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İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ

Year 2021, Volume: 3 Issue: 2, 1 - 17, 31.12.2021

Süleyman Çakır

Abstract

In the literature, it is observed that most of the Malmquist Productivity Index (MPI) studies use classical DEA models with an optimistic point of view. Since traditional DEA models do not include a pessimistic perspective, decision makers are deprived of some important managerial information. In this study, productivity analysis is performed using double frontier DEA-based MPI model, which addresses optimistic and pessimistic perspectives together. In the application, the productivity changes between the years 2018-2019 of 9 electrical equipment manufacturing firms listed in ISO500 firms announced by Istanbul Chamber of Industry (ISO) is conducted. Thanks to the proposed model, decision makers are given the opportunity to make a more comprehensive assessment by taking into account two conflicting perspectives simultaneously.

Keywords

Malmquist verimlilik endeksi iki sınırlı veri zarflama analizi performans ölçümü verimlilik analizi ISO500 firmaları

References

  • [1] Charnes A., Cooper W.W., and Rhodes E. “Measuring the efficiency of decision making Units", European Journal of Operational Research, 2, 429–444, 1978.
  • [2] Emrouznejad A., and Yang G.L. “A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016”, Socio-Economic Planning Sciences, 61, 4-8, 2018.
  • [3] Malmquist, S. “Index numbers and indifference surfaces”. Trabajos de Estatistica 4,209–242, 1953.
  • [4] Caves D.W. Christensen L.R. and Diewert W.E. “The economic theory of index numbers and the measurement of input, output, and productivity”, Econometrica 50 (6) 1393–1414, 1982a.
  • [5] Caves D.W. Christensen L.R. and Diewert W.E. “Multilateral comparisons of output, input, and productivity using superlative index numbers”. The Economic Journal, 92, 73–86, 1982b.
  • [6] Färe R, Grosskopf S, Norris M,, and Zhang, Z. “Productivity growth, technical progress and efficiency change in industrialized countries”, American Economic Review, 84:66–83, 1994.
  • [7] Wang, D.D. “Performance assessment of major global cities by DEA and Malmquist index analysis”, Computers, Environment and Urban Systems, 77, 2019.
  • [8] Amani, N., Valami, H.B., and Ebrahimnejad, A.,. “Application of Malmquist productivity index with carry-overs in power industry”, Alexandria Engineering Journal, 57(4), 3151-3165, 2018.
  • [9] Aparicio J., Crespo-Cebada E., Pedraja-Chaparro F., and Santin D. “Comparing school ownership performance using a pseudo-panel database: A Malmquist-type index approach”, European Journal of Operational Research, 256(2), 533-542, 2017.
  • [10] Sheng Y., Shi X., and Zhang, D. “Energy trade efficiency and its determinants: A Malmquist index approach”, Energy Economics, 50, 306-314, 2015.
  • [11] Chen Y., and Ali A.I. DEA “Malmquist productivity measure: New insights with an application to computer industry”, European Journal of Operational Research, 159, 239–249, 2004.
  • [12] Pastor J.T, and Lovell C.A.K., “A global Malmquist productivity index”, Economics Letters, 88, 266-271, 2000.
  • [13] Yu M.M. “The capacity productivity change and the variable input productivity change: a new decomposition of the Malmquist productivity index”, Applied Mathematics and Computation, 185, 375–381, 2005.
  • [14] Kao, C. “Malmquist productivity index based on common-weights DEA:The case of Taiwan forests after reorganization”, Omega 38, 484–491, 2011.
  • [15] Fuentes R., and Lillo-Bañuls A. “Smoothed bootstrap Malmquist index based on DEA model to compute productivity of tax offices”, Expert Systems with Applications, 42(5), 2442-2450, 2015.
  • [16] Zhang N., Zhou P., and Kung C.C. “Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis”, Renewable and Sustainable Energy Reviews, 41, 584-593, 2015.
  • [17] Wang Y.M., and Lan Y.X. Measuring Malmquist productivity index: A new approach based on double frontiers data envelopment analysis, Mathematical and Computer Modelling 54, 2760–277, 2011.
  • [18] Parkan C., and Wang M.L. The Worst Possible Relative Efficiency Analysis Based on Inefficient Production Frontier. Working Paper, Department of Management Sciences, City University Of Hong Kong, 2000.

DYNAMIC PRODUCTIVITY MEASUREMENT in ISO500 FIRMS USING DOUBLE FRONTIER MALMQUIST PRODUCTIVITY INDEX

Year 2021, Volume: 3 Issue: 2, 1 - 17, 31.12.2021

Süleyman Çakır

Abstract

In the literature, it is observed that most of the Malmquist Productivity Index (MPI) studies use classical DEA models with an optimistic point of view. Since traditional DEA models do not include a pessimistic perspective, decision makers are deprived of some important managerial information. In this study, productivity analysis is performed using double frontier DEA-based MPI model, which addresses optimistic and pessimistic perspectives together. In the application, the productivity changes between the years 2018-2019 of 9 electrical equipment manufacturing firms listed in ISO500 firms announced by Istanbul Chamber of Industry (ISO) is conducted. Thanks to the proposed model, decision makers are given the opportunity to make a more comprehensive assessment by taking into account two conflicting perspectives simultaneously.

