{"id":"https://openalex.org/W2074948550","doi":"https://doi.org/10.1109/soli.2012.6273550","title":"Four types of typical discrete Choice Models: Which are you using?","display_name":"Four types of typical discrete Choice Models: Which are you using?","publication_year":2012,"publication_date":"2012-07-01","ids":{"openalex":"https://openalex.org/W2074948550","doi":"https://doi.org/10.1109/soli.2012.6273550","mag":"2074948550"},"language":"en","primary_location":{"id":"doi:10.1109/soli.2012.6273550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/soli.2012.6273550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of 2012 IEEE International Conference on Service Operations and Logistics, and Informatics","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100516143","display_name":"Lijun Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijun Yu","raw_affiliation_strings":["School of Civil and Transportation Engineering, South China University of Technology, Guangzhou, China","School of Civil and Transportation Engineering; South China University of Technology; Guangzhou China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil and Transportation Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Civil and Transportation Engineering; South China University of Technology; Guangzhou China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023433946","display_name":"Sun Bin","orcid":"https://orcid.org/0009-0003-8662-995X"},"institutions":[{"id":"https://openalex.org/I4210113261","display_name":"Jiangxi Transportation Research Institute","ror":"https://ror.org/026xefd52","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210113261"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Sun","raw_affiliation_strings":["Jiangxi Ganyue Expressway Company Limited, Nanchang, Jiangxi, China","Jiangxi Ganyue Expressway Co. Ltd, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangxi Ganyue Expressway Company Limited, Nanchang, Jiangxi, China","institution_ids":["https://openalex.org/I4210113261"]},{"raw_affiliation_string":"Jiangxi Ganyue Expressway Co. Ltd, Nanchang, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"298","last_page":"301"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9702000021934509,"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"}},"topics":[{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9702000021934509,"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/T10841","display_name":"Economic and Environmental Valuation","score":0.9667999744415283,"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/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.926233172416687},{"id":"https://openalex.org/keywords/discrete-choice","display_name":"Discrete choice","score":0.7852399349212646},{"id":"https://openalex.org/keywords/heteroscedasticity","display_name":"Heteroscedasticity","score":0.7606536149978638},{"id":"https://openalex.org/keywords/mixed-logit","display_name":"Mixed logit","score":0.7343586683273315},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.6839855909347534},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5733028650283813},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5243856310844421},{"id":"https://openalex.org/keywords/generalized-extreme-value-distribution","display_name":"Generalized extreme value distribution","score":0.48243722319602966},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.4492081105709076},{"id":"https://openalex.org/keywords/multinomial-probit","display_name":"Multinomial probit","score":0.4455816149711609},{"id":"https://openalex.org/keywords/nested-logit","display_name":"Nested logit","score":0.43713632225990295},{"id":"https://openalex.org/keywords/mode-choice","display_name":"Mode choice","score":0.4359491467475891},{"id":"https://openalex.org/keywords/extreme-value-theory","display_name":"Extreme value theory","score":0.41457223892211914},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38947510719299316},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38198453187942505},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3578672707080841},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11429443955421448}],"concepts":[{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.926233172416687},{"id":"https://openalex.org/C190669063","wikidata":"https://www.wikidata.org/wiki/Q5282043","display_name":"Discrete choice","level":2,"score":0.7852399349212646},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.7606536149978638},{"id":"https://openalex.org/C95057490","wikidata":"https://www.wikidata.org/wiki/Q6883984","display_name":"Mixed logit","level":3,"score":0.7343586683273315},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6839855909347534},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5733028650283813},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5243856310844421},{"id":"https://openalex.org/C169707849","wikidata":"https://www.wikidata.org/wiki/Q1617240","display_name":"Generalized extreme value distribution","level":3,"score":0.48243722319602966},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.4492081105709076},{"id":"https://openalex.org/C46704056","wikidata":"https://www.wikidata.org/wiki/Q17086346","display_name":"Multinomial probit","level":3,"score":0.4455816149711609},{"id":"https://openalex.org/C2994206189","wikidata":"https://www.wikidata.org/wiki/Q5282043","display_name":"Nested logit","level":2,"score":0.43713632225990295},{"id":"https://openalex.org/C2776017872","wikidata":"https://www.wikidata.org/wiki/Q3226683","display_name":"Mode choice","level":3,"score":0.4359491467475891},{"id":"https://openalex.org/C147581598","wikidata":"https://www.wikidata.org/wiki/Q729429","display_name":"Extreme value theory","level":2,"score":0.41457223892211914},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38947510719299316},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38198453187942505},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3578672707080841},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11429443955421448},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/soli.2012.6273550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/soli.2012.6273550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of 2012 IEEE International Conference on Service Operations and Logistics, and Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2028754797","https://openalex.org/W4235161505"],"related_works":["https://openalex.org/W1520631868","https://openalex.org/W2027354766","https://openalex.org/W2060330342","https://openalex.org/W1999801275","https://openalex.org/W3011162699","https://openalex.org/W3124547437","https://openalex.org/W2312639526","https://openalex.org/W2188096172","https://openalex.org/W2103301350","https://openalex.org/W2230331767"],"abstract_inverted_index":{"Four":[0],"types":[1],"of":[2,46],"typical":[3],"discrete":[4],"Choice":[5],"Models:":[6],"Multinomial":[7],"logit":[8,12,20,90,104,107],"(MNL)":[9],"model,":[10,21],"Nested":[11],"(NL)model,":[13],"Heteroscedastic":[14,93],"Extreme":[15,94],"Value":[16,95],"(HEV)Model":[17,96],"and":[18,25,92],"Mixed":[19,106],"have":[22],"been":[23],"proposed":[24],"implemented":[26,55],"in":[27,48,84],"empirical":[28],"investigations,":[29],"although":[30],"there":[31],"is":[32,80,113],"no":[33],"universally":[34],"acknowledged":[35],"using":[36,59],"principle.":[37],"Here":[38],"we":[39],"report":[40],"study":[41],"to":[42,117],"test":[43],"this":[44],"type":[45],"models":[47,57],"a":[49],"travel":[50],"mode":[51,85],"choice":[52,83],"case.":[53],"We":[54,64],"four":[56],"calibration":[58],"software":[60],"programmed":[61],"by":[62],"ourselves.":[63],"found":[65],"that":[66,78],"if":[67],"sample":[68],"data":[69],"satisfied":[70],"with":[71],"IIA":[72,110],"property,":[73],"our":[74],"experience":[75],"has":[76],"confirmed":[77],"MNL":[79],"the":[81,102],"first":[82],"split":[86],"forecasting.":[87],"The":[88],"nested":[89],"model":[91,108],"are":[97],"not":[98],"significantly":[99],"better":[100],"than":[101],"multinomial":[103],"model.":[105],"corrects":[109],"flaw,":[111],"but":[112],"somewhat":[114],"more":[115],"difficult":[116],"estimate.":[118]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
