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題名 信用貸款額度與利率如何滿足消費者需求-以國軍輔導理財貸款為例
Using unsecured loans and interest rates to meet consumer needs: A case of employee loan programs in the military作者 蔚鎔璞
Yu, Rong-Pu貢獻者 朱琇妍
Chu, Shiou-Yen
蔚鎔璞
Yu, Rong-Pu關鍵詞 信用貸款
貸款屬性偏好
曲線擬合
效用函數
選擇式聯合分析
金融常識
Unsecured Loan
Loan attribute preferences
Curve fitting
Utility function
Conjoint analysis
Financial literacy日期 2024 上傳時間 4-Feb-2025 15:59:15 (UTC+8) 摘要 本研究聚焦於國軍官兵對信用貸款方案的需求與偏好，透過問卷調查與統計分析探討貸款額度、利率、還款年限、提供行庫及提早還款機制等屬性對消費者選擇的影響。本研究共回收398份有效問卷，並採用多項式羅吉斯回歸及CBC選擇式聯合分析進行資料處理，結合集群分析探討不同偏好群體的特性。同時，利用曲線擬合技術構建效用函數模型，分析貸款屬性與效用值之間的關係，精確預測消費者的選擇行為。結果顯示，貸款利率與還款年限為影響消費者選擇的關鍵因素，其中低利率與長期還款方案最受青睞。 研究發現消費者對貸款方案的偏好主要受產品自身屬性驅動，與個人背景如階級等變項無顯著關係。調查結果亦顯示，受訪者在金融常識方面仍有提升空間，特別是在貸款產品的選擇與決策上，這表明加強金融教育與資訊普及能進一步優化其決策能力。本研究依據實證結果提出多項建議，包括提升貸款方案的彈性與多樣性、進一步推廣金融教育，以及針對不同需求群體優化貸款方案設計，以期滿足官兵的多元資金需求並降低財務風險。
This study focuses on the preferences and demands of military personnel regarding personal loan programs. Using a survey and statistical analysis, it investigates how loan attributes such as amount, interest rate, repayment term, lending institution, and early repayment options influence consumer choices. A total of 398 valid questionnaires were collected, and the data were analyzed using multinomial logistic regression, choice-based conjoint (CBC) analysis, and cluster analysis to identify distinct preference groups. Additionally, utility function models were constructed through curve fitting techniques to analyze the relationship between loan attributes and utility values, enabling precise prediction of consumer choice behavior. Results indicate that interest rates and repayment terms are the key determinants of consumer preferences, with low-interest and long-term loan options being the most favored. Moreover, consumer preferences are primarily driven by product attributes rather than individual backgrounds such as rank. The findings also reveal room for improvement in respondents' financial literacy, particularly in understanding loan products, highlighting the need for enhanced financial education and information dissemination. Based on empirical results, the study offers recommendations to increase the flexibility and diversity of loan programs, promote financial education, and tailor loan plans to meet diverse consumer needs, ultimately reducing financial risks.參考文獻 壹、中文部分 一、專書 中華民國金融監督管理委員會(2004)。銀行風險管理實務範本：信用風險管理分論及案例彙編。普華永道國際會計師事務所。 黃景泰(2013)。金融人員消費者貸款必修12堂課。財團法人台灣金融研訓院。 二、期刊 王金利(1984)。台灣地區消費者需求形態實證分析：AIDS模型之應用。經濟研究，25，177-195。 陳光、任志良和孫海柱(2005)。最小二乘曲線擬合及Matlab實現。兵工自動化，24(3)，107-108。 三、學位論文 張純真(2006)。消費者偏好與購買行為之因果關係研究。國立台灣大學資訊管理學系碩士論文，未出版，台北。 莊堉蒨(2023)。網路影音平台使用者偏好分析。國立屏東大學國際經營與貿易學系碩士論文。未出版，屏東。 曾冠豪(2018)。以聯合分析探討消費者對汽車貸款商品之偏好。東吳大學企業管理學系碩士論文，未出版，台北。 賴義生(2007)。消費者小額信用貸款授信風險評估之個案研究。國立台北大學國際財務金融碩士論文，未出版，台北。 魏逢辰(2023)。消費者選擇個人信用貸款關鍵因素之研究。東吳大學企業管理學系碩士論文，未出版，台北。 四、網路資料 中華民國銀行商業同業公會全國聯合會(2024)個人信貸信貸主力商品彙整表，2024年10月18日，取自：www.ba.org.tw/FileDownLoad/DownloadList 金融監督管理委員會(2006)。強化金融教育宣導與普及金融知識，2024年10月18日，取自https://www.fsc.gov.tw 財團法人金融聯合徵信中心(2024)。信貸借款人各年齡層與性別交叉狀況的授信金額及利率統計表，2024年10月22日，取自：https://www.jcic.org.tw/main_ch/download_page.aspx?uid=213&pid=190 貳、外文部分 一、專書 Louviere, J., Hensher, A., & Swait, D. (2000). Stated Choice Methods.Cambridge University Press. 