A hybrid Bass–Markov model for the diffusion of a dual-type device-based telecommunication service: The case of WiBro service in Korea. (January 2015)

• Record Type: Journal Article
• Authors: Song, Youngkeun; Lee, Sungjoo; Zo, Hangjung; Lee, Hakyeon
• Is Part Of: Computers & industrial engineering. Volume 79(2015)
• Page Start: 85
• Page End: 94
• Publication Date: 2015-01
• Subjects: Diffusion of innovation -- Growth model -- Bass model -- Markov model -- Dual-type device; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2014.10.020
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A hybrid model is developed for the diffusion of a dual-type device-based service. The Bass model is employed for modeling the diffusion through Type 1 device. The Markov transition model is used to capture the diffusion through Type 2 device. The hybrid Bass–Markov model is then developed to produce the aggregate demand. The case of wireless broadband (WiBro) service in Korea is presented. Abstract: Because the increasing complexity of technology embedded in telecommunication services enables services to be provided via various mediums, the vital requisite for forecasting the diffusion of such services is to simultaneously capture different diffusion phenomena for different devices. This paper proposes a new diffusion model for a dual-type device-based service called the hybrid Bass–Markov model. The proposed model is targeted at the service environment where one type of device is new to the market, and the other type has existing competing services. The Bass model is selected to model service diffusion through the former type of device, while the Markov transition model is employed to capture the diffusion through the latter type of device. The hybrid Bass–Markov model is then developed to produce the aggregate demand. The case of the wireless broadband (WiBro) service in Korea is presented to illustrate the proposed model with a policy sensitivity analysis. This research is expected to be the basis of multi-type device-based service forecasting and, ultimately, will help researchers conduct demand forecasting of services offered by several different devices.