Abstract: Environmental studies have developed slowly within social sciences in Latin America. This paper seeks to assess and systematize the contribution of social sciences in the research on the human dimensions of global environmental change (HDGEC) in the region outlining its state of the art and process of development. Design/methodology/approach The approach taken is the organization of a manual compilation and systematic review of publications on topics related to the HDGEC in order to investigate major research topics covering the period between 2001 and 2008. Findings Although it is possible to identify an emergent body of the literature and scholarship in the region, the involvement of Latin American social science in the HDGEC research is still timid and tentative and not yet institutionalized. The evidence from this compilation has shown that this literature is fragmented bringing difficulties for the homogenization of criteria for analysis and assessment. Originality/value The paper is one of the very few attempts to assess and analyze the research on HDGEC in Latin America through an international perspective. It provides an overview of its development building upon the progress of environmental studies in the region and looks to its challenges ahead in order to call for more involvement of social sciences in these research activities.

Abstract: BACKGROUND: The availability and quality of irrigation water have become a serious concern because of global climate change and an increased competition for water by industry, domestic users and the environment. Therefore, exploring environmentally friendly water‐saving irrigation strategies is essential for achieving food and environmental security. In northern Ethiopia, where traditional furrow irrigation is widely practiced, water mismanagement and its undesirable environmental impact are rampant. A 2‐year field study was undertaken to compare the traditional irrigation management with surge and deficit irrigation practices on a Vertisol plot. RESULT: Results have shown that surge and deficit irrigation practices increase water productivity by 62% and 58%, respectively, when compared to traditional management. The study also found out that these practices reduce the adverse environmental impacts (waterlogging and salinity) of traditional management by minimizing deep percolation and tail water losses. Total irrigation depth was reduced by 12% (for surge) and 27% (for deficit) when compared to traditional management. CONCLUSION: Based on the results, the study concluded that surge and deficit irrigation technologies not only improve water productivity but also enhance environmental sustainability. Copyright © 2010 Society of Chemical Industry

Abstract: Regional‐scale assessment of soil C pools is essential to provide information for C cycling models, land management, and policy decisions, and elucidate the relative contribution of different C pools to total C (TC). We estimated TC and four soil C fractions, namely recalcitrant C (RC), hydrolyzable C (HC), hot‐water‐soluble C (SC), and mineralizable C (MC), at 0 to 30 cm across a 3585‐km 2 mixed‐use watershed in north‐central Florida. We used lognormal block kriging (BK) and regression block kriging (RK) to upscale soil C using 102 training samples and compared the models using 39 validation samples. Regression kriging produced the most accurate models for TC and RC, whereas the labile C fractions (HC, SC, and MC) were best modeled by BK. Maps produced by BK showed similar spatial patterns due to the strong correlation between the labile C fractions and the similarity of their spatial dependence structure. Estimates of TC and RC were similar due to their high correlation and the similarity of their global trend models. Total soil C amounted to 27.40 Tg across the watershed, indicating the potential of these soils to store C. Recalcitrant C totaled 22.49 Tg (82% of TC), suggesting that a large amount of TC could be potentially stored for centuries to millennia. Our estimates of soil C and fractions within a mixed‐use watershed in Florida highlight the importance of appropriately characterizing the inherent spatial dependence structure of soil C, as well as relevant regional environmental patterns (e.g., hydrology), to better explain the variability of soil C.

Abstract: Christopher Adams (“ The Sealed-Bid Abstraction in Online Auctions ”; “ Rejoinder—Causes and Implications to Some Bidders Not Conforming to the Sealed-Bid Abstraction ”) is a staff economist with the Federal Trade Commission (FTC). He has a Ph.D. in economics from the University of Wisconsin and a B.Comm (Hons) from the University of Melbourne. At the FTC, he has worked on mergers and antitrust cases in a number of industries including pharmaceuticals, real estate, software, and retail. Before joining the FTC, he taught at the University of Vermont. In 2007, he was awarded the FTC's Paul Rand Dixon Award for outstanding contributions to the Commission. Paulo Albuquerque (“ Online Demand Under Limited Consumer Search ”) is an assistant professor of marketing at the Simon Graduate School of Business, University of Rochester. He holds a Ph.D. in management from the UCLA Anderson School of Management. He is currently interested in competition and consumer behavior in online markets, new product diffusion across markets, and spatial competition models. Bart J. Bronnenberg (“ Online Demand Under Limited Consumer Search ”) is a professor of marketing and CentER research fellow at Tilburg University. He holds Ph.D. and M.Sc. degrees in management from INSEAD, Fontainebleau, France, and an M.S. in industrial engineering from Twente University, The Netherlands. He is currently interested in marketing strategy and multimarket competition in consumer goods and medical industries. He has previously worked, and continues to work, on empirical analyses of new product growth and consumer choice behavior. He was named the recipient of the 2003 and 2008 Paul Green Award, the 2003 International Journal of Research in Marketing (IJRM) Best Paper Award, and the 2004 John D. C. Little Best Paper Award. Anne T. Coughlan (“ Optimal Reverse Channel Structure for Consumer Product Returns ”) is the John L. and Helen Kellogg Professor of Marketing at the Kellogg School of Management at Northwestern University. Her research on channel design and compensation