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Modelling optimal risk allocation in PPP projects using artificial neural networks

journal contribution
posted on 2011-07-01, 00:00 authored by Xiaohua Jin, G Zhang
This paper aims to establish, train, validate, and test artificial neural network (ANN) models for modelling risk allocation decision-making process in public-private partnership (PPP) projects, mainly drawing upon transaction cost economics. An industry-wide questionnaire survey was conducted to examine the risk allocation practice in PPP projects and collect the data for training the ANN models. The training and evaluation results, when compared with those of using traditional MLR modelling technique, show that the ANN models are satisfactory for modelling risk allocation decision-making process. The empirical evidence further verifies that it is appropriate to utilize transaction cost economics to interpret risk allocation decision-making process. It is recommended that, in addition to partners' risk management mechanism maturity level, decision-makers, both from public and private sectors, should also seriously consider influential factors including partner's risk management routines, partners' cooperation history, partners' risk management commitment, and risk management environmental uncertainty. All these factors influence the formation of optimal risk allocation strategies, either by their individual or interacting effects.

History

Journal

International journal of project management

Volume

29

Issue

5

Pagination

591 - 603

Publisher

Pergamon

Location

Oxford, United Kingdom

ISSN

0263-7863

eISSN

1873-4634

Language

eng

Publication classification

C1 Refereed article in a scholarly journal; C Journal article

Copyright notice

2011, Pergamon

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