The purpose of this paper is to build a comprehensive indicator of Information Communication Technology (ICT). We first develop an ICT indicator for Taiwan high-technology industries. We then extend the Bresnahan, Brynjolffson and Hitt (2000) model to measure the impact of ICTs on economic performance and organization structure. In this paper, a new measure of ICTs provides a more complete picture of ICT activity in Taiwan high-technology industry.

The purpose of this study is to investigate the relationship between knowledge capital (including research & development (R&D), Automation capital stock (AICT), Electronic system (EICT)) diffusion and productivity. We used translog production function to estimate for all six Taiwan high-technology industries. And we also construct the diversification (DIV) and vertical indicator (VIC) to analysis the relationship with organization using the AICT and EICT.

In markets with cyclical fluctuations, firms may have different dynamic decision rules facing upturns and downturns of industry cycles. This paper extends the dynamic factor demand model to consider industry cycles. Because investment behavior could be endogenous uncertainty involved on industry dynamics, the current industry dynamic models with state-of-the-art would not appropriately interpret industry dynamics. In order to solve the uncertain problem, we utilize the idea of transfer probability in Markov switching model to catch the industry cyclical behavior. Explicitly incorporating the Markov regime switching mechanism based on Nelson and Kim (2000), this paper measures the firm¡¦s dynamic adjustments when facing upturns and downturns of industry cycles. The empirical work is based on firm level data of Taiwan high-technology industries. The empirical results show that the expansionary strategy in labor and capital usage may not have positive impacts on output when considering uncertainty that may be casued by business cycles. To have correct prediction in cyclical fluctuation becomes important task for high-technology firms. However, the positive contribution of exogenous technology to output growth is so significant. This proves why every industry tries to impel technology in recent years. The industry dynamic model integrated with cyclical fluctuation and demand uncertainty allows us to examine how sharp changes in financial factors might affect investment behavior, technological nature and adjustment effects for industries in facing demand and investment shocks.