Methods and applications of DEA cross-efficiency: Review and future perspectives

doi:10.1007/s42524-020-0133-1

Front. Eng

2021, Vol. 8

Issue (2) : 199-211 https://doi.org/10.1007/s42524-020-0133-1

REVIEW ARTICLE

Methods and applications of DEA cross-efficiency: Review and future perspectives

Jie WU¹, Jiasen SUN²(

), Liang LIANG³

¹. School of Management, University of Science and Technology of China, Hefei 230026, China
². Business School, Soochow University, Suzhou 215012, China; College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
³. School of Management, Hefei University of Technology, Hefei 230009, China

Download: PDF(323 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

The field of engineering management usually involves evaluation issues, such as program selection, team performance evaluation, technology selection, and supplier evaluation. The traditional self-evaluation data envelopment analysis (DEA) method usually exaggerates the effects of several inputs or outputs of the evaluated decision-making unit (DMU), resulting in unrealistic results. To address this problem, scholars have proposed the cross-efficiency evaluation (CREE) method. Compared with the DEA method, CREE can rank DMUs more completely by using reasonable weights. With the extensive application of this technique, several problems, such as non-unique weights and non-Pareto optimal results, have arisen in CREE methods. Therefore, the improvement of CREE has attracted the attention of many scholars. This paper reviews the theory and applications of CREE, including the non-uniqueness problem, the aggregation of cross-efficiency data, and applications in engineering management. It also discusses the directions for future research on CREE.

Keywords cross-efficiency evaluation efficiency secondary goal model aggregation review

Corresponding Author(s): Jiasen SUN

Just Accepted Date: 30 July 2020 Online First Date: 07 September 2020 Issue Date: 25 March 2021

Cite this article:

Jie WU,Jiasen SUN,Liang LIANG. Methods and applications of DEA cross-efficiency: Review and future perspectives[J]. Front. Eng, 2021, 8(2): 199-211.

URL:

https://academic.hep.com.cn/fem/EN/10.1007/s42524-020-0133-1
https://academic.hep.com.cn/fem/EN/Y2021/V8/I2/199

Fig.1 Numbers of papers about CREE published annually (data source: Web of Science Core Collection; search topic: cross-efficiency; categories: management, operations research, and management science).

Tab.1 Top 10 authors, journals, and institutions with most published papers about CREE

Fig.2 Theoretical development of CREE.

