{"id":"https://openalex.org/W4416612241","doi":"https://doi.org/10.1016/j.kscej.2025.100481","title":"Modeling intercity travel mode choice: Uncovering key factor interactions with machine learning","display_name":"Modeling intercity travel mode choice: Uncovering key factor interactions with machine learning","publication_year":2025,"publication_date":"2025-11-25","ids":{"openalex":"https://openalex.org/W4416612241","doi":"https://doi.org/10.1016/j.kscej.2025.100481"},"language":"en","primary_location":{"id":"doi:10.1016/j.kscej.2025.100481","doi":"https://doi.org/10.1016/j.kscej.2025.100481","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.kscej.2025.100481","pdf_url":null,"source":{"id":"https://openalex.org/S109054653","display_name":"KSCE Journal of Civil Engineering","issn_l":"1226-7988","issn":["1226-7988","1976-3808"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","jufo-1","kci-registered","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"KSCE Journal of Civil Engineering","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.kscej.2025.100481","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030597074","display_name":"S. Loganayagan","orcid":"https://orcid.org/0000-0002-3496-417X","observed_orcids":["https://orcid.org/0000-0002-3496-417X"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Loganayagan Shanmugam","raw_affiliation_strings":["Department of Civil Engineering, Kangeyam Institute of Technology, Kangeyam, Tiruppur District, Tamil Nadu"],"raw_orcid":"https://orcid.org/0000-0002-3496-417X","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Kangeyam Institute of Technology, Kangeyam, Tiruppur District, Tamil Nadu","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005812574","display_name":"Murugesan Ramasamy","orcid":"https://orcid.org/0000-0003-3490-0827","observed_orcids":["https://orcid.org/0000-0003-3490-0827"]},"institutions":[{"id":"https://openalex.org/I4405263326","display_name":"Government College of Engineering, Erode","ror":"https://ror.org/05a18pg38","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405263326"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Murugesan Ramasamy","raw_affiliation_strings":["Department of Civil Engineering, Government College of Engineering, Erode \u2013 638 316"],"raw_orcid":"https://orcid.org/0000-0003-3490-0827","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Government College of Engineering, Erode \u2013 638 316","institution_ids":["https://openalex.org/I4405263326"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5030597074"],"corresponding_institution_ids":[],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":{"value":1800,"currency":"USD","value_usd":1800},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":"5","first_page":"100481","last_page":"100481"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.975600004196167,"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":0.975600004196167,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.007199999876320362,"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.00430000014603138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/travel-time","display_name":"travel time","score":0.6690000295639038},{"id":"https://openalex.org/keywords/travel-cost","display_name":"travel cost","score":0.9990000128746033},{"id":"https://openalex.org/keywords/convenience","display_name":"convenience","score":0.8489999771118164},{"id":"https://openalex.org/keywords/travel-distance","display_name":"travel distance","score":0.4860000014305115},{"id":"https://openalex.org/keywords/sustainable-transport","display_name":"sustainable transport","score":0.6060000061988831}],"concepts":[{"id":"https://openalex.org/C2776017872","wikidata":"https://www.wikidata.org/wiki/Q3226683","display_name":"Mode choice","level":3,"score":0.6879000067710876},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6797999739646912},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.5949000120162964},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5733000040054321},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5615000128746033},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5364999771118164},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5167999863624573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4878999888896942},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46950000524520874},{"id":"https://openalex.org/C144072006","wikidata":"https://www.wikidata.org/wiki/Q4462116","display_name":"Travel behavior","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4223000109195709},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.3562000095844269},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C2779110102","wikidata":"https://www.wikidata.org/wiki/Q1323737","display_name":"Revealed preference","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C2780365114","wikidata":"https://www.wikidata.org/wiki/Q169478","display_name":"MATLAB","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3084000051021576},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C2985733770","wikidata":"https://www.wikidata.org/wiki/Q1233007","display_name":"Travel