Abstract
This study proposes the integration of two nonparametric methodologies - Data Envelopment Analysis and Artificial Neural Network for efficiency evaluation. The paper initially outlines the research work conducted in the education sector using DEA and ANN. Furthermore, the case study for the paper is conducted on various State Boards (which are used as DMU’s) in Indian Higher Secondary Education System for efficiency evaluation using DEA which is integrated with soft computing technique ANN in order to increase discriminatory power, ranking and future prediction. The above two methods are compared on their practical use as a performance measurement tool on a set of Indian State Boards in Indian Higher Secondary Education System with multiple inputs and outputs criteria. The results demonstrate that ANN-DEA Integration optimizes the performance and increases the discriminatory power and ranking of the decision making units.
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References
Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2(6), 429–444 (1978)
Banker, R.D., Charnes, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage. Sci. 30(9), 1078–1092 (1984)
Bradley, S., Johnes, G., Millington, J.: The effect of competition on the efficiency of secondary schools in England. Eur. J. Oper. Res. 135(3), 545–568 (2001)
Afonso, A., St Aubyn, M.: Non-parametric approaches to education and health efficiency in OECD countries. J. Appl. Econ. 8(2), 227–246 (2005)
Johnes, J., Li, Y.U.: Measuring the research performance of Chinese higher education institutions using data envelopment analysis. China Econ. Rev. 19(4), 679–696 (2008)
Kuah, C.T., Wong, K.Y.: Efficiency assessment of universities through data envelopment analysis. Procedia Comput. Sci. 3, 499–506 (2011)
Agasisti, T.: The efficiency of Italian secondary schools and the potential role of competition: a data envelopment analysis using OECD-PISA2006 data. Educ., Econ. Taylor Francis J. 21(5), 520–544 (2013)
Selim, S., Bursalıoğlu, S.A.: Efficiency of higher education in turkey: a bootstrapped two-stage DEA approach. Int. J. Stat. Appl. 5(2), 55–67 (2015)
Sagarra, M., et al.: Exploring the efficiency of Mexican universities: integrating data envelopment analysis and multidimensional scaling. Omega 63, 123–133 (2017)
Athanassopoulos, A.D., Curram, S.P.: A comparison of data envelopment analysis and artificial neural networks as tools for assessing the efficiency of decision making units. J. Oper. Res. Soc. 47(8), 1000–1016 (1996)
Emrouznejad, A., Shale, E.: A combined neural network and DEA for measuring efficiency of large scale datasets. Comput. Ind. Eng. 56(1), 249–254 (2009)
Liu, H.-H., Chen, T.-Y., Chiu, Y.-H., Kuo, F.-H.: A comparison of three-stage DEA and artificial neural network on the operational efficiency of semi-conductor firms in Taiwan. Mod. Econ. 4(1), 20–31 (2013)
Kuo, R.J., Wang, Y.C., Tien, F.C.: Integration of artificial neural network and MADA methods for green supplier selection. J. Clean. Prod. 18(12), 1161–1170 (2010)
Kwon, H.: Performance modeling of mobile phone providers: a DEA-ANN combined approach. Benchmarking Int. J. 22(6), 1120–1144 (2014)
Oladokun, V.O., Adebanjo, A.T., Charles-Owaba, O.E.: Predicting students’ academic performance using artificial neural network: a case study of an engineering course. Pac. J. Sci. Technol. 9(1), 72–79 (2008)
Chen, C., et al.: Online 24-h solar power forecasting based on weather type classification using artificial neural network. Sol. Energy 85(11), 2856–2870 (2011)
Cheh, J.J., Weinberg, R.S., Yook, K.C.: An application of an artificial neural network investment system to predict takeover targets. J. Appl. Bus. Res. (JABR) 15(4), 33–46 (2013)
Chhachhiya, D., Sharma, A., Gupta, M.: Designing optimal architecture of neural network with particle swarm optimization techniques specifically for educational dataset. In: 7th International Conference on Cloud Computing, Data Science & Engineering-Confluence, pp 52–57. IEEE, Noida (2017)
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Singh, N., Pant, M. (2018). Evaluating the Efficiency of Higher Secondary Education State Boards in India: A DEA-ANN Approach. In: Abraham, A., Muhuri, P., Muda, A., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2017. Advances in Intelligent Systems and Computing, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-76348-4_90
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DOI: https://doi.org/10.1007/978-3-319-76348-4_90
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