1	J Alcaraz, N Ramón, J L Ruiz, I Sirvent (2013). Ranking ranges in cross-efficiency evaluations. European Journal of Operational Research, 226(3): 516–521 https://doi.org/10.1016/j.ejor.2012.11.034
2	P Andersen, N C Petersen (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10): 1261–1264 https://doi.org/10.1287/mnsc.39.10.1261
3	T R Anderson, K Hollingsworth, L Inman (2002). The fixed weighting nature of a cross-evaluation model. Journal of Productivity Analysis, 17(3): 249–255 https://doi.org/10.1023/A:1015012121760
4	P C Baker, S Talluri (1997). A closer look at the use of data envelopment analysis for technology selection. Computers & Industrial Engineering, 32(1): 101–108 https://doi.org/10.1016/S0360-8352(96)00199-4
5	C P Barros (2006). A benchmark analysis of Italian seaports using data envelopment analysis. Maritime Economics & Logistics, 8(4): 347–365 https://doi.org/10.1057/palgrave.mel.9100163
6	A Boussofiane, R G Dyson, E Thanassoulis (1991). Applied data envelopment analysis. European Journal of Operational Research, 52(1): 1–15 https://doi.org/10.1016/0377-2217(91)90331-O
7	M Braglia, A Petroni (1999). Evaluating and selecting investments in industrial robots. International Journal of Production Research, 37(18): 4157–4178 https://doi.org/10.1080/002075499189718
8	M T Brannick, E Salas, C W Prince (1997). Team Performance Assessment and Measurement: Theory, Methods, and Applications. Hove, East Sussex: Psychology Press
9	C M Chang (2008). Engineering management in developing economies: The EMIDE approaches to meet the new challenges. International Journal of Innovation & Technology Management, 5(4): 381–400 https://doi.org/10.1142/S0219877008001461
10	A Charnes, W W Cooper, E Rhodes (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6): 429–444 https://doi.org/10.1016/0377-2217(78)90138-8
11	J X Chen (2011). Peer-estimation for multiple criteria ABC inventory classification. Computers & Operations Research, 38(12): 1784–1791 https://doi.org/10.1016/j.cor.2011.02.015
12	L Chen, Y M Wang (2016). Data envelopment analysis cross-efficiency model in fuzzy environments. Journal of Intelligent & Fuzzy Systems, 30(5): 2601–2609 https://doi.org/10.3233/IFS-151878
13	L Chen, Y M Wang (2020). DEA target setting approach within the cross efficiency framework. Omega, 96: 102072
14	W Chen, K Zhou, S Yang (2017). Evaluation of China’s electric energy efficiency under environmental constraints: A DEA cross efficiency model based on game relationship. Journal of Cleaner Production, 164: 38–44 https://doi.org/10.1016/j.jclepro.2017.06.178
15	M T Chu, J Z Shyu, R Khosla (2008). Measuring the relative performance for leading fabless firms by using data envelopment analysis. Journal of Intelligent Manufacturing, 19(3): 257–272 https://doi.org/10.1007/s10845-008-0079-3
16	W D Cook, L M Seiford (2009). Data envelopment analysis (DEA) — Thirty years on. European Journal of Operational Research, 192(1): 1–17 https://doi.org/10.1016/j.ejor.2008.01.032
17	Q Cui, Y Li (2015). Evaluating energy efficiency for airlines: An application of VFB-DEA. Journal of Air Transport Management, 44– 45: 34–41 https://doi.org/10.1016/j.jairtraman.2015.02.008
18	D K Despotis (2002). Improving the discriminating power of DEA: Focus on globally efficient units. Journal of the Operational Research Society, 53(3): 314–323 https://doi.org/10.1057/palgrave.jors.2601253
19	L Ding, Y Yang, W Wang, A C Calin (2019). Regional carbon emission efficiency and its dynamic evolution in China: A novel cross efficiency-malmquist productivity index. Journal of Cleaner Production, 241: 118260 https://doi.org/10.1016/j.jclepro.2019.118260
20	M Dotoli, N Epicoco, M Falagario, F Sciancalepore (2016). A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty. International Transactions in Operational Research, 23(4): 725–748 https://doi.org/10.1111/itor.12155
21	J Doyle, R Green (1994). Efficiency and cross-efficiency in DEA: Derivations, meanings and uses. Journal of the Operational Research Society, 45(5): 567–578 https://doi.org/10.1057/jors.1994.84
22	J Du, W D Cook, L Liang, J Zhu (2014). Fixed cost and resource allocation based on DEA cross-efficiency. European Journal of Operational Research, 235(1): 206–214 https://doi.org/10.1016/j.ejor.2013.10.002
23	R G Dyson, E Thanassoulis (1988). Reducing weight flexibility in data envelopment analysis. Journal of the Operational Research Society, 39(6): 563–576 https://doi.org/10.1057/jors.1988.96