problems, sales force management, sales force compensation, and pricing has been published in the top journals for marketing and operation and decision technologies. She is an area editor for Marketing Science and an author of the Marketing Channels textbook. Her favorite leisure activity is cultivating cacti and succulents in her greenhouse. Brett Danaher (“ Converting Pirates Without Cannibalizing Purchasers: The Impact of Digital Distribution on Physical Sales and Internet Piracy ”) is an assistant professor of economics at Wellesley College. He received a bachelor's of science in economics from Haverford College and a Ph.D. in managerial science and applied economics from The Wharton School of the University of Pennsylvania. His research interests include digital media, intellectual property, and the economics of information goods. Marnik G. Dekimpe (“ Estimating Cannibalization Rates for Pioneering Innovations ”) is a research professor at Tilburg University (The Netherlands) and a professor of marketing at the Catholic University Leuven (Belgium), and he is currently an academic trustee with both MSI and AiMark. He received his Ph.D. from the University of California, Los Angeles. He has advised several key players in the consumer packaged goods industry, especially on private-label and marketing-mix effectiveness issues. He has won best paper awards at Marketing Science, the Journal of Marketing Research, the International Journal of Research in Marketing, and Technological Forecasting and Social Change. He has also won the 2010 Louis W. Stern Award for his work on the valuation of Internet channels. He serves as editor for the International Journal of Research in Marketing and serves on the editorial boards of Marketing Science, the Journal of Marketing, the Journal of Marketing Research, Marketing Letters, the Review of Marketing Science, and the Journal of Interactive Marketing. Samita Dhanasobhon (“ Converting Pirates Without Cannibalizing Purchasers: The Impact of Digital Distribution on Physical Sales and Internet Piracy ”) is a Ph.D. candidate in public policy and management at the Heinz College, Carnegie Mellon University. Her research interests include digital piracy, digital media, and e-commerce marketing. Peter S. Fader (“ Customer-Base Analysis in a Discrete-Time Noncontractual Setting ”) is the Frances and Pei-Yuan Chia Professor of Marketing at The Wharton School of the University of Pennsylvania, and codirector of the Wharton Interactive Media Initiative. Scott Fay (“ The Economics of Buyer Uncertainty: Advance Selling vs. Probabilistic Selling ”) is an assistant professor of marketing at the Whitman School of Management at Syracuse University. He received a Ph.D. in economics from the University of Michigan and previously taught at the Warrington College of Business of the University of Florida. In his research, he employs analytical modeling to study a variety of topics, many of which are related to e-commerce, including reverse auctions, opaque products, the personalization process, the bundling of information goods, shipping fee schedules, retail price endings, and consumer bankruptcy. He was elected to and served two terms as the newsletter editor for the INFORMS Society for Marketing Science (2002–2006). He serves on the editorial board of Marketing Science, served as a guest area editor for Marketing Science, and recently received the Meritorious Service Award from Management Science. Bruce G. S. Hardie (“ Customer-Base Analysis in a Discrete-Time Noncontractual Setting ”) is a professor of marketing at the London Business School. His primary research interest lies in the development of data-based models to support marketing analysts and decision makers, with a particular interest in models that are easy to implement. Most of his current projects focus on the development of probability models for customer-base analysis. Ernan Haruvy (“ Search and Choice in Online Consumer Auctions ”) is an associate professor of marketing at the University of Texas at Dallas. He received his Ph.D. in economics in 1999 from the University of Texas at Austin. His research focuses primarily on market design, with a special interest in auctions, procurement, learning, and bounded rationality. Gerald Häubl (“ Optimal Reverse-Pricing Mechanisms ”) is the Canada Research Chair in Behavioral Science and an associate professor of marketing at the University of Alberta's School of Business. He is the founding director of the Institute for Online Consumer Studies (IOCS). He received M.S. and Ph.D. degrees in business administration and marketing from the Vienna University of Economics and Business Administration (Wirtschaftsuniversität Wien) in his native Austria. His primary research interests are consumer decision making, the construction of preference and value, human–information interaction, decision assistance for consumers, and bidding behavior in interactive-pricing markets. Ali Hortaçsu (“ Commentary—Do Bids Equal Values on eBay? ”) is a professor of economics at the University of Chicago. He received his Ph.D. from Stanford University in 2001, and his main research area is industrial organization. He has developed novel econometric methods to study auction and matchmaking markets, and he has applied these methods to answer market design questions in central bank operations, government bond auctions, electricity markets, online auctions, and online matchmaking. He has also developed empirical methods to study markets with search frictions, with applications to e-commerce and the mutual fund industry. He has been awarded an Alfred P. Sloan Fellowship and an NSF CAREER grant and is a research associate of the National Bureau of Economic Research. He has served as the coeditor for the International Journal of Industrial Organization and as associate editor for the Journal of Business and Economic Statistics and the Journal of Industrial Economics. Sandy Jap (“ The Seeds of Dissolution: Discrepancy and Incoherence in Buyer–Supplier Exchange ”) is the Dean's Term Chair Professor of Marketing at the Goizueta Business School at Emory University. She is a graduate of the University of Florida (Go Gators!) and has served on the faculties of the Sloan School of Management at the Massachusetts Institute of Technology and The Wharton School of the University of Pennsylvania. Her research interests lie in