This research demonstrates the positive effects of moment-to-moment entertainment and the negative effects of moment-to-moment information value on consumers' likelihood to continue watching during a television commercial. A notable finding is that both the entertainment and the information value have a strong multiplicative effect on the probability to stop viewing.
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References
1.
AakerDavid A., and NorrisDonald (1982), “Characteristics of TV Commercials Perceived as Informative,”Journal of Advertising Research, 22(2), 61–70.
2.
AakerDavid A., StaymanDouglas M., and HagertyMichael R. (1986), “Warmth in Advertising: Measurement, Impact, and Sequence Effects,”Journal of Consumer Research, 12(March), 365–81.
3.
AlwittLinda F., BenetSuzanne B., and PittsRobert E. (1993), “Temporal Aspects of TV Commercials Influence Viewers' Online Evaluations,”Journal of Advertising, 33(3), 9–21.
4.
Aptech (1992), Gauss Applications Manual: Maximum Likelihood.Maple Valley, WA: Systems Inc.
5.
BarwiseT.P., and EhrenbergAndrew S.C. (1988), Television and Its Audience.London: Sage Publications.
6.
BatraRajeev, MyersJohn G., and AakerDavid A. (1996), Advertising Management, 5th ed.Upper Saddle River, NJ: Prentice Hall.
7.
BaumgartnerHans, SujanMita, and PadgettDan (1997), “Patterns of Affective Reactions to Advertisements: The Integration of MTM Responses into Overall Judgments,”Journal of Marketing Research, 34(May), 219–32.
8.
BerlyneDaniel E. (1974), Studies in the New Experimental Aesthetics.New York: Appleton-Century-Crofts.
9.
BielAlexander L. (1998), “Likeability: Why Advertising That Is Well Liked Sells Well,” in How Advertising Works: The Role of Research, JonesJohn Philip, ed. Thousand Oaks, CA: Sage Publications, 111–20.
10.
BlessHerbert (2000), “The Interplay of Affect and Cognition: The Mediating Role of General Knowledge Structures,” in Feeling and Thinking: The Role of Affect in Social Thinking, JosephP. Forgas, ed. New York: Cambridge University Press, 201–222.
11.
BrownstoneDavid, and TrainKenneth (1999), “Forecasting New Product Penetration with Flexible Substitution Patterns,”Journal of Econometrics, 89(1), 109–129.
12.
ChaikenShelly, and EaglyAlice H. (1983), “Communication Modality as a Determinant of Persuasion: The Role of Communicator Salience,”Journal of Personality and Social Psychology, 45(August), 241–56.
13.
ClaeysChristel, SwinnenAn, and AbeelePiet Vanden (1995), “Consumers' Mean-End Chains for ‘Think’ and ‘Feel’ Products,”International Journal of Research in Marketing, 12(3), 193–208.
14.
DanaherPeter J. (1995), “What Happens to Television Ratings During Television Commercials?”Journal of Advertising Research, 35(1), 37–47.
15.
DanaherPeter J., and LawrieJennifer M. (1998), “Behavioral Measures of Television Audience Appreciation,”Journal of Advertising Research, 38(1), 54–65.
16.
EfronBradley (1988), “Logistic Regression, Survival Analysis, and the Kaplan Meier Curve,”Journal of the American Statistical Association, 83(June), 414–25.
17.
FanJianqing, and GijbelsIrène (1996), Local Polynomial Modeling and Its Applications.London: Chapman and Hall.
18.
FiedlerKlaus (2000), “Toward an Integrative Account of Affect and Cognition Phenomena Using the BIAS Computer Algorithm,” in Feeling and Thinking: The Role of Affect and Social Cognition, JosephP. Forgas, ed. New York: Cambridge University Press, 223–52.
19.
ForgasJoseph P. (2000), “Affect and Information Processing Strategies: An Interactive Relationship,” in Feeling and Thinking: The Role of Affect and Social Cognition, JosephP. Forgas, ed. New York: Cambridge University Press, 253–80.
20.
ForgasJoseph P. (2001), “The Affect Infusion Model (AIM): An Integrative Theory of Mood Effects on Cognition and Judgement,” in Theories of Mood and Cognition: A User's Guidebook, LeonardL. Martin, and CloreGerald L., eds. Mahwah, NJ: Lawrence Erlbaum Associates, 99–134.
21.
