Efficiency measurement for mixed two-stage nonhomogeneous network processes with shared extra intermediate resources
Qingxian AN, Xuyang LIU, Shijie DING
Efficiency measurement for mixed two-stage nonhomogeneous network processes with shared extra intermediate resources
Unreasonable allocation of shared resources reduces the system efficiency and is a considerable operational risk. Sub-processes with insufficient portion of shared resources could not help accomplish complicated tasks, and overstaffing and idle resources will occur in the sub-processes assigned with redundant shared resources. This unfair portion distribution may cause internal contradictions among sub-processes and even lead to the collapsing of the entire system. This study proposes a data-driven, mixed two-stage network data envelopment analysis model. This method aims to reasonably define the allocation portion of shared extra intermediate resources among several nonhomogeneous subsystems and measure the overall system performance. A data set of 58 international hotels is used to test the features of the proposed model.
shared resource allocation / mixed two-stage system / data envelopment analysis / efficiency
[1] |
Amin G R, Toloo M (2004). A polynomial-time algorithm for finding e in DEA models. Computers & Operations Research, 31(5): 803–805
CrossRef
Google scholar
|
[2] |
Amirteimoori A (2013). A DEA two-stage decision processes with shared resources. Central European Journal of Operations Research, 21(1): 141–151
CrossRef
Google scholar
|
[3] |
An Q, Meng F, Xiong B, Wang Z, Chen X (2018). Assessing the relative efficiency of Chinese high-tech industries: A dynamic network data envelopment analysis approach. Annals of Operations Research: 1–23
CrossRef
Google scholar
|
[4] |
An Q, Tao X, Dai B, Li J (2019). Modified distance friction minimization model with undesirable output: An application to the environmental efficiency of China’s regional industry. Computational Economics: 1–25
CrossRef
Google scholar
|
[5] |
Beasley J E (1995). Determining teaching and research efficiencies. Journal of the Operational Research Society, 46(4): 441–452
CrossRef
Google scholar
|
[6] |
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
CrossRef
Google scholar
|
[7] |
Brunaud B, Ochoa M P, Grossmann I E (2018). Product decomposition strategy for optimization of supply chain planning. Frontiers of Engineering Management, 5(4): 466–478
CrossRef
Google scholar
|
[8] |
Charnes A, Cooper W W (1962). Programming with linear fractional functionals. Naval Research Logistics Quarterly, 9(3–4): 181–186
CrossRef
Google scholar
|
[9] |
Charnes A, Cooper W W, Rhodes E (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6): 429–444
CrossRef
Google scholar
|
[10] |
Chen Y, Cook W D, Zhu J (2014). Additive efficiency decomposition in network DEA. In: Cook W, Zhu J, eds. Data Envelopment Analysis. International Series in Operations Research and Management Science.Boston, MA: Springer, 208: 91–118
|
[11] |
Chen Y, Du J, Sherman H D, Zhu J (2010). DEA model with shared resources and efficiency decomposition. European Journal of Operational Research, 207(1): 339–349
CrossRef
Google scholar
|
[12] |
Chen Y, Liang L, Yang F, Zhu J (2006). Evaluation of information technology investment: A data envelopment analysis approach. Computers & Operations Research, 33(5): 1368–1379
CrossRef
Google scholar
|
[13] |
Cook W D, Hababou M (2001). Sales performance measurement in bank branches. Omega, 29(4): 299–307
CrossRef
Google scholar
|
[14] |
Cook W D, Harrison J, Imanirad R, Rouse P, Zhu J (2013). Data envelopment analysis with nonhomogeneous DMUs. Operations Research, 61(3): 666–676
CrossRef
Google scholar
|
[15] |
Cook W D, Harrison J, Rouse P, Zhu J (2012). Relative efficiency measurement: The problem of a missing output in a subset of decision making units. European Journal of Operational Research, 220(1): 79–84
CrossRef
Google scholar
|
[16] |
Cook W D, Liang L, Zhu J (2010). Measuring performance of two-stage network structures by DEA: A review and future perspective. Omega, 38(6): 423–430
CrossRef
Google scholar
|
[17] |
Cook W D, 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
CrossRef
Google scholar
|
[18] |
Du J, Chen Y, Huo J (2015). DEA for non-homogenous parallel networks. Omega, 56: 122–132
CrossRef
Google scholar
|
[19] |
Halkos G E, Tzeremes N G, Kourtzidis S A (2014). A unified classification of two-stage DEA models. Surveys in Operations Research and Management Science, 19(1): 1–16
CrossRef
Google scholar
|
[20] |
Huang C W, Ho F N, Chiu Y H (2014). Measurement of tourist hotels’ productive efficiency, occupancy, and catering service effectiveness using a modified two-stage DEA model in Taiwan. Omega, 48: 49–59
CrossRef
Google scholar
|
[21] |
Imanirad R, Cook W D, Aviles-Sacoto S V, Zhu J (2015). Partial input to output impacts in DEA: The case of DMU-specific impacts. European Journal of Operational Research, 244(3): 837–844
CrossRef
Google scholar
|
[22] |
Imanirad R, Cook W D, Zhu J (2013). Partial input to output impacts in DEA: Production considerations and resource sharing among business subunits. Naval Research Logistics, 60(3): 190–207
