Resource allocation of a parallel system with interaction consideration using a DEA approach: an application to Chinese input-output table. (English) Zbl 1509.90102
Summary: Resource allocation is a popular and important issue in the enterprise management. Recently, data envelopment analysis (DEA) as a non-parametric method for measuring the performance of decision-making units (DMUs) has brought a new flavour to this issue. However, most of resource allocation works by DEA focused on single stage system or consider the internal production process of the system as a ‘black box.’ With the competition and relation among economic entities enhance, the system becomes more and more complex and interactive. To go inside the ‘black box’, in this paper, we propose a new DEA approach to allocate the resource in a bidirectional interactive parallel system. We consider not only the resource allocation of a certain DMU, but also the resource allocation of all DMUs for a centralized decision maker through centralized models. Moreover, the leader-follower relationship between two subunits is studied by a non-cooperative model as a theoretical extension. Finally, the approach is applied to Chinese input-output table in the cooperation scenario. We compare our approach with the traditional approach and find that it can obtain more potential gains.
MSC:
| 90B50 | Management decision making, including multiple objectives |
| 91B32 | Resource and cost allocation (including fair division, apportionment, etc.) |
| 90C08 | Special problems of linear programming (transportation, multi-index, data envelopment analysis, etc.) |
Keywords:
data envelopment analysis; resource allocation; parallel system; interactive unit; potential gainsReferences:
| [1] | Amirteimoori, A.; Tabar, M., Resource allocation and target setting in data envelopment analysis, Expert Syst Appl, 37, 3036-3039 (2010) |
| [2] | An, Q.; Chen, H.; Xiong, B.; Wu, J.; Liang, L., Target intermediate products setting in a two-stage system with fairness concern, Omega (2016) · doi:10.1016/j.omega.2016.12.005 |
| [3] | Basso, A.; Peccati, LA, Optimal resource allocation with minimum activation levels and fixed costs, Euro J Ope Res, 131, 536-549 (2001) · Zbl 1161.91423 |
| [4] | Beasley, JE, Allocating fixed costs and resources via data envelopment analysis, Euro J Ope Res, 147, 198-216 (2003) · Zbl 1011.90529 |
| [5] | Bi, G.; Ding, J.; Luo, Y.; Liang, L., Resource allocation and target setting for parallel production system based on DEA, Appl Math Modell, 35, 4270-4280 (2011) · Zbl 1225.90048 |
| [6] | Bi, G.; Feng, C.; Ding, J.; Khan, MR, Estimating relative efficiency of DMU: Pareto principle and Monte Carlo oriented DEA approach, INFOR, 50, 44-57 (2012) · Zbl 07683610 |
| [7] | Chen, C.; Yan, H., Network DEA model for supply chain performance evaluation, Euro J Ope Res, 213, 147-155 (2011) · Zbl 1237.90038 |
| [8] | Chen, Y.; Zhu, J., Measuring information technology’s indirect impact on firm performance, Info Technol Manage, 5, 9-22 (2004) |
| [9] | Cook, WD; Liang, L.; Zhu, J., Measuring performance of two-stage network structures by DEA: a review and future perspective, Omega, 38, 423-430 (2010) |
| [10] | Cook, WD; Seiford, LM, Data envelopment analysis (DEA)-Thirty years on, Euro J Ope Res, 192, 1-17 (2009) · Zbl 1180.90151 |
| [11] | Ding, J.; Feng, C.; Bi, G.; Liang, L.; Khan, MR, Cone ratio models with shared resources and nontransparent allocation parameters in network DEA, J Product Anal, 44, 1-19 (2014) |
| [12] | Du, J.; Chen, Y.; Huo, J., DEA for non-homogenous parallel networks, Omega, 56, 122-132 (2015) |
| [13] | Fang, L., Centralized resource allocation based on efficiency analysis for step-by-step improvement paths, Omega, 51, 24-28 (2015) |
