Modelling the Growth of Mobile Telephony Services in India

Abstract

Quick deployments, competition, advancement in technologies and reduced cost of access have propelled the growth of mobile services in India. Predicting growth of subscriber base is critical for service providers so that they can plan their network investments accordingly. Accurate forecast of subscriber base will also help policy makers and regulators to formulate appropriate policies and guidelines for sustainable growth of mobile services. It is the objective of the study to forecast better the penetration of mobile services. We demonstrate the use of internal influence based logistic model and constant rate exponential model for predicting growth of mobile services. We indicate that though these models forecast with reasonable amount of accuracy the early stages of mobile service diffusion in the country as we are currently witnessing, comprehensive models which take into consideration various external factors that affect growth of the sector need to be developed.

An econometric analysis of mobile services growth across regions of India

“…Specifically, the S-curve theories ignore such external factors as government policies, technological advancements, and service innovations. As in [18], previous studies have pointed out that the saturation limit depends on a number of factors including growth in disposable income of potential subscribers; price of services; competition in the market place; price and availability of alternative communication channels such as the Internet; and regulatory policies regarding spectrum allocation and interconnection. Even in recent studies [27], only the internal diffusion model is used to predict the mobile growth pattern without taking in to account any of the external factors.…”

“…where α is the speed of adjustment as illustrated in [18]. For this curve, the maximum growth rate occurs at 37% of the saturation limit N * i,t [16].…”

Analysis of Inter-Regional Mobile Services Growth in India

“…Specifically, the S-curve theories ignore such external factors as government policies, technological advancements, and service innovations. As in [18], previous studies have pointed out that the saturation limit depends on a number of factors including growth in disposable income of potential subscribers, price of services, competition in the market place, price and availability of alternative communication channels, such as the Internet and regulatory policies regarding spectrum allocation and interconnection. In [10], income and price were incorporated in a diffusion process framework to model growth of mobile telecom in the crosscountry study.…”

“…In [10], income and price were incorporated in a diffusion process framework to model growth of mobile telecom in the crosscountry study. In [11], a comprehensive model is built taking to account as many as 18 As more and more subscribe to mobile services, the utility of the system increases which results in marginal number of non-users subscribing to the system. This induces further growth and so on.…”

“…Hence the variation of price across regions is expected to be minimal. (1) where a is the speed of adjustment as illustrated in [18]. Equation (1) describes the internal influence model as illustrated in [16].…”