Enterprise resources planning (ERP) systems attract many attentions from industry sector because of their ability to facilitate and integrate the enterprise operations. However, many expenses accompany the implementation of these systems and consecutive changes which doing a precise and comprehensive performance evaluation a necessary part of this process. These evaluations should consider operational and technical aspects of ERP systems to reflect the effectiveness of them toward the organization's requirements. In this paper, a Two-stage data envelopment analysis model (DEA) is presented in order to evaluate the efficiency of ERP systems in such a way that the operational and the technical aspect are evaluated in the first stage and the second stage of DEM model, respectively. Based on the obtained results the ERP systems’ functionality and customizability to the client processes are the Two key features that need to be considered by the providers. Furthermore, the findings of parameter sensitivity analysis of the proposed model provide deep and managerial insights into the further usability improvements of ERP systems.

This study proposes a framework for supplier evaluation, selection, and assignment that incorporates a Two-stage game-theoretic approach method. The objective is to provide manufacturers with insights to choose suitable suppliers for di, erent manufacturing processes. The framework applies to the decision logic of multiple manufacturing processes. In the , rst stage, a non-cooperative game model is utilized for supplier evaluation and selection. The interactive behaviors between a manufacturer and some supplier candidates are modeled and analyzed so that the Supplier Evaluation Value (SEV) can be obtained using the Nash equilibrium. In the second stage, the SEVs become the input for the Shepley values calculation of each supplier under a cooperative game model. The Shapley values are utilized to create a set of limited supplier allocation. This paper provides managerial insights to verify the viability of the proposed approach for supplier selection and allocation. Thus, it enables Supply Chain Management (SCM) manager to optimize supplier evaluation, selection, and order assignment.

Regular neTwork data envelopment analysis (NDEA) models for calculating the efficiency of decisionmaking units (DMUs) with Two-stage construction requires the data set to be deterministic. In the real world, however, there are many observations that have stochastic behavior. This paper proposes a neTwork DEA with Two-stage structures models by the attention to stochastic data. The stochastic Two-stage neTwork DEA models are formulated based on the P-models of chance constrained programming and leader-follower concepts. On the basis of probability distribution properties and by the assumption of stochastic single factor components of data set, the probabilistic form of models is transformed to the equivalent deterministic linear programming model. In addition, the relationship between each stage as leader or follower is discussed. A real case on 16 commercial banks in China has been clari ed to con rm the applicability of the proposed approaches under different levels.

The natural disasters such as floods and storms have always led to widespread damages and serious disruptions in power distribution neTworks. After presenting a new index to quantitatively calculate the resilience of the power distribution neTwork, this paper proposes a Two-stage approach to enhance distribution neTwork resilience against natural disasters in the presence of distributed generation (DG) units including solar cells and conventional gas-fired power sources. The first stage includes determining the boundaries of isolated zones and the optimal capacity of the DG units in each zone to improve the resilience by considering budget constraints. The second stage includes determining the optimal location of DG units in each zone to optimize the distribution neTwork losses. A genetic algorithm (GA) based optimization method is developed to solve the proposed problem. The performance of the proposed approach is assessed and illustrated by numerical studies on a practical power distribution system from Iran.