IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i9p5304-d551553.html
   My bibliography  Save this article

Development of Model to Predict Natural Disaster-Induced Financial Losses for Construction Projects Using Deep Learning Techniques

Author

Listed:
  • Ji-Myong Kim

    (Department of Architectural Engineering, Mokpo National University, Mokpo 58554, Korea)

  • Junseo Bae

    (School of Computing, Engineering and Physical Sciences, University of the West of Scotland, Paisley PA1 2BE, UK)

  • Seunghyun Son

    (Department of Architectural Engineering, Kyung Hee University, Suwon 17104, Korea)

  • Kiyoung Son

    (School of Architectural Engineering, University of Ulsan, Ulsan 44610, Korea)

  • Sang-Guk Yum

    (Department of Civil Engineering, Gangneung-Wonju National University, Gangneung 25457, Korea)

Abstract

This study goals to develop a model for predicting financial loss at construction sites using a deep learning algorithm to reduce and prevent the risk of financial loss at construction sites. Lately, as the construction of high-rise buildings and complex buildings increases and the scale of construction sites surges, the severity and frequency of accidents occurring at construction sites are swelling, and financial losses are also snowballing. Singularly, as natural disasters rise and construction projects in urban areas increase, the risk of financial loss for construction sites is mounting. Thus, a financial loss prediction model is desired to mitigate and manage the risk of such financial loss for maintainable and effective construction project management. This study reflects the financial loss incurred at the actual construction sites by collecting claim payout data from a major South Korean insurance company. A deep learning algorithm was presented in order to develop an objective and scientific prediction model. The results and framework of this study provide critical guidance on financial loss management necessary for sustainable and successful construction project management and can be used as a reference for various other construction project management studies.

