The Diffusion of the Internet and the Geography of the Digital Divide in the United States

This paper analyses the rapid diffusion of the Internet across the United States over the past decade for both households and firms. We put the Internet's diffusion into the context of economic diffusion theory where we consider costs and benefits on the demand and supply side. We also discuss several pictures of the Internet's physical presence using some of the current main techniques for Internet measurement. We highlight different economic perspectives and explanations for the digital divide, that is, unequal availability and use of the Internet.

Understanding the Opportunity-Centric Accessibility for Public Charging Infrastructure

In this study, we utilize data from over 28,000 public charging stations (PCSs) and 5.5 million points of interest across twenty U.S. metropolitan areas to underscore the importance of considering the availability of opportunities when assessing accessibility to PCSs, rather than relying solely on spatial proximity. Specifically, we conduct comprehensive comparisons of opportunity-centric accessibility measures with distance-based measures and perform counterfactual analyses under various PCS deployment strategies. Our findings reveal significant inequalities in PCS access across different neighborhoods under distance-based and opportunity-centric measures. However, a greater disparity exists when considering opportunities, with high-income communities having significantly better access to PCSs. Counterfactual analyses suggest that equitable deployment based on distance measures result in the least equitable outcomes when considering opportunities, primarily due to the existing disparity in opportunity distributions in our cities. Our insights highlight the complexity of locating PCSs and can guide nationwide PCS deployment for long-term societal benefits

E-governance in cities

This paper describes and analyses the way European urban policymakers guide their city into the information age. We develop an analytical framework to be able to analyse, assess and compare urban ICT policies. In the empirical part, the frame is applied to a number of cities. We conclude that the most successful cities apply a balanced mix of content, infrastructure and access policies. Furthermore, success depends on the capacity of urban management to engage in local networks with local companies, citizens and intermediary organisations, as well as their ability to mobilise external resources.

Geographical and institutional distances in venture capital deals: How syndication and experience drive internationalization patterns

Drawing on a novel dataset of worldwide venture capital deals, we investigate how venture capitalists (VCs) overcome the complexity of investing in geographically and institutionally distant regions. Our results indicate that syndicating with local VCs is a common way for foreign VCs to gain deal access, overcome the complexity of investing in distant regions and offset their lack of within-country experience. The foreign VC's distance from the portfolio company ceases to be a serious investment obstacle when he can rely on a highly experienced local VC. Our results further suggest that inexperienced VCs, i.e. those VCs with a large need for syndication, increase their chances to invest across borders when they invest in small deals jointly with local inexperienced partners. --Multiple Regression Analysis,Syndicates,Venture Capital,Internationalization,Distance,Experience

Data-driven model development in environmental geography - Methodological advancements and scientific applications