二、期刊 Ahmad, I., & Minkarah, I. (1988). Questionnaire survey on bidding in construction. Journal of Management in Engineering, 4(3), 229–243. Bech, M., & Gyrd-Hansen, D. (2005). Effects coding in discrete choice experiments. Health Economics, 14(11), 1079–1083. Bolboacă, S. D., & Jäntschi, L. (2007). Design of experiments: Useful orthogonal arrays for number of experiments from 4 to 16. Entropy, 9(4), 198–232. Chen, Y., Fan, H., & Huang, Y. (2023). The impact of online credit lending model on the public's overspending decision. Advances in Economics. https://doi.org/10.54254/2754-1169/24/20230416 Dobson, K., & Khatri, N. (2000). Cognitive therapy: Looking backward, looking forward. Journal of Clinical Psychology, 56(7), 907–923. de Levie, R. (2000). Curve fitting with least squares. Critical Reviews in Analytical Chemistry, 40(1), 59–74. 10.1080/10408340091164180 Frangos, C., Fragkos, K., Sotiropoulos, I., Manolopoulos, G., & Valvi, A. (2012). Factors affecting customers’ decision for taking out bank loans: A case of Greek customers. Journal of Marketing Research and Case Studies, 2012, Article 927167, 16. Harrison, R., Özayan, A., & Meyers, S. (1998). A conjoint analysis of new food products processed from underutilized small crawfish. Journal of Agricultural and Applied Economics, 30(2), 257–265. Johnson, A., Villanova, D., & Smith, R. (2023). Loan amount versus monthly payments: The effect of loan application formats on consumer borrowing decisions. Journal of Consumer Research, 50(4), 765–786. Norton, J., & Bass, F. (1987) A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products. Management Science, 33, 1069-1086. Pekelman, D., & Sen, S. (1979). Improving prediction in conjoint measurement. Journal of Marketing Research, 16(2), 215–221. Syakur, M., Khotimah, B., Rochman, E., & Satoto, B. (2018). Integration K-means clustering method and elbow method for identification of the best customer profile cluster. IOP Conference Series: Materials Science and Engineering, 336(1), 012017. Wonder, N., Wilhelm, W., & Fewings, D. (2008). The financial rationality of consumer loan choices: Revealed preferences concerning interest rates, down payments, contract length, and rebates. Journal of Consumer Affairs, 42(2), 243–270. 三、網路資料 Consumer Financial Protection Bureau. (2019). Youth financial education curriculum review. Retrieved October 3, 2024, from https://www.consumerfinance.gov 描述 碩士
國立政治大學
行政管理碩士學程
112921319資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112921319 資料類型 thesis dc.contributor.advisor 朱琇妍 zh_TW dc.contributor.advisor Chu, Shiou-Yen en_US dc.contributor.author (Authors) 蔚鎔璞 zh_TW dc.contributor.author (Authors) Yu, Rong-Pu en_US dc.creator (作者) 蔚鎔璞 zh_TW dc.creator (作者) Yu, Rong-Pu en_US dc.date (日期) 2024 en_US dc.date.accessioned 4-Feb-2025 15:59:15 (UTC+8) - dc.date.available 4-Feb-2025 15:59:15 (UTC+8) - dc.date.issued (上傳時間) 4-Feb-2025 15:59:15 (UTC+8) - dc.identifier (Other Identifiers) G0112921319 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/155495 - 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) 112921319 zh_TW dc.description.abstract (摘要) 本研究聚焦於國軍官兵對信用貸款方案的需求與偏好，透過問卷調查與統計分析探討貸款額度、利率、還款年限、提供行庫及提早還款機制等屬性對消費者選擇的影響。