Methods and Measures for Analyzing Complex Street Networks and Urban Form

Complex systems have been widely studied by social and natural scientists in terms of their dynamics and their structure. Scholars of cities and urban planning have incorporated complexity theories from qualitative and quantitative perspectives. From a structural standpoint, the urban form may be characterized by the morphological complexity of its circulation networks - particularly their density, resilience, centrality, and connectedness. This dissertation unpacks theories of nonlinearity and complex systems, then develops a framework for assessing the complexity of urban form and street networks. It introduces a new tool, OSMnx, to collect street network and other urban form data for anywhere in the world, then analyze and visualize them. Finally, it presents a large empirical study of 27,000 street networks, examining their metric and topological complexity relevant to urban design, transportation research, and the human experience of the built environment.Comment: PhD thesis (2017), City and Regional Planning, UC Berkele

Urban morphology and housing market

Urban morphology has been a longstanding field of interest for geographers but without adequate focus on its economic significance. From an economic perspective, urban morphology appears to be a fundamental determinant of house prices since morphology influences accessibility. This PhD thesis investigates the question of how the housing market values urban morphology. Specifically, it investigates people’s revealed preferences for street patterns. The research looks at two distinct types of housing market, one in the UK and the other in China, exploring both static and dynamic relationships between urban morphology and house price. A network analysis method known as space syntax is employed to quantify urban morphology features by computing systemic spatial accessibility indices from a model of a city’s street network. Three research questions are empirically tested. Firstly, does urban configuration influence property value, measured at either individual or aggregate (census output area) level, using the Cardiff housing market as a case study? The second empirical study investigates whether urban configurational features can be used to better delineate housing submarkets. Cardiff is again used as the case study. Thirdly, the research aims to find out how continuous change to the urban street network influences house price volatility at a micro-level. Data from Nanjing, China,is used to investigate this dynamic relationship. The results show that urban morphology does, in fact, have a statistically significant impact on housing price in these two distinctly different housing markets. I find that urban network morphology features can have both positive and negative impacts on housing price. By measuring different types of connectivity in a street network it is possible to identify which parts of the network are likely to have negative accessibility premiums (locations likely to be congested) and which parts are likely to have positive premiums (locations highly connected to destination opportunities). In the China case study, I find that this relationship holds dynamically as well as statically, showing evidence that price change is correlated with some aspects of network change

