Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building and Real Estate | en_US |
| dc.creator | Wong, Ming-wah James | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/1347 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Forecasting manpower demand in the construction industry of Hong Kong | en_US |
| dcterms.abstract | Manpower is undoubtedly a valuable asset upon which the construction industry depends. Rapid changes of the economy, working arrangements, and technology in construction advocate reliable estimations of manpower demand to lessen future skills imbalance. Forecasting of the skill requirements appears to supply the means to an adequate resolution as there is no doubt that to facilitate human resources planning and budgeting, an organisation must precisely and in advance be able to determine the demand for personnel in each of the various disciplines. However, the reliability of the current construction manpower demand forecasts in Hong Kong has proved to be unsatisfactory. A solid understanding of future skill needs for the development of the industry is still lacking. The overall aim of this research is, therefore, to develop advanced manpower demand forecasting models, at both project level and industry level, to facilitate manpower planning for the construction industry of Hong Kong. At the project level, statistical models for forecasting the demand of labour demand for a given type of construction project were developed using multiple regression analysis. Details of 50 construction projects were analyzed to examine the relationships between the independent variables and the labour requirements. Forecasting models were developed to predict the demand for total labour and ten essential trades. Results reveal that project cost and project type play an important role in determining the project labour requirements. The derived models were validated by various diagnostic tests and comparing the predicted values with the out-of-sample actual values of four projects. The forecasting models could serve as practical and advanced tools for both contractors and government departments to predict the labour requirements and number of jobs created at an early outset, thus enabling proper human resources planning and budgeting. At the industry level, co-integration analysis was applied to develop a long-term relationship between aggregate manpower demand and the relevant variables in the construction industry. It was found that the aggregate manpower demand and the associated economic factors including construction output, wage, material price and interest rate are cointegrated. Subsequently, a vector error correction model incorporating short-run dynamics was developed for forecasting purposes. This model was then verified against various diagnostic statistical criteria. Upon completion of the aggregate model, occupational share manpower demand models were established by means of time series analyses at two levels: broad and detailed occupations. Using time series regression analysis, forecasting models for the share of seven broad occupational groups were derived by incorporating variables including the time trend, changing mix of works and technology. The occupational share models of the professional and associate professional specific skill occupations were then developed using exponential smoothing/moving average techniques. The construction output and labour productivity were found to be the most important and significant factors determining the quantity demand of construction manpower. Addressing these two attributes on policy formulation and implementation is critical to achieve a sustainable labour market. This research provides a significant contribution in the area of manpower demand forecasting. The forecasting models developed in this study can benefit the construction industry by providing critical information on the future construction manpower requirements and assist policy makers and training planners to formulate training strategies. Apart from this practical use, the research also contributes new knowledge to the area of manpower forecasting and planning. It enriches and updates the understanding of advanced forecasting methodologies for collating and compiling construction manpower statistics so as to facilitate manpower planning at project and industry levels. The study also explores valuable perspective on the link between macro and microeconomic factors which affect the demand for construction personnel. The research framework and methodology developed in this study can be replicated in a variety of cities in Mainland China and other Asian countries. This will provide a solid framework for conducting comparative studies in this region. | en_US |
| dcterms.extent | xix, 275 p. : ill. (some col.) ; 30 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2006 | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations. | en_US |
| dcterms.LCSH | Construction industry -- China -- Hong Kong -- Employees -- Supply and demand. | en_US |
| dcterms.LCSH | Construction workers -- China -- Hong Kong -- Supply and demand. | en_US |
| dcterms.accessRights | open access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b2059303x.pdf | For All Users | 8.42 MB | Adobe PDF | View/Open |
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