DEA-based malmquist productivity index measure of operating efficiencies: New insights with an application to container ports

  • Bo-xin Fu (付博新)Email author
  • Xiang-qun Song (宋向群)
  • Zi-jian Guo (郭子坚)


To investigate the long-term operating efficiencies of container ports, we extend the work of previous researches to present a new systemic and improved method of data envelopment analysis (DEA)-based Malmquist productivity index (MPI) in this paper. An approach based on both panel data and multi-inputs/outputs is considered comprehensively, and aims at measuring the operating efficiencies of 10 leading container ports in China from 2001 to 2006 by applying this new systematic calculation method. The results illustrate that the main influence factor of total factor productivity change is the technology change, and the container transportation of these 10 ports is on the healthy development status and will recover and grow reposefully in the following years.

Key words

port operating efficiency Malmquist productivity index (MPI) data envelopment analysis (DEA) 

CLC number

U 169.6 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Fulginiti L E, Perrin R K. LDC agriculture: Nonparametric Malmquist productivity indexes [J]. Journal of Development Economics, 1997, 53(2): 373–390.CrossRefGoogle Scholar
  2. [2]
    Madden G, Savage S J. Telecommunications productivity, catch up and innovation [J]. Telecommunications Policy, 1999, 23: 65–81.CrossRefGoogle Scholar
  3. [3]
    Pang R Z. Dynamic evaluation of main sea ports in mainland china based on DEA model [J]. Economic Research Journal, 2006, 41(6): 92–100 (in Chinese).Google Scholar
  4. [4]
    Golany B, Roll Y. An application procedure for DEA [J]. International Journal of Management Science, 1989, 17(3): 237–250.Google Scholar
  5. [5]
    Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision making units [J]. European Journal of Operational Research, 1978, 2(6): 429–444.zbMATHCrossRefMathSciNetGoogle Scholar
  6. [6]
    Färe R. Grosskopf S, Lindgren B, et al. Productivity change in Swedish pharmacies 1980–1989: A nonparametric Malmquist approach [J]. Journal of Productivity Analysis, 1992, 3(1): 85–102.CrossRefGoogle Scholar
  7. [7]
    Chen Y, Ali A I. DEA Malmquist productivity measure: New insights with an application to computer industry [J]. European of Journal of Operational Research, 2004, 159(1): 239–249.zbMATHCrossRefGoogle Scholar
  8. [8]
    Lin L C, Tseng L A. Application of DEA and SFA on the measurement of operating efficiencies for 27 International container ports [C]//Proceedings of the Eastern Asia Society for Transportation Studies. Bangkok, Thailand: Eastern Asia Soc Transportat Studies, 2005: 592–607.Google Scholar
  9. [9]
    David A G, Vlad M. Determinants of commercial bank performance in transition: An application of data envelopment analysis [J]. Comparative Economic Studies, 2006, 48: 497–522.CrossRefGoogle Scholar
  10. [10]
    Joe Z. Imprecise data envelopment analysis (IDEA): A review and improvement with an application [J]. European Journal of Operational Research, 2003, 144(3): 513–529.zbMATHCrossRefMathSciNetGoogle Scholar
  11. [11]
    Wang T F, Song D W, Cullinane K. Container port production efficiency: A comparative study of DEA and FDH approaches [J]. Journal of the Eastern Asia Society for Transportation Studies, 2003, 5: 698–713.Google Scholar
  12. [12]
    Hui Z, Trevor H, Robert T. Sparse principal component analysis [J]. Journal of Computational and Graphical Statistics, 2006, 15(2): 265–286.CrossRefMathSciNetGoogle Scholar
  13. [13]
    Zhang Y S, Zeng D M, Zhang L F. Improving PCA application in enterprise performance evaluation [J]. Journal of Shanxi Finance and Economics University, 2004, 26(4): 80–85 (in Chinese).MathSciNetGoogle Scholar
  14. [14]
    Ali A I, Seiford L M. Translation invariance in data envelopment analysis [J]. Operations Research Letters, 1990, 9: 403–405.zbMATHCrossRefGoogle Scholar
  15. [15]
    Coelli T. A guide to DEAP version 2.1: A data envelopment analysis (computer) [R]. Australia: University of New England, 1996.Google Scholar

Copyright information

© Shanghai Jiaotong University and Springer-Verlag GmbH 2009

Authors and Affiliations

  • Bo-xin Fu (付博新)
    • 1
    Email author
  • Xiang-qun Song (宋向群)
    • 1
  • Zi-jian Guo (郭子坚)
    • 1
  1. 1.School of Civil and Hydraulic EngineeringDalian University of TechnologyDalianChina

Personalised recommendations