国铁集团特别提示不要“买长乘短” 及时提交候补购票订单

Core Viewpoint - The railway department is implementing a ticketing strategy prioritizing long-distance travelers while accommodating short-distance needs, aiming to maximize resource utilization during the peak travel season of the Spring Festival [4][7]. Ticket Sales Strategy - The ticket sales strategy is divided into three phases: pre-allocation, dynamic adjustment, and open sales [5][6]. - In the pre-allocation phase, 20% of tickets are reserved for nearby stations to meet medium and long-distance travel demands, while the remaining tickets are allocated based on demand for long-distance segments [4][6]. - During the dynamic adjustment phase, if tickets remain unsold after one day, the railway will adjust allocations based on remaining tickets and demand, releasing additional long-distance tickets for high-demand segments [5][6]. - The open sales phase allows remaining long-distance tickets to be sold without restrictions, following a "first come, first served" principle for those who submitted requests [6]. Ticket Availability and Demand - As of February 15, over 247 million tickets have been sold for the Spring Festival period, indicating high travel demand [4]. - The strategy aims to ensure that long-distance travelers, who have fewer alternative travel options, are prioritized, while still providing some availability for short-distance travelers [7][8]. - The railway department has successfully fulfilled 12.8 million ticket requests through the waiting list system, with a success rate exceeding 70%, of which 51% were for short-distance tickets [8]. Recommendations for Travelers - Travelers with short-distance needs are advised to opt for short-distance trains and utilize the waiting list feature for long-distance tickets when necessary, maximizing the use of up to 60 combinations of "date + train number" to increase the chances of success [8]. - The railway department discourages the practice of purchasing long-distance tickets for short trips, as it can lead to inflated demand data and inefficient resource allocation [8].