Title: Stochastic goal programming model and satisfaction functions for media selection and planning problem
Authors: Belaïd Aouni; Cinzia Colapinto; Davide La Torre
Addresses: Decision Aid Research Group, Laurentian University, Ontario, P3E 2C6, Canada. ' Department of Management, Ca' Foscari University of Venice, Cannaregio 873-30121, Venice, Italy. ' Department of Economics, Management and Quantitative Methods, University of Milan, 7-20122, Milan, Italy
Abstract: In the knowledge society characterised by audience fragmentation and new media consumption, the success of a media campaign relies more on the effectiveness of the chosen media to achieve the desired aspiration levels. A media planner has limited financial resources and aims to get the best return on investment in terms of attention and engagement with potential customers, and at the same time to minimise total costs of advertising and communication. These objectives are conflicting, commensurable and their evaluations are generally stochastic. In this paper, we present a stochastic multi-objective approach for media planning decision-making and we propose two different goal programming formulations with satisfaction function based on scenario forecasting and deterministic equivalent. The proposed models will be illustrated through a numerical simulation based on data from the Italian market.
Keywords: media selection; media planning; stochastic programming; multiobjective programming; goal programming; preference modelling; satisfaction function; media campaigns; multicriteria decision making; MCDM; scenario forecasting; deterministic equivalents; numerical simulation; Italy; advertising; communication.
International Journal of Multicriteria Decision Making, 2012 Vol.2 No.4, pp.391 - 407
Published online: 30 Aug 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article