An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.     

An exploratory study of organizational flexibility in Malaysia: a research note

This note reports on an exploratory study examining the relationships between rules on employee behaviour and on management discretion and other aspects of organizations in Malaysia. Using the data from thirty-five Malaysian organizations, the authors highlight the differences between the implications of the rules for the two groups and their relationships with company performance.     

House Prices and Inflation

The present paper examines the long-run impact of inflation on homeowner equity by investigating the relationship between house prices and the prices of nonhousing goods and services, rather than return series and inflation rates as in previous empirical studies on the inflation hedging ability of real estate. There are two reasons for this methodological departure from prior practice: (1) while the total return on housing cannot be accurately measured, the total return on housing is fully reflected in housing prices, and (2) given that using returns or differencing a time series leads to a loss of long-run information contained in the series, valuable long-run information can be captured by using prices. Also, unlike previous related studies, we exclude housing costs from goods and services prices to avoid potential bias in estimating how inflation affects housing prices. Monthly data series are collected for existing and for new house prices as well as the consumer price index excluding housing costs for the period 1968–2000. Based on both autoregressive distributed lag (ARDL) models and recursive regressions, the empirical results yield estimated Fisher coefficients that are consistently greater than one over the sample period. Thus, we infer that house prices are a stable inflation hedge in the long run.     

The Impact of Innovativeness and Development Time on New Product Performance for Small Firms

Timing is becoming a new source of competitive advantage. The business press extols the benefits of faster product development. This paper examines whether competitive advantage can be gained by reducing development time across all types of new products or whether this advantage is restricted to certain types of new products. It proposes that product innovativeness moderates the relationship between development time and initial market performance. A survey of 110 small manufacturing firms in computer related industries supports the hypothesis. The survey findings indicate that a firm must guard against over- or under-development of the new product since product innovativeness was found to influence the impact of development time on market performance. The implications for managers are: beware of bringing a new product that is too much, too early or too little, too late.     

The Distributional Properties of the Debt to Equity Ratio: Some Implications for Empirical Research

The purpose here is to assess empirically the quasi-supply side model of the firm developed in the paper by Ashton et al. (2004 ) by testing the prediction of the model that the evolution of a firm's debt to equity ratio will be compatible with a non-linear (target adjustment) process whose underlying probability density function possesses no convergent moments. Using a thirty-two-year history of the debt to equity ratio for each of ninety 'mature' United Kingdom firms, a non-parametric estimation procedure shows that the debt to equity ratio evolves in terms of a process which is largely consistent with the predictions of this model. In particular, the evolution of the debt to equity ratio is compatible with a 'long (fat) tailed' density function with no convergent moments. This has the important implication, supported by our empirical analysis, that the linear dynamic models which characterize empirical work in this area will be mis-specified and will return inconsistent and temporally unstable estimates of the target adjustment process as a consequence.     

Intraday volume and volatility relations with and without public news

This paper reexamines the dynamic relation between intraday trading volume and return volatility of large and small NYSE stocks in two partitioned samples, with and without identifiable public news. We argue that the sequential information arrival hypothesis (SIAH) can be tested only in periods containing public news. After partitioning the sample into periods with and without public news, we find bi-directional Granger-causality between volume and volatility in the presence of public information as hypothesized by the SIAH. Our analysis further suggests that return volatility is higher in the periods with public news, while trading volume is significantly higher in the no-news period; perhaps owing to the importance of private information for trading stocks. Using the sample without public news, we find evidence that volume Granger-causes volatility without feedback. These results are broadly consistent with behavioral models like the overconfidence and biased self-attribution model of [Daniel, K., Hirshleifer, D., Subrahmanyam, A., 1998. Investor psychology and security market under- and over-reactions. Journal of Finance 53, 1839–1885]. It appears that overconfident investors overrate the precision of their private news signals and therefore trade too aggressively in the absence of public news; when public news arrives, investors’ biased self-attribution triggers excessive return volatility.     

