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From the perspective of spatial interaction, the impact of the modern service industry’s agglomeration on today’s increasingly connected cities is worth studying. This study uses a spatial econometric model to test the development trends and factors influencing the modern service industry’s agglomeration in the Yangtze River Delta city group. The results show that the industry has the highest agglomeration in leasing and business and the lowest in education. The overall concentration of the industry is generally low, implying a more fragmented distribution. Moreover, the agglomeration has a significant positive spatial correlation with economic development, knowledge intensity, and city size. However, it has a negative correlation with information technology level and transportation infrastructure, inconsistent with existing research. This study argues that the development of the information technology level and transportation infrastructure in a city could lead to the ‘virtual agglomeration’ of the modern service industry and gradual decentralisation in geographical distribution. This is a new paradox that city groups may face when improving their infrastructure and developing modern services. This study uses the spatial interaction perspective to propose policy recommendations for promoting the modern service industry’s agglomeration and coordinated regional development.

In the second half of the 20th century, urban waterfront development began in North America and spread around the world. During the development process, urban waterfronts were assigned various functions, however following their spatial transformation, various problems such as weak interaction with water, weak physical accessibility, and the loss of historical identity have occurred directly affecting open spaces. Since the 19th century, the transformation of Istanbul waterfronts has occurred in parallel to the urban development process but without being a part of holistic planning approach. In time, the loss of open spaces, the lack of qualities such as the spatial interaction with water, the weak accessibility by public transportation and the lack of diversity for recreational activities have grown into common problems. This article discusses the results of a study focused on the spatial characteristics of open spaces especially referring to historical waterfronts (Eminönü, Karaköy, Kadıköy, Üsküdar, Beşiktaş) in consideration with the qualities of ‘water-based environment’, ‘connectivity and continuity’, ‘imageability’, ‘compatibility’ and ‘looseness’.

Given the importance of entry promotion to prompt economic growth and promote structural transformation, this paper investigates the regional determinants of firm entry in the 30 Iranian regions, considering four different sizes-micro, small, medium, and large-over 2000-2015. Using a new and unique database, we estimate different spatial econometric models, which take into account three types of spatial interaction effects. We find that firm entry is related to some regional characteristics, but the relationship is not homogeneous across firms of different size. We also find that most types of firms are influenced by the negative effect of economic sanctions during the sample period., Fil: Cheratian, Iman. Academic Center for Education, Culture, and Research (ACECR); Iran., Fil: Goltabar, Saleh. Academic Center for Education, Culture, and Research (ACECR); Iran., Fil: Calá, Carla Daniela. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina.

This paper examines mobility governance in an environment where varied mobility practices occur. Drawing on a quasi-ethnography of canal users in England and Wales, we discuss how multiple mobilities (including boating, walking, cycling and running) are practised in the relatively confined and linear spaces of canals and adjacent towpaths, and often at the same time. We demonstrate how these different yet intertwined modes of movement, and their associated tempos, are governed through creative interplays of freedom and control, and hierarchy and etiquette. These findings give rise to wider questions regarding the potentialities of governmobility – i.e. a system in which mobilities are able to govern themselves. Our conclusion, therefore, explores how the governance of mobilities on the UK canal network might offer insight, or a ‘watery blueprint’, for mobility governance in other shared spaces. This includes exploring the debates between giving citizens greater freedom and agency to negotiate their own mobility juxtapositions and tensions, versus imposing upon them stricter rule-based systems of mobility regulation.

While previous studies have neglected the spatial interaction effects in modelling healthcare expenditure across countries, this study provides the first thorough spatial analysis of public healthcare expenditures between countries so far. It investigates the determinants of public healthcare expenditure in Sub‐Saharan Africa (SSA) using a balanced panel of 43 SSA countries over the period 2000 to 2015. Both spatial interdependence and individual heterogeneity are accounted for through the application of the spatial autoregressive model so as to avoid potential bias and inefficiencies in parameter estimates. In addition to statistically significant effects of income, population density, official development assistance, and political stability, the results indicate the existence of positive spatial dependence in public healthcare expenditure in SSA. This suggests that governments in SSA countries tend to base their decision to allocate healthcare expenditure on that of nearby countries. Moreover, the results reveal significant impacts of population density and official development assistance of neighbouring countries on a country's level of public healthcare expenditure.

Research in landscape architecture (LA) is an important area to improve natural, anthropogenic, social and economic sustainability. The focus point of the article is territory of historical greenery (THG) of LA, which originates as a result of interaction between material environment design and society. The study of THG problems today is based on the innate human right to live in a harmonious space of both aesthetic material and natural environment. Environmental quality criteria are important to understand the nature and human interaction embodied in LA as an expression of applied art. Therefore, urban spaces formed by the anthropogenic objects of LA, require studies of the systemic relationship between the material and natural environment and its function as a whole. Based on heuristic, qualitative and quantitative research methods and literature review of case studies, the article discusses the problems of interaction between contemporary society, historic legacy and natural processes. In this article, authors explore the natural human abilities to perceive and interact with the environment on the intuitive level. Universal design aims provide a value basis for social, cultural and functional interaction harmonization of the environment on the intuitive level. More universal and intuitive approach reveals the potential to enhance spatial interaction with the THG and to improve quality of its future management and development scenarios.

Spatial data science emerges as an important subclass of data science and focuses on extracting meaningful information and knowledge from spatial data to enable effective communication and interpretation of both spatial data and analytic results. It emphasizes the importance of location and spatial interaction by storing, analyzing, retrieving, and visualizing spatial and geometric information. Frequently, spatial objects are afflicted by spatial fuzziness, characterizing spatial objects with blurred interiors, uncertain boundaries, and imprecise locations. Fuzzy set theory and fuzzy logic have become powerful tools to adequately represent spatial fuzziness. This paper provides a survey and a review of the literature to understand the application of fuzzy approaches to spatial data science (projects) with the objective of proposing, motivating, and envisioning fuzzy spatial data science.

The deviation of implementation of China’s cultivated land protection policy is the core problem urgently needing to be solved in the process of protecting the country’s cultivated land. This paper aims to explain the universality of this implementation deviation from the perspective of the spatial interaction of fiscal land strategies. Based on the data of 30 provinces in China from 2000 to 2015, the spatial Durbin model is used to validate the corresponding theoretical hypothesis. The results show that: (1) At the national or regional level, the given local government’s behavior with regard to land conveyance and land-orientation investment will aggravate implementation deviations of the cultivated land protection policy in the local area. (2) Land conveyance and land-orientation investment behaviors cause a spatial spillover effect. As a result, these behaviors not only exacerbate the implementation deviation of the cultivated land protection policy in the local area, but also exacerbate this deviation in adjacent areas. (3) The spatial spillover effects of land conveyance and land-orientation investment strategies in the eastern, central and western regions of China show marked differences. However, in general, compared with the land transfer strategy, the spatial interactions of the land-orientation investment strategy represent the more important factor that gives rise to the widespread deviation in the implementation of the cultivated land protection policy. (4) The transformation of the performance appraisal system can help to weaken the interactive behavior of the land financing strategy. This can, in turn, not only alleviate the deviation degree of the implementation of the local cultivated land protection policy, but also the deviation degree of the implementation of the latter in adjacent areas.

Hidden biases of racial and socioeconomic preferences shape residential neighborhoods throughout the USA. Thereby, these preferences shape neighborhoods composed predominantly of a particular race or income class. However, the assessment of spatial extent and the degree of isolation outside the residential neighborhoods at large scale is challenging, which requires further investigation to understand and identify the magnitude and underlying geospatial processes. With the ubiquitous availability of location-based services, large-scale individual-level location data have been widely collected using numerous mobile phone applications and enable the study of neighborhood isolation at large scale. In this research, we analyze large-scale anonymized smartphone users’ mobility data in Milwaukee, Wisconsin, to understand neighborhood-to-neighborhood spatial interaction patterns of different racial classes. Several isolated neighborhoods are successfully identified through the mobility-based spatial interaction network analysis.

© 2019, Science Press. With rapid development of air transportation, the airspace structure of the future will need to be flexible and dynamic to accommodate the increase in traffic demand. The corridors-in-the-sky has become a new technology to support the full exploitation and utilization of airspace resources. This paper proposes a method of designing corridor, identifying congestion state, and analyzing the influence of air routes’ traffic flow. From this, we have reached a number of conclusions. (1) The congestion periods present the multi-peak “wavy” scattered distributions and the peaks back-end agglomeration characteristics in the whole day. (2) The congestion segments present the structural characteristics of unbalanced coverage and concentrated distribution to the crossing points. The corridors with high congestion level present as an italic “N-shaped” frame, which presents incomplete penetration of short segments. (3) For the temporal and spatial interaction, there are two types of congestion segments, and there are some common congestion periods in different congestion segments of multiple corridors. The high-density air route plays a relatively decisive role in corridor congestion, and the influence of two directions is unbalanced. This research can provide a basis for the dynamic evaluation of China’s airspace resources and corridors construction in the future.

The relationship between the regional economy and the infrastructure endowment has long been discussed in the literature. In this context, it can be said that ports play an important role for regions, as they affect their competitiveness, while the regional economic activity has an effect on port traffic. Both circumstances influence the inland distribution of maritime traffic and are interconnected by the configuration of the hinterland of ports. The hypothesis of this paper is that spatial interaction effects, both exogenous and endogenous, shape the inter-port distribution of maritime traffic. The endogenous interaction effect arises when the inter-port distribution of the flows is influenced by those of nearby regions, whereas the exogenous interaction effect appears when the circumstances of these neighbours affect the flows generated by the region considered. The inter-port distribution of Spanish maritime flows of foreign trade for the period 1995–2015 was analysed in order to confirm the validity of this hypothesis. To that end, the Spatial Econometric Interaction Modelling (SEIM) framework was followed, and a Spatial Durbin Model (SDM) to origin-destination flows was applied. The results confirm that endogenous and exogenous interaction effects impact the inland distribution of the Spanish container flows and reveal the existence of direct and network effects regarding the variables analysed.

Purpose The purpose of this paper is to explore the prospects of Malaysian seaports as hubs for seaport tourism. This symbiosis nexus between seaports and tourism needs to be explored to provide a luxury economic growth. Combinations of these two segments are expected to explore a new market in Malaysian tourism industry. Design/methodology/approach A thorough case study consists of five major seaports in Malaysia including Penang Port, Port Klang, Port of Tanjung Pelepas, Kuantan Port, Bintulu Port and Kota Kinabalu; these seaports have been selected to reveal their opportunities for the prospect of Malaysian seaport tourism via spatial interaction model. Findings Four main components including cruise activities, support from intra-region and inter-region economic corridors and the seaport regionalisation can be integrated to reveal the capacity of Malaysian seaport to be hub for seaport tourism. Originality/value This paper incorporates tourism sector as one of the streams in the fifth-generation seaports. Seaports and tourism are two economic generators in Malaysia and infusion of these components is expected to enhance the economic prospect, diversify the function of seaports and reduce the over-dependence on conventional tourism activities.

We study the relationship between public infrastructure and economic growth of Brazilian municipalities between 1970 and 2010. We generalize the regional economic growth model developed Glaeser et al. (1995)by incorporating public capital in the production function of firms. As municipalities are assumed to be subjected to various forms of spatial interaction, we use an econometric method capable of accommodating heterogeneity and spatial dependence between municipalities. The results suggest that access to electricity contributes positively to regional economic growth, access to sewage collection has positive effects on population growth and access to water supplies has positive impacts on per capita wage growth. Este artigo estuda a relação empírica entre infraestrutura pública e crescimento econômico dosmunicípios brasileiros entre 1970 e 2010. Para isto, generaliza-se o modelo de crescimento econômico regional desenvolvido por Glaeser et al. (1995) incorporando o capital público na função de produção das firmas. Para estimação, opta-se por um método econométrico capaz de acomodar heterogeneidade e dependência espacial entre os municípios. Os resultados sugerem que o acesso à energia elétrica e ao abastecimento de água afetam positivamente o crescimento do salário per capita. Considerando crescimento populacional, encontra-se efeitos positivos do acesso à energia elétrica e à coleta de esgoto.

The change of trade structures from the dynamic development of production networks globally had caused processing trade to become more prominent in China. This change drives ASEAN5 to be more aggressive in developing vertical intra-industry trade (VIIT) with China. This study aims to identify the catalysts that strengthened the VIIT relationship between ASEAN5 and China for manufacturing sub-sectors. Both decomposition-type threshold method and spatial panel econometric modelling are used and the results show that foreign direct investment (FDI) and difference in gross domestic products (DGDP) are the influential determinants of VIIT although their impacts vary across manufacturing sub-sectors. The results also confirm the presence of spatial interaction effects among ASEAN5 countries in relation to China’s trade. These suggest that deeper economic integration among ASEAN5 countries is vital in strengthening bilateral VIIT with China. Moreover, to foster the value chain between the two regions, emphasis on performing similar tasks with differentiated varieties of products is essential as the two regions have similar comparative advantages.

The aim of this article is to distinguish types of the suburbs that are typical for post-socialist European countries. The typology organizes the variety of suburban forms according to the degree to which they favour the creation of public spaces, or the access to such spaces in the city or nearby town. A new typology is based on six criteria: (1) the level of neighbourhood (spatial scale), (2) the time when the neighbourhood was erected, (3) spatial interaction with the nearest town/city, (4) the prevailing type of investment, (5) street layout, (6) access to the city centre by public transport. Suburbs are diversified in terms of their potential for the establishment of public spaces. It has been proved that individual housing in the form of neighbourhoods which are planned, densely populated and based on street grid is the most preferred type from the perspective of building social capital. The typology was developed for Warsaw Metropolitan Region, although it may be applied also in the research of post-socialist countries other than Poland and urban regions within them.

“Bottom-up†cluster identification, as opposed to “assigning†clusters by the fact of enterprises coexisting on a compact territory, is an important scientific and practical problem. Its solution may be found in a survey of regions’ competitive specialization in order to identify spatial clusters based on industries with high-level competitive potential. The data on gross regional product (GRP) and national gross value added across industries were an empirical basis of the study. This article explores the possibility to identify territorial clusters in a region where its competitive specialization meets the high competitive potential of an industry. Research methodology stands on regional and spatial economics theories, employs traditional economic instruments of results’ verification. To achieve the expected results we employed traditional instruments of verification, economic and statistical analysis as research methodology. Studying a wide range of literature sources have resulted into development of innovative industrial approach to cluster formation by identifying clustering priorities and industries’ integration potential. The approach is based on the assessment of regions’ industrial specialization that can measure industry’s contribution to regions competitiveness, as well as density of interregional competitive relations. Such assessment is useful in determining industries potentially attractive for clustering. These industries can generate positive effect from utilizing territory’s specialization. Obvious specialization will either indicate potential’s depletion or reveal vectors for developing the most competitive industries that actually create efficient clusters. This approach contributes sufficiently to the theory and methodology of cluster paradigm of social and economic development, as it allows identifying de-facto existing clusters instead of creating them artificially. The key principle of the method is prioritizing as a cluster an industry, which is characterized by maximum productivity in social and economic spheres. Considering the competition between regions and different levels of industry development, it is possible to identify perspective directions for advancing regions strategic competitiveness. Further research will be aimed at the method’s verification and expansion by analyzing prolonged retrospective of specific data, including the gravity components of the connectedness of regions economic space and network interactions effects between the participants of “artificial†and “natural†clusters in the Russian Federation.

Understanding spatial interactions such as human mobility has been one of the main analytical themes in geography, spatial economics, and traffic engineering for a long time. The intervening opportunities models, including the radiation model, provide a framework to elucidate spatial interactions generated by an individual’s distance-ordered decision-making process. However, such classical definitions of intervening opportunities have often failed to predict realistic flow volumes, particularly for short-distance flows. To overcome this problem, we have proposed a new formulation of intervening opportunities with a kernel function to introduce a fuzziness in spatial search behaviours of destinations, to develop a new variant of the radiation model. The mobility patterns resulting from the modified radiation model that included kernel-based intervening opportunities outperformed the original radiation model when fitted to four datasets of inter-regional flows.

In this work, we describe the design of a customized user interface (UI) for a mixed reality application in a heritage site. The visuals, widgets and spatial interaction techniques have been customized to improve the user experience without diverting the user’s attention by minimizing the effect of the limited field of view (FOV) of the see-through head-mounted display (HMD) used, Microsoft HoloLens v1. The approach consists in using diegetic elements that are coherent with the narrative of the heritage site, and widgets and augmented layers always entirely included in the FOV of the see-through display.

14 pages, 5 figures, 2 tables, supplementary information https://doi.org/10.1016/j.scitotenv.2020.142564, Climate change (CC) is a key, global driver of change of marine ecosystems. At local and regional scales, other local human stressors (LS) can interact with CC and modify its effects on marine ecosystems. Understanding the response of the marine environment to the combined effects of CC and LS is crucial to inform marine ecosystem-based management and planning, yet our knowledge of the potential effects of such interactions is fragmented. At a global scale, we explored how cumulative effect assessments (CEAs) have addressed CC in the marine realm and discuss progress and shortcomings of current approaches. For this we conducted a systematic review on how CEAs investigated at different levels of biological organization ecological responses, functional aspects, and the combined effect of CC and HS. Globally, the effects of 52 LS and of 27 CC-related stressors on the marine environment have been studied in combination, such as industrial fisheries with change in temperature, or sea level rise with artisanal fisheries, marine litter, change in sediment load and introduced alien species. CC generally intensified the effects of LS at species level. At trophic groups and ecosystem levels, the effects of CC either intensified or mitigated the effects of other HS depending on the trophic groups or the environmental conditions involved, thus suggesting that the combined effects of CC and LS are context-dependent and vary among and within ecosystems. Our results highlight that large-scale assessments on the spatial interaction and combined effects of CC and LS remain limited. More importantly, our results strengthen the urgent need of CEAs to capture local-scale effects of stressors that can exacerbate climate-induced changes. Ultimately, this will allow identifying management measures that aid counteracting CC effects at relevant scales, This article is based upon work from COST Action 15121 ‘Advancing marine conservation in the European and contiguous seas’ [MarCons (Katsanevakis et al., 2017); http://www.marcons-cost.eu] – supported by COST (European Cooperation in Science and Technology, CA15121). EG partially acknowledges also funding from the project PORTODIMARE “geoPORtal of TOols & Data for sustaInable Management of coAstal and maRine Environment” (2018–2020), Adriatic-Ionian Programme INTERREG Vsingle bondB Transnational 2014–2020, grant no. 205; MC partially from the EU Horizon 2020 research and innovation programme under grant agreement no 817578 (TRIATLAS project). With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

