Structural equation modelling was employed using AMOS 22.0 to test the conceptual model fitness. The outcome of the study illustrates that all the predictors (perceived usefulness, perceived ease of use, privacy concerns and peer influence) are valid antecedents that influence consumers’ attitude towards social media ads and impact their purchase intention. The study, thus, offers a comprehensive framework and practical recommendations to marketing practitioners to design rewarding social media marketing campaigns.
AlalwanA. A. (2018). Investigating the impact of social media advertising features on customer purchase intention. International Journal of Information Management, 42, 65–77.
2.
AlhabashS., McAlisterA. R., QuillamE. T., RifonN. J., & RichardsJ. I. (2013). Between likes and shares: Effects of emotional appeal and virality on the persuasiveness of anticyberbullying messages on Facebook. Cyberpsychology, Behaviour and Social Networking, 16(3), 175–182.
3.
AndersonJ. C., & GerbingD. W. (1988). Structural equation modelling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
4.
AroraN., SinghG., & GrewalB. (2016). Impact of spirituality on consumer perception creation and preference of products wsrt FMCG and Patanjali Ayurved Ltd. in Punjab. Journal of Marketing Vistas, 6(2), 32.
5.
AroraN., PrasharS., ParsadC., & TataS. V. (2019a). Influence of celebrity factors, consumer attitude and involvement on shoppers’ purchase intention using hierarchical regression. Decision, 46(3), 179–195.
6.
AroraN., PrasharS., ParsadC., & VijayT. S. (2019b). Mediating role of consumer involvement between celebrity endorsement and consumer evaluation: Comparative study of high and low involvement product. Asian Academy of Management Journal, 24(2),113–142.
7.
AroraN., PrasharS., TataS. V., & ParsadC. (2021). Measuring personality congruency effects on consumer brand intentions in celebrity-endorsed brands. Journal of Consumer Marketing. 10.1108/JCM-02-2020-3634
8.
AsastaniH. L., KusumawardhanaV. H., & WarnarsH. L. H. S. (2018, September). Factors affecting the usage of mobile commerce using technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT). In 2018 Indonesian association for pattern recognition international conference (INAPR) (pp. 322–328). IEEE.
9.
AyaburiE. W., & TrekuD. N. (2020). Effect of penitence on social media trust and privacy concerns: The case of Facebook. International Journal of Information Management, 50(February), 171–181.
10.
BeardenW. O., NetemeyerR. G., & TeelJ. E. (1989). Measurement of consumer susceptibility to interpersonal influence. Journal of Consumer Research, 15(4), 473–481.
11.
BilgihanA., BarredaA., OkumusF., & NusairK. (2016). Consumer perception of knowledge-sharing in travel-related online social networks. Tourism Management, 52(February), 287–296.
12.
BleierA., & EisenbeissM. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390–409.
13.
BoatengH., & OkoeA. F. (2015). Consumers’ attitude towards social media advertising and their behavioural response. Journal of Research in Interactive Marketing, 9(4), 299–312.
14.
BrightL. F., & LoganK. (2018). Is my fear of missing out (fomo) causing fatigue? Advertising, social media fatigue, and the implications for consumers and brands. Internet Research, 28(5), 1213–1227.
15.
BuchananT., PaineC., JoinsonA. N., & ReipsU. D. (2007). Development of measures of online privacy concern and protection for use on the Internet. Journal of the American Society for Information Science and Technology, 58(2), 157–165.
16.
ChangJ. H., ZhuY. Q., WangS. H., & LiY. J. (2018). Would you change your mind? An empirical study of social impact theory on Facebook. Telematics and Informatics, 35(1), 282–292.
17.
DavisF. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology).
18.
DavisF. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
19.
DodooN. A., & WuL. (2019). Exploring the anteceding impact of personalised social media advertising on online impulse buying tendency. International Journal of Internet Marketing and Advertising, 13(1), 73–95.
20.