기술지식의 복잡성 관리: 다양성, 융합성, 동태성

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 산업·조선공학부, 2018. 2. 박용태.지속적인 기술혁신을 창출하기 위해서 연구개발에 관련된 데이터와 정보를 가공하여 이를 창의적인 지식으로 전환시키는 기술지식경영이 강조되고 있다. 특히 최근 기술지식의 복잡성이 지속적으로 증가함에 따라 복잡성을 고려한 보다 체계적인 기술지식경영에 대한 요구가 증가하고 있다. 기술지식은 더 이상 하나의 단일 기술이 아닌 다양한 관련 기술과 학제를 포함하게 되었으며, 다양한 기술들이 서로 융합하여 새로운 기술로 발전하는 양상을 나타내고 있다. 또한, 기술지식을 활용하는 사람들이 더욱 다양해지고 그 파급효과가 광범위해짐에 따라 기술지식은 더욱 동적인 환경에 노출되고 있다. 이에, 본 학위 논문은 기술지식의 복잡성을 구성하는 특성에 대한 연구를 수행하며, 특히 복잡성으로 인해 발생하는 주요 경영 문제를 해결한다. 구체적으로, 본 학위 논문은 최근 기술지식의 복잡성을 구성하는 특성을 다양성, 융합성, 동태성로 정의하고 각 특성에 관련된 세 가지 연구 문제를 다룬다. 다양화된 기술지식의 구조 탐색 문제, 기술융합이 활발한 상황에서 기술 트렌드 예측 문제, 동적인 환경에 놓인 대형 기술 프로젝트 평가 문제를 다룬 세 가지 세부 연구는 적합한 방법론을 활용 및 창조적으로 결합하여 각 문제들을 효과적으로 다룬다. 첫 번째 연구는 기술지식의 다양성 관리 측면에서 기술지식의 구조 분석을 다룬다. 최근 기술지식은 다학제적인 성격을 가지며, 연구개발 전략의 올바른 방향을 설정하기 위해서 그 구조를 파악하고 연구 동향을 이해하는 것이 중요하다. 본 연구에서는 다학제적인 기술지식의 구조를 파악하는 방법으로 저널 인용 네트워크와 네트워크 분석을 활용한 프레임워크를 제시한다. 구체적으로, 저널 인용 네트워크를 구축하고 네트워크 중심성(centrality) 측정 및 중개(brokerage) 분석을 활용하여 다학제 연구가 대표적으로 활발히 일어나고 있는 나노과학기술 분야의 지적 구조를 탐색한다. 제안된 접근은 지식의 흐름 측면에서 중요한 기술 요소(technology element)와 지식 교환 측면에서 지식 원천(knowledge source)의 중개 역할을 파악함으로써 기술지식의 다학제적인 구조에 대한 미시적, 거시적 관점을 제공할 수 있다는 점에서 의의가 있다. 두 번째 연구는 기술지식의 융합성 관리 측면에서 기술융합의 예측을 다룬다. 오늘날 기술지식은 빠르게 진화하고 있으며, 융합을 통해 새로운 기술이 창출되는 양상을 보이고 있다. 이에 따라, 기술 간의 경계가 흐려지고 있으며 새로운 기술 트렌드를 예측하는 것이 더욱 어려워지고 있다. 본 연구에서는 새롭게 등장하는 유망 기술의 기술융합을 예측하는 방법으로 특허동시분류분석과 링크예측기법을 활용한 프레임워크를 제시한다. 제안된 접근은 네트워크의 특성을 바탕으로 잠재적인 링크를 예측하므로 과거에 존재 않았더라도 미래에 나타날 가능성이 높은 기술융합을 파악할 수 있다는 장점을 가진다. 이해를 돕기 위해, 제안된 접근은 3D 프린팅 기술에 적용되었으며, 향후 다양한 기술 및 산업에서 활용될 수 있을 것으로 기대된다. 마지막으로, 세 번째 연구는 기술지식의 동태성 관리 측면에서 대형 기술 프로젝트의 평가를 다룬다. 기술지식을 활용하는 사람들이 다양해지고, 기술지식이 영향을 미치는 파급효과의 범위가 확대됨에 따라 기술 투자 프로젝트의 의사결정 문제가 더욱 중요해지고 있다. 본 연구에서는 동적인 환경에서 프로젝트의 타당성을 분석하는 방법으로 시스템 다이내믹스(system dynamics)와 행위자 기반 모델링(agent-based modeling)을 결합한 프레임워크를 제시한다. 제안된 접근에서 시스템 다이내믹스 부분은 프로젝트의 비용과 효익을 구성하는 시스템 요소 간의 관계를 설명하고, 행위자 기반 모델링 부분은 사용자의 이질성(heterogeneity)을 고려한 창발적 행동(emergent behavior)을 묘사한다. 사례 연구를 통해 제안된 접근의 적용 가능성을 보였으며, 제안된 접근은 동적인 환경에서 프로젝트의 실현 가능성을 분석하기 위한 유연한 프레임워크를 제공할 수 있다는 점에서 의의가 있다.In order to create constant innovation, management of technological knowledge, where the data and information related to R&D are transformed into creative knowledge, has been increasingly emphasized. Moreover, as the complexity of recent technological knowledge continues to increase, there is a growing demand for more systematic management considering complexity to obtain novel insights about rising managerial problems and solutions. Technological knowledge no longer includes a single technology but various related technologies and disciplines, and various technologies converge into a new technology. In addition, as the people who use technological knowledge become more diversified and its ripple effects become more widespread, technological knowledge is exposed to a more dynamic environment. Therefore, this dissertation aims to examine the characteristics that constitute the complexity of technological knowledge, and resolve major managerial problems resulting from its characteristics. Specifically, this study defines the emerging characteristics that accelerate the complexity of technological knowledge as diversity, convergence, and dynamismthen three research questions related to each characteristic are addressed through three research themes. Each research theme is studied by utilizing and creatively combining appropriate methodologies to answer each research question. The first study focuses on the research theme for managing diversity in complexity, and deals with the identification of intellectual structure of technological knowledge. Recently, technological knowledge has a multidisciplinary nature. Hence, it is important to understand the knowledge structure and research trends in order to develop the direction of R&D strategy. In this study, a framework that includes journal citation network and network analysis is proposed as a method to identify the structure of multidisciplinary technological knowledge. Specifically, a journal citation network is constructedthen network centrality measures and brokerage analysis are used to explore the intellectual structure of nanoscience and nanotechnology, where multidisciplinary research is actively done. The proposed approach can provide a microscopic and macroscopic view of the multidisciplinary structure of technological knowledge by identifying the important technology element regarding knowledge flow, and the intermediary