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題名 台灣高齡化對詐騙案發生率的影響
The Impact of Population Aging on Fraud Incident Rates – Evidence from Taiwan作者 林園喬
Lin, Yuan-Chiao貢獻者 黃智聰
Huang, Jr-Tsung
林園喬
Lin, Yuan-Chiao關鍵詞 高齡化
詐騙案件發生率
空間自迴歸模型
數位素養
防詐政策
Aging
Fraud Incidence Rate
Spatial Autoregressive Model
Digital Literacy
Anti-Fraud Policy日期 2025 上傳時間 4-Aug-2025 14:47:22 (UTC+8) 摘要 隨著台灣社會邁入超高齡化階段，詐騙案件發生率亦呈現顯著上升趨勢，成為當前亟需關注之社會問題。高齡者因認知能力下降、數位適應力不足及社會孤立，易淪為詐騙犯罪之高風險受害群體。為釐清高齡化與詐騙案件間之關聯性，本研究以2011年至2023年間台灣20個縣市資料為樣本，採用空間自迴歸模型（Spatial Autoregressive Model, SAR）進行實證分析，探討高齡人口比例對詐騙案件發生率之影響，並控制失業率、獨居老人數、破獲率、志工參與程度、教育程度、網路使用率、儲蓄率及都市化程度等變數。 研究結果顯示，高齡人口比例對詐騙案件發生率具有顯著正向影響，驗證高齡化社會下老年族群詐騙風險確實升高。此外，失業率與破獲率亦與詐騙案件具顯著關聯，顯示經濟因素與執法成效對詐騙發生具重要影響。空間自我相關係數亦達顯著水準，反映詐騙案件存在明顯區域擴散效應。 本研究結果可為政府制定防詐政策提供實證依據，建議強化高齡者數位素養培訓、擴大社區關懷網絡，並提升警政破案能力，以降低高齡化社會中詐騙案件之發生風險。
As Taiwan transitions into a super-aged society, the incidence rate of fraud cases has shown a significant upward trend, becoming an urgent social issue. Elderly individuals, due to cognitive decline, limited digital literacy, and social isolation, are highly vulnerable to fraud victimization. To clarify the relationship between aging and fraud incidence, this study employs a Spatial Autoregressive Model (SAR) to analyze panel data from 20 counties in Taiwan from 2011 to 2023. The model examines the impact of the elderly population ratio on fraud incidence, while controlling for unemployment rate, number of solitary elderly under social care, fraud case clearance rate, volunteer participation, educational attainment, internet usage rate, savings rate, and degree of urbanization. The empirical results indicate that the proportion of elderly population has a significant positive effect on fraud incidence, confirming the elevated fraud risk among the elderly in an aging society. Additionally, unemployment rate and clearance rate are also significantly associated with fraud incidence, highlighting the influence of economic factors and law enforcement effectiveness. The spatial autoregressive coefficient is significant, suggesting a clear spatial diffusion effect of fraud cases. This study provides empirical evidence to inform government anti-fraud policies. It is recommended to enhance digital literacy training for the elderly, expand community support networks, and strengthen law enforcement capacity to reduce the risk of fraud in an aging society.參考文獻 一、中文部分 邱貴玲（2005），《企業志工發展趨勢研究－各國政策比較及國內、外企業志工個案探討》。台北市：行政院青年輔導委員會委託研究報告，頁45。 二、英文文獻 Anderson, Elijah (1999), Code of the Street: Decency, Violence, and the Moral Life of the Inner City. New York: W. W. Norton & Company. Becker, Gary S. (1968), “Crime and Punishment: An Economic Approach.” Journal of Political Economy, 76(2), 169–217. Blackwell, Calvin, Norman Maynard, James Malm, Mark Pyles, Marcia Snyder, and Mark Witte (2024), “Who Gets Duped? The Impact of Education on Fraud Detection in an Investment Task.” Journal of Economics and Finance, 48(3), 734–753. Braga, Anthony A., David Weisburd, and Brandon Turchan (2018), “Focused Deterrence Strategies Effects on Crime: A Systematic Review.” Campbell Systematic Reviews, 14(1), 1–75. Burnes, David, Charles R. Henderson Jr., Christine Sheppard, Rebecca Zhao, Karl Pillemer, and Mark S. Lachs (2022), “Prevalence of Financial Fraud and Scams Among Older Adults in the United States: A Systematic Review and Meta Analysis.” Journal of Elder Abuse & Neglect, 34(1), 1–26. Retrieved