Abstract: Fluctuations in container liner shipping rates are the norm in the industry, with different lines on the same route charging different rates, and even the same line on the same route charging different rates at different booking stages. As a result, cargo owners are naturally always concerned about container liner shipping rates. At the same time, due to the dynamic price play between lines, this often leads to customers engaging in booking cancellation-rebooking behavior. How to determine the relationship between pricing and slot allocation of liner companies has also become a key decision problem for liner companies in competitive markets.
Although the construction of a slot allocation optimization model based on revenue management can effectively solve the static slot allocation problem, most current studies divide customers into long-term contract customers and spot customers, ignoring the market segmentation differences between spot customers in the liner shipping market, such as differences in booking cancellation rates. And, of course, the differences in booking cancellation rates between spot customers at different booking stages are not taken into account.
This paper attempts to fill the gaps in existing research from both of the above perspectives. Given the uncertainty of the spot customer market and the withdrawal behavior of customers, a further segmentation of customers in the spot market based on big data of customer booking and withdrawal information, as well as the consideration of the impact of different booking phases to improve the slot utilization rate and the revenue of liner shipping companies, can provide a decision basis for liner shipping companies to formulate reasonable slot allocation and pricing strategies.
To address the problem of liner space allocation in the spot market, where customers frequently withdraw their bookings, a two-step space allocation method based on the division of customer credibility is proposed. First, based on the big data analysis of customers’ historical bookings, a method for predicting customers’ withdrawal rate based on different booking periods is proposed. On this basis, a two-stage slot allocation optimization model based on customer credibility in the spot market is constructed with the objective of maximizing the liner’s revenue, and an equivalent implementation of opportunity constraints is carried out. The empirical analyses are conducted on the example of a Dalian liner’s short sea route to verify the effectiveness and practicality of the model. The results show that, compared with the existing slot allocation strategy, the two-stage slot allocation strategy considering customer credibility can significantly improve the slot utilization rate and the company’s revenue.
The two-stage slot allocation optimization model based on customer reputation proposed in this article provides a new decision-making tool for shipping companies in fierce market competition. This model can not only improve slot utilization and reduce cancellation risk, but also flexibly adjust pricing strategies according to market changes to achieve maximum revenue. With the development of network technology and the continuous improvement of online booking systems, the application of this model will bring greater competitive advantages to shipping companies and promote the healthy development of the container shipping market. Future research can conduct an in-depth analysis of customer competition behavior among shipping companies, in order to optimize the model through more accurate pricing strategies and enhance its practicality and efficiency in practical applications.

Key words: slot allocation, customer credibility, two-stage mixed integer planning, liner shipping, customer back-orders

摘要： 针对即期市场中客户频繁退订的班轮运输舱位分配问题,提出了一种基于客户信誉度划分的两阶段舱位分配方法。首先,根据客户历史订舱的大数据分析,提出了基于不同订舱时段的客户退订率预测方法。在此基础上,以班轮公司收益最大化为目标,构建了基于即期市场客户信誉度的两阶段舱位分配优化模型,并进行了机会约束的等价转换。以大连某班轮公司的近洋航线为例进行实证分析,验证了该模型的有效性和实用性。研究结果表明,相较于现有的舱位分配策略,考虑客户信誉度的两阶段舱位分配策略可以显著提高舱位利用率和公司收益。

关键词: 舱位分配, 客户信誉度, 两阶段混合整数规划, 班轮运输, 客户退订