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Container ship investment Decisions―Newbuilding vs second-hand vessels

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  • Fan, Lixian
  • Li, Ziyan
  • Xie, Jiaqi
  • Yin, Jingbo

Abstract

Ship investment is a crucial strategic issue for shipping companies as the container shipping industry is highly capital-intensive. In practice, a company's ship investment decision mainly concerns new shipbuilding and second-hand vessels. The investment of new container ships with advanced technology is high in cost and the payback period is long. Differently, the second-hand vessels' investment cycle is shorter, but there are certain drawbacks in loading capacity and maintenance. Therefore, it is significant to investigate the investment selection of new-building and second-hand ships in the container shipping market. Previous studies have analyzed this topic at aggregate or industry level. Few studies have attempted to reveal ship type preferences from observed individual data. Therefore, using the data from the Clarkson's World Fleet Register between 2000 and 2021, this study employs the Nested Logit model to analyze the container ship investment preferences, and explore the impact of different variables on decision-making from the perspective of individual companies. The empirical results suggest the higher substitution effect among alternatives within the same nest than that of crossing nests. Along with discussion on the effects of various factors, it discloses the higher preferences of larger types of vessels in responding to competitors' capacity expansion, especially the larger companies. Therefore, it is important to distinguish the larger companies' capacity expansion between responding to demand and competing with competitors, especially for those companies adopting follower strategies.

Suggested Citation

  • Fan, Lixian & Li, Ziyan & Xie, Jiaqi & Yin, Jingbo, 2023. "Container ship investment Decisions―Newbuilding vs second-hand vessels," Transport Policy, Elsevier, vol. 143(C), pages 1-9.
    • Handle: RePEc:eee:trapol:v:143:y:2023:i:c:p:1-9
    DOI: 10.1016/j.tranpol.2023.09.005
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    References listed on IDEAS

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    1. Andreas G. Merikas & Anna A. Merika & George Koutroubousis, 2008. "Modelling the investment decision of the entrepreneur in the tanker sector: choosing between a second-hand vessel and a newly built one," Maritime Policy & Management, Taylor & Francis Journals, vol. 35(5), pages 433-447, October.
    2. Robin Greenwood & Samuel G. Hanson, 2015. "Waves in Ship Prices and Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(1), pages 55-109.
    3. McFadden, Daniel, 1980. "Econometric Models for Probabilistic Choice among Products," The Journal of Business, University of Chicago Press, vol. 53(3), pages 13-29, July.
    4. Alizadeh, Amir H. & Nomikos, Nikos K., 2007. "Investment timing and trading strategies in the sale and purchase market for ships," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 126-143, January.
    5. Christa Sys & Gust Blauwens & Eddy Omey & Eddy Van De Voorde & Frank Witlox, 2008. "In Search of the Link between Ship Size and Operations," Transportation Planning and Technology, Taylor & Francis Journals, vol. 31(4), pages 435-463, June.
    6. Wolfgang Bessler & Wolfgang Drobetz & Jorg Seidel, 2008. "Erratum: Ship funds as a new asset class: An empirical analysis of the relationship between spot and forward prices in freight markets," Journal of Asset Management, Palgrave Macmillan, vol. 9(3), pages 254-254, September.
    7. Xu, Jane Jing & Yip, Tsz Leung & Marlow, Peter B., 2011. "The dynamics between freight volatility and fleet size growth in dry bulk shipping markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 983-991.
    8. Feng Lian & Jiaru Jin & Zhongzhen Yang, 2019. "Optimal container ship size: a global cost minimization approach," Maritime Policy & Management, Taylor & Francis Journals, vol. 46(7), pages 802-817, October.
    9. Wolfgang Bessler & Wolfgang Drobetz & Jörg Seidel, 2008. "Ship funds as a new asset class: An empirical analysis of the relationship between spot and forward prices in freight markets," Journal of Asset Management, Palgrave Macmillan, vol. 9(2), pages 102-120, July.
    10. Lee, Choong Bae & Wan, Junbin & Shi, Wenming & Li, Kevin, 2014. "A cross-country study of competitiveness of the shipping industry," Transport Policy, Elsevier, vol. 35(C), pages 366-376.
    11. Kou, Ying & Luo, Meifeng, 2018. "Market driven ship investment decision using the real option approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 714-729.
    12. Lixian Fan & Meifeng Luo, 2013. "Analyzing ship investment behaviour in liner shipping," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(6), pages 511-533, November.
    13. Steve Engelen & Hilda Meersman & Eddy Van De Voorde, 2006. "Using system dynamics in maritime economics: an endogenous decision model for shipowners in the dry bulk sector," Maritime Policy & Management, Taylor & Francis Journals, vol. 33(2), pages 141-158, May.
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