interorganizational exchange management and the design and management of business-to-business markets with auction mechanisms. She is an area editor for the International Journal of Research in Marketing and an editorial board member of the Journal of Marketing Research and Marketing Letters. Ujwal Kayande (“ The Seeds of Dissolution: Discrepancy and Incoherence in Buyer–Supplier Exchange ”) is a professor of marketing in the Research School of Business at the Australian National University. He was previously on the faculty at the Smeal College of Business (Pennsylvania State University) and the Australian Graduate School of Management (University of New South Wales, Sydney). He obtained his Ph.D. from the University of Alberta. His current research focuses on developing quantitative models to understand marketplace behavior and the effect of marketing activity upon that behavior; additionally, he is interested in understanding the pathways by which quantitative models impact business practice. He is a recipient of the 1998 Don Lehmann Award from the American Marketing Association. Jun B. Kim (“ Online Demand Under Limited Consumer Search ”) is an assistant professor at the College of Management, Georgia Institute of Technology. He holds a Ph.D. in management from the UCLA Anderson School of Management and a Ph.D. in mechanical engineering from the Massachusetts Institute of Technology. His current research interests include information economics, choice models, and durable goods markets. Eric R. Nielsen (“ Commentary—Do Bids Equal Values on eBay? ”) is a University of Chicago economics graduate student specializing in labor economics, industrial organization, and econometrics. He received his A.B. from Harvard University in 2007. His current research focuses on matching markets and educational investment decisions. Peter T. L. Popkowski Leszczyc (“ Search and Choice in Online Consumer Auctions ”) is an associate professor of marketing at the School of Business, University of Alberta, and director of CampusAuctionMarket.com. He received is Ph.D. in marketing in 1992 from the University of Texas at Dallas. His research focuses on empirical and theoretical issues related to (Internet) auctions, influence of information on price formation, and charitable giving. R. Canan Savaskan (“ Optimal Reverse Channel Structure for Consumer Product Returns ”) is currently an associate professor at the Cox School of Business at Southern Methodist University. She received her Ph.D. in operations management from INSEAD, France. Her research is at the interface of operations and marketing, with a special focus on product returns management and reverse logistics. Jen Shang (“ Customer-Base Analysis in a Discrete-Time Noncontractual Setting ”) is an assistant professor at the School of Public and Environmental Affairs at Indiana University, Bloomington. She is a philanthropic psychologist who studies the psychological determinants for giving. She is the author of Fundraising: Principles and Practice. Jeffrey D. Shulman (“ Optimal Reverse Channel Structure for Consumer Product Returns ”) is an assistant professor of marketing at the Michael G. Foster School of Business at the University of Washington. His research focusing on strategic pricing issues has also appeared in Quantitative Marketing and Economics, Manufacturing and Service Operations Management, and the second edition of Kellogg on Marketing. He met his amazing wife Stephanie, mother of his beautiful daughter Olivia, while getting his Ph.D. in marketing at the Kellogg School of Management. Michael D. Smith (“ Converting Pirates Without Cannibalizing Purchasers: The Impact of Digital Distribution on Physical Sales and Internet Piracy ”) is an associate professor of information systems and marketing and the codirector of the Center for Digital Media Research at Carnegie Mellon University. He holds academic appointments at the School of Information Systems and Management and the Tepper School of Business. He received a bachelor's of science in electrical engineering (summa cum laude) and a master's of science in telecommunications science from the University of Maryland, and a Ph.D. in management science from the Sloan School of Management at MIT. Martin Spann (“ Optimal Reverse-Pricing Mechanisms ”) is a professor of electronic commerce at the School of Management of the Ludwig-Maximilians-University (LMU) in Munich, Germany. He received his Ph.D. from Goethe University in Frankfurt and was a professor of marketing and innovation at the University of Passau, Germany. He has visited the University of California at Los Angeles, the University of Southern California, and Bocconi University in Milan, Italy. His current research interests are electronic commerce, pricing, auctions, innovation management, prediction markets, and social network analysis. Kannan Srinivasan (“ Commentary—Bidders' Experience and Learning in Online Auctions: Issues and Implications ”) is the Rohet Tolani Distinguished Professor of International Business and the H. J. Heinz II Professor of Management, Marketing and Information Systems at the Tepper School of Business, Carnegie Mellon University. He is an associate editor for Management Science and Quantitative Marketing and Economics, and an area editor for Marketing Science. He has chaired 15 doctoral dissertations, and his students serve as faculty in various leading universities around the world. He is the President Elect of the INFORMS Society of Marketing Science. Shuba Srinivasan (“ Estimating Cannibalization Rates for Pioneering Innovations ”) is an associate professor of marketing and Dean's Research Fellow at Boston University's School of Management. Her research focuses on strategic marketing problems—in particular, linking marketing to financial performance, to which she applies her expertise in time-series analysis and econometrics. Her current research focuses on metrics for gauging marketing performance, and she has consulting experience with a wide spectrum of companies. Her research won the 2001 European Marketing Academy (EMAC) Best Paper Award. She serves on editorial boards of the Journal of Marketing Research and the International Journal of Research in Marketing, among others. Rahul Telang (“ Converting Pirates Without Cannibalizing Purchasers: The Impact of Digital Distribution on Physical Sales and Internet Piracy ”) is an