本研究共回收398份有效問卷，並採用多項式羅吉斯回歸及CBC選擇式聯合分析進行資料處理，結合集群分析探討不同偏好群體的特性。同時，利用曲線擬合技術構建效用函數模型，分析貸款屬性與效用值之間的關係，精確預測消費者的選擇行為。結果顯示，貸款利率與還款年限為影響消費者選擇的關鍵因素，其中低利率與長期還款方案最受青睞。 研究發現消費者對貸款方案的偏好主要受產品自身屬性驅動，與個人背景如階級等變項無顯著關係。調查結果亦顯示，受訪者在金融常識方面仍有提升空間，特別是在貸款產品的選擇與決策上，這表明加強金融教育與資訊普及能進一步優化其決策能力。本研究依據實證結果提出多項建議，包括提升貸款方案的彈性與多樣性、進一步推廣金融教育，以及針對不同需求群體優化貸款方案設計，以期滿足官兵的多元資金需求並降低財務風險。 zh_TW dc.description.abstract (摘要) This study focuses on the preferences and demands of military personnel regarding personal loan programs. Using a survey and statistical analysis, it investigates how loan attributes such as amount, interest rate, repayment term, lending institution, and early repayment options influence consumer choices. A total of 398 valid questionnaires were collected, and the data were analyzed using multinomial logistic regression, choice-based conjoint (CBC) analysis, and cluster analysis to identify distinct preference groups. Additionally, utility function models were constructed through curve fitting techniques to analyze the relationship between loan attributes and utility values, enabling precise prediction of consumer choice behavior. Results indicate that interest rates and repayment terms are the key determinants of consumer preferences, with low-interest and long-term loan options being the most favored. Moreover, consumer preferences are primarily driven by product attributes rather than individual backgrounds such as rank. The findings also reveal room for improvement in respondents' financial literacy, particularly in understanding loan products, highlighting the need for enhanced financial education and information dissemination. Based on empirical results, the study offers recommendations to increase the flexibility and diversity of loan programs, promote financial education, and tailor loan plans to meet diverse consumer needs, ultimately reducing financial risks. en_US dc.description.tableofcontents 第一章 緒論 1 第一節 研究動機 1 第二節 研究目的 3 第三節 研究流程 4 第二章 文獻探討 5 第一節 消費者貸款 5 第二節 消費者偏好 6 第三節 決策行為研究方式 7 第三章 研究設計 9 第一節 研究假說 9 第二節 問卷設計 11 第三節 研究方法 13 第四章 分析結果 15 第一節 敘述性統計 15 第二節 信用貸款屬性因子分析 22 第三節 集群分析 29 第四節 效用函數 32 第五節 貸款方案建議 35 第五章 結論與建議 44 第一節 結論 44 第二節 研究建議 46 第三節 研究限制與未來研究方向 48 參考文獻 50 附錄一 研究問卷 53 附錄二 集群分類表 57 附錄三 偏好集群ANOVA 57 附錄四 偏好集群成偶檢定 58 zh_TW dc.format.extent 2612821 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112921319 en_US dc.subject (關鍵詞) 信用貸款 zh_TW dc.subject (關鍵詞) 貸款屬性偏好 zh_TW dc.subject (關鍵詞) 曲線擬合 zh_TW dc.subject (關鍵詞) 效用函數 zh_TW dc.subject (關鍵詞) 選擇式聯合分析 zh_TW dc.subject (關鍵詞) 金融常識 zh_TW dc.subject (關鍵詞) Unsecured Loan en_US dc.subject (關鍵詞) Loan attribute preferences en_US dc.subject (關鍵詞) Curve fitting en_US dc.subject (關鍵詞) Utility function en_US dc.subject (關鍵詞) Conjoint analysis en_US dc.subject (關鍵詞) Financial literacy en_US dc.title (題名) 信用貸款額度與利率如何滿足消費者需求-以國軍輔導理財貸款為例 zh_TW dc.title (題名) Using unsecured loans and interest rates to meet consumer needs: A case of employee loan programs in the military en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 壹、中文部分 一、專書 中華民國金融監督管理委員會(2004)。銀行風險管理實務範本：信用風險管理分論及案例彙編。普華永道國際會計師事務所。 黃景泰(2013)。金融人員消費者貸款必修12堂課。財團法人台灣金融研訓院。 二、期刊 王金利(1984)。