Leeflang P., Wieringa J.E., Bijmolt T.H.A., Pauwels K.H. (Eds.) Advanced Methods for Modeling Market

Springer International Publishing AG, 2017. — 725 p. — (International Series in Quantitative Marketing) — ISBN: 331953467X.This volume presents advanced techniques to modeling markets, with a wide spectrum of topics, including advanced individual demand models, time series analysis, state space models, spatial models, structural models, mediation, models that specify competition and diffusion models.
It is intended as a follow-on and companion to Modeling Markets (2015), in which the authors presented the basics of modeling markets along the classical steps of the model building process: specification, data collection, estimation, validation and implementation. This volume builds on the concepts presented in Modeling Markets with an emphasis on advanced methods that are used to specify, estimate and validate marketing models, including structural equation models, partial least squares, mixture models, and hidden Markov models, as well as generalized methods of moments, Bayesian analysis, non/semi-parametric estimation and endogeneity issues. Specific attention is given to big data.
The market environment is changing rapidly and constantly. Models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performance. In today's environment of information overload, the challenge is to make sense of the data that is being provided globally, in real time, from thousands of sources. Although marketing models are now widely accepted, the quality of the marketing decisions is critically dependent upon the quality of the models on which those decisions are based.Advanced Methods for Modeling Markets (AMMM)
Advanced Individual Demand Models
Traditional Time-Series Models
Modern (Multiple) Time Series Models: The Dynamic System
State Space Models
Spatial Models
Structural Models
Mediation Analysis: Inferring Causal Processes in Marketing from Experiments
Modeling Competitive Responsiveness and Game Theoretic Models
Diffusion and Adoption Models
Structural Equation Modeling
Partial Least Squares Path Modeling
Mixture Models
Hidden Markov Models in Marketing
Generalized Method of Moments
Bayesian Analysis
Non- and Semiparametric Regression Models
Addressing Endogeneity in Marketing Models
Machine Learning and Big Data
The Future of Marketing Modeling