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An Alternative Approach to Efficiency Measurement of Seaports

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Maritime Economics & Logistics Aims and scope

Abstract

A whole series of changes in world economic order in the last decade such as globalisation of production and consumption, and structural changes in inter-port relations, port-hinterland relationships and logistics have strengthened the role of ports as nodes in the global transport system. In such an environment, port production economics plays an important role in port management considerations. This paper reviews approaches to performance measurement and provides an examination of the applicability of alternative (four-stage) Data Envelopment Analysis to seaport efficiency measurement. The study finds that alternative DEA is a potentially powerful approach to the evaluation of the overall efficiency of seaports.

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Notes

  1. Productivity from the point of view of manufacturer/service provider can be loosely defined as the ratio of output(s) to input(s). This definition can explain single output and single input easily. However, it is more common to find production with multiple outputs and inputs, in which case productivity refers to Total Factor Productivity, which is productivity measure involving all factors of production (Coelli et al 1998).

  2. The term DEA and the CCR model were first coined by Charnes et al (1978), which was later used in humanities and social science phenomenally over the last few decades.

  3. This section does not intend to review the development of DEA thoroughly for obvious reasons. Since this paper mainly focuses on the application of DEA to the seaport industry, only the key issues relevant to the current research are addressed. Interested readers may refer to Seiford and Throll (1990), Siegal (1980), Seiford (1996), Sarafoglou (1998), Callen (1990), Charnes et al (1991), Cooper et al (2000), Humphrey (1993), Roll and Sachish (1981), and Forsund and Sarafoglou (2002) for application of DEA in other fields of humanities and social science.

  4. As a corollary, the input-oriented distance function is defined as max{θ∣(Y, X/θ)∈F}.

  5. DRS means when port inputs are increased by one unit and port outputs increase by less than one unit. IRS will result in by more than one unit while CRS induces by exactly one unit. For more detailed graphical explanation of CRS, IRS, and DRS, one can refer to Zhu (2003) and Banker et al (2003).

  6. For a more detailed explanation including congestion model, refer to Byrnes et al (1984), and Ray et al (1998).

  7. For a more detailed explanation of factor-specific model, refer to Zhu (2000).

  8. To know more about the analysis of benchmarking model, see Zhu (2003).

References

  • Aigner, DJ and Chu, SF . (1968): On estimating the industry production function. American Economic Review 58: 824–839.

    Google Scholar 

  • Allen, R, Athanassopoulos, A, Dyson, RG and Thanassoulis, E . (1997): Weights restrictions and value judgements in data envelopment analysis: Evolution, development and future directions. Annals of Operational Research 73: 13–34.

    Article  Google Scholar 

  • Banker, RD, Charnes, A and Cooper, WW . (1984): Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Sciences 30: 1078–1092.

    Article  Google Scholar 

  • Banker, RD, Charnes, Cooper, WW, Seiford, LM, Thrall, RM and Zhu, J . (2004): Returns to scale in different DEA models. European Journal of Operational Research. in press.

  • Banos, J, Coto, P and Rodriguez, A . (1999): Allocative efficiency and over-capitaliation: An application. International Journal of Transport Economics 26: 181–199.

    Google Scholar 

  • Bennathan, E and Walters, A . (1979): Port pricing and investment policy for developing countries, Oxford University Press: London.

    Google Scholar 

  • Brockett, PL, Cooper, WW, Shin, HC and Wang, Y . (1998): Inefficiency and congestion in Chinese production before and after the 1978 economic reforms. Socio-Economic Planning Sciences 32: 1–20.

    Article  Google Scholar 

  • Byrnes, P, Fare, R and Grosskopf, S . (1984): Measuring productive efficiency: An application to Illinois strip mines. Management Sciences 23: 671–681.

    Article  Google Scholar 

  • Callen, JL . (1990): Efficiency measurement in the manufacturing firm. Journal of Productivity Analysis 2: 5–13.

    Article  Google Scholar 

  • Charnes, A, Cooper, WW, Lewin, AY and Seiford, LM . (1994): Data envelopment analysis: Theory, methodology and application. Kluwer Academic Publishers: Boston.

