Sustainability Assessment of Supply Chains by Inverse Network Dynamic Data Envelopment Analysis

Document Type : Article


1 Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj, Iran


This paper focuses on assessing sustainability of supply chains. In this paper, at first, we propose network dynamic range adjusted measure (RAM) model. Then, inverse version of network dynamic RAM model is proposed. Our inverse network dynamic data envelopment analysis (DEA) model changes both inputs and outputs of decision making units (DMUs) so that current efficiency scores of DMUs remain unchanged. We change inputs and outputs without any change in efficiency score of DMU under evaluation while inputs and outputs may have large ranges. A case study shows efficacy of our proposed model.


Main Subjects

1. Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix,
N.W., Smith, C.D., and Zacharia, Z.G. \De ning supply
chain management", Journal of Business logistics,
22(2), pp. 1-25 (2002).
2. Drumwright, M.E. \Socially responsible organizational
buying: Environmental concern as a non-economic
buying criterion", Journal of Marketing, 58(3), pp. 1-
19 (1994).
3. Murphy, P.R., Poist, R.F., and Braunschweig, C.D.
\Management of environmental issues in logistics:
Current status and future potential", Transportation
Journal, 34(1), pp. 48-56 (1994).
4. Carter, C.R. and Rogers, D.S. \A framework of sustainable
supply chain management: moving toward
new theory", International Journal of Physical Distribution
and Logistics Management, 38(5), pp. 360-387
5. Seuring, S.A. \Review of modeling approaches for sustainable
supply chain management", Decision Support
Systems, 54(4), pp. 1513-1520 (2013).
6. Tseng, M.L., Divinagracia, L., and Divinagracia, R.
\Evaluating rm's sustainable production indicators
in uncertainty", Computers & Industrial Engineering,
57(4), pp. 1393-1403 (2009).
7. Tseng, M.L. \Using a hybrid MCDM model to evaluate
rm environmental knowledge management in uncertainty",
Applied Soft Computing, 11(1), pp. 1340-1352
8. Tseng, M.L. and Chiu, A.S. \Evaluating rm's green
supply chain management in linguistic preferences",
Journal of Cleaner Production, 40, pp. 22-31 (2013).
9. Charnes, A., Cooper, W.W., and Rhodes, E. \Measuring
the eciency of decision making units", European
Journal of Operational Research, 2(6), pp. 429-444
M. Kalantary et al./Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 3723{3743 3741
10. Kumar, A., Jain, V., and Kumar, S. \Comprehensive
environment friendly approach for supplier selection",
Omega, 42(1), pp. 109-123 (2014).
11. Lewis, H.F. and Sexton, T.R. \Network DEA: E-
ciency analysis of organizations with complex internal
structure", Computers & Operations Research, 31(9),
pp. 1365-1410 (2004).
12. Fare, R. and Grosskopf, S. \Intertemporal production
frontiers: with dynamic DEA", Journal of the Operational
Research Society, 48(6), pp. 656-656 (1997).
13. Tone, K. and Tsutsui, M. \Dynamic DEA with network
structure: A slacks-based measure approach",
Omega, 42(1), pp. 124-131 (2014).
14. Bowen, F.E., Cousins, P.D., Lamming, R.C., and
Faruk, A.C. \The role of supply management capabilities
in green supply", Production and Operations
Management, 10(2), pp. 174-189 (2001).
15. Pesonen, H.L. \Environmental management of value
chains", Greener Management International, 33, pp.
45-58 (2001).
16. Seuring, S.A. \Green supply chain costing: joint cost
management in the polyester linings supply chain",
Greener Management International, pp. 71-80, Spring
17. Bose, I. and Pal, R. \Do green supply chain management
initiatives impact stock prices of rms?",
Decision Support Systems, 52(3), pp. 624-634 (2012).
18. Srivastava, S.K. \Green supply-chain management: A
