The continued usage of artificial intelligence in the United Arab Emirates public sector organisations: An extended information system success model

Dahabreh, Fares (2023) The continued usage of artificial intelligence in the United Arab Emirates public sector organisations: An extended information system success model. Doctoral thesis, Northumbria University.

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Abstract

In the past years, government around the globe showed significant interest in Artificial Intelligence (AI) technologies, more governments are setting their AI related strategies and using Artificial Intelligence technologies separately or integrated with other technologies such as Internet of Things (IoT) or Big Data (BD) to enhance their citizens’ offering, or increase the efficiency of their processes. Nevertheless, empirical research on what determines successful Artificial Intelligence (AI) usage and usage continuance in public settings remains scarce, especially regarding the impact of organisational constructs on the intention to continue usage of Artificial Intelligence in Public Sector Organisations in the United Arab Emirates. Therefore, this study was conducted to offer a better understanding of the impact of various organisational and technological factors on Intention to continue using Artificial Intelligence (AI) in organisations in the Public Sector in the United Arab Emirates.

This study tests the constructs identified from the updated Delone & McLean Information System Success Model (2013) and Technology-Organisation-Environment (T.O.E.) Framework and their impact on the successful usage and intention to continue usage of Artificial Intelligence in the Public Sector organisations in the United Arab Emirates. This was conducted through reviewing the existing literature in AI technologies and IS acceptance theories, which led to the introduction of a hybrid model from both the Delone & McLean Information Success Model (2013) and the Technology-Organisation-Environment Framework (TOE) with seven proposed constructs. A survey approach has been followed to collect primary data from 223 participants who use AI technologies in their respective federal and local public sector organisations. Structural Equation Modelling (SEM) has been used to test the conceptual model to measure the relationships impact significance of identified variables. The analysis of the data revealed that all seven constructs in the Delone & McLean Information Success Model and TOE framework hybrid model are accepted. The tested model showed moderate to high positive statistically significant correlations with intentions to continue usage of AI technologies. The results of the study revealed that Organisational Performance has a strong and positive significance impact on In Intentions to Continue Usage of AI technologies. In addition to that, analysis revealed that Organisational Culture and Digital Organisational Culture can be added to the model, as the results indicated that Organisational Culture has a strong and positive impact on Digital Organisational Culture. Moreover, the study demonstrates the importance of culture in public sector. When comparing impact significance, the study showed that Actual Usage of AI systems is positively impacted by the two variables; System Quality and Digital Organisational Culture, nevertheless Digital Organisational Culture has greater positive impact than System Quality. Moreover, Organisational Culture and Data Management both have positive impact on System Quality and Digital Organisational Culture, but Organisational Culture has greater positive impact on System Quality and Digital Organisational Culture more than the positive impact of Data Management on System Quality and Digital Organisational Culture.

This study makes important theoretical contributions to both Delone & McLean Information Success Model (2013) and the Technology-Organisation-Environment Framework by providing a novel framework and model that integrates key concepts and mechanisms from both theories, which enables a more comprehensive and nuanced understanding of the research of interest. Specifically, the model developed in this study enhances our understanding of the complex interplay between various cognitive, affective, and behavioral factors that influence the outcomes predicted by these theories, and sheds new light on the underlying processes and mechanisms that drive these effects. Moreover, this research has several managerial contributions and implications, provides insights for Public Sector Organisations to understand the factors affecting AI systems usage success, which will help them in prioritizing and utilizing their resources more effectively. A new conceptual model was tested and validated which would help Directors, ICT specialists and programmers, and data scientists in identifying new ways to facilitate AI technologies adoption and usage. In addition, the study highlighted the importance of organisational culture in the usage of AI related technologies.

Thus, this research through the introduced model may enhance the ability of public sector organisations in the United Arab Emirates to better manage data, and the quality of the AI systems used, in addition to instilling a corporate culture and digital organisational culture that would enhance the actual usage of AI system which would enhance the organisational performance, and accordingly influence the organisation’s intention decision to continue using AI technologies.

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