Finally, and most fundamentally, it will be difficult to predict the effects of techno-
logical changes on mass media industries without a more basic understanding of the needs
that media industries fulfill for consumers. Most media economics research focuses on
interactions between platforms or interactions between types of agents (e.g., advertisers
and viewers). Yet we still do not have a great understanding of why the typical viewer is
watching 3–5 h of video per day, why video media appear to be so prevalent and habit-
forming, or what is the range of different needs (education, entertainment, information,
status, social connection, etc.) that are addressed through video consumption. A basic
taxonomy of viewer needs and behaviors would be very helpful in predicting the specific
aspects of the current mass media industries that will evolve in response to future tech-
nological changes.
ACKNOWLEDGMENTS
I thank Simon Anderson, Peter Danaher, Ron Goettler, Catherine Tucker, and Joel Waldfogel for helpful
comments and discussions, with particular gratitude to Anderson and Waldfogel for inviting the chapter.
REFERENCES
Anderson, S.P., de Palma, A., 2012. Competition for attention in the information (overload) age. RAND J.
Econ. 43 (1), 1–25.
Anderson, S.P., Gans, J.S., 2011. Platform siphoning ad-avoidance and media content. Am. Econ. J. Micro-
econ. 3 (4), 1–34.
Anderson, S.P., Renault, R., 2006. Advertising content. Am. Econ. Rev. 39 (1), 305–326.
Athey, S., Calvano, E., Gans, J.S., 2013. The Impact of the Internet on Advertising Markets for News Media.
Mimeo, University of Toronto.
Becker, G., Murphy, K., 1993. A simple theory of advertising as a good or a bad. Q. J. Econ. 108 (4),
941–964.
Bergemann, D., Bonatti, A., 2011. Targeting in advertising markets implications for offline vs. online media.
RAND J. Econ. 42, 417–443.
Bergemann, D., Bonatti, A., 2014. Selling cookies. Am. Econ. J. Microecon. 7 (3), 259–294.
Bollinger, B.K., Cohen, M.A., Lai, J., 2013. Measuring Asymmetric Persistence and Interaction Effects of
Media Exposures Across Platforms. Mimeo, New York University.
Brasel, S.A., Gips, J., 2008. Breaking through fast-forwarding brand information and visual attention.
J. Mark. 72, 31–48.
Brasel, S.A., Gips, J., 2011. Media multitasking behavior concurrent television and computer usage. Cyberp-
sychol. Behav. Soc. Netw. 14 (9), 527–534.
Brasel, S.A., Gips, J., 2013. Tablets, touchscreens and touchpads how varying touch interfaces trigger
psychological ownership and endowment. J. Consum. Res. 24, 226–233.
Bronnenberg, B.J., Dube, J.-P., Mela, C.F., 2010. Do digital video recorders influence sales? J. Mark. Res.
30 (3), 447–468.
Brynjolfsson, E., Hu, J., Simester, D., 2011. Goodbye Pareto principle, hello long tail: the effect of internet
commerce on the concentration of product sales. Manag. Sci. 57 (8), 1373–1387.
Business Insider (BI), 2013. The Future of Digital 2013. Slide deck.
Cable Advertising Bureau (CAB), 2014. Why Ad-Supported Cable? White Paper.
Chevalier, J., Mayzlin, D., 2006. The effect of word of mouth on sales online book reviews. J. Mark. Res.
43 (3), 345–354.
Deng, Y., 2015. DVR Advertising Targeting. Mimeo, Duke University.
Digital TV Research, 2014. North America to Add 5 Million Pay TV Subscribers. Press release.
Dukes, A., Gal-Or, E., 2003. Negotiations and exclusivity contracts for advertising. Mark. Sci. 22 (2),
222–245.
222 Handbook of Media Economics
Ellison, G., Wolitsky, A.G., 2012. A search cost model of obfuscation. RAND J. Econ. 43, 417–441.
eMarketer, 2012. Traditional Media Still Most Trusted Sources of Info. Press release.
Esteves-Sorenson, C., Perretti, F., 2012. Micro-costs inertia in television viewing. Econ. J. 122 (563),
867–902.
Fetto, J., 2013. Americans Spend 58 Minutes a Day on Their Smartphones. Accessed March 2014.
http://www.experian.com/blogs/marketing-forward/2013/05/28/americans-spend-58-minutes-a-day-
on-their-smartphones/
.
George, L.M., Waldfogel, J., 2006. The New York Times and the market for newspapers. Am. Econ. Rev.
96 (1), 435–447.