This introductory chapter provides a brief overview of the theories and models that constitute what has come to be called urban science. Explaining and measuring the spatial structure of the city in terms of its form and function is one of the main goals of this science. It provides links between the way various theories about how the city is formed, in terms of its economy and social structure, and how these theories might be transformed into models that constitute the operational tools of urban informatics. First the idea of the city as a system is introduced, and then various models pertaining to the forces that determine what is located where in the city are presented. How these activities are linked to one another through flows and networks are then introduced. These models relate to formal models of spatial interaction, the distribution of the sizes of different cities, and the qualitative changes that take place as cities grow and evolve to different levels. Scaling is one of the major themes uniting these different elements grounding this science within the emerging field of complexity. We then illustrate how we might translate these ideas into operational models which are at the cutting edge of the new tools that are being developed in urban informatics, and which are elaborated in various chapters dealing with modeling and mobility throughout this book.

Disease dynamics, human mobility, and public policies co-evolve during a pandemic such as COVID-19. Understanding dynamic human mobility changes and spatial interaction patterns are crucial for understanding and forecasting COVID-19 dynamics. We introduce a novel graph-based neural network(GNN) to incorporate global aggregated mobility flows for a better understanding of the impact of human mobility on COVID-19 dynamics as well as better forecasting of disease dynamics. We propose a recurrent message passing graph neural network that embeds spatio-temporal disease dynamics and human mobility dynamics for daily state-level new confirmed cases forecasting. This work represents one of the early papers on the use of GNNs to forecast COVID-19 incidence dynamics and our methods are competitive to existing methods. We show that the spatial and temporal dynamic mobility graph leveraged by the graph neural network enables better long-term forecasting performance compared to baselines.

This study examines whether threat of stricter regulation influences the pricing behavior of firms. Using data on unregulated Swedish local district heating monopolists, we measure the threat level by the number of customer complaints about prices received by a national board. Exploiting a natural experiment, we find that firms reduce prices when customer complaints increase.

A quantitative study of urban vitality brings new insights for evaluating the external construction environment and internal development power of cities. However, it still has limited knowledge of the relations between people&rsquo, s diverse urban life and urban vitality, although urban activities are often used as the proxy for urban vitality. This paper aims to deeply mine the content of urban social life and reveal the driving mechanism of urban vitality after inspecting human activities. We propose a general framework for exploring the spatial pattern and driving mechanism of urban vitality using multi-source big data. It builds a mapping relationship between various urban activities and urban vitality aspects, including economic and social. In addition, the physical environment (static) and human&ndash, land interaction (dynamic) indicators are designed to analyze the driving mechanism of urban vitality using the Geographically Weighted Regression model. The results show that the spatial pattern and driving factors of urban vitality are heterogeneous over space regarding both the economic and social aspects of our experimental study. This work provides us with multiple perspectives to understand the connotation of urban vitality and urges us to develop rational strategies to make the city more vital, coordinated, and sustainable.

International audience; While the spatial and functional relationships between ports and cities have been put in question in the last decades, the continued importance of urbanization and maritime transport in global socio-economic development motivates deeper research on their interaction. The global trade network is often studied at the country level and all transport modes included, concluding that distance remains a strong counterforce to exchange. This article wishes to detect whether the global container shipping network obeys similar properties at the city level. More than 2 million inter-port vessel movements between 1977 and 2016 are assigned to about 9000 ports and 4600 cities to run a gravity model on two different network topologies. Gravitational properties are found, as larger cities connect more with each other but less at distance. The degree of distance effects negatively expanded in 40 years, confirming the “puzzling” or reinforcing effect of distance, yet it varies greatly depending on node aggregation and network topology. We conclude that ports and cities continue to share important interdependencies, but these often rest on a detrimental physical transformation. A discussion is proposed about the underlying operational and theoretical mechanisms at stake. Keywords container shipping; gravity model; maritime trade; port cities; spatial interaction; world city networks.