FrederickShane, and LoewensteinGeorge (1999), “Hedonic Adaptation,” in Well-Being: The Foundations of Hedonic Psychology, KahnemanDaniel, DienerEd, and SchwarzNorbert, eds. New York: Russell Sage Foundation, 302–319.
22.
FredricksonBarbara L., and KahnemanDaniel (1993), “Duration Neglect in Retrospective Evaluations of Affective Episodes,”Journal of Personality and Social Psychology, 65(July), 45–55.
HärdleWolfgang (1990), Applied Nonparametric Regression.Boston: Cambridge University Press.
25.
HelsonHarry (1964), Adaptation-Level Theory: An Experimental and Systematic Approach of Behavior.New York: Harper & Row.
26.
HolbrookMorris B. (1978), “Beyond Attitude Structure Toward the Informational Determinants of Attitude,”Journal of Marketing Research, 15(November), 545–56.
27.
HolbrookMorris B., and LehmannDonald R. (1980), “Form Versus Content in Predicting Starch Scores,”Journal of Advertising Research, 20(4), 53–64.
28.
HseeChristopher K., and AbelsonRobert P. (1991), “Velocity Relation: Satisfaction as a Function of the First Derivative of Outcome over Time,”Journal of Personality and Social Psychology, 60(March), 341–47.
29.
HughesG. David (1990), “Diagnosing Communications Problems with Continuous Measures of Subjects' Responses: Applications, Potential Applications, Limitations, and Future Research,” in Current Issues and Research in Advertising, Vol. 13, JamesH. Leigh, and MartinClaude R.Jr., eds. Ann Arbor: Division of Research, Graduate School of Business Administration, University of Michigan, 175–95.
30.
IsenAlice M. (2000), “Positive Affect and Decision Making,” in Handbook of Emotions, 2d edLewisMichael, and Haviland-JonesJeannette M., eds. New York: The Guilford Press, 417–35.
31.
JacobyJacob (1984), “Perspectives on Information Overload,”Journal of Consumer Research, 10(March), 432–35.
32.
JudgeGeorge G., Carter HillR., GriffithWilliam E., LütkepohlHelmut, and LeeTsoung-Chao (1988), Introduction to the Theory and Practice of Econometrics, 2d ed.New York: John Wiley & Sons.
33.
KahnemanDaniel (1999), “Objective Happiness,” in Well-Being: The Foundations of Hedonic Psychology, KahnemanDaniel, DienerEd, and SchwarzNorbert, eds. New York: Russell Sage Foundation, 3–25.
34.
KrugmanHerbert (1965), “The Impact of Television Advertising: Learning Without Involvement,”Public Opinion Quarterly, 29(Fall), 349–56.
35.
LairdNan, and OlivierDonald (1981), “Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques,”Journal of the American Statistical Association, 76(June), 231–40.
36.
LarsenRandy J., and FredricksonBarbara L. (1999), “Measurement Issues in Emotion Research,” in Well-Being: The Foundations of Hedonic Psychology, KahnemanDaniel, DienerEd, and SchwarzNorbert, eds. New York: Russell Sage Foundation, 41–60.
37.
LastovickaJohn (1983), “Convergent and Discriminant Validity of Television Rating Scales,”Journal of Advertising Research, 12(2), 12–23.
38.
LeeLung F. (1998), “Simulated Maximum Likelihood Estimation of Dynamic Discrete Choice Statistical Models: Some Monte Carlo Results,”Journal of Econometrics, 82(1), 1–35.
39.
LloydDavid W., and ClancyKevin J. (1991), “CPMs Versus CPMIs: Implications for Media Planning,”Journal of Advertising Research, 31(4), 34–44.
40.
MacKieDiane M., and WorthLeila T. (1991), “Feeling Good but Not Thinking Straight: The Impact of Positive Mood on Persuasion,” in Emotion and Social Judgments, JosephP. Forgas, ed. New York: Pergamon, 201–209.
41.
ManesStephen (2001), “Press a Button, Skip the Ads,”Forbes, 167(14), 146.
42.
MartinLeonard L., and CloreGerald L. (2001), Theories of Mood and Cognition: A User's Handbook.Mahwah, NJ: Lawrence Erlbaum Associates.
43.
MerendaPeter F. (1997), “A Guide to the Proper Use of Factor Analysis in the Conduct and Reporting of Research: Pitfalls to Avoid,”Measurement and Evaluation in Counseling and Development, 30(3), 156–64.
