bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying Areas with Elevated Disease Incidence Rates Using Empirical Bayes Estimators
Authors: Devine Owen J. , Louis Thomas A. , Halloran M. Elizabeth
Published: September 2010

Using maps of observed disease incidence rates to identify regions with potentially elevated risk may be misleading due to the instability of the observed rates in regions with small populations. We use a simulation study to examine the use of maps based on observed incidence rates in identifying such high‐risk areas as compared to maps based on empirical Bayes and constrained empirical Bayes rate estimates. In addition, because the existence of clusters of areas with elevated risk violates the usual distributional assumptions underlying the empirical Bayes approach, we also examine the robustness of the estimates and the impact of incorrect assumptions on identification of high‐risk regions. The simulation results indicate that the observed incidence rates were quite sensitive in terms of identifying areas with truly elevated rates. However, due to the instability of the observed rates, maps based on observed incidence incorrectly identified areas as high risk more frequently than did maps based on the estimators. The standard and constrained empirical Bayes estimates were more stable than the observed rates even when based on incorrect distributional assumptions. The standard empirical Bayes estimates, however, were oversmoothed in that too few areas were identified as having elevated risk. The constrained empirical Bayes approach provided sensitivity closer to that of the observed rates yet with the percentage of areas incorrectly identified as high risk equal to that of the standard empirical Bayes estimates. We illustrate an application of these results with an analysis of the geographic distribution of brain cancer mortality among counties in Ohio.
A Comparison of Three Exploratory Methods for Cluster Detection in Spatial Point Patterns
Authors: Fotheringham A. Stewart , Zhan F. Benjamin
Published: September 2010

This paper compares the performances of three exploratory methods for cluster detection in spatial point patterns where the at‐risk population is known. After reviewing two existing methods, Openshawet al.(1987) and Besag and Newell (1991), an alternative method is introduced. These three methods are then compared empirically using two point patterns drawn from a disaggregate housing database consisting of 28,832 observations. Each observation in the data set contains attributes of single‐family detached dwellings in the City of Amherst, New York. This paper provides some new insights into the performance of the three methods, as previous applications have used spatially aggregated (and hence rather inaccurate) data. The paper also demonstrates the utility of GIS for this type of spatial analysis.
Duration Modeling of Spatial Point Patterns
Authors: Pellegrini Pasquale A. , Reader Steven
Published: September 2010

This paper attempts to further the research by Odland and Ellis (1992) in applying event history methodology to the analysis of spatial point patterns (that is, event patterns). Its empirical focus is the event pattern derived from the adoption of an agricultural innovation, the Harvestore, in southern Ontario, Canada, from 1963 to 1986. Event history analysis involves the use of discrete‐state, continuous‐time stochastic models to investigate a temporal longitudinal record on discrete variables. Event history models are usually concerned with durations of time between events and the effects of intertemporal time dependencies on future event occurrences. As such, they are often referred to as duration models. Many of the methods used in event history analysis allow the use of other nonnegative interval measurements in place of standard temporal intervals to investigate a series of events. In particular, spatial intervals (or durations) of distances between events may also be accommodated by event history models. Our analysis extends the previous research of Odland and Ellis (1992) by using a wider range of parametric models to explore duration dependence, investigating the role of spatial censoring, and using a more extensive set of explanatory variables. In addition, simulation experiments and graphical tests are used to evaluate the empirical event pattern against one generated from Complete Spatial Randomness. Results indicate that the event pattern formed by the Harvestore adopter farms is clustered (that is, is described by positive duration dependency), the sales agent is a significant factor in the distribution of adopters, and that contrasting results are obtained from the analysis using censored data versus uncensored data.
Using Simple Genetic Algorithms to Calibrate Spatial Interaction Models
Authors: Diplock G. , Openshaw S.
Published: September 2010

The paper investigates the use of two genetic algorithms in an attempt to obtain globally optimal parameter estimates for a mix of simple and complex spatial interaction models. The genetic algorithms work well and are strongly advocated as a more robust approach particularly for use with the more complex multiparameter models where the differences in both performance and parameter values are judged to be significant.
A Computational Method for Market Area Analysis on a Network
Authors: Okabe Atsuyuki , Kitamura Masayuki
Published: September 2010

This paper shows a computational method for market area analysis assuming that stores and consumers are distributed over a network and the distance between two points on the network is given by the route distance. First, we consider five basic questions often raised in market area analysis, and show a general method, called the network transformation method, that gives an intuitive way of looking at computational methods for solving these questions. Second, assuming that consumers follow the Huff model, we consider four questions concerning market area delineation and market potential often discussed in market area analysis in practice. We show that the network transformation method is also useful to develop computational methods for solving these questions. One of the notable results is that market area delineation of the Huff model (which is analytically difficult to obtain on a plane) can be exactly obtained on a network.
Modeling the Uncertainty of Slope and Aspect Estimates Derived from Spatial Databases
Authors: Hunter Gary J. , Goodchild Michael F.
Published: September 2010