Ghosh, B., Stock, A., 2010. Advertising effectiveness, digital video recorders, and product market compe-
tition. Mark. Sci. 29 (4), 639–649.
Ghosh, B.P., Galbreth, M.R., Shang, G., 2013. The competitive impact of targeted television advertise-
ments using DVR technology. Decis. Sci. 44 (5), 951–971.
Godes, D., Mayzlin, D., 2004. Using online conversations to study word-of-mouth communication. Mark.
Sci. 23 (4), 545–560.
Goldfarb, A., Tucker, C., 2011a. Online display advertising targeting and obtrusiveness. Mark. Sci. 30 (3),
389–494.
Goldfarb, A., Tucker, C., 2011b. Privacy regulation and online advertising. Manag. Sci. 57 (1), 57–71.
Goldstein, D.G., McAfee, R.P., Suri, S., 2013. The cost of annoying ads. In: Proceedings of the 23rd Inter-
national World Wide Conference.
Gong, S., Zhang, J., Zhao, P., Jiang, X., 2015. Tweeting Increases Product Demand. Working paper.
Massachusetts Institute of Technology.
Google, 2012. The New Multi-Screen World Understanding Cross-Platform Consumer Behavior. White
Paper.
Hill, S., Benton, A., 2012. Talkographics Using What Viewers Say Online to Calculate Audience Affinity
Networks for Social TV-Based Recommendations. Mimeo, University of Pennsylvania.
Hu, Y., Du, R., Damangir, S., 2014. Decomposing the impact of advertising: augmenting sales with online
search data. J. Mark. Res. 51 (3), 300–310.
Interian, Y., Dorai-Raj, S., Naverniouk, I., Opalinski, P.J., Kaustuv, Zigmond, D., 2009. Ad quality on TV:
predicting television audience retention. In: Proceedings of the Third International Workshop on Data
Mining and Audience Intelligence for Advertising, Paris, France, pp. 85–91.
http://www.
australianscience.com.au/research/google/35368.pdf
.
Jayasinghe, L., Ritson, M., 2013. Everyday advertising context: an ethnography of advertising response in
the living room. J. Consum. Res. 40 (1), 104–121.
Joo, M., Wilbur, K.C., Cowgill, B., Zhu, Y., 2014. Television advertising and online search. Manag. Sci.
60 (1), 56–73.
Joo, J., Wilbur, K.C., Zhu, Y., 2015. Effects of TV advertising on keyword search. Int. J. Res. Mark.
forthcoming.
Kim, H., Hanssens, D.M., 2014. Paid and Earned Media, Consumer Interest and Motion Picture Revenue.
Mimeo, University of California, Los Angeles.
Kolsarici, C., Vakratsas, D., 2011. The Complexity of Multi-Media Effects: Marketing Science Institute
Working Paper Series 2011 Report No. 11–100. Marketing Science Institute.
http://www.mcgill.
ca/files/_nea/211583_MSIWP.pdf
.
Leichtman Research Group (LRG), 2013. The Rise and Plateau of DVRs. White Paper.
Lewis, R.A., Reiley, D.H., 2013. Down-to-the-minute effects of super bowl advertising on online search
behavior. In: 14th ACM Conference on Electronic Commerce, 9. p. 4, Article 61.
Liaukonyte, J., Teixeira, T., Wilbur, K.C., 2015. How TV ads influence online search. Mark. Sci. 34 (3),
311–330.
Magee, R.G., 2013. Can a print publication be equally effective online? Testing the effect of medium type on
marketing communications. Mark. Lett. 24, 85–95.
Naik, P.A., Peters, K., 2009. A hierarchical marketing communications model of online and offline media
synergies. J. Interact. Mark. 23, 288–299.
Naik, P.A., Raman, K., 2003. Understanding the impact of synergy in multimedia communications. J. Mark.
Res. 13 (4), 25–34.
223Recent Developments in Mass Media
Naik, P.A., Raman, K., Winter, R.S., 2005. Planning marketing-mix strategies in the presence of interaction
effects. Mark. Sci. 24 (1), 25–34.
Nielsen, 2010. Three Screen Report, 1st Quarter 2010. White Paper .
Nielsen, 2013. ‘Binging’ Is the New Viewing for Over-the-Top Streamers. Accessed March 2014.
http://www.nielsen.com/us/en/insights/news/2013/binging-is-the-new-viewing-for-over-the-top-
streamers.html
.
Nielsen, 2014a. The Cross-Platform Report. Accessed March 2014.
http://www.nielsen.com/us/en/
insights/reports/2014/shifts-in-viewing-the-cross-platform-report-q2-2014.html
.
