IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v143y2023icp1-9.html
   My bibliography  Save this article

Container ship investment Decisions―Newbuilding vs second-hand vessels

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X23002366
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tranpol.2023.09.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fan, Lixian & Gu, Bingmei & Yin, Jingbo, 2021. "Investment incentive analysis for second-hand vessels," Transport Policy, Elsevier, vol. 106(C), pages 215-225.
    2. Sinem Celik Girgin & Thanasis Karlis & Hong-Oanh Nguyen, 2018. "A Critical Review of the Literature on Firm-Level Theories on Ship Investment," IJFS, MDPI, vol. 6(1), pages 1-19, January.
    3. Papapostolou, Nikos C. & Pouliasis, Panos K. & Kyriakou, Ioannis, 2017. "Herd behavior in the drybulk market: an empirical analysis of the decision to invest in new and retire existing fleet capacity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 36-51.
    4. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    5. Ying Kou & Meifeng Luo, 2016. "Strategic capacity competition and overcapacity in shipping," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(4), pages 389-406, May.
    6. Jane Jing Xu & Tsz Leung Yip, 2012. "Ship investment at a standstill? An analysis of shipbuilding activities and policies," Applied Economics Letters, Taylor & Francis Journals, vol. 19(3), pages 269-275, February.
    7. Keun-Sik Park & Young-Joon Seo & A-Rom Kim & Min-Ho Ha, 2018. "Ship Acquisition of Shipping Companies by Sale & Purchase Activities for Sustainable Growth: Exploratory Fuzzy-AHP Application," Sustainability, MDPI, vol. 10(6), pages 1-13, May.
    8. Yang, Zhongzhen & Jiang, Zhenfeng & Notteboom, Theo & Haralambides, Hercules, 2019. "The impact of ship scrapping subsidies on fleet renewal decisions in dry bulk shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 177-189.
    9. Sel, Burakhan & Minner, Stefan, 2022. "A hedging policy for seaborne forward freight markets based on probabilistic forecasts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    10. Moutzouris, Ioannis C. & Nomikos, Nikos K., 2020. "Asset pricing with mean reversion: The case of ships," Journal of Banking & Finance, Elsevier, vol. 111(C).
    11. Yuting Gong & Xueqin Wang & Mo Zhu & Ying‐En Ge & Wenming Shi, 2023. "Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 69-89, January.
    12. Sun, Xiaolei & Tang, Ling & Yang, Yuying & Wu, Dengsheng & Li, Jianping, 2014. "Identifying the dynamic relationship between tanker freight rates and oil prices: In the perspective of multiscale relevance," Economic Modelling, Elsevier, vol. 42(C), pages 287-295.
    13. Zhang, Yi, 2018. "Investigating dependencies among oil price and tanker market variables by copula-based multivariate models," Energy, Elsevier, vol. 161(C), pages 435-446.
    14. Nektarios A. Michail & Konstantinos D. Melas, 2021. "Sentiment-Augmented Supply and Demand Equations for the Dry Bulk Shipping Market," Economies, MDPI, vol. 9(4), pages 1-14, November.
    15. Xiwen Bai & Jasmine Siu Lee Lam, 2019. "An integrated analysis of interrelationships within the very large gas carrier (VLGC) shipping market," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 372-389, September.
    16. Giamouzi, Maria & Nomikos, Nikos K, 2021. "Identifying shipowners’ risk attitudes over gains and losses: Evidence from the dry bulk freight market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    17. Zaili Yang & Esin Erol Mehmed, 2019. "Artificial neural networks in freight rate forecasting," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 390-414, September.
    18. 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.
    19. Wolfgang Drobetz & Dirk Schilling & Lars Tegtmeier, 2010. "Common risk factors in the returns of shipping stocks," Maritime Policy & Management, Taylor & Francis Journals, vol. 37(2), pages 93-120, March.
    20. Theodore Syriopoulos & Michael Tsatsaronis & Ioannis Karamanos, 2021. "Support Vector Machine Algorithms: An Application to Ship Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 55-87, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:trapol:v:143:y:2023:i:c:p:1-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.