{"id":"https://openalex.org/W2588898847","doi":"https://doi.org/10.1109/liss.2016.7854434","title":"The market segmentation on passenger transportation of High-speed Railway with logistic regression model","display_name":"The market segmentation on passenger transportation of High-speed Railway with logistic regression model","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2588898847","doi":"https://doi.org/10.1109/liss.2016.7854434","mag":"2588898847"},"language":"en","primary_location":{"id":"doi:10.1109/liss.2016.7854434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/liss.2016.7854434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Logistics, Informatics and Service Sciences (LISS)","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/A5056979630","display_name":"Yanjin Li","orcid":"https://orcid.org/0000-0002-6750-6693"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanjin Li","raw_affiliation_strings":["School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan, CN"],"affiliations":[{"raw_affiliation_string":"School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan, CN","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113751276","display_name":"Hai Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Zhu","raw_affiliation_strings":["School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, P.R China"],"affiliations":[{"raw_affiliation_string":"School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, P.R China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100620733","display_name":"Yonghong Liu","orcid":"https://orcid.org/0000-0003-3423-7375"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghong Liu","raw_affiliation_strings":["School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, P.R China"],"affiliations":[{"raw_affiliation_string":"School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, P.R China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056979630"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.24669783,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9689000248908997,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9689000248908997,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9635999798774719,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9567000269889832,"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/market-segmentation","display_name":"Market segmentation","score":0.7351312637329102},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.6754899621009827},{"id":"https://openalex.org/keywords/revenue","display_name":"Revenue","score":0.6213943958282471},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5265949964523315},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5136024951934814},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.4982883930206299},{"id":"https://openalex.org/keywords/research-object","display_name":"Research Object","score":0.4464454650878906},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.43439945578575134},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4188275933265686},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.381418913602829},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.34037452936172485},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.2982306480407715},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23607531189918518},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2342013418674469},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15933528542518616},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.12133431434631348},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10815092921257019},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09066468477249146},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.07090520858764648}],"concepts":[{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.7351312637329102},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.6754899621009827},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.6213943958282471},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5265949964523315},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5136024951934814},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.4982883930206299},{"id":"https://openalex.org/C2778631480","wikidata":"https://www.wikidata.org/wiki/Q17143022","display_name":"Research Object","level":2,"score":0.4464454650878906},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.43439945578575134},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4188275933265686},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.381418913602829},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34037452936172485},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.2982306480407715},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23607531189918518},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2342013418674469},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15933528542518616},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.12133431434631348},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10815092921257019},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09066468477249146},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.07090520858764648},{"id":"https://openalex.org/C178550888","wikidata":"https://www.wikidata.org/wiki/Q2043282","display_name":"Business administration","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/liss.2016.7854434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/liss.2016.7854434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Logistics, Informatics and Service Sciences (LISS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4300000071525574,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2065010396","https://openalex.org/W2166698530","https://openalex.org/W2319647657","https://openalex.org/W2382232514","https://openalex.org/W2797746357","https://openalex.org/W4237167522"],"related_works":["https://openalex.org/W2592395359","https://openalex.org/W2535231171","https://openalex.org/W2045342254","https://openalex.org/W1501331687","https://openalex.org/W2326647871","https://openalex.org/W4205247302","https://openalex.org/W2468652214","https://openalex.org/W2501551404","https://openalex.org/W1504527458","https://openalex.org/W2130144716"],"abstract_inverted_index":{"In":[0],"this":[1,16],"article,":[2],"traveling":[3],"passengers":[4],"along":[5,30],"Chongqing-Lichuan":[6,32,95],"High-speed":[7,33,96],"Railway":[8,34,97],"line":[9,35],"are":[10,36,60,79],"regarded":[11],"as":[12],"research":[13],"object":[14],"in":[15,82],"paper.":[17],"More":[18],"than":[19],"5000":[20],"random":[21],"sampling":[22,55],"data":[23],"of":[24,94,106],"passenger":[25,107],"travel":[26,65],"and":[27,42,66,77],"their":[28],"characteristic":[29,72],"the":[31,44,92],"obtained":[37],"through":[38,43],"SP/RP":[39],"questionnaire":[40],"design,":[41],"market":[45,58,85],"segmentation":[46],"by":[47],"using":[48],"Logistic":[49],"regression":[50],"to":[51,98],"deal":[52],"with":[53],"these":[54],"data,":[56],"three":[57,70],"segmentations":[59],"obtained:":[61],"migrant":[62],"workers,":[63],"non-economic":[64],"business":[67],"travel.":[68],"Then":[69],"traveler":[71],"indexes,":[73],"age,":[74],"monthly":[75],"income":[76],"profession":[78],"statistically":[80],"analyzed":[81],"each":[83],"subordinate":[84],"segmentation,":[86],"which":[87],"could":[88],"be":[89],"helpful":[90],"for":[91],"operators":[93],"design":[99],"differentiated":[100],"products,":[101],"thus":[102],"realizing":[103],"revenue":[104],"maximization":[105],"high-speed":[108],"railway":[109],"operation.":[110]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
