Optimizing government resource allocation in public sectors: investigating intelligent urban systems for effective crisis management
Springer Science and Business Media LLC - Trang 1-16 - 2023
Tóm tắt
This paper draws upon a theoretical framework for resource allocation to examine the differences in resource allocation capabilities of city governments that result from harnessing intelligent urban systems, also known as smart city construction. By analyzing data from 141 Chinese cities in 2020, we demonstrate that smart city construction has a positive influence on government resource allocation capacity. Moreover, we find that this positive relationship is strengthened when there is sufficient regional resource stock and weakened by the complexity of regional pandemics. This study highlights the critical mechanism of harnessing intelligent urban systems to optimize government resource allocation, contributing to the literature on resource allocation in public sectors, and providing clear practical implications for effective crisis management.
Tài liệu tham khảo
Acuto, M. (2020). COVID-19: Lessons for an Urban (izing) World. One Earth, 2(4), 317–319.
Alizadeh, M., Pishvaee, M. S., Jahani, H., Paydar, M. M., & Makui, A. (2022). Viable healthcare supply chain network design for a pandemic. Annals of Operations Research. https://doi.org/10.1007/s10479-022-04934-7
Allam, Z., & Jones, D. S. (2021). Future (post-COVID) digital, smart and sustainable cities in the wake of 6G: Digital twins, immersive realities and new urban economies. Land Use Policy, 101, 105201.
Alshamaila, Y., Papagiannidis, S., Alsawalqah, H., & Aljarah, I. (2023). Effective use of smart cities in crisis cases: A systematic review of the literature. International Journal of Disaster Risk Reduction, 85, 103521.
Alshater, M. M., Kampouris, I., Marashdeh, H., Atayah, O. F., & Banna, H. (2022). Early warning system to predict energy prices: The role of artificial intelligence and machine learning. Annals of Operations Research. https://doi.org/10.1007/s10479-022-04908-9
Bhattacharya, S., Maddikunta, P. K. R., Pham, Q.-V., Gadekallu, T. R., Chowdhary, C. L., Alazab, M., & Piran, M. J. (2021). Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey. Sustainable Cities and Society, 65, 102589.
Brodeur, A., Gray, D., Islam, A., & Bhuiyan, S. (2021). A literature review of the economics of COVID-19. Journal of Economic Surveys, 35(4), 1007–1044.
Bryce, C., Ring, P., Ashby, S., & Wardman, J. (2020). Resilience in the face of uncertainty: Early lessons from the COVID-19 pandemic. Journal of Risk Research, 23(7–8), 880–887.
Chamola, V., Hassija, V., Gupta, V., & Guizani, M. (2020). A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact. IEEE Access, 8, 90225–90265.
Chen, J., Guo, X., Pan, H., & Zhong, S. (2021). What determines city’s resilience against epidemic outbreak: Evidence from China’s COVID-19 experience. Sustainable Cities and Society, 70, 102892.
Chudik, A., Mohaddes, K., & Raissi, M. (2021). Covid-19 fiscal support and its effectiveness. Economics Letters, 205, 109939.
Craney, T. A., & Surles, J. G. (2002). Model-dependent variance inflation factor cutoff values. Quality Engineering, 14(3), 391–403.
Dickens, B. L., Koo, J. R., Wilder-Smith, A., & Cook, A. R. (2020). Institutional, not home-based, isolation could contain the COVID-19 outbreak. The Lancet, 395(10236), 1541–1542.
Duggal, R. (2020). Mumbai’s struggles with public health crises. Kerala’s COVID-19 Strategy, 55(21), 17.
Duro, J. A., Perez-Laborda, A., Turrion-Prats, J., & Fernández-Fernández, M. (2021). Covid-19 and tourism vulnerability. Tourism Management Perspectives, 38, 100819.
Earl, C., & Vietnam, R. (2020). Living with Authoritarianism: Ho Chi Minh City during COVID‐19 Lockdown. City & Society (Washington, DC).
Fan, D., Li, Y., Liu, W., Yue, X. G., & Boustras, G. (2021). Weaving public health and safety nets to respond the COVID-19 pandemic. Safety Science, 134, 105058.
Farrell, T. W., Ferrante, L. E., Brown, T., Francis, L., Widera, E., Rhodes, R., & Thothala, N. (2020). AGS position statement: resource allocation strategies and age-related considerations in the COVID-19 era and beyond. Journal of the American Geriatrics Society, 68(6), 1136–1142.
Fong, M. W., Gao, H., Wong, J. Y., Xiao, J., Shiu, E. Y., Ryu, S., & Cowling, B. J. (2020). Nonpharmaceutical measures for pandemic influenza in nonhealthcare settings—social distancing measures. Emerging Infectious Diseases, 26(5), 976.
