Scale and cost efficiency analysis of networks of processes

Research highlights? Network DEA considers subprocesses and intermediate flows among them. ? Simple technical and cost efficiency network DEA models are presented. ? Each subprocess can have its own Returns to Scale assumption. ? Overall Returns to Scale and scale, cost and allocative efficiency can be computed. ? Proposed models are illustrated with a problem from the literature In this paper a simple way of computing technical, scale, cost and allocative efficiency scores for homogeneous networks of processes is presented. The system Production Possibility Set (PPS) is formed through the composition of the PPS of the individual processes, which, in turn, are modelled in the conventional, axiomatic way using observed data. Firstly, the overall system scale and technical efficiency are computed using the relational network DEA approach. Local Returns To Scale (RTS) can also be estimated with these models. Secondly, assuming the prices of exogenous inputs are known, a minimum cost network DEA model is solved, from which cost and allocative efficiencies are derived. The proposed approach is illustrated with a two-stage problem from the literature, showing the usefulness of a more detailed problem assessment both in terms of technical and scale efficiency and RTS and in terms of cost and allocative efficiency.

[1]  Joe Zhu,et al.  DEA models for supply chain efficiency evaluation , 2006, Ann. Oper. Res..

[2]  Thomas R. Sexton,et al.  Organizational capability, efficiency, and effectiveness in Major League Baseball: 1901-2002 , 2009, Eur. J. Oper. Res..

[3]  Desheng Dash Wu,et al.  Supply chain DEA: production possibility set and performance evaluation model , 2011, Ann. Oper. Res..

[4]  Ming-Miin Yu,et al.  Measuring the efficiency and return to scale status of multi-mode bus transit – evidence from Taiwan's bus system , 2008 .

[5]  Joe Zhu,et al.  DEA Models For Supply Chain or Multi-Stage Structure , 2007 .

[6]  Magnus Tambour,et al.  Productivity and customer satisfaction in Swedish pharmacies: A DEA network model , 1999, Eur. J. Oper. Res..

[7]  Shiang-Tai Liu,et al.  Efficiency measures of PCB manufacturing firms using relational two-stage data envelopment analysis , 2009, Expert Syst. Appl..

[8]  Joe Zhu,et al.  Additive efficiency decomposition in two-stage DEA , 2009, Eur. J. Oper. Res..

[9]  Herbert F. Lewis,et al.  Two-Stage DEA: An Application to Major League Baseball , 2003 .

[10]  Walter Ukovich,et al.  A classification of DEA models when the internal structure of the Decision Making Units is considered , 2010, Ann. Oper. Res..

[11]  Chiang Kao,et al.  Efficiency measurement for network systems: IT impact on firm performance , 2010, Decis. Support Syst..

[12]  R. Banker Estimating most productive scale size using data envelopment analysis , 1984 .

[13]  Ming-Miin Yu,et al.  Efficiency and effectiveness in railway performance using a multi-activity network DEA model , 2008 .

[14]  Joe Zhu,et al.  DEA models for two‐stage processes: Game approach and efficiency decomposition , 2008 .

[15]  Ming-Miin Yu,et al.  Assessing the technical efficiency, service effectiveness, and technical effectiveness of the world's railways through NDEA analysis , 2008 .

[16]  Ming-Miin Yu,et al.  Efficiency and effectiveness of service business: evidence from international tourist hotels in Taiwan. , 2009 .

[17]  R. Färe,et al.  Intertemporal Production Frontiers: With Dynamic DEA , 1996 .

[18]  Thomas R. Sexton,et al.  Data Envelopment Analysis with Reverse Inputs and Outputs , 2004 .

[19]  Chiang Kao,et al.  Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan , 2008, Eur. J. Oper. Res..

[20]  Thomas R. Sexton,et al.  Network DEA: efficiency analysis of organizations with complex internal structure , 2004, Comput. Oper. Res..

[21]  Joe Zhu,et al.  Data Envelopment Analysis , 2007 .

[22]  Chiang Kao,et al.  Efficiency measurement for parallel production systems , 2009, Eur. J. Oper. Res..

[23]  Kaoru Tone,et al.  Network DEA: A slacks-based measure approach , 2009, Eur. J. Oper. Res..

[24]  José Luis Zofío,et al.  Network DEA efficiency in input-output models: With an application to OECD countries , 2007, Eur. J. Oper. Res..

[25]  Necmi K. Avkiran,et al.  Opening the black box of efficiency analysis: An illustration with UAE banks , 2009 .

[26]  Chien-Ming Chen,et al.  Production , Manufacturing and Logistics A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks , 2008 .

[27]  Chiang Kao,et al.  Efficiency decomposition in network data envelopment analysis: A relational model , 2009, Eur. J. Oper. Res..

[28]  R. Färe,et al.  PRODUCTIVITY AND INTERMEDIATE PRODUCTS: A FRONTIER APPROACH , 1995 .