Social context and advertising effectiveness: a dynamic study

References

• Aaker, D.A., D.M. Stayman, and M.R. Hagerty. 1986. Warmth in advertising: Measurement, impact, and sequence effects. Journal of Consumer Research 12, no. 4: 365–81.
   Web of Science ®Google Scholar
• Ambler, T., and T. Burne. 1999. The impact of affect on memory of advertising. Journal of Advertising Research 39, no. 2: 25–34.
   Web of Science ®Google Scholar
• Anderson, A.K., P.E. Wais, and J.D.E. Gabrieli. 2006. Emotion enhances remembrance of neutral events past. Proceedings of the National Academy of Sciences of the United States of America 103, no. 5: 1599–604.
   PubMed Web of Science ®Google Scholar
• Ariely, D., and J. Levav. 2000. Sequential choice in group settings: Taking the road less traveled and less enjoyed. Journal of Consumer Research 27, no. 3: 279–290.
   Google Scholar
• Atkinson, K. 2013. Six key trends as Upfront, NewFront blend into a giant play for video ad dollars: Who will come out on top in the negotiations? Advertising Age, 8 May. Available online at: http://adage.com/article/digitalnext/upfront-newfront-blend-a-giant-play-video-advertising-dollars/241331/ (accessed February 2014).
   Google Scholar
• Austin, J.T., and J.B. Vancouver. 1996. Goal constructs in psychology: Structure, process, and content. Psychological Bulletin 120, no. 3: 338–75.
   Web of Science ®Google Scholar
• Bellman, S., J.R. Rositter, A. Schweda, and D. Varan. 2012. How coviewing reduces the effectiveness of TV advertising. Journal of Marketing Communications 18, no. 5: 363–78.
   Google Scholar
• Bellman, S., A. Schweda, and D. Varan. 2010. The importance of social motives for watching and interacting with digital television. International Journal of Market Research 52, no. 1: 67.
   Web of Science ®Google Scholar
• Bibel, S. 2013. ABC claims the number 1 most co-viewed program during premiere week with The Goldbergs. TV By The Numbers, 2 October. Available online at: http://tvbythenumbers.zap2it.com/2013/10/02/abc-claims-the-number-1-most-co-viewed-program-during-premiere-week-with-the-goldbergs/206507/ (accessed February 2014).
   Google Scholar
• Brasel, S.A., and J. Gips. 2008. Breaking through fast-forwarding: Brand information and visual attention. Journal of Marketing 72, no. 6: 31.
   Web of Science ®Google Scholar
• Byzalov, D., and R. Shachar. 2004. The risk reduction role of advertising. Quantitative Marketing and Economics 2: 283–320.
   Web of Science ®Google Scholar
• Cauberghe, V., M. Geuens, and P. De Pelsmacker. 2011. Context effects of TV programme-induced interactivity and telepresence on advertising responses. International Journal of Advertising 30, no. 4: 641–63.
   Web of Science ®Google Scholar
• Chaney, A.J.B., M. Gartrell, J.M. Hofman, J. Guiver, N. Koenigstein, P. Kohli, and U. Paquet. 2013. Mining large-scale tv group viewing patterns for group recommendation. Technical Report, MSR-TR-2013-114, Microsoft Research, Microsoft Corporation.
   Google Scholar
• Colquitt, J.A., and C.P. Zapata-Phelan. 2007. Trends in theory building and theory testing: A five-decade study of the academy of management journal. Academy of Management Journal 50, no. 6: 1281–303.
   Web of Science ®Google Scholar
• Csikszentmihalyi, M., and R. Kubey. 1981. Television and the rest of life: A systematic comparison of subjective experience. Public Opinion Quarterly 45, no. 3: 317–28.
   Web of Science ®Google Scholar
• Edell, J.A., and M.C. Burke. 1987. The power of feelings in understanding advertising effects. Journal of Consumer Research 14, no. 3: 421.
   Web of Science ®Google Scholar
• Graser, M. 2004. Families watching and recalling more TV ads: Study finds groups are more receptive to commercials. Advertising Age, 5 December. Available online at: http://adage.com/article/madisonvine-news/families-watching-recalling-tv-ads/41727/ (accessed September 2013).
   Google Scholar
• Greene, W.H. 2010. Limdep 9.0: User's Manual. New York: Econometric Software Inc.
   Google Scholar
• Haridakis, P., and G. Hanson. 2009. Social interaction and co-viewing with YouTube: Blending mass communication reception and social connection. Journal of Broadcasting & Electronic Media 53, no. 2: 317–335.
   Google Scholar
• Jayasinghe, L., and M. Ritson. 2013. Everyday advertising context: An ethnography of advertising response in the family living room. Journal of Consumer Research 40, no. 1: 104–21.
   Web of Science ®Google Scholar
• Katz, E., J.G. Blumler, and M. Gurevitch. 1974. Uses and gratifications research. Public Opinion Quarterly 37: 509–23.
