Demand prediction and sharing strategy in resilient maritime transportation: Considering price and quality competition

Due to the impact of the trade war and the COVID-19 pandemic, the freight demand fluctuated dramatically: the maritime market has undergone a transformation from "one container is difficult to obtain", "one cabin is difficult to obtain" to "empty container pile port". Additionally, the international shipping prices soared first, but the international shipping price have then fluctuated back from the high, and gradually entered a reasonable range. Faced with these fluctuating situations and fierce competition, liners have been leveraging big data analysis technology to predict and share demand information to maintain a resilient transportation system. Targeting a duopoly market structure, this study considers the price and product quality competition environment and studies liners' prediction and sharing strategies of demand information. By establishing a game model to compare three scenarios, namely no demand information prediction, unilateral demand information prediction without sharing, and unilateral demand information prediction and sharing, this study analyzes the impacts of important factors such as market competition intensity and information accuracy on the expected returns of liners and consumer surplus. The research shows that: (1) Whether a liner company invests in predicting the demand information depends on the accuracy of the demand prediction information. When the accuracy of demand prediction information is high enough, liners invest in demand information prediction, resulting in a "win-win" situation in the maritime market. (2) Liners' sharing of demand prediction information reduces the intensity of maritime market competition, which leads to a "satisfactory win-win" situation where the expected returns of both parties increase, with the party sharing the demand information enjoying a greater increase. (3) Unilateral investment in demand information prediction may increase the consumer surplus, but sharing demand information will reduce consumer surplus.