Estimating the Impacts of Climate Change on Mortality in OECD Countries

The major contribution of this study is to combines both climatic and macroeconomic factors simultaneously in the estimation of mortality using the capital city of 22 OECD countries from the period 1990 to 2008. The empirical results provide strong evidences that higher income and a lower unemployment rate could reduce mortality rates, while the increases in precipitation and temperature variation have significantly positive impacts on the mortality rates. The effects of changing average temperature on mortality rates in summer and winter are asymmetrical and also depend on the location. Combining the future climate change scenarios with the estimation outcomes show that mortality rates in OECD countries in 2100 will be increased by 3.77% to 5.89%.Climate change; mortality; panel data model

Modeling the Effect of Oil Price on Global Fertilizer Prices

The main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, the autoregressive distributed lag (ARDL) model, and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model, are used to investigate the relationship between crude oil price and six global fertilizer prices. Weekly data for 2003-2008 for the seven price series are analyzed. The empirical results from ARDL show that most fertilizer prices are significantly affected by the crude oil price, which explains why global fertilizer prices reached a peak in 2008. We also find that that the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods, and that the peak crude oil price caused greater volatility in the crude oil price and global fertilizer prices. As volatility invokes financial risk, the relationship between oil price and global fertilizer prices and their associated volatility is important for public policy relating to the development of optimal energy use, global agricultural production, and financial integration.Volatility; Global fertilizer price; Crude oil price; Non-renewable fertilizers; Structural breakpoint unit root test

Toward a Community-oriented Development of Internet Platforms: a Qualitative Case Study

In this study, we seek to identify the development process of the virtual community. This study investigates the development process of two virtual communities: HSC (Home-stay Community) and UTC (University Teaching Community). This case study has produced two major findings. First, the sets of values established in a virtual community are related to the particular system functions employed in that community. While HSC members use blogs to collect related information and utilize forums to make bi-directional communication, UTC members seldom access blogs or edit Wiki pages. Second, motivation leads participants to join their community and to shape its boundaries. The information sharing process is shown to be an effective way of improving community development in the virtual context. Thus, managers are advised to pay attention to active and strongly-motivated players in the virtual context. Future studies may enrich the current investigation by focusing upon the relevant business models

Investigating the Development of Work-oriented Groups in an e-Learning Environment

[[abstract]]In this study, we have investigated developmental patterns of virtual groups in the e-learning environment. Our findings suggest that for virtual groups formed for the purpose of e-learning, dependency and inclusion characterize the initial stage of group development, as such characteristics reinforce cooperative relationships and help to build a stronger social bond among group members. This is followed by the second stage, swift work, which enables participants to labor as a team and facilitates continual collaboration among members. However, the third stage, conflict, is inevitable, as conflicts provide important diagnostic evidence for each member to assess and adjust his or her values and preference. Finally, by overcoming conflicts, partners build strong bonding, which fosters intimate communication and provides many opportunities for frequent interactions that demonstrate concern and desire to satisfy the needs and wishes of one another. Our finding suggests that initial active dependency interactions in the first period provide a sense of coherence. Accordingly, the instructor of a virtual learning system should encourage learners to express their concern for one another in order quickly to build strong norms. In addition, as work intensifies, the instructor could aim to support both the effective interaction channels of groups as well as their task-focused activities. Finally, to improve members’ involvement and information sharing, the instructor could provide feedback to groups regarding their level of interactivity and encourage members to remind each other about the quality and quantity of individual contribution.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SSCI[[booktype]]紙本[[booktype]]電子版[[countrycodes]]NZ

Leadership behind the Screen: Exploring Leadership in the Virtual Groups

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On the Patent Claim Eligibility Prediction Using Text Mining Techniques

With the widespread of computer software in recent decades, software patent has become controversial for the patent system. Of the many patentability requirements, patentable subject matter serves as a gatekeeping function to prevent a patent from preempting future innovation. Software patents may easily fall into the gray area of abstract ideas, whose allowance may hinder future innovation. However, without a clear definition of abstract ideas, determining the patent claim subject matter eligibility is a challenging task for examiners and applicants. In this research, in order to solve the software patent eligibility issues, we propose an effective model to determine patent claim eligibility by text-mining and machine learning techniques. Drawing upon USPTO issued guidelines, we identify 66 patent cases to design domain knowledge features, including abstractness features and distinguishable word features, as well as other textual features, to develop the claim eligibility prediction model. The experiment results show our proposed model reaches the accuracy of more than 80%, and domain knowledge features play a crucial role in our prediction model

Energy Efficiency Modeling and Analysis in Wireless Sensor Networks

We propose here an extended linear feedback model, taking the binary exponential backo® mechanism adopted in IEEE 802.15.4 CSMA/CA and analyse the energy consumption issues of the one hop sensor nodes. Numerical results show that the energy consumption in Wireless Sensor Networks (WSNs) can be reduced by applying CSMA protocol with ¯xed contention window size. Besides, an optimal contention window size can achieve the reasonable successful probability of the packet transmission without extra wastage of the battery power