Disruptive Technologies For Smart Cities’ Management

Dear Colleagues,

Cities will be revolutionized by new “smart” technologies enabling the transparent and efficient provision of government services, sustainability, and new administration methods (Sousa et al., 2022). Of particular interest are sensors, blockchains and big data processing, which have been made possible through artificial intelligence (AI) and have the potential to create tailor-made services for citizens (Allam and Dhunny, 2019; Secinaro et al. 2021a). This necessitates hybrid skills and integration, governance policies and transparency in the use of information (Secinaro et al., 2021b). The literature has demonstrated interesting initial results in increasing public energy sustainability (Chui et al., 2018), public safety (Srivastava et al., 2017), transport usability (Agarwal et al., 2015), air quality (Schürholz et al., 2020) and innovative dialogic approaches (Grossi et al., 2021).  Utilizing new technologies for smart cities’ management, such as artificial intelligence, big data and blockchains, is one of the main focuses of European and Italian recovery plans. This Special Issue aims to provide theoretical contributions, conceptual frameworks, measurement approaches and empirical evidence addressing research questions including (but not limited to):

• How can artificial intelligence transform cities into smart cities?
• How can technology increase the dialogic dimensions of cities and smart cities?
• What governance changes are required for the management of new technologies in smart cities?
• How can disruptive technologies foster city recovery?

References

Allam, Z., & Dhunny, Z. A. (2019). On big data, artificial intelligence and smart cities. Cities, 89, 80-91.

Agarwal, P. K., Gurjar, J., Agarwal, A. K., & Birla, R. (2015). Application of artificial intelligence for the development of intelligent transport system in smart cities. International Journal of Transportation Engineering and Traffic System, 1(2), 20-30.

Chui, K. T., Lytras, M. D., & Visvizi, A. (2018). Energy sustainability in smart cities: Artificial intelligence, smart monitoring, and optimization of energy consumption. Energies, 11(11), 2869.

Grossi, G., Biancone, P. P., Secinaro, S., & Brescia, V. (2021). Dialogic accounting through popular reporting and digital platforms. Meditari Accountancy Research.

Schürholz, D., Kubler, S., & Zaslavsky, A. (2020). Artificial intelligence-enabled context-aware air quality prediction for smart cities. Journal of Cleaner Production, 271, 121941.

Secinaro, S., Dal Mas, F., Brescia, V., & Calandra, D. (2021a). Blockchain in the accounting, auditing and accountability fields: a bibliometric and coding analysis. Accounting, Auditing & Accountability Journal.

Secinaro, S., Brescia, V., Calandra, D., & Biancone, P. (2021b). Towards a hybrid model for the management of smart city initiatives. Cities, 116, 103278.

Sousa M.J., Dal Mas F., Osório de Barros G., Tavares N. (2022) Artificial Intelligence: Technologies, Applications, and Policy Perspectives. Insights from Portugal. In: Jeyanthi P.M., Choudhury T., Hack-Polay D., Singh T.P., Abujar S. (eds) Decision Intelligence Analytics and the Implementation of Strategic Business Management. EAI/Springer Innovations in Communication and Computing. Springer, Cham.

Srivastava, S., Bisht, A., & Narayan, N. (2017). Safety and security in smart cities using artificial intelligence—A review. In 2017 7th International Conference on Cloud Computing, Data Science & Engineering-Confluence (pp. 130-133). IEEE.

Prof. Dr. Silvana Secinaro
Dr. Francesca Dal Mas
Dr. Maria José Sousa
Dr. Davide Calandra
Guest Editors

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• smart cities
• accountability
• blockchain
• artificial Intelligence
• dialogic accounting
• sustainability