{"id":"https://openalex.org/W3081618811","doi":"https://doi.org/10.1109/tem.2020.3016329","title":"Can Online Consumer Reviews Signal Restaurant Closure: A Deep Learning-Based Time-Series Analysis","display_name":"Can Online Consumer Reviews Signal Restaurant Closure: A Deep Learning-Based Time-Series Analysis","publication_year":2020,"publication_date":"2020-09-02","ids":{"openalex":"https://openalex.org/W3081618811","doi":"https://doi.org/10.1109/tem.2020.3016329","mag":"3081618811"},"language":"en","primary_location":{"id":"doi:10.1109/tem.2020.3016329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tem.2020.3016329","pdf_url":null,"source":{"id":"https://openalex.org/S154533451","display_name":"IEEE Transactions on Engineering Management","issn_l":"0018-9391","issn":["0018-9391","1558-0040"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Engineering Management","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/A5000963620","display_name":"Jie Tao","orcid":"https://orcid.org/0000-0002-8958-561X"},"institutions":[{"id":"https://openalex.org/I126350171","display_name":"Fairfield University","ror":"https://ror.org/04z49n283","country_code":"US","type":"education","lineage":["https://openalex.org/I126350171"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Tao","raw_affiliation_strings":["Dolan School of Business, Fairfield University, Fairfield, CT, USA"],"raw_orcid":"https://orcid.org/0000-0002-8958-561X","affiliations":[{"raw_affiliation_string":"Dolan School of Business, Fairfield University, Fairfield, CT, USA","institution_ids":["https://openalex.org/I126350171"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010146682","display_name":"Lina Zhou","orcid":"https://orcid.org/0000-0003-1864-0527"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lina Zhou","raw_affiliation_strings":["Belk College of Business, The University of North Carolina - Charlotte, Charlotte, NC, USA"],"raw_orcid":"https://orcid.org/0000-0003-1864-0527","affiliations":[{"raw_affiliation_string":"Belk College of Business, The University of North Carolina - Charlotte, Charlotte, NC, USA","institution_ids":["https://openalex.org/I102149020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0812,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.801265,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"70","issue":"3","first_page":"834","last_page":"848"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10609","display_name":"Digital Marketing and Social Media","score":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/closure","display_name":"Closure (psychology)","score":0.7431454062461853},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.7137962579727173},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.573891818523407},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5161903500556946},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.47280970215797424},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4411679208278656},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.43975770473480225},{"id":"https://openalex.org/keywords/business-intelligence","display_name":"Business intelligence","score":0.42205679416656494},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3351421356201172},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32681483030319214},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30543628334999084}],"concepts":[{"id":"https://openalex.org/C146834321","wikidata":"https://www.wikidata.org/wiki/Q2979672","display_name":"Closure (psychology)","level":2,"score":0.7431454062461853},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.7137962579727173},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.573891818523407},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5161903500556946},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.47280970215797424},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4411679208278656},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.43975770473480225},{"id":"https://openalex.org/C2767350","wikidata":"https://www.wikidata.org/wiki/Q6662173","display_name":"Business intelligence","level":2,"score":0.42205679416656494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3351421356201172},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32681483030319214},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30543628334999084},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tem.2020.3016329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tem.2020.3016329","pdf_url":null,"source":{"id":"https://openalex.org/S154533451","display_name":"IEEE Transactions on Engineering