DuffettR. G. (2015). Facebook advertising’s influence on intention-to-purchase and purchase amongst millennials. Internet Research, 25(4), 498–526.
21.
EcklerP., KalyangoY., & PaaschE. (2017). Facebook use and negative body image among US college women. Women & Health, 57(2), 249–267.
22.
EnliG., & RosenbergL. T. (2018). Trust in the age of social media: Populist politicians seem more authentic. Social Media+ Society, 4(1). 10.1177/2056305118764430
23.
FernandesE., SemuelH., & AdiwijayaM. (2020). The influence of social media advertising on purchase intention through utilitarian and hedonic shopping motivation: A study at beauty care and anti-aging clinic service in Surabaya. Petra International Journal of Business Studies, 3(1), 23–36.
24.
FishbeinM., & AjzenI. (1977). Belief, attitude, intention, and behaviour: An introduction to theory and research. Philosophy and Rhetoric, 10(2), 130–132.
25.
GefenD. (2000). E-commerce: The role of familiarity and trust. Omega, 28(6), 725–737.
26.
GenadiY. D., & FurkanL. M. (2020). Effect of informativeness, entertainment, and irritating on toward social media advertising attitude in mataram city community. JMM UNRAM - Master of Management Journal, 9(2), 186–197. 10.29303/jmm.v9i2.538
27.
GibreelO., AlOtaibiD. A., & AltmannJ. (2018). Social commerce development in emerging markets. Electronic Commerce Research and Applications, 27(C), 152–162.
28.
HamoudaM. (2018). Understanding social media advertising effect on consumers’ responses: An empirical investigation of tourism advertising on Facebook. Journal of Enterprise Information Management, 31(3), 426–445.
29.
HermidaA., FletcherF., KorellD., & LoganD. (2012). Share, like, recommend: Decoding the social media news consumer. Journalism Studies, 13(5–6), 815–824.
30.
HessT. J., McNabA. L., & BasogluK. A. (2014). Reliability generalization of perceived ease of use, perceived usefulness, and behavioural intentions. MIS Quarterly, 38(1), 1–28.
31.
HossainS. A., BaoY., HasanN., & IslamM. F. (2020). Perception and prediction of intention to use online banking systems: An empirical study using extended TAM. International Journal of Research in Business and Social Science, 9(1), 112–116.
32.
HuangL. K. (2017). A cultural model of online banking adoption: Long-term orientation perspective. Journal of Organizational and End User Computing, 29(1), 1–22.
33.
JiangZ., ChanJ., TanB. C., & ChuaW. S. (2010). Effects of interactivity on website involvement and purchase intention. Journal of the Association for Information Systems, 11(1), 34.
34.
JungA. (2018). How do new media environments influence consumer responses to advertising? A meta-analytic approach to ad avoidance. (Doctoral dissertations, Louisiana State University). 4673.
35.
KimS., JeongS. H., & HwangY. (2013). Predictors of pro-environmental behaviours of American and Korean students: The application of the theory of reasoned action and protection motivation theory. Science Communication, 35(2), 168–188.
36.
LeeC. S., & MaL. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behaviour, 28(2), 331–339.
37.
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.
38.
LeeY., KozarK. A., & LarsenK. R. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12(1), 50.
39.
LinC. A., & KimT. (2016). Predicting user response to sponsored advertising on social media via the technology acceptance model. Computers in Human Behaviour, 64(November), 710–718.
40.
Luna-NevarezC., & TorresI. M. (2015). Consumer attitudes toward social network advertising. Journal of Current Issues & Research in Advertising, 36(1), 1–19.
41.
MaS., SunX., XuJ., WangH., LiW., & SuQ. (2017). Improving semantic relevance for sequence-to-sequence learning of Chinese social media text summarization. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 10.18653/v1/P17-2100
42.
MacKenzieS. B., & LutzR. J. (1989). An empirical examination of the structural predictors of attitude toward the ad in an advertising pretesting context. Journal of Marketing, 53(2), 48–65.
43.