associate professor of information systems and management and the codirector of the Center for Digital Media Research at the School of Information Systems and Management at the Heinz College, Carnegie Mellon University. He received his Ph.D. in information systems from the Tepper School of Business, Carnegie Mellon University. Harald J. van Heerde (“ Estimating Cannibalization Rates for Pioneering Innovations ”) is a professor of marketing at the University of Waikato, Hamilton, New Zealand. He holds a Ph.D. (cum laude) from the University of Groningen, The Netherlands. His research focuses on assessing the effectiveness of the marketing mix using econometric models and covers various substantive domains such as sales promotions and advertising, pricing and price wars, and loyalty programs. His work has been awarded with the Paul E. Green and William F. O'Dell Awards (Journal of Marketing Research (JMR)), and with the International Journal of Research in Marketing (IJRM) Best Paper Award. He serves on the editorial board of JMR and is an area editor for IJRM. Qiong Wang (“ The Seeds of Dissolution: Discrepancy and Incoherence in Buyer–Supplier Exchange ”) is an assistant professor of marketing at the Smeal College of Business, Pennsylvania State University. She joined Smeal in the fall of 2006 after receiving her Ph.D. from the University of Florida in August 2006. Her primary research focuses on interorganizational exchange behavior, relationship development, and governance mechanisms. Xin Wang (“ Commentary—Bidders' Experience and Learning in Online Auctions: Issues and Implications ”) is an assistant professor of marketing at Brandeis International Business School, Brandeis University. She received her doctoral degree from the Tepper School of Business, Carnegie Mellon University. Her research interests include online auctions, service quality, and consumer learning. She also taught at the Krannert School of Management, Purdue University. Jinhong Xie (“ The Economics of Buyer Uncertainty: Advance Selling vs. Probabilistic Selling ”) is the Etheridge Professor of International Business and a professor of marketing at the Warrington College of Business Administration, University of Florida. She holds a Ph.D. in engineering and public policy from Carnegie Mellon University, an M.S. in optimal control from the Second Academy of the Ministry of Astronautics (China), and a B.S. in electrical engineering from Tsinghua University. Her research interests include pricing, network effects and standards competition, consumer social interactions, innovation strategies, and cross-culture effects. She is a recipient of INFORMS' John D. C. Little Best Paper Award, the Marketing Science Institute's Research Competition Award, the Product Development and Management Association's Research Competition Award, and the University of Florida's Best Teaching Award. She has served as an associate editor for Management Science and an area editor for Marketing Science. Robert Zeithammer (“ The Sealed-Bid Abstraction in Online Auctions ”; “ Rejoinder—Causes and Implications of Some Bidders Not Conforming to the Sealed-Bid Abstraction ”; “ Optimal Reverse-Pricing Mechanisms ”) is an assistant professor of marketing at the UCLA Anderson School of Management. His research focuses on auction-driven marketplaces, such as eBay, in which the burden of pricing is on the interplay between buyers' bidding strategies and the seller's selling strategies. He is working on models that capture the essence of such interplay and help us understand the nature of these emerging marketplaces. In addition, he is interested in choice-based conjoint analysis and the analysis of choices from subsets of brands. Kevin Xiaoguo Zhu (“ The Effects of Information Transparency on Suppliers, Manufacturers, and Consumers in Online Markets ”) received his Ph.D. from Stanford University and is currently on the faculty of the Rady School of Management, University of California, San Diego. His research focuses on technology-enabled innovations, electronic markets, economic impacts of IT on firms/industries, and IT-enabled supply chains. His work has been published in top academic journals, as well as in a book, Global E-Commerce (Cambridge University Press, 2006). His research has been recognized by several best paper awards in the field and the prestigious CAREER Award from the U.S. National Science Foundation. Zach Zhizhong Zhou (“ The Effects of Information Transparency on Suppliers, Manufacturers, and Consumers in Online Markets ”) is currently a postdoctoral research fellow at the Rady School of Management, University of California, San Diego. He received his Ph.D. from the University of California, Irvine. His research focuses on electronic markets, competitive marketing strategies of software vendors, and economics of IT security.

Abstract: Windle, M. J. S., Rose, G. A., Devillers, R., and Fortin, M-J. 2010. Exploring spatial non-stationarity of fisheries survey data using geographically weighted regression (GWR): an example from the Northwest Atlantic. – ICES Journal of Marine Science, 67: 145–154. Analyses of fisheries data have traditionally been performed under the implicit assumption that ecological relationships do not vary within management areas (i.e. assuming spatially stationary processes). We question this assumption using a local modelling technique, geographically weighted regression (GWR), not previously used in fisheries analyses. Outputs of GWR are compared with those of global logistic regression and generalized additive models (GAMs) in predicting the distribution of northern cod off Newfoundland, Canada, based on environmental (temperature and distance from shore) and biological factors (snow crab and northern shrimp) from 2001. Results from the GWR models explained significantly more variability than the global logistic and GAM regressions, as shown by goodness-of-fit tests and a reduction in the spatial autocorrelation of model residuals. GWR results revealed spatial regions in the relationships between cod and explanatory variables and that the significance and direction of these relationships varied locally. A k-means cluster analysis based on GWR t-values was used to delineate distinct zones of species–environment relationships. The advantages and limitations of GWR are discussed in terms of potential application to fisheries ecology.

