۹۳ / ۵٬۰۰۰ Integration of data envelopment analysis model and decision tree in order to evaluate units based on information technology
Subject Areas : GeneralAmir Amini 1 , علی رضا علی نژاد 2 , سمیه شفقی¬زاده 3
1 - دانشکده مهندسی صنایع، دانشگاه صنعتی ارومیه، ارومیه، ایران
2 - دانشکده مهندسی صنایع، دانشگاه صنعتی ارومیه، ارومیه، ایران
3 - دانشکده مهندسی صنایع، دانشگاه صنعتی ارومیه، ارومیه، ایران
Keywords:
Abstract :
Every organization needs an evaluation system to measure this usefulness in order to know the performance and usefulness of its units, and this issue is more important for financial institutions, including companies based on information technology. Data envelopment analysis is a non-parametric method for measuring the efficiency and productivity of decision making units (DMUs). On the other hand, data mining techniques allow DMUs to explore and discover meaningful information, which was previously hidden in large databases. This paper proposes a general framework combining data envelopment analysis with regression trees to evaluate the efficiency and productivity of DMUs. The result of the hybrid model is a set of rules that can be used by policy makers to discover the reasons for efficient and inefficient DMUs. As a case study using the proposed method to investigate the factors related to productivity, a sample including 18 branches of Iranian insurance in Tehran was selected and after modeling based on the advanced input-oriented LVM model with poor accessibility in data coverage analysis with Undesirable output was calculated and with the decision tree technique, rules are extracted to discover the reasons for productivity increase and productivity regression.
1. آذر عادل؛ مؤمنی منصور. 1383. اندازه¬گیری بهره¬وری در شرکت¬های تولیدی به وسیله مدل¬های تحلیل پوششی
داده¬ها، دو ماهنامه علمی پژوهشی دانشور رفتار، دانشگاه شاهد، سال یازدهم، شماره 8.
2. امامی میبدی علی. 1384. اصول و اندازه¬گیری کارایی و بهره¬وری (علمی- کاربردی)، مؤسسه مطالعات پژوهش¬های بازرگانی، چاپ دوم، تهران.
3. اسفاندرانی حمید. 1390. طراحی شبکه فروش بیمه¬های عمر (مورد مطالعاتی شرکت سهامی بیمه ایران به روش تحلیل پوششی داده¬ها(DEA)، پایان¬نامه کارشناسی¬ارشد، دانشگاه تربیت مدرس.
4. دعایی حبیب ا..؛ نیکخواه فرخانی زهرا. 1388. ارزیابی عملکرد عملیاتی و منابع انسانی نمایندگی¬های بیمه کارافرین در استان خوزستان با نگرش چندگانه به روش تحلیل پوششی داده¬ها، فصلنامه صنعت بیمه، سال بیست و چهارم، شماره3و4، پاییز و زمستان، شماره مسلسل96-95.
5. سلطان¬پناه هیرش و همکاران. 1386. ارزیابی کارایی شعب بیمه البرز با استفاده از تحلیل پوششی داده¬ها، فصلنامه صنعت بیمه، سال بیست و دوم، شماره4، زمستان، شماره مسلسل88، 151-177.
6. مشیري سعید؛ رضوان مهدی. 1385. اثر به¬کارگیري فناوري ارتباطات و اطلاعات در کارایی صنعت خدمات هوایی ایران، فصلنامه پژوهش هاي اقتصادي ایران، سال هشتم، ش 26.
7. مهرگان محمدرضا. 1383. مدل¬های کمی در ارزیابی عملکرد سازمان¬ها، انتشارات دانشگاه تهران.
8. Babazadeh, R. Razmi, J. Rabbani, M. Pishvaee, M. S. 2015. An integrated data envelopment¬ ¬¬analysis-mathematical programming approach to strategic biodiesel supply chain network design problem, Journal of Cleaner Production (Article in press).
9. Barros, C. P., Nektarios, M. & Assaf, A. 2010. Efficiency in the Greek insurance industry, European Journal of Operational Research DEA technology. Omega ,PP. 315-325.
10. Bretholt A, Pan J. . Evolving the latent variable model as a an environmental 9. Charnes, A, Cooper, WW, Rhodes, E. 1978. Measuring the efficiency of decision making units, European journal of operational research, 2, 429-444.
11. Barr, R., L.M. Siford and T.F. Simes. 1994. Forecasting bank failure: a non-parametric approach, Recherches Economiques de Louvain.
12. Breiman, L., J. Friedman, R. Olshenand C. Stone. 1984. Classification and Regression Trees, Pacific Grove, CA: Wadsworth-Monterey.
