Estimating the Ranking Download Need and Predicting its Trend Based on Pareto Distribution and Grey Prediction Model-the Case of the App Store in China

• Main Authors: En-Cih Jhu, 朱恩賜
• Other Authors: Zi-Ping Chiang
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/20474976247315072980

碩士 === 康寧大學 === 運籌與科技管理研究所 === 100 === The coming of digital era changes how people use mobile phones, and along with maturity on the wireless communication technologies as well as increase of equipments, the telecommunication companies can offer consumers with more diverse mobile value-added services. In other words, this means that along with the constantly increasing on the smart phone market, the volume by which people use smart phone on the employment of multi-media activities is greatly increased to nearly two folds while comparing it with the figure in the same period last year. Moreover, it also indicates that there is also gradual emergence on both mobile internet and application software; however, for both mobile phone application software developers and suppliers, the most key information is the demand data in the market. While at the present time what we are able to get is only limited message on App store ranking list, as a result, if we are able to make market downloading volume demand analysis and trend forecast on the basis of public data, they will become convenient and immediate analytical combination tool when setting up market goals and management strategies for both mobile software developers and suppliers. Thus, hopefully through statistics of ranking data from App Store in China areas in the paper, by way of Pareto Distribution Model, to make estimation on both downloading demands as well as downloading demand sequence on categorization of application software from ranking list in China areas, to then make inspection by combining with Rolling Grey Model, in order to find out input data set as applicable to application software industry in China areas, as well as to make forecast on downloading demands and application software downloading volume demand sequence. Moreover, with our expectation to set up an analytical combination tool on both market demands and trend forecasts for both software developers and suppliers, the research results are shown that for the application software markets in China areas, people are with higher acceptance on application software products with high unit pricing than those in America areas and there are still a large room for growth. Furthermore, by transferring the position of ranking list into downloading demand, it actually can make more elaborate order sequence on the downloading volume demand according to different categories of application software; however, there is a larger fluctuations on the historical trend of application software markets in China areas with Grey Prediction Model, as a result, to make recommendation only by using many sets of data as input, to then work on forecast for better forecasting accuracy.