Bibri, S. E. (2018). Transitioning from Smart Cities to Smarter Cities: The Future Potential of ICT of Pervasive Computing for Advancing Environmental Sustainability. Urban Book Series. https://doi.org/10.1007/978-3-319-73981-6_10
Bibri, S. E. (2021a). Data-driven smart sustainable cities of the future: urban computing and intelligence for strategic, short-term, and joined-up planning. Computational Urban Science, 1(1), 1–29. https://doi.org/10.1007/s43762-021-00008-9
Bibri, S. E. (2021b). The underlying components of data-driven smart sustainable cities of the future: a case study approach to an applied theoretical framework. European Journal of Futures Research, 9(1). https://doi.org/10.1186/s40309-021-00182-3
Bibri, S. E., & Krogstie, J. (2020). Data-Driven Smart Sustainable Cities of the Future : A Novel Model of Urbanism and Its Core Dimensions , Strategies , and Solutions. Journal of Futures Studies, 25(2), 77–94. https://doi.org/10.6531/JFS.202012
Branny, A., Møller, M. S., Korpilo, S., McPhearson, T., Gulsrud, N., Olafsson, A. S., … Andersson, E. (2022). Smarter greener cities through a social-ecological-technological systems approach. Current Opinion in Environmental Sustainability, 55, 1–11. https://doi.org/10.1016/j.cosust.2022.101168
Chao, K., Sarker, M. N. I., Ali, I., Firdaus, R. B. R., Azman, A., & Shaed, M. M. (2023). Big data-driven public health policy making: Potential for the healthcare industry. Heliyon, 9(9), e19681. https://doi.org/10.1016/j.heliyon.2023.e19681
Cheng, Z., Wang, L., & Zhang, Y. (2022). Does smart city policy promote urban green and low-carbon development? Journal of Cleaner Production, 379(P1), 134780. https://doi.org/10.1016/j.jclepro.2022.134780
Cugurullo, F. (2018). Exposing smart cities and eco-cities: Frankenstein urbanism and the sustainability challenges of the experimental city. Environment and Planning A: Economy and Space, 50(1), 73–92. https://doi.org/10.1177/0308518X17738535
D’Amico, G., Taddeo, R., Shi, L., Yigitcanlar, T., & Ioppolo, G. (2020). Ecological indicators of smart urban metabolism: A review of the literature on international standards. Ecological Indicators, 118(August). https://doi.org/10.1016/j.ecolind.2020.106808
Dong, F., Li, Y., Li, K., Zhu, J., & Zheng, L. (2022). Can smart city construction improve urban ecological total factor energy efficiency in China? Fresh evidence from generalized synthetic control method. Energy, 241, 122909. https://doi.org/10.1016/j.energy.2021.122909
Dunlap, A. (2023). The green economy as counterinsurgency, or the ontological power affirming permanent ecological catastrophe. Environmental Science and Policy, 139(October 2022), 39–50. https://doi.org/10.1016/j.envsci.2022.10.008
Engin, Z., van Dijk, J., Lan, T., Longley, P. A., Treleaven, P., Batty, M., & Penn, A. (2020a). Data-driven urban management: Mapping the landscape. Journal of Urban Management, 9(2), 140–150. https://doi.org/10.1016/j.jum.2019.12.001
Engin, Z., van Dijk, J., Lan, T., Longley, P. A., Treleaven, P., Batty, M., & Penn, A. (2020b). Data-driven urban management: Mapping the landscape. Journal of Urban Management, 9(2), 140–150. https://doi.org/10.1016/j.jum.2019.12.001
Galychyn, O., Fath, B. D., Shah, I. H., Buonocore, E., & Franzese, P. P. (2022). A multi-criteria framework for assessing urban socio-ecological systems: The emergy nexus of the urban economy and environment. Cleaner Environmental Systems, 5(December 2021), 100080. https://doi.org/10.1016/j.cesys.2022.100080
Geropanta, V., Karagianni, A., Mavroudi, S., & Parthenios, P. (2021). Exploring the relationship between the smart-sustainable city, well-being, and urban planning: An analysis of current approaches in Europe. Smart Cities and the un SDGs. Elsevier Inc. https://doi.org/10.1016/b978-0-323-85151-0.00010-5
Kremer, P., Haase, A., & Haase, D. (2019). The future of urban sustainability: Smart, efficient, green or just? Introduction to the special issue. Sustainable Cities and Society, 51(July). https://doi.org/10.1016/j.scs.2019.101761
Kutty, A. A., Wakjira, T. G., Kucukvar, M., Abdella, G. M., & Onat, N. C. (2022). Urban resilience and livability performance of European smart cities: A novel machine learning approach. Journal of Cleaner Production, 378(November 2021), 134203. https://doi.org/10.1016/j.jclepro.2022.134203
Li, X., Ma, C., & Lv, Y. (2022). Environmental Cost Control of Manufacturing Enterprises via Machine Learning under Data Warehouse. Sustainability, 14(18), 11571. https://doi.org/10.3390/su141811571
Liu, W., Wei, W., Yan, X., Dong, D., & Chen, Z. (2020). Sustainability risk management in a smart logistics ecological chain: An evaluation framework based on social network analysis. Journal of Cleaner Production, 276, 124189. https://doi.org/10.1016/j.jclepro.2020.124189
Lv, Y., Ma, C., Li, X., & Wu, M. (2021). Big data driven COVID-19 pandemic crisis management: Potential approach for global health. Archives of Medical Science, 17(3), 829–837. https://doi.org/10.5114/aoms/133522
Lv, Y., Ma, C., Wu, M., Li, X., & Hao, X. (2022). Assessment of Preschool’s Inclusive Participation in Social Responsibility Program Under Institutional Pressure: Evidence From China. Frontiers in Psychology, 13(March). https://doi.org/10.3389/fpsyg.2022.810719
