Acceptance Model of Cloud-Based Disaster Recovery Services with Artificial Intelligence

Kee, Kah Song (2023) Acceptance Model of Cloud-Based Disaster Recovery Services with Artificial Intelligence. Doctoral thesis, Asia e University.

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Abstract

This study highlights the critical role of IT systems in businesses and the challenges associated with managing IT risk. Companies invest substantial resources to ensure uninterrupted operations and avoid service disruptions. IT Disaster Recovery Plans (ITDRP) are essential for outlining a company's response to disruptive events, and their effectiveness is influenced by the plan's acceptance and perception within the company. Seamless availability of modern IT systems is crucial to prevent financial losses and missed revenue opportunities. Creating a disaster recovery plan is essential but can be challenging due to factors like lack of understanding, resources, and knowledge about potential obstacles. Investigating the acceptance of a recovery plan is crucial, particularly for successful recoveries. The study's main objectives include evaluating Cloud-based disaster recovery services, integrating Artificial Intelligence (AI) into Business Continuity Management (BCM) processes, and assessing the model with the introduction of mediating and moderating factors. The research design follows the UTAUT model and employs quantitative methods, utilizing cross-sectional surveys to gather data from a specific target population at a given time. Purposive sampling is used to select participants with specific traits or knowledge for valuable insights, and data analysis from 100 respondents is conducted using SmartPLS 3.0. The various determinants, such as Performance Expectancy (PE), Social Influence (SI), Facilitating Conditions (FC), Behavioural Intention (BI), and Trust (TR), that impact the acceptance of an ITDRP were studied. Integration of Cloud-based recovery services and AI into BCM processes enhances ITDRP effectiveness. Trust, mediated through intermediaries, also plays a crucial role in shaping stakeholder perception and acceptance of the plan. Ultimately, an effective plan that is user-friendly, endorsed by key individuals, supported by proper infrastructure, and trusted by stakeholders generates enthusiasm for its use. The research introduced a new variable, Trust, offering a fresh perspective on stakeholder responses to disaster recovery plans. Practical guidance is provided for companies, emphasizing the importance of trust in ensuring plan acceptance and implementation. This study has significant implications for both theory and practice in disaster recovery planning for IT systems.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	ITDRP, AI, BCM, UTAUT, SmartPLS 3.0, cloud-based disaster recovery
Divisions:	School of Graduate Studies
Depositing User:	Siti Nor Fairuz Rosaidee
Date Deposited:	26 Dec 2024 07:42
Last Modified:	26 Dec 2024 07:42
URI:	http://ur.aeu.edu.my/id/eprint/1241

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