role of each knowledge source regarding knowledge exchange. The second study focuses on the research theme for managing convergence in complexity, and deals with the prediction of technological convergence. As technological knowledge is rapidly evolving and new technologies are being created through convergence, the boundaries between technologies are blurred and it becomes more difficult to predict new technology trends. In this study, a framework that includes patent co-classification analysis and link prediction is proposed as a method to predict the technological convergence of emerging technologies. The proposed approach has the advantage in that it can discover the potential convergence, even if it does not exist in the past, because it predicts the potential link based on the characteristics of the network. The proposed approach is applied to 3D printing technology, and it is expected to be utilized in various technologies and industries in the future. Finally, the third study focuses on the research theme for managing dynamism in complexity, and deals with the evaluation of technology-intensive and large-scale projects. Increasingly, technology investment projects face a dynamic environment that incorporates both macroscopic system and microscopic individuals. In this study, a new approach to dynamic feasibility analysis for investment projects is proposed through an integrated simulation model using system dynamics (SD) and agent-based modeling (ABM). The combination of SD and ABM is suggested due to their complementary strengths. The former SD part elucidates the relationships among system elements that constitute project's benefits and costs, while the latter ABM part depicts users emergent behavior with their heterogeneity. A case study demonstrates the applicability of the proposed approach. The findings show that the proposed approach can provide a valuable and flexible framework for analyzing project feasibility in a dynamic environment.Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Purpose 3 1.3 Scope and framework 5 1.4 Outline 7 Chapter 2 Research Background 10 2.1 Theoretical Background 10 2.1.1 Concept of Complexity 10 2.1.2 Complexity Management 11 2.1.3 Dimension of Complexity 13 2.2 Methodological Background 15 2.2.1 Network Metrics: Centrality and Brokerage 15 2.2.2 Link Prediction 19 2.2.3 System Dynamics (SD) and Agent-based Modeling (ABM) 21 Chapter 3 Managing Diversity in Complexity 24 3.1 Introduction 24 3.2 Knowledge Source Network 27 3.3 Research Process 31 3.3.1 Overall Process 31 3.3.2 Knowledge Source Selection 32 3.3.3 Technology Element Composition 33 3.4 Identification of Intellectual Structure 37 3.4.1 Macro View of Intellectual Structure 37 3.4.2 Micro View of Intellectual Structure 43 3.5 Conclusion 56 Chapter 4 Managing Convergence in Complexity 58 4.1 Introduction 58 4.2 Convergence of Emerging Technologies 60 4.2.1 Understanding of Emerging Technology 60 4.2.2 Technological Convergence Analysis using Patents 61 4.3 Research process 63 4.3.1 Overall Process 63 4.3.2 Detailed Process 64 4.4 Prediction of Technological Convergence 69 4.4.1 Background 69 4.4.2 Data Collection and Data Partition 69 4.4.3 Patent Co-classification Network Construction 71 4.4.4 Link Prediction of Patent Network 73 4.4.5 Investigation and Prediction of Technological Convergence 75 4.5 Conclusion 83 Chapter 5 Managing Dynamism in Complexity 85 5.1 Introduction 85 5.2 Feasibility Studies 89 5.2.1 Feasibility Studies for Large-scale Projects 89 5.2.2 Dynamic Approach in Feasibility Study 90 5.3 Research Process 93 5.3.1 Conceptual Framework 93 5.3.2 Composition of Modules 95 5.3.3 Overall Process 100 5.4 Evaluation of Large-scale Project 103 5.4.1 Background 103 5.4.2 Modeling Process 104 5.4.3 Results 115 5.5 Discussion 118 5.5.1 Theoretical and Practical Implications 118 5.5.2 Generalization 119 5.6 Conclusion 122 Chapter 6 Conclusion 124 6.1 Summary and Contributions 124 6.2 Limitations and Future Research 129 Bibliography 131 Appendix 150 Appendix A Supplementary Information about SD and ABM 150 Appendix A.1 System Dynamics (SD) 150 Appendix A.2 Agent-based Modeling (ABM) 151 Appendix B Prior Research on Formulating Integrated SD Model and AB Model 152 Appendix C List of 73 Nano Journals 153 Appendix D Centrality Score of Nano Knowledge Sources 156 Appendix E Brokerage Score of Nano Knowledge Sources in Weighted Version 159 Appendix F Description and Assumption of Overall Variables in Combined Model 162 초 록 168Docto

