The spatial structure debate in spatial interaction modeling: 50 years on:

Spatial interaction and spatial structure are foundational geographical abstractions, though there is often variation in how they are conceptualized and deployed in quantitative models. In particul...

[1]  Bert van Wee,et al.  Accessibility Indicators for Location Choices of Offices: An Application to the Intraregional Distributive Effects of High-Speed Rail in the Netherlands , 2007 .

[2]  R. J. Bennett,et al.  Spatial Structure and Spatial Interaction: Modelling Approaches to the Statistical Analysis of Geographical Data , 1985 .

[3]  Daniel A. Griffith,et al.  SPATIAL AUTOCORRELATION and EIGENFUNCTIONS OF THE GEOGRAPHIC WEIGHTS MATRIX ACCOMPANYING GEO‐REFERENCED DATA , 1996 .

[4]  Xin Meng,et al.  Modelling interprovincial migration in China from 1995 to 2015 based on an eigenvector spatial filtering negative binomial model , 2019, Population, Space and Place.

[5]  M. Aitkin,et al.  A method of fitting the gravity model based on the Poisson distribution. , 1982, Journal of regional science.

[6]  Peter Nijkamp,et al.  Dynamic Spatial Interaction Models: New Directions , 1987 .

[7]  Britton Harris,et al.  Equilibrium Values and Dynamics of Attractiveness Terms in Production-Constrained Spatial-Interaction Models , 1978 .

[8]  Marc Gaudry,et al.  Spatially autocorrelated errors in origin-destination models: A new specification applied to aggregate mode choice☆ , 1989 .

[9]  Emanuela Marrocu,et al.  Different tourists to different destinations. Evidence from spatial interaction models , 2013 .

[10]  Joris Pinkse,et al.  The Future of Spatial Econometrics , 2010 .

[11]  Daniel A. Griffith,et al.  A Variance-Stabilizing Coding Scheme for Spatial Link Matrices , 1999 .

[12]  Matthieu de Lapparent,et al.  A comparison of Euclidean Distance, Travel Times, and Network Distances in Location Choice Mixture Models , 2019, Networks and Spatial Economics.

[13]  Daniel A. Griffith,et al.  A spatial filtering specification for the auto-Poisson model , 2002 .

[14]  D. Griffith,et al.  Explorations into the Relationship between Spatial Structure and Spatial Interaction , 1980 .

[15]  C. Beauchemin,et al.  Three sub-Saharan migration systems in times of policy restriction , 2020, Comparative Migration Studies.

[16]  D. Bolduc,et al.  Spatial Autoregressive Error Components in Travel Flow Models: An Application to Aggregate Mode Choice , 1995 .

[17]  Alan Wilson.  Urban and Regional Dynamics from the Global to the Local: Hierarchies, ‘DNA’, and ‘Genetic’ Planning , 2010 .

[18]  S. Openshaw,et al.  A comparison of migration behaviour in Japan and Britain using spatial interaction models , 2003 .

[19]  Daniel A. Griffith,et al.  Visualizing analytical spatial autocorrelation components latent in spatial interaction data: An eigenvector spatial filter approach , 2011, Comput. Environ. Urban Syst..

[20]  F. Mello-Sampayo.  A Spatial Analysis of Mental Healthcare in Texas , 2016 .

[21]  C. Thomas-Agnan,et al.  Spatial dependence in (origin‐destination) air passenger flows , 2014 .

[22]  J. Pooler.  Competition among destinations in spatial interaction models: a new point of view , 1998 .

[23]  Daniel A. Griffith,et al.  A linear regression solution to the spatial autocorrelation problem , 2000, J. Geogr. Syst..

[24]  A. Stewart Fotheringham,et al.  Encoding Spatial Information: The Evidence for Hierarchical Processing , 1992, Spatio-Temporal Reasoning.

[25]  Manfred M. Fischer,et al.  The Geography of Knowledge Spillovers between High-Technology Firms in Europe - Evidence from a Spatial Interaction Modelling Perspective , 2006 .

