政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/139547
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 113822/144841 (79%)
造訪人次 : 51820545      線上人數 : 502
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/139547
    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/139547


    題名: 利用網絡DEA與網絡SFA探討企業社會責任對於銀行效率之影響
    The effect of corporate social responsibility on bank performances: an application of network data envelopment analysis and network stochastic frontier analysis
    作者: 胡聚男
    Hu, Chu-Nan
    貢獻者: 黃台心
    Huang, Tai-Hsin
    胡聚男
    Hu, Chu-Nan
    關鍵詞: 企業社會責任
    共用生產要素
    網絡DEA
    網絡SFA
    環境變數
    截斷迴歸模型
    關聯結構
    成本吝嗇假說
    Corporate social responsibility
    Shared inputs
    Network DEA
    Network SFA
    Environmental variables
    Truncated regression model
    Copula
    Cost skimping hypothesis
    日期: 2020
    上傳時間: 2022-04-01 15:01:47 (UTC+8)
    摘要: 本文將銀行生產過程分成兩個階段,此架構更能反映在存款與企業社會責任
    扮演中間產出的角色。第一階段利用部分勞工與資本設備生產存款與企業社會責任;第二階段是銀行獲利階段,利用剩餘的勞工與資本設備,搭配上階段的中間產出--存款與企業社會責任,製造放款、投資與非利息收入等三種最終產出。由於勞工與資本拆成兩個階段使用,故須利用共用生產要素之網絡 DEA 與網絡SFA 兩種模型評估銀行效率,並在控制銀行體質與各國文化等環境變數下,探討企業社會責任對於銀行效率的影響。

    值得一提者,在網絡 DEA 模型下,本文使用兩步驟法 (two-step approach),在第二步驟採用截斷迴歸模型 (truncated regression model) 估計環境變數對效率之影響,而非文獻上常用之 Tobit 模型,並使用 Simar and Wilson (2007) 提出的兩種演算法調整截斷迴歸模型估計標準誤存在偏誤的問題;另在在網絡 SFA 下,本文則延伸 Huang et al. (2017) 的架構,將環境變數納入成本函數中,加入產出面距離函數以及兩條成本份額方程式,共計四條聯立估計。由於納入環境變數,使得本文網絡 SFA 運用關聯結構法推導的概似函數型態相當複雜,實證估計時
    面臨極大挑戰。

    有關樣本銀行投入和產出資料,主要綜整自 BankScope 與 Orbis Bank Focus資料庫,蒐集 2003-2014 年間跨國 187 家銀行的相關數據以及 CAMEL 指標。至於企業社會責任資料則取自於 EIRIS 資料庫,並細分為員工、社區、環境、公司治理、利益攸關人、賄賂與 ESG 傳遞等七個面向。此外,本文研究主題為跨國的銀行效率比較,故採用 Hofstede et al. (1991, 2010) 建構的文化指標以控制國家異質性,包含個人主義、長期關係傾向、對不確定性趨避程度以及權力距離等四個面向。

    網絡 DEA 與網絡 SFA 模型的實證結果,在多個面向上相當類似,與環境相關企業社會責任對於銀行效率有正面影響,可能因為銀行越重視「環境」議題,有助於銀行推出綠色產品,例如綠色放款、綠色債券,或藉由綠色存款取得較成本的資金來源,因此環境是銀行從事策略性企業社會責任的關鍵。然而,當銀行從事與「員工」或「社區」相關的企業社會責任議題時,可能降低銀行效率,顯示這類活動可能比較偏向利他行為。值得注意者,當銀行管理階層傳達 ESG 風險與機會越全面時,其「ESG 傳遞」面向分數越高,但在網絡 SFA 與網絡 DEA會得到相反的結果。本研究認為網絡 SFA 將要素價格納入第二階段的成本函數中,網絡 DEA 僅從生產函數角度使用投入和產出變數進行效率評估,忽略要素價格,故網絡 SFA 的估計結果應較網絡 DEA 合宜。本研究結果支持「成本吝嗇」假說,該假說認為當銀行審核放款、投資等營運活動不謹慎時,雖然會花費較少成本而提高經營效率,但也會造成銀行穩定度不佳,因此「ESG 傳遞度」越高的銀行,其營運流程相對較為謹慎致成本相對較高,故效率表現應當較差。最後,「公司治理」、「利益攸關人」與「賄賂」在網絡 DEA 多半無法得到顯著的結果,但在網絡 SFA 實證結果則依序得到對效率的影響為顯著負向、正向與正向。
    This dissertation divides the production process of commercial banking into two stages for describing the dual roles of deposits and corporate social responsibility (CSR) activities and for linking CSR with cost efficiency. In the first stage, banks expend a portion of their labor and physical capital inputs to collect deposits and engage in CSR; in the second stage, they employ their remaining labor and physical capital and two intermediate goods (i.e., deposits and CSR) to produce loans, investments, and noninterest income. Because the labor and capital inputs are utilized in both stages, we adopt the network data envelopment analysis (DEA) and network stochastic frontier analysis (SFA) models to evaluate bank efficiency, and we investigate the relationship between efficiency and various CSR activities after controlling for bank structures and their country-specific cultural factors.