   Web of Science ®Google Scholar
• Krugman, D.M., G.T. Cameron, and C.M. White. 1995. Visual attention to programming and commercials: The use of in-home observations. Journal of Advertising 24, no. 1: p. 1.
   Web of Science ®Google Scholar
• Krugman, D.M. and K.F. Johnson. 1991. Differences in the consumption of traditional broadcast and VCR movie rentals. Journal of Broadcasting & Electronic Media 35, no. 2: 213–232.
   Google Scholar
• Kubey, R.W., and M. Csikszentmihalyi. 1990. Television as escape: Subjective experience before an evening of heavy viewing. Communication Reports 3, no. 2: 92–100.
   Google Scholar
• Kwak, H. 2012. Self-disclosure in online media: An active audience perspective. International Journal of Advertising 31, no. 3: 485–510.
   Web of Science ®Google Scholar
• Lee, B., and R.S. Lee. 1995. How and why people watch TV: Implications for the future of interactive television. Journal of Advertising Research 35, no. 6: 9.
   Web of Science ®Google Scholar
• Lull, J. 1980. The social uses of television. Human Communication Research 6, no. 3: 197–209.
   Google Scholar
• Mora, J.D. 2012. Fuzzy dynamic groups: Measures and implications for television audiences. In Fuzzy methods for customer relationship management and marketing: Applications and classification, ed. A. Meier and L. Donzé, 41–60. Hershey PA: IGI Global.
   Google Scholar
• Mora, J.D., J. Ho, and R. Krider. 2011. Television co-viewing in Mexico: An assessment on people meter data. Journal of Broadcasting & Electronic Media 55, no. 4: 448–69.
   Web of Science ®Google Scholar
• Mora, J.D., R.E. Krider, and J. Ho. 2015. Who decides what to watch on TV at home? Insights from people-meter data in Mexico. Journal of Advertising Research 55, no.1: 22–36.
   Google Scholar
• Nielsen 2009. Does ESPN spell love? Nielsen Newswire, 2 December. Available online at: http://www.nielsen.com/us/en/insights/news/2009/does-espn-spell-love.html (accessed September 2013).
   Google Scholar
• Nielsen 2014. Nielsen Twitter social TV ratings. Available online at: http://www.nielsensocial.com/product/nielsen-twitter-tv-ratings/ (accessed July 2014).
   Google Scholar
• Puntoni, S., and, N.T. Tavassoli. 2007. Social context and advertising memory. Journal of Marketing Research 44, no. 2: 284–96.
   Web of Science ®Google Scholar
• Rennhoff, A.D., and K.C. Wilbur. 2011. The effectiveness of post-release movie advertising. International Journal of Advertising 30, no. 2: 305.
   Web of Science ®Google Scholar
• Ritson, M., and R. Elliot. 1999. The social uses of advertising: An ethnographic study of adolescent advertising audiences. Journal of Consumer Research 26, no. 3: 260–77.
   Web of Science ®Google Scholar
• Rust, R., and M. Alpert. 1984. An audience flow model of television viewing choice. Marketing Science 3, no. 1: 113–127.
   Google Scholar
• Schmitt, K.L., K.C. Woolf, and D.R. Anderson. 2003. Viewing the viewers: Viewing behaviors by children and adults during television programs and commercials. Journal of Communication 53, no. 2: 265–81.
   Web of Science ®Google Scholar
• Shachar, R., and J.W. Emerson. 2000. Cast demographics, unobserved segments, and heterogeneous switching costs in a television viewing choice model. Journal of Marketing Research 37, no. 2: 173–86.
   Web of Science ®Google Scholar
• Sigelman, L., and L. Zeng. 1999. Analyzing censored and sample-selected data with Tobit and Heckit models. Political Analysis 8, no. 2: 167–82.
   Google Scholar
• Swamy, P.A.V.B., and G.S. Tavlas. 1995. Random coefficient models: Theory and applications. Journal of Economic Surveys 9, no. 2: 165–96.
   Google Scholar
• Vosgerau, J., K. Wertenbroch, and Z. Carmon. 2006. Indeterminacy and live television. Journal of Consumer Research 32, no. 4: 487–95.
   Web of Science ®Google Scholar
• Yang, S., V. Narayan, and H. Assael. 2006. Estimating the interdependence of television program viewership between spouses: A Bayesian simultaneous equation model. Marketing Science 25, no. 4: 336–49.
   Web of Science ®Google Scholar
• Yang, S., Y. Zhao, T. Erdem, and Y. Zhao. 2010. Modeling the intrahousehold behavioral interaction. Journal of Marketing Research 47, no. 3: 470–84.
   Web of Science ®Google Scholar
• Zufryden, F.S., J.H. Pedrick, and A. Sankaralingam 1993. Zapping and its impact on brand purchase behavior. Journal of Advertising Research 33, no. 1: 58–66.
   Web of Science ®Google Scholar