Applying a random coefficients logistic model to contractors' decision to bid

Contractors' decision to bid is dependent on many individual characteristics, including some that are unobservable by their competitors. There is natural heterogeneity across contractors in terms of their (i) intrinsic bid/no‐bid preferences; and (ii) responses to decision to bid factors. This heterogeneity can be accounted for by applying a random coefficients approach to multiple bid/no‐bid responses through logistic modelling. The bid/no‐bid data were collected from managers of large and medium‐sized contractors in Hong Kong via a designed bidding experiment. Two random coefficients logistic models are developed. Model 1 considers only two groups of decision to bid factors, namely market environment factors (i.e. number of bidders, market conditions) and project‐specific factors (i.e. type and size of project). Model 2 extends Model 1 by adding two subject factors (i.e. years of experience, firm size) to study the effect of these individual factors on decision to bid. The results show that there is significant unobserved heterogeneity across contractors and that ignoring its effect results in a downward bias in the parameter estimates of the decision to bid factors. In using this approach contractors can better account for unobserved characteristics of their competitors when formulating their competitive strategies in deciding to bid.

[1]  Marija J. Norusis,et al.  SPSS 16.0 Statistical Procedures Companion , 2003 .

[2]  Gary J. Russell,et al.  A Probabilistic Choice Model for Market Segmentation and Elasticity Structure , 1989 .

[3]  Christine Pasquire,et al.  The effect of competitive tendering on value in construction , 1997 .

[4]  A. Shash Factors considered in tendering decisions by top UK contractors , 1993 .

[5]  Alan J. Wilson,et al.  Economic Theory and the Construction Industry. , 1975 .

[6]  Mark S. Handcock,et al.  Modeling Experimental and Observational Data , 1995 .

[7]  Mohammed Fadhil Dulaimi,et al.  The factors influencing bid mark-up decisions of large- and medium-size contractors in Singapore , 2002 .

[8]  Mohammed Wanous,et al.  To bid or not to bid: a parametric solution , 2000 .

[9]  Daniel King,et al.  Risk and Need-for-Work Premiums in Contractor Bidding , 1991 .

[10]  Alberto Fernández,et al.  Causes of Subcontracting: Evidence from Panel Data on Construction Firms , 2000 .

[11]  Pradeep K. Chintagunta,et al.  Investigating Heterogeneity in Brand Preferences in Logit Models for Panel Data , 1991 .

[12]  Irtishad Ahmad,et al.  Questionnaire Survey on Bidding in Construction , 1988 .

[13]  S. Menard Applied Logistic Regression Analysis , 1996 .

[14]  Patricia M. Hillebrandt,et al.  The Construction Company in and out of Recession , 1995 .

[15]  Martin Skitmore,et al.  Testing Vickery's revenue equivalence theory in construction auctions , 2006 .

[16]  Frank Harris and Ronald McCaffer Modern Construction Management , 1977 .

[17]  Martin Skitmore,et al.  The effect of client and type and size of construction work on a contractor's bidding strategy , 2001 .

[18]  R. Fellows,et al.  An examination of the importance of resource considerations when contractors make project selection decisions , 1992 .

[19]  Cheng Hsiao,et al.  Analysis of Panel Data , 1987 .

[20]  A. Raftery Bayesian Model Selection in Social Research , 1995 .

[21]  Ching-Torng Lin,et al.  Bid/no-bid decision-making – a fuzzy linguistic approach , 2004 .

[22]  Richard de Neufville,et al.  Bidding Models: Effects of Bidders' Risk Aversion , 1977 .

[23]  J. A. Calvin Regression Models for Categorical and Limited Dependent Variables , 1998 .

[24]  Irtishad Ahmad Decision‐Support System for Modeling Bid/No‐Bid Decision Problem , 1990 .

[25]  Wai-ki Fu The effect of experience in construction contract bidding , 2004 .

[26]  David Lowe,et al.  A logistic regression approach to modelling the contractor's decision to bid , 2004 .

[27]  W. Zikmund Business Research Methods , 1984 .

[28]  Dipak C. Jain,et al.  A Random-Coefficients Logit Brand-Choice Model Applied to Panel Data , 1994 .

[29]  Seung Heon Han,et al.  Contractor’s Risk Attitudes in the Selection of International Construction Projects , 2005 .

[30]  A. Kadefors Institutions in building projects: Implications for flexibility and change , 1995 .

[31]  Mohammed Wanous,et al.  A neural network bid/no bid model: the case for contractors in Syria , 2003 .

[32]  Peter E. Rossi,et al.  A Bayesian Approach to Estimating Household Parameters , 1993 .

[33]  Martin Skitmore,et al.  Estimating processes of smaller builders , 1994 .

[34]  H P Lo,et al.  A LATENT CLASS MODEL APPLIED TO STATED PREFERENCE DATA. IN: TRAVEL BEHAVIOUR RESEARCH. THE LEADING EDGE , 2001 .