Seminar - Bee-Lan Oo - Modelling Individual Contractors’ Bid/No-bid Decision
Monday 12 November 2007, 1.00 - 2.00 pm
Civil Engineering Lecture Theatre 3
Abstract:
This research is based on the premise that there is heterogeneity in the population of contractors, i.e. that individual contractors exhibit different bidding behaviour when confronted with a given set of bidding variables. The aim of this study is to demonstrate through statistical modelling that individual Hong Kong and Singapore contractors’ bid/no-bid decision are influenced, to varying degrees, by (1) market conditions, (2) number of bidders, (3) project type and (4) project size; and that heterogeneity exists both at macro- (i.e. contractors operating within different competitive environments) and micro-levels (i.e. contractors operating within the same competitive environment). Data were gathered using a designed bidding experiment.
Individual-specific parameter estimates that relate the bidding variables to individual contractors’ bid/no-bid decision were obtained using the random-coefficients logistic model. The results show that not only there is significant heterogeneity between the Hong Kong and Singapore contractors in terms of both their intrinsic bid/no-bid preferences and responses to the bidding variables that affect their bid/no-bid decision, but also that the individual Hong Kong and Singapore contractors have different degrees of sensitivity towards the bidding variables (which is reflected in the varying individual-specific parameter estimates)
About the presenter:
With a Diploma in Building from Malaysia, Bee started in Singapore construction firms as Quantity Surveyor. In 2003, Bee obtained her bachelor degree in Building Construction Management from UNSW with 1st Class Honours and the University Medal. Following this, she has decided to take on her PhD studies in the Hong Kong Polytechnic University and has managed to complete her PhD in three years in September 2007. Her main field of study is in construction management and economics