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DEA and transportation efficiency

In: Handbook of International Trade and Transportation

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  • Kevin Hyosoo Park
  • Young-Tae Chang

Abstract

Efficiency gains in transport operation benefit transport operators by increasing competitive advantage. Moreover, they increase social welfare through reduction in trade costs. A popular method to measure efficiency is data envelopment analysis (DEA), a programming-based technique. This chapter summarizes key DEA models used in transportation and international trade research. The authors explain divergent DEA models, such as CCR, BCC, and directional distance function. They go on to cover some of the recent applications, for example bootstrapped truncated regression, to find determinants of efficiency. In each section, they review relevant studies in the transportation or international trade sector. Lastly, they suggest directions for future research.

Suggested Citation

  • Kevin Hyosoo Park & Young-Tae Chang, 2018. "DEA and transportation efficiency," Chapters, in: Bruce A. Blonigen & Wesley W. Wilson (ed.), Handbook of International Trade and Transportation, chapter 15, pages 453-477, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:17028_15
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    Cited by:

    1. Hensmans, Manuel, 2021. "Exploring the dark and bright sides of Internet democracy: Ethos-reversing and ethos-renewing digital transformation," Technological Forecasting and Social Change, Elsevier, vol. 168(C).

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    Keywords

    Economics and Finance;

    Statistics

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