Factors Influencing the Adoption and Implementation of Predictive Maintenance Technologies in Organizations
| dc.contributor.advisor | Dr Sa'ed Salhieh | |
| dc.contributor.author | Alnashwan, Mohammed | |
| dc.date.accessioned | 2023-10-24T12:25:13Z | |
| dc.date.available | 2023-10-24T12:25:13Z | |
| dc.date.issued | 2023-08 | |
| dc.description.abstract | Significant research has explored the numerous advantages of predictive maintenance technologies. In today's Industry 4.0 era, organizations, especially in the manufacturing sector, are increasingly adopting predictive maintenance practices and technologies to forecast equipment failure enabling them to proactive maintain manufacturing and processing tasks and activities. Predictive maintenance technologies enable organizations to meet their production costs as well as product quality and quantity objectives. Accordingly, studies have associated predictive maintenance technologies and practices with the capabilities of improving organizational performance in the economic, ecological/environmental, and social dimensions. However, despite the numerous advantages, many organizations have not leveraged these technologies due to various organizational, financial, and human-related barriers. As a result, drawing from relevant literature and the data from the Abu Dhabi National Oil Company (ADNOC), the study will explore the factors that influence the adoption of predictive maintenance technologies, the consequent impact on organizational performance and provide suggestions for businesses looking to adopt and use these technologies. In a questionnaire conducted with 108 respondents from different companies in the UAE, relevant insights are found pertaining to the factors that influence the adoption and implementation of predictive maintenance technologies in organizations. One of the most important factors reported by participants in this study is the user perception factor, which reflects important perceptions about the implementation of specific technologies to improve organizational performance. Another relevant factor discussed in the study is the job effectiveness factor. | |
| dc.identifier.other | 20000017 | |
| dc.identifier.uri | https://bspace.buid.ac.ae/handle/1234/2363 | |
| dc.language.iso | en | |
| dc.publisher | The British University in Dubai (BUiD) | |
| dc.subject | predictive maintenance technologies | |
| dc.subject | United Arab Emirates (UAE) | |
| dc.subject | organizational performance | |
| dc.subject | job effectiveness | |
| dc.title | Factors Influencing the Adoption and Implementation of Predictive Maintenance Technologies in Organizations | |
| dc.type | Dissertation |