state-of-the-art literature review", International Journal
of Management Review, 9(1), pp. 53-80 (2007).
19. Liu, Z.L., Anderson, T.D., and Cruz, J.M. \Consumer
environmental awareness and competition in two-stage
supply chains", European Journal of Operational Research,
218(3), pp. 602-613 (2012).
20. Zhang, L., Wang. J., and You. J. \Consumer environmental
awareness and channel coordination with two
substitutable products", European Journal of Operational
Research, 241(1), pp. 63-73 (2015).
21. Ghosh, D. and Shah, J. \Supply chain analysis under
green sensitive consumer demand and cost sharing
contract", International Journal of Production Economics,
164, pp. 319-329 (2015).
22. Xie, G. \Modeling decision processes of a green supply
chain with regulation on energy saving level", Computers
& Operations Research, 54, pp. 266-273 (2015).
23. Genovese, A., Acquaye, A.A., Figueroa, A., and Koh,
S.L. \Sustainable supply chain management and the
transition towards a circular economy: Evidence and
some applications", Omega, 66, pp. 344-357 (2017).
24. Su, C.M., Horng, D.J., Tseng, M.L., Chiu, A.S., Wu,
K.J., and Chen, H.P. \Improving sustainable supply
chain management using a novel hierarchical grey-
DEMATEL approach", Journal of Cleaner Production,
134, pp. 469-481(2016).
25. Dubey, R., Gunasekaran, A., Papadopoulos, T.,
Childe, S.J., Shibin, K.T., and Wamba, S.F. \Sustainable
supply chain management: framework and further
research directions", Journal of Cleaner Production,
142, pp. 1119-1130 (2017).
26. Kumar, D., Rahman, Z., and Chan, F.T. \A fuzzy
AHP and fuzzy multi-objective linear programming
model for order allocation in a sustainable supply
chain: A case study", International Journal of Computer
Integrated Manufacturing, 30(6), pp. 535-551
27. Azadi, M., Jafarian, M., Farzipoor Saen, R., and
Mirhedayatian, S.M. \A new fuzzy DEA model for
evaluation of eciency and e ectiveness of suppliers
in sustainable supply chain management context",
Computers & Operations Research, 54, pp. 274-285
28. Li, Y. and Cui, Q. \Carbon neutral growth from 2020
strategy and airline environmental ineciency: A network
range adjusted environmental data envelopment
analysis", Applied Energy, 199, pp. 13-24 (2017).
29. Awasthi, A., Chauhan, S.S., and Goyal, S.K. \A fuzzy
multicriteria approach for evaluating environmental
performance of suppliers", International Journal of
Production Economics, 126(2), pp. 370-378 (2010).
30. Buyukozkan, G. and C ifci, G. \A novel fuzzy multicriteria
decision framework for sustainable supplier
selection with incomplete information", Computers in
Industry, 62(2), pp. 164-174 (2011).
31. Erol, I., Sencer, S., and Sari, R. \A new fuzzy
multi-criteria framework for measuring sustainability
performance of a supply chain", Ecological Economics,
70(6), pp. 1088-1100 (2011).
32. Govindan, K., Khodaverdi, R., and Jafarian, A. \A
fuzzy multi criteria approach for measuring sustainability
performance of a supplier based on triple
bottom line approach", Journal of Cleaner Production,
47, pp. 345-354 (2013).
33. Kuo, R.J., Wang, Y.C., and Tien, F.C. \Integration of
arti cial neural network and MADA methods for green
supplier selection", Journal of Cleaner Production,
18(12), pp. 1161-1170 (2010).
34. Punniyamoorthy, M., Mathiyalagan, P., and
Parthiban, P. \A strategic model using structural
equation modeling and fuzzy logic in supplier
selection", Expert Systems with Applications, 38(1),
pp. 458-474 (2011).
35. Amindoust, A., Ahmed, S., Sagha nia, A. and
Bahreininejad, A. \Sustainable supplier selection: A
ranking model based on fuzzy inference system", Applied
Soft Computing, 12(6), pp. 1668-1677 (2012).
36. Yeh, W.C. and Chuang, M.C. \Using multi-objective
genetic algorithm for partner selection in green supply
