سنجش ضریب کارایی تجاری‌سازی در پارک‌های علم و فناوری ایران با توجه به ظرفیت صنعتی و نوآوری منطقه‌ای

References

Azadinejad, A., Amadeh, H., & Emami Maibodi, A. (2014). Studying Factors Influencing Technical Efficiency of Industrial Sector Among Different Regions (With Data Envelopement Analysis). Journal of Economic Research (Tahghighat- E- Eghtesadi), 49(1), 173-188 (In Persian).

Bahari, A., Hosseini-Nahad, S., Habibi-Nia, Gh. (2013). Using the bootstrap simulation process to estimate the non-parametric efficient production frontier, investigating the problems in the process presented in Saeed Ebadi's article. Journal of Operational Research in its Applications, 10(2), 113-135 (In Persian).

Balcombe, K., Fraser, I. (2008). An application of the DEA double bootstrap to examine sources of efficiency in Bangladesh rice farming. Applied Economics, 40(15), 1919-1925.

Brümmer, B. (2001). Estimating confidence intervals for technical efficiency: the case of private farms in Slovenia. European review of agricultural economics, 28(3), 285-306.

Charnes, A., Cooper, W.W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429–444.

De Jorge-Moreno, J., Rojas Carrasco, O. (2015). Technical efficiency and its determinants factors in Spanish textiles industry (2002-2009). Journal of Economic Studies, 42(3).

Dong, F., Featherstone, A. M. (2006). Technical and scale efficiencies for chinese rural credit cooperatives: a bootstrapping approach in data envelopment analysis. Journal of Chinese Economic and Business Studies, 4(1), 57-75.

Efron, B., Tibshirani, R. (1993). An introductionto the bootstrap: Monographs on Statistics andApplied Probability. New York and London: Chapman and Hall/CRC.

Farrell, M.J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A (General), 253-290.

Gocht, A., Balcombe, K. (2006). Ranking efficiency units in DEA using bootstrapping an applied analysis for Slovenian farm data. Agricultural Economics, 35(2), 223-229.

Halkos, G., Tzeremes, N. (2010). Performance evaluation using bootstrapping DEA techniques: Evidence from industry ratio analysis. MPRA Paper.

Lee, B. L., Worthington, A. C. (2014). Technical efficiency of mainstream airlines and low-cost carriers: new evidence using bootstrap data envelopment analysis truncated regression. Journal of Air Transport Management, 38, 15-20.

Odeck, J. (2009). Statistical precision of DEA and Malmquist indices: A bootstrap application to Norwegian grain producers. Omega, 37(5), 1007-1017.

Office of Technology Affairs of the Ministry of Science (2019). Statistical results from universities and science and technology parks in Iran (In Persian).

Shahiki Tash, M. N., Taherpoor, J., & Shivaii, E. (2014). Assesment of Factors Affecting Technical Inefficiency of Manufacturing Industries in Iran. Economics Research, 14(52), 47-27 (In Persian).

Simar, L. (1996). Aspects of statistical analysis in DEA-type frontier models. Journal of productivity analysis, 7(3), 177-185.

Simar, L., Wilson, P.W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management science, 44(1), 49-61.

Simar, L., Wilson, P.W. (2000). A general methodology for bootstrapping in non-parametric frontier models. Journal of applied statistics, 27(6), 779-802.

Zakaria, S., Salleh, M.I., & Hassan, S. (2014). A Bootstrap Data Envelopment Analysis (BDEA) approach in Islamic banking sector: A method to strengthen efficiency measurement. In 2014 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 657-661). IEEE.

Zarra-Nezhad, M., Khodadad Kashi, F., & Yousefi Hajiabad, R. (2012). Evaluation of Technical Efficiency in Iranian Manufacturing Sector. Quarterly Journal of Quantitative Economics, 9(2), 31-48 (In Persian).