Die Erfassung räumlich kontinuierlicher Daten und raum-zeitlicher Dynamiken ist ein Forschungsschwerpunkt der Umweltgeographie. Zu diesem Ziel sind Modellierungsmethoden erforderlich, die es ermöglichen, aus limitierten Felddaten raum-zeitliche Aussagen abzuleiten. Die Komplexität von Umweltsystemen erfordert dabei die Verwendung von Modellierungsstrategien, die es erlauben, beliebige Zusammenhänge zwischen einer Vielzahl potentieller Prädiktoren zu berücksichtigen. Diese Anforderung verlangt nach einem Paradigmenwechsel von der parametrischen hin zu einer nicht-parametrischen, datengetriebenen Modellentwicklung, was zusätzlich durch die zunehmende Verfügbarkeit von Geodaten verstärkt wird. In diesem Zusammenhang haben sich maschinelle Lernverfahren als ein wichtiges Werkzeug erwiesen, um Muster in nicht-linearen und komplexen Systemen zu erfassen. Durch die wachsende Popularität maschineller Lernverfahren in wissenschaftlichen Zeitschriften und die Entwicklung komfortabler Softwarepakete wird zunehmend der Fehleindruck einer einfachen Anwendbarkeit erzeugt. Dem gegenüber steht jedoch eine Komplexität, die im Detail nur durch eine umfassende Methodenkompetenz kontrolliert werden kann. Diese Problematik gilt insbesondere für Geodaten, die besondere Merkmale wie vor allem räumliche Abhängigkeit aufweisen, womit sie sich von "gewöhnlichen" Daten abheben, was jedoch in maschinellen Lernanwendungen bisher weitestgehend ignoriert wird. Die vorliegende Arbeit beschäftigt sich mit dem Potenzial und der Sensitivität des maschinellen Lernens in der Umweltgeographie. In diesem Zusammenhang wurde eine Reihe von maschinellen Lernanwendungen in einem breiten Spektrum der Umweltgeographie veröffentlicht. Die einzelnen Beiträge stehen unter der übergeordneten Hypothese, dass datengetriebene Modellierungsstrategien nur dann zu einem Informationsgewinn und zu robusten raum-zeitlichen Ergebnissen führen, wenn die Merkmale von geographischen Daten berücksichtigt werden. Neben diesem übergeordneten methodischen Fokus zielt jede Anwendung darauf ab, durch adäquat angewandte Methoden neue fachliche Erkenntnisse in ihrem jeweiligen Forschungsgebiet zu liefern. Im Rahmen der Arbeit wurde eine Vielzahl relevanter Umweltmonitoring-Produkte entwickelt. Die Ergebnisse verdeutlichen, dass sowohl hohe fachwissenschaftliche als auch methodische Kenntnisse unverzichtbar sind, um den Bereich der datengetriebenen Umweltgeographie voranzutreiben. Die Arbeit demonstriert erstmals die Relevanz räumlicher Überfittung in geographischen Lernanwendungen und legt ihre Auswirkungen auf die Modellergebnisse dar. Um diesem Problem entgegenzuwirken, wird eine neue, an Geodaten angepasste Methode zur Modellentwicklung entwickelt, wodurch deutlich verbesserte Ergebnisse erzielt werden können. Diese Arbeit ist abschließend als Appell zu verstehen, über die Standardanwendungen der maschinellen Lernverfahren hinauszudenken, da sie beweist, dass die Anwendung von Standardverfahren auf Geodaten zu starker Überfittung und Fehlinterpretation der Ergebnisse führt. Erst wenn Eigenschaften von geographischen Daten berücksichtigt werden, bietet das maschinelle Lernen ein leistungsstarkes Werkzeug, um wissenschaftlich verlässliche Ergebnisse für die Umweltgeographie zu liefern

Shared teaching with multimedia‐enhanced video‐conferencing

Video‐conferencing was used to share a short series of lectures between several universities. A high bandwidth network (155Mbit/s) permitted near broadcast TV quality video to be combined with fully mixed, high‐quality audio. The lectures were supported by visual aids made available using Microsoft NetMeeting to provide multipoint, shared applications. NetMeeting is shown to be a stable and effective platform for distributing multimedia material at a much higher resolution than is possible using the video signals common in most video‐conference lectures, although care must be taken when constructing animated material

A Review of Positive Feedback Mechanisms in Technology Markets, Regional Clusters, and Organizations

The concept of path dependence has often been criticized as vague and only narrowly applicable. Although we can find some very refined definitions of the concept, we also find a wide range of empirical phenomena being described as path-dependent. We argue that more detailed accounts of the positive feedback mechanisms that form paths can take path dependence beyond this state of being overdetermined, but under-specified. Reviewing three well-described cases of path-dependent dynamics in technology markets, regional clustering, and organizations, we define a core set of positive feedback mechanisms that constitute path dependence at different analysis levels and clarify the relationship between positive feedback and increasing returns. We show that path-dependent processes, that is, processes driven by positive feedback that veer toward rigidity or lock-in, can be (but do not have to be) found under many labels, including structural inertia, coevolution, or institutional persistence. We conclude that a precise definition of path dependence does not need to be at odds with the concept’s widespread use in understanding organizational and industrial development processes