from https://doi.org/10.1080/08946566.2022.2032352 Button, Mark, Les Johnston, Kwabena Frimpong, and Geoff Smith (2007), “New Directions in Policing Fraud: The Emergence of the Counter Fraud Specialist in the United Kingdom.” International Journal of the Sociology of Law, 35(4), 192–208. Button, Mark., Chris Lewis, and Jacki Tapley (2009), Fraud Typologies and the Victims of Fraud: Literature Review. London: National Fraud Authority. Carvalho, Leandro S., Silvia Prina, and Justin Sydnor (2016), “The Effect of Saving on Risk Attitudes and Intertemporal Choices.” Journal of Development Economics, 120, 41–52. Retrieved from https://doi.org/10.1016/j.jdeveco.2016.01.001 Chalfin, Aaron and Jusin McCrary (2017), “Criminal Deterrence: A Review of the Literature.” Journal of Economic Literature, 55(1), 5–48. Chen, Hongliang, Yunsha Pu, and David Atkin (2023), “Migration Stress, Risky Internet Uses, and Scam Victimization: An Empirical Study Among Chinese Migrant Workers.” Telematics and Informatics, 83, 102022. Retrieved from https://doi.org/10.1016/j.tele.2023.102022 Clarke, Ronald V. and John E. Eck (2005), Crime Analysis for Problem Solvers in 60 Small Steps. Washington DC: U.S. Department of Justice, Office of Community Oriented Policing Services. Cobb, Sidney (1976), “Social Support as a Moderator of Life Stress.” Psychosomatic Medicine, 38, 300–314. Cohen, Lawrence E. and Marcus Felson (1979), “Social Change and Crime Rate Trends: A Routine Activity Approach.” American Sociological Review, 44, 588–608. DeLiema, Marguerite, Martha Deevy, Annamaria Lusardi, and Olivia S. Mitchell (2018), “Financial Fraud Among Older Americans: Evidence and Implications.” Journals of Gerontology: Social Sciences, 75(4), 861–868. Dodel, Matias and Gustavo Mesch (2018), “Inequality in Digital Skills and the Adoption of Online Safety Behaviors.” Information Communication & Society, 21(5), 712–728. Retrieved from https://doi.org/10.1080/1369118X.2018.1428652 Donald, F. Norris (2021), “A Look at Local Government Cybersecurity in 2020.” PM Magazine. Retrieved from https://icma.org/articles/pm-magazine/look-local-government-cybersecurity-2020 Elegbe, Ifeoluwa Stella (2024), “Cybercrime Victimization: Online Routine Behaviors, Guardianship, and Identity Theft Victimization in a Nationally Reflective Sample.” Master’s thesis, Georgia Southern University. Retrieved from https://digitalcommons.georgiasouthern.edu/etd/2759/ Engels, Christian, Kamlesh Kumar and Dennis Philip (2020), “Financial Literacy and Fraud Detection.” European Journal of Finance, 26(2), 1-23. Federal Trade Commission (FTC) (2023), Consumer Sentinel Network Data Book 2022. Washington DC: Federal Trade Commission. Financial Conduct Authority (2024), Guidance for Firms that Enables a Risk-Based Approach to Payments. London: Financial Conduct Authority. Friedman, Milton (1957), A Theory of the Consumption Function. Princeton, New Jersey: Princeton University Press. House, James S. (1981), Work Stress and Social Support. Boston: Addison-Wesley Publishing Company. James, Bryan D., Patricia A. Boyle, and David A. Bennett (2014), “Correlates of Susceptibility to Scams in Older Adults Without Dementia.” Journal of Elder Abuse & Neglect, 26(2), 107–122. Kadoya, Yoshihiko, Mostafa Saidur Rahim Khan, Jin Narumoto, and Satoshi Watanabe (2021), “Who Is Next? A Study on Victims of Financial Fraud in Japan.” Frontiers in Psychology, 12, 1-13. Retrieved from