Estimates of slope and aspect are commonly made from digital elevation models (DEMs), and are subject to the uncertainty present in such models. We show that errors in slope and aspect depend on the spatial structure of DEM errors. We propose a general‐purpose model of DEM errors in which a spatially auto‐regressive random field is added as a disturbance term to elevations. In addition, we propose a general procedure for propagating such errors through GIS operations. In the absence of explicit information on the spatial structure of DEM errors, we demonstrate the potential utility of a worst‐case analysis. A series of simulations are used to make general observations about the nature and severity of slope and aspect errors.
Buffon's Needle and the Probability of Intercepting Short‐Distance Trips by Multiple Screen‐Line Surveys
Authors: Kirby Howard R.
Published: September 2010

For transport planning purposes, information on origin‐destination movements may be obtained by stopping traffic at the roadside and interviewing drivers. The roadside interview stations are usually located so that they lie on one of a number of lines (called screen lines) that cross from one side of the survey area to another. In this way, all movements with the origin on one side of a screen line and the destination on the other are intercepted. For regional surveys, a grid of screen‐lines may be used. The movements intercepted are not, however, representative of all those in the region. That is because shorter‐distance movements are underrepresented; the coarser the grid, the worse the effect. The extent of this underrepresentation is estimated in this paper by calculating the probability of intercepting a trip of given direct length, under the assumption that the screen lines constitute a uniform rectangular grid, and that trips of a given length are distributed over the region at random. The result is an extension to the Buffon needle problem. Ways in which such a result, obtained for an idealized situation, may be extended to apply to more realistic situations, are discussed: in particular it is shown how the trip‐length frequency distribution of all trips may be estimated from that of intercepted trips, using a simple formula that is applicable to a much more general pattern of screen lines.
Statistical Inferences in Bidimensional Regression Models
Authors: Nakaya Tomoki
Published: September 2010

This paper proposes formal procedures of significance tests for bidimensional regression models (Tobler 1994): (1) significance tests of estimated parameters, (2) significance tests of bidimensional correlation coefficient, and (3) significance tests for comparison of bidimensional regression models. These tests are demonstrated by reexamination of the cognitive map study in Kanazawa City (Wakabayashi 1994). The empirical results statistically support the systematic distortion in the cognitive map, enlargement and rotation, indicated by the Euclidean model in the previous study, and discern the affine model as a more proper model that can identify more components of systematic cognitive distortion.
The Influence of Data Aggregation on the Stability of p‐Median Location Model Solutions
Authors: Murray Alan T. , Gottsegen Jonathan M.
Published: September 2010

Location planning often makes use of data in an aggregate form without a clear understanding of the consequences. Although research has been directed toward addressing aggregate data usage in location planning, there have been conflicting findings on the stability of location model solutions obtained using aggregated data. This paper analyzes the question of location model solution stability from a somewhat different perspective than previous researchers in that locational configurations identified for aggregate data are evaluated using the original disaggregate data. Analytical results demonstrate that a high level of solution stability does exist when aggregated data are utilized. Further, this analysis is based upon the use of what can be expected to be worst case aggregation approaches. This suggests that the use of aggregate data is adequate for conducting locational studies.
Rethinking Retail Theory: Circuits of Power as an Integrative Paradigm
Authors: Hallsworth Alan G.
Published: September 2010

Retailers have gained substantial market advantage from the use of locational modeling. This paper suggests that the wider context to their trading should also be borne in mind. A mix of corporate and regulatory influences situates retailers in a system where the concept of power can be very fluid. This paper suggests that the work of Stuart Clegg may help unravel some of the complexities and it utilizes case studies to illustrate particular strategic power plays in retailing.
Calibration and Test of a Discrete Choice Model with Endogenous Choice Sets
Authors: Dai Jian
Published: September 2010

Conventional discrete choice models assume implicitly that the choice set is independent of the decisionmaker's preferences conditional on the explanatory variables of the models. This assumption is implausible in many choice situations where the decisionmaker selects his or her choice set. This paper estimates and tests a discrete choice model with endogenous choice sets based on Horowitz' theoretical work. To calibrate the model, a new probability simulator is introduced and a sequential estimation procedure is developed. The model and calibration methods are tested in an empirical application as well as Monte Carlo simulations. The empirical results are used to test the theory of endogenous choice sets and to examine the differences between the new model and a conventional choice model in parameter estimates and predicted choice probabilities. The empirical results strongly suggest that ignoring the endogeneity of choice sets in choice modeling can have serious consequences in applications.
Measuring Diversity: Choice in Local Housing Markets
Authors: Les Magdalena , Maher Chris
Published: September 2010

