Moment-to-Moment Optimal Branding in TV Commercials: Preventing Avoidance by Pulsing

Published Online:https://doi.org/10.1287/mksc.1100.0567

References

  • Aaker D. A., Bruzzone D. E. Causes of irritation in advertising. J. Marketing (1985) 49(2):47–57CrossrefGoogle Scholar
  • Aitchinson J.Cutting Edge Advertising: How to Create the World's Best Print for Brands in the 2lst Century (1999) (Prentice Hall, New York) Google Scholar
  • Albert J. H., Chib S. Bayesian analysis of binary and polychotomous response data. J. Amer. Statist. Assoc. (1993) 88(422):669–679CrossrefGoogle Scholar
  • Arnheim R.The Power of the Center: A Study of Composition in the Visual Arts (1988) (University of California Press, Berkeley) Google Scholar
  • Baker W. E., Honea H., Russell C. A. Do not wait to reveal the brand name: The effect of brand-name placement on television advertising effectiveness. J. Advertising (2004) 33(3):77–85CrossrefGoogle Scholar
  • Bass F. M., Bruce N., Majumdar S., Murthi B. P. S. Wearout effects of different advertising themes: A dynamic Bayesian model of the advertising-sales relationship. Marketing Sci. (2007) 26(2):179–195LinkGoogle Scholar
  • Berlyne D. E.Aesthetics and Psychobiology (1971) (Appleton-Century-Crofts, New York) Google Scholar
  • Billio M., Casarin R., Sartore D., Mazzi G. L., Savio G. Bayesian inference on dynamic models with latent factors. Growth and Cycle in the Eurozone (2007) (Palgrave Macmillan, Basingstoke, Hampshire, UK) 25–44CrossrefGoogle Scholar
  • Bolls P. D., Muehling D. D., Yoon K. The effect of television commercial pacing on viewers' attention and memory. J. Marketing Comm. (2003) 9(1):17–28CrossrefGoogle Scholar
  • Book A. C., Schick C. D.Fundamentals of Copy and Layout (1997) (NTC/Contemporary Publishing Group, Lincolnwood, IL) Google Scholar
  • Brown S. C., Craik F. I. M., Tulving E., Craik F. I. M. Encoding and retrieval of information. The Oxford Handbook of Memory (2000) (Oxford University Press, Oxford, UK) 93–107Google Scholar
  • Bryce W. J., Yalch R. F. Hearing versus seeing: A comparison of learning of spoken and pictorial information in television advertising. J. Current Issues Res. Advertising (1993) 15(1):1–20CrossrefGoogle Scholar
  • Burns J. J., Anderson D. R. Attentional inertia and recognition memory in adult television viewing. Comm. Res. (1993) 20(6):777–799CrossrefGoogle Scholar
  • Calvo M. G., Lang P. J. Gaze patterns when looking at emotional pictures: Motivationally biased attention. Motivation Emotion (2004) 28(3):221–243CrossrefGoogle Scholar
  • Carter C. K., Kohn R. On Gibbs sampling for state space models. Biometrika (1994) 81(3):541–553CrossrefGoogle Scholar
  • Chib S. Marginal likelihood from the Gibbs output. J. Amer. Statist. Assoc. (1995) 90(432):1313–1321CrossrefGoogle Scholar
  • Cronin J. J. In-home observations of commercial avoidance behavior. J. Current Issues Res. Advertising (1995) 17(2):69–75CrossrefGoogle Scholar
  • Donderi D. C. Visual complexity: A review. Psych. Bull. (2006) 132(1):73–97CrossrefGoogle Scholar
  • Duchowski A. T.Eye Tracking Methodology: Theory and Practice (2003) (Springer-Verlag, London) CrossrefGoogle Scholar
  • d'Ydewalle G., Desmet G., Van Rensbergen J., Underwood G. Film perception: The processing of film cuts. Eye Guidance in Reading and Scene Perception (1998) (Elsevier Science, Amsterdam) 357–367CrossrefGoogle Scholar
  • Fazio R. H., Herr P. M., Powell M. C. On the development and strength of category–brand associations in memory: The case of mystery ads. J. Consumer Psych. (1992) 1(1):1–13CrossrefGoogle Scholar
