Analyzing the Business Strategies of Mobile Phone Operators Using Agent-Based Simulation

Analyzing the Business Strategies of Mobile Phone Operators Using Agent-Based Simulation

Biswas Subrata Kumar, Mina Ryoke
Copyright: © 2013 |Pages: 8
DOI: 10.4018/jkss.2013040106
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Mobile telephone service was first introduced to Japanese market in the mid-1980s and from then on, this area of business has shown a rapid growth of the number of the subscribers. However, recently, the mobile telephone market in Japan has become saturated. Most of the adult populations have at least one mobile phone set nowadays. Moreover, there are hardly any distinct differences in the quality of voice/packet services or, in the performance of the mobile phone sets of different operators. In this situation, mobile telephone operators are taking different approaches to attract new users as well as users from their competitors. However, as the industry is well saturated, it is difficult to predict the effect of these strategies of the companies in the market. This paper will propose a model that will help the market researchers to estimate the effects of any business strategy based on user mobility. The simulation result of this research will help the strategy makers of the field of mobile telecommunication to understand the current user sentiment and to predict the reaction of the users before any new service is introduced to the market. In this research, the Conjoint Analysis Method has been used to find the user utility function and the Agent Based Simulation (ABS) method has been used to simulate the movement of the market. The result can be used in the future and it will be possible to implement this same model with few adjustments to predict the user movement in other market conditions. .
Article Preview
Top

2. Methodology And Approach

This research is implemented in three steps. First of all, a user survey has been conducted to gather information of the mobile telephone users and their priorities. In the second step, using this raw information, a conjoint analysis (Orme, 2005) has been done to detect the utility function. This utility function has shown how the mobile telephone users react to the different choices. Lastly, simulation and modeling of user mobility has been done according to the user mobility function and the influence of other agents. The simulation model is shown in Figure 1.

Figure 1.

Basic structure of ABS model

jkss.2013040106.f01

To develop a proper evaluation model, it is important to find out the characteristics of the mobile phone users and the response of the users to the different strategies of the mobile telephone operators. In this research, to predict users response to these strategy choices, a user mobility function has been created based on the user choices. Company strategy decision and user response to the companys new strategies are closely related to each other, and this relationship has been expressed by mathematical functions to run an effective simulation process for evaluation. From these functions, it will be possible to estimate the changes of the total number of users (market share) after the strategy implementation of the mobile telephone companies.

Complete Article List

Search this Journal:
Reset
Volume 15: 1 Issue (2024)
Volume 14: 1 Issue (2023)
Volume 13: 4 Issues (2022): 2 Released, 2 Forthcoming
Volume 12: 4 Issues (2021)
Volume 11: 4 Issues (2020)
Volume 10: 4 Issues (2019)
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing