Measuring efficiency in DEA in the presence of common inputs

References

• Abbott, M., & Doucouliagos, C. (2003). The efficiency of Australian universities: A data envelopment analysis. Economics of Education Review, 22(1), 89–97. doi:10.1016/S0272-7757(01)00068-1
   Web of Science ®Google Scholar
• Abd Aziz, N. A., Mohd Janor, R., & Mahadi, R. (2013). Comparative departmental efficiency analysis within a university: A DEA approach. Proceedings of the 6th International Conference on University Learning and Teaching (InCULT 2012). Procedia – Social and Behavioral Sciences, 90, 540–548. doi:10.1016/j.sbspro.2013.07.124
   Google Scholar
• Agasisti, T., Catalano, G., Landoni, P., & Verganti, R. (2012). Evaluating the performance of academic departments: An analysis of research-related output efficiency. Research Evaluation, 21(1), 2–14. doi:10.1093/reseval/rvr001
   Web of Science ®Google Scholar
• Agha, S., Kuhail, I., Abdelnabi, N., Salem, M., & Ghanim, A. (2011). Assessment of academic departments efficiency using data envelopment analysis. Journal of Industrial Engineering and Management, 4(2), 301–325. doi:10.3926/jiem.2011.v4n2.p301-325
   Google Scholar
• Amirteimoori, A., & Nashtaei, R. A. (2006). The role of time in multi-component efficiency analysis: An application. Applied Mathematics and Computation, 177(1), 11–17. doi:10.1016/j.amc.2005.10.029
   Web of Science ®Google Scholar
• Avilés-Sacoto, S. V., Cook, W. D., & Güemes-Castorena, D. (2014). Competitiveness among higher education institutions: A two-stage Cobb-Douglas model for efficiency measurement of Schools of Business. Journal of Centrum Cathedra: The Business and Economics Research Journal, 7(1), 210–220. doi:10.7835/jcc-berj-2014-0097
   Google Scholar
• Avilés-Sacoto, S. V., Cook, W. D., Güemes-Castorena, D., & Cantú-Delgado, H. (2015). Time-staged outputs in DEA. OMEGA, the International Journal in Management Science, 55, 1–9. doi:10.1016/j.omega.2015.01.019
   Web of Science ®Google Scholar
• Banker, R., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale efficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092. doi:10.1287/mnsc.30.9.1078
   Web of Science ®Google Scholar
• Beasley, J. (1990). Comparing university departments. OMEGA, the International Journal in Management Science, 18(2), 171–183. doi:10.1016/0305-0483(90)90064-G
   Web of Science ®Google Scholar
• Beasley, J. (1995). Determining teaching and research efficiencies. Journal of the Operational Research Society, 46(4), 441–452. doi:10.2307/2584592
   Web of Science ®Google Scholar
• Bessent, A., Bessent, W., Charnes, A., Cooper, W., & Thorogood, N. (1983). Evaluation of educational program proposals by means of data envelopment analysis. Educational Administration Quarterly, 19(2), 82–107. doi:10.1177/0013161X83019002006
   Web of Science ®Google Scholar
• Bian, Y., Hu, M., & Xu, H. (2015). Measuring efficiencies of parallel systems with shared inputs/outputs using data envelopment analysis. Kybernetes, 44(3), 336–352. doi:10.1108/K-04-2014-0067
   Web of Science ®Google Scholar
• Cáceres, V. H., Kristjanpoller, R. W., & Tabilo, A. J. (2014). Análisis de la eficiencia técnica y su relación con los resultados de la evaluación de desempeño en una Universidad chilena. Innovar, 24(54), 199–217. doi:10.15446/innovar.v24n54.46720
   Google Scholar
• Carrico, C. S., Hogan, S. M., Dyson, R. G., & Athanassopoulos, A. D. (1997). Data envelopment analysis and university selection. The Journal of the Operational Research Society, 48(12), 1163–1177. doi:10.2307/3010747
   Web of Science ®Google Scholar
• Chalos, P. (1997). An examination of budgetary inefficiency in education using data envelopment analysis. Financial Accountability and Management, 13(1), 55–69. doi:10.1111/1468-0408.00026
   Google Scholar
• Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. doi:10.1016/0377-2217(78)90138-8
   Web of Science ®Google Scholar
• Chen, P., Hsu, S., Chan, C., & Yu, M. (2013). Efficiency measurements in multi-activity data envelopment analysis with shared inputs an application to farmers’ cooperatives. China Agricultural Economic Review, 5(1), 24–42. doi:10.1108/17561371311294748
   Web of Science ®Google Scholar
• Chen, Y., Du, J., Sherman, D., & Zhu, J. (2010). DEA model with shared resources and efficiency decomposition. European Journal of Operational Research, 207(1), 339–349. doi:10.1016/j.ejor.2010.03.031
   Web of Science ®Google Scholar
• Cook, W. D., Du, J., Liang, L., & Zhu, J. (2014). Fixed cost and resource allocation based on DEA cross efficiency. European Journal of Operational Research, 235(1), 206–214. doi:10.1016/j.ejor.2013.10.002
   Web of Science ®Google Scholar
• Cook, W. D., Green, R. H., & Zhu, J. (2006). Dual – Role factors in DEA. IIE Transactions, 38, 1–11. doi:10.1080/0740817050024557
   Web of Science ®Google Scholar
• Cook, W. D., & Hababou, M. (2001). Sales performance measurement in bank branches. OMEGA, the International Journal in Management Science, 29(4), 299–307. doi:10.1016/S0305-0483(01)00025-1