Statistical Inference for Propagation Processes on Complex Networks

Die Methoden der Netzwerktheorie erfreuen sich wachsender Beliebtheit, da sie die Darstellung von komplexen Systemen durch Netzwerke erlauben. Diese werden nur mit einer Menge von Knoten erfasst, die durch Kanten verbunden werden. Derzeit verfügbare Methoden beschränken sich hauptsächlich auf die deskriptive Analyse der Netzwerkstruktur. In der hier vorliegenden Arbeit werden verschiedene Ansätze für die Inferenz über Prozessen in komplexen Netzwerken vorgestellt. Diese Prozesse beeinflussen messbare Größen in Netzwerkknoten und werden durch eine Menge von Zufallszahlen beschrieben. Alle vorgestellten Methoden sind durch praktische Anwendungen motiviert, wie die Übertragung von Lebensmittelinfektionen, die Verbreitung von Zugverspätungen, oder auch die Regulierung von genetischen Effekten. Zunächst wird ein allgemeines dynamisches Metapopulationsmodell für die Verbreitung von Lebensmittelinfektionen vorgestellt, welches die lokalen Infektionsdynamiken mit den netzwerkbasierten Transportwegen von kontaminierten Lebensmitteln zusammenführt. Dieses Modell ermöglicht die effiziente Simulationen verschiedener realistischer Lebensmittelinfektionsepidemien. Zweitens wird ein explorativer Ansatz zur Ursprungsbestimmung von Verbreitungsprozessen entwickelt. Auf Grundlage einer netzwerkbasierten Redefinition der geodätischen Distanz können komplexe Verbreitungsmuster in ein systematisches, kreisrundes Ausbreitungsschema projiziert werden. Dies gilt genau dann, wenn der Ursprungsnetzwerkknoten als Bezugspunkt gewählt wird. Die Methode wird erfolgreich auf den EHEC/HUS Epidemie 2011 in Deutschland angewandt. Die Ergebnisse legen nahe, dass die Methode die aufwändigen Standarduntersuchungen bei Lebensmittelinfektionsepidemien sinnvoll ergänzen kann. Zudem kann dieser explorative Ansatz zur Identifikation von Ursprungsverspätungen in Transportnetzwerken angewandt werden. Die Ergebnisse von umfangreichen Simulationsstudien mit verschiedenstensten Übertragungsmechanismen lassen auf eine allgemeine Anwendbarkeit des Ansatzes bei der Ursprungsbestimmung von Verbreitungsprozessen in vielfältigen Bereichen hoffen. Schließlich wird gezeigt, dass kernelbasierte Methoden eine Alternative für die statistische Analyse von Prozessen in Netzwerken darstellen können. Es wurde ein netzwerkbasierter Kern für den logistischen Kernel Machine Test entwickelt, welcher die nahtlose Integration von biologischem Wissen in die Analyse von Daten aus genomweiten Assoziationsstudien erlaubt. Die Methode wird erfolgreich bei der Analyse genetischer Ursachen für rheumatische Arthritis und Lungenkrebs getestet. Zusammenfassend machen die Ergebnisse der vorgestellten Methoden deutlich, dass die Netzwerk-theoretische Analyse von Verbreitungsprozessen einen wesentlichen Beitrag zur Beantwortung verschiedenster Fragestellungen in unterschiedlichen Anwendungen liefern kann

Sustainability in the Global-Knowledge Economy

Knowledge affects all aspects of the economy, but digitalization probably represents the most ubiquitous of its appearances. This book analyzes, from a constructive point of view, some of its applications, extracting lessons to maximize its utility and exporting its use to other sectors. It also shows the caveats of its applications, allowing managers to learn its difficulties and how to overcome them from real-life cases. All the information is presented in an academic and rigorous way and represents an excellent starting point to study the effects of digitalization for both practitioners and researchers

Characterising and modeling the co-evolution of transportation networks and territories

The identification of structuring effects of transportation infrastructure on territorial dynamics remains an open research problem. This issue is one of the aspects of approaches on complexity of territorial dynamics, within which territories and networks would be co-evolving. The aim of this thesis is to challenge this view on interactions between networks and territories, both at the conceptual and empirical level, by integrating them in simulation models of territorial systems.Comment: Doctoral dissertation (2017), Universit\'e Paris 7 Denis Diderot. Translated from French. Several papers compose this PhD thesis; overlap with: arXiv:{1605.08888, 1608.00840, 1608.05266, 1612.08504, 1706.07467, 1706.09244, 1708.06743, 1709.08684, 1712.00805, 1803.11457, 1804.09416, 1804.09430, 1805.05195, 1808.07282, 1809.00861, 1811.04270, 1812.01473, 1812.06008, 1908.02034, 2012.13367, 2102.13501, 2106.11996