臺灣博碩士論文加值系統

本 研究以 資料包絡分析法 Data envelopment analysis, DEA 為依據，以存
款、員工人數、資本適足率 (BIS)為投入項目；壞帳、投資收入、放款為產出項目；
固定資產做為存在期間 (carry-over)。蒐集了共三十一家銀行做為研究標的，將台
灣地區隸屬金融控股公司銀行與非隸屬金融控股公司旗下銀行進行效率分析，採
2013年至 2017年止五個完整年度資料來進行實證分析。實證結果顯示 :
1. 台灣地區31家銀行2013年至2017年整體效率值與期間效率值，總效率高於平均數的共有18家銀行；以2013年平均期間效率值最低，2016年平均期間效率值最高。
2. 研究期間最佳整體效率值為1的共有11家銀行(安泰銀行、國泰世華、合作金庫、匯豐銀行、上海商銀、台北富邦、台灣中小企銀、臺灣銀行、土地銀行、玉山銀行以及兆豐銀行)；整體效率值最低三家銀行皆為非隸屬金控旗下銀行，依序為花旗銀行、遠東商銀及板信銀行。
3. 各投入項及產出項於研究期間五個完整年度皆達成效率銀行有上海商銀、土地銀行、玉山銀行、合作金庫以及安泰銀行。
4. 隸屬金控旗下子銀行平均整體效率高於非隸屬金控旗下銀行平均整體效率。而隸屬金控下子銀行2013年至2017年五個年度每年的平均期間效率皆高於非隸屬金控旗下銀行期間效率。而平均效率值皆以2013年為最低。
5. 隸屬金控旗下子銀行於 2016年達成效率家數為最多，共有 11家， 2017年達成效
率家數為最少，共有 8家；非隸屬金控旗下子銀行於 2015年及 2016年達成效率
家數為最多，皆為共有 9家； 2013年達成效率值家數為最少，共有 6家。

Based on Data Envelopment Analysis (DEA), this study uses deposits, number of employees, and capital adequacy ratio (BIS) as input items; bad debts, investment income, and loans are output items; fixed assets are used as Carry-over. A total of 30 banks were selected as research targets, and the banks in Taiwan were affiliated to the banks of financial holding companies and non-affiliated financial holding companies for efficiency analysis. The five full annual data from 2013 to 2017 were used for empirical analysis. The empirical results show that(1) The total efficiency value and period efficiency value of 31 banks in Taiwan from 2013 to 2017, the total efficiency is higher than the average of 18 banks; the average efficiency value in 2013 is the lowest, and the average efficiency in 2016 is The highest value.(2)A total of 11 banks with the best overall efficiency value during the study period (Antai Bank, Cathay Pacific, Cooperative Treasury, HSBC, Shanghai Commercial Bank, Taipei Fubon, Taiwan SME Bank, Bank of Taiwan, Land Bank, Yushan Banks and Mega Bank); the lowest overall efficiency of the three banks are non-affiliated by the Bank of Jinkong, followed by Citibank, Far East Commercial Bank and Board Bank.(3)Each input and output item reached the efficiency in the five full years of the study period. Banks include Shanghai Commercial Bank, Land Bank, Yushan Bank, Cooperative Treasury and Antai Bank.(4)The average overall efficiency of sub-banks affiliated to Jinkong is higher than the average overall efficiency of non-subordinated financial controllers. The annual average efficiency of the subordinates of the sub-bank of Jinkong from 2013 to 2017 is higher than that of non-subordinated financial controllers. The average efficiency value is the lowest in 2013.(5)Sub-banks affiliated with Jinkong achieved the highest number of efficiency in 2016, with 11 in total, and the number of efficiency households reached the least in 2017, with a total of 8; non-subordinate banks of Jinkong achieved efficiency in 2015 and 2016. The number of households is the largest, with a total of 9; in 2013, the number of efficiency values was the lowest, with a total of six.

第一章 緒論 1
第一節 研究背景 1
第二節 研究動機與目的 2
第三節 研究架構與流程 3
第二章 文獻回顧 5
第一節 銀行產業之國內相關文獻 5第二節 銀行產業之國外相關文獻 17
第三章 研究方法 29
第一節 資料包絡分析法29
第二節 動態SBM模型 34
第三節 建構本研究實證模型 41
第四章 實證結果與分析 42
第一節 研究資料分析 42
第二節 各變數敘述統計分析 44
第三節 效率實證結果與分析 49
第五章 結論 68
第一節 研究結論 68
參考文獻 71

