The Zone Definition Problem in Location-Allocation Modeling

Location-allocation modeling is a frequently used set of techniques for solving a variety of locational problems, some of which can be politically sensitive. The typical application of a location-allocation model involves locating facilities by selecting a set of sites from a larger set of candidate sites, with the selection procedure being a function of “optimality” in terms of the allocation of demand to the selected sites. In this paper we examine the sensitivity of one particular type of location-allocation model, the p-median procedure, to the definition of spatial units for which demand is measured. We show that a p-median solution is optimal only for a particular definition of spatial units and that variations in the definition of spatial units can cause large deviations in optimal facility locations. The broad implication of these findings is that the outcome of any location-allocation procedure using aggregate data should not be relied upon for planning purposes. This has important implications for a large variety of applications.     

The Local Implications of Major Job Transformations in the City: A Spatial Microsimulation Approach

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.     

On-line Model Updating in Hybrid Simulation Tests

Hybrid simulation has emerged as a relatively accurate and efficient tool for the evaluation of structural response under earthquake loading. In conventional hybrid simulation the response of a few critical components is obtained by testing while the numerical module is assumed to follow an analytical idealization. Where there is a much larger number of analytical components compared to the experimental parts, the overall response may be dominated by the idealized parts hence the value of hybrid simulation is diminished. It is proposed to modify the material constitutive relationship of the numerical model during the test, based on the data obtained from the physically tested component. An approach based on genetic algorithms is utilized as an optimization tool to identify the constitutive relationship parameters used in updating the numerical model. The proposed model updating approach is verified through two analytical examples of steel and reinforced concrete frames. The results show the effectiveness of the updating process in minimizing the errors, compared to the assumed exact solution.     

The Shaking Frequency Effect in the Dynamics of a Model Sandy Layer

Experimental results showing the frequency-dependent behavior of both dry and saturated sandy layers subjected to a horizontal excitation on a shaking table are presented. The largest settlements of a dry layer correspond to two specific frequencies. In the case of a saturated layer, there is a single peak frequency corresponding to the largest depth of sinking of a measuring plate in liquefied subsoil. The first peak of settlements coincides with the single peak of sinking in liquefied soil. The eigenfrequencies of the layer were estimated. A modification of the compaction law was proposed for low shaking frequencies.     

The Modifiable Areal Unit Problem,in a Regression Model Whose Independent Variable Is a Distance from a Predetermined Point

This paper deals with the modifiable areal unit problem in the context of a regression model where a dependent variable is an attribute value (say, income) of an atomic data unit (say, a household) and an independent variable is a distance from a predetermined point (say, a central business district) to the atomic data unit (a disaggregated model). We apply this disaggregated model to spatially aggregated data in which the dependent variable is the average income over a spatial unit and the independent variable is the average distance from each household in a spatial unit to the predetermined point (an aggregated model). First, estimating the slope coefficient by the least squares method, we prove that the variance of the estimator for the slope coefficient in the aggregated model is larger than that in the disaggregated model. Second, focusing on variations in the variance of the estimator for the slope coefficient in the aggregated model with respect to the number of zones, we obtain the number of zones in which the variance is close to that in the disaggregated model. Third, we obtain the zoning system that has the minimum variance for a fixed number of zones. We also calculate the maximum variance in order to examine the range of the variance.     

Modeling Migration Careers,Using Data from a British Survey

Development of more sophisticated techniques for modeling longitudinal data has implications for improving our understanding of migration. This paper uses longitudinal data from the British Social Change and Economic Life initiative to disentangle the effects of population heterogeneity, progress through the life cycle and secular change on observed migration differentials. The data consist of retrospective life histories from people sampled in several contrasting localities in Great Britain, in which residential moves can be linked to changes in occupation and household structure. We present a framework for analysis of data of this type using a generalized linear modeling approach, together with results concerning variations in the probability of migration with age, gender, and changes in household and occupational circumstances. Of particular note is the evidence of substantial duration-of-residence effects and an unexpected later-career increase in migration propensity.     

The Effect of Persuasive Messages on Policy Problem Recognition

Prior theories of individual behavior in recognizing public problems have centered on the role of policy entrepreneurs; institutional effects; information; and cultural, political, and social pressures. Our extension of these theories suggests that policy problem recognition is an attitudinal evaluation process. If the information is considered valid and the new attitude is negative in valence, then a policy problem is recognized. To test this theory, we use an embedded experiment in a national survey to measure the effect of persuasive messages on the concern for global warming. We find that the negativity of the message and the credibility of the source of the message both affect the level of increase in concern for global warming. Further, the impact of the message from the source is conditional based upon the recipient's ideology. This suggests that policy problem recognition is attitudinal and thus incorporates both analytical and affective components.     

A Combined Cluster and Interaction Model: The Hierarchical Assignment Problem

This article presents a new spatial modeling approach that deals with interactions between individual geographic entities. The developed model represents a generalization of the transportation problem and the classical assignment problem and is termed the hierarchical assignment problem (HAP). The HAP optimizes the spatial flow pattern between individual origin and destination locations, given that some grouping, or aggregation of individual origins and destinations is permitted to occur. The level of aggregation is user specified, and the aggregation step is endogenous to the model itself. This allows for the direct accounting of aggregation costs in pursuit of optimal problem solutions. The HAP is formulated and solved with several sample data sets using commercial optimization software. Trials illustrate how HAP solutions respond to changes in levels of aggregation, as well as reveal the diverse network designs and allocation schemes obtainable with the HAP. Connections between the HAP and the literature on the p-median problem, cluster analysis, and hub-and-spoke networks are discussed and suggestions for future research are made.     

