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contributor authorSrijesh Pradhan
contributor authorErin Arneson
date accessioned2022-01-31T23:29:00Z
date available2022-01-31T23:29:00Z
date issued1/1/2021
identifier other%28ASCE%29ME.1943-5479.0000869.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4269801
description abstractThe swift and cost-efficient postdisaster reconstruction of highways, roads, and bridges is a necessary component of resilient transportation infrastructure systems. However, the US construction industry often reports temporary increases in construction labor wages following large-scale disasters due to a gap between labor supply and demand, a concept known as demand surge. Utilizing publicly available big data related to the construction labor market and postdisaster infrastructure repair expenditures, this study seeks to (1) measure construction labor demand surge in the highways, roads, and bridges construction sector following federally-declared disasters in US metro-areas and (2) identify when such postdisaster demand surge occurs. A total of 118 US metro-areas were analyzed for demand surge following federally-declared disaster events from 2004 to 2017. Findings highlight inflated postdisaster construction labor wages in metro-areas, with the demand surge spiking within six months after a disaster. This data-driven study is the first to quantitatively measure postdisaster demand surge in the US highways, roads, and bridges sector following multihazard disaster events. Knowledge of the demand surge can guide predisaster planning and decision-making processes for local, state, and national agencies and inform postdisaster best practices for contractors and engineers coordinating transportation system construction projects.
publisherASCE
titlePostdisaster Labor-Demand Surge in the US Highways, Roads, and Bridges Construction Sector
typeJournal Paper
journal volume37
journal issue1
journal titleJournal of Management in Engineering
identifier doi10.1061/(ASCE)ME.1943-5479.0000869
journal fristpage04020102-1
journal lastpage04020102-10
page10
treeJournal of Management in Engineering:;2021:;Volume ( 037 ):;issue: 001
contenttypeFulltext


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