Title: Measuring dynamic competitiveness among container ports: an autoregressive distributed lag approach

Authors: Chien-wen Shen; Heng-chi Lee; Ching-chih Chou

Addresses: Department of Business Administration, National Central University, No. 300, Jhongda Rd., Jhongli City, Taoyuan County 32001, Taiwan ' Department of Logistics Management, National Kaohsiung First University of Science and Technology, No. 2, Jhuoyue Rd., Nanzih, Kaohsiung City 811, Taiwan ' Graduate Institute of Management, National Kaohsiung First University of Science and Technology, No. 2, Jhuoyue Rd., Nanzih, Kaohsiung City 811, Taiwan

Abstract: This paper proposes a method for applying the autoregressive distributed lag (ARDL) approach to the analysis of port competitiveness to overcome the methodological limitations of the commonly used time series approach, which may cause inconsistent orders of integration or large standard errors. An empirical analysis based on the ARDL approach was also conducted to investigate the competitive relationships among the top five worldwide container ports: Shanghai, Singapore, Hong Kong, Shenzhen, and Busan. Their long-term relationships were first evaluated by the bounds testing procedures with three alternative models. Then the long-term ARDL models were developed to understand their long-term equilibriums. In addition, we estimated short-run dynamics by the ARDL model's error correction form. Our approach can provide maritime transport practitioners a practical tool for reliable port competition analysis and container demand forecasting.

Keywords: container transport; autoregressive distributed lag model; error correction model; ECM; modelling; dynamic competitiveness; container ports; Shanghai; Singapore; Hong Kong; Shenzhen; Busan; port competition analysis; container demand forecasting; container shipping.

DOI: 10.1504/IJSTL.2013.056855

International Journal of Shipping and Transport Logistics, 2013 Vol.5 No.6, pp.637 - 651

Received: 07 Nov 2012
Accepted: 03 Apr 2013
Published online: 28 Feb 2014 *

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