In this paper a method of measuring object diversity, based on an application of a diversity index, is proposed. The problem of finding an appropriate measure of diversity is formulated as a projection from a finite‐dimensional space onto a one‐dimensional space. In such an approach, the measure of diversity is expressed in the form of a one‐dimensional descriptor (index). Properties of the index, such as exactness of measurement of diversity and examination of the behavior of the index as a function in three‐dimensional space, are described and illustrated. A procedure for normalizing the index and identifying characteristic points for the interpretation of the results is proposed. The utilization of characteristic points and a fuzzy set theory to distinguish the levels of diversity is also proposed. An application of the method to measure the diversity of the housing stock in local areas of some Australian cities is presented. A further application of the normalized diversity index, that is, to find a relationship between housing diversity and population characteristics in particular areas, is also developed.
The Impact of U.S. Airline Deregulation on Airport Traffic Patterns
Authors: Reynolds‐Feighan Aisling J.
Published: September 2010

This paper surveys changes in the U.S. National Airway System since the 1960s. The most appropriate measures for summarizing air traffic distributions at airports are investigated, with the Gini Index of Concentration being used extensively to analyze U.S. airport traffic patterns over a twenty‐four‐year period. The properties of the Gini index and other measures are compared and discussed in detail in the context of analyzing air traffic distributions. It is shown how concentration in the traffic patterns at the larger airports was at a high level prior to deregulation, but since 1978, the patterns have gradually become even more concentrated.
Optimization in an Error Backpropagation Neural Network Environment with a Performance Test on a Spectral Pattern Classification Problem
Authors: Fischer Manfred M. , Staufer Petra
Published: September 2010

This paper attempts to develop a mathematically rigid framework for minimizing the cross‐entropy function in an error backpropagating framework. In doing so, we derive the backpropagation formulae for evaluating the partial derivatives in a computationally efficient way. Various techniques of optimizing the multiple‐class cross‐entropy error function to train single hidden layer neural network classifiers with softmax output transfer functions are investigated on a real‐world multispectral pixel‐by‐pixel classification problem that is of fundamental importance in remote sensing. These techniques include epoch‐based and batch versions of backpropagation of gradient descent, PR‐conjugate gradient, and BFGS quasi‐Newton errors. The method of choice depends upon the nature of the learning task and whether one wants to optimize learning for speed or classification performance. It was found that, comparatively considered, gradient descent error backpropagation provided the best and most stable out‐of‐sample performance results across batch and epoch‐based modes of operation. If the goal is to maximize learning speed and a sacrifice in classification accuracy is acceptable, then PR‐conjugate gradient error backpropagation tends to be superior. If the training set is very large, stochastic epoch‐based versions of local optimizers should be chosen utilizing a larger rather than a smaller epoch size to avoid unacceptable instabilities in the classification results.
The Detection of Clusters Using a Spatial Version of the Chi‐Square Goodness‐of‐Fit Statistic
Authors: Rogerson Peter A.
Published: September 2010

A test statistic for the detection of spatial clusters is developed by generalizing the common chi‐square goodness‐of‐fit test. The paper includes a discussion of the relationship between the statistic and other associated statistics, and provides an analysis of both its null distribution and power. The paper concludes with the development of a local version of the statistic and an application to leukemia clustering in central New York.
Two New Location Covering Problems: The Partial P‐Center Problem and the Partial Set Covering Problem
Authors: Daskin Mark S. , Owen Susan Hesse
Published: September 2010

Two new covering problems are introduced. The partial covering P‐center problem minimizes a coverage distance in such a way that a given fraction of the population is covered. The partial set covering problem seeks the minimum number of facilities needed to cover an exogenously specified fraction of the population within a given coverage distance. The problems are formulated as integer linear programming problems. Bisection search algorithms are outlined for the two problems. The search algorithm repeatedly solves a Lagrangian relaxation of the maximal covering problem. Computational results for the Lagrangian relaxation of the maximal covering problem and for the bisection search algorithms are presented on problems with up to 150 nodes.
Incorporating Soil Associations into Linear Programming Models for Development of Irrigation Scenarios
Authors: He Chansheng
Published: September 2010

