Implementing citizen centric technology in developing smart cities: A model for predicting the acceptance of urban technologies

Abstract

Local urban identity, culture and knowledge ecosystems continue to shape innovative capacity and technological acceptance despite global exchange in talent, trade and technology. This has important implications for the development and implementation of future smart cities. The last two decades of smart city research has presented smart cities as a generic, universal aspiration without taking into consideration such local cultural differences. Future smart cities have several tasks ahead of them. The first is selecting culturally appropriate technologies from the vast array of global technologies now on offer. The second task is adapting such technology and the third task is in managing the acceptance of such technology. The above process is not linear but must be iterative, with technology acceptance considered simultaneously alongside the selection and adoption of such technologies. This study integrates the substantial literature on Technology Acceptance Modelling into the smart city discourse to begin to address this need. It also further develops our understanding of technology acceptance using the Structural Equation Modelling Method. A new synthetic model is proposed consisting of twelve factors, which have been selected based on a targeted literature review. A survey-based method was used to develop and cross-validate the model sampling a diverse population from various Iranian cities. The result of the above process is a new model named the Urban Services Technology Acceptance Model (USTAM).The validated model includes key factors related to technology such as Self-Efficacy, Operation, Work Facilitation, Relative Advantage and Compatibility. The USTAM is a useful tool for the prediction of technology acceptance in the implementation of smart cities. The final model is significant for various reasons. Firstly, it is significant for ensuring that selected technology is appropriate to local cultural contexts. Secondly it is significant to ensure that integration of technologies at metropolitan scales is managed effectively. The final significant reason is that it is well-suited to helping developing economies participate in the smart city boom in a resource efficient manner. The proposed model can potentially help cities achieve this by guiding them in the selection of appropriate technologies. The proposed model is developed with specific reference to Iran and Bangladesh. The authors suggest that the model is useful for cities of different cultural identities and characteristics, who wish to initiate their own distinctive smart city strategies.