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Modelling Client Satisfaction Levels: The Impact of Contractor Performance
Author(s) -
Robby Soetanto,
David Proverbs
Publication year - 2012
Publication title -
construction economics and building
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.4
H-Index - 20
ISSN - 2204-9029
DOI - 10.5130/ajceb.v2i1.2883
Subject(s) - respondent , predictive power , regression analysis , predictive modelling , operations management , computer science , business , engineering , machine learning , philosophy , epistemology , political science , law
The performance of contractors is known to be a key determinant of client satisfaction.Here, using factor analysis, clients’ satisfaction is defined in several dimensions. Based onclients’ assessment of contractor performance, a number of satisfaction models developedusing the multiple regression (MR) technique are presented. The models identify arange of variables encompassing contractor performance, project performance and respondent(i.e. client) attributes as useful predictors of satisfaction levels. Contractor performanceattributes were found to be of utmost importance indicating that clientsatisfaction levels are mainly dependent on the performance of the contractor. Furthermore,findings suggest that subjectivity is to some extent prevalent in clients’ performanceassessment. The models demonstrate accurate and reliable predictive power as confirmedby validation tests. Contractors could use the models to help improve their performanceleading to more satisfied clients. This would also promote the development ofharmonious working relationships within the construction project coalition

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