An inadequate streamflow supply in Saginaw Bay, Michigan, affects the irrigation development in the region. Linear programming (LP) models are developed in this paper to help irrigation planners determine optimal irrigation scenarios. To incorporate the spatial variations of the soil and climate into the optimization models, soil associations are used as the basic analysis unit for estimating crop yields, irrigation requirements, and expected economic returns. The yields and irrigation requirements of corn, drybeans, and soybeans are simulated by the CERES‐MAIZE, BEANGRO, and SOYGRO models at each of the twelve soil associations in the study area over the period of 1951–1980. The yield and irrigation requirement of sugarbeets are simulated by the YIELD model for all the soils in the study area over the period of 1956–1987. The crop prices, simulated crop yields and irrigation requirements, and variable costs are used to compute the expected gross margins and other coefficients in the LP models. The optimization results provide irrigation scenarios that are linked to specific soil associations, which are more useful to decision makers for identifying and targeting individual soils for irrigation development than are the spatially lumped optimal solutions. This study demonstrates that through integration of GIS and simulation models, spatial variations of the climate, soil, and water resources can be better represented in the optimization models to produce more realistic irrigation scenarios.
Market Rules and Spatial Outcomes: Insights from the Corporate Restructuring of U.S. Food Retailing
Authors: Wrigley Neil
Published: September 2010

In this paper a study of the corporate restructuring of the U.S. food retail industry, during and following the period of regulatory relaxation and high‐leverage capital transformations of the 1980s, is used to interrogate the complex relationships between market regulation, investment regimes, corporate strategies, and spatial outcomes. It is shown that changes in the “rules” governing investment and competition in the United States in the 1980s triggered countervailing spatial processes in the food retail industry. Those processes took more than a decade to work themselves through, but by the late 1990s a radically altered corporate landscape was beginning to emerge. In particular, consolidation of the industry had finally gained momentum–creating an industry whose leading firms are likely by 2002 to have a market share double the level of the early 1990s. The paper concludes by considering the insights which a consideration of corporate restructuring and regulation in this U.S. industry offers for some important areas of conceptual debate in economic geography. In particular, it is argued that industries in which capital structure transformations of the firm must be confronted and treated as a central issue have an intrinsic, but until recently neglected, importance in theoretical debate in the discipline.
Spatial Characteristics and Comparisons of Interaction and Median Clustering Models
Authors: Murray Alan T.
Published: September 2010

Cluster analysis has been pursued from a number of directions for identifying interesting relationships and patterns in spatial information. A major emphasis is currently on the development and refinement of optimization‐based clustering models for the purpose of exploring spatially referenced data. Within this context, two basic methods exist for identifying clusters that are most similar. An interesting feature of these two approaches is that one method approximates the relationships inherent in the other method. This is significant given that the approximation approach is invariably utilized for cluster detection in spatial and aspatial analysis. A number of spatial applications are investigated which highlight the differences in clusters produced by each model. This is an important contribution because the differences are in fact quite significant, yet these contrasts are not widely known or acknowledged.
Combining Geostatistical Methods and Hierarchical Scene Models for Analysis of Multiscale Variation in Spatial Data
Authors: Collins John B. , Woodcock Curtis E.
Published: September 2010

Concepts from Hierarchical Analysis of Variance (ANOVA) can be combined with ideas from geostatistics to describe the multiscale structure of spatial data. Hierarchical ANOVA involves modeling spatial data as the sum of effects associated with processes acting at different spatial scales. These effects can be modeled as stationary regionalized variables, whose spatial structure can be described using the variogram. According to this model, the variogram of the spatial data is the sum of variograms and cross‐variograms of the effects. Whereas hierarchical ANOVA reveals the relationship between scale and variability, the hierarchical decomposition of the variogram relates scale with spatial structure. This analysis method can reveal otherwise undetected features of spatial data, and can guide further analysis.
Spatial Analysis of the Factors Contributing to the Relationship between the Transient, Meridional Eddy Sensible, and Latent Heat Flux in the Southern Hemisphere
Authors: Raphael Marilyn , Cherry Steve
Published: September 2010

In this paper principal component analysis (PCA) and singular value decomposition (SVD) are used to define the importance of the variables contributing to the relationship between the transient latent and sensible heat fluxes and to show their temporal and spatial variation. SVD is offered as an alternative means of isolating spatial and temporal structures in data with the advantage that it can depict simultaneous space‐time variations that are aggregates of the results produced by PCA. Both methods of analysis produced two very important uncorrelated modes of variability in January and July, indicating that the transient heat fluxes are influenced by few controlling factors. We suggest that these modes of variability represent the influences of the meridional temperature gradient, atmospheric moisture, and activity within the source and sink regions of the transient heat fluxes. The physical relationships between the heat fluxes that appear to represented by the statistical modes of variability are discussed.
Evaluation of Zone Orderings Based on the Correlation of Order Differences and Distances
Authors: Ohsawa Yoshiaki , Koshizuka Takeshi
Published: September 2010