    Under the network DEA framework, we use a truncated regression model, as suggested by Simar and Wilson (2007), to estimate the effects of chosen environmental variables on efficiency. This approach contrasts with the widely applied Tobit model that has been utilized in numerous previous relevant studies. In addition, we adjust the biases of the standard errors from the truncated regression model using two algorithms proposed by Simar and Wilson (2007). We also extend the findings of Huang et al. (2017) by incorporating environmental variables into the inefficiency term of the cost frontier, and we simultaneously estimate the parameter coefficients of the output distance function, cost frontier, and two cost share equations. We derive the joint probability density function of these four equations by applying the copula method. The incorporation of environmental variables substantially complicates the function, which is thus very difficult to estimate.

    We combine the Bankscope and Orbis Bank Focus databases to compile input–output data and CAMEL indices for 187 banks in 27 countries during 2003–2014. We collect a set of CSR measures from the Ethical Investment Research and Information Service (EIRIS) database and divide them into seven dimensions: employee, community, environment, governance, stakeholder, bribery, and ESG delivery. We then rescale the scores. In addition, we include the four cultural indices developed by Hofstede et al. (1991, 2010) (i.e., individualism, long-term orientation, uncertainty avoidance, and power distance) in the regression model to partially control for country heterogeneity.

    The empirical results of the network DEA and network SFA are similar in several aspects. For example, banks that engage in frequent environment-related CSR activities may pay higher attention to environmental issues and produce more green financial products, such as green loans and green bonds, than banks that rarely engage in environment-related CSR activities. The former banks may acquire green deposits and thereby reduce their funding costs. This implies that banks engage in environmental CSR due to strategic motivation. Conversely, the employee and community dimensions reduce bank efficiency, indicating that these dimensions are consistent with an altruistic motive. The results of analysis of the ESG delivery dimension using the network SFA model support the cost skimping hypothesis, which suggests that superior efficiency may partially be due to a bank’s relatively less careful monitoring of lending or other operations. However, the network DEA provides the opposite result from network SFA. Because the network SFA considers input prices when estimating the cost frontier and efficiency and the network DEA does not, our findings validate the results of the network SFA. Finally, the governance, stakeholder, and bribery dimensions have no significant effect on efficiency in the network DEA, but they exert negative, positive, and positive effects, respectively, on efficiency in the network SFA.
    參考文獻: Abbott, W. F., & Monsen, R. J. (1979). On the measurement of corporate social responsibility: Self-reported disclosures as a method of measuring corporate social involvement. Academy of management journal, 22(3), 501-515.
    Abdul-Majid, M., Saal, D. S., & Battisti, G. (2010). Efficiency in Islamic and conventional banking: an international comparison. Journal of productivity analysis, 34(1), 25-43.
    Abedifar, P., Hasan, I., & Tarazi, A. (2016). Finance-growth nexus and dual-banking systems: Relative importance of Islamic banks. Journal of Economic Behavior & Organization, 132, 198-215.
    Afonso, A., & Aubyn, M. S. (2006). Cross-country efficiency of secondary education provision: A semi-parametric analysis with non-discretionary inputs. Economic modelling, 23(3), 476-491.
    Ahlin, C., & Bose, P. (2007). Bribery, inefficiency, and bureaucratic delay. Journal of Development Economics, 84(1), 465-486.
    Aly, H. Y., Grabowski, R., Pasurka, C., & Rangan, N. (1990). Technical, scale, and allocative efficiencies in US banking: An empirical investigation. The review of Economics and Statistics, 211-218.
    Angbazo, L. (1997). Commercial bank net interest margins, default risk, interest-rate risk, and off-balance sheet banking. Journal of Banking & Finance, 21(1), 55-87.