    Book  Google Scholar 

  • Charnes, A, Cooper, WW and Rhodes, E . (1978): Measuring the efficiency of decision making units. European Journal of Operational Research 2: 429–444.

    Article  Google Scholar 

  • Charnes, A, Cooper, WW and Thrall, RM . (1991): A structure for classifying and characterizing efficiency and inefficiency in data envelopment analysis. Journal of Productivity Analysis 2: 197–234.

    Article  Google Scholar 

  • Coelli, T, Prasada Rao, DS and Battese, GE . (1998): An introduction to efficiency and productivity analysis. Kluwer Academic Publishers: Boston.

    Book  Google Scholar 

  • Cooper, WW, Seiford, LM and Tone, K . (2000): Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. Kluwer Academic Publishers: Boston.

    Google Scholar 

  • Cooper, WW, Seiford, LM and Zhu, J . (1999): A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA. Socio-Economic Planning Science 34: 1–25.

    Article  Google Scholar 

  • Coto, P, Banos, J and Rodriguez, A . (2000): Economic efficiency in Spanish ports: Some empirical evidence. Maritime Policy and Management 27: 169–174.

    Article  Google Scholar 

  • Cullinane, K and Song, Dong-Wook . (1998): Container terminals in South Korea: Problems and panaceas. Maritime Policy and Management 25: 63–80.

    Article  Google Scholar 

  • Cullinane, K, Song, DW and Gray, R . (2002): A stochastic frontier model of the efficiency of major container terminals in Asia: Assessing the influence of administrative and ownership structures. Transportation Research Part A 36: 743–762.

    Google Scholar 

  • Cullinane, KPB . (2002): The productivity and efficiency of ports and terminals: Methods and applications. In: Grammenos, CT (ed). Maritime Economics and Business, Informa Publishing: London. pp. 803–831.

    Google Scholar 

  • De Monie, G . (1987): Measuring and evaluating port performance and productivity. Monographs on Port Management No. 6, UNCTAD.

  • De, P and Ghosh, B . (2002): Productivity, efficiency and technological change in Indian ports. International Journal of Maritime Economics 4: 348–368.

    Article  Google Scholar 

  • Dowd, TJ and Leschine, TM . (1990): Container terminal productivity: A perspective. Maritime Policy and Management 17: 108–109.

    Article  Google Scholar 

  • Estache, A, Gonzalez, M and Trujillo, L . (2001): Technical efficiency gains from port reform: The potential for yardstick competition in Mexico. Policy Research Working Paper 2637, The World Bank: Washington.

    Book  Google Scholar 

  • Farrell, MJ . (1957): The measurement of productive efficiency. Journal of the Royal Statistical Society 120: 253–290.

    Article  Google Scholar 

  • Fleming, DK . (1997): World container port rankings. Maritime Policy and Management 24: 175–181.

    Article  Google Scholar 

  • Forsund, FR and Sarafoglou, N. (2002): On the origins of data envelopment analysis. Journal of Productivity Analysis 17: 23–40.

    Article  Google Scholar 

  • Ghosh, B and De, P . (2000): Impact of performance indicator and labour endowment on traffic: Empirical evidence from Indian ports. International Journal of Maritime Economics 2: 259–281.

    Article  Google Scholar 

  • Han, Chul-Hwan . (2002): An empirical study on the determinants of port performance and efficiency. Proceedings of the Second International Port Forum and Conference for the 20th Anniversary of Korean Association of Shipping Studies, Korean Association of Shipping Studies, Gwangyang.

  • Humphrey, DB . (1993): Cost and technical change: Effects from bank deregulation. Journal of Productivity Analysis 4: 9–34.

    Article  Google Scholar 

  • Lee, Jae-Wan . (2001): Challenges faced in container port development in Asia and the Pacific Region. Proceedings of 16th International Conference of The Korea Port Economic Association.

  • Liu, Z . (1995): The comparative performance of public and private enterprises. Journal of Transport Economics and Policy 29: 263–274.

