Smartphone development has opened the door to many future business opportunities. Many smartphone manufacturers in Taiwan have received orders from large international companies (mainly as OEMs or ODMs), while only few manufacturers have developed their own brands. If the authors can provide these enterprises with an effective decision-making strategy, they will be able to make the best decisions in time. The purpose of this paper is to take critical success factors (CSFs) and the existing internal capabilities of an enterprise in an external environment into account to build an operational model guide that enterprise in its decision making process. This study combined the Delphi method and the analytic network process (ANP) model to construct a decision model, calculate the weighting of every criterion and sub-criterion, and determine the optimal decision-making strategy in the smartphone industry. Then, the authors chose the HTC Corporation as a case study. The results showed that the development trend of the smartphone industry was the integration of mobile phones. The strategy of excellent functions strategy is the optimal strategy for the implementation of the alternatives.

Here, we numerically investigate the lowest stability and bifurcation boundary of supercritical Taylor vortices in flows with different wavenumbers and for various radius ratios; the radius ratios range from those corresponding to axisymmetrical Taylor vortex flow (TVF) to those corresponding to wavy vortex flow (WVF). The variation in the wavenumber of a supercritical TVF is found to affect the stability of the flow, because the wavenumber of the Taylor vortices remains constant only when the flow is quasi-static. The variation in the wavenumber is examined and found to be significant when the radius ratio is less than 0.7842. The results for TVF are compared with those for the flow during the quasi-static transition from TVF to WVF.

The purpose of this research is to predict the total market demand of photovoltaic (PV) system of the world. By using the Grey forecasting model, the results were precise and valid. Then, the sensitivity analysis was conducted to select the most appropriate horizontal adjusting factor (HAF) and to determine the growth type of PV industry. The result showed the HAF was 0.4, which indicated the growth speed is in a low speed but very close to normal speed. The average residual error was 10.5% from 1995 to 2007 compared to the actual value in the same period. Then, the forecasted value from 2008 to 2011 showed an increasing shape and would reach 8554.9 MW in 2011. This research found the growth type of PV industry of the world, offering meaningful information for firms to decide the strategy in the future. For government, the result could also help to implement adequate policies to support the development of PV industry in the future.