44.
OlneyThomas J., HolbrookMorris B., and BatraRajeev (1991), “Consumer Responses to Advertising: The Effects of Ad Content, Emotions, and Attitude Toward the Ad on Viewing Time,”Journal of Consumer Research, 17(March), 440–53.
PasadeosYorgo (1990), “Perceived Informativeness of and Irritation with Local Advertising,”Journalism Quarterly, 67(1), 35–39.
47.
PetersenTrond (1991), “Time Aggregation Bias in Continuous-Time Hazard-Rate Models,” in Sociological Methodology, PeterV. Marsden, ed. Cambridge, MA: Basil Blackwell, 263–90.
48.
PetersonRobert A. (2000), “A Meta-Analysis of Variance Accounted For and Factor Loadings in Exploratory Factor Analysis,”Marketing Letters, 11(3), 261–75.
49.
PietersRik G.M., WarlopLuk, and WedelMichel (2002), “Breaking Through the Clutter: Benefits of Advertisement Originality and Familiarity for Attention and Memory,”Management Science, 48(June), 765–81.
50.
PolsfussMark, and HessMike (1991), “‘Liking’ Through MTM Evaluation: Identifying Key Selling Segments in Advertising,”Advances in Consumer Research, 18(1), 540–44.
51.
PoniewozikJames (1999), “Here Come PVRs,”Time Canada, 154(13), 50.
52.
PutoChristopher P., and WellsWilliam D. (1984), “Informational and Transformational Advertising: The Differential Effects of Time,”Advances in Consumer Research, 11(1), 638–43.
53.
RamsayJim O., and SilvermanBernard W. (1997), Functional Data Analysis.New York: Springer.
54.
ResnikAlan, and SternBruce L. (1977), “An Analysis of Information Content in Television Advertising,”Journal of Marketing, 41(January), 50–53.
55.
RossWilliam T., and SimonsonItamar (1991), “Evaluations of Pairs Experiences: A Preference for Happy Endings,”Journal of Behavioral Decision Making, 4, 273–82.
56.
RossiterJohn R., PercyLarry, and DonovanRobert J. (1991), “A Better Advertising Grid,”Journal of Advertising Research, 31(5), 11–21.
57.
SchlingerMary J. (1979), “A Profile of Responses to Commercials,”Journal of Advertising Research, 19(2), 37–46.
58.
SchwarzNorbert (2001), “Feelings as Information: Implications for Affective Influences on Information Processing,” in Theories of Mood and Cognition: A User's Guidebook, LeonardL. Martin, and CloreGerald L., eds. Mahwah, NJ: Lawrence Erlbaum Associates, 159–76.
59.
SiddarthS., and ChattopadhyayAmitava (1998), “To Zap or Not to Zap: A Study of the Determinants of Channel Switching During Commercials,”Marketing Science, 17(2), 124–38.
60.
TavassoliNader T., ShultzClifford J., and FitzsimonsGavan J. (1995), “Program Involvement: Are Moderate Levels Best for Ad Memory and Attitude Toward the Ad?”Journal of Advertising Research, 35(5), 61–65.
61.
ter HofstedeFrenkel, and WedelMichel (1998), “A Monte Carlo Study of Time Aggregation in Continuous-Time and Discrete-Time Parametric Hazard Models,”Economics Letters, 58(2), 149–56.
62.
TseAlan Ching Biu (2001), “Zapping Behavior During Commercial Breaks,”Journal of Advertising Research, 41(3), 25–29.
63.
van BuurenStef (1991), Principal Curves of Time-Intensity Data.Leiden, Netherlands: Department of Psychology, Leiden University.
64.
van BuurenStef (1992), “Analyzing Time-Intensity Responses in Sensory Evaluation,”Food Technology, 46(2), 101–104.
65.
van MeursLex (1998), “Zapp! A Study on Switching Behavior During Commercial Breaks,”Journal of Advertising Research, 38(1), 43–53.
66.
Vanden AbeelePiet, and MacLachlanDouglas L. (1994), “Process Tracing of Emotional Responses to TV Ads: Revisiting the Warmth Monitor,”Journal of Consumer Research, 20(March), 586–600.
67.
VareyCarol, and KahnemanDaniel (1992), “Experiences Extend Across Time: Evaluation of Moments and Episodes,”Journal of Behavioral Decision Making, 5, 169–85.