As the transitional area between urban and rural areas, land-use change in suburbs is drastic, which generates negative effects on the ecological environment. However, the identification of the suburbs remains controversial. Usually, the density of the population and residential land is referenced, and the close spatial interactions between urban areas and suburbs are generally neglected. To fill this research gap, this study adopts a case study method to map the suburbs of Jiangsu based on estimating the spatial interactions. First, a regression model is built to estimate the population distribution. Second, a radiation model is utilized to evaluate the spatial interaction at a grid level. After the main urban area is identified based on the high density of the population and construction land, the interaction strength between the main urban grid and other grid areas is calculated, and the grids that share high values of interaction strength with urban grids are identified as suburban areas. Finally, the suburbs of Jiangsu in 1998 and 2018 are mapped, and the ecological landscape pattern metrics are used to verify the effects of suburban expansion. As a result, the suburban expansion of Jiangsu over the 20 years was significant, and the effects of suburban expansion on ecological land fragmentation were evident. On the basis of the results, the enlightenment of mapping suburbs on ecological landscape planning is discussed.

This chapter explores the role of strategic interactions that affect the spatial allocation of structural funds in the European Union. More specifically, this chapter seeks to test if the interactions between government decisions are strategic substitutes or complements in the context of the European structural funds allocation. First, we present a theoretical model which depicts how the strategic interactions could affect the allocation of public grants in a bargaining process. Then, we test the direction of strategic interaction on the allocation of structural funds for the 2000–2006 programming period using spatial econometric techniques. We find a negative spatial interaction between European funds allocated to a region and the funds received by its neighborhood. Our results suggest strategic substitutability in the lobbying effort of regions to attract European funds.

Spatial interaction models have seen extensive use in public and private sector planning over the past 50 years. This paper reviews a number of facets of the application of these models. In particular we focus on developments in testing how well the models work in a number of different contexts related to applied spatial analysis and planning. We also speculate on the future of spatial interaction modelling in an era of ‘Big Data’.

A theoretical model was developed using the entropy approach to cope with the random component of the utility function to find that the spatial accessibility improves as the provider capacity increases or the opportunity cost of traveling to and from health provider decreases. The Kernel Density Estimation of the model show disparities in healthcare accessibility with extensive pockets of poor accessibility in rural and peripheral areas in Texas, when using hospitals’ location and number of hospital beds or counties’ centroid and data on Primary Care Physician. The model can be beneficially used to evaluate policies indicative of changes in the provision of health services, such as closures of rural hospitals or capacity increases, potentially have spatially very differentiated accessibility outcomes.

Many papers analyse the role of transport infrastructure in the economic development and competitiveness of regions. However, the literature has paid little attention to the impact of the changing patterns of international trade on the use of the infrastructure. The hypothesis of this work is that the evolution of the geographical pattern of countries' foreign trade influences the inland distribution of maritime traffic and, consequently, the use of the infrastructure. The inter-port distribution of the Spanish exports in 2000 and 2015 was analysed in order to confirm the validity of this hypothesis. To that end, the Spatial Interaction Models approach was adopted. The results suggest that the final destination of the flows does influence the inland distribution of the Spanish container flows and, consequently, that the use of the inland transport infrastructure has evolved in line with the geographical pattern of foreign trade.

Movement patterns of intra-urban goods/things and the ways they differ from human mobility and traffic flow patterns have seldom been explored due to data access and methodological limitations, esp...

Accounting for spatial interactions between farms is highly relevant for the analysis of agricultural policy impacts. Existing studies, however, only account for homogeneous (average) spatial interactions. We develop a mixture modelling framework to account for unobserved heterogeneity, allowing spatial interaction to vary across endogenously defined farm types. We apply this approach to study farmer decisions to exit the farming business using a large panel dataset covering all registered farms in Brittany, France, for the period 2004–2014. While exiting is on average positively correlated with neighbouring farm size, we find substantial variation between farm types, and a negative correlation for a significant proportion of farms. The approach we develop not only enables us to identify different correlations between neighbouring farm size and exits from farming but also yields different results than pooled estimations.

Under China’s Belt and Road (B&R) initiative, Carat Canal, a potential new channel of the Century Maritime Silk Road, will have a great impact on the shipping networks and the evolution of hub ports. A modified gravity prediction model with entropy maximizing principle is developed to calculate the changes in transshipment traffic. Taking account both customer preferences and spatial interaction, numerical experiments show that the opening of the Carat Canal shifts traffic volumes from the Malacca Strait, influences transshipment market shares among hub ports, and diversifies shipping network pattern. This study serves as a reference for hub port development along the Maritime Silk Road.

