東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Essays on Natural Disaster Aversion /

Lu, Pei-Jyun,

FindBook

Google Book

Amazon

博客來

Essays on Natural Disaster Aversion /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Essays on Natural Disaster Aversion // Pei-Jyun Lu.
作者:	Lu, Pei-Jyun,
面頁冊數:	1 electronic resource (111 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-06, Section: A.
Contained By:	Dissertations Abstracts International86-06A.
標題:	American studies. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31639682
ISBN:	9798346811657

Essays on Natural Disaster Aversion /
Lu, Pei-Jyun,

Essays on Natural Disaster Aversion /Pei-Jyun Lu. - 1 electronic resource (111 pages)

Source: Dissertations Abstracts International, Volume: 86-06, Section: A.

Natural disasters cause significant economic losses and death tolls worldwide. In the United States alone, weather-related disasters have cost over $2.5 trillion in the past four decades, with increasing severity over time. Governments implement disaster risk reduction policies to mitigate these impacts by promoting avoidance behaviors, reducing exposure, and minimizing damage to people, crops, and property. However, critical questions remain understudied: Do these policies effectively reduce weather-related impacts? How can their efficacy be evaluated? What drives governments to terminate ineffective policies? This dissertation addresses these questions and provides insights for policymakers. The first chapter, "Tropical Cyclone Day-Off Orders, Warnings, and Avoidance Behavior," examines Taiwan's day-off policy during tropical cyclones, which allows residents to avoid exposure to strong winds, landslides, and flooding. Using transportation data as a proxy for avoidance behavior, the analysis reveals that while mandatory day-off orders reduce exposure, people may take similar actions even without them. Comparing Taiwan with Miami-Dade County, Florida, the study finds similar avoidance patterns in areas without mandatory orders. These findings suggest that providing reliable information may allow individuals to make informed decisions, reducing unnecessary disruptions.The second chapter, "Efficacy Analysis of Cloud Seeding Programs in Kansas Agriculture," evaluates cloud seeding as a hail suppression strategy for protecting crops in Kansas, a state prone to severe hailstorms. The findings show that cloud seeding reduces hailstorm intensity but does not significantly lower crop loss ratios, as hailstones remain large enough to cause damage. Additionally, cloud seeding unintentionally increases flood-related crop losses and exhibits spillover effects, reducing downwind counties' sorghum productivity. Despite a positive net present value overall, these spillover effects lead to negative net present value in downwind counties, complicating the program's cost-benefit profile.The third chapter, "Factors Influencing Policy Termination: The Cloud Seeding Program in Kansas," investigates the determinants of policy termination using Kansas' cloud seeding program as a case study. Analysis reveals that counties experiencing higher hail-induced crop losses are more likely to terminate the program, reflecting its perceived inefficacy. Furthermore, neighboring counties' termination decisions delay the termination process, aligning with diffusion theory, which posits that governments learn from neighbors' experiences. This study highlights the role of inefficacy and policy diffusion in driving termination decisions.In conclusion, this dissertation explores the effectiveness and sustainability of disaster risk reduction policies through the lens of two case studies: Taiwan's tropical cyclone day-off orders and Kansas' cloud seeding program. The findings emphasize the importance of rigorous evaluation to improve policy design and highlight the need for continued research into innovative risk reduction strategies to enhance resilience against natural disasters.

English

ISBN: 9798346811657Subjects--Topical Terms:

2122720
American studies.
Subjects--Index Terms:

Cost-benefit analysis

Essays on Natural Disaster Aversion /
LDR:04616nmm a22004453i 4500 001 2428295
005 20250414021659.5
006 m o d
007 cr|nu||||||||
008 261011s2024 miu||||||m |||||||eng d
020 $a 9798346811657
035 $a (MiAaPQD)AAI31639682
035 $a AAI31639682
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Lu, Pei-Jyun, $e author. $0 (orcid)0009-0002-6884-1925 $3 3815412
245 1 0 $a Essays on Natural Disaster Aversion / $c Pei-Jyun Lu.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (111 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 86-06, Section: A.
500 $a Advisors: Skidmore, Mark Committee members: Lupi, Frank; Horan, Rick; Swinton, Scott.
502 $b Ph.D. $c Michigan State University $d 2024.
520 $a Natural disasters cause significant economic losses and death tolls worldwide. In the United States alone, weather-related disasters have cost over $2.5 trillion in the past four decades, with increasing severity over time. Governments implement disaster risk reduction policies to mitigate these impacts by promoting avoidance behaviors, reducing exposure, and minimizing damage to people, crops, and property. However, critical questions remain understudied: Do these policies effectively reduce weather-related impacts? How can their efficacy be evaluated? What drives governments to terminate ineffective policies? This dissertation addresses these questions and provides insights for policymakers. The first chapter, "Tropical Cyclone Day-Off Orders, Warnings, and Avoidance Behavior," examines Taiwan's day-off policy during tropical cyclones, which allows residents to avoid exposure to strong winds, landslides, and flooding. Using transportation data as a proxy for avoidance behavior, the analysis reveals that while mandatory day-off orders reduce exposure, people may take similar actions even without them. Comparing Taiwan with Miami-Dade County, Florida, the study finds similar avoidance patterns in areas without mandatory orders. These findings suggest that providing reliable information may allow individuals to make informed decisions, reducing unnecessary disruptions.The second chapter, "Efficacy Analysis of Cloud Seeding Programs in Kansas Agriculture," evaluates cloud seeding as a hail suppression strategy for protecting crops in Kansas, a state prone to severe hailstorms. The findings show that cloud seeding reduces hailstorm intensity but does not significantly lower crop loss ratios, as hailstones remain large enough to cause damage. Additionally, cloud seeding unintentionally increases flood-related crop losses and exhibits spillover effects, reducing downwind counties' sorghum productivity. Despite a positive net present value overall, these spillover effects lead to negative net present value in downwind counties, complicating the program's cost-benefit profile.The third chapter, "Factors Influencing Policy Termination: The Cloud Seeding Program in Kansas," investigates the determinants of policy termination using Kansas' cloud seeding program as a case study. Analysis reveals that counties experiencing higher hail-induced crop losses are more likely to terminate the program, reflecting its perceived inefficacy. Furthermore, neighboring counties' termination decisions delay the termination process, aligning with diffusion theory, which posits that governments learn from neighbors' experiences. This study highlights the role of inefficacy and policy diffusion in driving termination decisions.In conclusion, this dissertation explores the effectiveness and sustainability of disaster risk reduction policies through the lens of two case studies: Taiwan's tropical cyclone day-off orders and Kansas' cloud seeding program. The findings emphasize the importance of rigorous evaluation to improve policy design and highlight the need for continued research into innovative risk reduction strategies to enhance resilience against natural disasters.
546 $a English
590 $a School code: 0128
650 4 $a American studies. $3 2122720
650 4 $a Public policy. $3 532803
653 $a Cost-benefit analysis
653 $a Hurricane
653 $a Natural disaster
653 $a Policy analysis
653 $a Weather modification
690 $a 0503
690 $a 0438
690 $a 0323
690 $a 0630
710 2 $a Michigan State University. $b Agricultural, Food and Resource Economics - Doctor of Philosophy. $e degree granting institution. $3 3815276
720 1 $a Skidmore, Mark $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-06A.
790 $a 0128
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31639682