DEVELOPMENT OF RISK ALLOCATION MODEL FOR PUBLIC – PRIVATE PARTNERSHIP (PPP) - PROCURED MASS HOUSING PROJECTS IN ABUJA, NIGERIA

Abstract

Inadequate supply of decent and affordable houses for urban low-income earners has constituted a challenging situation for both developing and developed economies. The housing crisis that accounts for about 23 million deficits has compelled the Nigeria Federal Government to collaborate with the organized private sector (OPS) in executing mass housing through the PublicPrivate Partnership (PPP) arrangement. PPP Projects are not immune to risk; hence, PPP-procured mass housing projects (MHP) has plethora of risk which calls for the effective allocation of the risks between the government and the OPS in ensuring the success of the scheme. The aim of the study is to develop a risk allocation model that can guide decision makers in PPP-procured MHP in Nigeria. The study adopted mixed-method design based on quantitative and qualitative approaches. The study was also piloted through Delphi Survey method in which the risks peculiar to PPP-procured MHP were established. Data were collected through Questionnaires administration on identified PPP-procured MHP stakeholders in Abuja and In-depth interviews were also conducted on some selected stakeholders on the three case studies in the area. Descriptive and inferential statistics were employed to analyze the data such as mean index scores, standard deviation, Kruskas-Wallis, factor analysis and Partial least square Structural Equation Modeling (PLS-SEM). Fuzzy synthetic Evaluation method were subsequently applied to model the effect of risks, the critical risk assessment in the sector and also to model the risk allocation. The mean index scores was normalized and shows that out of the 63 identified risk factors; only 31 were critical risk factors (CRFs) and these were grouped into five critical risk factor groups (CRFGs) according to their relationship to the main group. The Fuzzy risk assessment model (FRAM) shows that the overall risk level (ORL) of PPP-procured MHP is high with index of 5.65 on a scale of 7 indicating that these projects are risky investment to the government and the OPS. Overall Financial and Macroeconomics risk group (CRFG 1) with 5.69 indices contributes most significantly to the ORL of PPP-procured MHP in Nigeria. The study also assessed the effect of risk allocation on PPP-procured MHP delivery; the effects of Risk Allocation Criteria (RAC) and Risk Severity on Project delivery indexes were explored using PLS-SEM technique. The study thus shows that observing the risk allocation criteria does not affect the delivery of PPP mass housing projects but the identified critical risk factors determine the risk allocation criteria to be adopted in the delivery of PPP-procured mass housing projects. On risk allocation modeling, the developed Fuzzy Risk Allocation Decision Model (FRADM) for PPP-procured MHP deals with the imprecise and subjective nature of risk allocation and it handles the simultaneous consideration of multiple risk allocation criteria and multiple decision-makers. The model is a five-tier system in which the output of the preceding steps are fed into subsequent steps to handle the problem of imprecision and subjectivity. The output variables of the model are the risk allocation proportions between the government and the OPS according to their risk carrying capabilities to control and manage an evaluated risk factor. Part of the conclusion of the research was that no particular risk factor was wholly allocated to either the government or the OPS based on the FRADM hence the government and the OPS need to come to the round table and discuss the risk factors and their severities whenever new PPP MHP is to begin in ensuring the sustainability of the scheme. The study recommends that stakeholders should understand their risk management capabilities before allocating a particular risk factor and that adequate financial resource should be made available before government embarks on the procurement of PPP-procured mass housing scheme/projects.