Spatial Patterns of Headquarters

This study of the spatial concentration of the headquarters of exchange-listed companies suggests that the relevancy of the "efficiency parameter" of agglomeration theory still holds in explaining the location of headquarters, especially when the production function is reinterpreted as a productivity function. The sample of 5189 headquarters exceeds previous studies of Fortune 500 firms. Across industries, a high degree of clustering is found: 40% of the nation's headquarters were found in twenty counties. Cluster analysis suggests grouping patterns for headquarters; discriminant analysis confirms the uniqueness of these spatial clustering patterns across 229 urban counties. For certain industries, the clustering occurs within small areas. The headquarters of these spatially-correlated groups of firms money and media, gas and electric, business services, and machining technology were mapped at the county and zipcode level for counties within major metropolitan areas. The spatial density patterns take on traditional urban forms: core, ring and wedge.

The Survival and Birth of Firms

Using a modified form of the location quotient, a "growth quotient," this study traces the survival and growth for the headquarters of publicly listed firms in the United States. At the county level, the spatial concentrations of headquarters listed in 1997 are correlated with the spatial concentrations of corporate headquarters that survived from 1986 though 1996. Counties that house the headquarters of many different survival firms continue to spawn new headquarters. Counties with headquarters of survival firms in only one or two industries tend to maintain and spawn firms in only those industries. These conclusions support the Porter thesis that firms will spatially cluster for competitive advantage.

Spatial Concentration of Institutional Property Ownership: New Wave Atomistic or Traditional Urban Clustering

NCREIF investors acquire property in counties that meet socioeconomic filtering criteria. In contrast to atomistic predictions, these investors acquire their apartment buildings, offices, retail facilities, and warehouses in density clusters. These clusters follow a model of a negative exponential demand curve, a model that previously explained the technologically caused density gradient of urban areas. Institutional investors signal their belief that clustering of properties is a value dimension.

Dilettante, Venturesome, Tory and Crafts: Drivers of Performance Among Taxonomic Groups

Empirical research has failed to cumulate into a coherent taxonomy of small firms. This may be because the method adapted from biology by Bill McKelvey has almost never been adopted. His approach calls for extensive variables and a focused sample of organizations, contrary to most empirical studies, which are specialized. Comparing general and special purpose approaches, we find some of the latter have more explanatory power than others and that general purpose taxonomies have the greatest explanatory power. Examining performance, we find the types do not display significantly different levels of performance but they display highly varied drivers of performance

The Relationship between School Learning Climate and Student Achievement

Based on the review of the literature and research, the relationship of school learning climate and student achievement is explored. Common ideological, organizational, and leadership factors characteristic of high-achieving, effective schools are identified and their relationships examined. Ideological factors identified are: 1) A belief that all students are expected by staff to reach high levels of achievement; 2) A belief that individual and school-wide performance on achievement tests is an appropriate goal and measure of school effectiveness; and 3) A belief that self-concept is an important factor in student achievement. Organizational factors identified are: 1) High degree of trust; 2) High level of satisfaction and morale; 3) Opportunity for input; and 4) Safe and orderly environment. Leadership factors examined are: 1) Sense of vision; 2) Clearly stated goals and expectations; 3) Effective communication skills; and 4) Strong instructional leadership

Merging remotely sensed data with geophysical models

Thesis (Ph.D.) University of Alaska Fairbanks, 1996Geophysical models are usually derived from the idealistic viewpoint that all required external parameters are, in principle, measurable. The models are then driven with the best available data for those parameters. In some cases, there are few measurements available, because of factors such as the location of the phenomena modeled. Satellite imagery provides a synoptic overview of a particular environment, supplying spatial and temporal variability as well as spectral data, making this an ideal source of data for some models. In other cases, although frequent satellite image observations are available, they are of little use to the modeler, because they do not provide values for the parameters demanded by the model. This thesis contains two examples of geophysical models that were derived expressly to utilize measurements and qualitative observations taken from satellite images as the major driving elements of the model. The methodology consists of designing a model such that it can be 'run' by numerical data extracted from image data sets, and using the image data for verification of the model or adjustment of parameters. The first example is a thermodynamic model of springtime removal of nearshore ice from an Arctic river delta area, using the Mackenzie River as a study site. In this example, a multi-date sequence of AVHRR images is used to provide the spatial and temporal patterns of melt, allowing the required physical observations in the model to be parameterized and tested. The second example is a dynamic model simulating the evolution of a volcanic ash cloud under the influence of atmospheric winds. In this case, AVHRR images are used to determine the position and size of the ash cloud as a function of time, allowing tuning of parameters and verification of the model

Confinement contains condensates

Dynamical chiral symmetry breaking and its connection with the generation of hadron masses has historically been viewed as a vacuum phenomenon. We argue that confinement makes such a position untenable. If quark-hadron duality is a reality in QCD, then condensates, those quantities that were commonly viewed as constant empirical mass-scales that fill all spacetime, are instead wholly contained within hadrons; viz., they are a property of hadrons themselves and expressed, e.g., in their Bethe-Salpeter or light-front wave functions. We explain that this paradigm is consistent with empirical evidence, and incidentally expose misconceptions in a recent Comment.Comment: 10 pages, 2 figure

Essence of the vacuum quark condensate

We show that the chiral-limit vacuum quark condensate is qualitatively equivalent to the pseudoscalar meson leptonic decay constant in the sense that they are both obtained as the chiral-limit value of well-defined gauge-invariant hadron-to-vacuum transition amplitudes that possess a spectral representation in terms of the current-quark mass. Thus, whereas it might sometimes be convenient to imagine otherwise, neither is essentially a constant mass-scale that fills all spacetime. This means, in particular, that the quark condensate can be understood as a property of hadrons themselves, which is expressed, for example, in their Bethe-Salpeter or light-front wavefunctions.Comment: 5 pages, 1 figur

The Effect of Commercial Bank Ownership on the Composition of the Loan Portfolio

Thomas Stanley is an Associate Professor of Finance, T. Chotigeat is Professor of Economics, and Craig Roger is an Assistant Professor of Management in the College of Business Administration at Nicholls State University. Jerry Hood is Professor of Finance at Loyola University in New Orleans