RT Journal Article T1 Assessing the effect of advertising expenditures upon sales: A Bayesian structural time series model. A1 Gallego, Víctor A1 Suarez García, Pablo A1 Angulo, Pablo A1 Gómez-Ullate Otaiza, David AB We propose a robust implementation of the Nerlove-Arrow model using a Bayesian structural time series model to explain the relationship between advertising expenditures of a countrywide fast-food franchise network with its weekly sales. Due to the flexibility and modularity of the model, it is well suited to generalization to other markets or situations. Its Bayesian nature facilitates incorporating a priori information reflecting the manager's views, which can be updated with relevant data. This aspect of the model will be used to support the decision of the manager on the budget scheduling of the advertising firm across time and channels. PB Wiley SN 1524-1904 YR 2019 FD 2019-05 LK https://hdl.handle.net/20.500.14352/13555 UL https://hdl.handle.net/20.500.14352/13555 LA eng NO © 2019 Wiley. Número especial.Workshop on Games and Decisions in Reliability and Risk (GDRR)(5. 2017. Madrid,España).The authors acknowledge financial support from the Spanish Ministry of Economy and Competitiveness, through the "Severo Ochoa Programme for Centres of Excellence in R&D", Grant/Award Number: SEV-2015-0554; Spanish Ministry of Education, Grant/Award Number: FPU16/05034; Spanish MINECO-FEDER, Grant/Award Number: MTM2015-65888-C4-3 and MTM2015-72907-EXP. NO Ministerio de Economía y Competitividad (MINECO)/FEDER NO Centro de Excelencia Severo Ochoa NO Ministerio de Ciencia, Innovación y Universidades (MICINN) DS Docta Complutense RD 5 abr 2025