Rough Set Theory

he financial management field has witnessed significant developments in recent years to help decision makers, managers and investors, to made optimal decisions. In this regard, the institutions investment strategies and their evaluation methods continuously change with the rapid transfer of information and access to the fi- nancial data. When information is available as several inputs and output factors, the data envelopment analysis (DEA) applies to calculate the efficiency of com- panies. Distinguishing efficient companies from inefficient ones, makes it possi- ble for the financial managers to select suitable portfolios. The discriminating power of DEA depends on the number of companies under evaluation and the number of inputs and outputs. When the number of inputs and outputs are high compared to the number of units, most of the units will be evaluated as efficient, thus the discriminating power of DEA decreases and the results are not reliable. To deal with this problem, the Quick-Reduct algorithm of the rough set theory (RST) was used in this study to reduce inputs or outputs. It should be noted that the advantage of this algorithm is its ability to use negative data.

The purpose of this research is selecting the Most Effective Strategic Capability for Sustainable Development under Risk and Uncertainty in the Oil Industry by Rough Set Theory. The research methodology is qualitative and quantitative. The target population in the qualitative section included 14 industrial management specialists at the university level and in the quantitative section 32 senior managers in companies active in the Oil Industry. In this research, were used Meta-synthesis and Delphi analysis methods were used to identify the components and propositions of the research and in a small part, the analytical approaches of Ruff collection. The results showed that among the 15 final statements of risk and uncertainty in the Oil Industry, the risk of change in domestic law relative to political / economic diplomacy in the development of infrastructure for the Oil Industry X5 as the most important risk statement and uncertainty in the field. Political and legal risks that have been identified as a measure of the strategic viability of sustainable development. Finally, it was found that, despite the most probable risks selected in this study, namely the risk of changes in domestic law to political / economic diplomacy in the development of infrastructure of the Oil Industry "X5" Existence of sanctions of the world powers "X1" Strategic capabilities of sustainable economic development is the most important feature that should be considered in the country's inflationary conditions.

Recently, Building Information Modeling (BIM) has emerged as a new technology in the construction industry, which is gradually gaining popularity among stakeholders. Despite the importance of BIM, the literature review shows a gap in the evaluation of BIM applications in Iran. Therefore, the aim of the current research is to evaluate the applications of BIM in construction projects. Since the evaluation of the most appropriate option is a multi-criteria decision-making problem. Therefore, decision makers use preferences that are uncertain in evaluating options. Rough's theory, which is efficient in such conditions, is used. First, by using the concept of Rough's theory to transform the preferences of experts and the combined method of Analysis Hierarchy Process (AHP) and VIKOR, is used for evaluation. The results show that the proposed decision method is effective improved objectivity in BIM application evaluation under subjective condition.