[26]  A. Fotheringham.  Spatial Flows and Spatial Patterns , 1984 .

[27]  A. Curtis,et al.  Large-scale information surfaces: an analysis of city-name recalls in the United States , 1995 .

[28]  J. Arvis,et al.  The Poisson quasi-maximum likelihood estimator: a solution to the ‘adding up’ problem in gravity models , 2013 .

[29]  Ian R. Gordon.  Economic Explanations of Spatial Variation in Distance Deterrence , 1985 .

[30]  E. Sheppard.  The Distance-Decay Gravity Model Debate , 1984 .

[31]  J. Hodges,et al.  Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love , 2010 .

[32]  Juan de Dios Ortúzar,et al.  Modelling Transport: Ortúzar/Modelling Transport , 2011 .

[33]  Tom Thomas,et al.  An empirical model for trip distribution of commuters in the Netherlands: Transferability in time and space reconsidered. , 2013 .

[34]  D. McMillen,et al.  Perspectives on Spatial Econometrics: Linear Smoothing with Structured Models , 2012 .

[35]  Y Ishikawa.  An Empirical Study of the Competing Destinations Model Using Japanese Interaction Data , 1987 .

[36]  Riccardo Scarpa,et al.  Cumulative attraction and spatial dependence in a destination choice model for beach recreation , 2018, Tourism Management.

[37]  A. Fotheringham.  SPATIAL STRUCTURE AND DISTANCE‐DECAY PARAMETERS , 1981, Annals of the Association of American Geographers.

[38]  Manfred M. Fischer,et al.  Constrained variants of the gravity model and spatial dependence: model specification and estimation issues , 2013, J. Geogr. Syst..

[39]  Daniel A. Griffith,et al.  Spatial Structure and Spatial Interaction: 25 Years Later , 2007 .

[40]  Alison J. Heppenstall,et al.  Extending Spatial Interaction Models with Agents for Understanding Relationships in a Dynamic Retail Market , 2011 .

[41]  Inge Thorsen,et al.  A Competing Destinations Approach to Modeling Commuting Flows: A Theoretical Interpretation and An Empirical Application of the Model , 2000 .

[42]  Robert Walker,et al.  Searching for New Manufacturing Plant Locations: A Study of Location Decisions in Central Appalachia , 1990 .

[43]  A S Fotheringham,et al.  Intermetropolitan Migration and Hierarchical Destination Choice: A Disaggregate Analysis from the US Public Use Microdata Samples , 1999 .

[44]  L. Lo,et al.  Substitutability, Spatial Structure, and Spatial Interaction , 2010 .

[45]  H. Overman,et al.  Mostly Pointless Spatial Econometrics? , 2012 .

[46]  Daniel A. Griffith,et al.  Spatial Autocorrelation in Spatial Interaction , 2009 .

[47]  Martin Clarke,et al.  Developing and Applying a Disaggregated Retail Location Model with Extended Retail Demand Estimations , 2015 .

[48]  Frank J. Cesario,et al.  A new interpretation of the “normalizing” or “balancing” factors of gravity-type spatial models , 1977 .

[49]  Daniel A. Griffith,et al.  Random effects specifications in eigenvector spatial filtering: a simulation study , 2015, J. Geogr. Syst..

[50]  J. Ord,et al.  Evaluating the friction of distance parameter in gravity models , 1974 .

[51]  Jianbang Gan,et al.  Spatial spillover effects of global forest product trade , 2020 .

[52]  Paul Harris,et al.  A Simulation Study on Specifying a Regression Model for Spatial Data: Choosing between Autocorrelation and Heterogeneity Effects , 2019 .

[53]  A. Fotheringham,et al.  Spatial Competition and Agglomeration in Urban Modelling , 1985 .

[54]  Daniel A. Griffith,et al.  Spatially varying coefficient models in real estate: Eigenvector spatial filtering and alternative approaches , 2016, Comput. Environ. Urban Syst..