    Google Scholar 

  • Martinez-Budria, E, Diaz-Armas, R, Navarro-Ibanez, M and Ravelo-Mesa, T . (1999): A study of the efficiency of Spanish port authorities using data envelopment analysis. International Journal of Transport Economics 26: 237–253.

    Google Scholar 

  • Ray, S, Seiford, M and Zhu, J . (1998): Market entity behaviour of Chinese state-owned enterprises. Omega 26: 263–278.

    Article  Google Scholar 

  • Roll, Y and Hayuth, Y . (1993): Port performance comparison applying data envelopment analysis (DEA). Maritime Policy and Management 20: 153–161.

    Article  Google Scholar 

  • Roll, Y and Sachish, A . (1981): Productivity measurement at the plant level. Omega 9: 37–42.

    Article  Google Scholar 

  • Sarafoglou, N . (1998): The most influential DEA publications: A comment on Seiford. Journal of Productivity Analysis 9: 279–281.

    Article  Google Scholar 

  • Seiford, L and Throll, RM . (1990): Recent development in DEA. Journal of Econometrics 46: 7–38.

    Article  Google Scholar 

  • Seiford, LM . (1996): Data envelopment analysis: The evolution of the state of the art (1978–1995). Journal of Productivity Analysis 7: 99–137.

    Article  Google Scholar 

  • Shephard, RW . (1970): Theory of cost and production functions. Princeton University Press: Princeton, NJ.

    Google Scholar 

  • Siegal, IH . (1980): Company productivity: Measurement for improvement. Working Paper, W.E. Upjohn Institute for Employment.

  • Talley, WK . (1988): Optimum throughput and performance evaluation of marine terminals. Maritime Policy and Management 15: 327–331.

    Article  Google Scholar 

  • Tongzon, J . (2001): Efficiency measurement of selected Australian and other international ports using data envelopment analysis. Transportation Research Part A, 35: 113–128.

    Google Scholar 

  • Valantine, VC and Gray, R . (2001): The measurement of port efficiency using data envelopment analysis. Proceedings of the Ninth World Conference on Transport Research, 22–27 July, Seoul.

  • Walter, A . (1975): Marginal cost pricing in ports. The Logistics and Transportation Review 11: 297–308.

    Google Scholar 

  • Wang, Teng-Fei, Song, Dong-Wook and Cullinane, K . (2002): The applicability of data envelopment analysis to efficiency measurement of container ports. Conference Proceedings of the IAME 2002, Panama.

  • Wilson, J, Mann, C, Woo, YP, Assamie, N and Choi, I . (2002): Trade facilitation: A development perspective in the Asia Pacific Region. World Bank Working Paper Presented at APEC, World Bank, Washington, DC.

    Google Scholar 

  • Zhu, J . (2000): Multi-factor performance measure model with an application to fortune 500 companies. European Journal of Operational Research 123: 105–124.

    Article  Google Scholar 

  • Zhu, J . (2003): Quantitative models for performance evaluation and benchmarking. Kluwer Academic Publishers: Boston.

    Book  Google Scholar 

Download references

Acknowledgements

This study was supported (in part) by research funds for 2003 of Chosun University, South Korea. We are deeply indebted to Dr Nagesh Kumar, RIS, New Delhi, Dr Buddhadeb Ghosh, Indian Statistical Institute, Kolkata, Dr Saon Ray, RIS, New Delhi, Dr Mirza Beg, and Dr Chiranjiv Neogi, Indian Statistical Institute, Kolkata for their comments. We are also grateful to two anonymous referees for their useful comments. The usual disclaimers apply.

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  1. Division of Economics and International Trade, Chosun University, 375 Seosuk-dong, Gwangju City, 501-759, South Korea

    Ro-kyung Park

  2. Research and Information System for the Non-Aligned and Other Developing Countries (RIS), Zone IV-B, Fourth Floor, India Habitat Centre, Lodhi Road, New Delhi, 110 003, India

    Prabir De

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Park, Rk., De, P. An Alternative Approach to Efficiency Measurement of Seaports. Marit Econ Logist 6, 53–69 (2004). https://doi.org/10.1057/palgrave.mel.9100094

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