{"id":"https://openalex.org/W4323315450","doi":"https://doi.org/10.3390/ijgi12030109","title":"Spatial Non-Stationarity of Influencing Factors of China\u2019s County Economic Development Base on a Multiscale Geographically Weighted Regression Model","display_name":"Spatial Non-Stationarity of Influencing Factors of China\u2019s County Economic Development Base on a Multiscale Geographically Weighted Regression Model","publication_year":2023,"publication_date":"2023-03-04","ids":{"openalex":"https://openalex.org/W4323315450","doi":"https://doi.org/10.3390/ijgi12030109"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi12030109","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi12030109","pdf_url":"https://www.mdpi.com/2220-9964/12/3/109/pdf?version=1678174915","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/12/3/109/pdf?version=1678174915","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101694843","display_name":"Ziwei Huang","orcid":"https://orcid.org/0000-0002-6994-9017"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziwei Huang","raw_affiliation_strings":["School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510006, China","School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510006, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107873063","display_name":"Shaoying Li","orcid":"https://orcid.org/0000-0002-4703-5660"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaoying Li","raw_affiliation_strings":["School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China"],"raw_orcid":"https://orcid.org/0000-0002-4703-5660","affiliations":[{"raw_affiliation_string":"School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079040297","display_name":"Yihuan Peng","orcid":"https://orcid.org/0000-0002-3953-8815"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yihuan Peng","raw_affiliation_strings":["Guangdong Centre for Marine Development Research, Guangzhou 510220, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Centre for Marine Development Research, Guangzhou 510220, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021117983","display_name":"Feng Gao","orcid":"https://orcid.org/0000-0003-0398-4255"},"institutions":[{"id":"https://openalex.org/I4210126705","display_name":"Guangzhou Urban Planning Survey & Design Institute","ror":"https://ror.org/02crg7060","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210126705"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Gao","raw_affiliation_strings":["Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China","Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510030, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China","institution_ids":[]},{"raw_affiliation_string":"Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510030, China","institution_ids":["https://openalex.org/I4210126705"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5107873063"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":14.3499,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.98402758,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"12","issue":"3","first_page":"109","last_page":"109"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11014","display_name":"Regional Economics and Spatial Analysis","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10298","display_name":"Urban Transport and Accessibility","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/geographically-weighted-regression","display_name":"Geographically Weighted Regression","score":0.715488612651825},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.6754341125488281},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.6718615293502808},{"id":"https://openalex.org/keywords/urban-agglomeration","display_name":"Urban agglomeration","score":0.6276187300682068},{"id":"https://openalex.org/keywords/ordinary-least-squares","display_name":"Ordinary least squares","score":0.6138715147972107},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.5431851148605347},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5148164629936218},{"id":"https://openalex.org/keywords/yangtze-river","display_name":"Yangtze river","score":0.44984859228134155},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.4324556589126587},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4201034903526306},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4191589057445526},{"id":"https://openalex.org/keywords/economic-geography","display_name":"Economic geography","score":0.40128907561302185},{"id":"https://openalex.org/keywords/regional-science","display_name":"Regional science","score":0.39325258135795593},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.30398136377334595},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19102492928504944}],"concepts":[{"id":"https://openalex.org/C2910321205","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geographically Weighted Regression","level":2,"score":0.715488612651825},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.6754341125488281},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.6718615293502808},{"id":"https://openalex.org/C154611951","wikidata":"https://www.wikidata.org/wiki/Q393233","display_name":"Urban agglomeration","level":2,"score":0.6276187300682068},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.6138715147972107},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.5431851148605347},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5148164629936218},{"id":"https://openalex.org/C3018003528","wikidata":"https://www.wikidata.org/wiki/Q5413","display_name":"Yangtze river","level":3,"score":0.44984859228134155},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.4324556589126587},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4201034903526306},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4191589057445526},{"id":"https://openalex.org/C26271046","wikidata":"https://www.wikidata.org/wiki/Q187097","display_name":"Economic geography","level":1,"score":0.40128907561302185},{"id":"https://openalex.org/C148383697","wikidata":"https://www.wikidata.org/wiki/Q1781695","display_name":"Regional