84611 - MODELLI STATISTICI PER L'ANALISI DI MERCATO

Academic Year 2024/2025

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Statistics, Economics and Business (cod. 8876)

Learning outcomes

At the end of the course, students known and will be able to implement statistical tools useful for market research and intelligence. In particular students will be able to: design and realize a statistical survey concerning consumer's preferences on alternatives brands; estimate, evaluate and interpretate the results of the utilizations of discrete choice models and of market response models.

Course contents

Part One - Brand Choice Models

Random Utility Models

Multinomial Logit Model

IIA assumption

Nested Logit Models

Probit Model

Case Studies

Part Two - Flexible Segmentation

Conjoint Analysis

Market Share Simulation

Part Three - Market Response Models

Analysis of Advertising's Recall

Sales Response Models

Market Share Response Models

SUR Method

Dynamic Response Models

Case Studies

Part Four: Customer Satisfaction Measurement and Analysis

SEM Models

case Sudies

Readings/Bibliography

Part One

Franses, P.H., Paap, R. (2001), Quantitative modeling in marketing research, Cambridge University Press.

Part Two

Brasini, S., Freo, M., Tassinari, F., Tassinari, G. (1999), Marketing e pubblicità, Il Mulino, Cap. 6.

Part Three

Brasini, S., Freo, M., Tassinari, F., Tassinari, G. (1999), Marketing e pubblicità, Il Mulino, Capp. 7-8

Hanssens, D.M., Parsons, L., Schultz, R.L. (2002), Market response models: econometric and time series analysis, Kluwer.

Parte Four

Lecture notes on the teacher's website

Teaching methods

Aiming to develop a teaching method more interactive as possible, the class work will be made by frontal lectures, case studies and group work.

It is compulsory that students have attended the module 1 and 2 of formation to security on work places, in e-learning mode.

Assessment methods

Exam is written and is formed by three questions, two of theoretical kind and one of interpretations of the results of the applications of ine of the statistical methods object of the course. Student can substitute the "interpretative" answer with a group work to present during classes (this work weights one third of the exam).

Teaching tools

Files with the slides of the lectures on teacher's website.

Data set and research papers on the teaches's web site.

Case studies on the teacher website

Office hours

See the website of Giorgio Tassinari

SDGs

Quality education Industry, innovation and infrastructure

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.