In the contemporaneous sustainable manufacturing scenario and fourth industrial revolutions, requirements of most cutting-edge CNC machine tools are indispensable for finished products with high accuracy, precision and green complaints in particular. Such requirements have impelled the advanced manufacturing industries to evaluate and choose the proper CNC machine tools for best customized performances. In the face of proper and effective green evaluation, this paper incorporates a heterogeneous expert group based decision framework considering multiple significant technical and green criteria by assessing relative importance of diverse conflicting criteria having substantial contribution in performance analysis of CNC machine tools. As a demonstration of the suggested mathematical model, three real life decision making problems related to 3 axes-CNC machine tools based on the collected quantitative and linguistic data from catalogues, manufacturer’s portals, questionnaires, customer reviews etc. are established. The calculated findings are close to those obtained by previous researchers as well as are verified by well-established techniques. Besides, sensitivity and statistical analysis are performed to examine the robustness and stability of the ranking orders of the alternatives as well as to investigate the efficacy and consistency of the proposed method. Hence thus proposed formulated MCDM approach proves to be a highly effective and reliable decision making tool for choosing the most suitable CNC machine tools.

Knowledge management strategies are considered as the foundation of learning organizations. One of the problems of Iranian organizations is the assessment of knowledge management processes. The purpose of the present study is to present an applied organized model for the assessment of knowledge management performance in six dimensions, i.e., the financial dimension, stakeholders, local processes, growth and learning, employee satisfaction, and environment and community; identifying and investigating the correlation among the criteria; mapping network relations; weighing the indices using DEMATEL Technique; ranking assessment dimensions of knowledge management using ORESTE Technique; drawing strategic map; and designing Balanced Scorecard for improved performance of knowledge management. The population and sample of the study included 25 petrochemical Tehran managers and senior experts in information technology section. The results of this study provides a comprehensive view for the decision makers of Iran Petrochemical Industries for an improved performance in knowledge management.

Performance measurement is one of the primary tasks in every organization and it helps organization setup appropriate targets for future. There are several ways to assess the performance of the organization, and data envelopment analysis (DEA) is one of the most important methods. DEA is an appropriate technique to measure the efficiency of decision-making units, but does not provide complete information about the unit & apos; s productivity. Malmquist productivity index is one of the methods for measuring productivity and the main advantage of this index is the possibility of the productivity changes over time. In this study, DEA is used to measure service performance and economic foundation so that the performance of four companies within a 3-month period were evaluated. In this work, the cost of the system and investment were used as inputs, revenue and profit were considered as the output and constant returns to scale (CCR) was used to analyze the system, which yields 0.9 for all units when all input/output data were considered in crisp form. The efficacy of different units using interval data also showed different productivity compared with the crisp model. The productivity measures of the companies in three-month period were studied using the Malmquist based productivity index and the results were analyzed.

Among the activists of the money market, banks as the most important financial institutions undertake an important role in optimal appropriation of financial short-term resources. Furthermore, they allocate the short-term surplus funds to enterprises, which have a short-term need. Holding a main part of the funds in economy circulation, banks have a critical role in adjustment of economic relations. Banks are facing different types of risks in their daily operations. In the banking system, the CAMELS indictors are used to evaluate and rate of the performance of banks. The CAMELS rating model is one of the most effective systems of financial assessment in banks. Therefore, in this research, the effects of CAMELS indicators of banks on risk taking of Iranian banks are studied. The statistical population of the national banking system includes all governmental and private banks. The whole statistical population is studied as a research sample during 2006-2011. Taking into consideration the fact that the research data or section-bounded and time-bounded, a combinational regression analysis has been used. The results of the combinational regression analysis have supported the presence of a reverse and meaningful effect of the indicators of assets quality and sensitivity of market risk on risk taking in national banks. In addition, the results have supported the direct and meaningful effects of capital sufficiency and quality of profit-making on risk taking, however, the effects of the indicators of management quality and liquidity quality on risk taking have been rejected.

Construction sites are accident-prone locations and therefore safety management plays an im-portant role in these workplaces. This study presents an adaptive algorithm for performance as-sessment of project management with respect to resilience engineering and job security in a large construction site. The required data are collected using questionnaires in a large construction site. The presented algorithm is composed of radial basis function (RBF), artificial neural networks multi-layer perceptron (ANN-MLP), and statistical tests. The results indicate that preparedness, fault-tolerance, and flexibility are the most effective factors on overall efficiency. Moreover, job security and resilience engineering have similar statistical impacts on overall system efficiency. The results are verified and validated by the proposed algorithm.