Abstract: Abstract The Department of Defense is currently conducting a review of archival information in an attempt to verify the types, quantities, and locations of chemical warfare material and conventional munitions disposed of by the Department of Defense (DoD) in waters of the United States, in accordance with Section 314 of the Fiscal Year (FY) 2007 National Defense Authorization Act (NDAA), and report the results of that review annually in the Defense Environmental Programs Annual Report to Congress. Previous to this effort, disposal of military munitions, including chemical warfare materials (CWM) and conventional munitions, in the ocean from World War I through 1970 was done by many nations and was not well documented. A 2001 U.S. Army report entitled “Off-shore Disposal of Chemical Agents and Weapons Conducted by the United States” indicated that the disposal of CWM in the ocean through 1970 was more widespread geographically than was widely known. In accordance with Section 314, the DoD published updated information on disposals in the 2006 and 2007 “Defense Environmental Programs Annual Report to Congress.” Two directives implemented in 2006 and 2007, respectively, by the Minerals Management Service referenced an increased concern with unexploded ordnance (UXO) in deep water ( 〈 xref ref-type="bibr" rid="bib5" 〉 NTLs 2006-G12 〈 /xref 〉 and 〈 xref ref-type="bibr" rid="bib6" 〉 2007-G01 〈 /xref 〉 ). With the industry’s increase in deep-water exploration, the potential for encounters with military munitions is increasing. This paper will describe an unprecedented in-depth study that provided the oil and gas industry quantitative avoidance criteria and risk management analysis of CWM including drums that were critical during a routine geohazard survey in the Gulf of Mexico. During the underway period, a team of UXO technicians from AMTI, an operation of Science Applications International Corporation, located and identified munitions and drums in one of seven known dumping zones in 1,710 feet of water. Using their global munitions expertise and the information obtained in the previously conducted study, AMTI provided analysis of supporting conclusions and risk mitigation strategies, including in-depth decontamination procedures. The UXO technicians used proven risk assessment and risk mitigation processes and quickly assessed and quantified risk.

Abstract: Rami Atar (“ The cμ/θ Rule for Many-Server Queues with Abandonment ”) is an associate professor in the Department of Electrical Engineering, Technion, Israel, where he received his Ph.D. in 1997. His research interests are in stochastic processes and their applications, including PDE techniques in stochastic control, and asymptotic analysis of queueing models. Achal Bassamboo (“ On the Accuracy of Fluid Models for Capacity Sizing in Queueing Systems with Impatient Customers ”) is an associate professor of managerial economics and decision sciences in the Kellogg School of Management at Northwestern University. His research focuses on using stochastic models to manage service operations, flexibility in service and production systems, and on strategic information sharing in services and retail. Tamer Boyacı (“ Information Acquisition for Capacity Planning via Pricing and Advance Selling: When to Stop and Act? ”) is an associate professor of operations management at McGill University's Desautels Faculty of Management. His research interests include supply chain management, closed-loop supply chains, and sustainable operations, as well as the operations-marketing interface. His research has appeared in academic journals including Operations Research, Manufacturing & Service Operations Management, Production and Operations Management, IIE Transactions, and Naval Research Logistics. Huseyin Cavusoglu (“ An Analysis of the Impact of Passenger Profiling for Transportation Security ”) is an assistant professor of information systems and operations management at the School of Management at the University of Texas at Dallas, where he received his Ph.D. in management science. He has published in various journals including Management Science, Information Systems Research, INFORMS Journal on Computing, Decision Analysis, IEEE Transactions on Software Engineering, IEEE Transactions on Engineering Management, Communications of the ACM, and the International Journal of Electronic Commerce. His major research interests include assessment of the value of IT security and design of IT security architecture. Cristiano Cervellera (“ Functional Optimization Through Semilocal Approximate Minimization ”) received the M.Sc. degree in electronic engineering from the University of Genoa, Italy, in 1998, and the Ph.D. degree in electronic engineering and computer science in 2002. Since 2002 he has been a researcher at the Genoa branch of the Institute of Intelligent Systems for Automation of the Italian National Research Council. His research interests include number-theoretic methods for optimization, optimal control, neural networks, and machine learning. He is particularly interested in the development of efficient algorithms for the approximate solution of nonlinear optimization problems. William Chung (“ Subproblem Approximation in Dantzig-Wolfe Decomposition of Variational Inequality Models with an Application to a Multicommodity Economic Equilibrium Model ”) received a B.Eng. degree in industrial engineering from Ryerson University in Toronto, Ontario, Canada, a master's of applied science, and a Ph.D. in management sciences from the University of Waterloo in Waterloo, Ontario, Canada. He is an associate professor in the Department of Management Sciences, City University of Hong Kong. His current research interests are in enhancing modeling methods and solution techniques for large-scale mathematical programming models. Yu Ding (“ A Computable Plug-In Estimator of Minimum Volume Sets for Novelty Detection ”) is an associate professor in the Department of Industrial and Systems Engineering at Texas A & M University. He received his Ph.D. in mechanical engineering from the University of Michigan in 2001. His research interests include systems informatics, machine learning, and quality and reliability engineering. He is a member of INFORMS. Jörn Dunkel (“ Stochastic Root Finding and Efficient Estimation of Convex Risk Measures ”) is a postdoctoral research assistant at the Rudolf Peierls Centre for Theoretical Physics and Junior Research Fellow of Mansfield College at the University of Oxford. He received his Ph.D. from the University of Augsburg