Suggested Citation

  • Ji-Myong Kim & Junseo Bae & Seunghyun Son & Kiyoung Son & Sang-Guk Yum, 2021. "Development of Model to Predict Natural Disaster-Induced Financial Losses for Construction Projects Using Deep Learning Techniques," Sustainability, MDPI, vol. 13(9), pages 1-12, May.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:5304-:d:551553
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/9/5304/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/9/5304/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pengcheng Xiang & Fuyuan Jia & Xiaohui Li, 2018. "Critical Behavioral Risk Factors among Principal Participants in the Chinese Construction Industry," Sustainability, MDPI, vol. 10(9), pages 1-22, September.
    2. Eduardo Cavallo & Sebastian Galiani & Ilan Noy & Juan Pantano, 2013. "Catastrophic Natural Disasters and Economic Growth," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1549-1561, December.
    3. Ji-Myong Kim & Kag-Cheon Ha & Sungjin Ahn & Seunghyun Son & Kiyoung Son, 2020. "Quantifying the Third-Party Loss in Building Construction Sites Utilizing Claims Payouts: A Case Study in South Korea," Sustainability, MDPI, vol. 12(23), pages 1-13, December.
    4. Sungjin Ahn & Taehui Kim & Ji-Myong Kim, 2020. "Sustainable Risk Assessment through the Analysis of Financial Losses from Third-Party Damage in Bridge Construction," Sustainability, MDPI, vol. 12(8), pages 1-15, April.
    5. Sang-Guk Yum & Sungjin Ahn & Junseo Bae & Ji-Myong Kim, 2020. "Assessing the Risk of Natural Disaster-Induced Losses to Tunnel-Construction Projects Using Empirical Financial-Loss Data from South Korea," Sustainability, MDPI, vol. 12(19), pages 1-15, September.
    6. Chuk Kyo Kim, 2019. "Economic Development of Korea," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 11117, August.
    7. Ji-Myong Kim & Taehui Kim & Sungjin Ahn, 2020. "Loss Assessment for Sustainable Industrial Infrastructure: Focusing on Bridge Construction and Financial Losses," Sustainability, MDPI, vol. 12(13), pages 1-16, July.
    8. Toya, Hideki & Skidmore, Mark, 2007. "Economic development and the impacts of natural disasters," Economics Letters, Elsevier, vol. 94(1), pages 20-25, January.
    9. Ji-Myong Kim & Kiyoung Son & Sang-Guk Yum & Sungjin Ahn, 2020. "Analyzing the Risk of Safety Accidents: The Relative Risks of Migrant Workers in Construction Industry," Sustainability, MDPI, vol. 12(13), pages 1-11, July.
    10. I Ben-David & T Raz, 2001. "An integrated approach for risk response development in project planning," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(1), pages 14-25, January.
    11. Sang-Guk Yum & Ji-Myong Kim & Kiyoung Son, 2020. "Natural Hazard Influence Model of Maintenance and Repair Cost for Sustainable Accommodation Facilities," Sustainability, MDPI, vol. 12(12), pages 1-11, June.
    12. Ji-Myong Kim & Taehui Kim & Kiyoung Son & Sang-Guk Yum & Sungjin Ahn, 2019. "Measuring Vulnerability of Typhoon in Residential Facilities: Focusing on Typhoon Maemi in South Korea," Sustainability, MDPI, vol. 11(10), pages 1-11, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yin Junjia & Aidi Hizami Alias & Nuzul Azam Haron & Nabilah Abu Bakar, 2023. "A Bibliometric Review on Safety Risk Assessment of Construction Based on CiteSpace Software and WoS Database," Sustainability, MDPI, vol. 15(15), pages 1-24, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Junseo Bae & Sang-Guk Yum & Ji-Myong Kim, 2021. "Harnessing Machine Learning for Classifying Economic Damage Trends in Transportation Infrastructure Projects," Sustainability, MDPI, vol. 13(11), pages 1-12, June.
    2. Ji-Myong Kim & Kag-Cheon Ha & Sungjin Ahn & Seunghyun Son & Kiyoung Son, 2020. "Quantifying the Third-Party Loss in Building Construction Sites Utilizing Claims Payouts: A Case Study in South Korea," Sustainability, MDPI, vol. 12(23), pages 1-13, December.
    3. Sang-Guk Yum & Sungjin Ahn & Junseo Bae & Ji-Myong Kim, 2020. "Assessing the Risk of Natural Disaster-Induced Losses to Tunnel-Construction Projects Using Empirical Financial-Loss Data from South Korea," Sustainability, MDPI, vol. 12(19), pages 1-15, September.
    4. Ji-Myong Kim & Kwang-Kyun Lim & Sang-Guk Yum & Seunghyun Son, 2022. "A Deep Learning Model Development to Predict Safety Accidents for Sustainable Construction: A Case Study of Fall Accidents in South Korea," Sustainability, MDPI, vol. 14(3), pages 1-17, January.
    5. Ji-Myong Kim & Taehui Kim & Sungjin Ahn, 2020. "Loss Assessment for Sustainable Industrial Infrastructure: Focusing on Bridge Construction and Financial Losses," Sustainability, MDPI, vol. 12(13), pages 1-16, July.
    6. Sungjin Ahn & Taehui Kim & Ji-Myong Kim, 2020. "Sustainable Risk Assessment through the Analysis of Financial Losses from Third-Party Damage in Bridge Construction," Sustainability, MDPI, vol. 12(8), pages 1-15, April.
    7. Gignoux, Jérémie & Menéndez, Marta, 2016. "Benefit in the wake of disaster: Long-run effects of earthquakes on welfare in rural Indonesia," Journal of Development Economics, Elsevier, vol. 118(C), pages 26-44.
    8. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Emmanuel Apergis & Nicholas Apergis, 2021. "The impact of COVID-19 on economic growth: evidence from a Bayesian Panel Vector Autoregressive (BPVAR) model," Applied Economics, Taylor & Francis Journals, vol. 53(58), pages 6739-6751, December.
    10. Markus Brueckner & Sudyumna Dahal & Haiyan Lin, 2024. "Natural Disasters and Human Development in Asia–Pacific: The Role of External Debt," JRFM, MDPI, vol. 17(6), pages 1-27, June.
    11. Francesco Porcelli & Riccardo Trezzi, 2019. "The impact of earthquakes on economic activity: evidence from Italy," Empirical Economics, Springer, vol. 56(4), pages 1167-1206, April.
    12. Volpe Martincus, Christian & Blyde, Juan, 2013. "Shaky roads and trembling exports: Assessing the trade effects of domestic infrastructure using a natural experiment," Journal of International Economics, Elsevier, vol. 90(1), pages 148-161.
    13. Narasingha Das & Partha Gangopadhyay, 2023. "Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    14. Yasuyuki Sawada, 2017. "Disasters, Household Decisions, and Insurance Mechanisms: A Review of Evidence and a Case Study from a Developing Country in Asia," Asian Economic Policy Review, Japan Center for Economic Research, vol. 12(1), pages 18-40, January.
    15. Darshana Rajapaksa & Moinul Islam & Shunsuke Managi, 2017. "Natural Capital Depletion: the Impact of Natural Disasters on Inclusive Growth," Economics of Disasters and Climate Change, Springer, vol. 1(3), pages 233-244, October.
    16. SAWADA Yasuyuki & MASAKI Tatsujiro & NAKATA Hiroyuki & SEKIGUCHI Kunio, 2017. "Natural Disasters: Financial preparedness of corporate Japan," Discussion papers 17014, Research Institute of Economy, Trade and Industry (RIETI).
    17. Felbermayr, Gabriel & Gröschl, Jasmin, 2014. "Naturally negative: The growth effects of natural disasters," Journal of Development Economics, Elsevier, vol. 111(C), pages 92-106.
    18. Diego D'iaz & Pablo Paniagua & Cristi'an Larroulet, 2024. "Earthquakes and the wealth of nations: The cases of Chile and New Zealand," Papers 2405.12041, arXiv.org.
    19. Gu, Zheng & Li, Yunxian & Zhang, Minghui & Liu, Yifei, 2023. "Modelling economic losses from earthquakes using regression forests: Application to parametric insurance," Economic Modelling, Elsevier, vol. 125(C).
    20. Naqvi, Asjad, 2017. "Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters," World Development, Elsevier, vol. 99(C), pages 395-418.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:5304-:d:551553. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.