[55]  A. Stewart Fotheringham,et al.  Spatially Weighted Interaction Models (SWIM) , 2016 .

[56]  Pierre Legendre,et al.  All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices , 2002 .

[57]  Yongwan Chun,et al.  Modeling network autocorrelation within migration flows by eigenvector spatial filtering , 2008, J. Geogr. Syst..

[58]  Daniel A. Griffith,et al.  Spatial Structure and Spatial Interaction: A Review , 1976 .

[59]  Stéphane Dray,et al.  Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM) , 2006 .

[60]  James P. LeSage,et al.  Interpretation and Computation of Estimates from Regression Models using Spatial Filtering , 2013 .

[61]  M. Baxter.  Model Misspecification and Spatial Structure in Spatial-Interaction Models , 1983 .

[62]  A. Stewart Fotheringham,et al.  Modeling Discontinuous Change in Retailing Systems: Extensions of the Harris- Wilson Framework With Results From a Simulated Urban Retailing System , 2010 .

[63]  Christopher J Paciorek,et al.  The importance of scale for spatial-confounding bias and precision of spatial regression estimators. , 2010, Statistical science : a review journal of the Institute of Mathematical Statistics.

[64]  Clifford M. Guy.  Recent Advances in Spatial Interaction Modelling: An Application to the Forecasting of Shopping Travel , 1987 .

[65]  J. Ubøe,et al.  Laboratory Testing of Spurious Spatial Structure in Trip Distribution Models , 2008 .

[66]  Stamatis Kalogirou,et al.  Destination Choice of Athenians: An Application of Geographically Weighted Versions of Standard and Zero Inflated Poisson Spatial Interaction Models , 2016 .

[67]  Andries S. Brandsma,et al.  A Biparametric Approach to Spatial Autocorrelation , 1979 .

[68]  Tomoki Nakaya,et al.  Hierarchical Destination Choice and Spatial Interaction Modelling: A Simulation Experiment , 2001 .

[69]  Economic Geography: Spatial Interaction , 2017 .

[70]  Ticiana Grecco Zanon Moura,et al.  Spatial interaction effects on inland distribution of maritime flows , 2019, Transportation Research Part A: Policy and Practice.

[71]  Gerald A. P. Carrothers.  An Historical Bedew of the Gravity and Potential Concepts of Human Interaction , 1956 .

[72]  Jessica Gurevitch,et al.  Ecography 25: 601 -- 615, 2002 , 2022 .

[73]  E. Sheppard,et al.  Those gravity parameters again , 1975 .

[74]  David E. Boyce,et al.  Enhanced Destination Choice Models Incorporating Agglomeration Related to Trip Chaining While Controlling for Spatial Competition , 2009 .

[75]  Alan Wilson,et al.  A statistical theory of spatial distribution models , 1967 .

[76]  A. Stewart Fotheringham,et al.  Calibrating spatial interaction models from GPS tracking data: An example of retail behaviour , 2019, Comput. Environ. Urban Syst..

[77]  A. Curtis,et al.  Regularities in Spatial Information Processing: Implications for Modeling Destination Choice , 1999 .

[78]  Steven Brakman,et al.  Introduction: Whither Spatial Econometrics? , 2012 .

[79]  P. Legendre,et al.  Modelling directional spatial processes in ecological data , 2008 .

[80]  G. Leckie,et al.  Analysing inter-provincial urban migration flows in China: A new multilevel gravity model approach , 2018, Migration Studies.

[81]  Estimating and interpreting internal migration flows in Russia by accounting for network effects , 2020, Socio-Economic Planning Sciences.

[82]  L. Lo,et al.  Spatial Structure and Spatial Interaction: A Simulation Approach , 1991 .

[83]  Daniel A. Griffith,et al.  Spatial Autocorrelation in Spatial Interactions Models: Geographic Scale and Resolution Implications for Network Resilience and Vulnerability , 2015 .

[84]  E. Manley,et al.  New Forms of Data for Understanding Urban Activity in Developing Countries , 2018, Applied Spatial Analysis and Policy.