and holds an M.Sc. in mathematics and an M.Sc. in physics, both from Humboldt-Universität zu Berlin. His current research interests include stochastic finance (credit risk models, Monte Carlo methods), biophysics (bacterial motility), nonequilibrium systems (active nematics), and relativistic stochastic processes. Gadi Fibich (“ Aggregate Diffusion Dynamics in Agent-Based Models with a Spatial Structure ”) is a professor of applied mathematics at Tel Aviv University. He received his Ph.D. in 1994 from New York University. His research interests include mathematical modeling in economics and management sciences. J. David Fuller (“ Subproblem Approximation in Dantzig-Wolfe Decomposition of Variational Inequality Models with an Application to a Multicommodity Economic Equilibrium Model ”) is a professor in the Department of Management Sciences, Faculty of Engineering, University of Waterloo, in Waterloo, Ontario, Canada. He obtained a B.Sc. in mathematics from Queen's University in Kingston, Ontario, in 1973, an M.Sc. in applied mathematics from the University of British Columbia, in Vancouver in 1975, and a Ph.D. in interdisciplinary studies from the University of British Columbia in 1980. His main research interests are in models of energy markets, and algorithms for their solution. Vishal Gaur (“ Assortment Planning and Inventory Decisions Under Stockout-Based Substitution ”) is an associate professor of operations management at the Johnson Graduate School of Management at Cornell University. His research interests include retail operations and problems on the interface of operations and finance. Chanit Giat (“ The cμ/θ Rule for Many-Server Queues with Abandonment ”) is a Ph.D. student in the Department of Electrical Engineering, Technion, Israel. Her research interests are in stochastic processes, and asymptotic analysis and control of queueing systems. Ro'i Gibori (“ Aggregate Diffusion Dynamics in Agent-Based Models with a Spatial Structure ”) works in the IT and financial services industries. He received his M.Sc. degree in mathematics in 2007 and M.A. degree in psychology in 2003, both from Tel Aviv University. His research interests include stochastic modeling, analysis, and simulation in marketing and networks. Renato Guseo (“ Correction to the Paper ‘Optimal Product Launch Times in a Duopoly: Balancing Life-Cycle Revenues with Product Cost’ ”) is full professor in statistics, since 1994, at the University of Padua, Department of Statistical Sciences, Italy. Educated at the University of Padua, he was assistant professor in statistics at the Catholic University S.C. of Milan, director of the Department of Statistical Sciences at the University of Udine, and presenter of a B.Sc. course in regional economics and firms' networks at the University of Padua. His current research is focused on statistical quality control, design of hierarchical experiments, diffusion of innovations, competition and substitution, cellular automata, network automata, intervention and control in subsystems, oil and gas depletion models, and diffusion of emerging energy technologies. Walter J. Gutjahr (“ Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies ”) is an associate professor in the Department of Statistics and Decision Support Systems at the University of Vienna, Austria. He received his Ph.D. in mathematics and the habilitation in applied mathematics and computer science, both from the University of Vienna. After several years of activity in technical and management positions at Siemens Corporation in the area of information technology, he took a position at the University of Vienna, where he currently teaches applied mathematics and operations research. His research interests include combinatorial optimization, evolutionary computation, analysis of algorithms, software engineering, project management, scheduling, and health-care management. He has published numerous scientific articles, and his papers on ant colony optimization are currently among the most frequently cited articles in the field. Kurt Heidenberger (“ Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies ”) is professor and chair of the Department of Innovation and Technology Management at the University of Vienna, Austria. He received an M.A. in mathematics, a Ph.D. in economics and social science, and the habilitation in business administration, all from the University of Erlangen-Nürnberg, Germany. His research interests include applications of management science and decision-support systems to issues of strategic management, innovation/technology management, and health policy. His work has been published extensively in scientific journals, and he has broad experience in research and consulting with major corporations, government agencies, and international institutes such as the World Health Institute. Dorothée Honhon (“ Assortment Planning and Inventory Decisions Under Stockout-Based Substitution ”) is an assistant professor of operations management at the McCombs School of Business of the University of Texas at Austin. Her research interests include assortment planning, variety theory, retail operations, and inventory management. Particularly, she studies multiproduct problems with customer-driven substitution. Stephen C. Hora (“ An Analytic Method for Evaluating the Performance of Aggregation Rules for Probability Densities ”) is a research professor in engineering and public policy at the University of Southern California, where he also serves as director of the National Center for Risk and Economic Analysis of Terrorism Events. He formerly served at the College of Business and Economics at the University of Hawaii at Hilo where much of the work reported in this article was completed. His interests are in risk and decision analyses of terrorist, technological, and environmental threats and hazards. Jianhua Z. Huang (“ A Computable Plug-in Estimator of Minimum Volume Sets for Novelty Detection ”) is a professor in the Department of Statistics at Texas A & M University. He received his Ph.D. in statistics from the University of California at Berkeley in 1997. His research interests include computational statistics, statistical machine learning, and applications of statistics in economics, business, and engineering. Eric Logan Huggins (“ Inventory Control with Generalized Expediting ”) is an associate professor of management in the School of Business at Fort Lewis College. His research interests include supply-chain management, inventory control, and optimization of sports and games. He works, lives, and plays (not necessarily in that order) in Durango, Colorado. Tetsuo Iida (“ Competition and Cooperation in a Two-Stage Supply Chain with Demand Forecasts ”) is an associate professor at the Faculty of Business Administration, Komazawa University. His research interests include supply chain management and inventory models. Ramesh Johari (“ Investment and Market Structure in Industries with Congestion ”) is an assistant professor at Stanford University, with a full-time appointment in the Department of Management Science and Engineering, and courtesy appointments in the Departments of Computer Science and Electrical Engineering. His research has largely focused on the development of mathematical models for analysis, design, and optimization of large-scale systems, particularly telecom networks and information services. Byungwan Koh (“ An Analysis of the Impact of Passenger Profiling for Transportation Security ”) is a Ph.D. candidate in the School of Management at the University of Texas at Dallas. He obtained his B.A. in business administration from Korea University, Seoul, and M.S. in management engineering from KAIST Graduate School of Management, Seoul. His current research interests are information security and privacy, economics of user profiling, and economics of digital contents. Hai Lan (“ A Confidence Interval Procedure for Expected Shortfall Risk Measurement via Two-Level Simulation ”) is an assistant professor of management science at Antai College of Economics and Management, Shanghai Jiao Tong University, China. His research interests include risk management and simulation in financial engineering. Danilo Macciò (“ Functional Optimization Through Semilocal Approximate Minimization ”) received the M.Sc. degree in telecommunication engineering in 2005 and the Ph.D. degree in mathematical engineering and simulation in 2009 from the University of Genoa, Italy. He is working as a Research Fellow at the Genoa branch of the Institute of Intelligent Systems for Automation of the Italian National Research Council. His research interests include numeric solutions of functional optimization problems, neural networks, and maximum likelihood estimation. Cinzia Mortarino (“ Correction to the Paper ‘Optimal Product Launch Times in a Duopoly: Balancing Life-Cycle Revenues with Product Cost’ ”) has been an associate professor in the Department of Statistical Sciences at the University of Padua, Italy, since 2006. She received her Ph.D. degree in applied statistics to economic and social sciences from the university and served as an assistant professor in the Faculty of Economics at the University of Modena and Reggio Emilia, Italy. Her research interests include design of experiments, statistical quality control, innovation diffusion models, statistical methodology, and applications. Marco Muselli (“ Functional Optimization Through Semilocal Approximate Minimization ”) is a senior researcher at the Institute of Electronics, Computer and Telecommunication Engineering of the Italian National Research Council. His research interests include machine learning, bioinformatics, neural networks, global optimization, mathematical statistics, and probability theory. He is particularly focused on the development of new efficient rule generation methods and their applications in several fields, especially in the solution of biomedical problems. Mahesh Nagarajan (“ Dynamic Supplier Contracts Under Asymmetric Inventory Information ”) is an assistant professor at the Sauder School of Business at the University of British Columbia. He obtained his Ph.D. from the Marshall School of Business at the University of Southern California, Los Angeles. Barry L. Nelson (“ A Confidence Interval Procedure for Expected Shortfall Risk Measurement via Two-Level Simulation ”) is the Charles Deering McCormick Professor and Chair of the Department of Industrial Engineering and Management Sciences at Northwestern University. His research interests are in the design and analysis of stochastic simulation experiments, including multivariate input modeling, optimization via simulation and metamodeling. He is a Fellow of INFORMS. Tava Lennon Olsen (“ Inventory Control with Generalized Expediting ”) is the Ports of Auckland Chair of Operations and Supply Chain Management in the Department of Information Systems and Operations Management at the University of Auckland Business School. Her research interests include supply-chain management, pricing and inventory control, stochastic modeling of manufacturing, service, and health-care systems, queueing systems, and stochastic games. Özalp Özer (“ Information Acquisition for Capacity Planning via Pricing and Advance Selling: When to Stop and Act? ”) is an associate professor of management at the University of Texas at Dallas. Previously he was a faculty member at Columbia University and Stanford University. His general research interest is to investigate the impact of technology and information on the design and control of production and distribution systems, management and coordination of supply chains, and pricing management. This paper represents his long-standing interest in developing decision tools and strategies that can be used by businesses. It was originally motivated by a consulting project with Ericsson. Chiwoo Park (“ A Computable Plug-in Estimator of Minimum Volume Sets for Novelty Detection ”) is a Ph.D. student in the Department of Industrial and Systems Engineering at Texas A & M University. His research interests include predictive modeling, statistical machine learning, and their engineering applications, especially for nanotechnology and sensor network. Joseph Pasia (“ Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies ”) is assistant professor at the Institute of Mathematics, University of the Philippines–Diliman. He received his M.S. degree in applied mathematics from the university in 2001 and a Ph.D. degree in social and economic sciences in 2006 from the University of Vienna, Austria. He is a post-doctoral research fellow at the Faculty of Engineering, Shinshu University, Japan. His research interests include operations research in logistics, evolutionary computation, and multiobjective optimization. Srinivasan Raghunathan (“ An Analysis of the Impact of Passenger Profiling for Transportation Security ”) is a professor of information systems in the School of Management, the University of Texas at Dallas. He obtained a B.Tech. degree in electrical engineering from IIT, Madras, post graduate diploma in management from IIM, Calcutta, and Ph.D. in business