13. Charnes A., W. W. Cooper , Rhodes E. 1978. Measuring the Efficiency, European Journal of Operations Research, No 2.
14. Chen, Y., Cook, W.D., Li, N., Zhu, J. 2009. Additive efficiency decomposition in two stage DEA. European Journal of Operational Research.
15. Emrouznejad A., Anouze A. 2010. Data envelopment analysis with classification and regression tree-a case of banking efficiency, Expert Systems.
16. Efron, B. and Tibishirani R. 1993. An Introduction to the Bootstrap, New York: Chapman and Hall.
17. Fakhari A., Eftekhari Moghadam A.M. 2013. Combination of classification and regression in decision tree for multi-labeling image annotation and retrieval, Applied Soft Computing.
18.Fan Ch.K, & Cheng, Sh.W. 2009. Using Analytic Hierarchy Process Method and Technique for Order Preference by Similarity to Ideal Solution to Evaluate Curriculum in Department of Risk Management and Insurance, J. Soc. Sci., 19(1).
19. Farzipoor R. 2007. Suppliers selection in the presence of both cardinal and ordinal data, European Journal of Operational Research.
20. Emroznejad A., DEA Home page ,http://www.deazone.com/tutorial.
21. Han J., Kamber M. . Data Mining Concept and Techniques. nd Edition. San Francisco, Elsvier.
22. Hand D.J., Manilla H., Smyth P. 2001. Principles of Data, Cambridge, MA: MIT Press.
23. Hosseini Bamakan, S. M. Gholami, P. 2014. A Novel Feature Selection Method Based on an Integrated Data Envelopment Analysis and Entropy Model, 2nd International Conference on Information Technology and Quantitative Management, ITQM 2014, Procedia Computer Science 31, 632 – 638.
24. Hwang S., Kao T.L. 2007. Measuring Managerial Efficiency in Non-Life Insurance Companies: An Application of Two-Stage Data Envelopment Analysis, International Journal of a Management, vol. , No. .
25. Jahanshahloo GR. , Alirezaee MR. 1992. Measuring the efficiency of academic units at the Teacher Training University, Procedings of th Annual Iranian math conference.
26. Kim, H. and G.J. Koehler.1995. Theory and practice of decision tree induction, Omega.
27. Lee, S. 2010. Using data envelopment analysis and decision trees for efficiency analysis and recommendation of B2C controls, Decision Support Systems, 49, 486–497.
28. Luhnen, M. 2009. Efficiency and Competition in Insurance Markets, Dissertation no. 3675.
28. Mahlberg,B & Url, Th. 2010. Single Market effects on productivity in the German insurance industry, Journal of Banking & Finance.
28. Malmquist, S. 1953. Index numbers and indifference surfaces. Trabajos de Estatis- tica.
29. Nagurur, N. N. Rajbhanari, B. 2001. Data envelopment analysis for the performance evaluation of air conditioning and refrigeration companies in Thailand, Business Performance Management.
30. Park, J. Lee, D.S. Christakis, N, and Barabasi,A.L.. 2009. The impact of cellular networks on disease comorbidity, Molecular Systems Biology.
31. Pille, P. and Paradi J. 1997. Facets at the frontier and efficiency measurement in DEA, Paper presented at the Fifth European Workshop on Efficiency and Productivity Analysis.
32. Seol, H. Choi, J. Park, G. Park, Y. 2007. A framework for benchmarking service process using data Envelopment analysis and decision tree, Expert Systems with Applications, 32, 432–440.
33. Shahroudi K., Taleghani M., Mohammadi G. 2001. Efficiency Decomposition in Data Envelopment Analysis: An application to Insurance companies in Iran.
34.Sueyoshi T., Goto P. 2009. DEA-discriminate analysis Methodological comparison among eight discriminant analysis approaches, European Journal of Operational Research.
35. Tavana, M., Keramatpour, M., Santos-Arteaga, F.J., Ghorbaniane, E. 2015. A Fuzzy Hybrid Project Portfolio Selection Method Using Data Envelopment Analysis, TOPSIS and Integer Programming, Expert Systems with Applications (Article in press).
36. Torgo L. 1997. Functional models for regression tree leaves, Proceedings of the th International Conference on Machine Learning.
37. Wang, C. H. Chuang, J. J. 2015. Integrating decision tree With back propagation network to conduct business diagnosis and performance simulation For solar companies, Decision Support Systems (Article in press).
38. Xie X. 2010. Are publicly held firms less efficient? Evidence from the US property-liability insurance industry, Journal of Banking & Finance.
39. Yao, Sh., Han,zh.,& Feng, G. 2007. On technical efficiency of China's insurance industry after WTO accession, China Economic Review.