24	C Enberg (2012). Enabling knowledge integration in coopetitive R&D projects — The management of conflicting logics. International Journal of Project Management, 30(7): 771–780 https://doi.org/10.1016/j.ijproman.2012.01.003
25	T Ertay, D Ruan (2005). Data envelopment analysis based decision model for optimal operator allocation in CMS. European Journal of Operational Research, 164(3): 800–810 https://doi.org/10.1016/j.ejor.2004.01.038
26	R Färe, S Grosskopf, M Norris, Z Zhang (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. The American Economic Review, 84(1): 66–83
27	Z Geng, J Dong, Y Han, Q Zhu (2017). Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes. Applied Energy, 205: 465–476 https://doi.org/10.1016/j.apenergy.2017.07.132
28	D Guo, J Wu (2013). A complete ranking of DMUs with undesirable outputs using restrictions in DEA models. Mathematical and Computer Modelling, 58(5–6): 1102–1109 https://doi.org/10.1016/j.mcm.2011.12.044
29	A Hatami-Marbini, P J Agrell, M Tavana, P Khoshnevis (2017). A flexible cross-efficiency fuzzy data envelopment analysis model for sustainable sourcing. Journal of Cleaner Production, 142: 2761–2779 https://doi.org/10.1016/j.jclepro.2016.10.192
30	J D Hong, K Y Jeong (2017). Cross efficiency based heuristics to rank decision making units in data envelopment analysis. Computers & Industrial Engineering, 111: 320–330 https://doi.org/10.1016/j.cie.2017.06.015
31	G R Jahanshahloo, M Khodabakhshi, F Hosseinzadeh Lotfi, M R Moazami Goudarzi (2011). A cross-efficiency model based on super-efficiency for ranking units through the TOPSIS approach and its extension to the interval case. Mathematical and Computer Modelling, 53(9–10): 1946–1955 https://doi.org/10.1016/j.mcm.2011.01.025
32	C Kao, S T Liu (2019). Cross efficiency measurement and decomposition in two basic network systems. Omega, 83: 70–79 https://doi.org/10.1016/j.omega.2018.02.004
33	K F Lam (2010). In the determination of weight sets to compute cross-efficiency ratios in DEA. Journal of the Operational Research Society, 61(1): 134–143 https://doi.org/10.1057/jors.2008.138
34	W J Lannes (2001). What is engineering management? IEEE Transactions on Engineering Management, 48(1): 107–115 https://doi.org/10.1109/17.913170
35	K H Lee, R Farzipoor Saen (2012). Measuring corporate sustainability management: A data envelopment analysis approach. International Journal of Production Economics, 140(1): 219–226 https://doi.org/10.1016/j.ijpe.2011.08.024
36	F Li, Q Zhu, Z Chen, H Xue (2018). A balanced data envelopment analysis cross-efficiency evaluation approach. Expert Systems with Applications, 106: 154–168 https://doi.org/10.1016/j.eswa.2018.04.009
37	H B Li, L Lei (2007). DEA-based project knowledge management performance evaluation. In: International Conference on Management Science & Engineering. Harbin, 1561–1566
38	L Liang, J Wu, W D Cook, J Zhu (2008a). Alternative secondary goals in DEA cross-efficiency evaluation. International Journal of Production Economics, 113(2): 1025–1030 https://doi.org/10.1016/j.ijpe.2007.12.006
39	L Liang, J Wu, W D Cook, J Zhu (2008b). The DEA game cross-efficiency model and its Nash equilibrium. Operations Research, 56(5): 1278–1288 https://doi.org/10.1287/opre.1070.0487
40	S Lim (2012a). Context-dependent data envelopment analysis with cross-efficiency evaluation. Journal of the Operational Research Society, 63(1): 38–46 https://doi.org/10.1057/jors.2011.29
41	S Lim (2012b). Minimax and maximin formulations of cross-efficiency in DEA. Computers & Industrial Engineering, 62(3): 726–731 https://doi.org/10.1016/j.cie.2011.11.010
42	S Lim, K W Oh, J Zhu (2014). Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market. European Journal of Operational Research, 236(1): 361–368 https://doi.org/10.1016/j.ejor.2013.12.002
43	S Lim, J Zhu (2015). DEA cross-efficiency evaluation under variable returns to scale. Journal of the Operational Research Society, 66(3): 476–487 https://doi.org/10.1057/jors.2014.13
44	L C Lin, C C Tseng (2007). Operational performance evaluation of major container ports in the Asia-Pacific region. Maritime Policy & Management, 34(6): 535–551 https://doi.org/10.1080/03088830701695248
45	R Lin, Z Chen, W Xiong (2016). An iterative method for determining weights in cross efficiency evaluation. Computers & Industrial Engineering, 101: 91–102 https://doi.org/10.1016/j.cie.2016.08.024
