Quantitative models in marketing research / Philip Hans Franses and Richard Paap.

Format:

Book

Author/Creator:

Franses, Philip Hans, 1963- author.

Paap, Richard, author.

Language:

English

Subjects (All):

Marketing research--Mathematical models.

Marketing research.

Physical Description:

1 online resource (xiii, 206 pages) : digital, PDF file(s).

Edition:

1st ed.

Place of Publication:

Cambridge : Cambridge University Press, 2001.

Language Note:

English

Summary:

Advances in data collection and data storage techniques have enabled marketing researchers to study the individual characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics. This 2001 book presents important and practically relevant quantitative models for marketing research. Each model is presented in detail with a self-contained discussion, which includes: a demonstration of the mechanics of the model, empirical analysis, real world examples, and interpretation of results and findings. The reader of the book will learn how to apply the techniques, as well as understand the methodological developments in the academic literature. Pathways are offered in the book for students and practitioners with differing numerical skill levels; a basic knowledge of elementary numerical techniques is assumed.

Contents:

On marketing research

Data

Models

Features of marketing research data

Quantitative models

Marketing performance measures

A continuous variable

A binomial variable

An unordered multinomial variable

An ordered multinomial variable

A limited continuous variable

A duration variable

A continuous dependent variable

The standard Linear Regression model

Estimation

Estimation by Ordinary Least Squares

Estimation by Maximum Likelihood

Diagnostics, model selection and forecasting

Diagnostics

Model selection

Forecasting

Modeling sales

Advanced topics

A binomial dependent variable

Representation and interpretation

Modeling a binomial dependent variable

The Logit and Probit models

Model interpretation

The Logit model

The Probit model

Visualizing estimation results

Modeling the choice between two brands

Modeling unobserved heterogeneity

Modeling dynamics

Sample selection issues

An unordered multinomial dependent variable

The Multinomial and Conditional Logit models

The Multinomial Probit model

The Nested Logit model

Forecasting.

Notes:

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Includes bibliographical references (p. 196-201) and index.

ISBN:

1-107-12279-1

0-521-14365-9

0-511-11936-4

0-511-15345-7

0-511-30344-0

1-280-15484-5

0-511-04764-9

0-511-75379-9

OCLC:

437073140