Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index
The impact of Big Data (BD) creates challenges in selecting relevant and significant data to be used as criteria to facilitate flood management plans. Studies on macro domain criteria expand the criteria selection, which is important for assessment in allowing a comprehensive understanding of the cu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/6/1/25 |
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| author | Mohammad Fikry Abdullah Zurina Zainol Siaw Yin Thian Noor Hisham Ab Ghani Azman Mat Jusoh Mohd Zaki Mat Amin Nur Aiza Mohamad |
| author_facet | Mohammad Fikry Abdullah Zurina Zainol Siaw Yin Thian Noor Hisham Ab Ghani Azman Mat Jusoh Mohd Zaki Mat Amin Nur Aiza Mohamad |
| author_sort | Mohammad Fikry Abdullah |
| collection | DOAJ |
| description | The impact of Big Data (BD) creates challenges in selecting relevant and significant data to be used as criteria to facilitate flood management plans. Studies on macro domain criteria expand the criteria selection, which is important for assessment in allowing a comprehensive understanding of the current situation, readiness, preparation, resources, and others for decision assessment and disaster events planning. This study aims to facilitate the criteria identification and selection from a macro domain perspective in improving flood management planning. The objectives of this study are (a) to explore and identify potential and possible criteria to be incorporated in the current flood management plan in the macro domain perspective; (b) to understand the type of flood measures and decision goals implemented to facilitate flood management planning decisions; and (c) to examine the possible structured mechanism for criteria selection based on the decision analysis technique. Based on a systematic literature review and thematic analysis using the PESTEL framework, the findings have identified and clustered domains and their criteria to be considered and applied in future flood management plans. The critical review on flood measures and decision goals would potentially equip stakeholders and policy makers for better decision making based on a disaster management plan. The decision analysis technique as a structured mechanism would significantly improve criteria identification and selection for comprehensive and collective decisions. The findings from this study could further improve Malaysia Adaptation Index (MAIN) criteria identification and selection, which could be the complementary and supporting reference in managing flood disaster management. A proposed framework from this study can be used as guidance in dealing with and optimising the criteria based on challenges and the current application of Big Data and criteria in managing disaster events. |
| first_indexed | 2024-03-09T20:06:30Z |
| format | Article |
| id | doaj.art-237b5e40fabb40d3a3130c2f0f04b3d7 |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-09T20:06:30Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-237b5e40fabb40d3a3130c2f0f04b3d72023-11-24T00:29:09ZengMDPI AGBig Data and Cognitive Computing2504-22892022-03-01612510.3390/bdcc6010025Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation IndexMohammad Fikry Abdullah0Zurina Zainol1Siaw Yin Thian2Noor Hisham Ab Ghani3Azman Mat Jusoh4Mohd Zaki Mat Amin5Nur Aiza Mohamad6Leeds University Business School, University of Leeds, Leeds LS2 9JT, UKNational Water Research Institute of Malaysia (NAHRIM), Seri Kembangan 43300, MalaysiaNational Water Research Institute of Malaysia (NAHRIM), Seri Kembangan 43300, MalaysiaNational Water Research Institute of Malaysia (NAHRIM), Seri Kembangan 43300, MalaysiaNational Water Research Institute of Malaysia (NAHRIM), Seri Kembangan 43300, MalaysiaNational Water Research Institute of Malaysia (NAHRIM), Seri Kembangan 43300, MalaysiaNational Water Research Institute of Malaysia (NAHRIM), Seri Kembangan 43300, MalaysiaThe impact of Big Data (BD) creates challenges in selecting relevant and significant data to be used as criteria to facilitate flood management plans. Studies on macro domain criteria expand the criteria selection, which is important for assessment in allowing a comprehensive understanding of the current situation, readiness, preparation, resources, and others for decision assessment and disaster events planning. This study aims to facilitate the criteria identification and selection from a macro domain perspective in improving flood management planning. The objectives of this study are (a) to explore and identify potential and possible criteria to be incorporated in the current flood management plan in the macro domain perspective; (b) to understand the type of flood measures and decision goals implemented to facilitate flood management planning decisions; and (c) to examine the possible structured mechanism for criteria selection based on the decision analysis technique. Based on a systematic literature review and thematic analysis using the PESTEL framework, the findings have identified and clustered domains and their criteria to be considered and applied in future flood management plans. The critical review on flood measures and decision goals would potentially equip stakeholders and policy makers for better decision making based on a disaster management plan. The decision analysis technique as a structured mechanism would significantly improve criteria identification and selection for comprehensive and collective decisions. The findings from this study could further improve Malaysia Adaptation Index (MAIN) criteria identification and selection, which could be the complementary and supporting reference in managing flood disaster management. A proposed framework from this study can be used as guidance in dealing with and optimising the criteria based on challenges and the current application of Big Data and criteria in managing disaster events.https://www.mdpi.com/2504-2289/6/1/25Big DataPESTEL analysisdisaster management planmacro domain criteriaflood criteriadecision analysis |
| spellingShingle | Mohammad Fikry Abdullah Zurina Zainol Siaw Yin Thian Noor Hisham Ab Ghani Azman Mat Jusoh Mohd Zaki Mat Amin Nur Aiza Mohamad Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index Big Data and Cognitive Computing Big Data PESTEL analysis disaster management plan macro domain criteria flood criteria decision analysis |
| title | Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index |
| title_full | Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index |
| title_fullStr | Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index |
| title_full_unstemmed | Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index |
| title_short | Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index |
| title_sort | big data in criteria selection and identification in managing flood disaster events based on macro domain pestel analysis case study of malaysia adaptation index |
| topic | Big Data PESTEL analysis disaster management plan macro domain criteria flood criteria decision analysis |
| url | https://www.mdpi.com/2504-2289/6/1/25 |
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