| [14] | Feng, C.; Chu, F.; Ding, J.; Bi, G.; Liang, L., Carbon emissions abatement (CEA) allocation and compensation schemes based on DEA, Omega, 53, 78-89 (2015) |
| [15] | Fukuyama, H.; Mirdehghan, SM, Identifying the efficiency status in network DEA, Euro J Ope Res, 220, 85-92 (2012) · Zbl 1253.90170 |
| [16] | Golany, B.; Phillips, FY; Rousseau, JJ, Models for improved effectiveness based on DEA efficiency results, IIE Trans, 25, 2-10 (1993) |
| [17] | Hadi-Vencheh, A.; Foroughi, AA; Soleimani-damaneh, M., A DEA model for resource allocation, Econ Mod, 25, 983-993. (2008) |
| [18] | Halkos, GE; Tzeremes, NG; Kourtzidis, SA, A unified classification of two-stage DEA models, Surv Ope Res Mac edcax nage Sci, 19, 1-16 (2014) |
| [19] | Kao, C., Efficiency decomposition in network data envelopment analysis: a relational model, Euro J Ope Res, 192, 949-962 (2009) · Zbl 1157.90494 |
| [20] | Kao, C., Efficiency measurement for parallel production systems, Euro J Ope Res, 196, 1107-1112 (2012) · Zbl 1176.90168 |
| [21] | Kao, C.; Hwang, SN, Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in Taiwan, Eur J Ope Res, 185, 418-429 (2008) · Zbl 1137.91497 |
| [22] | Kao, C.; Hwang, SN, Efficiency measurements for network systems: IT impact of firm performance, Deci Support Syst, 48, 437-446 (2010) |
| [23] | Karabati, S.; Kouvelis, P.; Yu, G., A min-max-sum resource allocation problem and its applications, Oper Res, 49, 913-922 (2001) · Zbl 1163.90550 |
| [24] | Korhonen, P.; Syrjänen, M., Resource allocation based on efficiency analysis, Manage Sci, 50, 1134-1144 (2004) · Zbl 1232.91366 |
| [25] | Lewis, HF; Sexton, TR, Network DEA: Efficiency analysis of organizations with complex internal structure, Comput Ope Res, 31, 1365-1410 (2004) · Zbl 1061.90061 |
| [26] | Liang, N.; Chen, Y.; Zha, Y.; Hu, H., Performance evaluation of Individuals in workgroups with shared outcomes using DEA, INFOR, 53, 78-89 (2015) · Zbl 07683465 |
| [27] | Liu, JS; Lu, WM, Network-based method for ranking of efficient units in two-stage DEA models, J Oper Res Soc, 63, 1153-1164 (2012) |
| [28] | Sahoo, B.; Zhu, J.; Tone, K.; Klemen, B., Decomposing technical efficiency and scale elasticity in two-stage network DEA, Euro J Ope Res, 233, 584-594 (2014) · Zbl 1339.90117 |
| [29] | Salo, A.; Keisler, J.; Morton, A., Portfolio decision analysis: improved methods for resource allocation (2011), New York: Springer Science & Business Media · Zbl 1222.90004 |
| [30] | Tone, K.; Tsutsui, M., Network DEA: a slacks-based measure approach, Euro J Ope Res, 197, 243-252 (2009) · Zbl 1157.90465 |
| [31] | Tone, T.; Tsutsui, M., Slacks-based network DEA: data envelopment analysis, 231-259 (2014), New York: Springer |
| [32] | Wu, J.; An, Q., New approaches for resource allocation via DEA models, Int J Info Technol Deci Making, 11, 103-117 (2012) |
| [33] | Wu, J.; An, Q.; Ali, S.; Liang, L., DEA based resource allocation considering environmental factors, Math Comput Modell, 58, 1128-1137 (2013) |
| [34] | Wu, J.; Xiong, B.; An, Q.; Sun, J.; Wu, H., Total-factor energy efficiency evaluation of Chinese industry by using two-stage DEA model with shared inputs, Annal Ope Res (2015) · doi:10.1007/s10479-015-1938-x |
| [35] | Yan, H.; Wei, Q.; Hao, G., DEA models for resource reallocation and production input/output estimation, Euro J Ope Res, 136, 19-31 (2002) · Zbl 1086.90535 |
| [36] | Yang, Z.; Zhang, Q., Resource allocation based on DEA and modified Shapley value, Appl Math Comput, 263, 280-286 (2015) · Zbl 1410.90126 |
| [37] | Yu, MM; Chen, LH; Hsiao, B., A fixed cost allocation based on the two-stage network data envelopment approach, J Business Res, 69, 1817-1822 (2016) |
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