46	B Liu, C Tian, Y Li, H Song, Z Ma (2018). Research on the effects of urbanization on carbon emissions efficiency of urban agglomerations in China. Journal of Cleaner Production, 197: 1374–1381 https://doi.org/10.1016/j.jclepro.2018.06.295
47	H H Liu, Y Y Song, G L Yang (2019). Cross-efficiency evaluation in data envelopment analysis based on prospect theory. European Journal of Operational Research, 273(1): 364–375 https://doi.org/10.1016/j.ejor.2018.07.046
48	S T Liu (2018). A DEA ranking method based on cross-efficiency intervals and signal-to-noise ratio. Annals of Operations Research, 261(1–2): 207–232 https://doi.org/10.1007/s10479-017-2562-8
49	W Liu, Y M Wang, S Lv (2017a). An aggressive game cross-efficiency evaluation in data envelopment analysis. Annals of Operations Research, 259(1–2): 241–258 https://doi.org/10.1007/s10479-017-2524-1
50	X Liu, J Chu, P Yin, J Sun (2017b). DEA cross-efficiency evaluation considering undesirable output and ranking priority: A case study of eco-efficiency analysis of coal-fired power plants. Journal of Cleaner Production, 142: 877–885 https://doi.org/10.1016/j.jclepro.2016.04.069
51	C Lo Storto (2016). Ecological efficiency based ranking of cities: A combined DEA cross-efficiency and Shannon’s entropy method. Sustainability, 8(2): 124 https://doi.org/10.3390/su8020124
52	W M Lu, S F Lo (2007). A closer look at the economic-environmental disparities for regional development in China. European Journal of Operational Research, 183(2): 882–894 https://doi.org/10.1016/j.ejor.2006.10.027
53	R Ma, L Yao, M Jin, P Ren (2014). The DEA game cross-efficiency model for supplier selection problem under competition. Applied Mathematics & Information Sciences, 8(2): 811–818 https://doi.org/10.12785/amis/080242
54	M Mahdiloo, R Farzipoor Saen, K H Lee (2015). Technical, environmental and eco-efficiency measurement for supplier selection: An extension and application of data envelopment analysis. International Journal of Production Economics, 168: 279–289 https://doi.org/10.1016/j.ijpe.2015.07.010
55	A Noorizadeh, M Mahdiloo, R Farzipoor Saen (2013). Using DEA cross-efficiency evaluation for suppliers ranking in the presence of non-discretionary inputs. International Journal of Shipping and Transport Logistics, 5(1): 95–111 https://doi.org/10.1504/IJSTL.2013.050595
56	H H Örkcü, H Bal (2011). Goal programming approaches for data envelopment analysis cross efficiency evaluation. Applied Mathematics and Computation, 218(2): 346–356 https://doi.org/10.1016/j.amc.2011.05.070
57	A Oukil (2019). Embedding OWA under preference ranking for DEA cross-efficiency aggregation: Issues and procedures. International Journal of Intelligent Systems, 34(5): 947–965 https://doi.org/10.1002/int.22082
58	J Park, H Bae, J Bae (2014). Cross-evaluation-based weighted linear optimization for multi-criteria ABC inventory classification. Computers & Industrial Engineering, 76: 40–48 https://doi.org/10.1016/j.cie.2014.07.020
59	N Ramón, J L Ruiz, I Sirvent (2010a). A multiplier bound approach to assess relative efficiency in DEA without slacks. European Journal of Operational Research, 203(1): 261–269 https://doi.org/10.1016/j.ejor.2009.07.009
60	N Ramón, J L Ruiz, I Sirvent (2010b). On the choice of weights profiles in cross-efficiency evaluations. European Journal of Operational Research, 207(3): 1564–1572 https://doi.org/10.1016/j.ejor.2010.07.022
61	N Ramón, J L Ruiz, I Sirvent (2011). Reducing differences between profiles of weights: A “peer-restricted” cross-efficiency evaluation. Omega, 39(6): 634–641 https://doi.org/10.1016/j.omega.2011.01.004
62	N Ramón, J L Ruiz, I Sirvent (2014). Dominance relations and ranking of units by using interval number ordering with cross-efficiency intervals. Journal of the Operational Research Society, 65(9): 1336–1343 https://doi.org/10.1057/jors.2013.90
63	M J Rezaee, H Izadbakhsh, S Yousefi (2016). An improvement approach based on DEA-game theory for comparison of operational and spatial efficiencies in urban transportation systems. KSCE Journal of Civil Engineering, 20(4): 1526–1531 https://doi.org/10.1007/s12205-015-0345-9
64	W Rödder, E Reucher (2011). A consensual peer-based DEA-model with optimized cross-efficiencies — Input allocation instead of radial reduction. European Journal of Operational Research, 212(1): 148–154 https://doi.org/10.1016/j.ejor.2011.01.035
