Bangladeş'teki İmalat Sanayilerinde Teknik Verimlilik: DEA Parametrik Olmayan Analiz

Bu çalışmanın amacı, Bangladeş imalat sanayiinin teknik verimliliğini değerlendirmektir. Seçilen üç farklı VZA modeliyle VZA analizini kullandık: CCR, BCC ve gevşek tabanlı model. Bu çalışmada girdi değişkenleri olarak firma sayısı, işgücü, maaş/ücretler, sanayi ve sanayi dışı maliyetler, çıktı değişkeni olarak brüt çıktı değeri alınmıştır. Analizimiz, Ortak verimli endüstrilerin içecek imalatı, Tütün imalatı, hazır giyim, kauçuk ve plastik imalatı, ulaşım teçhizatı, Geri dönüşüm, metalik olmayan mineral ürünler, makine ve teçhizat, motorlu taşıtlar ve römorklar ve makine ve teçhizatın Onarımı olduğunu buldu. Üç VZA modeli kullanılarak, çoğu durumda, hazır giyim endüstrilerinin içecek ve tütün ürünleri imalatının, yeterlilik başarısı pozisyonlarında en yüksek performans gösterenler arasında kaldığını keşfetti. Bu araştırma, bu endüstrilerin önemli verimlilik iyileştirmeleri yaptığını ve aynı zamanda küresel pazarda rekabet etmeye devam etme yeteneği kazandıklarını göstermektedir.

Technical Efficiency in the Manufacturing Industries in Bangladesh: A DEA Non-Parametric Analysis

This study's aim is to evaluate the technical efficiency of Bangladesh's manufacturing industry. We utilized DEA analysis with selected three distinct DEA models: CCR, BCC, and the slack-based model. In this study, the number of firms, labour, salary/wages, industrial and non-industrial cost are considered as inputs variables, and the gross output value is set as the output variable. Our analysis found that Common efficient industries are the Manufacture of beverages, Manufacture of tobacco, readymade garments, rubber and plastic, transport equipment, Recycling, non-metallic mineral products, machinery and equipment, motor vehicles & trailers and Repairs of machine & equipment. By using three DEA model explored that, in most circumstances manufacture of beverages, tobacco products, of Readymade garments industries remain among topmost performers in positions of proficiency achievement. This research suggests that those industries have made significant efficiency improvements, and they have also gained the ability to continue competing in the global marketplace.

