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28208 - Marketing Models

Academic Year 2018/2019

                
                        Docente:
                        Elisa Montaguti
                    
                        Credits:
                        10
                    
                        SSD:
                        SECS-P/08
                    
                        Language:
                        Italian
                    
                        Moduli:
                        
                            Elisa Montaguti
                            (Modulo 1)
                        
                            Sara Valentini
                            (Modulo 2)
                        
                        Teaching Mode:
                        
                                    Traditional lectures (Modulo 1)
                                
                                    Traditional lectures (Modulo 2)
                                
                            Campus:
                            Bologna
                        
                            Corso:
                            Second cycle degree programme (LM) in
                            Statistics, Economics and Business (cod. 8876)

                            Teaching resources on Virtuale

Learning outcomes

At the end of the course students will be able to analyze consumer behavior while using both individual and aggregate data. More specifically students will be able to specify and estimate marketing models aiming at supporting decision making for targeting, marketing mix activities and planning.

Course contents

This course will cover important marketing phenomena such as:

-targeting

-market/consumer response to sales promotions

-market/consumer response to communications

-brand and product category choice

while analyzing data collected both at the individual and aggregate (e.g. market) level.

To do so, we will use, among others, the following statistical methods:

-multiple regression

-logistic regression

-multinomial and conditional logit

-nested models.

Readings/Bibliography

Teacher's notes
Blattberg R.C, B. Kim e S.A. Neslin “Database Marketing,” Springer 2008 pp 105-117; pp-245-287
Peter S. Fader e Bruce S. Hardie (2012) “Reconcyling and Clarifying CLV Formulas” pp-1-9.
Peter S.H. Leefl ang Jaap E. Wieringa Tammo H.A. Bijmolt Koen H. Pauwel “Modeling Markets,”. Capitoli "Model Specification" and “Data”, pp-65-92.
Scott A. Neslin and Harald J. van Heerde (2009), "Promotion Dynamics", Foundations and Trends® in Marketing: Vol. 3: No. 4, pp 178-199; 214-224.
Lattin, James, Douglas Carroll and Paul Green “Analyzing Multivariate Data” Capitolo 13.
S Chib, PB Seetharaman, A Strijnev(2004) “Model of brand choice with a no-purchase option calibrated to scanner-panel data”, Journal of Marketing Research, (41), May, 184-196.
Chintagunta, Pradeep K.; Jain, Dipak C.; Vilcassim, Naufel J (1991) “Investigating Heterogeneity in Brand Preferences in Logit Models for Panel Data” Journal of Marketing Research (JMR) . Nov91, Vol. 28 Issue 4, p417-428

Teaching methods

The course involves both lectures and weekly lab sessions

During the lab several software will be used including: Excel, SAS, STATA and R

Assessment methods

The course assessment is based on a written exam.

Students will have the opportunity to carry out non mandatory assignments that can contribute to the final assessment for no more that 10%.

Office hours

See the website of Elisa Montaguti

See the website of Sara Valentini