Factors Influencing Adoption of Digital Twin Advanced Technologies for Smart City Development: Evidence from Malaysia
Author(s): |
Ahsan Waqar
Idris Othman Hamad Almujibah Muhammad Basit Khan Saleh Alotaibi Adil A. M. Elhassan |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 26 February 2023, n. 3, v. 13 |
Page(s): | 775 |
DOI: | 10.3390/buildings13030775 |
Abstract: |
Digital Twin Technology (DTT) has gained significant attention as a vital technology for the efficient management of smart cities. However, its successful implementation in developing countries is often hindered by several barriers. Despite limited research available on smart city development in Malaysia, there is a need to investigate the possible challenges that could affect the effective implementation of DTT in the country. This study employs a mixed methodology research design, comprising an interview, a pilot survey, and the main survey. Firstly, we identified barriers reported in the literature and excluded insignificant factors through interviews. Next, we conducted an Exploratory Factor Analysis (EFA) on the pilot survey results to further refine the factors. Finally, we performed a Structural Equation Modeling (SEM) analysis on the main survey data to develop a model that identifies barriers to DTT implementation in smart city development in Malaysia. Our findings suggest the presence of 13 highly significant barriers, which are divided into four formative constructs. We found that personalization barriers are highly crucial, while operational barriers were less important for DTT implementation in smart city development in Malaysia. |
Copyright: | © 2023 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10712369 - Published on:
21/03/2023 - Last updated on:
10/05/2023