References

  • [1] Charnes A., Cooper W.W., and Rhodes E. “Measuring the efficiency of decision making Units", European Journal of Operational Research, 2, 429–444, 1978.
  • [2] Emrouznejad A., and Yang G.L. “A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016”, Socio-Economic Planning Sciences, 61, 4-8, 2018.
  • [3] Malmquist, S. “Index numbers and indifference surfaces”. Trabajos de Estatistica 4,209–242, 1953.
  • [4] Caves D.W. Christensen L.R. and Diewert W.E. “The economic theory of index numbers and the measurement of input, output, and productivity”, Econometrica 50 (6) 1393–1414, 1982a.
  • [5] Caves D.W. Christensen L.R. and Diewert W.E. “Multilateral comparisons of output, input, and productivity using superlative index numbers”. The Economic Journal, 92, 73–86, 1982b.
  • [6] Färe R, Grosskopf S, Norris M,, and Zhang, Z. “Productivity growth, technical progress and efficiency change in industrialized countries”, American Economic Review, 84:66–83, 1994.
  • [7] Wang, D.D. “Performance assessment of major global cities by DEA and Malmquist index analysis”, Computers, Environment and Urban Systems, 77, 2019.
  • [8] Amani, N., Valami, H.B., and Ebrahimnejad, A.,. “Application of Malmquist productivity index with carry-overs in power industry”, Alexandria Engineering Journal, 57(4), 3151-3165, 2018.
  • [9] Aparicio J., Crespo-Cebada E., Pedraja-Chaparro F., and Santin D. “Comparing school ownership performance using a pseudo-panel database: A Malmquist-type index approach”, European Journal of Operational Research, 256(2), 533-542, 2017.
  • [10] Sheng Y., Shi X., and Zhang, D. “Energy trade efficiency and its determinants: A Malmquist index approach”, Energy Economics, 50, 306-314, 2015.
  • [11] Chen Y., and Ali A.I. DEA “Malmquist productivity measure: New insights with an application to computer industry”, European Journal of Operational Research, 159, 239–249, 2004.
  • [12] Pastor J.T, and Lovell C.A.K., “A global Malmquist productivity index”, Economics Letters, 88, 266-271, 2000.
  • [13] Yu M.M. “The capacity productivity change and the variable input productivity change: a new decomposition of the Malmquist productivity index”, Applied Mathematics and Computation, 185, 375–381, 2005.
  • [14] Kao, C. “Malmquist productivity index based on common-weights DEA:The case of Taiwan forests after reorganization”, Omega 38, 484–491, 2011.
  • [15] Fuentes R., and Lillo-Bañuls A. “Smoothed bootstrap Malmquist index based on DEA model to compute productivity of tax offices”, Expert Systems with Applications, 42(5), 2442-2450, 2015.
  • [16] Zhang N., Zhou P., and Kung C.C. “Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis”, Renewable and Sustainable Energy Reviews, 41, 584-593, 2015.
  • [17] Wang Y.M., and Lan Y.X. Measuring Malmquist productivity index: A new approach based on double frontiers data envelopment analysis, Mathematical and Computer Modelling 54, 2760–277, 2011.
  • [18] Parkan C., and Wang M.L. The Worst Possible Relative Efficiency Analysis Based on Inefficient Production Frontier. Working Paper, Department of Management Sciences, City University Of Hong Kong, 2000.
There are 18 citations in total.

Details

Primary Language Turkish
Subjects Industrial Engineering
Journal Section Articles
Authors

Süleyman Çakır

Publication Date December 31, 2021
Submission Date March 21, 2021
Published in Issue Year 2021 Volume: 3 Issue: 2

Cite

APA Çakır, S. (2021). İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ. Uluslararası Batı Karadeniz Mühendislik Ve Fen Bilimleri Dergisi, 3(2), 1-17.
AMA Çakır S. İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ. UMÜFED. December 2021;3(2):1-17.
Chicago Çakır, Süleyman. “İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ”. Uluslararası Batı Karadeniz Mühendislik Ve Fen Bilimleri Dergisi 3, no. 2 (December 2021): 1-17.
EndNote Çakır S (December 1, 2021) İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ. Uluslararası Batı Karadeniz Mühendislik ve Fen Bilimleri Dergisi 3 2 1–17.
IEEE S. Çakır, “İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ”, UMÜFED, vol. 3, no. 2, pp. 1–17, 2021.
ISNAD Çakır, Süleyman. “İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ”. Uluslararası Batı Karadeniz Mühendislik ve Fen Bilimleri Dergisi 3/2 (December 2021), 1-17.
JAMA Çakır S. İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ. UMÜFED. 2021;3:1–17.
MLA Çakır, Süleyman. “İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ”. Uluslararası Batı Karadeniz Mühendislik Ve Fen Bilimleri Dergisi, vol. 3, no. 2, 2021, pp. 1-17.
Vancouver Çakır S. İKİ SINIRLI MALMQUIST VERİMLİLİK ENDEKSİ YÖNTEMİYLE ISO500 FİRMALARINDA DİNAMİK VERİMLİLİK ÖLÇÜMÜ. UMÜFED. 2021;3(2):1-17.
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