https://doi.org/10.3389/fpsyg.2021.649565 Karlan, Dean, Aishwarya Lakshmi Ratan, and Jonathan Zinman (2014), “Savings by and for the Poor: A Research Review and Agenda.” Review of Income and Wealth, 60(1), 36–78. Levine, Timothy R. (2014), “Truth-Default Theory (TDT): A Theory of Human Deception and Deception Detection.” Journal of Language and Social Psychology, 33(4), 378–392. Loewenstein, George F., Elke U. Weber, Christopher K. Hsee, and Ned Welch (2001), “Risk as Feelings.” Psychological Bulletin, 127(2), 267–286. Modic, David and Stephen E. G. Lea (2013), “Scam Compliance and the Psychology of Persuasion.” Journal of Applied Social Psychology, 43(7), 1360–1374. Nagin, Daniel S. (2013), “Deterrence in the Twenty-First Century.” Crime and Justice, 42(1), 199–263. Perry, Vanessa G. and Marlene D. Morris (2005), “Who Is in Control? The Role of Self-Perception, Knowledge, and Income in Explaining Consumer Financial Behavior.” Journal of Consumer Affairs, 39(2), 299–313. Retrieved from https://doi.org/10.1111/j.1745-6606.2005.00016.x Reyns, Bradford W. (2013), “Online Routines and Identity Theft Victimization: Further Expanding Routine Activity Theory Beyond Direct-Contact Offenses.” Journal of Research in Crime and Delinquency, 50(2), 216–238. Shaw, Clifford R. and Henry D. McKay (1942), Juvenile Delinquency and Urban Areas. Chicago: University of Chicago Press. Temple, Jeromey (2007), “Older People and Credit Card Fraud.” Trends & Issues in Crime and Criminal Justice, No. 343. Retrieved from https://www.aic.gov.au/publications/tandi/tandi343 Van Wyk, Judy and Karen A. Mason (2001), “Investigating Vulnerability and Reporting Behavior for Consumer Fraud Victimization: Opportunity as a Social Aspect of Age.” The Journal of Contemporary Criminal Justice, 17(4), 328–345. Wang, Donghui, Yuwei Duan, and Yongai Jin (2024), “Navigating Online Perils: Socioeconomic Status, Online Activity Lifestyles, and Online Fraud Targeting and Victimization of Old Adults in China.” Preprint published on SSRN. Retrieved from https://ssrn.com/abstract=4835478 Wei Li, Ming Peng, and Weixing Wu (2021), “Financial Literacy and Fraud Detection—Evidence from China.” International Review of Economics & Finance,76, 478-494. Zhang, Chunxia, Lin Liu, Suhong Zhou, Jiaxin Feng, Jianguo Chen, and Luzi Xiao (2024), “Contact Fraud Victimization among Urban Seniors: An Analysis of Multilevel Influencing Factors.” Computers in Human Behavior, 151, 107271. Retrieved from https://doi.org/10.1016/j.chb.2024.107271 三、 網站資料與數據來源 中華民國統計資訊網，縣市重要指標，取自網址: https://winstacity.dgbas.gov.tw/DgbasWeb/ZWeb/StateFile_ZWeb.aspx 行政院主計總處，主計總處查詢系統，取自網址: https://www.stat.gov.tw/cl.aspx?n=3654 行政院內政部，戶政司全球資訊網，取自網址: https://www.ris.gov.tw/app/portal/346 描述 碩士
國立政治大學
行政管理碩士學程
112921080資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112921080 資料類型 thesis dc.contributor.advisor 黃智聰 zh_TW dc.contributor.advisor Huang, Jr-Tsung en_US dc.contributor.author (Authors) 林園喬 zh_TW dc.contributor.author (Authors) Lin, Yuan-Chiao en_US dc.creator (作者) 林園喬 zh_TW dc.creator (作者) Lin, Yuan-Chiao en_US dc.date (日期) 2025 en_US dc.date.accessioned 4-Aug-2025 14:47:22 (UTC+8) - dc.date.available 4-Aug-2025 14:47:22 (UTC+8) - dc.date.issued (上傳時間) 4-Aug-2025 14:47:22 (UTC+8) - dc.identifier (Other Identifiers) G0112921080 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158645 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 行政管理碩士學程 zh_TW dc.description (描述) 112921080 zh_TW dc.description.abstract (摘要) 隨著台灣社會邁入超高齡化階段，詐騙案件發生率亦呈現顯著上升趨勢，成為當前亟需關注之社會問題。