Modelling the Satisfaction of Contractors: The Impact of Client Performance
| dc.contributor.author | Soetanto, Robby | |
| dc.contributor.author | Proverbs, David G. | |
| dc.date.accessioned | 2008-06-04T14:24:38Z | |
| dc.date.available | 2008-06-04T14:24:38Z | |
| dc.date.issued | 2002 | |
| dc.identifier.citation | Engineering, Construction and Architectural Management, 9(5/6): 453-465 | |
| dc.identifier.issn | 09699988 | |
| dc.identifier.issn | 1365232X | |
| dc.identifier.doi | 10.1108/eb021239 | |
| dc.identifier.uri | http://hdl.handle.net/2436/29540 | |
| dc.description.abstract | An assessment of the performance of UK clients on 55 ‘case projects’ as considered by contractors is presented and used to develop models of contractors' satisfaction. Principal component analysis (PCA) reveals five dimensions to contractor satisfaction, classified in this research as (i) support provided to contractors, (ii) clients' attitude, (iii) clients' understanding of their own needs, (iv) quality of clients' brief, and (v) financial aspects of performance. Knowledge of these models should enable clients to perform better, which is conducive towards satisfactory participant performance and overall project performance. The models identify three key aspects of client performance that are found to significantly influence contractors' satisfaction levels, namely, (i) the capability of the client's representative, (ii) the client's past performance and project management experience and (iii) the financial soundness and reputation of the client. Additionally, the nature of the project and certain characteristics of contractors also influence satisfaction levels. The models demonstrated accurate predictive power and were found to be valid and robust. Clients could use the models to help improve their performance, leading to more successful project implementation. This will also promote the development of harmonious working relationships within the construction project coalition (PC). (Emerald Group Publishing Limited) | |
| dc.language.iso | en | |
| dc.publisher | Wiley InterScience | |
| dc.relation.url | https://www.emeraldinsight.com/doi/abs/10.1108/eb021239 | |
| dc.subject | Multiple regression analysis | |
| dc.subject | Construction industry | |
| dc.subject | Construction client | |
| dc.subject | Principal Component Analysis (PCA) | |
| dc.subject | Contractor satisfaction | |
| dc.subject | Performance measures | |
| dc.subject | Modelling | |
| dc.subject | Construction planning | |
| dc.subject | Construction management | |
| dc.subject | Construction project organisation | |
| dc.subject | Client performance | |
| dc.subject | Performance monitoring | |
| dc.subject | Project performance | |
| dc.title | Modelling the Satisfaction of Contractors: The Impact of Client Performance | |
| dc.type | Journal article | |
| dc.identifier.journal | Engineering, Construction and Architectural Management | |
| html.description.abstract | An assessment of the performance of UK clients on 55 ‘case projects’ as considered by contractors is presented and used to develop models of contractors' satisfaction. Principal component analysis (PCA) reveals five dimensions to contractor satisfaction, classified in this research as (i) support provided to contractors, (ii) clients' attitude, (iii) clients' understanding of their own needs, (iv) quality of clients' brief, and (v) financial aspects of performance. Knowledge of these models should enable clients to perform better, which is conducive towards satisfactory participant performance and overall project performance. The models identify three key aspects of client performance that are found to significantly influence contractors' satisfaction levels, namely, (i) the capability of the client's representative, (ii) the client's past performance and project management experience and (iii) the financial soundness and reputation of the client. Additionally, the nature of the project and certain characteristics of contractors also influence satisfaction levels. The models demonstrated accurate predictive power and were found to be valid and robust. Clients could use the models to help improve their performance, leading to more successful project implementation. This will also promote the development of harmonious working relationships within the construction project coalition (PC). (Emerald Group Publishing Limited) |
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