{"id":"https://openalex.org/W4285385574","doi":"https://doi.org/10.1108/k-06-2021-0473","title":"Graph-theoretic approach to detecting real-time intents within purchase conversion funnel using clickstream data","display_name":"Graph-theoretic approach to detecting real-time intents within purchase conversion funnel using clickstream data","publication_year":2022,"publication_date":"2022-07-14","ids":{"openalex":"https://openalex.org/W4285385574","doi":"https://doi.org/10.1108/k-06-2021-0473"},"language":"en","primary_location":{"id":"doi:10.1108/k-06-2021-0473","is_oa":false,"landing_page_url":"https://doi.org/10.1108/k-06-2021-0473","pdf_url":null,"source":{"id":"https://openalex.org/S168682784","display_name":"Kybernetes","issn_l":"0368-492X","issn":["0368-492X","1758-7883"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kybernetes","raw_type":"journal-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/A5079906801","display_name":"Hongming Gao","orcid":"https://orcid.org/0000-0001-6273-6695"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongming Gao","raw_affiliation_strings":["School of Management, Guangzhou University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6273-6695","affiliations":[{"raw_affiliation_string":"School of Management, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015102884","display_name":"Hongwei Liu","orcid":"https://orcid.org/0000-0003-1133-4930"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Liu","raw_affiliation_strings":["School of Management, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1133-4930","affiliations":[{"raw_affiliation_string":"School of Management, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017665745","display_name":"Weizhen Lin","orcid":"https://orcid.org/0000-0003-1646-4152"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weizhen Lin","raw_affiliation_strings":["School of Management, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1646-4152","affiliations":[{"raw_affiliation_string":"School of Management, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067260549","display_name":"Chunfeng Chen","orcid":"https://orcid.org/0000-0001-6309-4196"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunfeng Chen","raw_affiliation_strings":["School of Management, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6309-4196","affiliations":[{"raw_affiliation_string":"School of Management, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8076,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.7630662,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"52","issue":"11","first_page":"5139","last_page":"5163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10609","display_name":"Digital Marketing and Social Media","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T11437","display_name":"Digital Platforms and Economics","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/clickstream","display_name":"Clickstream","score":0.9131940603256226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.778714656829834},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5683109760284424},{"id":"https://openalex.org/keywords/funnel","display_name":"Funnel","score":0.5413060784339905},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.5023138523101807},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45346227288246155},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4330289661884308},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37272658944129944},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29248321056365967},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.19603395462036133},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.1455872356891632}],"concepts":[{"id":"https://openalex.org/C138744977","wikidata":"https://www.wikidata.org/wiki/Q5132438","display_name":"Clickstream","level":5,"score":0.9131940603256226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.778714656829834},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5683109760284424},{"id":"https://openalex.org/C17435862","wikidata":"https://www.wikidata.org/wiki/Q29957","display_name":"Funnel","level":2,"score":0.5413060784339905},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.5023138523101807},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45346227288246155},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4330289661884308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37272658944129944},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29248321056365967},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19603395462036133},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.1455872356891632},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C130436687","wikidata":"https://www.wikidata.org/wiki/Q7978591","display_name":"Web