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Two-dimensional efficiency decomposition to measure the demand effect in productivity analysis

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  • Lee, Chia-Yen
  • Johnson, Andrew L.

Abstract

This paper proposes a two-dimensional efficiency decomposition (2DED) of profitability for a production system to account for the demand effect observed in productivity analysis. The first dimension identifies four components of efficiency: capacity design, demand generation, operations, and demand consumption, using Network Data Envelopment Analysis (Network DEA). The second dimension decomposes the efficiency measures and integrates them into a profitability efficiency framework. Thus, each component’s profitability change can be analyzed based on technical efficiency change, scale efficiency change and allocative efficiency change. An empirical study based on data from 2006 to 2008 for the US airline industry finds that the regress of productivity is mainly caused by a demand fluctuation in 2007–2008 rather than technical regression in production capabilities.

Suggested Citation

  • Lee, Chia-Yen & Johnson, Andrew L., 2012. "Two-dimensional efficiency decomposition to measure the demand effect in productivity analysis," European Journal of Operational Research, Elsevier, vol. 216(3), pages 584-593.
    • Handle: RePEc:eee:ejores:v:216:y:2012:i:3:p:584-593
    DOI: 10.1016/j.ejor.2011.08.004
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    2. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    3. Duygun, Meryem & Prior, Diego & Shaban, Mohamed & Tortosa-Ausina, Emili, 2016. "Disentangling the European airlines efficiency puzzle: A network data envelopment analysis approach," Omega, Elsevier, vol. 60(C), pages 2-14.
    4. Barak, Sasan & Dahooei, Jalil Heidary, 2018. "A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 134-149.
    5. Charles-Henri Dimaria & Chiara Peronni, 2012. "A new unit labour cost changes decomposition Four pillars of cost competitiveness recovery," Working Papers halshs-00826324, HAL.
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    8. Fangqing Wei & Yanan Fu & Feng Yang & Chun Sun & Sheng Ang, 2023. "Closest target setting with minimum improvement costs considering demand and resource mismatches," Operational Research, Springer, vol. 23(3), pages 1-29, September.
    9. Lee, Chia-Yen & Johnson, Andrew L., 2014. "Proactive data envelopment analysis: Effective production and capacity expansion in stochastic environments," European Journal of Operational Research, Elsevier, vol. 232(3), pages 537-548.
    10. Ang, Sheng & Chen, Chien-Ming, 2016. "Pitfalls of decomposition weights in the additive multi-stage DEA model," Omega, Elsevier, vol. 58(C), pages 139-153.
    11. Tavassoli, Mohammad & Faramarzi, Gholam Reza & Farzipoor Saen, Reza, 2014. "Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 146-153.
    12. Appelbaum, Elie & Berechman, Joseph, 1991. "Demand conditions, regulation, and the measurement of productivity," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 379-400, February.
    13. Georges Assaf, A. & Gillen, David, 2012. "Measuring the joint impact of governance form and economic regulation on airport efficiency," European Journal of Operational Research, Elsevier, vol. 220(1), pages 187-198.
    14. Lee, Chia-Yen, 2014. "Meta-data envelopment analysis: Finding a direction towards marginal profit maximization," European Journal of Operational Research, Elsevier, vol. 237(1), pages 207-216.
    15. Charles-Henri Dimaria, 2012. "Cannon Was Right But Incomplete: Frankel Was A Neglected Early Contribution To Growth Theory," Working Papers halshs-00826519, HAL.
    16. Chia-Yen Lee & Andrew Johnson, 2015. "Effective production: measuring of the sales effect using data envelopment analysis," Annals of Operations Research, Springer, vol. 235(1), pages 453-486, December.
    17. Lee, Chia-Yen, 2016. "Most productive scale size versus demand fulfillment: A solution to the capacity dilemma," European Journal of Operational Research, Elsevier, vol. 248(3), pages 954-962.
    18. Yu, Ming-Miin & Chang, Yu-Chun & Chen, Li-Hsueh, 2016. "Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 186-198.
    19. Wang, H. & Zhou, P. & Xie, Bai-Chen & Zhang, N., 2019. "Assessing drivers of CO2 emissions in China's electricity sector: A metafrontier production-theoretical decomposition analysis," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1096-1107.
    20. Zhao, Yu & Morita, Hiroshi & Maruyama, Yukihiro, 2019. "The measurement of productive performance with consideration for allocative efficiency," Omega, Elsevier, vol. 89(C), pages 21-39.
    21. Heshmati, Almas & C. Kumbhakar, Subal & Kim, Jungsuk, 2016. "Persistent and Transient Efficiency of International Airlines," Working Paper Series in Economics and Institutions of Innovation 444, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.

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