This study analyses the effect of the spatial factor, location, and interaction effects among peer companies, on the productivity growth of agri‐food companies in Spain. With this aim, we build a productivity growth index and apply a multiequational Seemingly Unrelated Regression on a sample of 344 Spanish cooperatives and investor‐owned firms for the period 2010–2012. Our findings show that agri‐food firms are influenced by spatial factors finding interesting differences between cooperatives and investor‐owned firms. With regard to the geographical location, cooperatives in the western of Spain show higher productivity growth rates, whereas investor‐owned firms in the northeast of Spain present better results. The interaction effect among closer peer companies is also a relevant factor to determine the productivity growth in agri‐food companies. This factor is more relevant for cooperatives than for investor‐owned firms.

Data and estimates on the spatial distribution of consumer spending form the foundation of retail location analysis and location-allocation spatial interaction models. The presented research presents and compares four methods to estimate consumer spending that combine different levels of detail in household spending data across multiple levels of household aggregation (i.e. census units). Results demonstrate that these methods, which use publicly available census data, can capture a substantial amount of reported sales. Furthermore, comparison of the best method with the de facto industry standard for business data in Canada shows a strong correlation (R2 > 0.85) across space and is within 10% of aggregate industry-derived spending estimate. Analysis of the spending data across space finds that the majority of spending occurs in census metropolitan areas with high spending clusters that offer unique opportunities for retail location. We interrogate the socio-demographic characteristics of the popu...

Owing to the complexity of sources and nonlinear dose-response relationship, evaluating the combined risks of pollutants in lakes remains a considerable challenge. In this study, we developed chose a non-parametric risk assessment method with source diagnostic and spatial interactions (LISA analysis) between the pollutants was developed for zoning the risks of combined pollution. Taihu Lake was chosen as the studied region, and the heavy metals and polycyclic aromatic hydrocarbons (PAHs) in the sediments were observed to test this method. Results showed that the developed method distinguished the “hot spots” of pollution in the eastern and northern Taihu Lake, and more than 50% pollutants were attributed to the combustion of petroleum fossil fuels. The main risk control area for heavy metals is mostly distributed in western Taihu Lake, accounting for 22.5% of the total area, while that for PAHs accounts for the smallest proportion, at only 3.4% of the total area. This study shows that the spatial interaction between pollutants could be a useful tool for evaluating the combined risks of pollutants, which can also provide better decision support for lake risk management.

Polycentric urban development is gaining momentum in both scholarly research and real-life practice. This brings new demand for planning support systems to simulate and analyse the urban spatial structure in terms of polycentricity under various urban policy scenarios. With the help of emerging urban data, urban simulation techniques, and network science, this study proposes a workflow to simulate the urban spatial structure with spatial interaction as a part of the planning support system. Using Singapore as a case study, this study has explored the resulting urban spatial structure with four employment distribution strategies. The results suggest that planning practices impact urban spatial structure and its spatial interaction by redistributing urban morphological elements, such as employment in this study. Also, our results show that the physical urban spatial structure and spatial interaction are closely related. These results reinforce the role of urban planning practice to achieve a more sustainable and coherent urban built environment. Through this empirical evidence, our workflow exemplifies the potential of the planning support system to help urban planners and governments understand their urban policy regarding urban polycentricity.

This study aims to analyze the relationship between economic growth regency in Subosukawonosraten Region with leading sector approach. The linkage of leading sectors towards economic growth of other regions in the Subosukawonosraten Region determined by Multiple Linear Regression analysis. The results of the Multiple Linear Regression analysis is the most sector that has a significant influence on the other regional economic growth is sectors industry. In addition, sectors that have a significant influence on regional economic growth are real estate, agriculture, construction, information and communication, accommodation provision, trade, government and water supply, respectively.

Industrial upgrading plays a significant role in promoting eco-efficiency, but existing studies ignore this aspect. Using improved and comprehensive measures of eco-efficiency, we assess how industrial upgrading influences the eco-efficiency of a certain province with provincial panel data during the period 1998–2017. We find that industrial upgrading significantly promotes eco-efficiency and yields significantly positive spatial spillover effects. Our findings provide empirical evidence that the government should push forward industrial upgrading decisively, as well as strengthening inter-regional and central-provincial collaboration in promoting eco-efficiency.

