The Influence of Predictive Technology on Business Sustainability in Oil and Gas Support Services Industry

Mohd Isnari, Idris (2023) The Influence of Predictive Technology on Business Sustainability in Oil and Gas Support Services Industry. Doctoral thesis, Asia e University.

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Abstract

This study focuses on the role of predictive technology in enhancing business sustainability within the oil and gas support service industry. The oil and gas industry is under increasing pressure to improve its environmental and social performance while maintaining profitability. Predictive technology, which involves the use of data analytics, artificial intelligence, and machine learning, has the potential to enhance business sustainability by improving operational efficiency, reducing costs, and minimizing environmental impacts. This study examines the imperatives of predictive technology adoption and implementation, as well as the challenges and opportunities associated with its use. A qualitative approach is used to investigate the use of predictive technology within a specific oil and gas support service company. Data were collected using semi-structured interviews and document analysis to meet the research objectives. Participants of this study were managers and technical experts from the oil and gas support services industry in several cities within Malaysia. The findings of the study indicate that the industry players perceived predictive technology can significantly improve business sustainability by several ways namely increase operational efficiency, cost savings, better asset management, better service to the customer, enable well-informed decision and better risk management. Despite some challenges the adopters believe that factors such as data quality and security, sound financial resources, skilled technical talent, government support, labour mobility and the growth of digital economy are enablers essential for successful adoption of predictive technology leading to business sustainability. Subsequently, the study reports the key elements of sustainable strategy with regard to implementing predictive technology that is collaborative partnerships, business scalability planning, talent management, leadership and change management as well as continuous monitoring and evaluation. This study proposes a framework of predictive technology implementation toward enhancing business sustainability from the oil and gas support services industry, which may assist industrialists in planning for effective technology adoption. The findings of this study limits generalizability to other business environment, which is common for qualitative research. While the study primarily focuses on an exploratory study of predictive technology's imperatives, further research could examine empirically to a larger sample, the factors found by this research.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Predictive technology, business sustainability, oil and gas sector, support service industry, artificial intelligence
Divisions:	School of Management
Depositing User:	Muhamad Aizat Nazmi Mohd Nor Hamin
Date Deposited:	02 Nov 2023 03:19
Last Modified:	02 Nov 2023 03:32
URI:	http://ur.aeu.edu.my/id/eprint/1116

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