社會脆弱性評估對於理解人口、社會經濟及科技因素如何影響社區在災害發生前的準備能力、災害期間的應變能力，以及災後的復原能力具有重要意義。本研究探討網際網路可近性（Internet Accessibility）在社會脆弱性評估中的作用，並建立一個多維度資料立方體（Multidimensional Data Cube）架構，以支援脆弱性資料在空間、時間及指標等維度上的管理與分析。本研究以印尼日惹特區（Special Region of Yogyakarta）2019年至2022年的資料為基礎，設計並評估兩種分析情境：其一僅採用傳統的人口與社會經濟指標，其二則進一步納入網際網路可近性指標。研究採用主成分分析（Principal Component Analysis, PCA）與因素分析（Factor Analysis, FA）來辨識主要影響指標，並計算社會脆弱性指數（Social Vulnerability Index, SVI）。研究結果顯示，網際網路可近性指標持續呈現高度相關性，並顯著影響主成分的組成結構，進而改變部分傳統指標的相對重要性。然而，納入網際網路可近性後，對研究區各縣市整體脆弱性分類結果的影響並不顯著。此外，多維度資料立方體架構能有效支援社會脆弱性資料於不同空間與時間尺度下的組織、彙整、驗證及檢索作業。
研究結果證明，網際網路可近性已成為當代社會脆弱性的重要組成面向，而多維度資料立方體則提供了一種有效率的框架，用於管理與分析具有動態特性的脆弱性資料。

Understanding how demographic, socioeconomic, and technological factors influence a community's ability to prepare for, respond to, and recover from disasters is guide policy development and resource allocation. This study investigates the role of internet accessibility in social vulnerability assessment and develops a multidimensional data cube framework to support the management and analysis of vulnerability data across spatial, temporal, and indicator dimensions. Using data from the Special Region of Yogyakarta, Indonesia, for the period 2019–2022, two assessment scenarios were evaluated: one based on conventional demographic and socioeconomic indicators and another incorporating internet accessibility indicators. Principal Component Analysis (PCA) and Factor Analysis (FA) were employed to identify dominant indicators and calculate the Social Vulnerability Index (SVI). The results show that internet accessibility indicators consistently exhibit strong correlations and influence the composition of principal components, altering the relative importance of several conventional indicators. However, the inclusion of internet accessibility does not substantially change the overall vulnerability classifications of the regencies studied. In addition, the multidimensional data cube framework successfully supports the organization, aggregation, validation, and retrieval of social vulnerability data across multiple spatial and temporal scales. These findings demonstrate that internet accessibility represents an important contemporary dimension of social vulnerability and that multidimensional data cubes provide an efficient framework for managing and analyzing dynamic vulnerability data.

Armaș, I., & Gavriș, A. (2013). Social vulnerability assessment using spatial multi-criteria analysis (SEVI model) and the Social Vulnerability Index (SoVI model) – a case study for Bucharest, Romania. Natural Hazards and Earth System Sciences, 13(6), 1481–1499. https://doi.org/10.5194/nhess-13-1481-2013
Aroca-Jimenez, E., Bodoque, J. M., Gracia, J. A., & Diez-Herrero, A. (2017). Construction of an integrated social vulnerability index in urban areas pro...: 成功大學資源整合查詢服務系統. Nat. Hazards Earth Syst. Sci, 17, 1541–1557.
