Discretionary models of data envelopment analysis (DEA) assume that all inputs and outputs are discretionary, i.e., controlled by the management of each decision making unit (DMU) and varied at its discretion. In any realistic situation, however, there may exist exogenously fixed or non-discretionary inputs or outputs that are beyond the control of a DMU s , management. There are some models that incorporate non-discretionary inputs into DEA models. This paper reviews these approaches, providing a discussion of strengths and weaknesses and highlighting potential limitations. Moreover, a new method is developed that overcomes existing weaknesses.

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Purpose The main objective of this study is to present a conceptual model of sustainable product service supply chain (SPSSC) performance assessment in the oil and gas industry. Design/methodology/approach Based on an in-depth study of the previous literature, the indicators related to PSSC performance assessment were determined. Then, exploratory factor analysis and confirmatory factor analysis were applied to identify and confirm the sub-criteria and criteria pertaining to the proposed model. Findings The obtained results identify ten criteria related to the proposed model as follows: “Environmental performance”, “Customer performance”, “financial performance”, “Information technology Performance”, “Social Performance”, “Risk performance”, “Logistics performance”, “Operational performance”, “Organizational performance” and “performance of innovation and growth”. Research limitations/implications As the present research was conducted in the Iranian context, caution should be taken regarding the generalizability of the obtained results. Originality/value Based on a set of the identified criteria, this study proposes a conceptual model of the PSSC performance assessment in the oil and gas industry which hopefully could be useful for other organizations in this industry and other organizations in other parts of the world.

Oil and gas industries are among the industries involved in the international service supply chain, which include domestic and international transportation, import and export, and technology information. By creating utility and satisfaction from environmental perspective throughout the service supply chain, the supply chain managers of leading companies have recently tried to use green logistics and improve environmental performance in the entire of their service supply chain as a valuable resource for sustainable competitive advantage. Thus, the main reasons for investment in creating a sustainable green service supply chain includes management of unwanted environmental, social, and economic risks and creating sustainable services by increasing revenue and enhancing cooperation. Given the purpose of this article which is to provide a framework to assess sustainable green SSCM dimensions. Organizational factors, environmental factors were obtained. In this study, structural equation modelling (SEM) was used to test the hypotheses.

Considering the importance and extensive range of decision-making, scientists from various fields have had many discussions on this issue. Various models have been proposed to facilitate decision-making and have had much utilization. In many site selection problems, multiple objectives must be obtained, simultaneously. This study uses a mathematical model to select a suitable location for the refinery in the multi attribute environment. The proposed model uses a large amount of qualitative and quantitative information in the frame of multi objective functions for the first time in the refinery site selection and is flexible enough to use decision makers' opinions in order to achieve goals. For this reason, after a brief overview of the selected area characteristics, using analytic hierarchy process (AHP) for weighting the criteria, a mathematical operation research model is proposed to determine the best alternatives.