You May Not Reap What You Sow: How Employees’ Moral Awareness Minimizes Ethical Leadership’s Positive Impact on Workplace Deviance

Although a growing body of research has shown the positive impact of ethical leadership on workplace deviance, questions remain as to whether its benefits are consistent across all situations. In this investigation, we explore an important boundary condition of ethical leadership by exploring how employees’ moral awareness may lessen the need for ethical leadership. Drawing on substitutes for leadership theory, we suggest that when individuals already possess a heightened level of moral awareness, ethical leadership’s role in reducing deviant actions may be reduced. However, when individuals lack this strong moral disposition, ethical leadership may be instrumental in inspiring them to reduce their deviant actions. To enhance the external validity and generalizability of our findings, the current research used two large field samples of working professionals in both Turkey and the USA. Results suggest that ethical leadership’s positive influence on workplace deviance is dependent upon the individual’s moral awareness—helpful for those employees whose moral awareness is low, but not high. Thus, our investigation helps to build theory around the contingencies of ethical leadership and the specific audience for whom it may be more (or less) influential.     

Experience, information asymmetry, and rational forecast bias

This study examines whether it is ever rational for analysts to post biased estimates and how information asymmetry and analyst experience factor into the decision. Using a construct where analysts wish to minimize their forecasting error, we model forecasted earnings when analysts combine private information with consensus estimates to determine the optimal forecast bias, i.e., the deviation from the consensus. We show that the analyst??s rational bias increases with information asymmetry, but is concavely related with experience. Novice analysts post estimates similar to the consensus but as they become more experienced and develop private information channels, their estimates become biased and deviated from the consensus. Highly seasoned analysts, who have superior analytical skills and valuable relationships, need not post biased forecasts.     

Does Bank Diversification Improve Output Growth? Evidence from the Recent Global Crisis

This study examines whether the diversity of activities conducted by the banking sector in the years approaching the recent global financial crisis alleviated the adverse impact of the crisis. Using data for 28 industries in 66 countries, we find that bank diversification has strengthened country resilience to the crisis, as measured by industry growth over the period 2008–2009. However, we find that while both bank‐based and market‐based economies have been affected negatively by the crisis, the contribution of bank diversification in mitigating the real impact of the crisis is pronounced only in bank‐based economies. Overall, our findings suggest that countries with significant bank diversification have also been the most resilient to the recent global crisis.     

中国和印度的贸易扩张:威胁还是机遇?

本文探讨了中印之间以及中印与其它国家之间的贸易竞争性和互补性。研究结果表明:(1)印度在第三方市场,尤其在服装、纺织品和皮革制品等方面,面临来自中国的强烈竞争;(2)中印之间的贸易增长具有一定潜力;(3)中国在中等技术行业对东亚各国、美国和大多数欧洲国家构成挑战,而印度主要对周边的南亚国家构成威胁;(4)在贸易的互补性方面,中国和印度大幅上升的进口为美国、欧洲和东亚一些国家,尤其是日本、韩国、马来西亚、新加坡和泰国的出口提供了扩张的机会。同时我们发现中国的出口结构正在发生变化,技术密集型和高科技产品的出口份额在增加,这表明从长期来看,由中国劳动密集型产品出口带来的挑战将会削弱。本文探讨了中印之间以及中印与其它国家之间的贸易竞争性和互补性。研究结果表明:(1)印度在第三方市场,尤其在服装、纺织品和皮革制品等方面,面临来自中国的强烈竞争;(2)中印之间的贸易增长具有一定潜力;(3)中国在中等技术行业对东亚各国、美国和大多数欧洲国家构成挑战,而印度主要对周边的南亚国家构成威胁;(4)在贸易的互补性方面,中国和印度大幅上升的进口为美国、欧洲和东亚一些国家,尤其是日本、韩国、马来西亚、新加坡和泰国的出口提供了扩张的机会。同时我们发现中国的出口结构正在发生变化,技术密集型和高科技产品的出口份额在增加,这表明从长期来看,由中国劳动密集型产品出口带来的挑战将会削弱。