MadhavanV., GeorgeS., & KidiyoorG. (2019). Perceived intrusiveness of rich media ads in online advertising: Evidences from young Indian travellers. Cogent Economics & Finance, 7(1). 10.1080/23322039.2019.1645631
44.
Maleki MinbashrazgahM., Bagheri GarbollaghH., & EynaliM. (2021). Social media advertising: Analysis of the Role of informativeness, social image and creativity in advertising on purchase intention (Case of study: Customers sport products company Majid). Communication Management in Sport Media, 8(2), 50–60.
45.
MarshP. (2014). 5 things to know about content, advertising and trust. Retrieved, 11March2015, from www.newscyclesolutions.com/5-things-to-know-about-content-advertising-and-trust/
46.
MatikitiR., MpinganjiraM., & Roberts-LombardM. (2018). Application of the technology acceptance model and the technology–organisation–environment model to examine social media marketing use in the South African tourism industry. South African Journal of Information Management, 20(1), 1–12.
47.
MensahI. K. (2020). Perceived usefulness and ease of use of mobile government services: The moderating impact of electronic word of month (eWOM). International Journal of Technology Diffusion, 11(1), 1–16.
48.
OkazakiS., Navarro-BailónM. Á., & Molina-CastilloF. J. (2012). Privacy concerns in quick response code mobile promotion: The role of social anxiety and situational involvement. International Journal of Electronic Commerce, 16(4), 91–120.
49.
PettyR. E. (2013). Two routes to persuasion: State of the art. International Perspectives on Psychological Science, 2(1), 229–247.
50.
PitafiA. H., KanwalS., & KhanA. N. (2020). Effects of perceived ease of use on SNSs-addiction through psychological dependence, habit: The moderating role of perceived usefulness. International Journal of Business Information Systems, 33(3), 383–407.
51.
RakthamW., ChaipoopirutanaS., & CombsH. (2017, March). Factors influencing consumer attitudes toward social media advertising. In International Conference on Humanities, Social Sciences and Education (pp. 32-36).
52.
RanaM., & AroraN. (2021). How does social media advertising persuade? An investigation of the moderation effects of corporate reputation, privacy concerns and intrusiveness. Journal of Global Marketing, 34(5), 1–20.
53.
RanaM., & AroraN. (2022). Predicting user response behaviour towards social media advertising and e-WoM antecedents. Review of Marketing Science. 10.1515/roms-2022-0006
54.
RauniarR., RawskiG., YangJ., & JohnsonB. (2014). Technology acceptance model (TAM) and social media usage: An empirical study on Facebook. Journal of Enterprise Information Management, 27(1), 6–30.
55.
TaharA., RiyadhH. A., SofyaniH., & PurnomoW. E. (2020). Perceived ease of use, perceived usefulness, perceived security and intention to use -filing: The role of technology readiness. The Journal of Asian Finance, Economics, and Business, 7(9), 537–547.
56.
TaylorS., & ToddP. A., 1995. Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.
57.
VenkateshV. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365.
58.
VenkateshV., ThongJ. Y., & XuX. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376.
59.
WangH., MengY., & WangW. (2013). The role of perceived interactivity in virtual communities: Building trust and increasing stickiness. Connection Science, 25(1), 55–73.
60.
WieseM., & AkareemH. S. (2020). Determining perceptions, attitudes and behaviour towards social network site advertising in a three-country context. Journal of Marketing Management, 36(5–6), 420–455.
61.
WuJ. H., & WangS. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719–729.
62.
YounisR. A. A., & HammadR. (2020). Employer image, corporate image and organizational attractiveness: The moderating role of social identity consciousness. Personnel Review, 50(1), 244–263.
63.
ZaroualiB., PonnetK., WalraveM., & PoelsK. (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 Behaviour, 69(C), 157–165.
64.
ZhangJ., & MaoE. (2016). From online motivations to ad clicks and to behavioural intentions: An empirical study of consumer response to social media advertising. Psychology & Marketing, 33(3), 155–164.
