Networks & Spatial Economics最新文献_第6页

Collaborative Network Topologies in Spatial Economies 空间经济中的协同网络拓扑

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-05-04 DOI: 10.1007/s11067-022-09564-x

Shaun Lichter, T. Friesz, C. Griffin, Amir Bagherzadeh

引用次数: 2

A Circular Economy Model of Economic Growth with Circular and Cumulative Causation and Trade 基于循环累积因果关系和贸易的经济增长循环经济模型

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-04-22 DOI: 10.1007/s11067-022-09559-8

K. Donaghy

引用次数: 5

Targeted Advertising in the Public Transit Network Using Smart Card Data 基于智能卡数据的公交网络定向广告

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-03-01 DOI: 10.1007/s11067-022-09558-9

H. Faroqi, M. Mesbah, Jiwon Kim, A. Khodaii

引用次数: 3

Time Evolution of City Distributions in Germany 德国城市分布的时间演变

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-03-01 DOI: 10.1007/s11067-021-09557-2

K. Ikeda, M. Osawa, Y. Takayama

引用次数: 1

The Network Structure of Innovation Networks 创新网络的网络结构

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-01-26 DOI: 10.1007/s11067-021-09556-3

Shixun Wang, Lihong Yang

引用次数: 0

A Granular Local Search Matheuristic for a Heterogeneous Fleet Vehicle Routing Problem with Stochastic Travel Times 具有随机行程时间的异构车队车辆路径问题的粒度局部搜索数学

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-01-24 DOI: 10.1007/s11067-021-09553-6

Ramon Faganello Fachini, V. Armentano, F. Toledo

引用次数: 0

The Fuel and Energy Industry of China and Russia in the Context of the Transition to the Low-Carbon Development Trajectory 向低碳发展轨道转型背景下的中俄燃料能源工业

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-01-01 DOI: 10.14530/se.2022.3.141-167

V. Kryukov, Y. Kryukov

{"title":"The Fuel and Energy Industry of China and Russia in the Context of the Transition to the Low-Carbon Development Trajectory","authors":"V. Kryukov, Y. Kryukov","doi":"10.14530/se.2022.3.141-167","DOIUrl":"https://doi.org/10.14530/se.2022.3.141-167","url":null,"abstract":"The article analyzes the issues of energy cooperation between Russia and China in connection with the ‘green transition’ in China, China reaching the peak level of emissions in 2030 and its transition to carbon neutrality by 2060. In the foreseeable future, the key area of energy cooperation between the two countries will be the gas sector, with natural gas is being considered as a ‘transitional’ fuel on the way from coal to renewable energy sources. The Chinese economy is actively moving to the use of gas in the energy and residential sectors. At the same time, considering the scale of the Chinese economy, coal will be in demand for a long time, since technological and economic reasons make it difficult to abandon this raw material quickly in favor of less carbon-intensive types of energy resources. Against this background, the Russian fuel and energy industry can avail of the contradictory trends in the energy sector of China – the existing desire for development with low-carbohydrate emissions and current significant volumes of coal generation. This creates a stable basis for the development of bilateral energy cooperation for the upcoming decades. Russia and China have different views on low-carbon development, which is dictated by the different role of energy resources in the economy of each country. China seeks self-sufficiency in supply and therefore purposefully follows the path of the ‘green transition’, while Russia proceeds from the relative duration of the era of non-renewable energy resources. For this reason, ‘green’ projects in Russia are still more related to environmental care within the framework of individual projects ‘on the ground’, and not with a systematic movement towards decarbonization of the energy industry","PeriodicalId":54733,"journal":{"name":"Networks & Spatial Economics","volume":"32 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88647608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Spatial Analysis of Socio-Economic Systems: Genesis and Current State 社会经济系统的空间分析:起源与现状

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-01-01 DOI: 10.14530/se.2022.1.192-198

Viacheslav Seliverstov

引用次数: 0

Comparative Analysis of the Spatial Structures of the Moscow and St. Petersburg Agglomerations 莫斯科与圣彼得堡城市群空间结构的比较分析

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-01-01 DOI: 10.14530/se.2022.1.073-100

D. Olifir

{"title":"Comparative Analysis of the Spatial Structures of the Moscow and St. Petersburg Agglomerations","authors":"D. Olifir","doi":"10.14530/se.2022.1.073-100","DOIUrl":"https://doi.org/10.14530/se.2022.1.073-100","url":null,"abstract":"The article provides a comparative analysis of the existing spatial structure of urban settlement of the two largest agglomerations of our country – Moscow and St. Petersburg. Quantitative (dynamics of the number of settlements with the status of a city, dynamics of the population of cities, the number of houses under construction and the total area of residential units under construction) and qualitative (analysis of the automobile and railway networks) indicators are used. The following scientific methods are used in the work: statistical, geostructural, cartographic modeling, grouping method. 2002–2021 the two agglomerations are characterized by positive trends in population growth, which are associated with migration growth. The supporting framework of the Moscow agglomeration is represented by a uniform radial-circular type with a mixed monopolycentric model with a dominant core and the presence of large sub-centers, while the St. Petersburg agglomeration is a coastal type with a pronounced monocentric model and exclusive dominance of the core. On the basis of the existing supporting frames, to determine the stages of development of two agglomerations, a spatial typology of cities was carried out depending on the degree of their remoteness from the corresponding central points (nuclei). As a result, five orders (belts) with averaged transport availability isochrones were identified. Transformation processes of staged agglomeration development proceed most intensively within the entire Moscow agglomeration, which is at the stage of suburbanization. In the St. Petersburg agglomeration, the most active urbanized zone are cities located at distances of up to 50 km from the central point of the core, and it is characterized by a transition from the urbanization stage to the suburbanization stage","PeriodicalId":54733,"journal":{"name":"Networks & Spatial Economics","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77982720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Proximity Graphs 距离图

IF 2.4 3区工程技术

Networks & Spatial Economics Pub Date : 2022-01-01 DOI: 10.1007/978-3-030-94106-2_15

M. Barthelemy

引用次数: 1