Decision support for target country selection of future generation sovereign wealth funds: Hedging the country industry risk

AbstractThis paper addresses the challenging problem of selecting target country for future Sovereign Wealth Funds’ (SWFs) asset allocation to hedge the industry risk, which is rarely studied in the field. The target country selection includes which country and how much to invest to obtain the return objective and minimize the risk of these funds. In terms of the industrial perspective, the home country as the investor should consider SWF as part of its budget to make decision in long term. In order to control the risk, this paper measures the similarity between the home and the recipient country of SWF investment. The industrial risk of SWFs’ recipient country is also taken into consideration which is measured by concentration ratio. Based on an analytical process of target country selection, the paper finds that Kazakhstan, India, Australia, Greece, Spain, United States, Austria, Portugal, Peru, Netherlands are the top 10 countries that China should consider as its investment priorities

A DECISION SUPPORT SYSTEM FOR THE ENVIRONMENTAL IMPACT OF ICT AND E-BUSINESS

Information and communication technologies (ICT) and e-business are affecting our economic progress, social development, and the environment profoundly and in a complex manner. As an emerging field of research, significant interests have been aroused but quantitative studies are rather limited. Traditional systematic approaches for impact studies have been found to be insufficient to deal with this research topic. In order to further explore the relationship between ICT/e-business and the environment, the approach adopted in this study aimed to simulate how ICT/e-business indicators interact with environmental indicators quantitatively. Owing to lack of data and information in the current area in government bodies/councils/research institutes, two questionnaire surveys were conducted. Details of the data collection progress are provided. An artificial neural network (ANN) approach, embedded in a more predictive and empirical model, is suggested herein as a new methodology and possible solution. Furthermore an expert decision support system (EDSS), built around these neural networks with a user-friendly interface and being able to post-process data to information, is developed. The system could be used, for example, by an individual company to analyze how its ICT/e-business adoptions influence its environmental performance.Expert decision support system (EDSS), decision support system (DSS), environmental impact, information and communication technology (ICT), artificial neural network (ANN)