A Study on the Industrial Organization of Telecommunications Industry based on the computer aided simulation model considering the substitution effect between telecommunications systems

本研究旨在从供给与需求两方面分析电信产业的整体特征。为此，我们构建了该行业的仿真模型。至于需求侧分析，我们检验了包含替代效应的需求模型，该模型已经用额外的数据开发出来。在这个分析中，我们试图检验假设，“无线寻呼服务通过它们之间的替代效应抑制了对移动电话服务的需求。”为了实现这一目标，我们建立了更通用的模型，其中包括移动电话、无线寻呼服务、小灵通和固定接入。因此，我们当然承认2^<和>代蜂窝电话与无线电寻呼之间的替代，但对于1^<和>st代蜂窝电话，我们看不到替代的迹象。因此，移动电话市场在早期受到抑制的原因并不是替代，而是影响。相反，这种现象可以用蜂窝电话服务本身的成本结构来解释，从无线电寻呼到2^<和>代蜂窝电话的转变可能会带来整个蜂窝电话市场的爆炸式扩张。从两个角度来看，这个结果很重要。首先，我们不能忽视供给侧（关税或价格水平），以解释和预测电信市场的动态以及需求侧。其次，建立包含双方的仿真模型，并分析其灵敏度，以增加估计的置信度。对于供给侧（成本结构），除了对参数成本函数进行统计估计外，我们还使用了数据包络分析（DEA）。虽然DEA通常用于衡量几家公司的技术效率低下，但我们可以证明该方法可以应用于成本分析，包括对某一行业自然垄断的检验（“用数据包络分析法衡量手机市场的自然垄断”）。然而，DEA的结果与统计估计的结果不同。在DEA文献中，经常会说DEA没有足够的方法来处理时间序列数据，这一点可能会影响到上述问题。为了改善这种情况，我们在Fare和Grosskopf（1996）和Sengupta（1995）的基础上开发了一种动态DEA方法。可以说，这些努力使建立电信行业I-O模拟器的基本框架成为可能，这是本研究的最终目标。少

This study aims to investigate the characteristics of the telecommunications industry as a whole from both sides of supply and demand analysis. For this purpose, we composed a simulation model of the this industry.As for the demand side analysis, we examined the demand model including substitution effects which was developed already with additional data. In this analysis, we tried to test the hypothesis, "The radio paging service suppress the demand for the cellular telephone service through the substitution effect between them." For this objective, we built the more general model which covers cellular telephone, the radio paging service, PHS, fixed access. As the result, we certainly admit the substitution between the 2^<nd> generation of cellular telephone and the radio paging, but as for the 1^<st>st generation of cellular telephone, we can not see the hint of substitution. Therefore, the reason why the cellular telephone market suppressed in early stage is not due to the substituti … More on effect. Rather, this phenomenon can be explained by the cost structure of cellular telephone service of 1^<st> generation itself, and the shift from radio paging to 2^<nd> generation cellular telephone might bring the explosive expansion of the whole cellular telephone market.This result is important from two points of view. The first, we can not neglect the supply side (tariff or price level) in order to explain and forecast the dynamics of telecommunications market as well as the demand side. The second, it is needed to build the simulation model including both side and analyze its sensitivity in order to add more confidence in estimation.As for the supply side (the cost structure), we use Data Envelopment Analysis (DEA) besides of estimating the parametric cost function statistically. Though DEA is often used to measure the technical inefficiency of several companies, we can show this method can be applied to the cost analysis including the test of natural monopoly of a certain industry ("The measurement of natural monopoly in cellular telephone market using Data Envelopment Analysis"). However, the results by DEA are different from those by statistical estimation. In DEA literatures, it is often said that DEA does not have sufficient way of treating time series data, and this point might affect the above mentioned problem. In order to improve this situation, we developed a dynamic DEA methodology based on Fare and Grosskopf(1996) and Sengupta(1995).It can be said that these efforts make possible to build a basic framework of the I-O simulator for telecommunication industry which is the final objectives of this study. Less