Forman, C., Goldfarb, A., & Greenstein, S. (2005). Geographic location and the diffusion of internet technology. Electronic Commerce Research and Applications, 4(1), 1–13.
Goswami, M., Daultani, Y., Paul, S. K., & Pratap, S. (2022). A framework for the estimation of treatment costs of cardiovascular conditions in the presence of disease transition. Annals of Operations Research. https://doi.org/10.1007/s10479-022-04914-x
Han, C., Zhang, R., Liu, X., Wang, X., & Liu, X. (2023). The virus made me lose control: The impact of COVID-related work changes on employees’ mental health, aggression, and interpersonal conflict. Frontiers in Public Health, 11, 1119389.
He, H., & Harris, L. (2020). The impact of Covid-19 pandemic on corporate social responsibility and marketing philosophy. Journal of Business Research, 116, 176–182.
Hu, M., Roberts, J. D., Azevedo, G. P., & Milner, D. (2021). The role of built and social environmental factors in Covid-19 transmission: A look at America’s capital city. Sustainable Cities and Society, 65, 102580.
Ismagilova, E., Hughes, L., Dwivedi, Y. K., & Raman, K. R. (2019). Smart cities: Advances in research-An information systems perspective. International Journal of Information Management, 47, 88–100. https://doi.org/10.1016/j.ijinfomgt.2019.01.004
Ivanoska-Dacikj, A., & Stachewicz, U. (2020). Smart textiles and wearable technologies–opportunities offered in the fight against pandemics in relation to current COVID-19 state. Reviews on Advanced Materials Science, 59(1), 487–505.
Jaiswal, R., Agarwal, A., & Negi, R. (2020). Smart solution for reducing the COVID-19 risk using smart city technology. IET Smart Cities, 2(2), 82–88.
Khan, J., Ishizaka, A., & Mangla, S. K. (2022). Assessing risk of supply chain disruption due to COVID-19 with fuzzy VIKORSort. Annals of Operations Research. https://doi.org/10.1007/s10479-022-04940-9
Khansari, N., Mostashari, A., & Mansouri, M. (2014). Impacting sustainable behavior and planning in smart city. International Journal of Sustainable Land Use and Urban Planning, 1(2), 46–61.
Kraemer, M. U., Yang, C.-H., Gutierrez, B., Wu, C.-H., Klein, B., Pigott, D. M., & Li, R. (2020). The effect of human mobility and control measures on the COVID-19 epidemic in China. Science, 368(6490), 493–497.
Kumar, A., Luthra, S., Mangla, S. K., & Kazançoğlu, Y. (2020). COVID-19 impact on sustainable production and operations management. Sustainable Operations and Computers, 1, 1–7.
Kunzmann, K. R. (2020). Smart cities after COVID-19: Ten narratives. disP-the Planning Review, 56(2), 20–31.
Lau, H., Khosrawipour, V., Kocbach, P., Mikolajczyk, A., Schubert, J., Bania, J., & Khosrawipour, T. (2020). The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China. Journal of Travel Medicine., 27(3), taaa037.
Li, H., Meng, L., Wang, Q., & Zhou, L.-A. (2008). Political connections, financing and firm performance: Evidence from Chinese private firms. Journal of Development Economics, 87(2), 283–299.
Li, Y., Wang, X., Gong, T., & Wang, H. (2022). Breaking out of the pandemic: How can firms match internal competence with external resources to shape operational resilience? Journal of Operations Management., 69(3), 384–403.
Liu, W., Xu, Y., Fan, D., Li, Y., Shao, X.-F., & Zheng, J. (2021a). Alleviating corporate environmental pollution threats toward public health and safety: The role of smart city and artificial intelligence. Safety Science, 143, 105433.
Liu, W., Yue, X. G., & Tchounwou, P. B. (2020). Response to the COVID-19 epidemic: The Chinese experience and implications for other countries. International Journal of Environmental Research and Public Health, 17(7), 2304.
Liu, Z. J., Panfilova, E., Mikhaylov, A., & Kurilova, A. (2021b). Assessing stability in the relationship between parties in crowdfunding and crowdsourcing projects during the COVID-19 crisis. Journal of Global Information Management (JGIM), 30(4), 1–18.
Lopes, J. M., Morales, C. C., Alvarado, M., Melo, V. A. Z. C., Paiva, L. B., Dias, E. M., & Pardalos, P. M. (2022). Optimization methods for large-scale vaccine supply chains: A rapid review. Annals of Operations Research, 316(1), 699–721. https://doi.org/10.1007/s10479-022-04720-5
Marquis, C., & Qian, C. L. (2014). Corporate social responsibility reporting in China: Symbol or substance? Organization Science, 25(1), 127–148.
Midilli, A., Dincer, I., & Ay, M. (2006). Green energy strategies for sustainable development. Energy Policy, 34(18), 3623–3633.