Birkmann, J., Cardona, O. D., Carreño, M. L., Barbat, A. H., Pelling, M., Schneiderbauer, S., Kienberger, S., Keiler, M., Alexander, D., Zeil, P., & Welle, T. (2013). Framing vulnerability, risk and societal responses: The MOVE framework. Natural Hazards, 67(2), 193–211. https://doi.org/10.1007/s11069-013-0558-5
Bizimana, J.-P., Twarabamenye, E., & Kienberger, S. (2015). Assessing the social vulnerability to malaria in Rwanda. Malaria Journal, 14(2). https://doi.org/10.1186/1475-2875-14-2
Bjarnadottir, S., Li, Y., Mark, •, Stewart, G., Bjarnadottir, S., Li, Y., & Stewart, M. G. (2011). Social vulnerability index for coastal communities at risk to hurricane hazard and a changing climate. Natural Hazards, 59, 1055–1075. https://doi.org/10.1007/s11069-011-9817-5
Burton, C. G. (2010). Social Vulnerability and Hurricane Impact Modeling. Natural Hazards Review, 11(2), 58–68. https://doi.org/10.1061/(ASCE)1527-6988(2010)11:2(58)
Chakraborty, J., Tobin, G. A., & Montz, B. E. (2005). Population Evacuation: Assessing Spatial Variability in Geophysical Risk and Social Vulnerability to Natural Hazards. Natural Hazards Review, 6(1), 23–33. https://doi.org/10.1061/(ASCE)1527-6988(2005)6:1(23)
Chesley, S. R., & Ward, S. N. (2006). A Quantitative Assessment of the Human and Economic Hazard from Impact-generated Tsunami. Natural Hazards, 38, 355–374. https://doi.org/10.1007/s11069-005-1921-y
Cutter, S. L., Emrich, C. T., Morath, D. P., & Dunning, C. M. (2013). Integrating social vulnerability into federal flood risk management planning. Journal of Flood Risk Management, 6(4), 332–344. https://doi.org/10.1111/jfr3.12018
Cutter, S. L., & Finch, C. (2008a). Temporal and spatial changes in social vulnerability to natural hazards. Proceedings of the National Academy of Sciences of the United States of America, 105(7), 2301–2306. https://doi.org/10.1073/pnas.0710375105
Cutter, S. L., & Finch, C. (2008b). Temporal and spatial changes in social vulnerability to natural hazards. In M. B. L. Turner II, Clark University, Worcester (Ed.), Proceedings of National Academy of Sciences of The United States of America (pp. 2301–2306). The National Academy of Sciences of the USA.
de Oliveira Mendes, J. M. (2009). Social vulnerability indexes as planning tools: beyond the preparedness paradigm. Journal of Risk Research, 12(1), 43–58. https://doi.org/10.1080/13669870802447962
di Girasole, E. G., & Cannatella, D. (2017). Social vulnerability to natural hazards in urban systems. An application in Santo Domingo (Dominican Republic). Sustainability (Switzerland), 9(11). https://doi.org/10.3390/su9112043
Ekpenyong, A. S., & Udoh, J. C. (2018). A GIS Analysis of the Spatial Pattern of Social Vulnerability in Akwa Ibom State, Nigeria. International Journal of Social Sciences, University of Uyo, Faculty of Social Sciences, Nigeria, 12(2), 118–131. http://ijss.com.ng/index.php/ijss/article/view/7
FAO UN. (2018). Guidance on spatial technologies for disaster risk management in aquaculture (J. Aguilar-Manjarrez, L. C. Wickliffe, & A. Dean, Eds.). http://www.fao.org/3/CA2368EN/ca2368en.pdf
Fatemi, F., Ardalan, A., Aguirre, B., Mansouri, N., & Mohammadfam, I. (2017). Social vulnerability indicators in disasters: Findings from a systematic review. International Journal of Disaster Risk Reduction, 22, 219–227. https://doi.org/10.1016/J.IJDRR.2016.09.006
Fekete, A. (2009). Validation of a social vulnerability index in context to river-floods in Germany. Natural Hazards and Earth System Sciences, 9(2), 393–403. https://doi.org/10.5194/nhess-9-393-2009
Flanagan, B. E., Gregory, E. W., Hallisey, E. J., Heitgerd, J. L., & Lewis, B. (2011). A Social Vulnerability Index for Disaster Management. Journal of Homeland Security and Emergency Management, 8(1). https://doi.org/10.2202/1547-7355.1792
Frigerio, I., Carnelli, F., Cabinio, M., & De Amicis, M. (2018). Spatiotemporal Pattern of Social Vulnerability in Italy. International Journal of Disaster Risk Science, 9(2), 249–262. https://doi.org/10.1007/s13753-018-0168-7
Frigerio, I., Ventura, S., Strigaro, D., Mattavelli, M., De Amicis, M., Mugnano, S., & Boffi, M. (2016). A GIS-based approach to identify the spatial variability of social vulnerability to seismic hazard in Italy. In Applied Geography (Vol. 74, pp. 12–22). https://doi.org/10.1016/j.apgeog.2016.06.014
Guillard-Gonçalves, C., Cutter, S. L., Emrich, C. T., & Zêzere, J. L. (2015). Application of Social Vulnerability Index (SoVI) and delineation of natural risk zones in Greater Lisbon, Portugal. Journal of Risk Research, 18(5), 651–674. https://doi.org/10.1080/13669877.2014.910689
Haraguchi, M., & Lall, U. (2019). Concepts, Framework, and Policy tools for Disaster Risk Management: Lingking with CLimate Change and Sustainable Development. In M. Nagao, J. L. Broadhurst, S. Edusah, & K. G. Awere (Eds.), Sustainable Development in Africa: Concepts and Methodological Approaches (5). Spears Media Press LLC.
