Project selection and prioritisation: A case of Power Generation in Zimbabwe.

Muringa, Simbarashe (2015) Project selection and prioritisation: A case of Power Generation in Zimbabwe. UNSPECIFIED thesis, UNSPECIFIED.

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Official URL: http://hdl.handle.net/11408/2382

Abstract

This study investigates the various decision methods and models used by the Government of Zimbabwe in the process of identifying and prioritising national power generation projects for capitalisation purposes. The selection and prioritisation process was considered to be central to the pooling and channelling of resources towards optimal electricity generation in the country in the context of ZIMASSET power projects. The study’s main objective was to address the identified disconnection between the decision making process for approval of a power generation project as a “National Strategic Project” and its subsequent inadequate capitalisation which, in turn, inhibited timely successful execution and expected contribution to the national economy. The study combines interpretive and critical realism, supported by an inductive approach. The design was generally descriptive; although with influences of both the exploratory and explanatory researches. The study was largely qualitative and applied some quantitative aspects covered in the AHP Model. The study data was gathered using both primary and secondary data collection methods. Purposive judgmental sampling was done targeting officials in government institutions involved in the power generation projects. Twenty-six survey questionnaires were used as the main study instruments because the researcher only managed to conduct one interview out of the five that were planned. The study revealed that each government institution had its own perception of what happens in the selection and prioritisation process; resulting in fragmented rather than standard, centralised and transparent processes. It was also noted that the various methods in use were not always based on the multi-criteria ranking methodology; hence there was no standard criteria framework. In terms of policy, the study revealed that the Indigenisation and Empowerment Act (Chapter 14:33; 2007) and its associated regulations; and the National Investment Policy of Zimbabwe were being used to support the National Energy Policy (2012). However, there was need for policy awareness, clarity and consistency. Further, Zimbabwe was yet to come up with a comprehensive PPP policy framework and legislation. Sources of funding remained a major challenge; with FDI inflows subdued for various reasons. The study, therefore, recommended that the Government of Zimbabwe: uses a centrally maintained transparent system to select and prioritize public power generation projects; should develop appropriate and cohesive policies that facilitate attraction of FDI and private sector participation in power generation projects; expedite the enactment of the PPP Act on the basis of the Joint Venture Bill (aka Public-Private Partnership Bill); adopt the AHP Model in all government institutions as a common user MCDA tool for selection and prioritisation of power generation projects. The AHP method has no bias associated with the use of other MCDA methods. Further studies, as case studies, were suggested in order to allow for assessment of the AHP application in determining preference scores for actual project alternatives; subject to availability of specific rating information for each alternative, within an identified power project portfolio. The study also suggested further research into the actual contribution made by the current partners in PPP arrangements and licensed IPPs in enhancing the country’s power generation capacity.

Item Type: Thesis (UNSPECIFIED)
Uncontrolled Keywords: Project selection.,Project prioritisation.,Power Generation in Zimbabwe.
Divisions: Universities > State Universities > Midlands State University
Depositing User: Mr. Edmore Sibanda
Date Deposited: 05 Jul 2017 22:40
Last Modified: 05 Jul 2017 22:40
URI: http://researchdatabase.ac.zw/id/eprint/4776

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