高齡者因認知能力下降、數位適應力不足及社會孤立，易淪為詐騙犯罪之高風險受害群體。為釐清高齡化與詐騙案件間之關聯性，本研究以2011年至2023年間台灣20個縣市資料為樣本，採用空間自迴歸模型（Spatial Autoregressive Model, SAR）進行實證分析，探討高齡人口比例對詐騙案件發生率之影響，並控制失業率、獨居老人數、破獲率、志工參與程度、教育程度、網路使用率、儲蓄率及都市化程度等變數。 研究結果顯示，高齡人口比例對詐騙案件發生率具有顯著正向影響，驗證高齡化社會下老年族群詐騙風險確實升高。此外，失業率與破獲率亦與詐騙案件具顯著關聯，顯示經濟因素與執法成效對詐騙發生具重要影響。空間自我相關係數亦達顯著水準，反映詐騙案件存在明顯區域擴散效應。 本研究結果可為政府制定防詐政策提供實證依據，建議強化高齡者數位素養培訓、擴大社區關懷網絡，並提升警政破案能力，以降低高齡化社會中詐騙案件之發生風險。 zh_TW dc.description.abstract (摘要) As Taiwan transitions into a super-aged society, the incidence rate of fraud cases has shown a significant upward trend, becoming an urgent social issue. Elderly individuals, due to cognitive decline, limited digital literacy, and social isolation, are highly vulnerable to fraud victimization. To clarify the relationship between aging and fraud incidence, this study employs a Spatial Autoregressive Model (SAR) to analyze panel data from 20 counties in Taiwan from 2011 to 2023. The model examines the impact of the elderly population ratio on fraud incidence, while controlling for unemployment rate, number of solitary elderly under social care, fraud case clearance rate, volunteer participation, educational attainment, internet usage rate, savings rate, and degree of urbanization. The empirical results indicate that the proportion of elderly population has a significant positive effect on fraud incidence, confirming the elevated fraud risk among the elderly in an aging society. Additionally, unemployment rate and clearance rate are also significantly associated with fraud incidence, highlighting the influence of economic factors and law enforcement effectiveness. The spatial autoregressive coefficient is significant, suggesting a clear spatial diffusion effect of fraud cases. This study provides empirical evidence to inform government anti-fraud policies. It is recommended to enhance digital literacy training for the elderly, expand community support networks, and strengthen law enforcement capacity to reduce the risk of fraud in an aging society. en_US dc.description.tableofcontents 第一章 緒論 8 第一節 研究背景與動機 8 第二節 研究目的 10 第三節 研究範圍與方法 11 第四節 研究架構與流程 12 第二章 文獻回顧 15 第一節 高齡化與詐騙案件的全球趨勢 15 第二節 高齡化程度與詐騙案發生率之關聯性 17 第三節 其他社會經濟因素與詐騙案件發生率之關聯性 18 第三章 現況分析 30 第一節 台灣詐騙案增加現況 30 第二節 台灣高齡化現況 33 第四章 研究方法 36 第一節 空間計量模型 36 第二節 變數說明 37 第五章 實證分析 50 第一節 空間計量相關檢定結果 50 第二節 實證模型估計結果 55 第三節 變數解釋分析 61 第六章 結論與建議 71 第一節 研究結論 71 第二節 政策建議 72 第三節 研究限制 74 第四節 未來展望 76 參考文獻 78 zh_TW dc.format.extent 1820558 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112921080 en_US dc.subject (關鍵詞) 高齡化 zh_TW dc.subject (關鍵詞) 詐騙案件發生率 zh_TW dc.subject (關鍵詞) 空間自迴歸模型 zh_TW dc.subject (關鍵詞) 數位素養 zh_TW dc.subject (關鍵詞) 防詐政策 zh_TW dc.subject (關鍵詞) Aging en_US dc.subject (關鍵詞) Fraud Incidence Rate en_US dc.subject (關鍵詞) Spatial Autoregressive Model en_US dc.subject (關鍵詞) Digital Literacy en_US dc.subject (關鍵詞) Anti-Fraud Policy en_US dc.title (題名) 台灣高齡化對詐騙案發生率的影響 zh_TW dc.title (題名) The Impact of Population Aging on Fraud Incident Rates – Evidence from Taiwan en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文部分 邱貴玲（2005），《企業志工發展趨勢研究－各國政策比較及國內、外企業志工個案探討》。台北市：行政院青年輔導委員會委託研究報告，頁45。 