  • Feichtinger G., Hartl R. F., Sethi S. P. Dynamic optimal control models in advertising: Recent developments. Management Sci. (1994) 40(2):195–226LinkGoogle Scholar
  • Feinberg F. M. On continuous-time optimal advertising under S-shaped response. Management Sci. (2001) 47(11):1476–1487LinkGoogle Scholar
  • Frühwirth-Schnatter S. Data augmentation and dynamic linear models. J. Time Ser. Anal. (1994) 15(2):183–202CrossrefGoogle Scholar
  • Gamerman D. Markov chain Monte Carlo for dynamic generalized linear models. Biometrika (1998) 85(1):215–227CrossrefGoogle Scholar
  • Germeys F., d'Ydewalle G. The psychology of film: Perceiving beyond the cut. Psych. Res. (2007) 71(4):458–466CrossrefGoogle Scholar
  • Gelfand A. E., Hills S. E., Racine-Poon A., Smith A. F. M. Illustration of Bayesian inference in normal data models using Gibbs sampling. J. Amer. Statist. Assoc. (1990) 85(412):972–985CrossrefGoogle Scholar
  • Greyser S. A. Irritation in advertising. J. Advertising Res. (1973) 13(1):3–10Google Scholar
  • Grover R., Fine J. The sound of many hands zapping. BusinessWeek (2006) May 22). http://www.businessweek.com/magazine/content/06_21/b3985063.htmGoogle Scholar
  • Gustafson P., Siddarth S. Describing the dynamics of attention to TV commercials: A hierarchical Bayes analysis of the time to zap an ad. J. Appl. Statist. (2007) 34(5):585–609CrossrefGoogle Scholar
  • Hahn M., Hyun J.–S. Advertising cost interactions and the optimality of pulsing. Management Sci. (1991) 37(2):157–169LinkGoogle Scholar
  • Heeter C., Greenberg B. S. Profiling the zappers. J. Advertising Res. (1985) 25(2):15–19Google Scholar
  • Janiszewski C. The influence of display characteristics on visual exploratory search behavior. J. Consumer Res. (1998) 25(3):290–301CrossrefGoogle Scholar
  • Krugman D. M., Cameron G. T., White C. M. Visual attention to programming and commercials: The use of in-home observations. J. Advertising (1995) 24(1):1–12CrossrefGoogle Scholar
  • Kutner M. H., Nachtsheim C. J., Neter J.Applied Linear Regression Models (2004) (McGraw-Hill, New York) Google Scholar
  • Lachaab M., Ansari A., Jedidi K., Trabelsi A. Modeling preference evolution in discrete choice models: A Bayesian state-space approach. Quant. Marketing Econom. (2006) 4(1):57–81CrossrefGoogle Scholar
  • Lang A. The limited capacity model of mediated message processing. J. Comm. (2000) 50(1):46–70CrossrefGoogle Scholar
  • Lang A., Zhou S., Schwartz N., Bolls P. D., Potter R. F. The effects of edits on arousal, attention, and memory for television messages: When an edit is an edit can an edit be too much? J. Broadcasting Electron. Media (2000) 44(1):94–109CrossrefGoogle Scholar
  • Lang A., Shin M., Bradley S. D., Wang Z., Lee S., Potter D. Wait! Don't turn that dial! More excitement to come! The effects of story length and production pacing in local television news on channel changing behavior and information processing in a free choice environment. J. Broadcasting Electron. Media (2005) 49(1):3–22CrossrefGoogle Scholar
  • Martin A. D., Quinn K. M. Dynamic ideal point estimation via Markov chain Monte Carlo for the U.S. Supreme Court, 1953–1999. Political Anal. (2002) 10(2):134–153CrossrefGoogle Scholar
  • Mihaylova M., Stomonyakov V., Vassilev A. Peripheral and central delay in processing high spatial frequencies: Reaction time and VEP latency studies. Vision Res. (1999) 39(4):699–705CrossrefGoogle Scholar
  • Naik P. A., Mantrala M. K., Sawyer A. G. Planning media schedules in the presence of dynamic advertising quality. Marketing Sci. (1998) 17(3):214–235LinkGoogle Scholar
