Examination the Usefulness of Selected Classification Methods in the Pre-Qualification of Construction Contractors

Examination the Usefulness of Selected Classification Methods in the Pre-Qualification of Construction Contractors

Paweł Błaszczyk (Institute of Mathematics, University of Silesia, Katowice, Poland) and Tomasz Błaszczyk (Department of Operational Research, University of Economics in Katowice, Katowice, Poland)
DOI: 10.4018/ijitpm.2017010102
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Abstract

For most of projects, including major infrastructure enterprises a key success factor is an appropriately selected general contractor. In addition to technical and organizational criteria the assessment of its financial capacity is strongly important to provide liquidity to the cash flows of the project. Unfortunately, the practical experience of the construction market during the economic downturn shows that many projects have been delayed or suspended as a result of the bankruptcy of general contractors. The purpose of this paper is to present the results of studies on the use of Partial Least Square, Fisher Linear Discriminant, Support Vector Machine methods, and the authors' proprietary approach to the Extraction by Applying Weighted Criterion of Difference Scatter Matrices (EWCDSM) for the pre-qualification of potential contractors. The study included an ex post evaluation of selected large construction companies, operated in Poland by reference the fact of their bankruptcy or maintain the market to historical financial data for the prior year period. Then, for the same set of data the authors performed the identification of companies at risk of bankruptcy. The results obtained are confronted with the actual condition of the surveyed companies. Proposed operating models have been validated on publicly available financial data of construction companies listed on the Polish Stock Exchange.
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Introduction

During the economic downturn a growing number of bankrupted companies is observed. It’s reason due to the non-revenue generating contracts with the need to incur the fixed costs of maintaining capacity, delays in payment for loss of liquidity and insolvency of customers, resulting in a lack of payment for the order or the products delivered. Failure to pay for the contractor is in the best case, the need for temporary financing funds from other sources, at the expense of the use of debt financing or destination of their income from other contracts to cover costs already incurred manufacture of a product or completion of the service that is not covered by the customer. On the other hand, the project owner or the general contractor is exposed to the risk of bankruptcy of its subcontractors. In this case, the money involved in the project in the form of an advance or partial payments made yet are usually very difficult to recover. Depending on the legal structure of the contract, owner of the project may also be forced to settle certain liabilities incurred by the bankrupt contractor for the project. Another problem is the suspension of the work on the project, resulting in the need to secure already realized the extent the selection of a new contractor, sometimes changing technology and project parameters what, amongst others could be the critical factor of project delays (see. Motaleb & Kishk, 2013).

An advanced multi-criteria approach is appropriate in project management for not only human resources selection (Hajeeh, 2013).

The problem of contractor pre-selection has been recognized and supported by optimization methods based on different classes of models. El-Sawalhi made a review (El-Sawalhi, Eaton & Rustom R., 2007). and pointed out the following:

  • Dimensional Weighting Aggregation (DWA)

  • Knowledge Based System (KBS),

  • Multi-attriubute Analysis (MAA),

  • Fuzzy set Pre-qualification,

  • PERT model for contractor pre-qualifiaction,

  • Analytical Hierarchy Process (AHP),

  • Multi-attribute utility,

  • Case-based reasoning,

  • Artificial Neural Networks (ANN).

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