65	J L Ruiz (2013). Cross-efficiency evaluation with directional distance functions. European Journal of Operational Research, 228(1): 181–189 https://doi.org/10.1016/j.ejor.2013.01.030
66	J Sarkis (2000). An analysis of the operational efficiency of major airports in the United States. Journal of Operations Management, 18(3): 335–351 https://doi.org/10.1016/S0272-6963(99)00032-7
67	J Sarkis, S Talluri (2004). Performance based clustering for benchmarking of US airports. Transportation Research Part A, Policy and Practice, 38(5): 329–346 https://doi.org/10.1016/j.tra.2003.11.001
68	J Sarkis, J Weinrach (2001). Using data envelopment analysis to evaluate environmentally conscious waste treatment technology. Journal of Cleaner Production, 9(5): 417–427 https://doi.org/10.1016/S0959-6526(00)00084-6
69	T R Sexton, R H Silkman, A J Hogan (1986). Data envelopment analysis: Critique and extensions. New Directions for Program Evaluation, (32): 73–105
70	J Shang, T Sueyoshi (1995). A unified framework for the selection of a flexible manufacturing system. European Journal of Operational Research, 85(2): 297–315 https://doi.org/10.1016/0377-2217(94)00041-A
71	H Shi, Y Wang, L Chen (2019). Neutral cross-efficiency evaluation regarding an ideal frontier and anti-ideal frontier as evaluation criteria. Computers & Industrial Engineering, 132: 385–394 https://doi.org/10.1016/j.cie.2019.04.035
72	L Song, F Liu (2018). An improvement in DEA cross-efficiency aggregation based on the Shannon entropy. International Transactions in Operational Research, 25(2): 705–714 https://doi.org/10.1111/itor.12361
73	M Song, J Zhang, S Wang (2015). Review of the network environmental efficiencies of listed petroleum enterprises in China. Renewable & Sustainable Energy Reviews, 43: 65–71 https://doi.org/10.1016/j.rser.2014.11.050
74	M Song, Q Zhu, J Peng, E D R Santibanez Gonzalez (2017). Improving the evaluation of cross efficiencies: A method based on Shannon entropy weight. Computers & Industrial Engineering, 112: 99–106 https://doi.org/10.1016/j.cie.2017.07.023
75	J Sun, Y Fu, X Ji, R Y Zhong (2017a). Allocation of emission permits using DEA-game-theoretic model. Operations Research, 17(3): 867–884 https://doi.org/10.1007/s12351-016-0289-y
76	J Sun, G Li, Z Wang (2018a). Optimizing China’s energy consumption structure under energy and carbon constraints. Structural Change and Economic Dynamics, 47: 57–72 https://doi.org/10.1016/j.strueco.2018.07.007
77	J Sun, G Li, Z Wang (2019). Technology heterogeneity and efficiency of China’s circular economic systems: A game meta-frontier DEA approach. Resources, Conservation and Recycling, 146: 337–347 https://doi.org/10.1016/j.resconrec.2019.03.046
78	J Sun, Z Wang, G Li (2018b). Measuring emission-reduction and energy-conservation efficiency of Chinese cities considering management and technology heterogeneity. Journal of Cleaner Production, 175: 561–571 https://doi.org/10.1016/j.jclepro.2017.12.042
79	J Sun, J Wu, D Guo (2013). Performance ranking of units considering ideal and anti-ideal DMU with common weights. Applied Mathematical Modelling, 37(9): 6301–6310 https://doi.org/10.1016/j.apm.2013.01.010
80	J Sun, J Wu, Y Wang, L Li, Y Wang (2018c). Cross-efficiency evaluation method based on the conservative point of view. Expert Systems, e12336 https://doi.org/10.1111/exsy.12336
81	J Sun, R Yang, X Ji, J Wu (2017b). Evaluation of decision-making units based on the weight-optimized DEA model. Kybernetika, 53(2): 244–262 https://doi.org/10.14736/kyb-2017-2-0244
82	J Sun, Y Yuan, R Yang, X Ji, J Wu (2017c). Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis. Transport Policy, 60: 75–86 https://doi.org/10.1016/j.tranpol.2017.09.001
83	S Sun (2002). Assessing computer numerical control machines using data envelopment analysis. International Journal of Production Research, 40(9): 2011–2039 https://doi.org/10.1080/00207540210123634
84	S Talluri, K Paul Yoon (2000). A cone-ratio DEA approach for AMT justification. International Journal of Production Economics, 66(2): 119–129 https://doi.org/10.1016/S0925-5273(99)00123-1
85	Y Tan, Y Zhang, R Khodaverdi (2017). Service performance evaluation using data envelopment analysis and balance scorecard approach: An application to automotive industry. Annals of Operations Research, 248(1–2): 449–470 https://doi.org/10.1007/s10479-016-2196-2