壹、中文文獻
1.王永宇(2015)，「台灣金控業之二階段動態績效評估」，東吳大學經濟學系碩士論文。
2.王東方 (2016)，「中國銀行產業之績效研究」，嶺東科技大學財務金融系碩士論文。
3.白燿東(2013)，「銀行分支機構績效評估-以國內A商業銀行運用Network DEA模型分析為例」，東吳大學EMBA碩士在職班論文。
4.朱耀祥(2016)，「以資料包絡分析法評估本國銀行之經營績效(2012~2015)」，國立屏東大學國際貿易學系在職專班碩士論文。
5.何依倫、林俊岳(2012)，「金融海嘯後台灣上市之金融控股公司之經營效率評估-應用四階段DEA」，文大商管學報第十七卷第一期頁43-64。
6.巫曉寧(2013)，「利用動態網絡資料包絡法探討銀行跨年期效率」，國立臺北科技大學經營管理系碩士論文。
7.李俊浩（2016），「臺灣銀行產業之經營績效研究-效率與生產力指數之應用」嶺東科技大學財務金融學系碩士論文。
8.張群芬（2016），「金融控股公司體系下之臺灣銀行業效率分析」，國立虎尾科技大學經營管理所在職專班碩士論文。
9.梁連文、李盈慧(2016)，「企業社會責任與銀行效率關連性之探討-三階段資料包絡分析法」，會計與財金研究，第九卷，第一期，頁11-30。
10.郭依婷(2012)，「台灣本國金控銀行經營績效之實證研究」，世新大學財務金融學研究所碩士論文。
11.陳富強、馮淑琴、方顯光(2011)，「探討台灣地區本國銀行獲利能力與市場能力-二階段DEA」，華人經濟研究第九卷第二期頁33-52。
12.陳嘉軒（2009），「從績效評估探討銀行產業之風險效率衡量－DEA模型之應用」，東海大學工業工程與經營資訊學系博士論文。
13.曾譯生(2015)，「運用資料包絡分析法評估策略聯盟績效-以台灣商業銀行與越南商業銀行為例」，國立高雄應用科技大學工業工程與管理系碩士論文。
14.黃筱晴(2013)，「國際化對台灣銀行業績效影響」，中國文化大學經濟學系碩士論文。
15.廖惠民(2015)，「以DEA法評估公營銀行與民營銀行的經營效率」，交通大學經營管理學程碩士論文。
16.蔡伊倫（2015），「銀行之績效評估-兩階段動態資料包絡法模型」，東吳大學經濟學系碩士論文。
17.蔡泓儒(2014)，「金控子銀行與獨立銀行之效率比較」，國立成功大學財務金融學系碩士論文。
18.蔡義倫（2015），「金控銀行與獨立銀行之共同邊界效率分析」，國立政治大學經濟學系碩士論文。
19.遲淑華(2012)，「金融改革、金融監管與動態效率關聯性之探討－以台灣或大陸之商業銀行為例」，國立政治大學金融研究所博士論文。
20.簡維毅（2017），「銀行業布局金融科技專利之績效評估-運用Network DEA模型」，東吳大學經濟學系碩士論文。






