Capacity management by global shipping alliances: findings from a game experiment

Abstract

The present article uses game experiments to understand the dynamics of oligopolistic competition in liner shipping markets. We show how a limited number of carriers, interacting over time, acting independently or grouped into global shipping alliances, are able to effectively and jointly reduce excess capacity. A serious game (called TRALIN) has been designed to this end, mimicking the global liner shipping market where four to five global shipping alliances compete on a set of 12 routes, connecting four ports of call for a few sequential voyages. Carriers are initially subject to low profits due to over-capacity and have to anticipate competitor capacity decisions and vessel deployment simultaneously. Results from 18 experimental games with 4644 decisions were collected and statistically analysed to confirm the main tenets of oligopoly theory and to highlight the existence of a learning effect from successive interactions (rounds in games). Our results suggest that a ‘coordinated’ reduction in capacity is more likely to occur when the number of competitors is limited, but even more when excessive capacity is high, urging the need for cooperation; a learning effect amongst market participants is detected over time. Serious games are flexible tools for improving our understanding of competition, the organization of liner shipping networks, and the role played by global shipping alliances. This tool may help practitioners to understand how over-capacity is evolving within the competitive process, and what factors may influence it. Although voluntarily made simplistic for the purpose of experiments, our design allows one to focus on the main tenets of oligopoly theory as applied to shipping markets.

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Source: Authors from Ghorbani et al. (2019)

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Notes

  1. 1.

    The online version of TRALIN is available in a beta version. Interested readers can send a request to nicolas.gruyer@economics-games.com.

  2. 2.

    With the liner shipping system, it is possible for members of a GSA to compete on a specific trade but to cooperate on other trades through, for instance, consortia, slot- or vessel-chartering agreements. In our example, we assume that they are competing on the transatlantic trade.

  3. 3.

    In future developments of the game, we could imagine that players negotiate and trade their ships instead of using a central agency.

  4. 4.

    The initial total capacity supply usually reaches between 320,000 and 500,000 TEUs (4 or 5 companies × 15 or 20 containerships × 5000 TEUs per vessel), when the aggregate cargo demand for the whole network is only 243,000 TEUs, meaning that the required carrying capacity (50 ships) is more or less exceeded according to treatments.

  5. 5.

    A Variance Inflation Factor (VIF) test indicated values fairly close to 1 and smaller than 5 for the variables number of vessels, freight rates, capacity utilisation and cargo demand (1.86, 1.46, 1.64 and 1. 87, respectively), thus suggesting a moderate correlation between the independent variables.

  6. 6.

    It was not possible to test for random effects in the model because of the non-panel structure of data. It could be done at the cost of dramatic reduction in the number of observations, by pooling the GSA decisions for all routes. This was also tested but did not provide any interesting additional knowledge for this study.

  7. 7.

    Capacity model versus simple quadratic model: F = 91.504*** (Prob < 0.01). Concentration model versus simple quadratic model: F  = 10.741*** (Prob < 0.01). The three models (Capacity, Concentration, single-sloped Quadratic) altogether: F = 11.842*** (Prob < 0.01).

  8. 8.

    That is, intercept and slope of the demand curve are more or less a proxy of elastic demand; market size, measured by cargo demand; freight rate and capacity utilisation.

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Acknowledgements

The authors are indebted to Nicolas Gruyer, co-founder of www.economics-games.com, a portal of classroom games for teaching economics, who first believed in the serious game TRALIN and helped us to develop the online beta version. We are also grateful to Frédéric Salladarré, from the University of Rennes, for his careful assistance on early versions of the manuscript. Finally, we also wish to express our special thanks to the many students in Nantes, Marseilles, Bordeaux, Tangier, Hô Chi Minh City, Tam Dao, Shanghai, Malmö, Copenhagen and Abidjan who participated enthusiastically in the TRALIN sessions, in particular Srey Neath Pan, from Cambodia, who wrote a master dissertation about this experimental game. We also wish to express our appreciation to the MEL editor and reviewers for their insightful comments, which have helped us significantly to improve the paper.

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Cariou, P., Guillotreau, P. Capacity management by global shipping alliances: findings from a game experiment. Marit Econ Logist (2021). https://doi.org/10.1057/s41278-021-00184-9

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Keywords

  • Oligopoly
  • Directed networks
  • Serious game
  • Shipping
  • Global shipping alliances
  • Capacity management