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Article: Construction manpower demand forecasting: a comparative study of univariate time series, multiple regression and econometric modelling techniques
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TitleConstruction manpower demand forecasting: a comparative study of univariate time series, multiple regression and econometric modelling techniques
 
AuthorsWong, JMW1
Chan, APC2
Chiang, YH2
 
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
 
CitationEngineering, Construction and Architectural Management, 2011, v. 18 n. 1, p. 7-29 [How to Cite?]
DOI: http://dx.doi.org/10.1108/09699981111098667
 
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.
 
ISSN0969-9988
 
DOIhttp://dx.doi.org/10.1108/09699981111098667
 
DC FieldValue
dc.contributor.authorWong, JMW
 
dc.contributor.authorChan, APC
 
dc.contributor.authorChiang, YH
 
dc.date.accessioned2011-07-27T01:27:28Z
 
dc.date.available2011-07-27T01:27:28Z
 
dc.date.issued2011
 
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.description.natureLink_to_subscribed_fulltext
 
dc.identifier.citationEngineering, Construction and Architectural Management, 2011, v. 18 n. 1, p. 7-29 [How to Cite?]
DOI: http://dx.doi.org/10.1108/09699981111098667
 
dc.identifier.citeulike8622862
 
dc.identifier.doihttp://dx.doi.org/10.1108/09699981111098667
 
dc.identifier.epage29
 
dc.identifier.hkuros173582
 
dc.identifier.issn0969-9988
 
dc.identifier.issue1
 
dc.identifier.openurl
 
dc.identifier.scopuseid_2-s2.0-79953177487
 
dc.identifier.spage7
 
dc.identifier.urihttp://hdl.handle.net/10722/135074
 
dc.identifier.volume18
 
dc.languageeng
 
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 Management
 
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 techniques
 
dc.typeArticle
 
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Author Affiliations
  1. The University of Hong Kong
  2. Hong Kong Polytechnic University