When two‐dimensional zones are arranged into one‐dimensional tables, spatial characteristics on the original space should be preserved as much as possible. In this respect, we evaluate nine systematically generated zone orderings based on the magnitude of the Pearson's correlations of the order differences and the Euclidean distances. We show that standard row order is the best. The sensitivity of the shape and size of the study area, the critical distance, and the level of zonal aggregation are also examined.
A Bayesian Approach to Prediction Using the Gravity Model, with an Application to Patient Flow Modeling
Authors: Congdon Peter
Published: September 2010

This paper investigates the potential for estimation and prediction by Bayesian methods of hospitalization flows classified by place of residence and hospital site. The focus is especially with respect to emergency (unplanned) admissions to hospitals. The need for strategic modeling and forecasting arises since the structure of U.K. emergency service provision is subject to changes involving site closures or changes in bed numbers. The gravity model, reflecting patient demand, hospital supply, and distance effects has been applied to patient flows, but generally in a situation of unchanged destination states. It may be modified, however, in accordance with major changes in hospital service structure, to include access effects (the interplay of supply and distance) and temporal variation in its parameters. Therefore, prediction may be applied to a “new” situation defined, for example, by closures of entire hospital sites. The modeling approach used may be adapted to other flow models where destinations may be added or eliminated (for example, trade‐area models). A case study involves a sector of London subject to such a restructuring following the U.K. government's 1997–98 review of London's emergency services.
Influence of Race on Household Residential Utility
Authors: Sermons M William
Published: September 2010

Residential location choice models are an important tool employed by urban geographers, planners, and transportation engineers for understanding household residential location behavior and for predicting future residential location activity. Racial segregation and residential racial preferences have been studied extensively using a variety of analysis techniques in social science research, but racial preferences have generally not been adequately incorporated into residential location choice models. This research develops residential location choice model specifications with a variety of alternative methods of addressing racial preferences in residential location decisions. The research tests whether social class, family structure, and in‐group racial preferences are sufficient to explain household sensitivity to neighborhood racial composition. The importance of the interaction between the proportion of in‐group race neighbors and other‐race neighbors is also evaluated. Models for the San Francisco Bay metropolitan area are estimated and evidence of significant avoidance behavior by households of all races is found. The results suggest that social class differences, family structure differences, and in‐group racial preferences alone are not sufficient to explain household residential racial preference and that households of all races practice racial avoidance behavior. Particularly pronounced avoidance of black neighbors by Asian households, Hispanic neighbors by black households, and Asian neighbors by white households are found. Evidence of a decrease in household racial avoidance intensity in neighborhoods with large numbers of own‐race neighbors is also found.
A Statistical Method for Analyzing the Relative Location of Points in a Bounded Region
Authors: Sadahiro Yukio , Takami Kentaro
Published: September 2010

This paper develops a statistical method for analyzing the relative location of points in a bounded region. The location of points in relation to the center of the region in which they are located is discussed. Four spatial objects called reference objects are defined to represent the relative location: (1) the boundary, (2) skeleton, (3) nucleus, and (4) global center. The distribution of distance between points and a reference object yields a cumulative distribution function (CDF). Comparison of CDFs for a reference object allows us to analyze whether the points tend to be located close to the reference object or, for instance, whether the points are clustered around the center of the region. The significance of the CDF is statistically tested by Monte Carlo simulation. The method proposed is applied to the distribution of restaurants in retail clusters.
Multiscale Statistical Models for Hierarchical Spatial Aggregation
Authors: Kolaczyk Eric D. , Huang Haiying
Published: September 2010

Scale dependency is an inherent property of geographic phenomena since most geographic patterns under observation vary with scale. Across numerous disciplines, including geography, various types of so‐called “multiscale” models have been used for the task of modeling and understanding the effects of scale. However, most of these models are descriptive—as opposed to inferential—in nature, and few of them (particularly outside geography) are well adapted to the wide variety of data structures typically encountered in geography. In this paper, we introduce a new, general framework for multiscale statistical modeling and inference that is explicitly designed for a broad class of geographic data. The key structural assumption underlying these models is that of a set of hierarchically defined partitions, corresponding to successive aggregations of an initial data space. Within our framework the effects of scale associated with such aggregation are captured through a fundamental decomposition of the data likelihood, directly induced by the hierarchical nature of the partitions, into individual components of local information at all possible spatial resolutions. Upon combining these multiscale likelihoods with an appropriately defined Bayesian prior probability structure, a powerful inferential framework results. We describe in detail how this framework may be used for the tasks of statistical estimation and classification, and illustrate its usage with an analysis of data from census geography.
Specification of the World City Network
Authors: Taylor Peter J.
Published: September 2010

