[1] Momeni, M. (2011). New topics of research in operations. Moalef Publication. (In Persian). https://telketab.com/book/
[2] Tolou, M., & Khoshhalnakhjiri, Z. (2011). A new mixed integer linear model for selecting the most efficient decision unit with variable returns to scale approach. Industrial management (Tehran university), 8, 37–50. (In Persian). http://ensani.ir/fa/article/478460/
[3] Safari, S., & Azar, A. (2004). Evaluation of the organization’s performance based on quality awards indicators - DEA approach. Business strategies, 2(8), 1–14. (In Persian). https://cs.shahed.ac.ir/article_1941.html?lang=en
[4] Salehi Sarbijan, M., & Rahim, D. (2012). Examining the efficiency and the factors affecting it using the method of data coverage analysis and econometrics (applied study of comprehensive public universities of the country) [presentation]. The first international conference on econometrics, methods and applications (pp. 1–23). (In Persian). https://elmnet.ir/article/20204353-81842/
[5] Zerafat Angiz Langroudi, M. (2011). A method for ranking options with the help of fuzzy concept and data envelopment analysis. Operations research in its applications (applied mathematics), 8(4), 49–57. (In Persian). https://jamlu.liau.ac.ir/index.php?slc_lang=en&sid=1
[6] Hwang, C. L., & Lin, M. J. (2012). Group decision making under multiple criteria: methods and applications (Vol. 281). Springer Science & Business Media.
[7] Cook, W. D., & Kress, M. (1990). A data envelopment model for aggregating preference rankings. Management science, 36(11), 1302–1310.
[8] Chen, C. M. (2009). Evaluation and design of supply chain operations using DEA. Erasmus University Rotterdam.
[9] Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
[10] Catudan, J. M. J. (2016). The impact of tourist arrivals, physical infrastructures, and employment, on regional output growth. Procedia - social and behavioral sciences, 219, 175–184. DOI:10.1016/j.sbspro.2016.05.003
[11] Massidda, C., & Etzo, I. (2012). The determinants of Italian domestic tourism: a panel data analysis. Tourism management, 33(3), 603–610. DOI:https://doi.org/10.1016/j.tourman.2011.06.017
[12] Jovanoviä, S., & Ivana, I. (2016). Infrastructure as important determinant of tourism development in the countries of Southeast Europe. Ecoforum journal, 5(1), 288-294.
[13] Emrouznejad, A., & Yang, G. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-economic planning sciences, 61, 4–8. DOI:https://doi.org/10.1016/j.seps.2017.01.008
[14] Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the royal statistical society series a: statistics in society, 120(3), 253–281.
[15] Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078–1092.
[16] Karnameh Haghighi, H., & Taqvi, M. (2016). Evaluating the efficiency of the tourism industry using data envelopment analysis: a case study of Iran [presentation]. International conference on new approaches to human sciences in the 21st century. (In Persian). https://civilica.com/doc/641815/
[17] Sexton, T. R., Silkman, R. H., & Hogan, A. J. (1986). Data envelopment analysis: Critique and extensions. New directions for program evaluation, 1986(32), 73–105. DOI:10.1002/ev.1441