台灣地區消費者需求形態實證分析：AIDS模型之應用。經濟研究，25，177-195。 陳光、任志良和孫海柱(2005)。最小二乘曲線擬合及Matlab實現。兵工自動化，24(3)，107-108。 三、學位論文 張純真(2006)。消費者偏好與購買行為之因果關係研究。國立台灣大學資訊管理學系碩士論文，未出版，台北。 莊堉蒨(2023)。網路影音平台使用者偏好分析。國立屏東大學國際經營與貿易學系碩士論文。未出版，屏東。 曾冠豪(2018)。以聯合分析探討消費者對汽車貸款商品之偏好。東吳大學企業管理學系碩士論文，未出版，台北。 賴義生(2007)。消費者小額信用貸款授信風險評估之個案研究。國立台北大學國際財務金融碩士論文，未出版，台北。 魏逢辰(2023)。消費者選擇個人信用貸款關鍵因素之研究。東吳大學企業管理學系碩士論文，未出版，台北。 四、網路資料 中華民國銀行商業同業公會全國聯合會(2024)個人信貸信貸主力商品彙整表，2024年10月18日，取自：www.ba.org.tw/FileDownLoad/DownloadList 金融監督管理委員會(2006)。強化金融教育宣導與普及金融知識，2024年10月18日，取自https://www.fsc.gov.tw 財團法人金融聯合徵信中心(2024)。信貸借款人各年齡層與性別交叉狀況的授信金額及利率統計表，2024年10月22日，取自：https://www.jcic.org.tw/main_ch/download_page.aspx?uid=213&pid=190 貳、外文部分 一、專書 Louviere, J., Hensher, A., & Swait, D. (2000). Stated Choice Methods.Cambridge University Press. 二、期刊 Ahmad, I., & Minkarah, I. (1988). Questionnaire survey on bidding in construction. Journal of Management in Engineering, 4(3), 229–243. Bech, M., & Gyrd-Hansen, D. (2005). Effects coding in discrete choice experiments. Health Economics, 14(11), 1079–1083. Bolboacă, S. D., & Jäntschi, L. (2007). Design of experiments: Useful orthogonal arrays for number of experiments from 4 to 16. Entropy, 9(4), 198–232. Chen, Y., Fan, H., & Huang, Y. (2023). The impact of online credit lending model on the public's overspending decision. Advances in Economics. https://doi.org/10.54254/2754-1169/24/20230416 Dobson, K., & Khatri, N. (2000). Cognitive therapy: Looking backward, looking forward. Journal of Clinical Psychology, 56(7), 907–923. de Levie, R. (2000). Curve fitting with least squares. Critical Reviews in Analytical Chemistry, 40(1), 59–74. 10.1080/10408340091164180 Frangos, C., Fragkos, K., Sotiropoulos, I., Manolopoulos, G., & Valvi, A. (2012). Factors affecting customers’ decision for taking out bank loans: A case of Greek customers. Journal of Marketing Research and Case Studies, 2012, Article 927167, 16. Harrison, R., Özayan, A., & Meyers, S. (1998). A conjoint analysis of new food products processed from underutilized small crawfish. Journal of Agricultural and Applied Economics, 30(2), 257–265. Johnson, A., Villanova, D., & Smith, R. (2023). Loan amount versus monthly payments: The effect of loan application formats on consumer borrowing decisions. Journal of Consumer Research, 50(4), 765–786. Norton, J., & Bass, F. (1987) A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products. Management Science, 33, 1069-1086. Pekelman, D., & Sen, S. (1979). Improving prediction in conjoint measurement. Journal of Marketing Research, 16(2), 215–221. Syakur, M., Khotimah, B., Rochman, E., & Satoto, B. (2018). Integration K-means clustering method and elbow method for identification of the best customer profile cluster. IOP Conference Series: Materials Science and Engineering, 336(1), 012017. Wonder, N., Wilhelm, W., & Fewings, D. (2008). The financial rationality of consumer loan choices: Revealed preferences concerning interest rates, down payments, contract length, and rebates. Journal of Consumer Affairs, 42(2), 243–270. 三、網路資料 Consumer Financial Protection Bureau. (2019). Youth financial education curriculum review. Retrieved October 3, 2024, from https://www.consumerfinance.gov zh_TW
