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A contractor's analysis of the likelihood of payment of claims

A contractor's analysis of the likelihood of payment of claims Purpose – The purpose of this paper is to present an original model, and one of practical use, for a contractor's internal analysis of the likelihood of late and incomplete payments, in an uncertain payment environment. Payments typically dominate the thinking of a contractor and the way a contractor operates. The model applies equally to subcontractors, suppliers and consultants. Design/methodology/approach – The model is based on Markov chains, specially adapted to the problem, where the states are defined as the period of time by which the payment is overdue. In addition, there are special states corresponding to claims that have been paid, and those that need resolution. Transitions between states reflect the payment characteristics on the project (which itself depends on the type of project and the owner‐contractor relationship). Findings – Real project data confirm the validity of the model. Output from the model can be shown to agree with actual contractor payment data. The output is in terms of probability of payment by a certain date, and mean time to payment for amounts owing. Such information assists the contractor in its financial management practices. Practical implications – The paper gives a summary approach for contractors. A strength and paradox of the model is its simplicity in usage, yet it overlies hidden more extensive mathematics, which might generally not be known or is necessary to be known to contractors. The model analysis feeds into the contractor's cash flow calculations, overall project risk analysis and accounting procedures. Originality/value – The paper represents an original contribution to the modelling and analysis of contractor payments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Financial Management of Property and Construction Emerald Publishing

A contractor's analysis of the likelihood of payment of claims

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References (53)

Publisher
Emerald Publishing
Copyright
Copyright © 2010 Emerald Group Publishing Limited. All rights reserved.
ISSN
1366-4387
DOI
10.1108/13664381011063412
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to present an original model, and one of practical use, for a contractor's internal analysis of the likelihood of late and incomplete payments, in an uncertain payment environment. Payments typically dominate the thinking of a contractor and the way a contractor operates. The model applies equally to subcontractors, suppliers and consultants. Design/methodology/approach – The model is based on Markov chains, specially adapted to the problem, where the states are defined as the period of time by which the payment is overdue. In addition, there are special states corresponding to claims that have been paid, and those that need resolution. Transitions between states reflect the payment characteristics on the project (which itself depends on the type of project and the owner‐contractor relationship). Findings – Real project data confirm the validity of the model. Output from the model can be shown to agree with actual contractor payment data. The output is in terms of probability of payment by a certain date, and mean time to payment for amounts owing. Such information assists the contractor in its financial management practices. Practical implications – The paper gives a summary approach for contractors. A strength and paradox of the model is its simplicity in usage, yet it overlies hidden more extensive mathematics, which might generally not be known or is necessary to be known to contractors. The model analysis feeds into the contractor's cash flow calculations, overall project risk analysis and accounting procedures. Originality/value – The paper represents an original contribution to the modelling and analysis of contractor payments.

Journal

Journal of Financial Management of Property and ConstructionEmerald Publishing

Published: Aug 3, 2010

Keywords: Contracting out; Payments; Modelling

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