Evaluation of decision-making units based on the weight-optimized DEA model

Jiasen Sun; Rui Yang; Xiang Ji; Jie Wu

Kybernetika (2017)

  • Volume: 53, Issue: 2, page 244-262
  • ISSN: 0023-5954

Abstract

top
Data envelopment analysis (DEA) is a methodology for measuring best relative efficiencies of a group of peer decision-making units (DMUs) that take multiple inputs to produce multiple outputs. However, the traditional DEA model only aims to maximize the efficiency of the DMU under evaluation. This usually leads to very small weights (even zero weights) being assigned to some inputs or outputs. Correspondingly, these inputs or outputs have little or even no contribution to efficiency, which is unfair and irrational. The purpose of this paper is to address this problem. Two new weight-optimized models are proposed based upon the perspective of cross evaluation. Using the results of an Advanced Manufacturing Technology (AMT) example, it is found that all AMTs are fully sorted. The decision maker can easily choose the best AMT. In addition, unreasonable weights of AMTs are effectively avoided.

How to cite

top

Sun, Jiasen, et al. "Evaluation of decision-making units based on the weight-optimized DEA model." Kybernetika 53.2 (2017): 244-262. <http://eudml.org/doc/288226>.

@article{Sun2017,
abstract = {Data envelopment analysis (DEA) is a methodology for measuring best relative efficiencies of a group of peer decision-making units (DMUs) that take multiple inputs to produce multiple outputs. However, the traditional DEA model only aims to maximize the efficiency of the DMU under evaluation. This usually leads to very small weights (even zero weights) being assigned to some inputs or outputs. Correspondingly, these inputs or outputs have little or even no contribution to efficiency, which is unfair and irrational. The purpose of this paper is to address this problem. Two new weight-optimized models are proposed based upon the perspective of cross evaluation. Using the results of an Advanced Manufacturing Technology (AMT) example, it is found that all AMTs are fully sorted. The decision maker can easily choose the best AMT. In addition, unreasonable weights of AMTs are effectively avoided.},
author = {Sun, Jiasen, Yang, Rui, Ji, Xiang, Wu, Jie},
journal = {Kybernetika},
keywords = {data envelopment analysis (DEA); efficiency; weight-optimized model; cross evaluation},
language = {eng},
number = {2},
pages = {244-262},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Evaluation of decision-making units based on the weight-optimized DEA model},
url = {http://eudml.org/doc/288226},
volume = {53},
year = {2017},
}

TY - JOUR
AU - Sun, Jiasen
AU - Yang, Rui
AU - Ji, Xiang
AU - Wu, Jie
TI - Evaluation of decision-making units based on the weight-optimized DEA model
JO - Kybernetika
PY - 2017
PB - Institute of Information Theory and Automation AS CR
VL - 53
IS - 2
SP - 244
EP - 262
AB - Data envelopment analysis (DEA) is a methodology for measuring best relative efficiencies of a group of peer decision-making units (DMUs) that take multiple inputs to produce multiple outputs. However, the traditional DEA model only aims to maximize the efficiency of the DMU under evaluation. This usually leads to very small weights (even zero weights) being assigned to some inputs or outputs. Correspondingly, these inputs or outputs have little or even no contribution to efficiency, which is unfair and irrational. The purpose of this paper is to address this problem. Two new weight-optimized models are proposed based upon the perspective of cross evaluation. Using the results of an Advanced Manufacturing Technology (AMT) example, it is found that all AMTs are fully sorted. The decision maker can easily choose the best AMT. In addition, unreasonable weights of AMTs are effectively avoided.
LA - eng
KW - data envelopment analysis (DEA); efficiency; weight-optimized model; cross evaluation
UR - http://eudml.org/doc/288226
ER -