Nielsen, 2014b. Social TV on the Rise: Almost One in Two Online Australians Engaging in Digital
Conversation. Accessed March 2014.
http://www.nielsen.com/au/en/insights/news/2014/social-tv-
on-the-rise.html
.
Ofcom, 2013. Communications Market Report 2013. White Paper.
Ohnishi, H., Manchanda, P., 2012. Marketing activity, blogging and sales. Int. J. Res. Mark. 29 (2012),
221–234.
Pearson, S., Barwise, P., 2007. PVRs and advertising exposure: a video ethnographic study. Qual. Mark.
Res. Int. J. 11 (4), 386–399.
Reis, F., 2015. Patterns of Substitution between Internet and Television in the Era of Media Streaming -
Evidence from a Randomized Experiment. Working paper. Carnegie Mellon University.
Robinson, J.P., Martin, S., 2009. Of time and television. Ann. Am. Acad. Pol. Soc. Sci. 625, 74–86.
Sahagian, J., 2013. Study U.S. Smartphone Penetration Is at 74 Percent. Accessed March 2014. http://www.
emarketer.com/Article/Smartphone-Tablet-Uptake-Still-Climbing-US/1010297
.
Schweidel, D.A., Kent, R.J., 2010. Predictors of the gap between program and commercial audiences: an
investigation using live tuning data. J. Mark. 74 (3), 18–33.
Stephen, A.T., Galak, J., 2012. The effects of traditional and social earned media on sales: a study of a micro-
lending marketplace. J. Mark. Res. 44 (Oct.), 624–639.
Teixeira, T., Wedel, M., Pieters, R., 2010. Moment-to-moment optimal branding in TV commercials
preventing avoidance by pulsing. Mark. Sci. 29 (5), 783–804.
Television Bureau of Advertising (TVB), 2014. TV Basics. Accessed March 2014. http://www.tvb.org/
research/95487
.
TiVo, 2013. TiVo Research and Analytics Netflix Not Cannibalizing Traditional TV Viewing.
http//www.
marketwired.com/press-release/TiVo-Research-and-Analytics-Netflix-Not-Cannibalizing-
Traditional-TV-Viewing-1815308.htm
. Accessed April 2014.
Tuchman, A., Nair, H.S., Gardete, P., 2015. Complementarities in Consumption and the Consumer
Demand for Advertising. Mimeo, Stanford GSB.
Waldfogel, J., 2013. Digitization and the Quality of New Media Products: The Case of Music. Working
paper. University of Minnesota.
Wallsten, S., 2014. What Are We Not Doing When We’re Online? Mimeo, NBER.
Wilbur, K.C., 2008. How the digital video recorder changes traditional television advertising. J. Advert.
37 (1), 143–149.
Wilbur, K.C., 2015. Television Advertising Avoidance. Mimeo, University of California, San Diego.
Wilbur, K.C., Zhu, Y., 2009. Click fraud. Mark. Sci. 28 (2), 293–308.
Wilbur, K.C., Xu, L., Kempe, D., 2013. Correcting audience externalities in television advertising. Mark.
Sci. 32 (6), 892–912.
Woo, J., Choi, J.Y., Shin, J., Lee, J., 2014. The effect of new media on consumer media usage: an empirical
study in South Korea. Technol. Forecast. Soc. Change 89 (Nov.), 3–11.
Wu, J., Cook Jr., V.J., Strong, E.C., 2005. A two-stage model of the promotional performance of pure
online firms. Inf. Syst. Res. 16 (4), 334–351.
Zantedeschi, D., Feit, E.M., Bradlow, E.T., 2014. Measuring Multi-Channel Advertising Effectiveness
Using Consumer-Level Advertising Response Data. Mimeo, University of Pennsylvania.
Zentner, A., 2012. Internet adoption and advertising expenditures on traditional media: an empirical analysis
using a panel of countries. J. Econ. Manage. Strat. 21 (4), 913–926.
Zigmond, D., Stipp, H., 2010. Assessing a new advertising effect measurement of impact of television
commercials on internet search queries. J. Advert. Res. 50 (2), 162–168.
Zigmond, D., Stipp, H., 2011. Multitaskers may be advertisers’ best audience. Harv. Bus. Rev. 12 (1/2), 32–33.
Zufryden, F.S., Pedrick, J.H., Sankaralingam, A., 1993. Zapping and its impact on brand purchase behavior.
J. Advert. Res. 33, 58–66.
224 Handbook of Media Economics
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.