Abstract
Civil infrastructure systems are disturbed by natural or man-made hazards at an increasing frequency and severity. Among these systems, transportation systems are especially vulnerable due to their nature and are of significant importance to urban built environments as they maintain the mobility of urban dwellers and goods. Mobility disturbances are significant not only due to the direct losses associated but also due to the greater economic impacts driven by indirect losses stemming from the economic interactions of regions and sectors. Therefore, understanding the economic impacts of urban mobility disturbances is critical. To achieve a better understanding of the status quo of the research on transportation disturbances and economic impact analysis, a literature review was conducted. The review indicates that most of the articles fail to leverage realistic hazard impact information and explicit network modeling, consequently jeopardizing the credibility of the results. To begin addressing the gaps in the field, an interdisciplinary framework was designed to investigate the economic impacts of mobility disturbances. To validate the framework, a case study was conducted to estimate the economic impacts of commuting-based mobility disturbances resulting from a potential earthquake scenario in the Greater Los Angeles Area. The direct and indirect economic losses were estimated to be 285.49 and 93.48 million dollars, respectively. The results indicated that the economic losses could vary significantly among regions as well as industries. Among the five counties in the study region, Los Angeles County suffered the most. In addition, industries related to finance, education and scientific services, etc. were estimated to experience larger losses.
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Notes
Please note that this paper is complementing an earlier publication by the authors (Wei et al. 2018).
It is widely assumed as well as accepted in transportation safety domain that bridges are the most important components in transportation infrastructure.
The multi-disciplinary framework is unable to deal with this factor currently; however, this is a limitation that our future work will address.
The economic region in the full deployment of the framework will be the regions in Los Angeles that we have the input-output table for.
These values are published annually by Bureau of Transportation Statistics. Average cost of driving includes fuel, maintenance, and tires. Available online at: www.rita.dot.gov/bts
These values are conducted out by the California Department of Transportation and recommended to be used in statewide transportation projects analysis.
The Vehicle Operation Cost Parameters are statewide representative average values recommended by the California Department of Transportation to be used in the economic analysis of highway and other projects.
California Department of Transportation, Vehicle Operation Cost Parameters, http://www.dot.ca.gov/hq/tpp/offices/eab/benefit_cost/LCBCA-economic_parameters.html, last accessed 2018/4/25.
Retail Gasoline and Diesel Prices, U.S. Energy Information Administration, https://www.eia.gov/dnav/pet/pet_pri_gnd_dcus_y05la_a.htm, last accessed 2018/4/25.
Your Driving costs Report 2017, American Automobile Association (AAA), https://exchange.aaa.com/automotive/driving-costs/#.WsNoF2hL82x, last accessed 2018/4/25.
Los Angeles County is the most populous county as well as international trade center and manufacturing center in the USA. It is also home to many well-known companies such as Paramount Pictures and 21st Century Fox. https://www.lacounty.gov, last accessed 2018/4/25.
California Employment Development Department, Labor Market Data and Information, http://www.labormarketinfo.edd.ca.gov/geography/lmi-by-county.html, last accessed 2018/4/25.
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Acknowledgements
This material is based upon work supported by National Key R&D Program of China under Grant No. 2017YFC0803308, National Natural Science Foundation of China (NSFC) under Grant No. U1709212, 71741023, and Tsinghua University Initiative Scientific Research Program under Grant No. 2014z21050 and 2015THZ0. The authors are thankful for the support of Ministry of Science and Technology of China, NSFC, and Tsinghua University. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.
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Wei, F., Koc, E., Soibelman, L. et al. Disturbances to Urban Mobility and Comprehensive Estimation of Economic Losses. Polytechnica 1, 48–60 (2018). https://doi.org/10.1007/s41050-018-0005-1
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DOI: https://doi.org/10.1007/s41050-018-0005-1