World cities are generally deemed to form an urban system or city network but these are never explicitly specified in the literature. In this paper the world city network is identified as an unusual form of network with three levels of structure: cities as the nodes, the world economy as the supranodal network level, and advanced producer service firms forming a critical subnodal level. The latter create an interlocking network through their global location strategies for placing offices. Hence, it is the advanced producer service firms operating through cities who are the prime actors in world city network formation. This process is formally specified in terms of four intercity relational matrices—elemental, proportional, distance, and asymmetric. Through this specification it becomes possible to apply standard techniques of network analysis to world cities for the first time. In a short conclusion the relevance of this world city network specification for both theory and policy‐practice is briefly discussed.
Reevaluating the Relationship Between In‐, Out‐, and Net Migration for Nonmetropolitan Counties: An Update on Beale's U‐Shaped Curve
Authors: Vias Alexander C.
Published: September 2010

The relationship of gross migration to net migration is continuously undergoing reevaluation in the literature. However, one major finding by Beale (1969) that produced the famous u‐shaped curve has received little attention, a surprising situation considering the significant changes that have taken place in rural America since 1969. In this paper I use gross migration data from IRS returns for 1995–1998, and differentiate the rates using a number of classification schemes developed by the USDA and the Census Bureau. The results show that rural America is a diverse place, and that migration rates vary tremendously depending on the geographic, economic, and social characteristics of the county. Furthermore, the relationship between gross and net migration varies much more than previously suggested, especially in negative net migration counties, a finding with implications for migration theory and public policy.
The Local Implications of Major Job Transformations in the City: A Spatial Microsimulation Approach
Authors: Ballas Dimitris , Clarke Graham P.
Published: September 2010

The changing dynamics of regional and local labor markets during the last decades have led to an increasing labor market segmentation and socioeconomic polarization and to a rise of income inequalities at the regional, urban, and intraurban level. These problems call for effective social and local labor market policies. However, there is also a growing need for methods and techniques capable of efficiently estimating the likely impact of social and economic change at the local level. For example, the common methodologies for estimating the impacts of large firm openings or closures operate at the regional level. The best of these models disaggregate the region to the city (Armstrong 1993; Batey and Madden 1983). This paper demonstrates how spatial microsimulation modeling techniques can be used for local labor market analysis and policy evaluation to assess these impacts (and their multiplier effects) at the local level‐to measure the effects on individuals and their neighborhood services. First, we review these traditional macroscale and mesoscale regional modeling approaches to urban and regional policy analysis and we illustrate their merits and limitations. Then, we examine the potential of spatial microsimulation modeling to create a new framework for the formulation, analysis and evaluation of social and local labor market policies at the individual or household level. Outputs from a local labor market microsimulation model for Leeds are presented. We show how first it is possible to investigate the interdependencies between individual's or households labor market attributes at the microscale and to model their accessibilities to job opportunities in different localities. From this base we show how detailed what‐if microspatial analysis can be performed to estimate the impact of major changes in the local labor market through job losses or gains, including local multiplier effects.
Concentration Effects, Spatial Mismatch, or Neighborhood Selection? Exploring Labor Market and Neighborhood Variations in Male Unemployment Risk Using Census Microdata from Great Britain
Authors: Fieldhouse Edward , Tranmer Mark
Published: September 2010

A classification of census enumeration districts has recently been added to the 1991 British Census 2% Sample of Anonymised Records (SAR). Through the use of multilevel modeling techniques, the area classification information on the SAR is used to investigate geographical differences in unemployment. Previous research has indicated that where a person lives can affect their propensity to unemployment. However, the understanding of these relationships are confounded by the reciprocal nature of the relationship between unemployment, housing, and geographical location. This paper examines the relative importance of the individual, the type of neighborhood of residence, and the local labor market in which one lives in explaining variations in unemployment risk. It also examines the role of housing tenure at an individual and contextual level in mediating this relationship. Two competing hypotheses are evaluated. The first is that local concentrations of unemployment are the result of the process of neighborhood selection. The other suggests there are contextual affects on unemployment risk, which may include access to job opportunities and “concentration effects.” The paper concludes that most neighborhood level variation in unemployment is due to housing market effects, particularly neighborhood selection. As well as offering insights into the relationship between unemployment and geographical location, this paper aims to demonstrate methodological innovations in the analysis of census microdata. In particular it shows how area classifications can be used in conjunction with microdata in a multilevel modeling framework, to get a better understanding of the role of individual and contextual factors in social processes.
Securitization of Longevity Risk Using Percentile Tranching
Authors: Kim Changki , Choi Yangho
Published: September 2010

