2020
DOI: 10.1108/jfmpc-07-2019-0063
|View full text |Cite
|
Sign up to set email alerts
|

Post-hazard labor wage fluctuations: a comparative empirical analysis among different sub-sectors of the U.S. construction sector

Abstract: Purpose The primary objectives of this study are to (1) highlight subsectors and industry groups of the construction sector that are most vulnerable to weather-related disasters (with highest labor cost escalation) and (2) analyze how immediate this labor wage escalation happens in different subsector of the construction sector. Design/methodology/approach The research methodology consists of three steps: (i) integrating various data sources to enable measurement of the county-level labor wage changes follow… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 15 publications
(21 reference statements)
0
1
0
Order By: Relevance
“…Secondly, post-disaster recovery priorities such as emergency health care, temporary housing, re-establishment of damaged urban infrastructures might result in an increase in recovery expenses to the point that financing a PDHR could become unachievable. Finally, after a disaster, reconstruction costs could experience significant growth due to increased demand for workforce and materials (Ahmadi Esfahani and Shahandashti, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…Secondly, post-disaster recovery priorities such as emergency health care, temporary housing, re-establishment of damaged urban infrastructures might result in an increase in recovery expenses to the point that financing a PDHR could become unachievable. Finally, after a disaster, reconstruction costs could experience significant growth due to increased demand for workforce and materials (Ahmadi Esfahani and Shahandashti, 2020).…”
Section: Introductionmentioning
confidence: 99%