تکامل شبکه تلفن همراه به سوی IMT-2000 در کره: تجزیه و تحلیل های اقتصادی

This paper develops a techno-economic model for evaluating mobile network evolution strategies and demonstrates its real-world applicability, using a Korean case study. A number of mobile network evolution strategies toward IMT-2000 are generated and evaluated with this model. The overall market performance is evaluated and its sensitivity to the key strategic variables such as technology choice, time to market and service coverage is analyzed. Given the regulatory condition that W-CDMA network should be deployed no later than 2004, it is found that direct evolution from cdma2000 1x to W-CDMA is more profitable than evolving via 1xEV-DO. Also, direct evolution from cdma2000 1x to 1xEV-DV appears to be a comparable choice, but with a higher supplier market risk. Finally, strategic implications of the empirical findings obtained in this study are discussed along with some further research issues.

Worldwide mobile telecommunications markets are so drastically changeable that predicting what will emerge in even three or four years is not an easy task. Following the second-generation (2G) mobile technologies, many interim solutions have been offered in the market and considered as an effective bridge to the third-generation (3G) broadband mobile technologies such as W-CDMA and cdma2000 3x. Typical examples are GPRS and EDGE in the GSM world and cdma2000 1x, 1xEV-DO and 1xEV-DV in the CDMA world. As new technologies are introduced and deployed in telecommunications markets, a number of questions arise about the optimal technology deployment strategy and the most effective network evolution path to ensure future profitability. Technology choice, deployment timing and coverage expansion plan are critical to a company's future profitability. As one of the leading CDMA markets in the world, the Korean market is now eager to find out what target and which evolution path toward that target are most profitable, with consideration of the market risk and the technological risk involved in each network evolution scenario. The purpose of this paper is to demonstrate how this strategic decision problem can be effectively dealt with by using a carefully designed techno-economic model. Following this introductory section, Section 2 briefly reviews the status of the Korean mobile telecom market and explains the background to the problem. Section 3 shows the structure of the techno-economic model along with some underlying key assumptions. Section 4 describes the key model components and formulas. Section 5 evaluates typical network evolution scenarios in the Korean mobile telecom market and discusses the strategic implications of the results. Finally, some promising future research topics are discussed in Section 6 with concluding remarks.

Market risk is closely related to market dynamics, market demand uncertainties, and existence of multiple interim technological solutions. The higher the market risk, the higher the delicacy and complexity of the Korean mobile operator’s decision-making. That is the reason why it is hard to assess the impact of a specific strategic decision for future profitability. The primary challenge is to assess and determine when to deploy a specific network and what strategy to implement, given market situations. In order to answer these questions, we need to use an accurate assessment tool like the techno-economic model developed in this paper. The usefulness and applicability of the model have been demonstrated by using a Korean case study. The analysis shows that direct evolution from cdma2000 1x to W-CDMA is more profitable than that via 1xEV-DO given the condition that the W-CDMA network should be installed before 2004 to meet the regulatory requirements. Also, the direct evolution from 1x to 1xEV-DV is comparable once the standard becomes available commercially within the time schedule specified in our scenario analysis. Compared to the conservative coverage expansion, the aggressive expansion appeared to contribute to a revenue increase, but with a higher risk. The techno-economic analysis performed in this paper is generic in the sense that it provides us with a generic approach to justify an investment or to choose a best option among consecutive upgrade investment options. The real-option concept has been adopted in the investment analysis models as in Benaroch (2001). If we develop our model further to incorporate the real-option concept more explicitly, it can be used in a more general context. The techno-economic model developed in this paper has many merits, especially in its modeling accuracy and practicality. But it has some limitations too. First, it assumes that the number of BTSs and their geographic distribution are given and fixed. This means that the model is not a green-field model. Some revisions, especially in the multi-service network dimensioning module, should be made before it can be applied to a green-field situation. Second, it is basically a single service provider model. Hence, it is somewhat limited for reflecting market competition effects in a dynamically changing market situation. In order to incorporate the competition effect into the model, we need to enhance it further to be a dynamic market game model. All of these tasks remain to be done in the future.