Investigating the Mathematical Models (TOPSIS, SAW) to Prioritize the Investments in the Accepted Pharmaceutical

Document Type : Research Paper


Department of Accounting, University of Kurdistan (UOK), Sanandej, Iran



Considering the importance of decision- making in investment, this study prioritizes the accepted pharmaceutical companies in Tehran stock exchange, during 2013-2017 using the following criteria: the return on investment (ROI), reminded increment (RI), return on sales (ROS) and the earnings per share (EPS). Price per earnings ratio of each share (P/E), return on equity (ROE), return on assets (ROA).
After prioritization mentioned companies, they were ranked using mathematical models: SAW and TOPSIS. The object of the study is to encourage financial decision- makers to use math models (SAW, TOPSIS) instead of previous accounting techniques in order to represent the pharmaceutical companies more perfect than before.
The comparison between ranked mentioned companies' according to two math models (SAW, TOPSIS) showed that there is not a significant deference between ranks obtained from SAW and TOPSIS. Furthermore, it is found out that the ranking of the involved companies' was not the same during the study. Some had better process while others not only didn’t have improvement but also gained worse ranking during the study than before.


[1] Azar, A; Anvari, A; Rostami, M R.,The Measurement of the Current Companies Relative Performance of Stock Exchange with a Tegumentary Analysis of Data (information technology indexes), Journal of the Accounting and Auditing Studies, 2007 ,14 ( 50),P. 119-139 , (in Persian).
[2] Aliakbarpoor, Z., Izadikhah, M., Evaluation and ranking DMUs in the presence of both undesirable and ordinal factors in data envelopment analysis, International Journal of Automation and Computing,2012, 9 (6), P. 609-615. Doi: 10.1007/s11633-012-0686-5
[3] Asgharpour, M J., Mult-criteria Decision-Making, Tehran's University Publication, 2014, (in Persian).
[4] Dibachi, H., Behzadi, M.H., Izadikhah, M., Stochastic multiplicative DEA model for measuring the efficiency and ranking of DMUs under VRS technology, Indian Journal of Science and Technology,2014, 7 (11), P. 1765–1773.
[5] Diewert, E., Nakajima, T., Nakamura, A., Nakamura, E., Returns to scale: concept, estimation and analysis of Japan’s turbulent 1964–88 economy, Canadian Journal of Economics, 2011, 44(2). Doi:org/0008-40 85/11 /451-485.
[6] Izadikhah, M., Tavana, M., Di Caprio, D., Santos-Arteaga, F.J., A novel two-stage DEA production model with freely distributed initial inputs and shared intermediate outputs, Expert Systems with Applications,2018, 99 (1), P. 213-230. Doi: 10.1016/j.eswa.2017.11.005
[7] Jahankhahi, A; Zariffard, A; Are The Managers and Investors Using Appropriate Criterions for Company Value Measurement? Financial Researches Journal, 2005, 2 (7 -8), P.41-66. , (in Persian).
[8] Jahankhani,,A ;and Jahankhani ,A, The Usage of the Economic Added Value Conception in the Financial, Financial Researches, 2006,2 (5),P.68-86 , (in Persian).
[9] Khajavi, Sh;Salimifard, A R;R, Masoudthe usage of tegumentary Analysis of Data for Determining the Most Efficient Accepted Companies of the Tehran's Stock Exchange, Social and Human Sciences Magazine of the Shiraz University, 2005.,20 (20).P.43-57, (in Persian).
[10] Delavar, Ali (2011).Advanced Research Method, Tehran, The Unit of the Scientific Studies. , (in Persian).
[11] Rahnamaye Rodposhti, F; Heibati,F; the book of the Financial Management, Termeh Publication, 2019, (in Persian).
[12] Sarmad, Z), Research Methods in Behavioural Sciences, Tehran, Ageh Publication, 2019 (in Persian).
[13] Salehi S ,Jamshid ;Amiri,M;TaghaviFard ,M Taghi; Razavi, SH ., Efficient Units Ranking with the Approaches Combination of tegumentary Analysis of Data, and the Analytical Hierarchy process of the provincial trade organization, Knowledge Management Journal ,2008,21(81),P.75-90 , (in Persian).
[14] Mahmmodzade,S;Shahrabi,J;PariAzar,Mahmmod;Zaeri,M Saied; Project Choosing with The AHP and TOPSIS Method, The Academic Articles Collection of Universe knowledge, engineering and technology 24 years,2006, P. 1307-6484. , (in Persian).
[15] Momeni,M; Najafi,M, A.Evaluation of the Accepted Companies Economic Performance of the Tehran's Stock Exchange with the TOPSIS Model Use, Economic Studies Journal, Human Sciences, 2004, 1,(3), P.55-72 , (in Persian).
[16] Hili, R, ., How will Performance Evaluation Perform, Journal of Portfolio Management, 1998,P. 15-19.
[17] Jensen, M. and Meckling, W, ., They of the Firm: Managerial Behaviour, Agency Costs and Ownership Structure, Journal of Financial Economics,1976, 3, P. 305-360.
[18] Jeroen, B., Mario, V., Maximizing the weighted number of activity execution modes in project planning, European Journal of Operational Research, 2018270(3) P.1–15.
[19] Lawler, E. E. (2003). Reward practices and performance management system effectiveness. Organizational Dynamics32(4), 396-404.‏
[20] Maj, Jolanta. (2016). Corporate Social Responsibility and Diversity Reporting in Polish Companies THE Oil & Gas , International Multidisciplinary Scientific GeoConference: SGEM: Surveying Geology & mining Ecology Management, 3 123-130.‏
[21] Wang, P., Zhu, Z., & Wang, Y. (2016). A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design. Information Sciences, 345, 27-45.
[22] Izadikhah, M., Saeidifar, A., & Roostaee, R. (2014). Extending TOPSIS in fuzzy environment by using the nearest weighted interval approximation of fuzzy numbers. Journal of Intelligent & Fuzzy Systems, 27(6), 2725-2736. DOI: 10.3233/IFS-131109
[23] Simanaviciene, R., & Ustinovichius, L. (2010). Sensitivity analysis for multiple criteria decision making methods: TOPSIS and SAW. Procedia-Social and Behavioral Sciences, 2(6), 7743-7744.
[24] Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., Ghorbani, M. A., & Shahbazi, F. (2018). Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops. Geoderma, 310, 178-190.
[25] Salehi, A., & Izadikhah, M. (2014). A novel method to extend SAW for decision-making problems with interval data. Decision Science Letters, 3(2), 225-236.
[26] Chen, T. Y. (2012). Comparative analysis of SAW and TOPSIS based on interval-valued fuzzy sets: Discussions on score functions and weight constraints. Expert Systems with Applications, 39(2),  1848-1861.