{"id":"https://openalex.org/W2964370982","doi":"https://doi.org/10.1108/k-09-2018-0506","title":"A new methodology for customer behavior analysis using time series clustering","display_name":"A new methodology for customer behavior analysis using time series clustering","publication_year":2019,"publication_date":"2019-07-30","ids":{"openalex":"https://openalex.org/W2964370982","doi":"https://doi.org/10.1108/k-09-2018-0506","mag":"2964370982"},"language":"en","primary_location":{"id":"doi:10.1108/k-09-2018-0506","is_oa":false,"landing_page_url":"https://doi.org/10.1108/k-09-2018-0506","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/A5057409216","display_name":"Hossein Abbasimehr","orcid":"https://orcid.org/0000-0001-8615-5553"},"institutions":[{"id":"https://openalex.org/I51301133","display_name":"Azarbaijan Shahid Madani University","ror":"https://ror.org/05pg2cw06","country_code":"IR","type":"education","lineage":["https://openalex.org/I51301133"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Hossein Abbasimehr","raw_affiliation_strings":["Faculty of Information Technology and Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Islamic Republic of Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology and Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Islamic Republic of Iran","institution_ids":["https://openalex.org/I51301133"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077063417","display_name":"Mostafa Shabani","orcid":"https://orcid.org/0000-0001-7552-3525"},"institutions":[{"id":"https://openalex.org/I80543232","display_name":"K.N.Toosi University of Technology","ror":"https://ror.org/0433abe34","country_code":"IR","type":"education","lineage":["https://openalex.org/I80543232"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mostafa Shabani","raw_affiliation_strings":["Khajeh Nasir Toosi University of Technology, Tehran, Islamic Republic of Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Khajeh Nasir Toosi University of Technology, Tehran, Islamic Republic of Iran","institution_ids":["https://openalex.org/I80543232"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1683,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.79043155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"50","issue":"2","first_page":"221","last_page":"242"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9970999956130981,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9970999956130981,"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/T12384","display_name":"Customer churn and segmentation","score":0.9955000281333923,"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/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9714000225067139,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6736654043197632},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6412152647972107},{"id":"https://openalex.org/keywords/transaction-data","display_name":"Transaction data","score":0.6081311702728271},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.5981244444847107},{"id":"https://openalex.org/keywords/consumer-behaviour","display_name":"Consumer behaviour","score":0.49962735176086426},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4933988153934479},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.4526103436946869},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4512098431587219},{"id":"https://openalex.org/keywords/direct-marketing","display_name":"Direct marketing","score":0.4484557509422302},{"id":"https://openalex.org/keywords/marketing-research","display_name":"Marketing research","score":0.4284200072288513},{"id":"https://openalex.org/keywords/customer-relationship-management","display_name":"Customer relationship management","score":0.4241834580898285},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.41466620564460754},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.4109499454498291},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3633878827095032},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.2229389250278473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16477298736572266},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13641390204429626},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11605209112167358}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6736654043197632},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6412152647972107},{"id":"https://openalex.org/C127722929","wikidata":"https://www.wikidata.org/wiki/Q7833714","display_name":"Transaction data","level":3,"score":0.6081311702728271},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.5981244444847107},{"id":"https://openalex.org/C23213687","wikidata":"https://www.wikidata.org/wiki/Q301468","display_name":"Consumer behaviour","level":2,"score":0.49962735176086426},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4933988153934479},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.4526103436946869},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4512098431587219},{"id":"https://openalex.org/C536005652","wikidata":"https://www.wikidata.org/wiki/Q677073","display_name":"Direct marketing","level":2,"score":0.4484557509422302},{"id":"https://openalex.org/C48891531","wikidata":"https://www.wikidata.org/wiki/Q1141436","display_name":"Marketing research","level":2,"score":0.4284200072288513},{"id":"https://openalex.org/C98825075","wikidata":"https://www.wikidata.org/wiki/Q485643","display_name":"Customer relationship