Abstract

Securitizations that transfer risk to the financial markets are a potential solution to longevity risk in the annuity business. The classical Lee–Carter model is applied to generate the future stochastic survival distribution. A method to design inverse survivor bonds using percentile tranches and to calculate the security prices is presented. The percentile tranche method is a simple and practical way for the issuer to design and price the security. This method can serve to identify the risk–yield relationship, which can provide investors with clear insight regarding the appropriate choice of tranches.
Complexity and Adaptivity in Supply Networks: Building Supply Network Theory Using a Complex Adaptive Systems Perspective*
Authors: Pathak Surya D. , Day Jamison M. , Nair Anand , Sawaya William J. , Kristal M. Murat
Published: September 2010

Supply networks are composed of large numbers of firms from multiple interrelated industries. Such networks are subject to shifting strategies and objectives within a dynamic environment. In recent years, when faced with a dynamic environment, several disciplines have adopted the Complex Adaptive System (CAS) perspective to gain insights into important issues within their domains of study. Research investigations in the field of supply networks have also begun examining the merits of complexity theory and the CAS perspective. In this article, we bring the applicability of complexity theory and CAS into sharper focus, highlighting its potential for integrating existing supply chain management (SCM) research into a structured body of knowledge while also providing a framework for generating, validating, and refining new theories relevant to real‐world supply networks. We suggest several potential research questions to emphasize how a CAS perspective can help in enriching the SCM discipline. We propose that the SCM research community adopt such a dynamic and systems‐level orientation that brings to the fore the adaptivity of firms and the complexity of their interrelations that are often inherent in supply networks.
Vertical Integration with Price‐Setting Competitive Newsvendors*
Authors: Wu Chongqi , Petruzzi Nicholas C. , Chhajed Dilip
Published: September 2010

This article addresses the problem of distribution channel design under demand uncertainty. We consider two manufacturers, each producing a substitutable product and selling it through either a decentralized or an integrated retail store, which is modeled as a price‐setting newsvendor. A multiplicative demand function incorporating a random shock term is assumed. Of primary interest is how demand uncertainty and production cost affect the equilibrium distribution channel structure. Results indicate the following: On the one hand, if the random shock term is uniformly distributed on [0, x], then the equilibrium design does not depend on the variance of the shock. On the other hand, if the random shock term is uniformly distributed on [1 −r, 1 +r], then the equilibrium design does depend on the variance of the shock. In particular, an increase in r favors the integrated structure where both channels are integrated and hurts the decentralized configuration where both channels are decentralized. Additionally, we explain the qualitative similarities and differences between the structural properties of the equilibrium distribution channel structure when demand is, and is not, uncertain. We also establish that production cost always favors the decentralized structure, while it hurts the integrated one. One important managerial implication of our study is that, by reducing the number of decisions made in supply chains, the impact of demand uncertainty can be controlled to a certain extent.
“There Must be Mouse Dirt with the Pepper”: A Lutheran Approach to Choosing Songs1
Authors: Tönsing Gertrud
Published: September 2010

Abstract:  This paper stems from my doctoral research on the question, “What is a good song?” It is a response to the Praise and Worship movement, which started within the charismatic churches, but also has spread to many mainline churches, including my own in South Africa. While I am supportive of much that is good in this movement, I am also critical of the content and theology of many of the songs. This paper focuses on what we as Lutherans can learn from our founder when it comes to choosing what and how to sing in our services.
Keeping in Tune with the Times—Praise & Worship Music as Today's Evangelical Hymnody1 in North America
Authors: Hartje Gesa F.
Published: September 2010

Abstract:  In the heated discussion about different church music styles, one aspect often gets overlooked: the similarities between traditional hymns and the modern or contemporary Praise and Worship music (P&W). Aiming at unfolding some of these similarities, this article contemplates technological, sociological, and theological perspectives to reveal parallels between the two practices and postulates P&W as today's evangelical hymnody in North America.
A Tale of Two Politico-Economic Systems: Implications for Entrepreneurship in Central and Eastern Europe
Authors: Ireland R. Duane , Tihanyi Laszlo , Webb Justin W.
Published: September 2010

Following the collapse of socialism in the late 1980s, Central and Eastern European countries initiated attempts to adopt capitalist economic frameworks and promote entrepreneurship. However, persistent economic difficulties and high levels of unemployment have led to dissatisfaction with political parties favoring capitalism. We integrate identity, institutional, and social movement theories to describe the emergence of four competing social movements (capitalist democracy, socialist command, social democracy, and populist command) that are undertaken to pursue politico–economic reforms. We discuss the implications for developing an entrepreneurial culture in Central and Eastern Europe.
Toward a Theoretical Basis for Understanding the Dynamics of Strategic Performance in Family Firms
Authors: Chrisman James J. , Steier Lloyd P. , Chua Jess H.
Published: September 2010