[85]  E. Nissi,et al.  Detecting Local Variations in Spatial Interaction Models by Means of Geographically Weighted Regression , 2011 .

[86]  Daniel A. Griffith,et al.  A final comment on mis-specification and autocorrelation in those gravity parameters , 1976 .

[87]  Mike Baxter.  Misspecification in Spatial Interaction Models: Further Results , 1985 .

[88]  Manfred M. Fischer,et al.  Modeling Spatial Autocorrelation in Spatial Interaction Data: An Application to Patent Citation Data in the European Union , 2008 .

[89]  A. Stewart Fotheringham,et al.  Spatial Structure and the Parameters of Spatial Interaction Models , 2010 .

[90]  Y. Ishikawa.  Explorations into the Two-stage Destination Choice , 1989 .

[91]  J. Horowitz,et al.  TRAVEL-TIME CONSTRAINTS ON DESTINATION-CHOICE SETS. , 2010 .

[92]  Yoshiki Yamagata,et al.  Application of Lasso to the Eigenvector Selection Problem in Eigenvector Based Spatial Filtering , 2013 .

[93]  E. Sheppard.  Gravity Parameter Estimation , 2010 .

[94]  Inge Thorsen,et al.  Empirical Evaluation of Alternative Model Specifications to Predict Commuting Flows , 1998 .

[95]  Martin Clarke,et al.  From Big Noise to Big Data: Toward the Verification of Large Data sets for Understanding Regional Retail Flows , 2016 .

[96]  Daniel A. Griffith,et al.  Eigenvector selection with stepwise regression techniques to construct eigenvector spatial filters , 2016, J. Geogr. Syst..

[97]  Pingzhao Hu,et al.  An empirical test of the competing destinations model , 2002, J. Geogr. Syst..

[98]  F. Mello-Sampayo.  Testing competing destinations gravity models – evidence from BRIC international , 2017 .

[99]  Cheng Jin,et al.  Spatial Interaction Modeling of OD Flow Data: Comparing Geographically Weighted Negative Binomial Regression (GWNBR) and OLS (GWOLSR) , 2019, ISPRS Int. J. Geo Inf..

[100]  Daniel A. Griffith,et al.  Modeling spatial autocorrelation in spatial interaction data: empirical evidence from 2002 Germany journey-to-work flows , 2009, J. Geogr. Syst..

[101]  Karel Martens,et al.  A multilevel spatial interaction model of transit flows incorporating spatial and network autocorrelation , 2017 .

[102]  Jean-Claude Thill,et al.  Choice set formation for destination choice modelling , 1992 .

[103]  L. Curry.  A Spatial Analysis of Gravity Flows , 1972, The Random Spatial Economy and Its Evolution.

[104]  William R. Black,et al.  Network Autocorrelation in Transport Network and Flow Systems , 2010 .

[105]  L Lo.  Destination Interdependence and the Competing-Destinations Model , 1992 .

[106]  M. Clarke,et al.  Accounting for Temporal Demand Variations in Retail Location Models , 2018, Geographical Analysis.

[107]  G. Mulligan,et al.  Labor Migration Amongst Hierarchically Competing and Intervening Origins and Destinations , 1992, Environment & planning A.

[108]  Distance-decay parameters: a comment , 1982 .

[109]  Hanna Tuomisto,et al.  DISSECTING THE SPATIAL STRUCTURE OF ECOLOGICAL DATA AT MULTIPLE SCALES , 2004 .

[110]  A. Fotheringham,et al.  AN EMPIRICAL EVALUATION OF PARAMETER SENSITIVITY TO CHOICE SET DEFINITION IN SHOPPING DESTINATION CHOICE MODELS , 2005 .

[111]  Taylor Oshan,et al.  A primer for working with the Spatial Interaction modeling (SpInt) module in the python spatial analysis library (PySAL) , 2016 .

[112]  S. Fox,et al.  Quantitative geography III: Future challenges and challenging futures , 2020 .

