References
- Ackerberg, D. A. (2003). Advertising, learning, and consumer choice in experience good markets: An empirical examination. International Economic Review, 44(3), 1007–1040. https://doi.org/10.1111/1468-2354.t01-2-00098
- Anand, B. N., & Shachar, R. (2011). Advertising, the matchmaker. The RAND Journal of Economics, 42(2), 205–245. https://doi.org/10.1111/j.1756-2171.2011.00131.x
- Bartsch, A., & Hartmann, T. (2017). The role of cognitive and affective challenge in entertainment experience. Communication Research, 44(1), 29–53. https://doi.org/10.1177/0093650214565921
- Burns, J. J., & Anderson, D. R. (1993). Attentional inertia and recognition memory in adult television viewing. Communication Research, 20(6), 777–799. https://doi.org/10.1177/009365093020006002
- Chen, M., & Bargh, J. A. (1999). Consequences of automatic evaluation: Immediate behavioral predispositions to approach or avoid the stimulus. Personality & Social Psychology Bulletin, 25(2), 215–224. https://doi.org/10.1177/0146167299025002007
- Czerwinski, M., Cutrell, E., & Horvitz, E. (2000). Instant messaging: Effects of relevance and timing. People & Computers XIV, Proceedings of HCI, British Computer Society,2, 71–76.
- Danaher, P. J., & Beed, T. W. (1993). A coincidental survey of people meter panelists: Comparing what people say with what they do. Journal of Advertising Research, 33(1), 86–93.
- Davies, J. (2017, September 27). The FT warns advertisers after discovering high levels of domain spoofing. Digiday, https://digiday.com/media/ft-warns-advertisers-discovering-high-levels-of-domain-spoofing/
- De Houwer, J. (2007). A conceptual and theoretical analysis of evaluative conditioning. The Spanish Journal of Psychology, 10(2), 230–241. https://doi.org/10.1017/S1138741600006491
- De Pelsmacker, P., Geuens, M., & Anckaert, P. (2002). Media context and advertising effectiveness: The role of context appreciation and context/ad similarity. Journal of Advertising, 31 (2), 49–61. https://doi.org/10.1080/00913367.2002.10673666
- DeGroot, M. H. (1970). Optimal statistical decisions. McGraw-Hill.
- Erdem, T., & Keane, M. P. (1996). Decision-making under uncertainty: Capturing dynamic brand choice processes in turbulent consumer goods markets. Marketing Science, 15(1), 1–20. https://doi.org/10.1287/mksc.15.1.1
- Gangadharbatla, H., Ackerman, C., & Bamford, A. (2019). Antecedents and consequences of binge-watching for college students. First Monday, 24(12). https://doi.org/10.5210/fm.v24i12.9667
- Goettler, R. L., & Shachar, R. (2001). Spatial competition in the network television industry. Rand Journal of Economics, 32 (4), 624–656. https://doi.org/10.2307/2696385
- Greenwald, A. G., & Leavitt, C. (1984). Audience involvement in advertising: Four levels. Journal of Consumer Research, 11(1), 581–592. https://doi.org/10.1086/208994
- Guadagni, P. M., & Little, J. D. (1983). A logit model of brand choice calibrated on scanner data. Marketing Science, 2 (3), 203–238. https://doi:10.1287/mksc.2.3.203
- Hiel, A. V., & Mervielde, I. (2002). Effects of ambiguity and need for closure on the acquisition of information. Social Cognition, 20(5), 380–408. https://doi.org/10.1521/soco.20.5.380.21124
- Holbrook, M. B., & Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of Consumer Research, 9(2), 132–140. https://doi.org/10.1086/208906
- Huang, S. C., & Zhang, Y. (2011). Motivational consequences of perceived velocity in consumer goal pursuit. Journal of Marketing Research, 48 (6), 1045–1056. https://doi.org/10.1509/jmr.10.0063
- Koblin, J., & Maheshwari, S. (2017, May 14). As viewers drift online, advertisers hold fast to broadcast TV. The New York Times, https://www.nytimes.com/2017/05/14/business/media/advertisers-streaming-video-broadcast-tv.html?ref=business
- Kruglanski, A. W. (1990). Motivations for judging and knowing: Implications for causal attribution. In E. T. Higgins & R. M. Sorrentino (Eds.), Handbook of motivation and cognition: Foundations of social behavior (pp. 333–368). Guilford Press.