chain problems", Expert Systems with Applications,
38(4), pp. 4244-4253 (2011).
3742 M. Kalantary et al./Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 3723{3743
37. Wei, Q., Zhang, J., and Zhang, X. \Theory
and methodology. An inverse DEA model for inputs/
outputs estimate", European Journal of Operational
Research, 121(1), pp. 151-163 (2000).
38. Yan, H., Wei, Q., and Hao, G. \DEA models for
resource reallocation and production input/output estimation",
European Journal of Operational Research,
136(1), pp. 19-31 (2002).
39. Jahanshahloo, G.R., Lot , F.H., Shoja, N., Tohidi, G.,
and Razavyan, S. \The outputs estimation of a DMU
according to improvement of its eciency", Applied
Mathematics and Computation, 147(2), pp. 409-413
40. Jahanshahloo, G.R., Lot , F.H., Shoja, N., Tohidi, G.,
and Razavyan, S. \Input estimation and identi cation
of extra inputs in inverse DEA models", Applied
Mathematics and Computation, 156(2), pp. 427-437
41. Jahanshahloo, G.R., Lot , F.H., Shoja, N., Tohidi, G.,
and Razavyan, S. \Sensitivity of eciency classi cations
in the inverse DEA models", Applied Mathematics
and Computation, 169(2), pp. 905-916 (2005).
42. Jahanshahloo, G.R., Soleimani-Damaneh, M., and
Ghobadi, S. \Inverse DEA under inter-temporal dependence
using multiple-objective programming", European
Journal of Operational Research, 240(2), pp.
447-456 (2015).
43. Lertworasirikul, S., Charnsethikul, P., and Fang, S.C.
\Inverse data envelopment analysis model to preserve
relative eciency values: The case of variable returns
to scale", Computers & Industrial Engineering, 61(4),
pp. 1017-1023 (2011).
44. Banker, R.D., Charnes, A., and Cooper, W.W. \Some
models for estimating technical and scale ineciencies
in data envelopment analysis", Management Science,
30(9), pp. 1078-1092 (1984).
45. Amin, G.R., Emrouznejad, A., and Gattou , S. \Minor
and major consolidations in inverse DEA: Definition
and determination", Computers & Industrial
Engineering, 103, pp. 193-200 (2017).
46. Amin, G.R., Emrouznejad, A., and Gattou , S. \Modelling
generalized rms' restructuring using inverse
DEA", Journal of Productivity Analysis, 48(1), pp. 51-
61 (2017).
47. Eyni, M., Tohidi, G., and Mehrabeian, S. \Applying
inverse DEA and cone constraint to sensitivity analysis
of DMUs with undesirable inputs and outputs",
Journal of the Operational Research Society, 68(1), pp.
34-40 (2016).
48. Lovell, C.K. and Pastor, J.T. \Units invariant and
translation invariant DEA models", Operations Research
Letters, 18(3), pp. 147-151 (1995).
49. Pastor, J.T. and Ruiz, J.L. \Variables with negative
values in DEA", In Modeling Data Irregularities and
Structural Complexities in Data Envelopment Analysis,
Springer, USA, pp. 63-84 (2007).
50. Pastor, J.T. \Translation invariance in data envelopment
analysis: A generalization", Annals of Operations
Research, 66(2), pp. 93-102 (1996).
51. Cooper, W.W., Seiford, L., and Tone, K., Data envelopment
Analysis: A Comprehensive Text with Models,
Applications, References and DEA-Solver Software,
Springer, p. 490 (2007).
52. Cooper, W.W., Park, K.S., and Pastor, J.T. \RAM:
A range adjusted measure of ineciency for use with
additive models, and relations to other models and
measures in DEA", Journal of Productivity Analysis,
11(1), pp. 5-42 (1999).
53. Tone, K. and Tsutsui, M. \Network DEA: a slacksbased
measure approach", European Journal of Operational
Research, 197(1), pp. 243-252 (2009).
54. Fare, R. and Grosskopf, S. \Productivity and intermediate
products: A frontier approach", Economics
Letters, 50(1), pp. 65-70 (1996).
55. Fare, R. and Grosskopf, S. \Network DEA", Socio-
Economic Planning Sciences, 34(1), pp. 35-49 (2000).
56. Sexton, T.R. and Lewis, H.F. \................................