An important distinction between family and nonfamily firms and among different types of family firms is the manner in which strategy is formulated and implemented. These differences in strategic behaviors can cause variations in firm performance. Understanding the nature of these differences and how the family form of organization drives them therefore contributes to the development of a strategic management theory of the family firm, a unifying theme of the series of special issues published in Entrepreneurship Theory and Practice to date. This article briefly reflects on the progress made in understanding the strategic differences of family firms in this ongoing series and discusses the contributions of the articles and commentaries contained in this fifth special issue on theories of family enterprise.
Culture of Family Commitment and Strategic Flexibility: The Moderating Effect of Stewardship
Authors: Zahra Shaker A. , Hayton James C. , Neubaum Donald O. , Dibrell Clay , Craig Justin
Published: September 2010

The ability of family firms to identify and respond to changes in their external environments can be a key source of competitive advantage leading to success and survival. Some research, however, has suggested family firms are conservative and often lack the ability to adapt to their changing competitive environments. Using data from 248 family firms, we found a family firm's culture of commitment to the business is positively associated with its strategic flexibility—the ability to pursue new opportunities and respond to threats in the competitive environment. Further, we found stewardship–oriented organizational culture positively moderated the family commitment–strategic flexibility relationship.
Estimating Left Ventricular Ejection Fraction from Two‐Dimensional Echocardiograms: Visual and Computer‐Processed Interpretations
Authors: WONG MAYLENE , BRUCE STEVEN , JOSEPH DAVID , LIVELY HARRY
Published: September 2010

Digital echocardiography makes computer‐processed estimates of ejection fraction feasible for clinical use but increases physician reading time. The practicabilities were examined by three novice fellows and four experienced attendings. Ejection fraction was visually estimated from playback of videotape or cine‐loop displays. Ejection fraction was also estimated from single tracings of endocardium, digitized and applied to biplane Simpson's rule, and expressed in whole units. Differences between fellows' and attendings' visual estimates were close to 0 ± 6.4 median standard deviation. The 95% confidence intervals for reproducing visual and computer‐processed ejection fractions ranged from 15% to 46% of mean ejection fraction; for comparing the two methods, from 7% to 36%. Intraobserver reading errors varied widely and with one observer, systematically, and were independent of experience, but dependent on the quality of signals. Computer‐processed readings of ejection fraction should be reserved for images of reasonable quality and for confirming visually estimated ejection fractions between the lower limits of normal (45%‐50%) to moderately severely depressed (25%‐30%), when accuracy is clinically relevant or when a serial change is at the confidence limits of the reader and needs verification. (ECHOCARDIOGRAPHY, Volume 8, January 1991)
Correlations Between Cardiac Imaging and Electrophysiological Studies: What is the State of the Art?
Authors: MARTINS JAMES B. , COLLINS STEVEN M. , FISHER DAVID J.
Published: September 2010

Changes in ventricular activation produced by bundle branch block, pre‐excitation, and ventricular tachycardia and pacing have been studied by various cardiac imaging modalities. We reviewed results of previously published and newly generated imaging data correlated with known or measured electrophysiological studies. Echocardiography has been demonstrated to grossly correlate with abnormal ventricular wall motion when activation sequence was altered. However, phase analysis of radionuclide and cine‐computed tomography have provided detailed noninvasive activation data that correlated reasonably well with measured electrical activation sequence in both animals and man. Analysis of wall motion may not predict activation sequence when muscle is damaged or excessive translational movement of the heart occurs. Body surface mapping of electrical potentials has the capability to accurately but noninvasively register an electrical activation image of the heart that circumvents the problems of imaging contraction sequence. In the future, body surface potential mapping should be more widely used clinically and experimentally. (ECHOCARDIOGRAPHY, Volume 8, January 1991)
Use of Saline Contrast Echo Timing to Distinguish Intracardiac and Extracardiac Shunts: Failure of the 3‐ to 5‐Beat Rule
Authors: Freeman Jonathan A. , Woods Timothy D.
Published: September 2010

Patent foramen ovale (PFO) is thought to be associated with cryptogenic stroke and migraine headache. Saline contrast echocardiography (SCE) is the gold standard for identifying the presence of right‐to‐left shunt, whether from PFO or pulmonary arteriovenous malformation (PAVM). The timing of left heart contrast entry during SCE is used to distinguish a PFO from a PAVM, a method that is not as specific as previously thought. In this report, we describe a patient with a SCE demonstrating the early appearance of left heart bubbles during good effort Valsalva injections that is ultimately proven to be due to a PAVM. The case illustrates the limited specificity of left heart contrast timing during SCE as the sole criteria for differentiating intracardiac and extracardiac shunts.