{"id":"https://openalex.org/W3211101151","doi":"https://doi.org/10.1109/tcss.2021.3116043","title":"Evaluation and Spatial\u2013Temporal Difference Analysis of Urban Water Resource Utilization Efficiency Based on Two-Stage DEA Model","display_name":"Evaluation and Spatial\u2013Temporal Difference Analysis of Urban Water Resource Utilization Efficiency Based on Two-Stage DEA Model","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W3211101151","doi":"https://doi.org/10.1109/tcss.2021.3116043","mag":"3211101151"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2021.3116043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2021.3116043","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039340206","display_name":"Qiwei Xie","orcid":"https://orcid.org/0000-0002-4209-7192"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiwei Xie","raw_affiliation_strings":["Research Base of Beijing Modern Manufacturing Development, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Base of Beijing Modern Manufacturing Development, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023970001","display_name":"Hewen Ma","orcid":"https://orcid.org/0000-0001-5249-3722"},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hewen Ma","raw_affiliation_strings":["Faculty of Mathematics and Statistics, Hubei University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Statistics, Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044689658","display_name":"Xiaolong Zheng","orcid":"https://orcid.org/0000-0003-0405-5458"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Zheng","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112719601","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0002-0008-0659"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113600509","display_name":"Fei\u2010Yue Wang","orcid":"https://orcid.org/0000-0001-9185-3989"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei-Yue Wang","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5039340206"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":2.6142,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.89862774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"9","issue":"5","first_page":"1282","last_page":"1296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10357","display_name":"Efficiency Analysis Using DEA","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10357","display_name":"Efficiency Analysis Using DEA","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10969","display_name":"Water resources management and optimization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10841","display_name":"Economic and Environmental Valuation","score":0.9952999949455261,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/data-envelopment-analysis","display_name":"Data envelopment analysis","score":0.6840226650238037},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.6051744222640991},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5800129175186157},{"id":"https://openalex.org/keywords/per-capita","display_name":"Per capita","score":0.5598512887954712},{"id":"https://openalex.org/keywords/gross-domestic-product","display_name":"Gross domestic product","score":0.4708371162414551},{"id":"https://openalex.org/keywords/environmental-economics","display_name":"Environmental economics","score":0.4403526782989502},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.430152028799057},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.404554545879364},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35558104515075684},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.34304553270339966},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.32568246126174927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28791365027427673},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.23792144656181335},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17249137163162231}],"concepts":[{"id":"https://openalex.org/C22088475","wikidata":"https://www.wikidata.org/wiki/Q647974","display_name":"Data envelopment analysis","level":2,"score":0.6840226650238037},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.6051744222640991},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5800129175186157},{"id":"https://openalex.org/C127598652","wikidata":"https://www.wikidata.org/wiki/Q558635","display_name":"Per capita","level":3,"score":0.5598512887954712},{"id":"https://openalex.org/C114350782","wikidata":"https://www.wikidata.org/wiki/Q12638","display_name":"Gross domestic product","level":2,"score":0.4708371162414551},{"id":"https://openalex.org/C134560507","wikidata":"https://www.wikidata.org/wiki/Q753291","display_name":"Environmental economics","level":1,"score":0.4403526782989502},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.430152028799057},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.404554545879364},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35558104515075684},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34304553270339966},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.32568246126174927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28791365027427673},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.23792144656181335},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17249137163162231},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcss.2021.3116043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2021.3116043","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation"}],"awards":[{"id":"https://openalex.org/G5705954559","display_name":null,"funder_award_id":"61673381","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5823784751","display_name":null,"funder_award_id":"2020AAA0108401","