Managing TV commercials inventory in the Italian advertising market

Guerriero, Francesca; Miglionico, Giovanna; Olivito, Filomena

doi:10.1080/00207543.2016.1162919

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…Branch-and-bound techniques were applied to solve the problem using WINQSB software. Guerriero et al (2016) proposed a few formulations of the problem of accepting and scheduling commercials on TV. Among them, they added to the basic problem some constraints, such as avoiding product conflicts, assigning different lengths advertisements constraints, and specific breaks for commercials constraints.…”

Section: Maximising Tv-company Revenuementioning

confidence: 99%

“…This is only a weight characteristic and not one of effectiveness. GRP is calculated by summing up the ratings of all the advertisement airings during the entire advertising campaign (Lawrence, 1971, Araman and Popescu, 2010, Guerriero et al, 2016.…”

Section: Problem Definitionmentioning

confidence: 99%

“…The main goal of the TV networks management is to outline advertisement schedules, satisfying advertiser's constraints, while maximising TV revenues. The problem can be analysed from different perspectives, highlighting one or more features in accordance to which the decisions are taken (Guerriero et al, 2016). Potapov and Rzhanov (2015) discussed the problems of profitable media planning, claiming that qualitative media planning can save an average of 30% of an advertising budget.…”

Section: Introductionmentioning

confidence: 99%

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Scheduling TV advertisements via genetic algorithm

Czerniachowska

2019

EJIE

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Television advertising is vital to the television industry and is one of the most popular ways for advertisers to increase sales. This paper discusses the problem of scheduling TV advertisements according to each advertisers' need and budget limitations, with the objective of maximising total viewership. The proposed solution is the genetic algorithm, and its efficiency has been evaluated using list and random-list algorithms during long (one month) and short (one week) advertising campaign periods. Computational results show that this algorithm can obtain satisfactory results for real-world test problems, based on data from a marketing research company. [

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Section: Maximising Tv-company Revenuementioning

confidence: 99%

Section: Problem Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Scheduling TV advertisements via genetic algorithm

Czerniachowska

2019

EJIE

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“…A generalization of this work has been considered by Ghassemi‐Tari and Alaei (). Guerriero, Miglionico, and Olivito () consider the scheduling problem of an Italian television network where the network decides whether to accept the scheduling requests of clients with both rating points and budget requirements, and propose several heuristics to solve the resulting problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Managing Television Commercial Inventory under Competition: An Equilibrium Analysis

Geng

Mallik

2018

Decision Sciences

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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.

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“…In additions, the distributed model predictive control is also used to solve the optimal advertising strategy problem (Pourkargar et al, 2017a,b). For further discussion on various literature results, the reader may refer to the works of, for example, Hamilton (2009), Huang et al (2012), Chutani and Sethi (2012), García-Villoria and Salhi (2015), Lu et al (2016), Guerriero et al (2016), Schroeder and Tremblay (2016), Fang and Li (2015) and references therein.…”

Section: Introductionmentioning

confidence: 99%

Optimal impulsive control for advertising strategy problems based on a gradient-based PSO algorithm

Lin

Zhang

et al. 2018

Transactions of the Institute of Measurement and Control

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This paper considers an optimal advertising strategy problem. This is an important problem in marketing investment for new products in a free market. The main contributions of this paper are as follows. First, the problem is formulated as an optimal control problem of switched impulsive systems with the state inequality constraints, which is different from the existing nonlinear system models. As the complexity of such constraints and the switching instants are unknown, it is difficult to solve this problem by using conventional optimization techniques. To overcome this difficulty, by applying the penalty function, all the state inequality constraints are first written as non-differentiable penalty terms and imposed into the cost function. Then, the penalty terms are smoothed by using a novel smooth function, leading to a smooth optimal control problem with no state inequality constraints, and an improved gradient-based particle swarm optimization (PSO) algorithm is proposed for solving this problem. Error analysis results show that if the adjustable parameter is sufficiently small, the solution of the smooth optimal control problem is approximately equal to the original problem. Finally, a switched impulsive system for beer sales is established to illustrate the effectiveness of the developed algorithm.

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Managing TV commercials inventory in the Italian advertising market

Cited by 5 publications

References 11 publications

Scheduling TV advertisements via genetic algorithm

Scheduling TV advertisements via genetic algorithm

Managing Television Commercial Inventory under Competition: An Equilibrium Analysis

Optimal impulsive control for advertising strategy problems based on a gradient-based PSO algorithm

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