A Choice-Based Multi-Brand Diffusion Model Incorporating Replacement Demand

52 Pages Posted: 30 May 2008

See all articles by Duk Bin Jun

Duk Bin Jun

College of Business, Korea Advanced Institute of Science and Technology (KAIST)

Jungil Kim

Korea Advanced Institute of Science and Technology (KAIST)

Date Written: May 2008

Abstract

This paper proposes a brand-level forecasting model that incorporates both first purchase diffusion and the replacement component in sales. The model consists of a two-stage procedure in which customers are presented with purchase occasions according to a diffusion process or replacement process, and at each occasion, they make the decision to purchase and choose a brand according to a choice model. By incorporating marketing mix variables in the choice model, the model can identify the impact of competitive marketing mix activities on customers' purchase incidence decisions and brand choice decisions. This approach enables us to understand the overall process of customers' buying behavior and to identify sales to first-time buyers, brand loyal customers, and brand switching customers separately from the total sales amount. With this model, companies can develop their production and marketing plans based on a richer understanding of customers' behavior and select the target customer group based on their customer mix information. Our application of the proposed model to the Korean mobile terminal market showed reasonable fit and forecasting performance.

Keywords: Brand switching, Customer choice model, Long term forecasting, Replacement purchases

Suggested Citation

Jun, Duk Bin and Kim, Jungil, A Choice-Based Multi-Brand Diffusion Model Incorporating Replacement Demand (May 2008). KAIST College of Business Working Paper Series No. 2008-008, Available at SSRN: https://ssrn.com/abstract=1137537 or http://dx.doi.org/10.2139/ssrn.1137537

Duk Bin Jun (Contact Author)

College of Business, Korea Advanced Institute of Science and Technology (KAIST) ( email )

85 Hoegiro, Dongdaemoon-gu
Seoul 02455
Korea, Republic of (South Korea)

Jungil Kim

Korea Advanced Institute of Science and Technology (KAIST) ( email )

373-1 Kusong-dong
Yuson-gu
Taejon 305-701, 130-722
Korea, Republic of (South Korea)