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

Intelligent Knowledge Beyond Data Mining: Influences of Habitual Domains

Data mining is a useful analytic method and has been increasingly used by organizations to gain insights from large-scale data. Prior studies of data mining have focused on developing automatic data mining models that belong to first-order data mining. Recently, researchers have called for more study of the second-order data mining process. Second-order data mining process is an important step to convert data mining results into intelligent knowledge, i.e., actionable knowledge. Specifically, second-order data mining refers to the post-stage of data mining projects in which humans collectively make judgments on data mining models’ performance. Understanding the second-order data mining process is valuable in addressing how data mining can be used best by organizations in order to achieve competitive advantages. Drawing on the theory of habitual domains, this study developed a conceptual model for understanding the impact of human cognition characteristics on second-order data mining. Results from a field survey study showed significant correlations between habitual domain characteristics, such as educational level and prior experience with data mining, and human judgments on classifiers’ performance

How to Measure The Operating Efficiency of Internet Group-Buying Platform?

AbstractIn order to measure the operating efficiency of internet group-buying platform, this study sorts and analyses the transaction data from a large group-buying platform in China, defines the concept of matching efficiency as the measuring index of operating efficiency and the conversion-rate indicators in each stage of matching process. The definition and analysis of matching efficiency of internet group-buying platform fills up the deficiency in internet operating efficiency measurement domain

Risk Factor Analysis for AKI Including Laboratory Indicators: a Nationwide Multicenter Study of Hospitalized Patients

Background/Aims: Risk factor studies for acute kidney injury (AKI) in China are lacking, especially those regarding non-traditional risk factors, such as laboratory indicators. Methods: All adult patients admitted to 38 tertiary and 22 secondary hospitals in China in any one month between July and December 2014 were surveyed. AKI patients were screened according to the Kidney Disease: Improving Global Outcomes’ definition of AKI. Logistic regression was used to analyze the risk factors for AKI, and Cox regression was used to analyze the risk of in-hospital mortality for AKI patients; additionally, a propensity score analysis was used to reconfirm the risk factors among laboratory indicators for mortality. Results: The morbidity of AKI was 0.97%. Independent risk factors for AKI were advancing age, male gender, hypertension, and chronic kidney disease. All-cause mortality was 16.5%. The predictors of mortality in AKI patients were advancing age, tumor, higher uric acid level and increases in Acute Physiologic Assessment and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores. The hazard ratio (HR) for mortality with uric acid levels > 9.1 mg/dl compared with ≤ 5.2 mg/dl was 1.78 (95% CI: 1.23 to 2.58) for the AKI patients as a group, and was 1.73 (95% CI: 1.24 to 2.42) for a propensity score-matched set. Conclusion: In addition to traditional risk factors, uric acid level is an independent predictor of all-cause mortality after AKI