    Arlow, P., & Gannon, M. J. (1982). Social responsiveness, corporate structure, and economic performance. Academy of Management Review, 7(2), 235-241.
    Atkinson, S. E., & Cornwell, C. (1993). Measuring technical efficiency with panel data: A dual approach. Journal of Econometrics, 59(3), 257-261.
    Atkinson, S. E., & Cornwell, C. (1994). Estimation of output and input technical efficiency using a flexible functional form and panel data. International economic review, 245-255.
    Avkiran, N. K. (2015). An illustration of dynamic network DEA in commercial banking including robustness tests. Omega, 55, 141-150.
    Barros, C. P., & Dieke, P. U. (2008). Measuring the economic efficiency of airports: A Simar–Wilson methodology analysis. Transportation Research Part E: Logistics and Transportation Review, 44(6), 1039-1051.
    Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
    Banker, R. D., & Natarajan, R. (2008). Evaluating contextual variables affecting productivity using data envelopment analysis. Operations research, 56(1), 48-58.
    Banker, R. D., Chang, H., & Lee, S. Y. (2010). Differential impact of Korean banking system reforms on bank productivity. Journal of Banking & Finance, 34(7), 1450-1460.
    Barth, J. R., Lin, C., Ma, Y., Seade, J., & Song, F. M. (2013). Do bank regulation, supervision and monitoring enhance or impede bank efficiency?. Journal of Banking & Finance, 37(8), 2879-2892.
    Belasri, S., Gomes, M., & Pijourlet, G. (2020). Corporate social responsibility and bank efficiency. Journal of Multinational Financial Management, 100612.
    Battese, G. E., & Coelli, T. J. (1988). Prediction of firm level technical inefficiencies with a generalized frontier production function. Journal of econometrics, 38, 387-399.
    Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical economics, 20(2), 325-332.
    Becchetti, L., & Trovato, G. (2011). Corporate social responsibility and firm efficiency: a latent class stochastic frontier analysis. Journal of Productivity Analysis, 36(3), 231-246.
    Berger, A. N., Hanweck, G. A., & Humphrey, D. B. (1987). Competitive viability in banking: Scale, scope, and product mix economies. Journal of monetary economics, 20(3), 501-520.
    Berger, A. N., & De Young, R. (1997). Problem loans and cost efficiency in commercial banking. Journal of Banking and Finance, 21, 849-870.
    Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European journal of operational research, 98(2), 175-212.
    Berger, A. N., & Mester, L. J. (1997). Inside the black box: What explains differences in the efficiencies of financial institutions?. Board of Governors of the Federal Reserve System working paper, (1997-10).
    Bowen, H. R. (1953). Social responsibility of the business. Californian Management Review, 18(3), 49-58.
    Bowman, E. H., & Haire, M. (1975). A strategic posture toward corporate social responsibility. California management review, 18(2), 49-58.
    Boyle, E. J., Higgins, M. M., & Rhee, G. S. (1997). Stock market reaction to ethical initiatives of defense contractors: Theory and evidence. Critical Perspectives on Accounting, 8(6), 541-561.
    Brammer, S. J., & Pavelin, S. (2006). Corporate reputation and social performance: The importance of fit. Journal of Management Studies, 43(3), 435-455.
    Brammer, S., & Millington, A. (2008). Does it pay to be different? An analysis of the relationship between corporate social and financial performance. Strategic management journal, 29(12), 1325-1343.
    Carroll, A. B. (1979). A three-dimensional conceptual model of corporate performance. Academy of management review, 4(4), 497-505.
    Carroll, A. B. (1999). Corporate social responsibility: Evolution of a definitional construct. Business & society, 38(3), 268-295.
    Caves, D. W., Christensen, L. R., & Swanson, J. A. (1981). Productivity growth, scale economies, and capacity utilization in US railroads, 1955-74. The American Economic Review, 71(5), 994-1002.
    Chambers, R. G. (1988). Applied production analysis: a dual approach. Cambridge University Press.
    Chang, T. C., & Chiu, Y. H. (2006). Affecting factors on risk‐adjusted efficiency in Taiwan`s banking industry. Contemporary Economic Policy, 24(4), 634-648.
    Chao, C. M., Yu, M. M., & Wu, H. N. (2015). An application of the dynamic network DEA model: the case of banks in Taiwan. Emerging Markets Finance and Trade, 51(sup1), S133-S151.