Holand, I. S., Lujala, P., & Rød, J. K. (2011). Social vulnerability assessment for Norway: A quantitative approach. Norsk Geografisk Tidsskrift - Norwegian Journal of Geography, 65(1), 1–17. https://doi.org/10.1080/00291951.2010.550167
Jensen, C. S., Pedersen, T. B., & Thomsen, C. (2010). Multidimensional Databases and Data Warehousing. In M. T. (University ofWaterloo) Özsu (Ed.), Synthesis Lectures on Data Management (Vol. 2, Number 1). Morgan & Claypool Publishers series. https://doi.org/10.2200/s00299ed1v01y201009dtm009
Katic, K. (2017). SOCIAL VULNERABILITY ASSESSMENT TOOLS FOR CLIMATE CHANGE AND DRR PROGRAMMING: A Guide to Practitioners (Duska Tomanovic, Ed.). United Nations Development Programme (UNDP).
Khan, S. (2012). Vulnerability assessments and their planning implications: a case study of the Hutt Valley, New Zealand. Natural Hazards, 64, 1587–1607. https://doi.org/10.1007/s11069-012-0327-x
Kienberger, S., Blaschke, T., Rukhe, •, Zaidi, Z., Kienberger, S., Blaschke, Á. T., Blaschke, T., & Zaidi, R. Z. (2013). A framework for spatio-temporal scales and concepts from different disciplines: the “vulnerability cube.” Natural Hazards, 68, 1343–1369. https://doi.org/10.1007/s11069-012-0513-x
Kim, J., Tae-Hyoung, ·, & Gim, T. (2020). Assessment of social vulnerability to floods on Java, Indonesia. Natural Hazards, 102, 101–114. https://doi.org/10.1007/s11069-020-03912-1
Koks, E. E., Jongman, B., Husby, T. G., & Botzen, W. J. W. (2015). Combining hazard, exposure and social vulnerability to provide lessons for flood risk management. Environmental Science and Policy, 47, 42–52. https://doi.org/10.1016/j.envsci.2014.10.013
L., R., Schroter, D., & Glade, T. (2013). Conceptual Frameworks of Vulnerability Assessments for Natural Disasters Reduction. In Approaches to Disaster Management - Examining the Implications of Hazards, Emergencies and Disasters (1). InTech. https://doi.org/10.5772/55538
Lei, Y., Jing’ai Wang, •, Yue, Y., Zhou, H., Yin, W., Lei, Y., Wang, Á. J., Yue, Á. Y., Yin, Á. W., & Zhou, H. (2014). Rethinking the relationships of vulnerability, resilience, and adaptation from a disaster risk perspective. Natural Hazards, 70, 609–627. https://doi.org/10.1007/s11069-013-0831-7
Lianxiao, & Morimoto, T. (2019). Spatial analysis of social vulnerability to floods based on the MOVE framework and information entropy method: Case study of Katsushika Ward, Tokyo. Sustainability (Switzerland), 11(2). https://doi.org/10.3390/su11020529
Martins, V. N., e Silva, D. S., & Cabral, P. (2012). Social vulnerability assessment to seismic risk using multicriteria analysis: the case study of Vila Franca do Campo (São Miguel Island, Azores, Portugal). Natural Hazards, 62(2), 385–404. https://doi.org/10.1007/s11069-012-0084-x
Martins, V. N., Sousa, D., • S., Cabral, P., Silva, D. S. E., & Cabral, P. (2012). Social vulnerability assessment to seismic risk using multicriteria analysis: the case study of Vila Franca do Campo (São Miguel Island, Azores, Portugal). 62, 385–404. https://doi.org/10.1007/s11069-012-0084-x
Mavhura, E., Manyena, B., & Collins, A. E. (2017). An approach for measuring social vulnerability in context: The case of flood hazards in Muzarabani district, Zimbabwe. Geoforum, 86, 103–117. https://doi.org/10.1016/J.GEOFORUM.2017.09.008
Mwale, F. D., Adeloye, A. J., & Beevers, L. (2015). Quantifying vulnerability of rural communities to flooding in SSA: A contemporary disaster management perspective applied to the Lower Shire Valley, Malawi. International Journal of Disaster Risk Reduction, 12, 172–187. https://doi.org/10.1016/j.ijdrr.2015.01.003
Nelson, J. K., & Brewer, C. A. (2017). Evaluating data stability in aggregation structures across spatial scales: revisiting the modifiable areal unit problem. Cartography and Geographic Information Science, 44(1). https://doi.org/10.1080/15230406.2015.1093431
Nelson, K. S., Abkowitz, M. D., & Camp, J. V. (2015). A method for creating high resolution maps of social vulnerability in the context of environmental hazards. Applied Geography, 63, 89–100. https://doi.org/10.1016/j.apgeog.2015.06.011