Management","issn_l":"0018-9391","issn":["0018-9391","1558-0040"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Engineering Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W124349154","https://openalex.org/W1553969394","https://openalex.org/W1563704216","https://openalex.org/W1850325679","https://openalex.org/W1972581513","https://openalex.org/W1976355580","https://openalex.org/W1984500452","https://openalex.org/W1986078433","https://openalex.org/W1988271616","https://openalex.org/W1997259208","https://openalex.org/W2022057354","https://openalex.org/W2079223345","https://openalex.org/W2081580037","https://openalex.org/W2089309344","https://openalex.org/W2102636708","https://openalex.org/W2110242546","https://openalex.org/W2117717090","https://openalex.org/W2120135958","https://openalex.org/W2130486630","https://openalex.org/W2139334734","https://openalex.org/W2146487954","https://openalex.org/W2152978689","https://openalex.org/W2167517173","https://openalex.org/W2239794783","https://openalex.org/W2250539671","https://openalex.org/W2252691273","https://openalex.org/W2342352817","https://openalex.org/W2399358428","https://openalex.org/W2427312199","https://openalex.org/W2511832088","https://openalex.org/W2554367394","https://openalex.org/W2573659029","https://openalex.org/W2600278912","https://openalex.org/W2608847424","https://openalex.org/W2622365670","https://openalex.org/W2622816133","https://openalex.org/W2734777338","https://openalex.org/W2751120573","https://openalex.org/W2772668023","https://openalex.org/W2800569739","https://openalex.org/W2801998161","https://openalex.org/W2811103148","https://openalex.org/W2895547478","https://openalex.org/W2911806759","https://openalex.org/W2994075388","https://openalex.org/W3121775323","https://openalex.org/W3123091093","https://openalex.org/W3124946654","https://openalex.org/W3141714916","https://openalex.org/W4232568570","https://openalex.org/W6633169664","https://openalex.org/W6743622377","https://openalex.org/W6771508660"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W410723623","https://openalex.org/W2413243053","https://openalex.org/W2015341305","https://openalex.org/W4225593417","https://openalex.org/W2035068594","https://openalex.org/W2573498121","https://openalex.org/W3022298670","https://openalex.org/W3160494304","https://openalex.org/W1549477351"],"abstract_inverted_index":{"Business":[0],"closure":[1,28,61,90,142],"is":[2,76],"a":[3,13,79,110,116],"critical":[4],"stage":[5],"in":[6,71,106,140],"the":[7,18,35,44,51,57,68,72,129,167,176,179],"lifecycle":[8],"of":[9,15,37,59,128,178,184],"any":[10],"business.":[11],"Despite":[12],"body":[14],"literature":[16],"on":[17,26,43],"factors":[19,39],"influencing":[20],"business":[21,27,60,89,141,154,192],"failure":[22],"and/or":[23],"success,":[24],"studies":[25],"prediction":[29,58],"are":[30,170],"next":[31],"to":[32,78],"none.":[33],"Additionally,":[34],"identification":[36],"those":[38],"has":[40],"focused":[41],"primarily":[42],"managerial":[45,189],"and":[46,66,99,114,166,193],"economic":[47],"dimensions":[48],"rather":[49],"than":[50],"consumer":[52,64],"dimension.":[53],"This":[54],"research":[55,186],"investigates":[56],"from":[62,164],"online":[63,107,134,147],"reviews,":[65],"validates":[67],"predictive":[69],"models":[70],"restaurant":[73],"industry,":[74],"which":[75,144,172],"subject":[77],"relatively":[80],"high":[81],"attrition":[82],"rate.":[83],"Our":[84],"proposed":[85,130,180],"method":[86,131],"for":[87,122,152,175,191],"predicting":[88,153],"includes":[91],"several":[92],"novel":[93,117],"artifacts,":[94],"including":[95],"integrating":[96],"deep":[97],"learning":[98],"time-series":[100],"analysis":[101],"techniques,":[102],"extracting":[103],"information":[104],"embedded":[105],"reviews":[108,135,148],"using":[109,132],"hybrid":[111],"classification":[112],"method,":[113],"incorporating":[115],"triple":[118],"word":[119],"embedding":[120],"model":[121],"text":[123],"representation.":[124],"The":[125,182],"evaluation":[126],"results":[127,169],"Yelp":[133],"demonstrate":[136],"its":[137],"superior":[138],"performance":[139],"prediction,":[143],"indicate":[145],"that":[146],"provide":[149,173],"strong":[150],"signals":[151],"closure.":[155],"We":[156],"conduct":[157],"another":[158],"experiment":[159,168],"with":[160],"review":[161],"data":[162],"collected":[163],"TripAdvisors.com,":[165],"consistent,":[171],"evidence":[174],"generalizability":[177],"method.":[181],"findings":[183],"this":[185],"have":[187],"important":[188],"implications":[190],"investment":[194],"decision":[195],"making.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}