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No abstract available
Die Europäische Union befindet sich derzeit in einer sehr ernsten Krise; ein Scheitern des europäischen Projekts, das bislang in der konstant voranschreitenden Vertiefung und Erweiterung der Integrationsgemeinschaft bestand, ist nicht mehr kategorisch auszuschließen. Es zeichnet sich ein Auseinanderdriften von EU und Euro-Zone ab. Der Beitrag argumentiert, dass die zahlreichen und weitreichenden Maßnahmen, die in den letzten drei Jahren zur Rettung des Euro ergriffen wurden, die Währungsgemeinschaft substantiell gestärkt und weiter zusammengeschmiedet haben. Dabei wird auch die besondere Rolle, die Deutschland in diesem Reformprozess spielt, behandelt. Perspektivisch stellt sich die Frage, ob ein „Eurozonen-Kerneuropa“ entstehen kann, das den Einigungsprozess zukunftsfest zu machen vermöchte. Ein Neustart im Rahmen von „Eurozonen-Kerneuropa“ brächte für die EU der 28+ Mitgliedstaaten Zerfallsgefahren mit sich, die vor allem für die sogenannten Pre-Ins dramatisch sein könnten. Doch liegt in solch einem Neustart, der einer wahrhaftigen Herkulesaufgabe gleichkäme, vielleicht die einzige Überlebenschance des Integrationsgedankens.
Shopping Center sind eine Gruppe von Geschäften, die als Einheit geplant, gebaut und gemanagt wird. Lage, Zahl und Art der Geschäfte sind abhängig von der Größe des Einzugsgebiets, das es versorgt. Die ersten Shopping Center wurden in den USA in den 1920er Jahren gebaut, aber zunächst nur an relativ wenigen Orten kopiert. Erst seit den 1950er Jahren eröffneten in rascher Folge immer mehr Shopping Center, die zudem auch immer größer wurden. Standort war vor allem der suburbane Raum. Ende der 1990er Jahre gab es in den USA ca. 44.000 Shopping Center in denen mehr als die Hälfte des Einzelhandelsumsatzes des Landes erwirtschaftet wurde.
Im Laufe der Jahrzehnte mussten sich die Shopping Center ständig dem Markt anpassen, um dem enormen Konkurrenzdruck und den sich wandelnden Ansprüchen der Konsumenten gerecht zu werden. Seit Mitte der 1970er Jahre sind völlig neue Typen von Shopping Centern, wie Factory Outlet Center, Value Center, Power Center, Urban Entertainment Center und Hybrid Center entstanden. Die neuen Typen von Shopping Centern stehen im Mittelpunkt des Bandes.
Außerdem wird hinterfragt, ob die US-amerikanische Entwicklung zeitversetzt auch in Deutschland stattfinden wird. Auch hier müssen sich die Shopping Center dem Markt anpassen, allerdings sind die Rahmenbedingungen andere. Da derzeit bei uns die Ansiedlung von Factory Outlet Centern nach amerikanischen Vorbild konträr diskutiert wird, schenkt die Autorin diesen und ihrem hiesigen Entwicklungspotenzial besondere Aufmerksamkeit.
The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first three chapters can be dealt within the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 4, 5 and 6 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. Chapter 7 (case study) deals with a practical case and demonstrates the presented methods. It is possible to use this chapter independent in a seminar or practical training course, if the concepts of time series analysis are already well understood. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific parts are highlighted. This book is an open source project under the GNU Free Documentation License.
The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS Statistical Analysis System). Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first two chapters can be dealt with in the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 3, 4 and 5 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific part, including the diagrams generated with SAS, always starts with a computer symbol, representing the beginning of a session at the computer, and ends with a printer symbol for the end of this session. This book is an open source project under the GNU Free Documentation License.
The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS Statistical Analysis System). Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first two chapters can be dealt with in the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 3, 4 and 5 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific part, including the diagrams generated with SAS, always starts with a computer symbol, representing the beginning of a session at the computer, and ends with a printer symbol for the end of this session. This book is an open source project under the GNU Free Documentation License.
The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first three chapters can be dealt within the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 4, 5 and 6 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. Chapter 7 (case study) deals with a practical case and demonstrates the presented methods. It is possible to use this chapter independent in a seminar or practical training course, if the concepts of time series analysis are already well understood. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific parts are highlighted. This book is an open source project under the GNU Free Documentation License.
No abstract available
Nationalparks sind das älteste und bekannteste flächenbezogene Naturschutzinstrument weltweit. Für den Erhalt einer nachhaltigen Lebensgrundlage und die Entwicklung der Biodiversität sowie für mehr Naturdynamik in der Landschaft haben sie eine sehr große Bedeutung, auch in unseren Breiten. Dennoch ist die Einstellung zu Nationalparks von Seiten der unmittelbaren Anwohner nicht immer unproblematisch. Entsprechend versucht die vorliegende wissenschaftliche Analyse neue Erkenntnisse bezüglich der Akzeptanz der Nationalparks Bayerischer Wald und Berchtesgaden, den ältesten Deutschlands, aufzuzeigen. Empirische Grundlagen für diese Studie sind eine bayernweite Online-Befragung, qualitative Experteninterviews und aufwändige repräsentative schriftliche Befragungen in den Nationalpark-Landkreisen Regen und Freyung-Grafenau bzw. Berchtesgadener Land im Jahr 2018. Auch die zeitliche Entwicklung der Akzeptanz wird auf Basis der Ergebnisse von Vorgängerstudien, soweit möglich, berücksichtigt. Dabei sind es ökonomische, emotionale, interpersonelle, soziokulturelle und nicht zuletzt für Geographen besonders interessante raumzeitliche Prädiktoren der Akzeptanz beider Nationalparks, die im Fokus der Untersuchungen stehen.
No abstract available