Governments of developed and developing countries alike are unable to fund the construction and maintenance of vital physical infrastructure such as roads, railways, water and wastewater treatment plants, and power plants. Thus, they are more and more turning to the private sector as a source of finance through procurement methods such as concession contracts. The most common form of concession contract is the Build-Operate-Transfer (BOT) contract, where a government (Principal) grants a private sector company (Promoter) a concession to build, finance, operate and maintain a facility and collect revenue over the concession period before finally transferring the facility, at no cost to the Principal, as a fully operational facility. Theoretically speaking, these projects present a win-win-win solution for the community as well as both private and public sector participants. However, with the opportunity for private sector companies to earn higher returns comes greater risk. This is despite the fact that concession projects theoretically present a win-win-win solution to the problem of infrastructure provision. Unfortunately, this has not been the case in a number of countries including Australia. Private sector participants have admitted that there are problems that must be addressed to improve the process. Indeed they have attributed the underperformance of concession projects to the inability of both project Principals and Promoters to predict the impact of all financial and non-financial (risk) factors associated with concession project investments (CPIs) and to negotiate contracts to allow for these factors. Non-financial project aspects, such as social, environmental, political, legal and market share factors, are deemed to be important; but these aspects would usually be considered to lie outside the normal appraisal process. To allow for the effects of such qualitative aspects, the majority of Principal or promoting organisations resort to estimating the necessary money contingencies without an appropriate quantification of the combined effects of financial and non-financial (risks and opportunities) factors. In extreme cases, neglect of non-financial aspects can cause the failure of a project despite very favourable financial components; or can even cause the failure to go-ahead with a project that may have been of great non-financial benefit due to its projected ordinary returns. Hence, non-financial aspects need careful analysis and understanding so that they can be assessed and properly managed. It is imperative that feasibility studies allow the promoting organisation to include a combination of financial factors and non-financial factors related to the economic environment, project complexity, innovation, market share, competition, and the national significance of the project investment. While much research has already focused on the classification of CPI non-financial (risk) factors, and the identification of interdependencies between risk factors on international projects, no attempt has yet been made to quantify these risk interdependencies. Building upon the literature, this thesis proposes a generic CPI risk factor framework (RFF) including important interdependencies, which were verified and quantified using input provided by practitioners and researchers conversant with risk profiles of international and/or concession construction projects. Decision Support Systems (DSSs) are systems designed to assist in the decision making process by providing all necessary information to the analyst. There are a number of DSSs that have been developed over recent years for the evaluation of high-risk construction project investments, such as CPIs, which incorporate the analysis of both financial and non-financial (risk) aspects of the investment. However, although these DSSs have been useful to practitioners and researchers alike, they have not offered a satisfactory solution to the modelling problem and are all limited in their practical application for various reasons. Thus, the construction industry lacks a DSS that is capable of evaluating and comparing several CPI options, taking into consideration both financial and non-financial aspects of an investment, as well as including the uncertainties commonly encountered at the feasibility stage of a project, in an efficient and effective manner. These two criteria, efficiency and effectiveness, are integral to the usefulness and overall acceptance of the developed DSS in industry. This thesis develops an effective and efficient DSS to evaluate and compare CPI opportunities at the feasibility stage. The novel DSS design is based upon a combination of: (1) the mathematical modelling technique and financial analysis model that captures the true degree of certainty surrounding the project; and (2) the decision making technique and RFF that most closely reproduces the complexity of CPI decisions. Overall, this thesis outlines the methodology followed in the development of the DSS – produced as a stand-alone software product – and demonstrates its capabilities through a verification and validation process using real-life CPI case studies.