This study examines the factors influencing consumer intention to watch online video ads, by applying the theory of reasoned action. The attitude toward watching online video ads, the subjective norm, and prior frequency of watching online video ads positively influence the intention to watch online video ads. Further, beliefs held about entertainment and information outcomes from watching online video ads and subjective norm influence attitude toward watching these ads.
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References
1.
BealA. 2007. Can online video advertising really reach $4.3B by 2011? Marketing Pilgrim 2007; July 16. www.marketingpilgrim.com/2007/07/can-online-video-advertising-really-reach-43b-by-2011.html. 2007 Aug 2.
2.
eMarketer. 2008a. Video advertising growth factors. www.emarketer.com/Reports/All/Emarketer_2000537.aspx. 2008 Dec. 10.
3.
eMarketer. 2008b. Video advertising online: spending and pricing. www.emarketer.com/Reports/All/Emarketer_2000536.aspx. 2008 Dec. 10.
4.
SouthgateD, WestobyN, PageG. Creative determinants of viral video viewing. International Journal of Advertising, 2010; 29:349–368.
5.
AjzenI, FishbeinM. 1980. Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
6.
FishbeinM, AjzenI. 1975. Belief, attitude, intention and behavior: an introduction to theory and research. Reading, Massachusetts: Addison-Wesley.
7.
FitzmauriceJ. Incorporating consumers' motivations into the theory of reasoned action. Psychology & Marketing, 2005; 22:911–929.
8.
RamayahT, RouibahK, GopiMet al.A decomposed theory of reasoned action to explain intention to use Internet stock trading among Malaysian investors. Computers in Human Behavior, 2009; 25:1222–1230.
9.
OliverRL, BeardenWO. Crossover effects in the theory of reasoned action. Journal of Consumer Research, 1985; 12:324–340.
10.
BagozziRP, WongN, AbeSet al.Cultural and situational contingencies and the theory of reasoned action: application to fast food restaurant consumption. Journal of Consumer Psychology, 2000; 9:97–106.
11.
ChooH, ChungJE, PysarchikDT. Antecedents to new food product purchasing behavior among innovator groups in India. European Journal of Marketing, 2004; 38:608–625.
12.
BockGW, ZmudRW, KimYGet al.Behavioral intention formation in knowledge sharing: examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Quarterly, 2005; 29:87–111.
13.
RyanMJ. Behavioral intention formation: the interdependency of attitudinal and social influence variables. Journal of Consumer Research, 1982; 9:263–278.
14.
AlbarracínD, WyerRS. The cognitive impact of past behavior: influences on beliefs, attitudes, and future behavioral decisions. Journal of Personality and Social Psychology, 2000; 79:5–22.
15.
KidwellB, JewellRD. The influence of past behavior on behavioral intent: an information-processing explanation. Psychology & Marketing, 2008; 25:1151–1166.
16.
TaylorS, ToddP. Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intention. International Journal of Research in Marketing, 1995; 12:137–155.
17.
LinCA. 1999. Uses and gratifications. StoneG, SingletaryM, RichmondVP. Clarifying communication theories: a hands-on approach. Ames, Iowa: Iowa State University Press, 199–208.
18.
O'DonohoeS. Advertising uses and gratifications. European Journal of Marketing, 1994; 28:52–75.
19.
PollayRW, MittalB. Here's the beef: factors, determinants, and segments in consumer criticism of advertising. Journal of Marketing, 1993; 57:99–114.
20.
KorgaonkarPK, WolinLD. A multivariate analysis of web usage. Journal of Advertising Research, 1999; 39:53–68.
21.
PapacharissiZ, RubinAM. Predictors of Internet use. Journal of Broadcasting and Electronic Media, 2000; 44:175–196.
22.
KoH, ChoCH, RobertsMS. Internet uses and gratifications: a structural equation model of interactive advertising. Journal of Advertising, 2005; 34:57–70.
23.
FergusonDA, PerseEM. The world wide web as a functional alternative to television. Journal of Broadcasting and Electronic Media, 2000; 44:155–174.
24.
RodgersS, SheldonKM. An improved way to characterize Internet users. Journal of Advertising Research, 2002; 42:85–94.
25.
Pew Internet & American Life Project. 2009. The audience for online video-sharing sites shoots up. www.pewinternet.org/Reports/2009/13—The-Audience-for-Online-VideoSharing-Sites-Shoots-Up/2-Demographics.aspx?r=1. 2010 Jul. 2.
26.
AjzenI. 2002, 2006Constructing a TPB questionnaire: conceptual and methodological considerations. www.people.umass.edu/aizen/pdf/tpb.measurement.pdf. 2008 Apr. 6.
27.
KlineRB. 2005. Principles and practice of structural equation Modeling. NY: Guilford Press.
28.
HairJF, BlackWC, BabinBJet al.2006. Multivariate data analysis, 6th. Upper Saddle River, NJ: Prentice Hall.
29.
FornellC, LarckerDF. Structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing Research, 1981; 18:382–388.