[113]  Chang-i Hua,et al.  A Critical Review of the Development of the Gravity Model , 1979 .

[114]  R. Pace,et al.  Spatial Distribution of Retail Sales , 2005 .

[115]  Alan Wilson,et al.  Boltzmann, Lotka and Volterra and spatial structural evolution: an integrated methodology for some dynamical systems , 2008, Journal of The Royal Society Interface.

[116]  José Manuel Viegas,et al.  A new approach to modelling distance-decay functions for accessibility assessment in transport studies , 2013 .

[117]  Manfred M. Fischer,et al.  Knowledge Spillovers across Europe. Evidence from a Poisson Spatial Interaction Model with Spatial Effects , 2015 .

[118]  Manfred M. Fischer,et al.  A Spatial Autoregressive Poisson Gravity Model , 2013 .

[119]  A. Fotheringham,et al.  Modelling Hierarchical Destination Choice , 1986 .

[120]  C. Lloyd.  Measuring Spatial Structure , 2014 .

[121]  Ye Liu,et al.  Modelling Skilled and Less‐Skilled Interregional Migrations in China, 2000–2005 , 2017 .

[122]  Daniel P. McMillen,et al.  Spatial Autocorrelation Or Model Misspecification? , 2003 .

[123]  J. LeSage,et al.  Spatial Econometric Modeling of Origin-Destination Flows , 2008 .

[124]  A S Fotheringham,et al.  A New Set of Spatial-Interaction Models: The Theory of Competing Destinations † , 1983 .

[125]  Daniel A. Griffith,et al.  A Spatial Filtering Specification for the Autologistic Model , 2004 .

[126]  Mike Coombes,et al.  Measuring destination attractivity: A migration example , 2000 .

[127]  J. Elhorst,et al.  The Slx Model , 2015 .

[128]  Jonathan Silberman,et al.  Knowledge flows between universities and industry: the impact of distance, technological compatibility, and the ability to diffuse knowledge , 2019 .

[129]  Competing-destinations gravity model applied to trade in intermediate goods , 2017 .

[130]  B. Fingleton,et al.  Where is the Economics in Spatial Econometrics? , 2012 .

[131]  S. Fotheringham,et al.  Modelling spatial choice: a review and synthesis in a migration context , 2002 .

[132]  C. Ghisetti,et al.  Analysing domestic tourism flows at the provincial level in Spain by using spatial gravity models , 2020 .

[133]  Philip Rees,et al.  The Development of a Migration Model for England and Wales: Overview and Modelling Out-Migration , 2004 .

[134]  J. Ord,et al.  Map pattern and friction of distance parameters: reply to comments by R. J. Johnston, and by L. Curry, D. A. Griffith and E. S. Sheppard , 1975 .

[135]  Alan Wilson,et al.  Entropy in Urban and Regional Modelling: Retrospect and Prospect. 城市和区域建模中的熵：回顾与展望 , 2010 .

[136]  Tamara de la Mata,et al.  Social networks and trade of services: modelling interregional flows with spatial and network autocorrelation effects , 2013, J. Geogr. Syst..

[137]  Daniel Arribas-Bel,et al.  Accidental, open and everywhere: Emerging data sources for the understanding of cities , 2014 .

[138]  Tomoki Nakaya,et al.  Introducing bootstrap methods to investigate coefficient non-stationarity in spatial regression models , 2017 .

[139]  A. Anas.  Discrete choice theory, information theory and the multinomial logit and gravity models , 1983 .

[140]  R. Johnston.  ON REGRESSION COEFFICIENTS IN COMPARATIVE STUDIES OF THE ‘FRICTIONS OF DISTANCE’ , 1976 .

[141]  Michael Tiefelsdorf,et al.  Misspecifications in interaction model distance decay relations: A spatial structure effect , 2003, J. Geogr. Syst..

[142]  Taylor M. Oshan.  Potential and Pitfalls of Big Transport Data for Spatial Interaction Models of Urban Mobility , 2020 .

