A Data-Driven Approach for Decision Making in a Regional Interdisciplinary Resiliency Center

Thinesh Selvaratnam , Rinaz Riyaz Mohamed , Berna Eren-Tokgoz , Liv Haselbach , Ginger Gummelt , Brian D. Williams , Matthew I. Pyne

International Journal of Disaster Risk Science ›› 2025, Vol. 16 ›› Issue (3) : 513 -520.

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International Journal of Disaster Risk Science ›› 2025, Vol. 16 ›› Issue (3) : 513 -520. DOI: 10.1007/s13753-025-00643-4
Progress Update

A Data-Driven Approach for Decision Making in a Regional Interdisciplinary Resiliency Center

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Abstract

Lamar University established a Center for Resiliency in 2021 in response to the increasing natural and human-made disasters in the Southeast Texas region. Now more than ever a robust decision-making framework is essential for this recently established regional interdisciplinary resiliency center to make well-informed decisions, prioritize funding effectively, and nurture collaboration across various fields to help communities vulnerable to these threats. This article provides a progress update and presents a methodology integrating VOSviewer and Google Trends to develop such a decision-making framework for the Center for Resiliency at Lamar University in the Southeast Texas region. Four prominent study areas in resilience—Climate Stressors and Disasters, Mental Wellness, Energy and Optimization, and Resilience Planning—were identified. These findings were validated with real-time insights from Google Trends, ensuring practical relevance to recent resilience needs to provide an understanding of evolving resilience dynamics. Furthermore, the paper discusses the status of research conducted at the Lamar University Center for Resiliency, showcasing its commitment to fostering resilience through diverse initiatives across five academic colleges. Integrating VOSviewer and Google Trends offers a robust framework for informed decision making, aligning research efforts with the Southeast Texas region’s current and future resilience needs.

Keywords

Decision making / Disaster decision making / Google trends / Resiliency center / Resilience science / VOSviewer

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Thinesh Selvaratnam, Rinaz Riyaz Mohamed, Berna Eren-Tokgoz, Liv Haselbach, Ginger Gummelt, Brian D. Williams, Matthew I. Pyne. A Data-Driven Approach for Decision Making in a Regional Interdisciplinary Resiliency Center. International Journal of Disaster Risk Science, 2025, 16(3): 513-520 DOI:10.1007/s13753-025-00643-4

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References

[1]

American Society of Civil Engineers. 2022. Reliability and resilience in the balance. https://www.texasce.org/our-programs/beyond-storms/. Accessed 26 May 2025.

[2]

BagdiT, GhoshS, SarkarA, HazraAK, BalachandranS, ChaudhuryS. Evaluation of research progress and trends on gender and renewable energy: A bibliometric analysis. Journal of Cleaner Production, 2023, 423: 138654

[3]

Blake, E.S., and D.A. Zelinsky. 2018. Hurricane Harvey 17 August–1 September 2017. Miami, FL: National Weather Service NOAA. https://www.nhc.noaa.gov/dat0061/tcr/AL092017_Harvey.pdf. Accessed 26 May 2025.

[4]

ChoiH, VarianH. Predicting the present with Google Trends. Economic Record, 2012, 88(s1): 2-9

[5]

Chris, M. 2018. Hurricane Harvey was year’s costliest U.S. disaster at $125 billion in damages. https://www.texastribune.org/2018/01/08/hurricane-harvey-was-years-costliest-us-disaster-125-billion-damages/. Accessed 26 May 2025.

[6]

CohenSA, ZhuangT, XiaoM, MichaudJB, AmanatullahDF, KamalRN. Google trends analysis shows increasing public interest in platelet-rich plasma injections for hip and knee osteoarthritis. The Journal of Arthroplasty, 2021, 36(10): 3616-3622

[7]

DaimTU, RuedaG, MartinH, GerdsriP. Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technological Forecasting and Social Change, 2006, 73(8): 981-1012

[8]

GuptaB, BhattacharyaD. Bibliometric approach towards mapping the dynamics of science and technology. DESIDOC Journal of Library & Information Technology, 2003, 24(1): 3-8

[9]

JunS-P, YooHS, ChoiS. Ten years of research change using Google Trends: From the perspective of big data utilizations and applications. Technological Forecasting and Social Change, 2018, 130: 69-87

[10]

KaruppiahK, SankaranarayananB, AliSM. A systematic review of sustainable business models: Opportunities, challenges, and future research directions. Decision Analytics Journal, 2023, 8: 100272

[11]

KimD, KimD, RhoS, HwangE. Detecting trend and bursty keywords using characteristics of Twitter stream data. International Journal of Smart Home, 2013, 7: 209-220

[12]

LiZ, KeH, LinQ, ShenZ, ChenY. Global trends in gut microbiota and clostridioides difficile infection research: A visualized study. Journal of Infection and Public Health, 2022, 15(7): 806-815

[13]

MoedHF, HaleviG. A bibliometric approach to tracking international scientific migration. Scientometrics, 2014, 101(3): 1987-2001

[14]

National Oceanic and Atmospheric Administration. 2022. Hurricane costs. https://coast.noaa.gov/states/fast-facts/hurricane-costs.html. Accessed 26 May 2025.

[15]

SelvaratnamT, HaselbachL, Eren-TokgozB, GummeltG, BoudreauxK, WilliamsBD, PyneMI, LinkovI. Establishing a regional interdisciplinary resilience center: A bottom-up approach. Environment Systems and Decisions, 2023, 43(2): 191-199

[16]

TiwariS. Smart warehouse: A bibliometric analysis and future research direction. Sustainable Manufacturing and Service Economics, 2023, 2: 100014

[17]

U.S. Army Corps of Engineers. 2017. Principal port of the United States. https://usace.contentdm.oclc.org/digital/collection/p16021coll2/id/3114. Accessed 17 Apr 2024.

[18]

van EckNJ, WaltmanL. How to normalize cooccurrence data? An analysis of some well-known similarity measures. Journal of the American Society for Information Science and Technology, 2009, 60(8): 1635-1651

[19]

van EckNJ, WaltmanL. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 2010, 84(2): 523-538

[20]

Wang, C., T. Lv, and X. Deng. 2020. Bibliometric and visualized analysis of China’s smart grid research 2008–2018. Frontiers in Research Metrics and Analytics 5. https://doi.org/10.3389/frma.2020.551147.

[21]

WeiN, HuY, LiuG, LiS, YuanG, ShouX, ZhangX, ShiJ, ZhaiH. A bibliometric analysis of familial hypercholesterolemia from 2011 to 2021. Current Problems in Cardiology, 2023, 48(7): 101151

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