management","level":2,"score":0.4241834580898285},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.41466620564460754},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.4109499454498291},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3633878827095032},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2229389250278473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16477298736572266},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13641390204429626},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11605209112167358},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/k-09-2018-0506","is_oa":false,"landing_page_url":"https://doi.org/10.1108/k-09-2018-0506","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W203157900","https://openalex.org/W1580201134","https://openalex.org/W1751719206","https://openalex.org/W1798220690","https://openalex.org/W1886156989","https://openalex.org/W1894414046","https://openalex.org/W1911940340","https://openalex.org/W1978551333","https://openalex.org/W1996926811","https://openalex.org/W1998612608","https://openalex.org/W2008299439","https://openalex.org/W2011479129","https://openalex.org/W2012609801","https://openalex.org/W2020550672","https://openalex.org/W2021109866","https://openalex.org/W2029387089","https://openalex.org/W2033799444","https://openalex.org/W2037809340","https://openalex.org/W2049017883","https://openalex.org/W2052835589","https://openalex.org/W2062625370","https://openalex.org/W2072094247","https://openalex.org/W2072593151","https://openalex.org/W2075150581","https://openalex.org/W2076261257","https://openalex.org/W2078752440","https://openalex.org/W2087924048","https://openalex.org/W2098759488","https://openalex.org/W2099492140","https://openalex.org/W2107651406","https://openalex.org/W2128160875","https://openalex.org/W2132373491","https://openalex.org/W2145489396","https://openalex.org/W2147953360","https://openalex.org/W2154819685","https://openalex.org/W2158703410","https://openalex.org/W2161888784","https://openalex.org/W2165385958","https://openalex.org/W2166058515","https://openalex.org/W2204903869","https://openalex.org/W2279867091","https://openalex.org/W2296306426","https://openalex.org/W2369810130","https://openalex.org/W2474310541","https://openalex.org/W2477805304","https://openalex.org/W2513975426","https://openalex.org/W2554789915","https://openalex.org/W2591467549","https://openalex.org/W2604628886","https://openalex.org/W2610239597","https://openalex.org/W2621145631","https://openalex.org/W2624545785","https://openalex.org/W2789467789","https://openalex.org/W2883853984","https://openalex.org/W2891606812","https://openalex.org/W2900958317","https://openalex.org/W2940656499","https://openalex.org/W2994440511","https://openalex.org/W3123920865","https://openalex.org/W3125877494"],"related_works":["https://openalex.org/W642407701","https://openalex.org/W2085699531","https://openalex.org/W1967673583","https://openalex.org/W1552628970","https://openalex.org/W2566315021","https://openalex.org/W2039336362","https://openalex.org/W4240052287","https://openalex.org/W2736243208","https://openalex.org/W2347358774","https://openalex.org/W4238411277"],"abstract_inverted_index":{"Purpose":[0],"The":[1,62,133,194,215,245],"purpose":[2],"of":[3,16,20,40,58,74,83,95,110,119,125,146,173,199,218,241,325,369],"this":[4,211,373],"paper":[5,262,333],"is":[6,28,46,297,327,351,374],"to":[7,35,165,186,209,264,280,283,307,338,390],"propose":[8],"a":[9,84,176,335],"new":[10,26,336],"methodology":[11,27,45,275,318,337],"that":[12,76,114,192,251,378],"handles":[13],"the":[14,17,56,65,79,91,96,106,120,122,130,139,144,147,188,200,203,238,265,273,291,308,322,367,370,375,380],"issue":[15],"dynamic":[18,239,323,341],"behavior":[19,126,220,240,296,342],"customers":[21,41,113,150,174,242,303,326],"over":[22,42,243,300,354],"time.":[23,43,244],"Design/methodology/approach":[24],"A":[25],"presented":[29],"based":[30],"on":[31,105,143,267,347],"time":[32,59,301,344,387],"series":[33,60,345,388],"clustering":[34,346,389],"extract":[36],"dominant":[37,123],"behavioral":[38],"patterns":[39],"This":[44,86,261,332,350],"implemented":[47],"using":[48,78,116,129,343],"bank":[49,189,204],"customers\u2019":[50],"transactions":[51],"data":[52,63,82,87,92,109],"which":[53,319,358],"are":[54,77,115,127,248,304],"in":[55,230,286,357,393],"form":[57],"data.":[61,349],"include":[64],"recency":[66],"(R),":[67],"frequency":[68],"(F)":[69],"and":[70,167,180,221,257,302,383,386],"monetary":[71,148,384],"(M)":[72],"attributes":[73],"businesses":[75,282],"point-of-sale":[80],"(POS)":[81],"bank.":[85,97],"were":[88,136,151,184],"obtained":[89,134,246],"from":[90,138],"analysis":[93,145],"department":[94],"Findings":[98],"After":[99],"carrying":[100],"out":[101],"an":[102,314,352],"empirical":[103],"study":[104,377],"acquired":[107],"transaction":[108],"2,531":[111],"business":[112,293],"POS":[117],"devices":[118],"bank,":[121],"trends":[124,135,217,247,285,392],"discovered":[128,216],"proposed":[131,222,274],"methodology.":[132],"analyzed":[137],"marketing":[140,182,223,233],"viewpoint.":[141],"Based":[142],"attribute,":[149],"divided":[152],"into":[153],"four":[154],"main":[155],"segments,":[156],"including":[157],"high-value":[158],"growing":[159,162],"customers,":[160,163],"middle-value":[161],"prone":[164],"churn":[166],"churners.":[168],"For":[169],"each":[170],"resulted":[171],"group":[172],"with":[175,191],"distinctive":[177],"trend,":[178],"effective":[179,315],"practical":[181],"recommendations":[183,224],"devised":[185],"improve":[187],"relationship":[190,269],"group.":[193],"prone-to-churn":[195],"segment":[196],"contains":[197],"most":[198],"customers;":[201],"therefore,":[202],"should":[205],"conduct":[206],"interesting":[207],"promotions":[208],"retain":[210],"segment.":[212],"Practical":[213],"implications":[214],"customer":[219,268,287,295,316,340,394],"can":[225,253,276,320],"be":[226,254,277],"helpful":[227],"for":[228,329],"banks":[229],"devising":[231],"segment-specific":[232],"strategies":[234],"as":[235,272],"they":[236,252],"illustrate":[237],"visualized":[249],"so":[250],"easily":[255],"interpreted":[256],"used":[258],"by":[259],"banks.":[260],"contributes":[263],"literature":[266],"management":[270],"(CRM)":[271],"effectively":[278],"applied":[279],"different":[281],"reveal":[284,391],"behavior.":[288,395],"Originality/value":[289],"In":[290],"current":[292],"condition,":[294],"changing":[298],"continually":[299],"churning":[305],"due":[306],"reduced":[309],"switching":[310],"costs.":[311],"Therefore,":[312],"choosing":[313],"segmentation":[317,360],"consider":[321],"behaviors":[324],"essential":[328],"every":[330],"business.":[331],"proposes":[334],"capture":[339],"time-ordered":[348],"improvement":[353],"previous":[355],"studies,":[356],"static":[359],"approaches":[361],"have":[362],"often":[363],"been":[364],"adopted.":[365],"To":[366],"best":[368],"authors\u2019":[371],"knowledge,":[372],"first":[376],"combines":[379],"recency,":[381],"frequency,":[382],"model":[385]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
