Colour by numbers in Excel 2007 : solving algebraic equations without algebra

This is an update of an earlier paper, and is written for Excel 2007. A series of Excel 2007 models is described. The more advanced versions allow solution of f(x)=0 by examining change of sign of function values. The function is graphed and change of sign easily detected by a change of colour. Relevant features of Excel 2007 used are Names, Scatter Chart and Conditional Formatting. Several sample Excel 2007 models are available for download, and the paper is intended to be used as a lesson plan for students having some familiarity with derivatives. For comparison and reference purposes, the paper also presents a brief outline of several common equation-solving strategies as an Appendix.

Common secure index for conjunctive keyword-based retrieval over encrypted data

We consider the following problem: users in a dynamic group store their encrypted documents on an untrusted server, and wish to retrieve documents containing some keywords without any loss of data confidentiality. In this paper, we investigate common secure indices which can make multi-users in a dynamic group to obtain securely the encrypted documents shared among the group members without re-encrypting them. We give a formal definition of common secure index for conjunctive keyword-based retrieval over encrypted data (CSI-CKR), define the security requirement for CSI-CKR, and construct a CSI-CKR based on dynamic accumulators, Paillier’s cryptosystem and blind signatures. The security of proposed scheme is proved under strong RSA and co-DDH assumptions.

Investor sentiment as conditioning information in asset pricing

This paper assesses whether incorporating investor sentiment as conditioning information in asset-pricing models helps capture the impacts of the size, value, liquidity and momentum effects on risk-adjusted returns of individual stocks. We use survey sentiment measures and a composite index as proxies for investor sentiment. In our conditional framework, the size effect becomes less important in the conditional CAPM and is no longer significant in all the other models examined. Furthermore, the conditional models often capture the value, liquidity and momentum effects.

Robust numeric set watermarking : numbers don’t lie

Ever since Cox et. al published their paper, “A Secure, Robust Watermark for Multimedia” in 1996 [6], there has been tremendous progress in multimedia watermarking. The same pattern re-emerged with Agrawal and Kiernan publishing their work “Watermarking Relational Databases” in 2001 [1]. However, little attention has been given to primitive data collections with only a handful works of research known to the authors [11, 10]. This is primarily due to the absence of an attribute that differentiates marked items from unmarked item during insertion and detection process. This paper presents a distribution-independent, watermarking model that is secure against secondary-watermarking in addition to conventional attacks such as data addition, deletion and distortion. The low false positives and high capacity provide additional strength to the scheme. These claims are backed by experimental results provided in the paper.

The importance of good data, analysis and interpretation for showing the economics of reducing healthcare-associated infection

To the Editor—In a recent review article in Infection Control and Hospital Epidemiology, Umscheid et al1 summarized published data on incidence rates of catheter-associated bloodstream infection (CABSI), catheter-associated urinary tract infection (CAUTI), surgical site infection (SSI), and ventilator- associated pneumonia (VAP); estimated how many cases are preventable; and calculated the savings in hospital costs and lives that would result from preventing all preventable cases. Providing these estimates to policy makers, political leaders, and health officials helps to galvanize their support for infection prevention programs. Our concern is that important limitations of the published studies on which Umscheid and colleagues built their findings are incompletely addressed in this review. More attention needs to be drawn to the techniques applied to generate these estimates...

Conceptualising business models : definitions, frameworks and classifications

The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in terms of how it creates and captures customer value. This abstract and generic definition is made more specific and operational by the compositional elements that need to address the customer, value proposition, organizational architecture (firm and network level) and economics dimensions. Business model archetypes complement the definition and elements by providing a more concrete and empirical understanding of the business model concept. The main contributions of this paper are (1) explicitly including the customer value concept in the business model definition and focussing on value creation, (2) presenting four core dimensions that business model elements need to cover, (3) arguing for flexibility by adapting and extending business model elements to cater for different purposes and contexts (e.g. technology, innovation, strategy),(4) stressing a more systematic approach to business model archetypes by using business model elements for their description, and (5) suggesting to use business model archetype research for the empirical exploration and testing of business model elements and their relationships.