    Charnes, A., & Cooper, W. W. (1962). Programming with linear fractional functionals. Naval Research logistics quarterly, 9(3‐4), 181-186.
    Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
    Chen, Y., & Zhu, J. (2004). Measuring information technology`s indirect impact on firm performance. Information Technology and Management, 5(1-2), 9-22.
    Chen, Y., Du, J., Sherman, H. D., & Zhu, J. (2010). DEA model with shared resources and efficiency decomposition. European Journal of Operational Research, 207(1), 339-349.
    Chen, Y. C., Chiu, Y. H., Huang, C. W., & Tu, C. H. (2013). The analysis of bank business performance and market risk—Applying Fuzzy DEA. Economic modelling, 32, 225-232.
    Chen, Y. K., Shen, C. H., Kao, L., & Yeh, C. Y. (2018). Bank liquidity risk and performance. Review of Pacific Basin Financial Markets and Policies, 21(01), 1850007.
    Chilingerian, J. A. (1995). Evaluating physician efficiency in hospitals: A multivariate analysis of best practices. European journal of operational research, 80(3), 548-574.
    Cochran, P. L., & Wood, R. A. (1984). Corporate social responsibility and financial performance. Academy of management Journal, 27(1), 42-56.
    Coelli, T. J., Rao, D. S. P., O`Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis. Springer Science & Business Media.
    Cook, W. D., Liang, L., & Zhu, J. (2010). Measuring performance of two-stage network structures by DEA: a review and future perspective. Omega, 38(6), 423-430.
    Dam, L., Koetter, M., & Scholtens, B. (2009). Why do firms do good? Evidence from managerial efficiency. Evidence from Managerial Efficiency (March 17, 2009).
    Da Cruz, N. F., & Marques, R. C. (2014). Revisiting the determinants of local government performance. Omega, 44, 91-103.
    Das, A., & Kumbhakar, S. C. (2012). Productivity and efficiency dynamics in Indian banking: An input distance function approach incorporating quality of inputs and outputs. Journal of Applied Econometrics, 27(2), 205-234.
    Davis, K. (1960). Can business afford to ignore social responsibilities?. California management review, 2(3), 70-76.
    Davies, H. (1995). Interpreting guanxi: The role of personal connections in a high context transitional economy. China business: Context and issues, 155-169.
    Delis, M., Iosifidi, M., & Tsionas, M. G. (2017). Endogenous bank risk and efficiency. European Journal of Operational Research, 260(1), 376-387.
    Devaney, M., & Weber, W. L. (2002). Small-business lending and profit efficiency in commercial banking. Journal of Financial Services Research, 22(3), 225-246.
    DeYoung, R., & Nolle, D. E. (1996). Foreign-owned banks in the United States: Earning market share or buying it?. Journal of Money, Credit and Banking, 28(4), 622-636.
    DeYoung, R., & Hasan, I. (1998). The performance of de novo commercial banks: A profit efficiency approach. Journal of Banking & Finance, 22(5), 565-587.
    Dietsch, M., & Lozano-Vivas, A. (2000). How the environment determines banking efficiency: A comparison between French and Spanish industries. Journal of Banking & Finance, 24(6), 985-1004.
    Drucker, P. F. (1984). Converting social problems into business opportunities: The new meaning of corporate social responsibility. California Management Review (pre-1986), 26(000002), 53.
    Du, K., & Sim, N. (2016). Mergers, acquisitions, and bank efficiency: Cross-country evidence from emerging markets. Research in International Business and Finance, 36, 499-510.
    Eilbirt, H., & Parket, I. R. (1973). The practice of business: The current status of corporate social responsibility. Business horizons, 16(4), 5-14.
    Eling, M., & Luhnen, M. (2010). Efficiency in the international insurance industry: A cross-country comparison. Journal of Banking & Finance, 34(7), 1497-1509.
    Faccio, M., Marchica, M. T., & Mura, R. (2016). CEO gender, corporate risk-taking, and the efficiency of capital allocation. Journal of Corporate Finance, 39, 193-209.
    Färe, R., Grosskopf, S., Lovell, C. K., & Yaisawarng, S. (1993). Derivation of shadow prices for undesirable outputs: a distance function approach. The review of economics and statistics, 374-380.
    Fare, R., Färe, R., Fèare, R., Grosskopf, S., & Lovell, C. K. (1994). Production frontiers. Cambridge University Press.
    Färe, R., Grosskopf, S., & Roos, P. (1995). Productivity and quality changes in Swedish pharmacies. International Journal of Production Economics, 39(1-2), 137-144.