86	P von Geymueller (2009). Static versus dynamic DEA in electricity regulation: The case of US transmission system operators. Central European Journal of Operations Research, 17(4): 397–413 https://doi.org/10.1007/s10100-009-0099-x
87	Y M Wang, K S Chin (2010a). Some alternative models for DEA cross-efficiency evaluation. International Journal of Production Economics, 128(1): 332–338 https://doi.org/10.1016/j.ijpe.2010.07.032
88	Y M Wang, K S Chin (2010b). A neutral DEA model for cross-efficiency evaluation and its extension. Expert Systems with Applications, 37(5): 3666–3675 https://doi.org/10.1016/j.eswa.2009.10.024
89	Y M Wang, K S Chin (2011). The use of OWA operator weights for cross-efficiency aggregation. Omega, 39(5): 493–503 https://doi.org/10.1016/j.omega.2010.10.007
90	Y M Wang, K S Chin, P Jiang (2011a). Weight determination in the cross-efficiency evaluation. Computers & Industrial Engineering, 61(3): 497–502 https://doi.org/10.1016/j.cie.2011.04.004
91	Y M Wang, K S Chin, Y Luo (2011b). Cross-efficiency evaluation based on ideal and anti-ideal decision making units. Expert Systems with Applications, 38(8): 10312–10319 https://doi.org/10.1016/j.eswa.2011.02.116
92	Y M Wang, K S Chin, S Wang (2012). DEA models for minimizing weight disparity in cross-efficiency evaluation. Journal of the Operational Research Society, 63(8): 1079–1088 https://doi.org/10.1057/jors.2011.116
93	Y M Wang, R Greatbanks, J B Yang (2005). Interval efficiency assessment using data envelopment analysis. Fuzzy Sets and Systems, 153(3): 347–370 https://doi.org/10.1016/j.fss.2004.12.011
94	Y M Wang, S Wang (2013). Approaches to determining the relative importance weights for cross-efficiency aggregation in data envelopment analysis. Journal of the Operational Research Society, 64(1): 60–69 https://doi.org/10.1057/jors.2012.43
95	Y H Wong, J E Beasley (1990). Restricting weight flexibility in data envelopment analysis. Journal of the Operational Research Society, 41(9): 829–835 https://doi.org/10.1057/jors.1990.120
96	J Wu, J Chu, J Sun, Q Zhu (2016a). DEA cross-efficiency evaluation based on Pareto improvement. European Journal of Operational Research, 248(2): 571–579 https://doi.org/10.1016/j.ejor.2015.07.042
97	J Wu, J Chu, J Sun, Q Zhu, L Liang (2016b). Extended secondary goal models for weights selection in DEA cross-efficiency evaluation. Computers & Industrial Engineering, 93: 143–151 https://doi.org/10.1016/j.cie.2015.12.019
98	J Wu, J Chu, Q Zhu, P Yin, L Liang (2016c). DEA cross-efficiency evaluation based on satisfaction degree: An application to technology selection. International Journal of Production Research, 54(20): 5990–6007 https://doi.org/10.1080/00207543.2016.1148278
99	J Wu, D Huang, Z Zhou, Q Zhu (2020). The regional green growth and sustainable development of China in the presence of sustainable resources recovered from pollutions. Annals of Operations Research, 290: 27–45 https://doi.org/10.1007/s10479-019-03226-x
100	J Wu, M Li, Q Zhu, Z Zhou, L Liang (2019a). Energy and environmental efficiency measurement of China’s industrial sectors: A DEA model with non-homogeneous inputs and outputs. Energy Economics, 78: 468–480 https://doi.org/10.1016/j.eneco.2018.11.036
101	J Wu, L Liang (2012). A multiple criteria ranking method based on game cross-evaluation approach. Annals of Operations Research, 197(1): 191–200 https://doi.org/10.1007/s10479-010-0817-8
102	J Wu, L Liang, Y Chen (2009a). DEA game cross-efficiency approach to Olympic rankings. Omega, 37(4): 909–918 https://doi.org/10.1016/j.omega.2008.07.001
103	J Wu, L Liang, M Song (2010). Performance based clustering for benchmarking of container ports: An application of DEA and cluster analysis technique. International Journal of Computational Intelligence Systems, 3(6): 709–722 https://doi.org/10.1080/18756891.2010.9727734
104	J Wu, L Liang, F Yang (2009b). Achievement and benchmarking of countries at the Summer Olympics using cross efficiency evaluation method. European Journal of Operational Research, 197(2): 722–730 https://doi.org/10.1016/j.ejor.2008.06.030
105	J Wu, L Liang, F Yang (2009c). Determination of the weights for the ultimate cross efficiency using Shapley value in cooperative game. Expert Systems with Applications, 36(1): 872–876 https://doi.org/10.1016/j.eswa.2007.10.006