modeling","level":3,"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/C127613066","wikidata":"https://www.wikidata.org/wiki/Q557770","display_name":"Web API","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/k-06-2021-0473","is_oa":false,"landing_page_url":"https://doi.org/10.1108/k-06-2021-0473","pdf_url":null,"source":{"id":"https://openalex.org/S168682784","display_name":"Kybernetes","issn_l":"0368-492X","issn":["0368-492X","1758-7883"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kybernetes","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1511558225","https://openalex.org/W1536060714","https://openalex.org/W1966716734","https://openalex.org/W1992889781","https://openalex.org/W1996074959","https://openalex.org/W2006603393","https://openalex.org/W2034926402","https://openalex.org/W2036634567","https://openalex.org/W2037295150","https://openalex.org/W2039722754","https://openalex.org/W2056943035","https://openalex.org/W2056944867","https://openalex.org/W2070387265","https://openalex.org/W2074724691","https://openalex.org/W2085063596","https://openalex.org/W2086037720","https://openalex.org/W2089192108","https://openalex.org/W2095649738","https://openalex.org/W2096473998","https://openalex.org/W2107521404","https://openalex.org/W2109505752","https://openalex.org/W2113933725","https://openalex.org/W2122989928","https://openalex.org/W2124764091","https://openalex.org/W2125441033","https://openalex.org/W2140929211","https://openalex.org/W2148143831","https://openalex.org/W2151987718","https://openalex.org/W2321837197","https://openalex.org/W2341359542","https://openalex.org/W2408574227","https://openalex.org/W2525952498","https://openalex.org/W2529436585","https://openalex.org/W2611012316","https://openalex.org/W2766711123","https://openalex.org/W2790068398","https://openalex.org/W2801922753","https://openalex.org/W2911964244","https://openalex.org/W2913153410","https://openalex.org/W2916191623","https://openalex.org/W2969161295","https://openalex.org/W2969598588","https://openalex.org/W3007090855","https://openalex.org/W3037819556","https://openalex.org/W3045688179","https://openalex.org/W3102359981","https://openalex.org/W3123399111","https://openalex.org/W3125952450","https://openalex.org/W3149213291","https://openalex.org/W4234314512","https://openalex.org/W4235779660","https://openalex.org/W6674778633","https://openalex.org/W6818654693"],"related_works":["https://openalex.org/W2073875810","https://openalex.org/W2356551568","https://openalex.org/W2081113335","https://openalex.org/W2358635018","https://openalex.org/W2364686644","https://openalex.org/W2889922688","https://openalex.org/W2368101485","https://openalex.org/W3201452447","https://openalex.org/W4242602405","https://openalex.org/W2145557708"],"abstract_inverted_index":{"Purpose":[0],"Purchase":[1],"conversion":[2,23,46,74,116,226,402,461],"prediction":[3,403],"aims":[4,66],"to":[5,15,59,67,82,110,172,190,271,287,393,436],"improve":[6],"user":[7],"experience":[8],"and":[9,52,97,164,177,179,203,262,293,303,305,329,354,368,397,404],"convert":[10,153],"visitors":[11],"into":[12,140,156],"real":[13],"buyers":[14],"drive":[16],"sales":[17],"of":[18,72,114,159,195,234,254,297,308,339,351,364,371,384,441,452,459],"firms;":[19],"however,":[20],"the":[21,73,88,115,134,151,173,183,193,200,205,225,241,246,260,266,272,277,299,321,349,362,369,372,382,385,390,438,453,457],"total":[22],"rate":[24],"is":[25,33,188,389],"low,":[26],"especially":[27],"for":[28,283,361],"e-retailers.":[29],"To":[30,381],"date,":[31],"little":[32],"known":[34],"about":[35],"how":[36],"e-retailers":[37],"can":[38,228,325],"scientifically":[39],"detect":