Sarkar, S., Taraphder, U., Datta, S., Swain, S. P., & Saikhom, D. (2017). Multivariate Statistical Data Analysis-Principal Component Analysis (PCA). International Journal of Livestock Research, 7(5), 60. https://doi.org/10.5455/ijlr.20170415115235
Sboui, T., Bédard, Y., Brodeur, J., & Badard, T. (2007). A conceptual framework to support semantic interoperability of geospatial datacubes. International Conference on Conceptual Modeling: Advances in Conceptual Modeling - Foundations and Applications, 4802 LNCS, 378–387. https://doi.org/10.1007/978-3-540-76292-8_44
Siagian, T. H., Purhadi, P., Suhartono, S., & Ritonga, H. (2014). Social vulnerability to natural hazards in Indonesia: driving factors and policy implications. Natural Hazards, 70(2), 1603–1617. https://doi.org/10.1007/s11069-013-0888-3
Stanturf, J. A., Goodrick, S. L., Warren, M. L., Charnley, S., & Stegall, C. M. (2015a). Social Vulnerability and Ebola Virus Disease in Rural Liberia. PLOS ONE, 10(9). https://doi.org/10.1371/journal.pone.0137208
Stanturf, J. A., Goodrick, S. L., Warren, M. L., Charnley, S., & Stegall, C. M. (2015b). Social Vulnerability and Ebola Virus Disease in Rural Liberia. PLOS ONE, 10(9). https://doi.org/10.1371/journal.pone.0137208
Tate, E. (2012). Uncertainty analysis for a social vulnerability. Annals of the Association of American Geographers. https://www.tandfonline.com/doi/pdf/10.1080/00045608.2012.700616?needAccess=true
Thomalla, F., Downing, T., Spanger-Siegfried, E., Han, G., & Rockström, J. (2006). Reducing hazard vulnerability: towards a common approach between disaster risk reduction and climate adaptation. Disasters, 30(1), 39–48. https://doi.org/10.1111/j.1467-9523.2006.00305.x
Török, I., Török, & Ibolya. (2018). Qualitative Assessment of Social Vulnerability to Flood Hazards in Romania. Sustainability, 10(10), 3780. https://doi.org/10.3390/su10103780
Van Zandt, S., Peacock, W. G., Henry, D. W., Grover, H., Highfield, W. E., & Brody, S. D. (2012). Mapping social vulnerability to enhance housing and neighborhood resilience. Housing Policy Debate, 22(1), 29–55. https://doi.org/10.1080/10511482.2011.624528
Vincent, K. (2004). Creating an Index of Social Vulnerability to Climate Change in Africa. https://www.researchgate.net/publication/228809913
WHO. (2020). Modes of transmission of virus causing COVID-19: implications for IPC precaution recommendations. https://doi.org/10.3201/eid2606.200239
Willis, I., & Fitton, J. (2016). A review of multivariate social vulnerability methodologies: a case study of the River Parrett catchment, UK. Natural Hazards and Earth System Sciences, 16(6), 1387–1399. https://doi.org/10.5194/nhess-16-1387-2016
Wood, S., Hyman, G., Deichmann, U., Barona, E., Tenorio, R., Guo, Z., Castano, S., Rivera, O., Diaz, E., & Marin, J. (2010). Community variations in social vulnerability to Cascadia-related tsunamis in the U.S. Pacific Northwest. Natural Hazards, 52, 369–389. https://link.springer.com/article/10.1007/s11069-009-9376-1
Yelland, P. M. (2013). Rolling Up Random Variables in Data Cubes. https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/41652.pdf
Yoon, D. K. (2012). Assessment of social vulnerability to natural disasters: a comparative study. Natural Hazards, 63(2), 823–843. https://doi.org/10.1007/s11069-012-0189-2
Zebardast, E. (2013). Constructing a social vulnerability index to earthquake hazards using a hybrid factor analysis and analytic network process (F’ANP) model. Natural Hazards, 65, 1331–1359–1331–1359. https://doi.org/10.1007/s11069-012-0412-1
Zhang, Y.-L., & You, W.-J. (2014). Social vulnerability to floods: a case study of Huaihe River Basin. Natural Hazards, 71(3), 2113–2125. https://doi.org/10.1007/s11069-013-0996-0
Zhou, Y., Liu, Y., Wu, W., & Li, N. (2015). Integrated risk assessment of multi-hazards in China. Natural Hazards, 78, 257–280. https://doi.org/10.1007/s11069-015-1713-y