貳、英文文獻
1.Bahrini, R.(2017) “Efficiency Analysis of Islamic Banks in the Middle East and North Africa Region: A Bootstrap DEA Approach,” International Journal of Financial Studies, Vol. 5, No. 7, 1-13.
2.Banker, R. D., A. Charnes and Cooper, W.W., (1984), “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis.” Management Science 30(9),1078-1092.
3.Bogetoft, P. and Nielsen, K. (2008), “DEA based auctions”. European Journal of Operational Research 184:685–700
4.Branco, A. P. Salgado,Jr., Cava, P. B. and Carneiro M. (2016) “Efficiency of the Brazilian Banking System: An Assessment Using DEA under Three Approaches,” Journal of Applied Finance & Banking, Vol. 6, No. 4, 27-42.
5.Cava, P. B., Salgado Jr. A. P. and Branco A. M. D. F. (2016) “Evaluation of bank efficiency in Brazil: A DEA Approach,” RAM. Revista de Administração Mackenzie, Vol. 17, No. 4, 62-84.
6.Chang, T.-C., and Chiu Y.-H., (2006) “Affecting Factors on Risk-adjusted Efficiency in Taiwans Banking Industry” Contemporary Economic Policy 24.4 , 634-648.
7.Charnes, A., W.W. Cooper and E. Rhodes (1978), “Measuring the efficiency of decision making units ”, European Journal of Operational Research 2(6),429-444.
8.Chaudhary, G. M., and Arshad A. (2016) “Impact of Privatization upon Efficiency of Enterprises: Evidence from the Banking Sector of Pakistan,” Journal of Business Studies Quarterly, Vol.7, No.3, 47-60.
9.Chen, C. M. (2009).,“A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks”, European Journal of Operational Research 194 (3),687-699.
10.Chen, C. M. (2009).,“A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks”, European Journal of Operational Research 194 (3),687-699.
11.Cuesta, R. A. and Orea,L. (2002), “Mergers and technical efficiency in Spanish savings banks: A stochastic distance function approach” Journal of Banking & Finance, Volume 26, Issue 12,2231-2247.
12.Fare, R. and Grosskopf, S. (1996),“Intertemporal Production Frontiers: With Dynamic DEA” , Boston: Kluwer Academic Publishers.
13.Farrell, M. J.(1957),“The Measurement of Productive Efficiency”, Journal of the Royal Statistical Society, SeriesA, Vol. 120, Part 3,253-281.
14.Kao, C.(2008), “Network data envelopment analysis: current development and future research”, Asia–Pacific productivity conference (APPC)
15.Kaur, P.(2016) “Efficiency of Microfinance Institutions in India: Are they reaching the poorest of the poor?” Vision, Vol. 20, No. 1, 54-65.
16.Lin, T. T., Lee,C.-C. and Chiu,T.-F. (2009),“Application of DEA in analyzing a bank’s operating performance”,Expert Systems with Applications, Volume 36, Issue 5, 8883-8891.
17.Majumder, M. Gopinath, G., M. and Ramudu, P. J. (2016) “Indian MFIs Pattern: Analytical Model Building,” SCMS Journal of Indian Management, 57-66.
18.Marwa, N. and Aziakpono, M. (2016) “Technical and Scale efficiency of Tanzanian Saving and Credit Cooperatives,” The Journal of Developing Areas, Vol. 50, No.1, 29-46.
19.Miencha, I. O., Selvam, M. and Onchangu, S. A. (2016) “Return on Assets Efficiency of Kenyan Banking Sector,” Journal of Internet Banking and Commerce, Vol. 21, No. 2, 1-17.
20.Nemoto, J. and Goto, M. (1999)“, Dynamic data envelopment analysis modeling intertemporal behavior of a firm in the presence of productive inefficiencies”, Economic Letters, 64 (1) 51-56.
21.Palečková, I.(2017) “Efficiency Change of Banking Sectors and Banks in the Financial conglomerates in Visegrad Group Countries,” Ekonomický č asopis, 65 , 79-92.
22.Park, K. S. and Park, K. (2009),“Measurement of multiperiod aggregative efficiency”, European Journal of Operational Research, 193 (2) 567-580.
23.Ramakrishna, Ramulu, G., M. and Kumar, B. P. (2016) “Financial Crisis and the Performance of Commercial Bank: Indian Experience,” Journal of International Economics, Vol.7, No. 2, 35-55.
24.Ramakrishna, Ramulu, G., M. and Kumar, B. P. (2016) “Financial Crisis and the Performance of Commercial Bank: Indian Experience,” Journal of International Economics, Vol.7, No. 2, 35-55.
25.Sueyoshi, T. and Sekitani, K. (2005),“Returns to scale in dynamic DEA”, European Journal of Operational Research, 161 (2)536-44.
26.Thoraneenitiyan, N. and Avkiran, N. K. (2009),“Measuring the impact of restructuring and country-specific factors on the efficiency of post-crisis East Asian banking systems: Integrating DEA with SFA”, Socio-Economic Planning Sciences, Volume 43, Issue 4,240-252.
27.Tone, K. and Tsutsui, M. (2010), “Dynamic DEA: A Slacks-based Measure Approach, ”, Omega, 38,145-156.
28.Tone, K. (2001), “A Slacks-based Measure of Efficiency in Data Envelopment Analysis,” European Journal of Operational Research, 130 (3), 498-509.
29.Tone, K. and Tsutsui, M. (2009) “Network DEA: A Slacks-Based Measure Approach,” European Journal of Operational Research, Vol. 197, No. 1, 243-252.
30.Van der Westhuizen, G. (2010),“The Role Of Interest Income And Non-Interest Income On The Relative Efficiency Of Bank Regions: The Case Of A Large South African Bank”,Gert.Studia Universitatis Babes-Bolyai 55.2. 3-23.
31.Wanke, P. and Barros, C. (2013) “Two-stage DEA: An application to major Brazilian banks,” Expert System with Applications, 41: 2337-2344.
32.Yüksel, S., Mukhtarov, S. and Mammadov, E. (2016) “Comparing the Efficiency of Turkish and Azerbaijani Banks: An application with Data Envelopment Analysis,” International Journal of Economics and Financial Issues, Vol. 6, No. 3, 1059-1067.