{"id":"https://openalex.org/W3120838428","doi":"https://doi.org/10.1145/3436286.3436398","title":"The evaluation of tourism industry efficiency in Hubei province based on three-stage DEA","display_name":"The evaluation of tourism industry efficiency in Hubei province based on three-stage DEA","publication_year":2020,"publication_date":"2020-04-28","ids":{"openalex":"https://openalex.org/W3120838428","doi":"https://doi.org/10.1145/3436286.3436398","mag":"3120838428"},"language":"en","primary_location":{"id":"doi:10.1145/3436286.3436398","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3436286.3436398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 2nd International Conference on Big Data and Artificial Intelligence","raw_type":"proceedings-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/A5103099923","display_name":"Xiao Hu","orcid":"https://orcid.org/0000-0002-2359-779X"},"institutions":[{"id":"https://openalex.org/I4210111616","display_name":"Wuhan Business University","ror":"https://ror.org/0282ggx30","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210111616"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao Hu","raw_affiliation_strings":["School of Tourism Management, Wuhan Business University, Wuhan Hubei China"],"affiliations":[{"raw_affiliation_string":"School of Tourism Management, Wuhan Business University, Wuhan Hubei China","institution_ids":["https://openalex.org/I4210111616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5103099923"],"corresponding_institution_ids":["https://openalex.org/I4210111616"],"apc_list":null,"apc_paid":null,"fwci":0.1795,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5976892,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"36","issue":null,"first_page":"239","last_page":"244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10357","display_name":"Efficiency Analysis Using DEA","score":0.9994999766349792,"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":0.9994999766349792,"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/T12306","display_name":"Urban and Freight Transport Logistics","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11223","display_name":"Maritime Ports and Logistics","score":0.965499997138977,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/data-envelopment-analysis","display_name":"Data envelopment analysis","score":0.8429551124572754},{"id":"https://openalex.org/keywords/tourism","display_name":"Tourism","score":0.7679703235626221},{"id":"https://openalex.org/keywords/stochastic-frontier-analysis","display_name":"Stochastic frontier analysis","score":0.5793420672416687},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5720376968383789},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.52532958984375},{"id":"https://openalex.org/keywords/environmental-economics","display_name":"Environmental economics","score":0.4687177240848541},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.24870610237121582},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.20660942792892456},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.13239938020706177},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09029984474182129},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08214220404624939},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.06591594219207764}],"concepts":[{"id":"https://openalex.org/C22088475","wikidata":"https://www.wikidata.org/wiki/Q647974","display_name":"Data envelopment analysis","level":2,"score":0.8429551124572754},{"id":"https://openalex.org/C18918823","wikidata":"https://www.wikidata.org/wiki/Q49389","display_name":"Tourism","level":2,"score":0.7679703235626221},{"id":"https://openalex.org/C2779341709","wikidata":"https://www.wikidata.org/wiki/Q7617818","display_name":"Stochastic frontier analysis","level":3,"score":0.5793420672416687},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5720376968383789},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.52532958984375},{"id":"https://openalex.org/C134560507","wikidata":"https://www.wikidata.org/wiki/Q753291","display_name":"Environmental economics","level":1,"score":0.4687177240848541},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.24870610237121582},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.20660942792892456},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.13239938020706177},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09029984474182129},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08214220404624939},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.06591594219207764},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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":1,"locations":[{"id":"doi:10.1145/3436286.3436398","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3436286.3436398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 2nd International Conference on Big Data and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.550000011920929,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1508671192","https://openalex.org/W1532189092","https://openalex.org/W1973594753","https://openalex.org/W1990697551","https://openalex.org/W1998113231","https://openalex.org/W2011531257","https://openalex.org/W2016035079","https://openalex.org/W2058589741","https://openalex.org/W2081747720","https://openalex.org/W2129763896","https://openalex.org/W2143070272","https://openalex.org/W2160622753","https://openalex.org/W2369575274","https://openalex.org/W2521640099","https://openalex.org/W2971741960","https://openalex.org/W2981206935","https://openalex.org/W3019761378","https://openalex.org/W3152552198","https://openalex.org/W4246430168"],"related_works":["https://openalex.org/W4381491368","https://openalex.org/W2017280802","https://openalex.org/W2121206197","https://openalex.org/W2617116687","https://openalex.org/W2182611879","https://openalex.org/W3122758318","https://openalex.org/W263736732","https://openalex.org/W4237376114","https://openalex.org/W2044273251","https://openalex.org/W3147306327"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"the":[3,16,35,43,76,96,119,124,143,170,198,210],"three-stage":[4],"DEA":[5],"(Data":[6],"Envelopment":[7],"Analysis)":[8],"model":[9],"is":[10,84,95,138],"used":[11],"to":[12,29,106,114,128,142,156],"estimate":[13],"and":[14,53,64,73,86,140,164],"evaluate":[15],"tourism":[17,44,83,158,179,203],"efficiency":[18,46,61,66,79,94,134,144,173,199,212],"of":[19,47,80,126,135,167,181,196,200],"12":[20,182],"major":[21],"prefecture-level":[22,183],"cities":[23,110,184],"in":[24,108,123,185],"Hubei":[25,48,81,136,186],"province":[26,137,187],"from":[27,112],"2008":[28],"2018.":[30],"The":[31,50,104,130,178,194],"results":[32],"show":[33],"that:":[34],"environment":[36,54,71,120],"variables":[37],"had":[38],"a":[39,89,175],"significant":[40],"impact":[41],"on":[42,209],"development":[45,91],"province.":[49],"stochastic":[51,74],"noise":[52,75],"effects":[55,72],"make":[56],"most":[57],"cities'":[58,148,202],"pure":[59,132,149,171],"technical":[60,78,102,133],"being":[62,67],"underestimated":[63],"scale":[65,107],"overestimated.":[68],"After":[69],"eliminating":[70],"integrated":[77,101],"province's":[82],"low":[85,100],"still":[87],"has":[88],"big":[90],"space.":[92],"Scale":[93],"main":[97],"reason":[98],"causing":[99],"efficiency.":[103],"returns":[105,127],"some":[109,147],"change":[111],"decreasing":[113],"increasing,":[115],"which":[116],"shows":[117],"that":[118],"factors":[121],"result":[122],"declining":[125],"scale.":[129],"overall":[131],"high":[139,176],"close":[141],"frontier,":[145],"but":[146],"technological":[150,172],"efficiencies":[151],"aren't":[152],"stable.":[153],"They":[154],"need":[155],"strengthen":[157],"products":[159],"innovation,":[160],"scientific":[161],"management":[162],"level":[163],"professional":[165],"quality":[166],"practitioners,":[168],"keeping":[169],"at":[174],"level.":[177],"industry":[180,204],"can":[188],"be":[189],"divided":[190],"into":[191],"three":[192],"types.":[193],"strategies":[195],"improving":[197],"different":[201],"are":[205],"put":[206],"forward":[207],"based":[208],"regional":[211],"structure":[213],"characteristics.":[214]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