[40,68,111],"users'":[41,220],"intents":[42],"within":[43,224],"a":[44,69,83,106,120,145,157,166,251,358,412,420,424],"purchase":[45,460],"funnel":[47,75,117,227],"during":[48,463],"their":[49,126,235,312,343],"ongoing":[50,100,373,465],"sessions":[51,142],"strategically":[53],"optimize":[54],"real-time":[55,70,90,332,398],"marketing":[56],"tactics":[57],"corresponding":[58],"dynamic":[60],"intent":[61,222,333],"states.":[62],"This":[63],"study":[64,392,418,431],"mainly":[65],"state":[71],"based":[76,143,445],"on":[77,144,346,411,446],"graph":[78,168,237,281,340,447],"theory,":[79],"which":[80,356],"refers":[81],"five-class":[84,425],"classification":[85,414,426],"problem":[86,194],"in":[87,257,378,401,423],"overt":[89],"choice":[91],"decisions":[92],"(RTCDs)\u2014click,":[93],"tag-to-wishlist,":[94],"add-to-cart,":[95],"remove-from-cart":[96],"purchase\u2014during":[98],"an":[99,327,464],"session.":[101,466],"Design/methodology/approach":[102],"The":[103,215,317,449],"authors":[104,152,201],"propose":[105],"novel":[107],"graph-theoretic":[108,216,247,323,421],"framework":[109],"different":[112],"states":[113,223],"by":[118],"identifying":[119],"user's":[121],"unobserved":[122],"mindset":[123],"revealed":[124],"from":[125,348],"navigation":[127],"process":[128],"graph,":[129],"namely":[130],"clickstream":[131,136,162,309,395,442],"graph.":[132],"First,":[133],"raw":[135],"data":[137,444],"are":[138,285],"identified":[139],"individual":[141],"30-min":[146],"time-out":[147],"heuristic":[148],"approach.":[149],"Then,":[150],"each":[154],"session":[155,374,443],"sequence":[158],"temporal":[160,167,322,433],"item-level":[161,434],"graphs":[163,310,396,435],"conduct":[165],"feature":[169],"engineering":[170],"according":[171],"basic,":[174,300],"single-,":[175,301],"dyadic-":[176,302],"triadic-node":[178,304],"global":[180,306],"characteristics.":[181],"Furthermore,":[182],"synthetic":[184],"minority":[185],"oversampling":[186],"technique":[187],"adopted":[189],"address":[191],"with":[192,208,259],"classifying":[196],"imbalanced":[197],"data.":[198],"Finally,":[199],"train":[202],"test":[204],"proposed":[206,454],"approach":[207,217,324,422,455],"several":[209],"popular":[210],"artificial":[211],"intelligence":[212],"algorithms.":[213],"Findings":[214],"validates":[218],"that":[219,245,320],"latent":[221],"be":[229,288],"interpreted":[230],"as":[231,269],"time-varying":[232,450],"natures":[233],"online":[236],"footprints.":[238],"In":[239,275,295,428],"particular,":[240],"experimental":[242],"results":[243],"indicate":[244],"feature-oriented":[248],"models":[249],"achieve":[250],"substantial":[252],"improvement":[253],"over":[255],"27%":[256],"line":[258],"macro-average":[261],"micro-average":[263],"area":[264],"under":[265],"precision-recall":[267],"curve,":[268],"compared":[270],"conventional":[273],"ones.":[274],"addition,":[276,429],"top":[278],"five":[279],"informative":[280],"features":[282,341],"RTCDs":[284,347],"found":[286],"Transitivity,":[289],"Edge,":[290],"Node,":[291],"Degree":[292],"Reciprocity.":[294],"view":[296],"interpretability,":[298],"characteristics":[307,451],"have":[311,342,408],"specific":[313,344],"advantages.":[314],"Practical":[315],"implications":[316],"findings":[318],"suggest":[319],"form":[326],"efficient":[328],"powerful":[330],"AI-based":[331],"detecting":[334],"decision-support":[335],"system.":[336],"Different":[337],"levels":[338],"interpretability":[345],"perspectives":[350],"consumer":[352],"behavior":[353],"psychology,":[355],"provides":[357],"theoretical":[359],"basis":[360],"design":[363],"computer":[365],"information":[366],"systems":[367],"optimization":[370],"intervention":[375],"or":[376],"recommendation":[377],"e-commerce.":[379],"Originality/value":[380],"best":[383],"authors'":[386],"knowledge,":[387],"this":[388,417,430],"first":[391],"apply":[394],"decision":[399],"choices":[400],"detection.":[405],"Most":[406],"studies":[407],"only":[409],"meditated":[410],"binary":[413],"problem,":[415],"while":[416],"applies":[419],"problem.":[427],"constructs":[432],"represent":[437],"original":[439],"structure":[440],"theory.":[448],"enhance":[456],"performance":[458],"detection":[462]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}