Technology, Natural Resources and Economic Growth: Improving the Environment for a Greener Future

Description Through a combination of global data analysis and focused country level analysis, this timely book provides answers to the most pertinent country and industry specific questions defining the current relationship between technology, natural resources and economic growth. Contents Contents: Preface Part I: Global Analysis 1. Economic Growth and the Environment 2. Energy Substitution and Carbon Dioxide Emissions 3. Pollution, Natural Resources, and Economic Growth 4. Trade Openness and Environmental Quality 5. Environmental Productivity 6. Energy Price-induced Technological Change 7. Trade-induced Technological Change 8. Regional Economic Integration Part II: Country-Level Analysis 9. Emissions Trading in the United States 10. Increasing Returns to Pollution Abatement in the United States 11. Policy-induced Competitiveness in the United States 12. Trade Liberalization, Technology, and the Environment 13. Policy Implementation and its Effectiveness in China 14. Clean Technological Inventions in Japan 15. Intervention of Economic Policy and its Nonlinear Effects in Japan 16. The Next Emerging Giants: India and Africa 17. Conclusion Index Further information Through a combination of global data analysis and focused country level analysis, this timely book provides answers to the most pertinent country and industry specific questions defining the current relationship between technology, natural resources and economic growth. Shunsuke Managi takes a distinctive approach by focusing on the design and implementation of environmental regulations that encourage technological progress and, in doing so, looks at ways to ensure productivity improvements in the face of increasingly stringent environmental regulations and natural resource depletion. The findings in this important book demonstrate how successful environmental policies can contribute to efficiency by encouraging, rather than inhibiting, technological innovation. Technology, Natural Resources and Economic Growth will provide a valuable resource for a wide readership including postgraduate students, researchers, academics and policy makers working in the fields of environmental and ecological economics.

Decomposition analysis of air pollution abatement in China: empirical study for ten industrial sectors from 1998 to 2009

This study analyzes the management of air pollutant substance in Chinese industrial sectors from 1998 to 2009. Decomposition analysis applying the logarithmic mean divisia index is used to analyze changes in emissions of air pollutants with a focus on the following five factors: coal pollution intensity (CPI), end-of-pipe treatment (EOP), the energy mix (EM), productive efficiency change (EFF), and production scale changes (PSC). Three pollutants are the main focus of this study: sulfur dioxide (SO2), dust, and soot. The novelty of this paper is focusing on the impact of the elimination policy on air pollution management in China by type of industry using the scale merit effect for pollution abatement technology change. First, the increase in SO2 emissions from Chinese industrial sectors because of the increase in the production scale is demonstrated. However, the EOP equipment that induced this change and improvements in energy efficiency has prevented an increase in SO2 emissions that is commensurate with the increase in production. Second, soot emissions were successfully reduced and controlled in all industries except the steel industry between 1998 and 2009, even though the production scale expanded for these industries. This reduction was achieved through improvements in EOP technology and in energy efficiency. Dust emissions decreased by nearly 65% between 1998 and 2009 in the Chinese industrial sectors. This successful reduction in emissions was achieved by implementing EOP technology and pollution prevention activities during the production processes, especially in the cement industry. Finally, pollution prevention in the cement industry is shown to result from production technology development rather than scale merit. © 2013 Elsevier Ltd. All rights reserved.

Decomposition of toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008

This study analyzes toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008. Decomposition analysis applying the logarithmic mean Divisia index is used to analyze changes in toxic chemical substance emissions by the following five factors: cleaner production, end-of-pipe treatment, transfer for further management, mixing of intermediate materials, and production scale. Based on our results, the chemical manufacturing sector reduced toxic chemical substance emissions mainly via end-of-pipe treatment. In the meantime, transfer for further management contributed to the reduction of toxic chemical substance emissions in the metal fabrication industry. This occurred because the environmental business market expanded in the 1990s, and the infrastructure for the recycling of metal and other wastes became more efficient. Cleaner production is the main contributor to toxic chemical reduction in the electrical product industry. This implies that the electrical product industry is successful in developing a more environmentally friendly product design and production process.

Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold

This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets. © 2013 Elsevier B.V.

Productivity growth and biased technological change in Japanese airports

In this paper, the productivities of Japanese airports over the period of 1987-2005 are analyzed using the Malmquist index, and technological bias is investigated. During this period, airports on average became less efficient and experienced technological regress. Our results indicate that the traditional growth accounting method, which assumes Hicks neutral technological change, is not appropriate for analyzing changes in productivity for Japanese airports.

Environment and productivities in developed and developing countries : the case of carbon dioxide and sulfur dioxide

We propose a productivity index for undesirable outputs such as carbon dioxide (CO2) and sulfur dioxide (SO2) emissions and measure it using data from 51 developed and developing countries over the period 1971-2000. About half of the countries exhibit the productivity growth. The changes in the productivity index are linked with their respective per capita income using a semi-parametric model. Our results show technological catch up of low-income countries. However, overall productivities both of SO2 and CO2 show somewhat different results.