A multi-attribute decision making methodology for selecting new R&D projects portfolio with a case study of Saudi oil refining industry
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[Thesis]
First Statement of Responsibility
Kabli, Mohammad Reda
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
University of Nottingham
Date of Publication, Distribution, etc.
2009
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
Thesis (Ph.D.)
Text preceding or following the note
2009
SUMMARY OR ABSTRACT
Text of Note
Energy is a resource of fundamental importance and if there is one thing that the world is going to need more in the future, it's energy. Increased energy demand is a major factor for the energy industry to invest in innovative technologies by developing processes and products that deliver improved efficiency and environmental performance. With oil continues to satisfy a major part of the energy needs, it is important for oil companies to invest wisely in Research and Development (R&D) projects. Literature is full of methods that address the problem of R&D portfolio selection. Despite their availability, R&D portfolio selection methods are not used widely. This is due to lacking several issues identified by researchers and practitioners. As a result, R&D portfolio selection is still an important area of concern. This research proposes a multi-attribute decision making methodology for selecting R&D portfolios with a case study of implementation of the methodology in the Saudi oil refining industry. Driven by the research question and some gaps identified in the related literature review, the methodology has been modified and improved. The methodology includes methods and techniques that aim to give insights to decision makers to evaluate individual projects and select the R&D portfolio. The methodology is divided into three stages with different steps in each stage by combining and modifying two well-known multi-attribute decision making methods: the Simple Multi-Attribute Rating Technique (SMART) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The case study describes further methods such as Integer Linear Programming (ILP) and Monte Carlo simulation for generating data to test the validation and operationality of the methodology. It is designed in a step-by-step, easy to apply way and considers the decision making type in a national oil company. It includes the preferences of the decision makers and takes into consideration the multiple, monetary and non- monetary, attributes that ought to be considered to satisfy not only the objectives of the Saudi national company (Aramco), but the strategic goals of the Saudi government as well.