106	J Wu, L Liang, F Yang, H Yan (2009d). Bargaining game model in the evaluation of decision making units. Expert Systems with Applications, 36(3): 4357–4362 https://doi.org/10.1016/j.eswa.2008.05.001
107	J Wu, L Liang, Y Zha (2009e). Preference voting and ranking using DEA game cross efficiency model. Journal of the Operations Research Society of Japan, 52(2): 105–111 https://doi.org/10.15807/jorsj.52.105
108	J Wu, L Liang, Y Zha, F Yang (2009f). Determination of cross-efficiency under the principle of rank priority in cross-evaluation. Expert Systems with Applications, 36(3): 4826–4829 https://doi.org/10.1016/j.eswa.2008.05.042
109	J Wu, J Sun, L Liang (2012a). Cross efficiency evaluation method based on weight-balanced data envelopment analysis model. Computers & Industrial Engineering, 63(2): 513–519 https://doi.org/10.1016/j.cie.2012.04.017
110	J Wu, J Sun, L Liang (2012b). DEA cross-efficiency aggregation method based upon Shannon entropy. International Journal of Production Research, 50(23): 6726–6736 https://doi.org/10.1080/00207543.2011.618150
111	J Wu, J Sun, L Liang, Y Zha (2011a). Determination of weights for ultimate cross efficiency using Shannon entropy. Expert Systems with Applications, 38(5): 5162–5165 https://doi.org/10.1016/j.eswa.2010.10.046
112	J Wu, J Sun, M Song, L Liang (2013). A ranking method for DMUs with interval data based on DEA cross-efficiency evaluation and TOPSIS. Journal of Systems Science and Systems Engineering, 22(2): 191–201 https://doi.org/10.1007/s11518-013-5216-7
113	J Wu, J Sun, Y Zha, L Liang (2011b). Ranking approach of cross-efficiency based on improved TOPSIS technique. Journal of Systems Engineering and Electronics, 22(4): 604–608 https://doi.org/10.3969/j.issn.1004-4132.2011.04.008
114	J Wu, P Xia, Q Zhu, J Chu (2019b). Measuring environmental efficiency of thermoelectric power plants: A common equilibrium efficient frontier DEA approach with fixed-sum undesirable output. Annals of Operations Research, 275(2): 731–749 https://doi.org/10.1007/s10479-018-2958-0
115	J Wu, H Yan, J Liu (2009g). Groups in DEA based cross-evaluation: An application to Asian container ports. Maritime Policy & Management, 36(6): 545–558 https://doi.org/10.1080/03088830903346095
116	Y C J Wu, M Goh (2010). Container port efficiency in emerging and more advanced markets. Transportation Research Part E, Logistics and Transportation Review, 46(6): 1030–1042 https://doi.org/10.1016/j.tre.2010.01.002
117	J Xu, Z Li (2012). A review on ecological engineering based engineering management. Omega, 40(3): 368–378 https://doi.org/10.1016/j.omega.2011.06.004
118	F Yang, S Ang, Q Xia, C Yang (2012). Ranking DMUs by using interval DEA cross efficiency matrix with acceptability analysis. European Journal of Operational Research, 223(2): 483–488 https://doi.org/10.1016/j.ejor.2012.07.001
119	G L Yang, J B Yang, W B Liu, X X Li (2013). Cross-efficiency aggregation in DEA models using the evidential-reasoning approach. European Journal of Operational Research, 231(2): 393–404 https://doi.org/10.1016/j.ejor.2013.05.017
120	M M Yu, S C Ting, M C Chen (2010). Evaluating the cross-efficiency of information sharing in supply chains. Expert Systems with Applications, 37(4): 2891–2897 https://doi.org/10.1016/j.eswa.2009.09.048
121	V F Yu, K J Hu (2014). An integrated approach for resource allocation in manufacturing plants. Applied Mathematics and Computation, 245: 416–426 https://doi.org/10.1016/j.amc.2014.07.112
122	M Zerafat Angiz, A Mustafa, M J Kamali (2013). Cross-ranking of decision making units in data envelopment analysis. Applied Mathematical Modelling, 37(1–2): 398–405 https://doi.org/10.1016/j.apm.2012.02.038
123	C Zopounidis, M Doumpos (2002). Multicriteria classification and sorting methods: A literature review. European Journal of Operational Research, 138(2): 229–246 https://doi.org/10.1016/S0377-2217(01)00243-0
124	K H Zoroofchi, R Farzipoor Saen, P B Lari, M Azadi (2018). A combination of range-adjusted measure, cross-efficiency and assurance region for assessing sustainability of suppliers in the presence of undesirable factors. International Journal of Industrial and Systems Engineering, 29(2): 163–176 https://doi.org/10.1504/IJISE.2018.091898
125	K H Zoroufchi, M Azadi, R Farzipoor Saen (2012). Developing a new cross-efficiency model with undesirable outputs for supplier selection. International Journal of Industrial and Systems Engineering, 12(4): 470–484 https://doi.org/10.1504/IJISE.2012.050124