    Favero, C. A., & Papi, L. (1995). Technical efficiency and scale efficiency in the Italian banking sector: a non-parametric approach. Applied economics, 27(4), 385-395.
    Fiordelisi, F., Marques-Ibanez, D., & Molyneux, P. (2011). Efficiency and risk in European banking. Journal of banking & finance, 35(5), 1315-1326.
    Friedman, M. (1970). A Friedman doctrine: The social responsibility of business is to increase its profits. The New York Times Magazine, 13(1970), 32-33.
    Fock, H. K., & Woo, K. S. (1998). The China market: Strategic implications of guanxi. Business Strategy Review, 9(3), 33-43.
    Fries, S., & Taci, A. (2005). Cost efficiency of banks in transition: Evidence from 289 banks in 15 post-communist countries. Journal of Banking & Finance, 29(1), 55-81.
    Fukuyama, H., & Matousek, R. (2011). Efficiency of Turkish banking: Two-stage network system. Variable returns to scale model. Journal of International Financial Markets, Institutions and Money, 21(1), 75-91.
    Fukuyama, H., & Weber, W. L. (2012). Estimating two-stage network technology inefficiency: an application to cooperative Shinkin banks in Japan. International Journal of Operations Research and Information Systems (IJORIS), 3(2), 1-23.
    Fukuyama, H., & Weber, W. L. (2015). Measuring Japanese bank performance: a dynamic network DEA approach. Journal of Productivity Analysis, 44(3), 249-264.
    Fukuyama, H., & Weber, W. L. (2017). Japanese bank productivity, 2007–2012: A dynamic network approach. Pacific Economic Review, 22(4), 649-676.
    Galdeano-Gómez, E., Céspedes-Lorente, J., & Martínez-del-Río, J. (2008). Environmental performance and spillover effects on productivity: evidence from horticultural firms. Journal of environmental management, 88(4), 1552-1561.
    Giokas, D. I. (1991). Bank branch operating efficiency: A comparative application of DEA and the loglinear model. Omega, 19(6), 549-557.
    Glass, J. C., McKillop, D. G., & Rasaratnam, S. (2010). Irish credit unions: investigating performance determinants and the opportunity cost of regulatory compliance. Journal of Banking & Finance, 34(1), 67-76.
    Gorodnichenko, Y., & Roland, G. (2017). Culture, institutions, and the wealth of nations. Review of Economics and Statistics, 99(3), 402-416.
    Hillman, A. J., & Keim, G. D. (2001). Shareholder value, stakeholder management, and social issues: What`s the bottom line?. Strategic management journal, 22(2), 125-139.
    Hirschberg, J. G., & Lloyd, P. J. (2002). Does the technology of foreign-invested enterprises spill over to other enterprises in China? An application of post-DEA bootstrap regression analysis. Modelling the Chinese Economy. Edward Elgar Press, London.
    Hofstede, G. (1991). Organizations and cultures: Software of the mind. McGrawHill, New York.
    Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and Organizations: Software of the Mind. Revised and expanded 3rd Edition. N.-Y.: McGraw-Hill.
    Holmes, S. L. (1976). Executive perceptions of corporate social responsibility. Business horizons, 19(3), 34-40.
    Holod, D., & Lewis, H. F. (2011). Resolving the deposit dilemma: A new DEA bank efficiency model. Journal of Banking & Finance, 35(11), 2801-2810.
    Hsiao, H. C., Chang, H., Cianci, A. M., & Huang, L. H. (2010). First financial restructuring and operating efficiency: evidence from Taiwanese commercial banks. Journal of Banking & Finance, 34(7), 1461-1471.
    Hua, Z., & Bian, Y. (2008). Performance measurement for network DEA with undesirable factors. International Journal of Management and Decision Making, 9(2), 141-153.
    Huang, C. J., & Liu, J. T. (1994). Estimation of a non-neutral stochastic frontier production function. Journal of productivity analysis, 5(2), 171-180.
    Huang, T. H., Chiang, D. L., & Tsai, C. M. (2015). Applying the new metafrontier directional distance function to compare banking efficiencies in Central and Eastern European countries. Economic Modelling, 44, 188-199.
    Huang, T. H., Lin, C. I., & Chen, K. C. (2017). Evaluating efficiencies of Chinese commercial banks in the context of stochastic multistage technologies. Pacific-Basin Finance Journal, 41, 93-110.
