Since the mid-20th century, Information technology-based Third Wave has been sweeping the world. Among new technologies, we are going to focus on emerging technology (ET), which has a characteristic of "creative destruction", and can create a new industry, change an existing industry or regional economic structure.Because China has unique socio-cultural and Chinese market has a larger scale and extraordinary network effect than those of other countries, ET is of special strategic significance for Chinese enterprises. Once a large number of people adopt emerging technology products (ETPs) in China, then a large-scale, lucrative emerging market will be formed in a short period of time. So, a study on ETP diffusion and the characteristics of emerging technology firms (ETFs) is of great significance.This research begins with a systematic review of literatures on new products diffusion. After analyzing characteristics of ETP diffusion, the market characteristics of ETF in China is summed up as follows:Technological improved ETP market shows an agglomerate growth with lagging profit; Technological breakthrough ETP market shows an explosive growth with lagging profit; Precocious ETP market withers away after a short hot pursuit of consumers. The keywords of market characteristics of ETP are critical sales and clustering growth (an agglomerate growth or explosive growth for different modes and/or different speeds of ETP diffusion). All those must be demonstrated with the dynamic changes of adopters spatial distribution. Due to the high uncertainty of ETP marketing, the traditional forecasting methods can not be applied to measure ETP marketing effectively. An effective tool, cellular automata model embedded small-world network and cross-entropy (CASWN-CE) method, has been found in this paper to measure the differences of adopters spatial distribution. Empirical research through analyzing and simulating the MP4 diffusion in Wuhan MP4 market shows that CASWN-CE is an effective method to measure ETP marketing and predict the success probabilities of ETPs in the regional market. Accordingly, a more accurate expected cash flow of ETP and the option value of ETP project can be calculated.After the success of an ETP, the value of this ETF will increased rapidly. A semi-parametric model combined with GMDH is build to estimate the value of ETFs in this paper, empirical research discovers the validity of this model and explains some "abnormalities". These "abnormalities" is as follows:investors concern the quality of whole asset of an ETF more than each share, the utilization of real assets and inventory of an ETF more than liquidity of its liquid assets, and the value of an ETF is negative correlation with its size.Finally, the characteristic function and feature model of ETFs are established in this paper. The industry characteristic of ETFs is clusters of SME engaged in innovative products or services of high-tech, at least one aspect of information technology, nanotechnology, bioengineering techniques; The technical characteristic of ETFs is a discrete technological innovation with the sequential multi-stage options, high uncertainty and its significant marginal effect and breaking power of performance; The market characteristic of ETFs is lagging-profited clustering growth under the constraint of critical sales. A three-dimensional feature model of ETFs can be used for analyzing and evaluating the growing stage and feature of an ETF. The characteristic function and feature model is provided here as a new tool for the management and strategy of ETF and venture capital policy, It has a guiding role. |