Abstract

Big data brings great opportunities to gain better understanding of the complexities and dynamics of the system of systems (SoS) of modern megacities and to facilitate their management in a sustainable manner. One of the major performance indicators of city operations management is to guarantee that the city has low vulnerability to natural and man-made hazards. It is necessary to construct urban hierarchical vulnerability indices (HVIs) to quantify and capture the resilience of the urban SoS to disastrous events such as, flooding, pandemics, explosion, infrastructure collapse, terrorist attacks, and financial crises etc. It is also imperative for the city governors and officials to understand how hazardous event(s) might change the HVIs at different levels, how policy interventions might positively or negatively affect the HVIs, and how structural changes (addition of new system or systems components i.e., new roads, buildings, and hospitals) can change the HVIs and in what manner. This paper presents a conceptual framework for defining and implementing HVIs by capturing the characteristics of urban SoS and taking advantage of the value generated by big data. We categorize the HVIs at different levels by considering characteristics of SoS. We then illustrate different dimensions of HVIs and relate them to the current vulnerability indices in literature and in practice. We also show how the value of big data generated and obtained in urban SoSs lead to the construction of a comprehensive HVIs into reality and examine how it could be used to better understanding the dynamic impacts of ever-increasing complexity and uncertainty of urban SoS. Using HVIs as key performance indicator (KPI) in city operations management enable cities to reengineer and reinvent themselves to promote socioeconomic growth and improve quality of life in a sustainable way.

Full Text
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