Analyzing Economies of Scale from Targeted Advertisements in Next-Generation TV

42 Pages Posted: 14 Mar 2018 Last revised: 22 Nov 2018

See all articles by Aman Tyagi

Aman Tyagi

Carnegie Mellon University, Department of Engineering and Public Policy, Students

Jon M. Peha

Carnegie Mellon University

Date Written: November 2018


In November 2017, the Federal Communication Commission (FCC) authorized Over-the-Air (OTA) broadcasters to use the Next-Generation Television (TV) standard, also known as the Advanced Television Systems Committee 3.0 (ATSC 3.0) standard, on a voluntary, market-driven basis. ATSC 3.0 allows broadcasters to send targeted advertisements via the internet and merge them with broadcasted video content on a user's device. Next-generation TV could also reach mobile devices, as well as traditional fixed TVs. This paper considers the scenario where broadcasters do send targeted advertisements via the internet. In such a scenario, broadcasters with more video channels could have revenue and cost advantages over broadcasters with fewer. If this economy of scale exists, then broadcasters will have incentive to consolidate video channels. Consolidation could occur through broadcaster mergers and acquisitions, the formation of coalitions of broadcasters to jointly manage advertisements, or the emergence of separate advertising firms that control advertisements for multiple broadcasters. In this paper, we will refer to the "competitors" which manages advertisements, where a competitor could be a broadcaster, a coalition of broadcasters, or an ad manager. Consolidation among any of these types of competitors could seriously undermine competition in the TV advertising market, and some forms of consolidation could reduce diversity in the creation of local TV content, including local news. Results from this research could inform policy decisions regarding ownership limits and antitrust rules for next-generation TV. In this paper, we develop an analytical model to estimate revenues and costs of advertising on different devices, including both fixed and mobile TVs, in a market where all competitors use next-generation TV. We derive when a competitor should send targeted advertisements to each device based on that device's characteristics so as to maximize that competitor's profit. We consider a hypothetical market with a given population and a total number of video channels, and vary the number of competitors and hence the number of video channels with each competitor. Changing the number of competitors in the market could change the number of targeted advertisements that a profit-maximizing competitor would choose to distribute over the internet to OTA viewers, and the fraction of advertisements viewed on each device that is targeted rather than untargeted. If we find that the combined profit of all competitors in a market increases substantially as the number of channels per competitor increases, then there is an incentive to consolidate. Using our equations, we develop software to simulate profit-maximizing strategies for competitors with different numbers of TV video channels, different types of devices, and different type of broadband connection, and thereby estimate costs and revenues. For baseline assumptions, we assume that TV market penetration and viewing habits, broadband availability, transit costs on mobile and fixed networks, targeted and untargeted advertisement revenues, and the number of devices of all types per capita are equal to today's US national averages. Thus, our baseline numerical assumptions are drawn from Nielsen Reports, FCC reports, census data, and other sources. We then investigate whether an economy of scale would exist in other possible future scenarios, such as if there were a large increase in TV viewing on mobile devices, a large change in mobile broadband cost due to 5G, or a large change in revenue per view of targeted and untargeted advertisements.

Keywords: Next-Generation Television, Advanced Television Systems Committee, ATSC 3.0, broadcast television, targeted advertisement, ownership rules, antitrust rules, competition

Suggested Citation

Tyagi, Aman and Peha, Jon M., Analyzing Economies of Scale from Targeted Advertisements in Next-Generation TV (November 2018). TPRC 46: The 46th Research Conference on Communication, Information and Internet Policy 2018. Available at SSRN: or

Aman Tyagi (Contact Author)

Carnegie Mellon University, Department of Engineering and Public Policy, Students ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213
United States

Jon M. Peha

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
PlumX Metrics