Supply chain DEA: production possibility set and performance evaluation model

Abstract

Performance evaluation is of great importance for effective supply chain management. The foundation of efficiency evaluation is to faithfully identify the corresponding production possibility set. Although a lot of researches have been done on supply chain DEA models, the exact definition for supply chain production possibility set is still in absence. This paper defines two types of supply chain production possibility sets, which are proved to be equivalent to each other. Based upon the production possibility set, a supply chain CRS DEA model is advanced to appraise the overall technical efficiency of supply chains. The major advantage of the model lies on the fact that it can help to find out the most efficient production abilities in supply chains, by replacing or improving inefficient subsystems (supply chain members). The proposed model also directly identifies the benchmarking units for inefficient supply chains to improve their performance. A real case validates the reasonableness and acceptability of this approach.

Measuring the environmental sustainability performance of global supply chains: A multi-regional input-output analysis for carbon, sulphur oxide and water footprints

“…Lehtinen and Ahola (2010) and Hassini (2012) have all reiterated that there exist incompatibilities between the known principles of performance measures and supply chains. Indeed, despite the fact that sustainability performance measurements remain fundamental in the shift of the operations function towards sustainable supply chains, recently reported that existing methods and possible approaches to measure and manage sustainability performance of supply chains such as at the industry level are lacking although performance measurement is of great importance for effective supply chain management (Yang et al 2011). This can be attributed to many factors; amongst them the existence of multiple and sometimes conflicting measures that characterize the performance of the supply chain (Liang et al 2006), the focus on reporting green supply chain management initiatives implementation rather than performance outcomes (Zhu et al 2008), the fact that supply chains are dynamic in nature (Gunasekaran et al 2004) and that environmental problems are multi-faceted (Hubbard 2009) and the result of inconsistent methodologies as expounded upon by Font and Harris (2004).…”

An Evaluation Method of Supply Chain Efficiency Considering Customers' Satisfaction

“…It also aims to provide a network DEA framework for the evaluation system. The framework is based on the supply chain model of Chen and Yan [25] and separating members concept model of Yan [26].…”

“…al. [26] introduced the supply chain DEA model in which every members in a chain can be replaced by introducing Figure 1: DEA models for supply chain separate production possibility set as in shown Fig. 1(d).…”

An environmental uncertainty-based diagnostic reference tool for evaluating the performance of supply chain value streams

“…Arguably, one of the main benefits of using DEA over other PM tools that are used for informing managerial action (for example regression analysis or cost-benefit ratio analysis) is its ability to provide benchmarking DMUs and a peer reference group for inefficient DMUs (Yang et al 2011). The technique enables the analyst to construct an overall performance index from multiple input and output variables and identify the most efficient frontier.…”

“…CCR remains one of the most frequently used DEA models in practical applications (Green and Cooks 2004). It is recognised as one of the most influential models by researchers (Seiford 1996), and has been successfully applied in many operations and supply chain performance studies (for example, Azadeh et al 2007;Li and Dai 2009;Azadi and Saen 2011;Yang et al 2011). Furthermore, it is appropriate in applications, such as the present application, where there are no economies (or diseconomies) of scale present due to significant variations in the size of DMUs.…”