administration from the University of Pittsburgh. His current research interests are in the economics of information security and the value of collaboration in supply chains. His papers have been published in journals such as Management Science, Information Systems Research, Journal of MIS, Production and Operations Management, and various IEEE transactions. Ramandeep S. Randhawa (“ On the Accuracy of Fluid Models for Capacity Sizing in Queueing Systems with Impatient Customers ”) is an assistant professor in the Information and Operations Management Department in the Marshall School of Business at the University of Southern California. His research focuses on designing service systems, flexibility in service and production systems, and revenue management. Marion S. Rauner (“ Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies ”) is an associate professor in the Department of Innovation and Technology Management at the University of Vienna, Austria. She received an M.B.A. in business informatics, a Ph.D. in social and economic sciences, and her habilitation in business administration, all from the University of Vienna, Austria, and an M.B.A. in business administration from Vienna University of Economics and Business Administration, Austria. Her research interests include international health-care systems, disease policy modeling, operations research in public health, and the evaluation and management of health-care technologies. She has published widely and was awarded the Young, Talented Scientists Award of the Vienna Municipal Government in 2000, the Pharmig Prize for Health Economics in 2002, and the Dr. Maria Schaumeyer Prize, as well as Kardinal-Innitzer-Prize, in 2003. She has also supported the Austrian sick fund for occupational injuries in optimally allocating prevention budgets since 2001. Sridhar Seshadri (“ Assortment Planning and Inventory Decisions Under Stockout-Based Substitution ”) is a professor in the Information, Risk and Operations Management Department of the McCombs School of Business, University of Texas at Austin. Nahum Shimkin (“ The cμ/θ Rule for Many-Server Queues with Abandonment ”) received his Ph.D. degree in electrical engineering from the Technion, Israel, in 1991. Subsequently he spent a year as a postdoctoral fellow at the Institute of Mathematics and Its Applications, University of Minnesota, and a couple of years as a senior research engineer in the Israeli defense industry. He is currently an associate professor of electrical engineering at the Technion and president of the Israeli Association for Automatic Control. His research interests include stochastic systems and control, queueing systems, reinforcement learning, dynamic games, and game theoretic analysis of communication networks. Greys Sošić (“ Dynamic Supplier Contracts Under Asymmetric Inventory Information ”) is an associate professor of operations management in the Information and Operations Management Department at the Marshall School of Business, University of Southern California. Her research interests include supply chain management, competition and cooperation in supply chains, and applied game theory, with particular emphasis on coalition formation and stability. Jeremy Staum (“ A Confidence Interval Procedure for Expected Shortfall Risk Measurement via Two-Level Simulation ”) is an associate professor of industrial engineering and management sciences and holds the Pentair-Nugent Chair at Northwestern University. His research interests include risk management, simulation in financial engineering, and simulation metamodeling. He serves as department editor for financial engineering at IIE Transactions. Benjamin Van Roy (“ Investment and Market Structure in Industries with Congestion ”) is an associate professor of management science and engineering, electrical engineering, and, by courtesy, computer science, at Stanford University. He is broadly interested in the formulation and analysis of mathematical models that address problems in information technology, business, and public policy. Joachim Wagner (“ Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies ”) is a management consultant. He received his Ph.D. in social and economic sciences from the University of Vienna, Austria, in 2008 and a master's in economical mathematics from the University of Ulm, Germany, in 2004. His research is focused on transfer pricing, internal markets, informational cascades, and disease policy modeling and has been published in journals such as International Journal of the Economics of Business, Zeitschrift fuer betriebswirtschaftliche Forschung, Journal of Economics and Business, and Review of Accounting Studies. Stefan Weber (“ Stochastic Root Finding and Efficient Estimation of Convex Risk Measures ”) is a professor of insurance and financial mathematics at Gottfried Wilhelm Leibniz University, Hannover, Germany. Prior to joining Leibniz University, he was an assistant professor at Cornell University and an honorary associate professor at Maastricht University. His current research interests include risk management and risk measures, Monte Carlo methods, credit risk, optimal portfolio choice, and behavioral finance. Gabriel Y. Weintraub (“ Investment and Market Structure in Industries with Congestion ”) is an assistant professor in the decision, risk, and operations division at Columbia Business School. His research covers several subjects that lie in the intersection between operations research/management science and microeconomics. He is particularly interested in developing mathematical and computational models for the economic analysis of problems in operations. He teaches the core M.B.A. class in operations management and a Ph.D. seminar in microeconomic and game theoretical modeling. Hao Zhang (“ Dynamic Supplier Contracts Under Asymmetric Inventory Information ”) is an assistant professor in the Department of Information and Operations Management at the Marshall School of Business at the University of Southern California. He received his Ph.D. in operations, information, and technology from Stanford University. His current research interests include contract-design theory and applications, incentive and information issues in supply chains, and partially observable Markov decision processes. Paul Zipkin (“ Competition and Cooperation in a Two-Stage Supply Chain with Demand Forecasts ”) is the R. J. Reynolds Professor of Business at the Fuqua School of Business, Duke University. This paper continues his long-standing interest in understanding inventory systems and supply chains.