CrossRef
Google scholar
|
[23] |
Jahanshahloo G R, Amirteimoori A R, Kordrostami S (2004a). Measuring the multi-component efficiency with shared inputs and outputs in data envelopment analysis. Applied Mathematics and Computation, 155(1): 283–293
CrossRef
Google scholar
|
[24] |
Jahanshahloo G R, Amirteimoori A R, Kordrostami S (2004b). Multi-component performance, progress and regress measurement and shared inputs and outputs in DEA for panel data: An application in commercial bank branches. Applied Mathematics and Computation, 151(1): 1–16
CrossRef
Google scholar
|
[25] |
Kao C (2012). Efficiency decomposition for parallel production systems. Journal of the Operational Research Society, 63(1): 64–71
CrossRef
Google scholar
|
[26] |
Kao C (2014). Network data envelopment analysis: A review. European Journal of Operational Research, 239(1): 1–16
CrossRef
Google scholar
|
[27] |
Kao C, Hwang S N (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research, 185(1): 418–429
CrossRef
Google scholar
|
[28] |
Kao C, Hwang S N (2010). Efficiency measurement for network systems: IT impact on firm performance. Decision Support Systems, 48(3): 437–446
CrossRef
Google scholar
|
[29] |
Li W, Liang L, Cook W D, Zhu J (2016). DEA models for non-homogeneous DMUs with different input configurations. European Journal of Operational Research, 254(3): 946–956
CrossRef
Google scholar
|
[30] |
Li W H, Liang L, Avilés-Sacoto S V, Imanirad R, Cook W D, Zhu J (2017). Modeling efficiency in the presence of multiple partial input to output processes. Annals of Operations Research, 250(1): 235–248
CrossRef
Google scholar
|
[31] |
Li Y, Chen Y, Liang L, Xie J (2014). DEA models for extended two-stage network structures. In: Cook W, Zhu J, eds. Data Envelopment Analysis. International Series in Operations Research and Management Science. Boston, MA: Springer, 208: 261–284
CrossRef
Google scholar
|
[32] |
Liang L, Cook W D, Zhu J (2008). DEA models for two-stage processes: Game approach and efficiency decomposition. Naval Research Logistics, 55(7): 643–653
CrossRef
Google scholar
|
[33] |
Liang L, Yang F, Cook W D, Zhu J (2006). DEA models for supply chain efficiency evaluation. Annals of Operations Research, 145(1): 35–49
CrossRef
Google scholar
|
[34] |
Rogge N, De Jaeger S (2012). Evaluating the efficiency of municipalities in collecting and processing municipal solid waste: A shared input DEA-model. Waste Management, 32(10): 1968–1978
CrossRef
Pubmed
Google scholar
|
[35] |
Seiford L M, Zhu J (1999). Profitability and marketability of the top 55 US commercial banks. Management Science, 45(9): 1270–1288
CrossRef
Google scholar
|
[36] |
Song M, Zhu S, Wang J, Zhao J (2020). Share green growth: Regional evaluation of green output performance in China. International Journal of Production Economics, 219: 152–163
CrossRef
Google scholar
|
[37] |
Wang Y M, Chin K S (2010). Some alternative DEA models for two-stage process. Expert Systems with Applications, 37(12): 8799–8808
CrossRef
Google scholar
|
[38] |
Wu J, Zhu Q, Chu J, Liu H, Liang L (2016a). Measuring energy and environmental efficiency of transportation systems in China based on a parallel DEA approach. Transportation Research Part D: Transport and Environment, 48: 460–472
CrossRef
Google scholar
|
[39] |
Wu J, Zhu Q, Ji X, Chu J, Liang L (2016b). Two-stage network processes with shared resources and resources recovered from undesirable outputs. European Journal of Operational Research, 251(1): 182–197
CrossRef
Google scholar
|
[40] |
Yang X, Heidug W, Cooke D (2019). An adaptive policy-based framework for China’s Carbon Capture and Storage development. Frontiers of Engineering Management, 6(1): 78–86
CrossRef
Google scholar
|
[41] |
Yin P, Chu J, Wu J, Ding J, Yang M, Wang Y (2019). A DEA-based two-stage network approach for hotel performance analysis: An internal cooperation perspective. Omega (In Press)
CrossRef
Google scholar
|
[42] |
Yu M M, Fan C K (2009). Measuring the performance of multimode bus transit: A mixed structure network DEA model. Transportation Research Part E: Logistics and Transportation Review, 45(3): 501–515
CrossRef
Google scholar
|
[43] |
Yu M M, Lin E T J (2008). Efficiency and effectiveness in railway performance using a multi-activity network DEA model. Omega, 36(6): 1005–1017
CrossRef
Google scholar
|
[44] |
Zha Y, Liang L (2010). Two-stage cooperation model with input freely distributed among the stages. European Journal of Operational Research, 205(2): 332–338
CrossRef
Google scholar
|
[45] |
Zhen L, Zhuge D, Murong L, Yan R, Wang S (2019). Operation management of green ports and shipping networks: Overview and research opportunities. Frontiers of Engineering Management, 6(2): 152–162
CrossRef
Google scholar
|
[46] |
Zhu W, Yu Y, Sun P (2018). Data envelopment analysis cross-like efficiency model for non-homogeneous decision-making units: The case of United States companies’ low-carbon investment to attain corporate sustainability. European Journal of Operational Research, 269(1): 99–110
CrossRef
Google scholar
|
/
〈 | 〉 |