The oil refining industry has a fundamental role, due to the fact that this industry plays an integral role in international trade, assists in catering the global demand for energy, contributes to energy security and encourages economic development in countries. Despite its integral nature, the threats the oil refining industry is imposing on the environment and the community cannot be overlooked. In order to maintain its position in the market and to be able to meet the competitive needs of the international market, the oil refining industry should work to find balance in its economic, environmental and social responsibilities. It is significant to note that doing this poses a challenge since each dimension requires efficient monitoring and management. This necessitates adopting a performance measurement system that can assist in tracking and evaluating companies’ performance from a sustainability perspective. This research has included reviews of past studies and conducted exploratory interviews in order to gain in-depth insight from both academics and industry practitioners with regards to performance measurement models of sustainability adopted for the oil refining sector. This leads to the realization that there are insufficient existing performance measurement models capable of successfully integrating sustainability alongside the primary properties of the oil refining sector and addressing the global challenges and trends affecting the industry.As a result, this research aims to address the identified gaps and limitations in the previous studies. This will be achieved through developing a performance measurement model that is comprehensive so as to be capable of integrating the three pillars of sustainability, incorporating the oil refining properties and addressing the current global challenges affecting the industry.The thesis has incorporated mixed methods in gathering the data and 4 phases were incorporated. The first phase includes conducting a critical review and exploratory interview to identify the research gap from the academic and practitioners’ perspectives. The second phase includes an extended literature review to develop a performance measurement theoretical model from a sustainability perspective and developing a theoretical framework which also sets out procedures, barriers, benefits and drawbacks. Next, the third phase includes an empirical study on the Egyptian oil refining sector through a focus group questionnaire which seeks to demonstrate the applicability of the proposed model. Finally, the fourth phase includes a survey, distributed globally, to test the applicability of the developed model and gather opinions on a global scale.The findings have shown that the existing models lacked the ability to provide a thorough assessment of the performance for oil refining companies. In contrast, the proposed model is expected to have the capability to be able to evaluate the performance of oil refining companies in a comprehensive way. This is achieved by incorporating a broader set of KPIs that align with sustainability goals when compared to existing models, which more typically reflect oil refining characteristics and addresses the current global challenges. One of the strengths of this study is the identification of limitations in the existing models. Extending from this, this study was able to provide comprehensive measurable indicators that have the ability to meet the sustainability goals and to meet the current global challenges. Furthermore, from a practical perspective, it is also expected to offer guidance to oil refining companies with regard to evaluating their sustainability performance and suggesting a roadmap for implementing the proposed model. Overall, the proposed model has the potential to assist oil refining companies in assessing their sustainability performance and providing recommendations for improvements. This will, in turn, reinforce companies’ market presence and enable them to remain competitive within the complex and changing global environment.
| Date of Award | 26 Feb 2024 |
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| Original language | English |
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| Supervisor | Abhijit Sharma (Main Supervisor) & Jason Wang (Co-Supervisor) |
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