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Decision-Making Among Businesses in Post-Catastrophe Uncertainty: How Economic Geographies Re-Form in New Orleans

Decision-Making Among Businesses in Post-Catastrophe Uncertainty: How Economic Geographies Re-Form in New Orleans
灾难后不确定性下的企业决策:新奥尔良的经济地理如何重组
批准号:
0554937
负责人:
Nina Lam
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-11-01 至 2007-10-31

项目摘要

项目成果

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中文摘要
翻译
该项目旨在了解灾难后城市环境中居民重新安置的商业方面。首要的研究问题是:企业如何就是否返回或搬迁做出空间决策,以及这些决策反过来如何影响景观和经济。具体来说,该项目将收集和分析时间关键数据,包括在卡特里娜飓风过后,企业在什么地方、如何、为什么以及何时返回新奥尔良。我们会定期进行电话调查和街道调查。街道调查将包括每两周对新奥尔良三条主要商业走廊的全面调查,追踪何时、何地以及哪些企业回归并存活(或倒闭)。电话调查每2~3周进行一次,共5轮,将针对全市的企业。在每一轮中,将按人口普查区和少数商业类别随机抽取500个完整的调查样本。这两组调查数据将被绘制成地图,并与人口普查、洪水灾害和其他GIS(地理信息系统)数据层相结合。这将提供一个有价值的,时间关键的时空数据集,可以用来回答一些具体的研究问题。很少有研究集中在收集时间关键的经验数据上,这些数据是关于企业如何在灾难发生后做出空间决策,决定他们是留在那里还是搬迁,尤其是像我们所看到的卡特里娜飓风这样影响整个新奥尔良大都市的灾难。为该项目收集的时间关键数据将提供独特的信息,说明在这种前所未有的情况下,企业之间是如何做出决策的。随着时间的推移,街道调查和电话调查的耦合和跟踪将为研究人类-社会-经济在空间和时间上的动态提供重要信息。这些数据将作为后续研究和与其他研究(例如关于个人决策的研究)进行比较的重要基准数据集。这个项目的成果也将有助于政府和规划机构为该区域的经济复苏制定有效的政策。
英文摘要
This project seeks to understand the commercial side of resettlement of residents in urban environments after a catastrophe. The overarching research question is: how businesses make spatial decisions on whether to return or relocate and how these decisions in turn impact the landscape and its economy. Specifically, the project will collect and analyze time-critical data on what, where, how, why, and when businesses return to New Orleans following the repopulation of the city after Hurricane Katrina. Both telephone surveys and street surveys of businesses will be conducted periodically. The street surveys will include a complete survey of three major commercial corridors in New Orleans every two weeks, tracking where, when, and what businesses return and survive (or fail). The telephone surveys, conducted every 2~3 weeks for 5 rounds, will target businesses throughout the entire city. In each round, a random sample of 500 complete surveys stratified by census tract and by a few business categories will be conducted. Both sets of survey data will then be mapped and integrated with census, flood damage, and other GIS (geographic information system) data layers. This will provide a valuable, time-critical spatial-temporal data set that can serve to answer a number of specific research questions.Very little research has focused on collecting time-critical, empirical data on how businesses make spatial decisions on whether they remain or relocate after a catastrophe, especially a catastrophe as deep and wide as we have seen in Hurricane Katrina that affects an entire metropolis of New Orleans. The time-critical data collected for this project will provide unique information on how decisions among businesses are made in this unprecedented case. The coupling and tracking of street and telephone surveys over time will provide vital information for research on human-social-economic dynamics over space and time. The data will serve as an important benchmark dataset for subsequent research and for comparisons with other studies (e.g. studies on decisions made by individuals). Results from this project will also help governmental and planning agencies in devising effective policies for economic recovery in the region.
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会议论文
Collaborative Research: HNDS-I: Cyberinfrastructure for Human Dynamics and Resilience Research
  • 批准号:
    2318203
  • 项目类别:
    Standard Grant
  • 资助金额:
    $49.7万
  • 财政年份:
    2023
  • 负责人:
    Nina Lam
  • 依托单位:
Collaborative Research: RII Track-2 FEC: Rural Confluence: Communities and Academic Partners Uniting to Drive Discovery and Build Capacity for Climate Resilience
  • 批准号:
    2316367
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $112.13万
  • 财政年份:
    2023
  • 负责人:
    Nina Lam
  • 依托单位:
RAPID: The Changing Roles of Social Media in Disaster Resilience: The Case of Hurricane Harvey
  • 批准号:
    1762600
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2018
  • 负责人:
    Nina Lam
  • 依托单位:
IBSS-L: Understanding Social and Geographical Disparities in Disaster Resilience Through the Use of Social Media
  • 批准号:
    1620451
  • 项目类别:
    Standard Grant
  • 资助金额:
    $83.46万
  • 财政年份:
    2016
  • 负责人:
    Nina Lam
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis