@article { author = {Ronaghi, M.H. and Feizi, K. and Asadpoor, A.}, title = {A Decision Making Model to Select Business Intelligence Systems by Using Grey Theory (Technical note)}, journal = {Advances in Industrial Engineering}, volume = {48}, number = {1}, pages = {73-82}, year = {2014}, publisher = {University of Tehran}, issn = {2783-1744}, eissn = {2783-1744}, doi = {10.22059/jieng.2014.51151}, abstract = {The term business intelligence (BI) can refer to various computerized methods and processes of turning data into information and then into knowledge, which is eventually used to enhance organizational Decision making. In the last decade, Business intelligence has evolved as one of the critical applications in organizations to provide useful insight, support decision-making, and drive organizational performance. Grey system theory was developed by Deng based upon the concept that information is sometimes incomplete or unknown. The intent is the same as with factor analysis, cluster analysis, and discriminant analysis, except that those methods often don't work well when sample size is small and sample distribution is unknown. With grey related analysis, interval numbers are standardized through norms, which allow transformation of index values through product operations. This article is a descriptive survey. We have tried to find a suitable solution for selecting business intelligence systems. In the proposed solution Grey theory is used to assigned adequate relative importance to the criteria then an optimum alternative between four brands was selected.}, keywords = {Business intelligence systems,Grey systems,Decision making}, url = {https://aie.ut.ac.ir/article_51151.html}, eprint = {https://aie.ut.ac.ir/article_51151_7a3e3bbd645e568c264285bebaa04f6e.pdf} }