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Port user typology and representations of port choice behavior: A Q-methodological study

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  • Jin-Young Kim

    (Division of General Studies, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 689-798, Republic of Korea)

Abstract

Research has identified many criteria that contribute to selecting a sea port, yet not much is known about how port users look at these criteria and how they argue on the factors that contribute to their port choice behavior. This study uses the Q methodology to explore the typology of port choice in conjunction with the port users’ own representations of their choice behavior. We employ an in-depth methodology that incorporates both quantitative and qualitative methods for an investigation of port choice behavior among port users particularly in South Korea. The analysis revealed four main types: Service- and corporation-oriented; Location and cost saver; On-time and task achiever; and Capacity and infrastructure friendly type. The results provide some implications and guidance for formulating policies and effective strategies for improving the competitiveness of port authorities and port operators.

Suggested Citation

  • Jin-Young Kim, 2014. "Port user typology and representations of port choice behavior: A Q-methodological study," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 16(2), pages 165-187, June.
    • Handle: RePEc:pal:marecl:v:16:y:2014:i:2:p:165-187
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    Citations

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    Cited by:

    1. Sang-Yoon Lee & Hyunwoo Lim & Hwa-Joong Kim, 2017. "Forecasting container port volume: implications for dredging," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(2), pages 296-314, June.
    2. Bob Castelein & Ron van Duin & Harry Geerlings, 2019. "Identifying Dominant Stakeholder Perspectives on Sustainability Issues in Reefer Transportation. A Q-Method Study in the Port of Rotterdam," Sustainability, MDPI, vol. 11(12), pages 1-21, June.
    3. Javier Cantillo & Víctor Cantillo-García & Víctor Cantillo & Julián Arellana, 2023. "Port choice using aggregate open data: an application to Colombian port zones," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(3), pages 520-548, September.
    4. Peng, Peng & Yang, Yu & Lu, Feng & Cheng, Shifen & Mou, Naixia & Yang, Ren, 2018. "Modelling the competitiveness of the ports along the Maritime Silk Road with big data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 852-867.
    5. Qu, Chenrui & Zeng, Qingcheng & Li, Kevin X. & Lin, Kun-Chin, 2020. "Modeling incentive strategies for landside integration in multimodal transport chains," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 47-64.
    6. Rivelino R. De Icaza & Gregory S. Parnell & Edward A. Pohl, 2019. "Gulf Coast Port Selection Using Multiple-Objective Decision Analysis," Decision Analysis, INFORMS, vol. 16(2), pages 87-104, June.
    7. Xiaoxi Deng & Ying Wang & Gi-Tae Yeo, 2017. "Enterprise Perspective-based Evaluation of Free Trade Port Areas in China," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 451-473, August.

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