  • Palmer S. E.Vision Science: Photons to Phenomenology (1999) (A Bradford Book, Cambridge, MA) Google Scholar
  • Pavelchak M. A., Gardner M. P., Broach V. C. Effect of ad pacing and optimal level of arousal on attitude toward the ad. Adv. Consumer Res. (1991) 18:94–99Google Scholar
  • Perse E. M. Implications of cognitive and affective involvement for channel changing. J. Comm. (1998) 48(3):49–68CrossrefGoogle Scholar
  • Pieters R., Wedel M. Attention capture and transfer in advertising: Brand, pictorial, and text-size effects. J. Marketing (2004) 68(2):36–50CrossrefGoogle Scholar
  • Pieters R., Wedel M. Goal control of attention to advertising: The Yarbus implication. J. Consumer Res. (2007) 34(2):224–233CrossrefGoogle Scholar
  • Pieters R., Wedel M., Zhang J. Optimal feature advertising design under competitive clutter. Management Sci. (2007) 53(11):1815–1828LinkGoogle Scholar
  • Rayner K. Eye movements in reading and information processing: 20 years of research. Psych. Bull. (1998) 124(3):372–422CrossrefGoogle Scholar
  • Rossi P. E., Allenby G. M. Bayesian statistics and marketing. Marketing Sci. (2003) 22(3):304–328LinkGoogle Scholar
  • Sekhon J., Mebane W. Genetic optimization using derivatives: Theory and applications to nonlinear models. Political Anal. (1998) 7(1):187–210CrossrefGoogle Scholar
  • Siddarth S., Chattopadhyay A. To zap or not to zap: A study of the determinants of channel switching during commercials. Marketing Sci. (1998) 17(2):124–138LinkGoogle Scholar
  • Sprott J. C., Bolliger J., Mladenoff D. J. Self-organized criticality in forest-landscape evolution. Phys. Lett. A (2002) 297(3–4):267–271CrossrefGoogle Scholar
  • Steinberg B., Hampp A. DVR ad skipping happens, but not always. Advertising Age (2007) May 31). http://adage.com/mediaworks/article?article_id=117023Google Scholar
  • Stewart D. W., Furse D. H.Effective Television Advertising (1986) (Lexington Books, Lexington, MA) Google Scholar
  • Stewart D. W., Koslow S. Executional factors and advertising effectiveness. J. Advertising (1989) 18(3):21–32CrossrefGoogle Scholar
  • Sueyoshi G. T. A class of binary response models for grouped duration data. J. Appl. Econometrics (1995) 10(4):411–431CrossrefGoogle Scholar
  • Tse A. C. B., Lee R. P. W. Zapping behavior during commercial breaks. J. Advertising Res. (2001) 41(3):25–29CrossrefGoogle Scholar
  • Wedel M., Pieters R. Eye fixations on advertisements and memory for brands: A model and findings. Marketing Sci. (2000) 19(4):297–312LinkGoogle Scholar
  • Wedel M., Pieters R. A review of eye-tracking research in marketing. Rev. Marketing Res. (2008) 4:123–147CrossrefGoogle Scholar
  • West M., Harrison J.Bayesian Forecasting and Dynamic Linear Models (1997) (Springer-Verlag, New York) Google Scholar
  • Wilbur K. C. How the digital video recorder changes traditional television advertising. J. Advertising (2008) 37(1):143–149CrossrefGoogle Scholar
  • Woltman Elpers J. L. C. M., Wedel M., Pieters F. G. M. Why do consumers stop watching TV commercials?: Two experiments on the influence of moment-to-moment entertainment and information value. J. Marketing Res. (2003) 40(4):437–453CrossrefGoogle Scholar
  • Woolley S. Zap! Forbes (2003) September). http://www.forbes.com/free_forbes/2003/0929/076.htmlGoogle Scholar
  • Yarbus A. L.Eye Movements and Vision (1967) (Plenum, New York) CrossrefGoogle Scholar
  • Yerkes R. M., Dodson J. D. The relation of strength of stimulus to rapidity of habit-formation. J. Comparative Neurology Psych. (1908) 18(5):459–482CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.