[143]  R. Johnston.  Map pattern and friction of distance parameters: a comment , 1975 .

[144]  D. Bolduc,et al.  Spatial autoregressive error components in travel flow models , 1992 .

[145]  Michael Batty,et al.  Visualizing aggregate movement in cities , 2018, Philosophical Transactions of the Royal Society B: Biological Sciences.

[146]  Gordon F. Mulligan,et al.  Spatial Flows and Competing Central Places: Towards a General Theory of Hierarchical Interaction , 1990 .

[147]  Martin Clarke,et al.  Refining and Operationalizing Entropy‐Maximizing Models for Business Applications. 商业应用模式下熵最大化模型的应用与改进 , 2010 .

[148]  A. Stewart Fotheringham.  Distance-Decay Parameters: A Reply , 1982 .

[149]  J. Jonides,et al.  Evidence of hierarchies in cognitive maps , 1985, Memory & cognition.

[150]  Manfred M. Fischer,et al.  The spatial autocorrelation problem in spatial interaction modelling: a comparison of two common solutions , 2016 .

[151]  A. Porojan,et al.  Trade Flows and Spatial Effects: The Gravity Model Revisited , 2001 .

[152]  Rodolfo Metulini,et al.  The network of migrants and international trade , 2018, Economia Politica.

[153]  M. Fischer,et al.  Barriers to cross-region research and development collaborations in Europe: evidence from the fifth European Framework Programme , 2015 .

[154]  D. Griffith,et al.  Modeling Network Autocorrelation in Space–Time Migration Flow Data: An Eigenvector Spatial Filtering Approach , 2011 .

[155]  Peter Nijkamp,et al.  Exponential or Power Distance-Decay for Commuting? An Alternative Specification , 2005 .

[156]  A. Stewart Fotheringham,et al.  Analysis of human mobility patterns from GPS trajectories and contextual information , 2016, Int. J. Geogr. Inf. Sci..

[157]  Andrew A. Lovett,et al.  Fitting Constrained Poisson Regression Models to Interurban Migration Flows , 2010 .

[158]  Jianquan Cheng,et al.  A Multiscale Flow-Focused Geographically Weighted Regression Modelling Approach and Its Application for Transport Flows on Expressways , 2019, Applied Sciences.

[159]  Daniel A Griffith,et al.  Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses. , 2006, Ecology.

[160]  Yongwan Chun,et al.  Modeling interregional commodity flows with incorporating network autocorrelation in spatial interaction models: An application of the US interstate commodity flows , 2012, Comput. Environ. Urban Syst..

[161]  Martijn Burger,et al.  On the Specification of the Gravity Model of Trade: Zeros, Excess Zeros and Zero-Inflated Estimation , 2009 .

[162]  J. Guldmann.  Competing destinations and intervening opportunities interaction models of inter-city telecommunication flows , 1998 .

[163]  James P. LeSage,et al.  A spatial interaction model with spatially structured origin and destination effects , 2006, J. Geogr. Syst..

[164]  C. Thomas-Agnan,et al.  Interpreting Spatial Econometric Origin‐Destination Flow Models , 2015 .

[165]  A. Stewart Fotheringham,et al.  A Comparison of Spatially Varying Regression Coefficient Estimates Using Geographically Weighted and Spatial‐Filter‐Based Techniques , 2018 .

[166]  Keunseo Kim,et al.  Spatiotemporal auto‐regressive model for origin–destination air passenger flows , 2018, Journal of the Royal Statistical Society: Series A (Statistics in Society).

[167]  A. Fotheringham.  Note---Consumer Store Choice and Choice Set Definition , 1988 .

[168]  A reply to the final comment , 1976 .

[169]  T. McNamara.  Mental representations of spatial relations , 1986, Cognitive Psychology.

[170]  Wim Bernasco,et al.  Modeling Micro-Level Crime Location Choice: Application of the Discrete Choice Framework to Crime at Places , 2010 .