time","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.26570001244544983},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2621999979019165},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.kscej.2025.100481","doi":"https://doi.org/10.1016/j.kscej.2025.100481","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.kscej.2025.100481","pdf_url":null,"source":{"id":"https://openalex.org/S109054653","display_name":"KSCE Journal of Civil Engineering","issn_l":"1226-7988","issn":["1226-7988","1976-3808"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","jufo-1","kci-registered","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"KSCE Journal of Civil Engineering","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.kscej.2025.100481","doi":"https://doi.org/10.1016/j.kscej.2025.100481","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.kscej.2025.100481","pdf_url":null,"source":{"id":"https://openalex.org/S109054653","display_name":"KSCE Journal of Civil Engineering","issn_l":"1226-7988","issn":["1226-7988","1976-3808"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","jufo-1","kci-registered","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"KSCE Journal of Civil Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.8970999717712402,"display_name":"Industry, innovation and infrastructure"},{"id":"https://metadata.un.org/sdg/11","score":0.8787999749183655,"display_name":"Sustainable cities and communities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W4323305033","https://openalex.org/W4388687576","https://openalex.org/W4389431661","https://openalex.org/W4390292152","https://openalex.org/W4390848603","https://openalex.org/W4392132809","https://openalex.org/W4392132815","https://openalex.org/W4392432791","https://openalex.org/W4393388062","https://openalex.org/W4394811823","https://openalex.org/W4394896929","https://openalex.org/W4396858892","https://openalex.org/W4396902065","https://openalex.org/W4399359665","https://openalex.org/W4399978670","https://openalex.org/W4400182295","https://openalex.org/W4400279470","https://openalex.org/W4401045442","https://openalex.org/W4401352679","https://openalex.org/W4401912295","https://openalex.org/W4402188440"],"related_works":["https://openalex.org/W4412959495","https://openalex.org/W4411865844","https://openalex.org/W3200358703","https://openalex.org/W3196725569","https://openalex.org/W4386765164","https://openalex.org/W4312293827","https://openalex.org/W4415465994","https://openalex.org/W7151822481","https://openalex.org/W2304613467","https://openalex.org/W4393388062"],"abstract_inverted_index":{"Intercity":[0,96],"travel":[1,36,51,142,152,181,185],"mode":[2,16,52,143,182],"choice":[3,29,53],"refers":[4],"to":[5,131,176],"the":[6,101,116,127,133,136,140,151,173,178,217],"decision-making":[7],"process":[8],"individuals":[9],"or":[10],"groups":[11],"undergo":[12],"when":[13],"selecting":[14],"a":[15,89],"of":[17,92,103,126,135,191],"transportation,":[18],"such":[19,60,220],"as":[20,61],"car,":[21],"train,":[22],"bus,":[23],"for":[24,80,106],"journeys":[25],"between":[26],"cities.":[27],"This":[28,86],"is":[30,78,115,130,156,214],"influenced":[31],"by":[32],"various":[33],"factors,":[34],"including":[35],"cost,":[37,62,187],"time,":[38,63,186],"convenience,":[39,65],"comfort,":[40],"environmental":[41],"impact,":[42],"and":[43,64,68,74,83,110,145,170,188,205,230],"personal":[44],"preferences.":[45],"The":[46,112,123,162,210],"key":[47],"challenge":[48],"in":[49,55],"intercity":[50,141],"lies":[54],"balancing":[56],"diverse":[57],"traveler":[58],"preferences,":[59],"with":[66,216],"sustainable":[67],"efficient":[69],"transportation":[70],"solutions.":[71],"Accurately":[72],"modeling":[73],"predicting":[75],"these":[76],"choices":[77],"essential":[79],"optimizing":[81],"infrastructure":[82],"policy":[84],"decisions.":[85],"paper":[87],"presents":[88],"Nonlinear":[90],"Effects":[91],"Key":[93],"Factors":[94],"on":[95,139,184],"Travel":[97,159,202,206],"Mode":[98],"Choice":[99],"through":[100],"Application":[102],"machine":[104,165],"learning":[105,166],"Enhanced":[107],"Predictive":[108],"Modeling":[109],"Insights.":[111],"proposed":[113,128,163,192,211],"technique":[114],"Viscoelastic":[117],"Constitutive":[118],"Artificial":[119],"Neural":[120],"Networks":[121],"(VCANN).":[122],"main":[124],"objective":[125],"method":[129,193,213],"explore":[132],"effects":[134,149],"influencing":[137],"factors":[138],"competition":[144],"evaluate":[146],"their":[147],"dynamic":[148],"across":[150],"distance.":[153],"Initially":[154],"data":[155],"collected":[157],"from":[158],"Preference":[160],"Dataset.":[161],"VCANN":[164,212],"model":[167],"was":[168],"developed":[169],"implemented":[171],"using":[172],"MATLAB":[174],"platform":[175],"predict":[177],"most":[179],"suitable":[180],"based":[183],"convenience.":[189],"Performance":[190],"examined":[194],"utilizing":[195],"performance":[196],"metrics":[197],"likes":[198],"Accuracy,":[199],"Precision,":[200],"Recall,":[201],"Time,":[203],"Convenience":[204],"cost":[207],"are":[208],"analysed.":[209],"compared":[215],"existing":[218],"methods":[219],"as,":[221],"Extreme":[222],"Gradient":[223],"Boosting":[224],"(XGBoost),":[225],"Long":[226],"Short-Term":[227],"Memory":[228],"(LSTM),":[229],"Geographically":[231],"weighted":[232],"random":[233],"forest":[234],"regression":[235],"(GWRFR).":[236]},"counts_by_year":[],"updated_date":"2026-09-23T05:00:35.095934","created_date":"2025-11-25T00:00:00"}
