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Fukuzawa Y.,Hitachi Ltd. | Samejima M.,Osaka University | Ujita H.,The Canon Institute for Global Studies
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

In developing Cyber Physical Systems, such as smart grid and smart cities, risk management technologies play an important role to provide safe and secure services. In this paper, focusing on changes of recent threats represented by Social engineering, a survey shows that the information security psychology is valuable for the risk management of the Cyber Physical Systems. Through surveying, we outline the risk management framework for Cyber Physical Systems. © Springer International Publishing Switzerland 2015. Source

Araki D.,Kobe University | Kamae I.,Kobe University | Kamae I.,University of Tokyo | Kamae I.,The Canon Institute for Global Studies
Kobe Journal of Medical Sciences

New schemes on the cost-effectiveness acceptability curve (CEAC) were developed, which can make the CEAC augmented to be more informative regarding the types of acceptance and statistical inference. Theoretical approaches have been undertaken to address two questions: 1) how the area under the curve (AUC) can be zoned by different types of acceptance displayed on the incremental cost-effectiveness plane, and 2) how the accepted dataset of incremental cost-effectiveness ratios (ICERs), which are generated by simulation runs, can be statistically associated with a threshold of ICER for acceptance. To address the first question, the AUC of a typically sigmoid-shaped CEAC was divided into three zones according to the three segmentations of the scattered plots accepted at South-east, North-east and South-west quadrants on the incremental cost-effectiveness plane. A solution for the second question was "a new CEAC of the mean" (mCEAC), which is defined by plotting a pair of the mean and its occurrence probability of ICER accepted at North-east quadrant on the incremental cost-effectiveness plane. All those schemes were graphically illustrated based on hypothetical examples using the bootstrapping simulation. Our new schemes on CEAC will provide decision makers with useful information on cost-effectiveness assessment beyond the standard presentation of CEAC. © 2015, Kobe Journal of Medical Sciences. All rights reserved. Source

Mizuno T.,Japan National Institute of Information and Communications Technology | Mizuno T.,Graduate University for Advanced Studies | Mizuno T.,Japan Science and Technology Agency | Mizuno T.,The Canon Institute for Global Studies | And 4 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

We investigate the structure of global inter-firm relationships using a unique dataset containing information on customers, suppliers, licensors, licensees and strategic alliances for each of 412,814 major incorporated non-financial firms in the world. We focus on three different networks: customer-supplier network, licensee-licensor network, and strategic alliance network. In/out-degree distribution of these networks follows a Pareto distribution with an exponent of 1.5. The shortest path length on the networks for any pair of firms is around six links. The networks have a scale-free property. We also find that stock price returns tend to be more highly correlated the closer two listed firms are to each other in the networks. This suggests that a non-negligible portion of price fluctuations stems from the propagation of a particular firm’s shocks through inter-firm relationships. © Springer International Publishing Switzerland 2015. Source

Mizuno T.,Japan National Institute of Information and Communications Technology | Mizuno T.,University of Tokyo | Mizuno T.,The Canon Institute for Global Studies | Watanabe T.,University of Tokyo | Watanabe T.,The Canon Institute for Global Studies

Why are product prices in online markets dispersed in spite of very small search costs? To address this question, we construct a unique dataset from a Japanese price comparison site, which records price quotes offered by e-retailers as well as customers' clicks on products, which occur when they proceed to purchase the product. The novelty of our approach is that we seek to extract useful information on the source of price dispersion from the shape of price distributions rather than focusing merely on the standard deviation or the coefficient of variation of prices, as previous studies have done. We find that the distribution of prices retailers quote for a particular product at a particular point in time (divided by the lowest price) follows an exponential distribution, showing the presence of substantial price dispersion. For example, 20 percent of all retailers quote prices that are more than 50 percent higher than the lowest price. Next, comparing the probability that customers click on a retailer with a particular rank and the probability that retailers post prices at a particular rank, we show that both decline exponentially with price rank and that the exponents associated with the probabilities are quite close. This suggests that the reason why some retailers set prices at a level substantially higher than the lowest price is that they know that some customers will choose them even at that high price. Based on these findings, we hypothesize that price dispersion in online markets stems from heterogeneity in customers' preferences over retailers; that is, customers choose a set of candidate retailers based on their preferences, which are heterogeneous across customers, and then pick a particular retailer among the candidates based on the price ranking. © 2013 Mizuno, Watanabe. Source

Hisano R.,ETH Zurich | Hisano R.,The Canon Institute for Global Studies | Sornette D.,ETH Zurich | Sornette D.,Swiss Finance Institute | And 7 more authors.

Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affects trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affects stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their "thematic" features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized facts in financial economies, namely that at certain times trading volumes appear to be "abnormally large," can be partially explained by the flow of news. In this sense, our results prove that there is no "excess trading," when restricting to times when news is genuinely novel and provides relevant financial information. © 2013 Hisano et al. Source

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