References

top
  1. Anderson, T. R., Hollingsworth, K., Inman, L., 10.1023/a:1015012121760, J. Productivity Anal. 17 (2002), 3, 249-255. DOI10.1023/a:1015012121760
  2. Andersen, P., Petersen, N. C., 10.1287/mnsc.39.10.1261, Management Sci. 39 (1993), 10, 1261-1264. Zbl0800.90096DOI10.1287/mnsc.39.10.1261
  3. Banker, R. D., Charnes, A., Cooper, W. W., 10.1287/mnsc.30.9.1078, Management Sci. 30 (1984), 9, 1078-1092. Zbl0552.90055DOI10.1287/mnsc.30.9.1078
  4. Bougnol, M. L., Dulá, J. H., 10.1016/j.ejor.2007.10.034, Europ. J. Oper. Res. 192 (2009), 2, 668-676. Zbl1157.90435MR2454796DOI10.1016/j.ejor.2007.10.034
  5. Boussofiane, A., Dyson, R. G., Thanassoulis, E., 10.1016/0377-2217(91)90331-o, Europ. J. Oper. Res. 52 (1991), 1, 1-15. DOI10.1016/0377-2217(91)90331-o
  6. Charnes, A., Cooper, W. W., Rhodes, E., 10.1016/0377-2217(78)90138-8, Europ. J. Oper. Res. 2 (1978), 6, 429-444. Zbl0425.90086MR0525905DOI10.1016/0377-2217(78)90138-8
  7. Chen, C. M., Delmas, M. A., Lieberman, M. B., 10.1002/smj.2199, Strategic Management J. 36 (2015), 1, 19-36. DOI10.1002/smj.2199
  8. Cook, W. D., Bala, K., 10.1016/j.omega.2005.02.002, Omega 35 (2007), 1, 39-52. DOI10.1016/j.omega.2005.02.002
  9. Cook, W. D., Seiford, L. M., 10.1016/j.ejor.2008.01.032, Europ. J. Oper. Res. 192 (2009), 1, 1-17. Zbl1180.90151MR2458453DOI10.1016/j.ejor.2008.01.032
  10. Cook, W. D., Tone, K., Zhu, J., 10.1016/j.omega.2013.09.004, Omega 44 (2014), 1-4. DOI10.1016/j.omega.2013.09.004
  11. Cook, W. D., Zhu, J., 10.1057/jors.2013.13, J. Oper. Res. Soc. 65 (2013), 2, 265-268. DOI10.1057/jors.2013.13
  12. Cook, W. D., Zhu, J., 10.1007/978-1-4899-7553-9_2, Springer US 2015. MR3362964DOI10.1007/978-1-4899-7553-9_2
  13. Cooper, W. W., Seiford, L. M., Tone, K., 10.1007/978-0-387-45283-8, Springer-Verlag US, 2007. Zbl1111.90001DOI10.1007/978-0-387-45283-8
  14. Cooper, W. W., Seiford, L. M., Zhu, J., 10.1007/1-4020-7798-x_1, Springer US 2004. MR2077628DOI10.1007/1-4020-7798-x_1
  15. Cui, Q., Li, Y., 10.1016/j.jairtraman.2015.02.008, J. Air Transport Management 44 (2015), 34-41. DOI10.1016/j.jairtraman.2015.02.008
  16. Despotis, D. K., 10.1057/palgrave/jors/2601253, J. Oper. Res. Soc. 53 (2002), 3, 314-323. Zbl1103.90350DOI10.1057/palgrave/jors/2601253
  17. Doyle, J. R., Green, R. H., 10.1038/sj/jors/0450509, J. Oper. Res. Soc. 45 (1994), 5, 567-578. Zbl0807.90016DOI10.1038/sj/jors/0450509
  18. Doyle, J. R., Green, R. H., 10.1080/03155986.1995.11732281, Infor 33 (1995), 3, 205-222. Zbl0832.90002DOI10.1080/03155986.1995.11732281
