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Mobile Empirical Analysis of investment income

Author: ZongWenPing
Tutor: LiNanCheng
School: Southwestern University of Finance and Economics
Course: Business Administration
Keywords: Mobile communication GSM Business strategy Econometrics
CLC: F626
Type: Master's thesis
Year: 2005
Downloads: 208
Quote: 2
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Abstract

Over last decade, with the monopoly being gradually broken and the competition being strengthened, our nation’s innovations of the telecommunication market have been reinforced, which result in a highly accelerated development of the telecommunication market. The telecommunication market has already become an important component of the national economy and a vital engine to power the high-speed augmentation of the national economy. Meanwhile, the existing problems of the telecommunication market are getting revealed: it is very hard to carry on the old growth pattern of so-called “high investment -high growth -high profit”following an expanding market scale with dropping growth rate; the operators profit less from the increment because of the keen market competition; the operators are taking huge risk in investing since the technology is rapidly developing with an indefinite direction and the facilities are updated so quickly. Thus, scientific investment and operative decision become key points on which the operators are focusing. Before investing in network construction, the telecommunication operators analyze the profits of their investment based on the running situation of the network and financial data, but generally, the analysis is just based on the present gross investment and the income. This static analytical method is unable to reflect the trend of the decrease of price and investment repayment, hence the investment return is overestimated and the investment risk is enlarged. The author thinks that it is obligatory to quantify the factors affecting the business income of telecommunication based on time series and find out the quantitative relation between the network size (investment) and the income, using the archive data of income and factors affecting income, and ultimately calculate the investment repayment. In a current telecommunication market with competition being more and more aggravated, the price competition becomes the main means of the telecommunication operator. Because of the property of "natural monopoly" of telecommunication network, augmentation of the quantity of customer by reduction of price can increase the profit of operator in a short time, but in the view of long-term effect, it will decrease the operator’s capacity of profiting, even let the operators down in a situation of loss. We think it needs to quantify the price impact on income and predict if the increases of earnings by decreased price can counteract the growth in consumed resources, if not, the operator will inevitably fall into the situation of loss in future. Following the qualitative analysis on the telecommunication market and mobile communication market of UNICOM in Chengdu, this study further analyzed its GSM business using the quantitative methods (GSM is one of the digital cell mobile communication systems, and GSM business refers to the various services of communication based on GSM system). After having qualitatively and quantitatively analyzed several important factors affecting the business earnings, we defined the quantitative relations among network size, network quality, price and the income, and thus calculated the repayment period of investment, which would provide the operators the qualitative and quantitative basis for determining the running strategies, such as: planning, construction, investment of network and price policy, etc. Through qualitative analysis of the market and business of mobile telecommunication in Chengdu UNICOM, this paper picked up price, traffic, network load as explanatory variable, basic conversation fee income as dependent variable, and adopted the monthly statistics data from January, 2003 to September, 2004, to build the multiple log-linear regression model. After implementing the stationary test and cointegrating test for these data , the author estimated the parameters of

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