二、英文文獻 Anderson, Elijah (1999), Code of the Street: Decency, Violence, and the Moral Life of the Inner City. New York: W. W. Norton & Company. Becker, Gary S. (1968), “Crime and Punishment: An Economic Approach.” Journal of Political Economy, 76(2), 169–217. Blackwell, Calvin, Norman Maynard, James Malm, Mark Pyles, Marcia Snyder, and Mark Witte (2024), “Who Gets Duped? The Impact of Education on Fraud Detection in an Investment Task.” Journal of Economics and Finance, 48(3), 734–753. Braga, Anthony A., David Weisburd, and Brandon Turchan (2018), “Focused Deterrence Strategies Effects on Crime: A Systematic Review.” Campbell Systematic Reviews, 14(1), 1–75. Burnes, David, Charles R. Henderson Jr., Christine Sheppard, Rebecca Zhao, Karl Pillemer, and Mark S. Lachs (2022), “Prevalence of Financial Fraud and Scams Among Older Adults in the United States: A Systematic Review and Meta Analysis.” Journal of Elder Abuse & Neglect, 34(1), 1–26. Retrieved from https://doi.org/10.1080/08946566.2022.2032352 Button, Mark, Les Johnston, Kwabena Frimpong, and Geoff Smith (2007), “New Directions in Policing Fraud: The Emergence of the Counter Fraud Specialist in the United Kingdom.” International Journal of the Sociology of Law, 35(4), 192–208. Button, Mark., Chris Lewis, and Jacki Tapley (2009), Fraud Typologies and the Victims of Fraud: Literature Review. London: National Fraud Authority. Carvalho, Leandro S., Silvia Prina, and Justin Sydnor (2016), “The Effect of Saving on Risk Attitudes and Intertemporal Choices.” Journal of Development Economics, 120, 41–52. Retrieved from https://doi.org/10.1016/j.jdeveco.2016.01.001 Chalfin, Aaron and Jusin McCrary (2017), “Criminal Deterrence: A Review of the Literature.” Journal of Economic Literature, 55(1), 5–48. Chen, Hongliang, Yunsha Pu, and David Atkin (2023), “Migration Stress, Risky Internet Uses, and Scam Victimization: An Empirical Study Among Chinese Migrant Workers.” Telematics and Informatics, 83, 102022. Retrieved from https://doi.org/10.1016/j.tele.2023.102022 Clarke, Ronald V. and John E. Eck (2005), Crime Analysis for Problem Solvers in 60 Small Steps. Washington DC: U.S. Department of Justice, Office of Community Oriented Policing Services. Cobb, Sidney (1976), “Social Support as a Moderator of Life Stress.” Psychosomatic Medicine, 38, 300–314. Cohen, Lawrence E. and Marcus Felson (1979), “Social Change and Crime Rate Trends: A Routine Activity Approach.” American Sociological Review, 44, 588–608. DeLiema, Marguerite, Martha Deevy, Annamaria Lusardi, and Olivia S. Mitchell (2018), “Financial Fraud Among Older Americans: Evidence and Implications.” Journals of Gerontology: Social Sciences, 75(4), 861–868. Dodel, Matias and Gustavo Mesch (2018), “Inequality in Digital Skills and the Adoption of Online Safety Behaviors.” Information Communication & Society, 21(5), 712–728. Retrieved from https://doi.org/10.1080/1369118X.2018.1428652 Donald, F. Norris (2021), “A Look at Local Government Cybersecurity in 2020.” PM Magazine. Retrieved from https://icma.org/articles/pm-magazine/look-local-government-cybersecurity-2020 Elegbe, Ifeoluwa Stella (2024), “Cybercrime Victimization: Online Routine Behaviors, Guardianship, and Identity Theft Victimization in a Nationally Reflective Sample.” Master’s thesis, Georgia Southern University. Retrieved from https://digitalcommons.georgiasouthern.edu/etd/2759/ Engels, Christian, Kamlesh Kumar and Dennis Philip (2020), “Financial Literacy and Fraud Detection.” European Journal of Finance, 26(2), 1-23. Federal Trade Commission (FTC) (2023), Consumer Sentinel Network Data Book 2022. Washington DC: Federal Trade Commission. Financial Conduct Authority (2024), Guidance