___

  • Ahmed, S. N. (2009). Productivity modeling in the apparel industry of Bangladesh: an application of data envelopment analysis (DEA) technique.
  • Ahn, H., & Le, M. H. (2014). An insight into the specification of the input-output set for DEA-based bank efficiency measurement. Management Review Quarterly, 64(1), 3-37.
  • Athanassopoulos, A. D., & Ballantine, J. A. (1995). Ratio and frontier analysis for assessing corporate performance: evidence from the grocery industry in the UK. Journal of the Operational Research Society, 46(4), 427-440.
  • 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.
  • Banker, R. D., Cooper, W. W., Seiford, L. M., Thrall, R. M., & Zhu, J. (2004). Returns to scale in different DEA models. European Journal of Operational Research, 154(2), 345-362.
  • Basso, A., & Funari, S. (2001). A data envelopment analysis approach to measure the mutual fund performance. European Journal of Operational Research, 135(3), 477-492.
  • Bayyurt, N., & Yılmaz, S. (2012). The impacts of governance and education on agricultural efficiency: an international analysis. Procedia-Social and Behavioral Sciences, 58, 1158-1165.
  • Buyukkeklik, A., Dumlu, H., & Evci, S. (2016). Measuring the efficiency of turkish SMEs: A data envelopment analysis approach. International Journal of Economics and Finance, 8(6), 190-200.
  • Carrillo, M., & Jorge, J. M. (2017). DEA-like efficiency ranking of regional health systems in Spain. Social Indicators Research, 133(3), 1133-1149.
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1981). Evaluating program and managerial efficiency: an application of data envelopment analysis to program follow through. Management science, 27(6), 668-697.
  • Cook, P. (2001). Finance and small and medium-sized enterprise in developing countries. Journal of Developmental Entrepreneurship, 6(1), 17.
  • Din, M.-u., Ghani, E., & Mahmood, T. (2007). Technical efficiency of Pakistan's manufacturing sector: A stochastic frontier and data envelopment analysis. The Pakistan Development Review, 1-18.
  • Düzakın, E., & Düzakın, H. (2007). Measuring the performance of manufacturing firms with super slacks based model of data envelopment analysis: An application of 500 major industrial enterprises in Turkey. European Journal of Operational Research, 182(3), 1412-1432.
  • Emran, S. J., & Moniruzzaman, M. (2020). The Dynamics and Sources of Technical Efficiency of the Manufacturing Industries in Bangladesh.
  • Farrell, M. The Measurement of Productive EfficiencyJournal of the Royal Statistical Society. Series A (General), 1957. In.
  • Frija, A., Chebil, A., Speelman, S., Buysse, J., & Van Huylenbroeck, G. (2009). Water use and technical efficiencies in horticultural greenhouses in Tunisia. Agricultural Water Management, 96(11), 1509-1516.
  • Gökgöz, F. (2010). Measuring the financial efficiencies and performances of Turkish funds. Acta Oeconomica, 60(3), 295-320.
  • Index, E. (2010). Finance division, Ministry of Finance, Government of the People Republic of Bangladesh. In.
  • Kassam, A. (2017). Efficiency analysis of healthcare sector. Engineering and Technology Journal, 35(5 Part A), 509-515.
  • Khan, A. H., & Farooq, S. (2019). Evaluating Technical Efficiency of Textile Firms in Pakistan: An Application of Data Envelopment Analysis (DEA) Approach. Paradigms, 13(2), 160-169.
  • Khan, M. F. Z. (2014). The Social and Financial Performance of Conventional and Islamic Microfinance Institutions in Pakistan. Al-Idah, 28(1), 17-34.
  • Khan, M. M. N., Ahmad, A., & Jehan, N. (2018). Pakistani Firms' Efficiency: An Empirical Study of Pakistani Listed Firms through Data Envelopment Analysis. Global Social Sciences Review (GSSR), 3, 158-174.
  • Li, L., Li, M., & Wu, C. (2013). Production efficiency evaluation of energy companies based on the improved super-efficiency data envelopment analysis considering undesirable outputs. Mathematical and Computer Modelling, 58(5-6), 1057-1067.
  • Mogha, S. K., Yadav, S. P., & Singh, S. P. (2014). New slack model based efficiency assessment of public sector hospitals of Uttarakhand: State of India. International Journal of System Assurance Engineering and Management, 5(1), 32-42.
  • Njikam, O. (2003). Trade reform and efficiency in Cameroon's manufacturing industries: AERC.
  • Pille, P., & Paradi, J. C. (2002). Financial performance analysis of Ontario (Canada) Credit Unions: An application of DEA in the regulatory environment. European Journal of Operational Research, 139(2), 339-350.
  • Raheli, H., Rezaei, R. M., Jadidi, M. R., & Mobtaker, H. G. (2017). A two-stage DEA model to evaluate sustainability and energy efficiency of tomato production. Information Processing in Agriculture, 4(4), 342-350.
  • Si, L.-B., & Qiao, H.-Y. (2017). Performance of Financial Expenditure in China's basic science and math education: Panel Data Analysis Based on CCR Model and BBC Model. EURASIA Journal of Mathematics, Science and Technology Education, 13(8), 5217-5224.
  • Staub, R. B., e Souza, G. d. S., & Tabak, B. M. (2010). Evolution of bank efficiency in Brazil: A DEA approach. European Journal of Operational Research, 202(1), 204-213.
  • Taymaz, E., & Saatci, G. (1997). Technical change and efficiency in Turkish manufacturing industries. Journal of Productivity Analysis, 8(4), 461-475.
  • Thanassoulis, E. (2001). Introduction to the theory and application of data envelopment analysis: Springer.
  • Titko, J., Stankevičienė, J., & Lāce, N. (2014). Measuring bank efficiency: DEA application. Technological and economic development of economy, 20(4), 739-757.
  • Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3), 498-509.
  • Wang, Y., Pan, J.-f., Pei, R.-m., Yi, B.-W., & Yang, G.-l. (2020). Assessing the technological innovation efficiency of China's high-tech industries with a two-stage network DEA approach. Socio-Economic Planning Sciences, 71, 100810.
  • Wei, C.-K., Chen, L.-C., Li, R.-K., & Tsai, C.-H. (2011). Exploration of efficiency underestimation of CCR model: Based on medical sectors with DEA-R model. Expert systems with applications, 38(4), 3155-3160.
  • Yadava, A. K., & Komaraiah, J. B. (2021). Benchmarking the performance of organic farming in India. Journal of Public Affairs, 21(2), e2208.
  • Zamanian, G. R., Shahabinejad, V., & Yaghoubi, M. (2013). Application of DEA and SFA on the Measurement of Agricultural Technical Efficiency in MENA Countries.
  • Zhu, J. (2015). Data Envelopment Analysis a Handbook of Models and Methods: Springer.