    Huang, T. H., Chen, K. C., & Lin, C. I. (2018). An extension from network DEA to copula-based network SFA: Evidence from the US commercial banks in 2009. The Quarterly Review of Economics and Finance, 67, 51-62.
    Huang, T. H., Lin, C. I., & Wu, R. C. (2019). Assessing the marketing and investment efficiency of Taiwan’s life insurance firms under network structures. The Quarterly Review of Economics and Finance, 71, 132-147.
    Hunter, W. C., & Timme, S. G. (1995). Core deposits and physical capital: A reexamination of bank scale economies and efficiency with quasi-fixed inputs. Journal of Money, Credit and Banking, 27(1), 165-185.
    Husted, B. W., & Allen, D. B. (2010). Corporate social strategy: Stakeholder engagement and competitive advantage. Cambridge University Press.
    Inoue, Y., & Lee, S. (2011). Effects of different dimensions of corporate social responsibility on corporate financial performance in tourism-related industries. Tourism Management, 32(4), 790-804.
    Kao, C., & Liu, S. T. (2004). Predicting bank performance with financial forecasts: A case of Taiwan commercial banks. Journal of Banking & Finance, 28(10), 2353-2368.
    Kao, C., & Hwang, S. N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European journal of operational research, 185(1), 418-429.
    Karim, M. Z. A., Chan, S. G., & Hassan, S. (2010). Bank efficiency and non-performing loans: Evidence from Malaysia and Singapore. Prague Economic Papers, 2(1), 118-132.
    Kohers, T., Huang, M. H., & Kohers, N. (2000). Market perception of efficiency in bank holding company mergers: the roles of the DEA and SFA models in capturing merger potential. Review of Financial Economics, 9(2), 101-120.
    Kong, W. H., Fu, T. T., & Yu, M. M. (2017). Evaluating Taiwanese Bank Efficiency Using the Two-Stage Range DEA Model. International Journal of Information Technology & Decision Making, 16(04), 1043-1068.
    Koutsomanoli-Filippaki, A., Margaritis, D., & Staikouras, C. (2012). Profit efficiency in the European Union banking industry: a directional technology distance function approach. Journal of Productivity Analysis, 37(3), 277-293.
    Krasnikov, A., Jayachandran, S., & Kumar, V. (2009). The impact of customer relationship management implementation on cost and profit efficiencies: evidence from the US commercial banking industry. Journal of marketing, 73(6), 61-76.
    Kumbhakar, S. C. (1991). Estimation of technical inefficiency in panel data models with firm-and time-specific effects. Economics Letters, 36(1), 43-48.
    Kumbhakar, S. C., & Wang, D. (2007). Economic reforms, efficiency and productivity in Chinese banking. Journal of Regulatory Economics, 32(2), 105-129.
    Lee, S., Singal, M., & Kang, K. H. (2013). The corporate social responsibility–financial performance link in the US restaurant industry: do economic conditions matter?. International Journal of Hospitality Management, 32, 2-10.
    Lensink, R., Meesters, A., & Naaborg, I. (2008). Bank efficiency and foreign ownership: Do good institutions matter?. Journal of Banking & Finance, 32(5), 834-844.
    Lentner, C., Szegedi, K., & Tatay, T. (2015). Corporate social responsibility in the banking sector. Pénzügyi Szemle/Public Finance Quarterly, 60(1), 95-103.
    Lewis, H. F., Mallikarjun, S., & Sexton, T. R. (2013). Unoriented two-stage DEA: The case of the oscillating intermediate products. European Journal of Operational Research, 229(2), 529-539.
    Li, K., Griffin, D., Yue, H., & Zhao, L. (2013). How does culture influence corporate risk-taking?. Journal of Corporate Finance, 23, 1-22.
    Liang, L., Cook, W. D., & Zhu, J. (2008). DEA models for two‐stage processes: Game approach and efficiency decomposition. Naval Research Logistics (NRL), 55(7), 643-653.
    Lin, T. Y., & Chiu, S. H. (2013). Using independent component analysis and network DEA to improve bank performance evaluation. Economic Modelling, 32, 608-616.
    Lopez, R. E. (1980). The structure of production and the derived demand for inputs in Canadian agriculture. American Journal of Agricultural Economics, 62(1), 38-45.
    Lopez, R. E., & Tung, F. L. (1982). Energy and Non‐Energy Input Substitution Possibilities and Output Scale Effects in Canadian Agriculture. Canadian Journal of Agricultural Economics/Revue canadienne d`agroeconomie, 30(2), 115-132.
