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Article: Construction manpower demand forecasting: a comparative study of univariate time series, multiple regression and econometric modelling techniques

TitleConstruction manpower demand forecasting: a comparative study of univariate time series, multiple regression and econometric modelling techniques
Authors
KeywordsBox jenkins
Error handling
Forecasting
Manpower planning
Accurate prediction
Issue Date2011
PublisherEmerald Group Publishing Limited. The Journal's web site is located at http://www.emeraldinsight.com/ecam.htm
Citation
Engineering, Construction and Architectural Management, 2011, v. 18 n. 1, p. 7-29 How to Cite?
Abstract
Purpose - The purpose of this paper is to examine the performance of the vector error-correction (VEC) econometric modelling technique in predicting short- to medium-term construction manpower demand. Design/methodology/approach - The VEC modelling technique is evaluated with two conventional forecasting methods: the Box-Jenkins approach and the multiple regression analysis, based on the forecasting accuracy on construction manpower demand. Findings - While the forecasting reliability of the VEC modelling technique is slightly inferior to the multiple log-linear regression analysis in terms of forecasting accuracy, the error correction econometric modelling technique outperformed the Box-Jenkins approach. The VEC and the multiple linear regression analysis in forecasting can better capture the causal relationship between the construction manpower demand and the associated factors. Practical implications - Accurate predictions of the level of manpower demand are important for the formulation of successful policy to minimise possible future skill mismatch. Originality/value - The accuracy of econometric modelling technique has not been evaluated empirically in construction manpower forecasting. This paper unveils the predictability of the prevailing manpower demand forecasting modelling techniques. Additionally, economic indicators that are significantly related to construction manpower demand are identified to facilitate human resource planning, and policy simulation and formulation in construction. © Emerald Group Publishing Limited 0969-9988.
Persistent Identifierhttp://hdl.handle.net/10722/135074
ISSN

 

Author Affiliations
  1. The University of Hong Kong
  2. Hong Kong Polytechnic University
DC FieldValueLanguage
dc.contributor.authorWong, JMWen_US
dc.contributor.authorChan, APCen_US
dc.contributor.authorChiang, YHen_US
dc.date.accessioned2011-07-27T01:27:28Z-
dc.date.available2011-07-27T01:27:28Z-
dc.date.issued2011en_US
dc.identifier.citationEngineering, Construction and Architectural Management, 2011, v. 18 n. 1, p. 7-29en_US
dc.identifier.issn0969-9988-
dc.identifier.urihttp://hdl.handle.net/10722/135074-
dc.description.abstractPurpose - The purpose of this paper is to examine the performance of the vector error-correction (VEC) econometric modelling technique in predicting short- to medium-term construction manpower demand. Design/methodology/approach - The VEC modelling technique is evaluated with two conventional forecasting methods: the Box-Jenkins approach and the multiple regression analysis, based on the forecasting accuracy on construction manpower demand. Findings - While the forecasting reliability of the VEC modelling technique is slightly inferior to the multiple log-linear regression analysis in terms of forecasting accuracy, the error correction econometric modelling technique outperformed the Box-Jenkins approach. The VEC and the multiple linear regression analysis in forecasting can better capture the causal relationship between the construction manpower demand and the associated factors. Practical implications - Accurate predictions of the level of manpower demand are important for the formulation of successful policy to minimise possible future skill mismatch. Originality/value - The accuracy of econometric modelling technique has not been evaluated empirically in construction manpower forecasting. This paper unveils the predictability of the prevailing manpower demand forecasting modelling techniques. Additionally, economic indicators that are significantly related to construction manpower demand are identified to facilitate human resource planning, and policy simulation and formulation in construction. © Emerald Group Publishing Limited 0969-9988.-
dc.languageengen_US
dc.publisherEmerald Group Publishing Limited. The Journal's web site is located at http://www.emeraldinsight.com/ecam.htm-
dc.relation.ispartofEngineering, Construction and Architectural Managementen_US
dc.subjectBox jenkins-
dc.subjectError handling-
dc.subjectForecasting-
dc.subjectManpower planning-
dc.subjectAccurate prediction-
dc.titleConstruction manpower demand forecasting: a comparative study of univariate time series, multiple regression and econometric modelling techniquesen_US
dc.typeArticleen_US
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0969-9988&volume=18&issue=1&spage=7&epage=29&date=2011&atitle=Construction+manpower+demand+forecasting:+a+comparative+study+of+univariate+time+series,+multiple+regression+and+econometric+modelling+techniques-
dc.identifier.emailWong, JMW: bsjamesw@gmail.comen_US
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1108/09699981111098667-
dc.identifier.scopuseid_2-s2.0-79953177487-
dc.identifier.hkuros173582en_US
dc.identifier.volume18en_US
dc.identifier.issue1en_US
dc.identifier.spage7en_US
dc.identifier.epage29en_US
dc.identifier.citeulike8622862-

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