Women Leading Research: Niratcha “Grace” Tungtisanont
SMITH BRAIN TRUST – With natural disasters occurring more frequently, a deeper understanding of emergency preparedness has become increasingly critical. Floods, in particular, demand more research into improving the effectiveness of disaster relief.
Niratcha “Grace” Tungtisanont, assistant professor in the Department of Logistics, Business and Public Policy at the University of Maryland’s Robert H. Smith School of Business, recognizes this demand. With a team of co-researchers, Tungtisanont has authored “Antecedents of Household Recovery Effectiveness from Floods: A Structural Econometric Analysis of Flooding in Thailand,” which investigates how various stakeholders — individuals, communities and governments — should act throughout the flood cycle to increase the likelihood of a successful recovery.
But this isn’t just an academic study taking place from a distance. Tungtisanont has firsthand experience with disaster relief. She assisted and worked with victims of the 2011 Thai floods. Tungtisanont observed the complex operational problems associated with flood disasters, ranging from unstructured service volunteers to garbage management.
The World Economic Forum has said that floods often produce the largest social, economic and humanitarian losses among natural disasters. On average, 250 million people worldwide are affected each year. The global economic costs top $90 billion and are projected to exceed $500 billion by 2030. Fatality trends from floods are also increasing, “a consequence of climate change,” explained the researchers.
For this study, Tungtisanont and her team examined how households can improve their resilience to more readily return to normal after a flood. “Specifically, we observe how household-level factors in the pre-flood stage — i.e. warning, experience, vulnerability and community/neighborhood ties — determine the degree of preparedness,” the researchers write.
What they found is that residents can prepare themselves before a flood event by moving their belongings out of harm’s way, storing food and other essential goods and making cement walls to block floodwaters. According to the researchers, “the diverse roles of service receivers — citizens, victims and restorers — are systemically critical to reducing financial loss and improving the effectiveness of the recovery process.”
This study also revealed that households with moderate and high community/neighborhood ties recovered best when compared to those with no or low/community neighborhood ties. Strong ties lead to higher preparedness, lower total monetary loss during floods and greater recovery.
Another key finding is the importance of warning quality before the flood.
“Accurate and timely messages from the government or humanitarian operation stakeholders are critical for households as they must invest in preparedness,” the researchers wrote. “As governments are one of the key service providers, we suggest they invest in improving disaster warning and other effective communication systems for better service outcomes.”
Tungtisanont and her team also suggested that governments prioritize households with vulnerable members because these individuals are more susceptible to injury from floods.
“Governments might execute policies that request households identify themselves as having vulnerable members,” explained the researchers. “Some examples might be putting red flags at the front of the house or reporting to the government in advance.”
Although this empirical study is the first to use field and archival data to explore the restoration and recovery process of flood disasters, the authors do not want it to be the last.
“Taking a potential victim’s perspective, we identify the salient factors that should be examined in future research, including behavioral factors such as community ties and influencing customers’ participation in recovery,” they wrote. “The better prepared stakeholders and service receivers are before the event, the more effective the operation will be during the event, ensuring minimum harm to households and better recovery.”
Niratcha "Grace" Tungtisanont is an assistant professor in the Department of Logistics, Business & Public Policy at the University of Maryland's Robert H. Smith School of Business.
Research interests: Involved with the 2011 Thai flood recovery, where she gained firsthand experience in assisting flood victims. Her research goal is to identify what strategic factors (e.g. resources, investments, policies, etc.) should be prioritized prior to and during a flood event. Her research findings draw upon macroeconomics and service strategy literature to consider the role of various stakeholders. Areas of expertise include disaster operations and crisis management, service operations strategy, and humanitarian service supply chain strategy.
Selected accomplishments: Invited to present her research at the 2017 Johnson OTIM symposium, INFORMS, and POMS Annual Meetings. Completed her PhD work at Clemson University with a College of Business Graduate Research Assistant Excellence Award for the 2016-17 academic year. She also earned a Master of Science in Agricultural and Resource Economics and a Bachelor of Art in Economics and Mathematics from the University of Arizona.
About this series: The Smith School faculty is celebrating Women’s History Month 2018 in partnership with ADVANCE, an initiative to transform the University of Maryland by investing in a culture of inclusive excellence. Daily faculty spotlights support activities from the school’s Office of Diversity Initiatives, starting with the seventh annual Women Leading Women forum on March 1, 2018.
Other fearless ideas from: Rajshree Agarwal | Ritu Agarwal | T. Leigh Anenson | Kathryn M. Bartol | Christine Beckman | Margrét Bjarnadóttir | M. Cecilia Bustamante | Jessica M. Clark | Rellie Derfler-Rozin | Waverly Ding | Wedad J. Elmaghraby | Rosellina Ferraro | Rebecca Hann | Amna Kirmani | Hanna Lee | Hui Liao | Jennifer Carson Marr | Wendy W. Moe | Courtney Paulson | Louiqa Raschid | Rebecca Ratner | Debra L. Shapiro | M. Susan Taylor | Niratcha (Grace) Tungtisanont | Vijaya Venkataramani | Janet Wagner | Yajin Wang | Yajun Wang | Liu Yang | Jie Zhang | Lingling Zhang
Image credit: Vlad
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