    Lozano-Vivas, A. (1997). Profit efficiency for Spanish savings banks. European Journal of Operational Research, 98(2), 381-394.
    Lozano-Vivas, A., & Pasiouras, F. (2010). The impact of non-traditional activities on the estimation of bank efficiency: international evidence. Journal of Banking & Finance, 34(7), 1436-1449.
    Lozano-Vivas, A., Pastor, J. T., & Hasan, I. (2001). European bank performance beyond country borders: What really matters?. Review of Finance, 5(1-2), 141-165.
    Mahoney, L., & Roberts, R. W. (2007, September). Corporate social performance, financial performance and institutional ownership in Canadian firms. In Accounting forum (Vol. 31, No. 3, pp. 233-253). Taylor & Francis.
    Maignan, I., Ferrell, O. C., & Hult, G. T. M. (1999). Corporate citizenship: Cultural antecedents and business benefits. Journal of the Academy of Marketing Science, 27(4), 455-469.
    Mamatzakis, E., Matousek, R., & Vu, A. N. (2016). What is the impact of bankrupt and restructured loans on Japanese bank efficiency?. Journal of Banking & finance, 72, S187-S202.
    Matthews, K. (2013). Risk management and managerial efficiency in Chinese banks: A network DEA framework. Omega, 41(2), 207-215.
    Maudos, J., Pastor, J. M., Perez, F., & Quesada, J. (2002). Cost and profit efficiency in European banks. Journal of international financial markets, institutions and money, 12(1), 33-58.
    McDonald, J. (2009). Using least squares and tobit in second stage DEA efficiency analyses. European journal of operational research, 197(2), 792-798.
    McGuire, J. W. (1963). Business and society. McGraw-hill.
    Mitton, T. (2002). A cross-firm analysis of the impact of corporate governance on the East Asian financial crisis. Journal of financial economics, 64(2), 215-241.
    Moskowitz, M. (1972). Choosing socially responsible stocks. Business and Society Review, 1(1), 71-75.
    Nelson, R. A. (1985). Returns to scale from variable and total cost functions: Evidence from the electric power industry. Economics Letters, 18(2-3), 271-276.
    O’Donnell, C. J., & Coelli, T. J. (2005). A Bayesian approach to imposing curvature on distance functions. Journal of Econometrics, 126(2), 493-523.
    Oum, T. H., & Yu, C. (1994). Economic efficiency of railways and implications for public policy: A comparative study of the OECD countries` railways. Journal of transport Economics and Policy, 121-138.
    Pastor, J., Perez, F., & Quesada, J. (1997). Efficiency analysis in banking firms: An international comparison. European Journal of Operational Research, 98(2), 395-407.
    Peloza, J., & Shang, J. (2011). How can corporate social responsibility activities create value for stakeholders? A systematic review. Journal of the academy of Marketing Science, 39(1), 117-135.
    Peterson, D. K. (2004). The relationship between perceptions of corporate citizenship and organizational commitment. Business & society, 43(3), 296-319.
    Poon, W. P., Lee, J., & Gup, B. E. (2009). Do solicitations matter in bank credit ratings? Results from a study of 72 countries. Journal of Money, Credit and Banking, 41(2‐3), 285-314.
    Pope, S., & Wæraas, A. (2016). CSR-washing is rare: A conceptual framework, literature review, and critique. Journal of Business Ethics, 137(1), 173-193.
    Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competition. New York, 300, 28.
    Reifschneider, D., & Stevenson, R. (1991). Systematic departures from the frontier: a framework for the analysis of firm inefficiency. International economic review, 715-723.
    Resti, A. (1997). Evaluating the cost-efficiency of the Italian banking system: What can be learned from the joint application of parametric and non-parametric techniques. Journal of banking & finance, 21(2), 221-250.
    Schaffnit, C., Rosen, D., & Paradi, J. C. (1997). Best practice analysis of bank branches: an application of DEA in a large Canadian bank. European Journal of Operational Research, 98(2), 269-289.
    Schankerman, M., & Nadiri, M. I. (1986). A test of static equilibrium models and rates of return to quasi-fixed factors, with an application to the bell system. Journal of Econometrics, 33(1-2), 97-118.
    Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. Management science, 45(9), 1270-1288.
    Sherman, H. D., & Gold, F. (1985). Bank branch operating efficiency: Evaluation with data envelopment analysis. Journal of banking & finance, 9(2), 297-315.