  19. Emrouznejad, A., Parker, B. R., Tavares, G., 10.1016/j.seps.2007.07.002, Socio-economic Planning Sci. 42 (2008), 3, 151-157. MR2593179DOI10.1016/j.seps.2007.07.002
  20. Falagario, M., Sciancalepore, F., Costantino, N., Pietroforte, R., 10.1016/j.ejor.2011.10.031, Europ. J. Oper. Res. 218 (2012), 2, 523-529. Zbl1244.90156MR2874471DOI10.1016/j.ejor.2011.10.031
  21. Green, R. H., Doyle, J. R., Cook, W. D., 10.1016/0377-2217(95)00039-9, Europ. J. Oper. Res. 90 (1996), 3, 461-472. Zbl0911.90009DOI10.1016/0377-2217(95)00039-9
  22. Jahanshahloo, G. R., Lotfi, F. H., Jafari, Y., Maddahi, R., 10.1016/j.apm.2010.07.020, Appl. Math. Modelling 35 (2011), 1, 544-549. Zbl1202.90249MR2677963DOI10.1016/j.apm.2010.07.020
  23. Ji, X., Sun, J., Wang, Y., Yuan, Q., 10.1016/j.jclepro.2016.02.117, J. Cleaner Product. 142 (2017), 894-906. DOI10.1016/j.jclepro.2016.02.117
  24. Ji, X., Wu, J., Zhu, Q., 10.1016/j.trd.2015.08.007, Transport. Res. Part D: Transport and Environment 48 (2016), 451-459. DOI10.1016/j.trd.2015.08.007
  25. Khouja, M., 10.1016/0360-8352(94)00032-i, Computers Industr. Engrg. 28 (1995), 1, 123-132. DOI10.1016/0360-8352(94)00032-i
  26. Liang, L., Wu, J., Cook, W. D., Zhu, J., 10.1016/j.ijpe.2007.12.006, Int. J. Product. Econom. 113 (2008), 2, 1025-1030. DOI10.1016/j.ijpe.2007.12.006
  27. Liang, L., Wu, J., Cook, W. D., Zhu, J., 10.1287/opre.1070.0487, Oper. Res. 56 (2008), 5, 1278-1288. Zbl1167.91330MR2468913DOI10.1287/opre.1070.0487
  28. Liang, L., Yang, F., Cook, W. D., Zhu, J., 10.1007/s10479-006-0026-7, Ann. Oper. Res. 145 (2006), 1, 35-49. Zbl1106.90045MR2258637DOI10.1007/s10479-006-0026-7
  29. Lim, S., 10.1016/j.cie.2011.11.010, Computers Industr. Engrg. 62 (2002), 3, 726-731. DOI10.1016/j.cie.2011.11.010
  30. Lim, S., Zhu, J., 10.1057/jors.2014.13, J. Oper. Res. Soc. 66 (2014), 3, 476-487. MR3362965DOI10.1057/jors.2014.13
  31. Lim, S., Zhu, J., DEA Cross Efficiency Under Variable Returns to Scale. In Data Envelopment Analysis., Springer US 2015. MR3362965
  32. Maddahi, R., Jahanshahloo, G.J. ZhuR., Lotfi, F. Hosseinzadeh, Ebrahimnejad, A., 10.1504/ijor.2014.058953, Int. J. Oper. Res. 19 (2014), 2, 234-245. MR3242695DOI10.1504/ijor.2014.058953
  33. Ramón, N., Ruiz, J.J. ZhuL., Sirvent, I., 10.1016/j.ejor.2009.07.009, Europ. J. Oper. Res. 203 (2010), 1, 261-269. Zbl1176.90313DOI10.1016/j.ejor.2009.07.009
  34. Ramón, N., Ruiz, J. L., Sirvent, I., 10.1016/j.ejor.2010.07.022, Europ. J. Oper. Res. 207 (2010), 3, 1564-1572. DOI10.1016/j.ejor.2010.07.022
  35. Ramón, N., Ruiz, J. L., Sirvent, I., 10.1016/j.omega.2011.01.004, Omega 39 (2011), 6, 634-641. DOI10.1016/j.omega.2011.01.004
  36. Sexton, T. R., Silkman, R. H., Hogan, A. J., 10.1002/ev.1441, New Directions for Program Evaluation 1986 (1986), 32, 73-105. DOI10.1002/ev.1441
  37. Sun, J., Miao, Y., Wu, J., Cui, L., Zhong, R., 10.14736/kyb-2014-5-0774, Kybernetika 50 (2014), 5, 774-785. Zbl1308.90078MR3301860DOI10.14736/kyb-2014-5-0774
  38. Sun, J., Wu, J., Guo, D., 10.1016/j.apm.2013.01.010, Appl. Math. Modelling 37 (2013), 9, 6301-6310. MR3039010DOI10.1016/j.apm.2013.01.010
  39. Sun, J., Wu, J., Liang, L., Zhong, R. Y., Huang, G. Q., 10.1080/00207543.2013.829592, Int. J. Product. Res. 52 (2014), 2, 419-435. DOI10.1080/00207543.2013.829592
  40. Sun, S., 10.1080/00207540210123634, Int. J. Product. Res. 40 (2002), 9, 2011-2039. Zbl1048.90509DOI10.1080/00207540210123634
  41. Tone, K., 10.1016/s0377-2217(99)00407-5, Europ. J. Oper. Res. 130 (2001), 3, 498-509. Zbl0990.90523MR1816667DOI10.1016/s0377-2217(99)00407-5
  42. Wang, Y. .M., Chin, K. S., 10.1016/j.ijpe.2010.07.032, Int. J. Product. Econom. 128 (2010), 1, 332-338. DOI10.1016/j.ijpe.2010.07.032
  43. Wang, Y. M., Chin, K. S., 10.1016/j.eswa.2009.10.024, Expert Systems Appl. 37 (2010), 5, 3666-3675. DOI10.1016/j.eswa.2009.10.024
  44. Wang, Y. M., Chin, K. S., Jiang, P., 10.1016/j.cie.2011.04.004, Computers Industr. Engrg. 61 (2011), 3, 497-502. DOI10.1016/j.cie.2011.04.004
  45. Wang, Y. M., Chin, K. S., Luo, Y., 10.1016/j.eswa.2011.02.116, Expert Systems Appl. 38 (2011), 8, 10312-10319. DOI10.1016/j.eswa.2011.02.116
  46. Wang, Y. M., Luo, Y., 10.1016/j.amc.2005.04.023, Appl. Math. Comput. 173 (2006), 2, 902-915. Zbl1112.90355MR2207985DOI10.1016/j.amc.2005.04.023
  47. Wu, J., Liang, L., Chen, Y., 10.1016/j.omega.2008.07.001, Omega 37 (2009), 4, 909-918. DOI10.1016/j.omega.2008.07.001
  48. Wu, J., Liang, L., Yang, F., 10.1016/j.eswa.2007.10.006, Expert Systems Appl. 36 (2009), 1, 872-876. DOI10.1016/j.eswa.2007.10.006
  49. Wu, J., Sun, J., Liang, L., 10.1016/j.cie.2012.04.017, Computers Industr. Engrg. 63 (2012), 2, 513-519. DOI10.1016/j.cie.2012.04.017
  50. Wu, J., Sun, J., Zha, Y., Liang, L., 10.3969/j.issn.1004-4132.2011.04.008, J. Systems Engrg. Electron. 22 (2011), 4, 604-608. DOI10.3969/j.issn.1004-4132.2011.04.008
  51. Zhou, P., Wang, B., Poh, K. L., 10.1016/j.ejor.2007.04.042, Europ. J. Oper. Res. 189 (2008), 1, 1-18. MR2397682DOI10.1016/j.ejor.2007.04.042

NotesEmbed ?

top

You must be logged in to post comments.