Managing Television Commercial Inventory under Competition: An Equilibrium Analysis

Abstract

We develop a game theoretic model for managing prime time on-air ad inventory in the television industry. The ad inventory in this industry is priced based on rating points or the number of viewers that watch a commercial. The rating points are sold through two distinct processes: the upfront, which occurs before the broadcast season, and the scatter, which occurs throughout during the broadcast season. Television networks need to allocate their total rating points inventory to these two markets before knowing either the performance rating of their shows or the scatter market price, both of which are ex ante uncertain. The television networks offer performance guarantees on the inventory that is sold in the upfront market while such guarantees are not offered in the scatter market. We consider the inventory competition between two television networks under such a setting. To the best of our knowledge, ours is the first article to consider competition in media revenue management. We establish the existence of unique Nash equilibrium under quantity competition and describe the sensitivity of the equilibrium outcome with respect to various problem parameters. We show that choosing quantity over price during the upfront is a dominant strategy for a television network. We compare our competitive model with a centralized system and discuss the managerial implications for our work.

Allocating revenues in a Smart TV ecosystem

“…For the reasons given above among others, there is great interest for many types of problems arising in networks, in particular in wireless communications and/or its integration with the Internet, in the Operations Research community (for recent references on the topic, see, e.g., Ribeiro et al., ; Risso et al., ; Morais and Mateus, ; Pagès‐Bernaus et al., ; Ye et al., ). Likewise, game theory has proved to be an interesting tool with which to analyze different problems, such as allocation/sharing problems (see, e.g., Petrosjan and Zaccour, ; Moretti and Patrone, ; Nagarajan and Sošić., ; Ackermann et al., ; Guajardo and Rönnqvist, ; Gutiérrez et al., ) or cooperation (see, e.g., Ahmadi‐Javid and Hoseinpour, ; Basso et al., ; Quintero‐Araujo et al., ), from many different areas of knowledge, in particular in communication network problems (see, e.g., Acemoglu and Ozdaglar, ; Gozalvez et al., ; Zhu and Başar, ; Bahbouni and Moussa, ; Goyal and Kaushal, ; van Hove, ; Taleizadeh et al., ; Wang et al., ; Colajanni et al., ; Geng and Mallik, ; Zeng et al., ). Furthermore, game theory has been also utilized to analyze engineering problems in the broadest sense (Sanchez‐Soriano, ).…”