for Firms that Enables a Risk-Based Approach to Payments. London: Financial Conduct Authority. Friedman, Milton (1957), A Theory of the Consumption Function. Princeton, New Jersey: Princeton University Press. House, James S. (1981), Work Stress and Social Support. Boston: Addison-Wesley Publishing Company. James, Bryan D., Patricia A. Boyle, and David A. Bennett (2014), “Correlates of Susceptibility to Scams in Older Adults Without Dementia.” Journal of Elder Abuse & Neglect, 26(2), 107–122. Kadoya, Yoshihiko, Mostafa Saidur Rahim Khan, Jin Narumoto, and Satoshi Watanabe (2021), “Who Is Next? A Study on Victims of Financial Fraud in Japan.” Frontiers in Psychology, 12, 1-13. Retrieved from https://doi.org/10.3389/fpsyg.2021.649565 Karlan, Dean, Aishwarya Lakshmi Ratan, and Jonathan Zinman (2014), “Savings by and for the Poor: A Research Review and Agenda.” Review of Income and Wealth, 60(1), 36–78. Levine, Timothy R. (2014), “Truth-Default Theory (TDT): A Theory of Human Deception and Deception Detection.” Journal of Language and Social Psychology, 33(4), 378–392. Loewenstein, George F., Elke U. Weber, Christopher K. Hsee, and Ned Welch (2001), “Risk as Feelings.” Psychological Bulletin, 127(2), 267–286. Modic, David and Stephen E. G. Lea (2013), “Scam Compliance and the Psychology of Persuasion.” Journal of Applied Social Psychology, 43(7), 1360–1374. Nagin, Daniel S. (2013), “Deterrence in the Twenty-First Century.” Crime and Justice, 42(1), 199–263. Perry, Vanessa G. and Marlene D. Morris (2005), “Who Is in Control? The Role of Self-Perception, Knowledge, and Income in Explaining Consumer Financial Behavior.” Journal of Consumer Affairs, 39(2), 299–313. Retrieved from https://doi.org/10.1111/j.1745-6606.2005.00016.x Reyns, Bradford W. (2013), “Online Routines and Identity Theft Victimization: Further Expanding Routine Activity Theory Beyond Direct-Contact Offenses.” Journal of Research in Crime and Delinquency, 50(2), 216–238. Shaw, Clifford R. and Henry D. McKay (1942), Juvenile Delinquency and Urban Areas. Chicago: University of Chicago Press. Temple, Jeromey (2007), “Older People and Credit Card Fraud.” Trends & Issues in Crime and Criminal Justice, No. 343. Retrieved from https://www.aic.gov.au/publications/tandi/tandi343 Van Wyk, Judy and Karen A. Mason (2001), “Investigating Vulnerability and Reporting Behavior for Consumer Fraud Victimization: Opportunity as a Social Aspect of Age.” The Journal of Contemporary Criminal Justice, 17(4), 328–345. Wang, Donghui, Yuwei Duan, and Yongai Jin (2024), “Navigating Online Perils: Socioeconomic Status, Online Activity Lifestyles, and Online Fraud Targeting and Victimization of Old Adults in China.” Preprint published on SSRN. Retrieved from https://ssrn.com/abstract=4835478 Wei Li, Ming Peng, and Weixing Wu (2021), “Financial Literacy and Fraud Detection—Evidence from China.” International Review of Economics & Finance,76, 478-494. Zhang, Chunxia, Lin Liu, Suhong Zhou, Jiaxin Feng, Jianguo Chen, and Luzi Xiao (2024), “Contact Fraud Victimization among Urban Seniors: An Analysis of Multilevel Influencing Factors.” Computers in Human Behavior, 151, 107271. Retrieved from https://doi.org/10.1016/j.chb.2024.107271 三、 網站資料與數據來源 中華民國統計資訊網，縣市重要指標，取自網址: https://winstacity.dgbas.gov.tw/DgbasWeb/ZWeb/StateFile_ZWeb.aspx 行政院主計總處，主計總處查詢系統，取自網址: https://www.stat.gov.tw/cl.aspx?n=3654 行政院內政部，戶政司全球資訊網，取自網址: https://www.ris.gov.tw/app/portal/346 zh_TW