- Kruglanski, A. W., & Freund, T. (1983). The freezing and unfreezing of lay-inferences: Effects on impressional primacy, ethnic stereotyping, and numerical anchoring. Journal of Experimental Social Psychology, 19(5), 448–468. https://doi.org/10.1016/0022-1031(83)90022-7
- Kruglanski, A. W., & Webster, D. W. (1996). Motivated closing of the mind: ‘Seizing’ and ‘Freezing’. Psychological Review, 103(2), 263–283. https://doi.org/10.1037/0033-295X.103.2.263
- Landwehr, J. R., Golla, B., & Reber, R. (2017). Processing fluency: An inevitable side effect of evaluative conditioning. Journal of Experimental Social Psychology, 70, 124–128. https://doi.org/10.1016/j.jesp.2017.01.004
- Lee, S., & Lumpkin, J. R. (1992). Differences in attitudes toward TV advertising: VCR usage as a moderator. International Journal of Advertising, 11(4), 333–342. https://doi.org/10.1080/02650487.1992.11104509
- Lyons, K. (2020, November 7). Netflix is testing a linear channel in France that should help with decision fatigue. The Verge. https://www.theverge.com/2020/11/7/21553998/netflix-linear-channel-france-streaming-cable-tv
- MacInnis, D. J., Moorman, C., & Jaworski, B. J. (1991). Enhancing and measuring consumers’ motivation, opportunity, and ability to process brand information from ads. The Journal of Marketing, 55(4), 32–53. https://doi.org/10.1177/002224299105500403
- Mathur, M., & Chattopadhyay, A. (1991). The impact of moods generated by television programs on responses to advertising. Psychology & Marketing, 8 (1), 59–77. https://doi.org/10.1002/mar.4220080106
- Neumann, R., Hess, M., Schulz, M., & Alpers, G. W. (2005). Automatic behavioural responses to valence: Evidence that facial action is facilitated by evaluative processing. Cognition & Emotion, 19(4), 499–513. https://doi.org/10.1080/02699930441000364.001
- Park, C. W., & Young, S. M. (1986). Consumer response to television commercials: The impact of involvement and background music on brand attitude formation. Journal of Marketing Research, 23(1), 11–24. https://doi.org/10.1177/002224378602300102
- Roets, A., & Van Hiel, A. (2011). Item selection and validation of a brief, 15-item version of the Need for Closure Scale. Personality and Individual Differences, 50(1), 90–94. https://doi.org/10.1016/j.paid.2010.09.004
- Rust, R. T., & Alpert, M. I. (1984). An audience flow model of television viewing choice. Marketing Science, 3 (2), 113–124. https://doi.org/10.1287/mksc.3.2.113
- Schweidel, D. A., & Kent, R. J. (2010). Predictors of the gap between program and commercial audiences: An investigation using live tuning data. Journal of Marketing, 74(1), 18–33. https://doi.org/10.1509/jmkg.74.3.018
- Speck, P. S., & Elliott, M. T. (1997). Predictors of advertising avoidance in print and broadcast media. Journal of Advertising, 26(3), 61–76. https://doi.org/10.1080/00913367.1997.10673529
- Statista. (2017). Genre breakdown of the top 250 TV programs in the United States in 2017. The Statistics Portal. https://www.statista.com/statistics/201565/most-popular-genres-in-us-primetime-tv/
- Statista. (2018). Global television advertising revenue from 2018 to 2022. The Statistics Portal. https://www.statista.com/statistics/237803/global-tv-advertising-revenue/
- Steiner, E., & Xu, K. (2020). Binge-watching motivates change: Uses and gratifications of streaming video viewers challenge traditional TV research. Convergence, 26(1), 82–101. https://doi.org/10.1177/1354856517750365
- Webster, A. (2012, April 19). Nielsen: Dramas most popular primetime TV, but reality shows win on product placement. The Verge. https://www.theverge.com/2012/4/19/2960515/nielsen-report-drama-most-popular-primetime-genre
- Webster, D. M., & Kruglanski, A. W. (1994). Individual differences in need for cognitive closure. Journal of Personality and Social Psychology, 67(6), 1049. https://doi.org/10.1037/0022-3514.67.6.1049
- Webster, D. M., & Kruglanski, A. W. (1997). Cognitive and social consequences of the need for cognitive closure. European Review of Social Psychology, 8(1), 133–173. https://doi.org/10.1080/14792779643000100
- Wilbur, K. C. (2008). A two-sided, empirical model of television advertising and viewing markets. Marketing Science, 27(3), 356–378. https://doi.org/10.1287/mksc.1070.0303
- Wilbur, K. C., Xu, L., & Kempe, D. (2013). Correcting audience externalities in television advertising. Marketing Science, 32(6), 892–912. https://doi.org/10.1287/mksc.2013.0807
- Yang, S., Narayan, V., & Assael, H. (2006). Estimating the interdependence of television program viewership between spouses: A bayesian simultaneous equation model. Marketing Science, 25(4), 336–349. https://doi.org/10.1287/mksc.1060.0195
- Zagalo, N., Branco, V., & Barker, A. (2003, November). From the necessity of film closure to inherent VR wideness. In International conference on virtual storytelling (pp. 74–77). Springer, Berlin, Heidelberg.
- Zhao, Y., Yang, S., Narayan, V., & Zhao, Y. (2013). Modeling consumer learning from online product reviews. Marketing Science, 32(1), 153–169. https://doi.org/10.1287/mksc.1120.0755
- Zillmann, D. (1991). Television viewing and physiological arousal. In J. Bryant & D. Zillmann (Eds.), Responding to the screen: Reception and reaction processes (pp. 103–134). Lawrence Erlbaum Associates, Inc.