Using group method of data handling to model customer choice behaviour

被引：0

作者：

Zhu, B. ^{[1
]}

He, C. H. ^{[1
]}

Niu, Y. ^{[1
]}

机构：

[1] Sichuan Univ, Sch Business, Chengdu 610065, Peoples R China

来源：

SCIENTIA IRANICA | 2014年 / 21卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Choice modelling; Group Method of Data Handling (GMDH); Artificial Neural; Network (ANN); Long-distance communication mode; NEURAL-NETWORK; DESIGN;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Choice modelling is valuable for understanding and predicting customer behaviour. This study introduces the Group Method of Data Handling (GMDH) into choice modelling and applies this new technique to model consumer choice in the long-distance communication market. When we compare the GMDH with the Artificial Neural Network (ANN) and logit models, the results show that the new model provides better predictions of customer choice than the ANN and logit models. In addition, the new model can identify the important explanatory variables that affect customer choice, and reveal how the variables affect this choice, which cannot be directly accomplished using the ANN model. This advantage will help firms to better analyse the behaviour of their customers and, thereby, develop suitable marketing strategies. (C) 2014 Sharif University of Technology. All rights reserved.

引用

页码：1051 / 1060

页数：10

共 29 条

[1] A nonparametric method of estimating the demand for mobile telephone networks - An application to the Korean mobile telephone market [J].

Ahn, H .

INFORMATION ECONOMICS AND POLICY, 2001, 13 (01) :95-106

[2] Recovering and profiling the true segmentation structure in markets: an empirical investigation [J].

Andrews, RL ;

Currim, IS .

INTERNATIONAL JOURNAL OF RESEARCH IN MARKETING, 2003, 20 (02) :177-192

[3] An empirical comparison of logit choice models with discrete versus continuous representations of heterogeneity [J].

Andrews, RL ;

Ainslie, A ;

Currim, IS .

JOURNAL OF MARKETING RESEARCH, 2002, 39 (04) :479-487

[4]

[Anonymous], 2001, Quantitative Models in Marketing Research

[5]

Barron A.R., 1988, 20TH INTERFACE 88 S, P192

[6] An Empirical Investigation of the Dynamic Effect of Marlboro's Permanent Pricing Shift [J].

Chen, Tao ;

Sun, Baohong ;

Singh, Vishal .

MARKETING SCIENCE, 2009, 28 (04) :740-758

[7] Measuring the effects of new brand introduction on inter-brand strategic interaction [J].

Chintagunta, PK .

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1999, 118 (02) :315-331

[8] COMPARING THE PREDICTIVE PERFORMANCE OF A NEURAL-NETWORK MODEL WITH SOME TRADITIONAL MARKET RESPONSE MODELS [J].

DASGUPTA, CG ;

DISPENSA, GS ;

GHOSE, S .

INTERNATIONAL JOURNAL OF FORECASTING, 1994, 10 (02) :235-244

[9]

Elder JF, 2000, NETWORK MODELS FOR CONTROL AND PROCESSING, P143

[10] An introduction to ROC analysis [J].

Fawcett, Tom .

PATTERN RECOGNITION LETTERS, 2006, 27 (08) :861-874

← 1 2 3 →