A Bayesian Approach to Prediction Using the Gravity Model,with an Application to Patient Flow Modeling

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.     

Urban and Rural Estimates of Poverty: Recent Advances in Spatial Microsimulation in Australia

This paper reports on the calculation of poverty rates for small areas in Australia using a spatial microsimulation model. The spatial microsimulation methodology used involves reweighting data from confidentialised unit record files (CURFs) from surveys conducted by the Australian Bureau of Statistics (ABS) to small area census data, also from the ABS. The method is described in this paper, and then maps of poverty using poverty rates derived from this small area estimation method are shown for the eastern coast of Australia and its capital cities. Further analysis of poverty rates in capital cities is then conducted. We find that areas of higher poverty risk can be clearly identified within Sydney, Melbourne, Canberra and Brisbane. We also find that areas of high poverty are frequently ‘buffered’ by areas of moderate poverty. This is not always the case since, in some areas, we find a high poverty area neighbouring a low poverty area but, generally, there appears to be a moderate poverty ‘buffer’ in most capital cities.     

The Problem of Creating a Kazakhstan Metallurgical Base

The author favors early development of the high-phosphorus oolitic iron ores of the Lisakovka deposit in Kustanay Oblast, selecting the area of Irtyshshkoye at the intersection of the Irtysh River and the Middle Siberian Railroad as the best site for an iron and steel plant. A Lisakovka-based steel plant would yield basic slag for fertilizer in the surrounding virgin lands farm territory.     

Development and Evaluation of an Optimal Composite Estimator in Spatial Microsimulation Small Area Estimation

A range of data is of geographic interest but is not available at a small area level from existing data sources. Small area estimation (SAE) offers techniques to estimate population parameters of target variables to detailed scales based on relationships between those target variables and relevant auxiliary variables. The resulting indirect small area estimate can deliver a lower mean squared error compared to its direct survey estimate, given that variance can be reduced markedly even if bias increases. Spatial microsimulation SAE approaches are widely utilized but only beginning to engage with the potential of composite estimators that use a weighted combination of indirect and direct estimators to reduce further the mean squared error of the small area estimate compared to an indirect SAE estimator alone. This article advances these approaches by constructing for the first time in the microsimulation literature an optimal composite estimator for such SAE approaches in which the combining weight is calculated from the mean squared errors of the two estimators; thus, optimizing the reduction in MSE of the resulting small area estimates. This optimal composite estimator is demonstrated and evaluated in a model-based simulation study and application based on the real data.     

A Model to Relate the Size of the Central Business District to the Population of a City

A set of dynamic models of CBD growth are developed. They hypothesize that growth rates depend upon the population growth rate together with the increasing unwillingness of people to travel to the city center as city size increases. A prediction of the model is that absolute decreases in CBD size can occur associated simply with population growth rather than technological change as is usually postulated. The models are tested using retail sales data for the United States. Good predictions are generally found, especially when the unique CBD of New York City is removed from the data set. However, the model which has the greatest theoretical validity relative to central place theory does not have the best fit to the data. Implications of this are discussed, along with those of utilizing transformations in regression models.     

Negotiating Statehood in a Hybrid Political Order: The Case of Somaliland

This article investigates the negotiation of statehood in Somaliland, a non‐recognized de facto state which emerged from Somalia's conflict and state collapse. The negotiation process centres on the continuing transformation of a hybrid political order, involving ‘formal’ as well as ‘informal’ spheres, both in existing institutions (as ‘rules of the game’) and in the bodies or agents enforcing these rules. The negotiation processes considered take place at the national and local level respectively, as well as between the two. These negotiations are heterogeneous, non‐linear and ongoing. The article demonstrates how the polity's tolerance for heterogeneous negotiations and different forms of statehood allowed local political actors to establish peace in their own local settings first. Although it did not produce uniform statehood, it provided the basis for communities to explore the scope for common statehood. On the national level, hybrid elements initially allowed for a healthy adaptation of statehood to local needs, and for legitimate, productive instruments of negotiation. This responsiveness was not maintained, and current hybrid elements threaten to undermine the polity's stability.     

The Aggregation Problem in Location-Allocation

Location-allocation solutions based on aggregate estimates of demand are subject to error because of a loss of locational information during aggregation. It is shown that any method to remove or reduce uncertainty must be solution-specific and therefore impractical, for both median and center classes of problems. The significance of the error is illustrated by simulation of solutions to a number of artificial and real problems. It is suggested that aggregation problems be specifically addressed in applications of location-allocation models, and possible methods are proposed.     

Stuck in a Rut: The Problem with Australia's Electoral Apparatus

The origins of the distinguishing features of the Australian Electoral Commission can be found in nineteenth-century South Australia, when that colony led the world in electoral administration. It was the first jurisdiction to develop a professional, permanent, independent election management body, with salaried electoral officials, and to pursue continuous, State-initiated enrolment. South Australia evolved this way because, to extend path dependence terminology, it was ‘locked out’ of inefficient British practices. After Federation in 1901, the new Australian Electoral Office, largely based on the South Australian model, continued the tradition. One unique and defining feature was the strong, permanent role of divisional returning officers –‘Electoral Kings’, in the words of the first Australian Chief Electoral Officer. The ‘Kings’ were an integral component of much that was good about Australia's way of running elections. However, this structure is no longer the most appropriate for an organisation such as the AEC. It has long outlived its usefulness and is holding the Commission back. And, perhaps ironically for an organisation with a long record of resistance to political interference, it is House of Representatives politicians, of all major parties, who are restraining the AEC from adopting sensible arrangements. The AEC is now, in path dependence terms, ‘locked in’ to inefficient practices.