{"id":"https://openalex.org/W2007793587","doi":"https://doi.org/10.1080/01446199600000004","title":"Residential construction demand forecasting using economic indicators: a comparative study of artificial neural networks and multiple regression","display_name":"Residential construction demand forecasting using economic indicators: a comparative study of artificial neural networks and multiple regression","publication_year":1996,"publication_date":"1996-01-01","ids":{"openalex":"https://openalex.org/W2007793587","doi":"https://doi.org/10.1080/01446199600000004","mag":"2007793587"},"language":"en","primary_location":{"id":"doi:10.1080/01446199600000004","doi":"https://doi.org/10.1080/01446199600000004","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01446199600000004","pdf_url":null,"source":{"id":"https://openalex.org/S128059648","display_name":"Construction Management and Economics","issn_l":"0144-6193","issn":["0144-6193","1466-433X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","jufo-1","norway-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Construction Management and Economics","raw_type":"journal-article"},"volume":null,"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/A5087024385","display_name":"Goh Bee Hua","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Goh Bee Hua","raw_affiliation_strings":["School of Building and Estate Management, National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Building and Estate Management, National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5087024385"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":4.677,"has_fulltext":false,"cited_by_count":86,"citation_normalized_percentile":{"value":0.94393742,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"14","issue":"1","first_page":"25","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9961000084877014,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9961000084877014,"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/T10632","display_name":"Housing Market and Economics","score":0.002899999963119626,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/demand-forecasting","display_name":"demand forecasting","score":0.8679999709129333},{"id":"https://openalex.org/keywords/economic-indicators","display_name":"economic indicators","score":0.9990000128746033},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.9990000128746033},{"id":"https://openalex.org/keywords/multiple-linear-regression","display_name":"multiple linear regression","score":0.9959999918937683},{"id":"https://openalex.org/keywords/forecasting-accuracy-comparison","display_name":"forecast accuracy comparison","score":0.8389999866485596},{"id":"https://openalex.org/keywords/singapore-housing-market","display_name":"Singapore housing market","score":0.652999997138977}],"concepts":[{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.8149313926696777},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6680904626846313},{"id":"https://openalex.org/C193809577","wikidata":"https://www.wikidata.org/wiki/Q3409300","display_name":"Demand forecasting","level":2,"score":0.5618297457695007},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5192989706993103},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5073170065879822},{"id":"https://openalex.org/C202353208","wikidata":"https://www.wikidata.org/wiki/Q1167393","display_name":"Economic indicator","level":2,"score":0.4828682243824005},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4703771471977234},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4696124196052551},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.43242311477661133},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4300190210342407},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.41865724325180054},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4015548825263977},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.36561307311058044},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3226337432861328},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3052701950073242},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.231271892786026},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22825494408607483},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20218154788017273},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.14770445227622986},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/01446199600000004","doi":"https://doi.org/10.1080/01446199600000004","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01446199600000004","pdf_url":null,"source":{"id":"https://openalex.org/S128059648","display_name":"Construction Management and Economics","issn_l":"0144-6193","issn":["0144-6193","1466-433X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","jufo-1","norway-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Construction Management and Economics","raw_type":"journal-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/46479","doi":null,"is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/46479","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5142999887466431}],"sustainable_development_goals_aurora":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6200000047683716}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W281358340","https://openalex.org/W572077994","https://openalex.org/W615439855","https://openalex.org/W645375789","https://openalex.org/W1503468974","https://openalex.org/W1507655388","https://openalex.org/W1564803941","https://openalex.org/W1588300724","https://openalex.org/W1964541176","https://openalex.org/W1996592256","https://openalex.org/W2004575508","https://openalex.org/W2011413757","https://openalex.org/W2019088249","https://openalex.org/W2024774441","https://openalex.org/W2056409211","https://openalex.org/W2076238694","https://openalex.org/W2082924607","https://openalex.org/W2120224355","https://openalex.org/W2270864342","https://openalex.org/W2438995916","https://openalex.org/W2766736793","https://openalex.org/W2797950480","https://openalex.org/W2898519191","https://openalex.org/W3148030349","https://openalex.org/W3203505176","https://openalex.org/W3207342693","https://openalex.org/W4210609092","https://openalex.org/W4246393709","https://openalex.org/W4285719527","https://openalex.org/W4300402905"],"related_works":["https://openalex.org/W2044445279","https://openalex.org/W2364232855","https://openalex.org/W2075910098","https://openalex.org/W2479396604","https://openalex.org/W1499950413","https://openalex.org/W7096328496","https://openalex.org/W2971684893","https://openalex.org/W7019413957","https://openalex.org/W2586051651","https://openalex.org/W3143204426"],"abstract_inverted_index":{"In":[0,118],"recent":[1],"years,":[2],"demand":[3,23,101,218],"for":[4,24,102,198,212],"residential":[5,25,103,216],"construction":[6,26,217],"has":[7],"been":[8],"growing":[9],"rapidly":[10],"in":[11,27,150,219],"Singapore.":[12,28,220],"This":[13],"paper":[14],"proposes":[15],"the":[16,30,47,54,68,74,77,86,115,122,129,147,163,173,187,213],"use":[17,69],"of":[18,70,76,91,125,132,152,172,183,215],"economic":[19,71,93,204],"indicators":[20,72,94,110,205],"to":[21,65,100,113,120,136,178],"predict":[22],"At":[29],"same":[31,130],"time,":[32],"two":[33,148],"forecasting":[34,123,154,170],"techniques":[35],"are":[36,95,111],"applied,":[37],"namely,":[38],"Artificial":[39],"Neural":[40],"Networks":[41],"(ANN)":[42],"and":[43],"Multiple":[44],"Regression":[45],"(MR),":[46],"former":[48],"being":[49],"a":[50,56,138,158],"state-of-the-art":[51,127],"technique":[52,79],"while":[53],"latter":[55],"conventional":[57,139],"one.":[58],"A":[59,89,142],"comparative":[60],"study":[61],"is":[62,134,144,176],"carried":[63],"out":[64],"determine":[66],"whether":[67],"with":[73,85],"application":[75],"ANN":[78,116,174],"can":[80],"produce":[81],"better":[82],"predictions":[83],"than":[84,195],"MR":[87,140,188],"method.":[88],"total":[90],"12":[92,109],"identified":[96],"as":[97,162,209],"significantly":[98],"related":[99],"construction.":[104],"Quarterly":[105],"data":[106,133],"from":[107,186],"these":[108],"used":[112,135,208],"develop":[114,137],"model.":[117,141,189],"order":[119],"assess":[121],"performance":[124],"this":[126],"technique,":[128],"set":[131],"comparison":[143],"made":[145],"between":[146],"models,":[149],"terms":[151],"their":[153],"accuracy,":[155],"by":[156],"using":[157],"relative":[159],"measure":[160],"known":[161],"Mean":[164],"Absolute":[165],"Percentage":[166],"Error":[167],"(MAPE).":[168],"The":[169,190],"error":[171],"model":[175],"found":[177],"be":[179,207],"about":[180],"one":[181],"fifth":[182],"that":[184,203],"derived":[185],"low":[191],"MAPE":[192],"values":[193],"(less":[194],"10%)":[196],"obtained":[197],"both":[199],"models":[200],"also":[201],"indicate":[202],"may":[206],"reliable":[210],"inputs":[211],"modelling":[214]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-06-24T00:00:00"}
