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Efficiency measurement using independent component analysis and data envelopment analysis

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  • Kao, Ling-Jing
  • Lu, Chi-Jie
  • Chiu, Chih-Chou

Abstract

Efficiency measurement is an important issue for any firm or organization. Efficiency measurement allows organizations to compare their performance with their competitors' and then develop corresponding plans to improve performance. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among these tools, the data envelopment analysis (DEA) approach is one of the most widely discussed. However, problems of discrimination between efficient and inefficient decision-making units also exist in the DEA context (Adler and Yazhemsky, 2010). In this paper, a two-stage approach of integrating independent component analysis (ICA) and data envelopment analysis (DEA) is proposed to overcome this issue. We suggest using ICA first to extract the input variables for generating independent components, then selecting the ICs representing the independent sources of input variables, and finally, inputting the selected ICs as new variables in the DEA model. A simulated dataset and a hospital dataset provided by the Office of Statistics in Taiwan's Department of Health are used to demonstrate the validity of the proposed two-stage approach. The results show that the proposed method can not only separate performance differences between the DMUs but also improve the discriminatory capability of the DEA's efficiency measurement.

Suggested Citation

  • Kao, Ling-Jing & Lu, Chi-Jie & Chiu, Chih-Chou, 2011. "Efficiency measurement using independent component analysis and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 210(2), pages 310-317, April.
    • Handle: RePEc:eee:ejores:v:210:y:2011:i:2:p:310-317
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    1. Adler, Nicole & Golany, Boaz, 2001. "Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe," European Journal of Operational Research, Elsevier, vol. 132(2), pages 260-273, July.
    2. Puig-Junoy, Jaume, 2000. "Partitioning input cost efficiency into its allocative and technical components: an empirical DEA application to hospitals," Socio-Economic Planning Sciences, Elsevier, vol. 34(3), pages 199-218, September.
    3. Kao, Chiang & Liu, Shiang-Tai, 2009. "Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks," European Journal of Operational Research, Elsevier, vol. 196(1), pages 312-322, July.
    4. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    5. Ray, Subhash C. & Jeon, Yongil, 2008. "Reputation and efficiency: A non-parametric assessment of America's top-rated MBA programs," European Journal of Operational Research, Elsevier, vol. 189(1), pages 245-268, August.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Ancarani, A. & Di Mauro, C. & Giammanco, M.D., 2009. "The impact of managerial and organizational aspects on hospital wards' efficiency: Evidence from a case study," European Journal of Operational Research, Elsevier, vol. 194(1), pages 280-293, April.
    8. W.W. Cooper & Timothy W. Ruefli & Honghui Deng & Jun Wu & Zhongyi Zhang, 2008. "Are state-owned banks less efficient? A long- vs. short-run Data Envelopment Analysis of Chinese banks," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 3(5), pages 533-556.
    9. David Parkin & Bruce Hollingsworth, 1997. "Measuring production efficiency of acute hospitals in Scotland, 1991-94: validity issues in data envelopment analysis," Applied Economics, Taylor & Francis Journals, vol. 29(11), pages 1425-1433.
    10. Sahoo, Biresh K. & Tone, Kaoru, 2009. "Decomposing capacity utilization in data envelopment analysis: An application to banks in India," European Journal of Operational Research, Elsevier, vol. 195(2), pages 575-594, June.
    11. N Adler & B Golany, 2002. "Including principal component weights to improve discrimination in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 985-991, September.
    12. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
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    3. Antônio Artur de Souza & Ewerton Alex Avelar & Alisson Maciel de Faria Marques & Douglas Rafael Moreira & Osmar Ferreira da Silva & Daniele Oliveira Xavier, 2014. "Performance Analysis Of Brazilian Public And Philanthropic Hospitals (Análise Do Desempenho De Hospitais Públicos E Filantrópicos Brasileiros)," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(2), pages 75-94.
    4. Chen, Zhongfei & Matousek, Roman & Wanke, Peter, 2018. "Chinese bank efficiency during the global financial crisis: A combined approach using satisficing DEA and Support Vector Machines☆," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 71-86.
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    7. Andrejić, Milan & Bojović, Nebojša & Kilibarda, Milorad, 2016. "A framework for measuring transport efficiency in distribution centers," Transport Policy, Elsevier, vol. 45(C), pages 99-106.
    8. Villanueva-Cantillo, Jeyms & Munoz-Marquez, Manuel, 2021. "Methodology for calculating critical values of relevance measures in variable selection methods in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 290(2), pages 657-670.
    9. Muhammed Ordu & Hediye Kirli Akin & Eren Demir, 2021. "Healthcare systems and Covid19: Lessons to be learnt from efficient countries," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(5), pages 1476-1485, September.
    10. R. K. Jha & B. S. Sahay & P. Charan, 2016. "Healthcare operations management: a structured literature review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 43(3), pages 259-279, September.
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