    Simar, L., & Wilson, P. W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of econometrics, 136(1), 31-64.
    Simar, L., & Wilson, P. W. (2011). Two-stage DEA: caveat emptor. Journal of Productivity Analysis, 36(2), 205.
    Sinkin, C., Wright, C. J., & Burnett, R. D. (2008). Eco-efficiency and firm value. Journal of Accounting and Public Policy, 27(2), 167-176.
    Staikouras, C., Mamatzakis, E., & Koutsomanoli-Filippaki, A. (2008). Cost efficiency of the banking industry in the South Eastern European region. Journal of International Financial Markets, Institutions and Money, 18(5), 483-497.
    Sun, L., & Chang, T. P. (2011). A comprehensive analysis of the effects of risk measures on bank efficiency: Evidence from emerging Asian countries. Journal of Banking & Finance, 35(7), 1727-1735.
    Surroca, J., Tribó, J. A., & Waddock, S. (2010). Corporate responsibility and financial performance: The role of intangible resources. Strategic management journal, 31(5), 463-490.
    Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498-509.
    Tone, K., & Tsutsui, M. (2009). Network DEA: A slacks-based measure approach. European journal of operational research, 197(1), 243-252.
    Van Beurden, P., & Gössling, T. (2008). The worth of values–a literature review on the relation between corporate social and financial performance. Journal of business ethics, 82(2), 407.
    Vance, S. C. (1975). Are socially responsible corporations good investment risks. Management review, 64(8), 19-24.
    Vitaliano, D. F., & Stella, G. P. (2006). The cost of corporate social responsibility: the case of the community reinvestment act. Journal of Productivity Analysis, 26(3), 235-244.
    Wainwright, K. (2005). Fundamental methods of mathematical economics/Alpha C. Chiang, Kevin Wainwright. Boston, Mass.: McGraw-Hill/Irwin,
    Wang, C. H., Gopal, R. D., & Zionts, S. (1997). Use of data envelopment analysis in assessing information technology impact on firm performance. Annals of operations Research, 73, 191-213.
    Wang, H. J., & Schmidt, P. (2002). One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels. journal of Productivity Analysis, 18(2), 129-144.
    Wu, J., Zhu, Q., Chu, J., & Liang, L. (2015). Two-stage network structures with undesirable intermediate outputs reused: a DEA based approach. Computational Economics, 46(3), 455-477.
    Wu, M. W., & Shen, C. H. (2013). Corporate social responsibility in the banking industry: Motives and financial performance. Journal of Banking & Finance, 37(9), 3529-3547.
    Wurgler, J. (2000). Financial markets and the allocation of capital. Journal of financial economics, 58(1-2), 187-214.
    Xue, M., & Harker, P. T. (1999). Overcoming the inherent dependency of DEA efficiency scores: a bootstrap approach. Unpublished Working Paper, Wharton Financial Institutions Center, University of Pennsylvania.
    Yang, C., & Liu, H. M. (2012). Managerial efficiency in Taiwan bank branches: A network DEA. Economic Modelling, 29(2), 450-461.
    Yang, S. L. (2016). Corporate social responsibility and an enterprise’s operational efficiency: considering competitor’s strategies and the perspectives of long-term engagement. Quality & Quantity, 50(6), 2553-2569.
    Yu, M. M., Chen, L. H., Chen, K. C., & Tone, K. (2013). Operational efficiency in Taiwan banks with consideration of nonperforming loans: a dynamic network DEA. In Workshop on DNDEA (pp. 106-8677).
    Zaim, O. (1995). The effect of financial liberalization on the efficiency of Turkish commercial banks. Applied Financial Economics, 5(4), 257-264.
    Zelenyuk, V., & Zheka, V. (2006). Corporate governance and firm’s efficiency: the case of a transitional country, Ukraine. Journal of Productivity Analysis, 25(1-2), 143-157.
    Zha, Y., Liang, N., Wu, M., & Bian, Y. (2016). Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach. Omega, 60, 60-72.
    Zhang, M., Zhang, W., & Zhang, S. (2016). National culture and firm investment efficiency: international evidence. Asia-Pacific Journal of Accounting & Economics, 23(1), 1-21.
    描述: 博士
    國立政治大學
    金融學系
    102352507
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0102352507
    資料類型: thesis
    DOI: 10.6814/NCCU202200370
    顯示於類別:[金融學系] 學位論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    250701.pdf9063KbAdobe PDF2191檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