Using an Extended Technology Acceptance Model to Predict Enterprise Architecture Adoption in Making Cities Smarter

Abstract

Presently cities are undergoing changes and transformations due to the adoption of information and communications technology. Enterprise Architecture (EA) is one of the approaches adopted by practitioners and researchers to facilitate smart city development as it can enhance the effectiveness of cities’ digital resources and sustainability capabilities. But, despite several literature on EA, studies on the adoption of EA to improve the sustainability of cities are still at the early stage. Besides, there are fewer studies that provided evidence on the adoption of EA to make cities sustainable grounded on established theoretical models and quantitative data. Therefore, this study aims to provide an understanding on the adoption of EA by different practitioners involved in a smart city project. Knowledge transfer and support services are integrated as new external variables needed to improve practitioners’ behavior intention and actual adoption of EA in making cities smarter. A model is developed grounded on an extension of Technology Acceptance Model (TAM), and data were collected via a cross-country survey. Partial least squares-structural equation modeling was employed to analyze the data. Findings from this study offer implications for research and practice and provide opportunities for future research.