{"id":"https://openalex.org/W4396648505","doi":"https://doi.org/10.1145/3653081.3653155","title":"Residential Location Selection in First-Tier Cities in China under Shared Autonomous Vehicle Conditions","display_name":"Residential Location Selection in First-Tier Cities in China under Shared Autonomous Vehicle Conditions","publication_year":2023,"publication_date":"2023-11-24","ids":{"openalex":"https://openalex.org/W4396648505","doi":"https://doi.org/10.1145/3653081.3653155"},"language":"en","primary_location":{"id":"doi:10.1145/3653081.3653155","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653081.3653155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 5th International Conference on Internet of Things, Automation 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/A5025386965","display_name":"Chen Guo","orcid":"https://orcid.org/0000-0001-7662-0546"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Guo","raw_affiliation_strings":["Transportation Institute, Inner Mongolia University, China"],"affiliations":[{"raw_affiliation_string":"Transportation Institute, Inner Mongolia University, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026209269","display_name":"Yueying Huo","orcid":"https://orcid.org/0000-0001-6440-1354"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueying Huo","raw_affiliation_strings":["Transportation Institute, Inner Mongolia University, China"],"affiliations":[{"raw_affiliation_string":"Transportation Institute, Inner Mongolia University, China","institution_ids":["https://openalex.org/I2722730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025386965"],"corresponding_institution_ids":["https://openalex.org/I2722730"],"apc_list":null,"apc_paid":null,"fwci":0.2297,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5412283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"444","last_page":"450"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10298","display_name":"Urban Transport and Accessibility","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T12546","display_name":"Smart Parking Systems Research","score":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/attractiveness","display_name":"Attractiveness","score":0.5857670307159424},{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.5741443634033203},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.5039131045341492},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.4810114800930023},{"id":"https://openalex.org/keywords/travel-behavior","display_name":"Travel behavior","score":0.44501176476478577},{"id":"https://openalex.org/keywords/urban-sprawl","display_name":"Urban sprawl","score":0.44411739706993103},{"id":"https://openalex.org/keywords/structural-equation-modeling","display_name":"Structural equation modeling","score":0.42844194173812866},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.416208416223526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.413134902715683},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3074638247489929},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.22718891501426697},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1632954180240631},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12435558438301086}],"concepts":[{"id":"https://openalex.org/C31173074","wikidata":"https://www.wikidata.org/wiki/Q2632514","display_name":"Attractiveness","level":2,"score":0.5857670307159424},{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.5741443634033203},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.5039131045341492},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.4810114800930023},{"id":"https://openalex.org/C144072006","wikidata":"https://www.wikidata.org/wiki/Q4462116","display_name":"Travel behavior","level":2,"score":0.44501176476478577},{"id":"https://openalex.org/C487182","wikidata":"https://www.wikidata.org/wiki/Q192042","display_name":"Urban sprawl","level":3,"score":0.44411739706993103},{"id":"https://openalex.org/C71104824","wikidata":"https://www.wikidata.org/wiki/Q1476639","display_name":"Structural equation modeling","level":2,"score":0.42844194173812866},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.416208416223526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.413134902715683},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3074638247489929},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.22718891501426697},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1632954180240631},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12435558438301086},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","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/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3653081.3653155","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653081.3653155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 5th International Conference on Internet of Things, Automation and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1964766293","https://openalex.org/W2023888699","https://openalex.org/W2160865385","https://openalex.org/W2210937236","https://openalex.org/W2256983726","https://openalex.org/W2287151480","https://openalex.org/W2467953227","https://openalex.org/W2515943586","https://openalex.org/W2562441746","https://openalex.org/W2582268785","https://openalex.org/W2591962503","https://openalex.org/W2616803378","https://openalex.org/W2767127672","https://openalex.org/W2806301036","https://openalex.org/W2809845116","https://openalex.org/W2901329227","https://openalex.org/W3145939510","https://openalex.org/W4206016539","https://openalex.org/W4206535450"],"related_works":["https://openalex.org/W2056014006","https://openalex.org/W656121716","https://openalex.org/W2095278931","https://openalex.org/W3153406193","https://openalex.org/W2359152176","https://openalex.org/W2349314038","https://openalex.org/W1994897687","https://openalex.org/W2815745848","https://openalex.org/W2465866556","https://openalex.org/W2123043280"],"abstract_inverted_index":{"Users":[0],"traveling":[1],"by":[2],"Shared":[3],"Autonomous":[4],"Vehicle":[5],"(SAV)":[6],"can":[7],"make":[8],"the":[9,38,41,55,73,79,133,167,172,191],"most":[10],"of":[11,93,149,171,193],"their":[12],"commute":[13],"and":[14,18,58,69,108,116,144,146],"reduce":[15],"parking":[16,130],"time":[17],"costs,":[19],"while":[20],"potential":[21],"changes":[22,39],"in":[23,40,84,178,183],"residential":[24,42,66,74,94],"location":[25,43,75,95],"choices":[26],"will":[27,151,180],"be":[28,198],"elaborated":[29],"under":[30,44,185],"SAV":[31,45,105,150,186],"travel":[32,46,103,187],"conditions.":[33],"In":[34],"order":[35],"to":[36,62,153,155,164,166,197],"explore":[37],"conditions,":[47,188],"this":[48,86],"paper":[49,87],"proposes":[50],"a":[51,89],"choice":[52],"model":[53,92],"combining":[54],"latent":[56,110],"variables":[57,111],"performs":[59],"elasticity":[60],"analysis":[61],"better":[63],"understand":[64],"how":[65],"locations":[67],"change":[68],"what":[70],"factors":[71],"influence":[72],"choice.":[76],"Based":[77],"on":[78],"questionnaire":[80],"survey":[81],"data":[82],"conducted":[83],"China,":[85],"constructs":[88],"multinomial":[90],"logit":[91],"selection":[96],"with":[97,123],"personal":[98],"attributes,":[99,104],"commuting":[100],"information,":[101],"shared":[102,137,142],"use":[106],"willingness,":[107],"attitude":[109],"(sharing":[112],"mode,":[113],"new":[114],"technology,":[115],"autonomous":[117],"vehicle)":[118],"as":[119],"explanatory":[120],"variables.":[121],"Groups":[122],"high":[124,129],"education,":[125],"long":[126],"driving":[127],"age,":[128],"costs":[131],"at":[132],"workplace,":[134],"having":[135],"used":[136],"cars,":[138],"positive":[139],"attitudes":[140],"towards":[141],"models":[143],"AV,":[145],"frequent":[147],"usage":[148],"tend":[152,163],"relocate":[154,165],"downtown;":[156],"groups":[157],"that":[158,175,190],"have":[159],"suffered":[160],"traffic":[161],"accidents":[162],"suburb.":[168],"The":[169],"results":[170],"study":[173],"suggest":[174],"first-tier":[176],"cities":[177],"China":[179],"not":[181],"grow":[182],"sprawl":[184],"but":[189],"attractiveness":[192],"suburban":[194],"areas":[195],"needs":[196],"increased.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}