[1]	Xiaoxiao XU, Patrick X. W. ZOU. System dynamics analytical modeling approach for construction project management research: A critical review and future directions[J]. Front. Eng, 2021, 8(1): 17-31.
[2]	Qingxian AN, Xuyang LIU, Shijie DING. Efficiency measurement for mixed two-stage nonhomogeneous network processes with shared extra intermediate resources[J]. Front. Eng, 2020, 7(2): 259-274.
[3]	Ibrahim Yahaya WUNI, Geoffrey Qiping SHEN, Bon-Gang HWANG. Risks of modular integrated construction: A review and future research directions[J]. Front. Eng, 2020, 7(1): 63-80.
[4]	Elodie HOCHSCHEID, Gilles HALIN. Generic and SME-specific factors that influence the BIM adoption process: An overview that highlights gaps in the literature[J]. Front. Eng, 2020, 7(1): 119-130.
[5]	Yang YU, Jiafu TANG. *Review of seru* production**[J]. Front. Eng, 2019, 6(2): 183-192.
[6]	Albert P. C. CHAN, Xiaozhi MA, Wen YI, Xin ZHOU, Feng XIONG. Critical review of studies on building information modeling (BIM) in project management[J]. Front. Eng, 2018, 5(3): 394-406.
[7]	Shengwei WANG, Wenjie GANG. Design and control optimization of energy systems of smart buildings today and in the near future[J]. Front. Eng, 2017, 4(1): 58-66.
[8]	Patrick X.W. ZOU, Morshed ALAM, Van Manh PHUNG, Dipika WAGLE, Rodney STEWART, Edoardo BERTONE, Oz SAHIN, Chris BUNTINE. Achieving energy efficiency in government buildings through mandatory policy and program enforcement[J]. Front. Eng, 2017, 4(1): 92-103.
[9]	Yin-biao Chen,Yi Zhang,Wen Ling. Practice on Ultra-low Emission and Energy Efficient Technologies in Coal-fired Power Plants[J]. Front. Eng, 2016, 3(4): 377-383.
[10]	Elizabeth A. Cudney,William L. Gillis. Quality Function Deployment Implementation in Construction: A Systematic Literature Review[J]. Front. Eng, 2016, 3(3): 224-230.
[11]	Fei Dai,Yoojung Yoon,Hota V. GangaRao. State of Practice of Construction Site Safety in the USA[J]. Front. Eng, 2016, 3(3): 275-282.
[12]	Bao-zhen Zhang,Han-ding Guo,Cai-xia Yang,Lei Wang. Research on Evaluating the Efficiency of the Project Financing of the Energy Service Company[J]. Front. Eng, 2016, 3(3): 252-257.
[13]	Xi-hua Li,Xiao-hong Chen. Trapezoidal Intuitionistic Fuzzy Aggregation Operator Based on Choquet Integral and Its Application to Multi-Criteria Decision-Making Problems[J]. Front. Eng, 2015, 2(3): 266-276.
[14]	Zhi-wen Wang,Jing Tong. An Empirical Study on the Internal Control Efficiency of Listed Engineering Companies[J]. Front. Eng, 2015, 2(2): 159-164.
[15]	Jian-ye Zheng. Consistency Guarantees for Professional Appraisal of Geotechnical Engineering Design under Market Leading and Deciding[J]. Front. Eng, 2015, 2(1): 82-85.

Viewed

Full text

Abstract

Cited

Shared

Discussed