This study focuses on diverse dimensions of distance shaping collaboration in Europe and the USA during the time period 1999–2009. We take a comparative perspective by analysing two different collaboration networks (patents and publications) and two different economic areas, in order to examine differences in collaboration activities. In particular, we investigate how the collaboration intensity between regions has been influenced by spatial, technological, and cultural distance and whether these distances have lost importance over time in the distinct networks. The study adopts a panel spatial interaction modelling perspective. The results show that indeed the impact of various kinds of distances differs between Europe and the USA and changes over time.

We develop a two-stage spatial point process model that introduces new characterizations of activation patterns in multi-subject functional Magnetic Resonance Imaging (fMRI) studies. Conventionally multi-subject fMRI methods rely on combining information across subjects one voxel at a time in order to identify locations of peak activation in the brain. The two-stage model that we develop here addresses shortcomings of standard methods by explicitly modeling the spatial stucture of functional signals and recognizing that corresponding cross-subject functional signals can be spatially misaligned. In our first stage analysis, we introduce a marked spatial point process model that captures the spatial features of the functional response and identifies a configuration of activation units for each subject. The locations of these activation units are used as input for the second stage model. The point process model of the second stage analysis is developed to characterize multi-subject activation patterns by estimating the strength of cross-subject interactions at different spatial ranges. The model uses spatial neighborhoods to account for the cross-subject spatial misalignment in corresponding functional units. We applied our methods to an fMRI study of 21 individuals who performed an attention test. We identified four brain regions that are involved in the test and found that our model results agree well with our understanding of how these regions engage with the tasks performed during the attention test. Our results highlighted that cross-subject interactions are stronger in brain areas that have a more specific function in performing the experimental tasks than in other areas.

The spatial location of an object can be represented in two frames of reference: egocentric (relative to the observer's body or body parts) and allocentric (relative to another object independent of the observer). The object positions relative to the two frames can be either congruent (e.g., both left or both right) or incongruent (e.g., one left and one right). Most of the previous studies, however, did not discriminate between the two types of spatial conflicts. To investigate the common and specific neural mechanisms underlying the spatial congruency effect induced by the two reference frames, we adopted a 3 (type of task: allocentric, egocentric, and color) × 2 (spatial congruency: congruent vs. incongruent) within-subject design in this fMRI study. The spatial congruency effect in the allocentric task was induced by the task-irrelevant egocentric representations, and vice versa in the egocentric task. The nonspatial color task was introduced to control for the differences in bottom-up stimuli between the congruent and incongruent conditions. Behaviorally, significant spatial congruency effect was revealed in both the egocentric and allocentric task. Neurally, the dorsal-medial visuoparietal stream was commonly involved in the spatial congruency effect induced by the task-irrelevant egocentric and allocentric representations. The right superior parietal cortex and the right precentral gyrus were specifically involved in the spatial congruency effect induced by the irrelevant egocentric and allocentric representations, respectively. Taken together, these results suggested that different subregions in the parieto-frontal network played different functional roles in the spatial interaction between the egocentric and allocentric reference frame. Hum Brain Mapp 38:2112-2127, 2017. © 2017 Wiley Periodicals, Inc.

El objetivo de esta investigación consiste en analizar la evolución de la distribución espacial y temporal de la inversión extranjera directa (IED) en las entidades federativas de México. La literatura que aborda el análisis de la IED en México es abundante y diversa; sin embargo, se argumenta que el análisis de la distribución espacio-temporal de la IED condicionada a la interacción espacial en México, aún está ausente. En este sentido, mediante la aplicación del enfoque de cadenas de Markov espaciales propuesto por Rey (2001), se encuentra que la divergencia regional en la captación de IED es un proceso que parece afianzarse cuando se analizan diferentes cortes en el tiempo. En particular, durante el periodo entre 2006 y 2013 el proceso de divergencia hacia estratos de mayor captación estaría impulsado por las entidades federativas que interactúan con entidades contiguas ubicadas en estratos de captación de IED menores.

Impacts of long distance commuting (LDC) on a host region have been a topic of research interest for some time. Recently, however, criticisms have surfaced about the validity of studies which address this topic. Specifically, temporal variability and spatial interaction have rarely been considered. This article argues that a single model which jointly incorporates these two aspects can improve the predictive power of LDC impacts. Using spatial panel modelling, 516 Local Government Areas (LGAs) across Australia over two census periods (2006 and 2011) were used to explore drivers of LDC. It was found that local labour market characteristics had minimal influence on recruitment strategies of firms that typically use LDC. Housing affordability does not impact on the decision of non-resident workers to either migrate into a region or adopt LDC into that region. However, local service provision and the availability of rental accommodation reduces the uptake of LDC. In addition, higher turnover of the resident population erodes social capital in host regions, which reduces the attractiveness of the local area and leads to increased use of LDC.