Mitton, C., & Donaldson, C. (2003). Resource allocation in health care: Health economics and beyond. Health Care Analysis, 11(3), 245–257.
Neirotti, P., De Marco, A., Cagliano, A. C., Mangano, G., & Scorrano, F. (2014). Current trends in Smart City initiatives: SOME stylised facts. Cities, 38, 25–36.
Prabhu, J., Kumar, P., Manivannan, S., Rajendran, S., Kumar, K., Susi, S., & Jothikumar, R. (2020). IoT role in prevention of COVID-19 and health care workforces behavioural intention in India-an empirical examination. International Journal of Pervasive Computing and Communications., 16, 331.
Shammi, M., Bodrud-Doza, M., Islam, A. R. M. T., & Rahman, M. M. (2020). COVID-19 pandemic, socioeconomic crisis and human stress in resource-limited settings: A case from Bangladesh. Heliyon, 6(5), e04063.
Sharifi, A., & Alizadeh, H. (2023). Societal smart city: Definition and principles for post-pandemic urban policy and practice. Cities, 134, 104207.
Sharifi, A., & Khavarian-Garmsir, A. R. (2020). The COVID-19 pandemic: Impacts on cities and major lessons for urban planning, design, and management. Science of the Total Environment, 749, 142391.
Sharifi, A., Khavarian-Garmsir, A. R., & Kummitha, R. K. R. (2021). Contributions of smart city solutions and technologies to resilience against the COVID-19 pandemic: A literature review. Sustainability, 13(14), 8018.
Shen, L., Huang, Z., Wong, S. W., Liao, S., & Lou, Y. (2018). A holistic evaluation of smart city performance in the context of China. Journal of Cleaner Production, 200, 667–679.
Shuja, J., Alanazi, E., Alasmary, W., & Alashaikh, A. (2021). COVID-19 open source data sets: A comprehensive survey. Applied Intelligence, 51(3), 1296–1325.
Siriwardhana, Y., De Alwis, C., Gür, G., Ylianttila, M., & Liyanage, M. (2020). The fight against the COVID-19 pandemic with 5G technologies. IEEE Engineering Management Review, 48(3), 72–84.
Stier, A. J., Berman, M. G., & Bettencourt, L. (2020). COVID-19 attack rate increases with city size. arXiv preprint arXiv:2003.10376.
Sun, J., & Zhang, Z. (2020). A post-disaster resource allocation framework for improving resilience of interdependent infrastructure networks. Transportation Research Part d: Transport and Environment, 85, 102455.
Tolbert, C. J., & Mossberger, K. (2006). The effects of e-government on trust and confidence in government. Public Administration Review, 66(3), 354–369.
Vieira, D. I., & Alvaro, A. (2018). A centralized platform of open government data as support to applications in the smart cities context. International Journal of Web Information Systems, 14(1), 2–28.
Whitelaw, S., Mamas, M. A., Topol, E., & Van Spall, H. G. (2020). Applications of digital technology in COVID-19 pandemic planning and response. The Lancet Digital Health., 2(8), e435.
Worby, C. J., & Chang, H.-H. (2020). Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic. Nature Communications, 11(1), 1–9.
Xia, H., Wang, Y., Zhang, J. Z., Zheng, L. J., Kamal, M. M., & Arya, V. (2023). COVID-19 fake news detection: A hybrid CNN-BiLSTM-AM model. Technological Forecasting and Social Change, 195, 122746.
Yan, Z., Sun, Z., Shi, R., & Zhao, M. (2023). Smart city and green development: Empirical evidence from the perspective of green technological innovation. Technological Forecasting and Social Change, 191, 122507.
Yang, S., & Chong, Z. (2021). Smart city projects against COVID-19: Quantitative evidence from China. Sustainable Cities and Society, 70, 102897.
Yao, H., Liu, W., Wu, C.-H., & Yuan, Y.-H. (2021). The imprinting effect of SARS experience on the fear of COVID-19: The role of AI and big data. Socio-Economic Planning Sciences, 80, 101086.
Yao, T., Huang, Z., & Zhao, W. (2020). Are smart cities more ecologically efficient? Evidence from China. Sustainable Cities and Society, 60, 102008.
Yuan, L., Xi, C., & Xiaoyi, W. (2012). Evaluating the readiness of government portal websites in China to adopt contemporary public administration principles. Government Information Quarterly, 29(3), 403–412.
Zhou, J., Hu, L., Yu, Y., Zhang, J. Z., & Zheng, L. J. (2022). Impacts of IT capability and supply chain collaboration on supply chain resilience: empirical evidence from China in COVID-19 pandemic. Journal of Enterprise Information Management. ahead-of-print.
Zhou, Q., Zhu, M., Qiao, Y., Zhang, X., & Chen, J. (2021). Achieving resilience through smart cities? Evidence from China. Habitat International, 111, 102348.