science","level":1,"score":0.39325258135795593},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.30398136377334595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19102492928504944},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/ijgi12030109","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi12030109","pdf_url":"https://www.mdpi.com/2220-9964/12/3/109/pdf?version=1678174915","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:65bbddbf20cd4d958e8a23dfe0a16f1c","is_oa":true,"landing_page_url":"https://doaj.org/article/65bbddbf20cd4d958e8a23dfe0a16f1c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information, Vol 12, Iss 3, p 109 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2220-9964/12/3/109/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/ijgi12030109","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/ijgi12030109","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi12030109","pdf_url":"https://www.mdpi.com/2220-9964/12/3/109/pdf?version=1678174915","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2957352141","display_name":null,"funder_award_id":"2020B121202019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5339226512","display_name":null,"funder_award_id":"RDI2220205141","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6279780978","display_name":null,"funder_award_id":"41871290","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7967246139","display_name":null,"funder_award_id":"42271467","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4323315450.pdf"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W2008305150","https://openalex.org/W2008674894","https://openalex.org/W2013061805","https://openalex.org/W2022243383","https://openalex.org/W2034439048","https://openalex.org/W2047120335","https://openalex.org/W2059443757","https://openalex.org/W2063454583","https://openalex.org/W2089743085","https://openalex.org/W2106687504","https://openalex.org/W2107677531","https://openalex.org/W2114314286","https://openalex.org/W2148169128","https://openalex.org/W2153131973","https://openalex.org/W2336820814","https://openalex.org/W2587190722","https://openalex.org/W2605916149","https://openalex.org/W2747207142","https://openalex.org/W2781551163","https://openalex.org/W2790272924","https://openalex.org/W2912855477","https://openalex.org/W2948613401","https://openalex.org/W2950301371","https://openalex.org/W2968760967","https://openalex.org/W2972068493","https://openalex.org/W2977350438","https://openalex.org/W2997063741","https://openalex.org/W2999339909","https://openalex.org/W2999806019","https://openalex.org/W3000521780","https://openalex.org/W3001292254","https://openalex.org/W3014179556","https://openalex.org/W3015928705","https://openalex.org/W3021305400","https://openalex.org/W3031934291","https://openalex.org/W3037230380","https://openalex.org/W3040830564","https://openalex.org/W3046701115","https://openalex.org/W3080541171","https://openalex.org/W3083064870","https://openalex.org/W3089629574","https://openalex.org/W3092286214","https://openalex.org/W3092600123","https://openalex.org/W3109994472","https://openalex.org/W3118777781","https://openalex.org/W3135530066","https://openalex.org/W3160475934","https://openalex.org/W3163361888","https://openalex.org/W3169535608","https://openalex.org/W3179473503","https://openalex.org/W3210912510","https://openalex.org/W3210917911","https://openalex.org/W3211816384","https://openalex.org/W3212267800","https://openalex.org/W4200271441","https://openalex.org/W4206497314","https://openalex.org/W4210326627","https://openalex.org/W4248953248","https://openalex.org/W4312084775","https://openalex.org/W4313593989","https://openalex.org/W6743112403","https://openalex.org/W6748597907","https://openalex.org/W6773594546"],"related_works":["https://openalex.org/W2093761689","https://openalex.org/W1520214864","https://openalex.org/W2995340247","https://openalex.org/W3011225402","https://openalex.org/W2032807833","https://openalex.org/W2748959688","https://openalex.org/W2134006231","https://openalex.org/W2948227782","https://openalex.org/W1980422890","https://openalex.org/W1619696804"],"abstract_inverted_index":{"The":[0,68,177],"development":[1,148],"of":[2,38,84,136,143,149],"the":[3,44,72,81,105,112,132,137,141,147,150,161,165,170],"county":[4,65,86,95,151],"economy":[5,87,152],"in":[6,18,153,180,193],"China":[7,154],"is":[8,13,23],"a":[9,50,91,99,185],"complicated":[10],"process":[11],"that":[12,71],"influenced":[14],"by":[15],"many":[16],"factors":[17,145],"different":[19,45,175],"ways.":[20],"This":[21],"study":[22,182],"based":[24],"on":[25,63,146],"multi-source":[26,73],"big":[27,74],"data,":[28,41],"such":[29],"as":[30],"Tencent":[31],"user":[32],"density":[33],"(TUD)":[34],"data":[35,75],"and":[36,48,97,117,169],"point":[37],"interest":[39],"(POI)":[40],"to":[42,57,79,130],"calculate":[43,80],"influencing":[46,82],"factors,":[47],"employed":[49],"multiscale":[51],"geographically":[52,118],"weighted":[53,119],"regression":[54,120],"(MGWR)":[55],"model":[56,107],"explore":[58],"their":[59],"spatial":[60,133,157],"non-stationarity":[61],"impact":[62],"China\u2019s":[64,85],"economic":[66,191],"development.":[67],"results":[69],"showed":[70,174],"can":[76,183],"be":[77],"useful":[78],"factor":[83],"because":[88,123],"they":[89],"have":[90,98],"significant":[92],"correlation":[93],"with":[94],"GDP":[96],"good":[100],"models":[101,122],"fitting":[102],"performance.":[103],"Besides,":[104],"MGWR":[106],"had":[108],"prominent":[109],"advantages":[110],"over":[111],"ordinary":[113],"least":[114],"squares":[115],"(OLS)":[116],"(GWR)":[121],"it":[124],"could":[125],"provide":[126],"covariate-specific":[127],"optimized":[128],"bandwidths":[129],"incorporate":[131],"scale":[134],"effect":[135],"independent":[138],"variables.":[139],"Moreover,":[140],"effects":[142],"various":[144],"exhibited":[155],"obvious":[156],"non-stationarity.":[158],"In":[159],"particular,":[160],"Yangtze":[162],"River":[163,167],"Delta,":[164,168],"Pearl":[166],"Beijing-Tianjin-Hebei":[171],"urban":[172],"agglomerations":[173],"characteristics.":[176],"findings":[178],"revealed":[179],"this":[181],"furnish":[184],"scientific":[186],"foundation":[187],"for":[188],"future":[189],"regional":[190],"planning":[192],"China.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2023-03-07T00:00:00"}