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"},{"id":"https://openalex.org/G6285185390","display_name":null,"funder_award_id":"2019QY(Y)0101","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"},{"id":"https://openalex.org/G8098779707","display_name":null,"funder_award_id":"9202002","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W1503711532","https://openalex.org/W1921611798","https://openalex.org/W1963617081","https://openalex.org/W1984127772","https://openalex.org/W1996733354","https://openalex.org/W2013310217","https://openalex.org/W2019257362","https://openalex.org/W2026945249","https://openalex.org/W2028226037","https://openalex.org/W2034687505","https://openalex.org/W2036036379","https://openalex.org/W2036732157","https://openalex.org/W2036895319","https://openalex.org/W2037016507","https://openalex.org/W2063608004","https://openalex.org/W2075786705","https://openalex.org/W2076452041","https://openalex.org/W2085290642","https://openalex.org/W2098212684","https://openalex.org/W2098940796","https://openalex.org/W2168175751","https://openalex.org/W2340785848","https://openalex.org/W2360105398","https://openalex.org/W2361933646","https://openalex.org/W2363059139","https://openalex.org/W2387296881","https://openalex.org/W2392407298","https://openalex.org/W2432002198","https://openalex.org/W2506753585","https://openalex.org/W2517906457","https://openalex.org/W2526781696","https://openalex.org/W2529185469","https://openalex.org/W2557843257","https://openalex.org/W2577694180","https://openalex.org/W2581029168","https://openalex.org/W2756857382","https://openalex.org/W2760091636","https://openalex.org/W2763725365","https://openalex.org/W2790586060","https://openalex.org/W2802791342","https://openalex.org/W2804344998","https://openalex.org/W2887825474","https://openalex.org/W2889232559","https://openalex.org/W2905038236","https://openalex.org/W2905290611","https://openalex.org/W2913183653","https://openalex.org/W2919255458","https://openalex.org/W2945445006","https://openalex.org/W2949441861","https://openalex.org/W2952473083","https://openalex.org/W2969868470","https://openalex.org/W2971042163","https://openalex.org/W2971377423","https://openalex.org/W2973498489","https://openalex.org/W2987531558","https://openalex.org/W2991400451","https://openalex.org/W3023114683","https://openalex.org/W3036840743","https://openalex.org/W3039221356","https://openalex.org/W3041790866","https://openalex.org/W3044912974","https://openalex.org/W3091952872","https://openalex.org/W3092374328","https://openalex.org/W3099720705","https://openalex.org/W3108881817","https://openalex.org/W3119335205","https://openalex.org/W3150207032","https://openalex.org/W3194417793","https://openalex.org/W6634565539","https://openalex.org/W7034883824","https://openalex.org/W7038607902"],"related_works":["https://openalex.org/W4226161467","https://openalex.org/W2886718573","https://openalex.org/W4200541242","https://openalex.org/W2036608594","https://openalex.org/W4221127391","https://openalex.org/W2044331835","https://openalex.org/W4388894273","https://openalex.org/W2782780157","https://openalex.org/W2044696968","https://openalex.org/W2088915718"],"abstract_inverted_index":{"In":[0,68],"the":[1,21,43,47,55,59,69,80,90,105,159,172,189,194,203,209,221],"present":[2],"study,":[3],"a":[4,71,215],"two-stage":[5],"data":[6],"envelopment":[7],"analysis":[8,85],"(DEA)":[9],"model":[10,38,197],"and":[11,19,28,58,107,117,153,165,185],"spatial":[12,83,195],"econometric":[13,84],"method":[14],"were":[15,66],"employed":[16],"to":[17,78,88,104],"evaluate":[18],"analyze":[20],"utilization":[22,97,146,173,212],"efficiency":[23,73,147,174,213],"of":[24,33,93,175,206,214],"urban":[25,94],"water":[26,95,123,144,176,210],"resources":[27,177],"spatial\u2013temporal":[29,91],"differences":[30,92],"in":[31,46,115,224],"cities":[32,141],"China.":[34],"The":[35],"traditional":[36],"DEA":[37],"was":[39,76,86],"enhanced":[40,219],"by":[41],"adopting":[42],"Shannon":[44],"entropy":[45],"first":[48],"stage.":[49],"After":[50],"selecting":[51],"variables":[52,65],"based":[53],"on":[54,112,182],"previous":[56],"step":[57],"Bayes":[60],"information":[61],"criterion":[62],"(BIC),":[63],"redundant":[64],"removed.":[67],"meanwhile,":[70],"comprehensive":[72],"score":[74],"(CES)":[75],"generated":[77],"rank":[79],"efficiency.":[81,98],"Finally,":[82],"applied":[87],"explore":[89],"resource":[96,145,211],"Results":[99],"demonstrate":[100],"that:":[101],"1)":[102],"according":[103],"calculations":[106],"analysis,":[108],"communities":[109],"should":[110],"concentrate":[111],"increasing":[113],"investment":[114],"equipment":[116],"technology":[118],"that":[119,171],"can":[120],"help":[121],"enhance":[122],"consumption":[124],"efficiency,":[125],"while":[126],"overlooking":[127],"some":[128],"minor":[129],"aspects,":[130],"such":[131],"as":[132],"per":[133],"capita":[134],"gross":[135],"domestic":[136],"product":[137],"(PCGDP);":[138],"2)":[139],"most":[140],"have":[142,155,167],"poor":[143],"(low":[148],"CES).":[149],"However,":[150],"both":[151],"input":[152],"output":[154],"much":[156],"room":[157],"for":[158],"improvement;":[160],"3)":[161],"Lhasa,":[162],"Beijing,":[163],"Haikou,":[164],"Shanghai":[166],"high":[168],"CES,":[169],"indicating":[170],"is":[178,200],"not":[179],"entirely":[180],"dependent":[181],"economic":[183,222],"development;":[184],"4)":[186],"through":[187],"performing":[188],"Lagrange":[190],"multiplier":[191],"(LM)":[192],"test,":[193],"error":[196],"(SEM)":[198],"test":[199],"passed":[201],"at":[202],"significant":[204],"level":[205],"5%.":[207],"Moreover,":[208],"city":[216],"may":[217],"be":[218],"with":[220],"development":[223],"neighboring":[225],"cities.":[226]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}