Lv, Y., Wu, M., Ma, C., Hao, X., & Zeng, X. (2022). Assessment of the status quo of social responsibility performance of inclusive kindergartens: Evidence from China. PloS One, 17(11), e0272742. https://doi.org/10.1371/journal.pone.0272742
Ma, C., & Ding, L. (2020a). A research on the seasonal difference of air pollution in Chengdu. IOP Conference Series: Earth and Environmental Science, 569(1). https://doi.org/10.1088/1755-1315/569/1/012071
Ma, C., & Ding, L. (2020b). Empirical research on influential factors of air pollution in Chinese provincial capital cities. IOP Conference Series: Earth and Environmental Science, 601(1), 012011. https://doi.org/10.1088/1755-1315/601/1/012011
Ma, C., & Qirui, C. (2023). Spatial-temporal evolution pattern and optimization path of family education policy: An LDA thematic model approach. Heliyon, 9(7), e17460. https://doi.org/10.1016/j.heliyon.2023.e17460
Ma, C., Wang, F., & Lv, Y. (2023). Teaching effects of using bullet-screen technology during classes on students’ learning: The mediating effect of perceived interactivity. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12054-3
Macke, J., Rubim Sarate, J. A., & de Atayde Moschen, S. (2019). Smart sustainable cities evaluation and sense of community. Journal of Cleaner Production, 239. https://doi.org/10.1016/j.jclepro.2019.118103
Mortaheb, R., & Jankowski, P. (2022). Smart city re-imagined: City planning and GeoAI in the age of big data. Journal of Urban Management, 12(1), 4–15. https://doi.org/10.1016/j.jum.2022.08.001
Sarker, M. N. I., Yang, B., Lv, Y., Huq, M. E., Kamruzzaman, M. M., M, M. K., … M, M. K. (2020). Climate Change Adaptation and Resilience through Big Data. International Journal of Advanced Computer Science and Applications, 11(3), 533–539. https://doi.org/10.14569/IJACSA.2020.0110368
Sato, A., Tani, S., Sasaki, K., Lin, W., Furuya, J., & Hirai, C. (2019). People-Centric City Enabled by Digital Platforms. Accelerating Social Innovation through Global Open Collaborative Creation. Retrieved from https://www.vitacastle.com/rev/archive/2019/r2019_04/pdf/P074-080_R4a05.pdf
Sheikh, H., Mitchell, P., & Foth, M. (2023). More-than-human smart urban governance: A research agenda. Digital Geography and Society, 4(October 2022), 100045. https://doi.org/10.1016/j.diggeo.2022.100045
Song, M., Tan, K. H., Wang, J., & Shen, Z. (2022). Modeling and evaluating economic and ecological operation efficiency of smart city pilots. Cities, 124(October 2021), 103575. https://doi.org/10.1016/j.cities.2022.103575
Wahab, A. M., & Mohamed, L. (2022). Making Kuantan As People Centric City: Enabling Data-Driven Decisions Via Smart City Implementation. Journal of Public Security and Safety, 13(1), 103–133.
Wang, J., Huang, K., Liu, H., & Yu, Y. (2022). The ecological boundary gap is gradually tightening in China’s megacities: Taking Beijing as a case. Science of the Total Environment, 806, 151484. https://doi.org/10.1016/j.scitotenv.2021.151484
Wu, D., Xie, Y., & Lyu, S. (2023). Disentangling the complex impacts of urban digital transformation and environmental pollution: Evidence from smart city pilots in China. Sustainable Cities and Society, 88(October 2022), 104266. https://doi.org/10.1016/j.scs.2022.104266
Wu, M., Hao, X., Wan, X., Ma, C., & Wu, Y. (2022). Opportunities and Challenges of Joint Training of Postgraduate Students by the University-Industry Collaboration Institutions in Big Data Era. ACM International Conference Proceeding Series, 194–198. https://doi.org/10.1145/3524383.3524431
Wu, M., Yan, B., Huang, Y., & Sarker, M. N. I. (2022). Big Data-Driven Urban Management: Potential for Urban Sustainability. Land, 11(5), 680. https://doi.org/10.3390/land11050680
Wu, Y. (2022). Ecological Smart City Construction Based on Ecological Economy and Network Governance. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/5682965
Xiao, Q., Zhao, L., Ji, L., & Xia, J. (2022). Ecological characteristics of distributed energy planning in ecological urban renewal design. Energy Reports, 8, 13037–13046. https://doi.org/10.1016/j.egyr.2022.09.114
Yao, Z. H. O. U., Jiang, C., & Shan-shan, F. E. N. G. (2022). Effects of urban growth boundaries on urban spatial structural and ecological functional optimization in the Jining Metropolitan Area, China. Land Use Policy, 117(May 2021), 106113. https://doi.org/10.1016/j.landusepol.2022.106113
Zeng, X., Yu, Y., Yang, S., Lv, Y., & Sarker, M. N. I. (2022). Urban Resilience for Urban Sustainability: Concepts, Dimensions, and Perspectives. Sustainability, 14(5), 2481. https://doi.org/10.3390/su14052481
Letters to Editor
[1] Letters that include statements of statistics, facts, research, or theories should include appropriate references, although more than three are discouraged.
[2] Letters that are personal attacks on an author rather than thoughtful criticism of the author’s ideas will not be considered for publication.
[3] Letters can be no more than 300 words in length.
[4] Letter writers should include a statement at the beginning of the letter stating that it is being submitted either for publication or not.
[5] Anonymous letters will not be considered.
[6] Letter writers must include their city and state of residence or work.
[7] Letters will be edited for clarity and length.