   Web of Science ®Google Scholar
• Cook, W. D., Hababou, M., & Tuenter, H. J. H. (2000). Multicomponent efficiency measurement and shared inputs in data envelopment analysis: An application to sales and service performance in bank branches. Journal of Productivity Analysis, 14(3), 209–224. doi:10.1023/A:102659880
   Web of Science ®Google Scholar
• Cook, W. D., Imanirad, R., Harrison, J., Rouse, P., & Zhu, J. (2013). Data envelopment analysis with non-homogeneous decision making units. Operations Research, 61(3), 666–676. doi:10.1287/opre.2013.1173
   Web of Science ®Google Scholar
• Cook, W. D., & Kress, M. (1999). Characterizing an equitable allocation of shared costs: A DEA approach. European Journal of Operational Research, 119(3), 652–661. doi:10.1016/S0377-2217(98)00337-3
   Web of Science ®Google Scholar
• Cook, W. D., & Zhu, J. (2005). Allocation of shared costs among decision making units: A DEA approach. Computers and Operations Research, 32(8), 2171–2178. doi:10.1016/j.cor.2004.02.007
   Web of Science ®Google Scholar
• Cook, W. D., & Zhu, J. (2011). Multiple variable proportionality in data envelopment analysis. Operations Research, 59(4), 1024–1032. doi:10.1287/opre.1110.0937
   Web of Science ®Google Scholar
• De Witte, K., & López-Torres, L. (2017). Efficiency in education: A review of literature and a way forward. Journal of the Operational Research Society, 68(4), 339–363. doi:10.1057/jors.2015.92
   Web of Science ®Google Scholar
• Ding, J., Dong, W., Liang, L., & Zhu, J. (2017). Goal congruence analysis in multi-division organizations with shared resources based on data envelopment analysis. European Journal of Operational Research, 263(3), 961–973. doi:10.1016/j.ejor.2017.06.040
   Web of Science ®Google Scholar
• Imanirad, R., Cook, W. D., & Zhu, J. (2013). Partial input to output impacts in DEA: Production considerations and resource sharing among business sub-units. Naval Research Logistics, 60(3), 190–207. doi:10.1002/nav.21528
   Web of Science ®Google Scholar
• Johnes, G., & Johnes, J. (1993). Measuring the research performance of UK economics departments: An application of data envelopment analysis. Oxford Economic Papers, 45(2), 332–347. doi:10.1093/oxfordjournals.oep.a042095
   Web of Science ®Google Scholar
• Kao, C. (2009). Efficiency measurement of parallel production systems. European Journal of Operational Research, 196(3), 1107–1112.
   Web of Science ®Google Scholar
• Kao, C., & Hung, H. (2008). Efficiency analysis of university departments: An empirical study. OMEGA. The International Journal in Management Science, 36, 653–666. doi:10.1016/j.omega.2006.02.003
   Web of Science ®Google Scholar
• Ma, J. (2015). A two-stage DEA model considering shared inputs and free intermediate measures. Expert Systems with Applications, 42(9), 4339–4347. doi:10.1016/j.eswa.2015.01.040
   Web of Science ®Google Scholar
• Marginson, S. (2014). Higher education and public good. In P. Gibb & R. Barnett (Eds.), Thinking about higher education (pp. 53–67). New York: Springer.
   Google Scholar
• Moreno, A., & Tadepalli, R. (2002). Assessing academic department efficiency at a public university. Managerial and Decision Economics, 23(7), 385–397. doi:10.1002/mde.1075
   Google Scholar
• Sebalj, D., Holbrook, A., & Bourke, S. (2012). The rise of ‘professional staff” and demise of the ‘non-academic’: A study of university staffing nomenclature preferences. Journal of Higher Education Policy and Management, 34(5), 463–472. doi:10.1080/1360080X.2012.715994
   Google Scholar
• Sîrbu, A., Cimpoies, D., & Racul, A. (2016). Use of data envelopment analysis to measure the performance efficiency of academic departments. Proceedings of the 5th International Conference “Agriculture for Life, Life for Agriculture”. Agriculture and Agricultural Science Procedia, 10, 578–585. doi:10.1016/j.aaspro.2016.09.037
   Google Scholar
• Smart, J. C. (2002). Higher education: Handbook of theory and research. New York: Algora Publishing.
   Google Scholar
• Tsai, P. F., & Molinero, C. (2002). A variable returns to scale data envelopment analysis model for the joint determination of efficiencies with an example of the UK Health Service. European Journal of Operations Research, 141(1), 21–38. doi:10.1016/S0377-2217(01)00223-5
   Web of Science ®Google Scholar
• Tyagi, P., Prasad Yadav, S., & Singh, S. P. (2009). Relative performance of academic departments using DEA with sensitivity analysis. Evaluation and Program Planning, 32(2), 168–177. doi:10.1016/j.evalprogplan.2008.10.002
   PubMed Web of Science ®Google Scholar
• Wu, J., Zhu, Q., Ji, X., Chu, J., & Liang, L. (2016). Two-stage network processes with shared resources and resources recovered from undesirable outputs. European Journal of Operational Research, 251(1), 182–197. doi:10.1016/j.ejor.2015.10.049
   Web of Science ®Google Scholar