Association Genetics and Local Adaptation of Populus trichocarpa Torr. & Gray

A major goal in plant science is overcoming the recalcitrance of plant biomass to cellulose extraction, to enable efficient production of cellulosic biofuel. We have started to understand the genetic basis of some important traits such as cell wall chemistry, but we do not know anything about the key structural and functional traits such as wood anatomy that greatly affect plant biomass recalcitrance. Furthermore, biofuel feedstocks have to be adapted to varied environmental conditions to ensure high productivity in plantations, but little is known about the molecular mechanisms underlying local adaptation. With the advancement in sequencing and genotyping technologies, association genetics has emerged as a powerful approach for unraveling complex traits in plants, thereby linking the natural variation present in the phenotype with the underlying genotype. Furthermore, the integration of phenotypic, genomic and environmental data has great premise for understanding plant adaptation in the face of climate change. Because of its rapid growth, hybrid vigor, broad geographic distribution, transformation potential, and the availability of tremendous genetic resources and wide phenotypic variation, Populus is a highly desirable genus for biofuel production and other wood products. My dissertation research uses an association genetics approach focused on important anatomical, morphological and physiological traits to address three key questions: (1) What genetic mechanisms underlie variation in morphological and physiological traits in P. trichocarpa? (2) What are the factors affecting local adaptation in P. trichocarpa and what is the relative contribution of climate and geography variables to population structure? (3) What genes or genomic regions are associated with variation in important functional and structural traits that can be targeted to enhance productivity and reduce recalcitrance of woody bioenergy feedstocks? My research will enhance understanding of the biology of Populus trichocarpa by determining the genetic basis of key agronomic traits such as vessel size and density, leaf area, and stomatal density that affect overall performance under field conditions using genome-wide association study (GWAS). Understanding the genetic basis of these traits is key for developing Populus as a biomass feedstock for biofuel production. Furthermore, morphological and structural traits are often tightly correlated with physiological performance. Therefore, another aspect of this study is to unravel the genetic basis of key physiological traits such as leaf chlorophyll content, carbon isotope composition and leaf water potential, and their correlation with morphological traits. This will aid in better understanding of stress tolerance and the overall biology of this species. Furthermore, by performing these studies in plantations that are clonally replicated in three environments, I evaluated the robustness of the associations. Using genotype environment association (GEA) and redundancy analysis (RDA) I identified loci conferring local adaptation in P. trichocarpa. Moreover, with RDA analysis I determined the relative contribution of climate and geography in neutral population structure. Similarly, I determined the relative contribution of genomic, climate and geography data in explaining phenotypic variation. A long-term goal of the project is to develop a selection model based on comprehensive genetic and phenotypic information so that the genome enabled breeding value can be estimated. This will enhance the efficiency of Populus breeding programs by shortening the breeding cycle and improving the accuracy of selection. This will aid in developing genetically improved trees with high biomass production and reduced recalcitrance to cellulose extraction, thereby furthering the development of the lignocellulosic biofuels industry

The role of airports in national civil aviation policies

The concept of a hub airport has evolved widening its scope as a national civil aviation policy-making tool, due to the ability to deliver wider socio-economic benefits to a country. However, not all airports can be converted into hubs. This research proposes a methodological approach to structural analysis of the airport industry, that could be applied to determine the competitive position of an airport in a given aviation network and devise airport strategies and national policy measures to improve the current position of the airport. This study presents a twelve-group taxonomy of airports, which analyses the changing geography of the airport industry in the East (Asia and The Middle East). Multivariate data have been used in a two-step Agglomerative Hierarchical Clustering exercise which represents three airport strategies: namely, degree-of-airport-activity (size and intensity of operations), network strategies (international and domestic hub), and the market segmentation strategies (service and destination orientation). Principal Component Analysis has been utilised as a data reduction tool. The study confirms the general hypothesis that a sound macro environment and liberalised approach to economic regulation in the air transport industry are important for successful hub operations. In addition, it sheds light on the fact that while the factors of geographical advantage, economic development, urbanisation, tourism and business attractiveness, physical and intellectual infrastructure, and political and administrative frameworks, are all basic prerequisites (qualifiers) for successful hubbing in the region, those factors would not necessarily guarantee a hub status unless the governments are also committed to develop the sector and take timely decisions (differentiators) to allow airports to benefit from the first mover advantage. Application of the proposed taxonomy was tested on a case study of the major international airport of Sri Lanka, to provide policy inputs to develop the airport that is currently identified as being overshadowed by the mega hubs in the region