Many places have suspended low-price marketing practices such as "fixed price" for online ride-hailing services. Recently, Xi'an, Shaanxi and other places have issued policies to completely suspend low-price marketing practices such as "fixed price" for online ride-hailing services, and strictly prohibit any form of price fraud and malicious price reduction. Previously, many places such as Yingtan in Jiangxi Province, Kaifeng in Henan Province, and Qingyuan in Guangdong Province have also introduced similar policies, prohibiting platforms from forcing drivers to accept orders through the "fixed price" model, and curbing disorderly low-price competition. Some notices pointed out that such orders disrupted market order and infringed on the rights and interests of practitioners.
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The so-called "fixed price" order means that after the passenger sets the destination, the system generates a fixed settlement price based on factors such as estimated mileage, duration, and real-time traffic conditions. Even if there is a traffic jam or route change, the passenger will still pay the initial price. Due to its low price and controllable expenses, this model is highly attractive to passengers. It was once an important means for online ride-hailing platforms to seize market share and can stimulate the growth of ride-hailing demand in the short term.
There are pros and cons, and this model also brings some significant troubles to the driver community. Many drivers reported that the unit price of "fixed price" orders is generally lower than that of normal orders, and the order time fee is not calculated, leading to the strange phenomenon of "increased order volume but no increase in income." When roads are congested or routes are adjusted, the actual operating costs of drivers increase, but their income cannot be increased accordingly, and labor rights and interests are difficult to be protected.
Regarding the current market controversy over fixed-price orders, Zhang Xiang, secretary-general of the International Intelligent Transportation Technology Association and visiting professor at the Yellow River Institute of Science and Technology, told Observer.com that "fixed-price" orders make drivers seem to have more orders, but the money they earn does not increase, which makes drivers work harder. Stopping the fixed price may effectively improve drivers' income. After the online ride-hailing platform cancels the fixed price, drivers’ operational freedom will be significantly improved. They can charge based on the actual mileage of the trip, and with long-term operating experience, drivers know that the more miles traveled, the greater the corresponding income. This billing method can also better protect their income.
For passengers, Zhang Xiang believes that the price of "fixed price" orders is transparent for passengers, and they pay according to the price. It is clear that there is no need to worry about being "ripped off". After the "fixed price" order is stopped, a few drivers may take long detours and infringe on the interests of passengers.
In addition, after the "fixed price" model is discontinued, passengers' considerations will change when choosing an online ride-hailing platform. Previously, "fixed price" was often the only indicator for passengers to judge whether a trip was favorable. After there is no longer a "fixed price", and with the large number of online ride-hailing platforms in various cities, passengers may choose specific orders based on past experience.
As for the platform, Zhang Xiang believes that although drivers can gain certain benefits after canceling the fixed-price model, the platform may also face the problem of losing consumers.
If some passengers previously chose this platform because of the flat-price model, once this model is cancelled, passengers will consider more factors when choosing an online ride-hailing platform. At this time, the trip price will become an uncertain floating form, and the platform itself has a big data model, which must include multiple parameters, such as trip price, real-time status of the vehicle, and the time the vehicle arrives at the pick-up point (i.e., the waiting time of passengers). These parameters will become important assessment indicators when passengers choose an online ride-hailing platform.
It should be noted that the algorithm model of the platform is usually not made public. However, in general, the basis for adjusting the algorithm of each platform is roughly the same, among which price is one of the key indicators. After all, most passengers will still give priority to choosing a platform based on price. Secondly, the time for the vehicle to arrive at the boarding point (passenger waiting time) is also very important. The shorter the waiting time, the sooner passengers can arrive at their destination. This factor also has a significant impact on passengers' choice.
Taken together, canceling the fixed-price model will not necessarily lead to an increase in driver income, nor may it directly lead to an improvement in the platform's service quality. Each pricing method and each algorithm model currently on the market has its own advantages and disadvantages.
At present, the online ride-hailing market has entered the stage of "stock game" from "barbaric growth".
According to data from the Ministry of Transport, the number of online ride-hailing platform companies nationwide has reached 385, and many places have successively issued warnings of capacity saturation, highlighting the problem of oversupply in the industry. Taking Shenzhen as an example, data in September 2025 shows that there are 27 online ride-hailing platforms there, and 134,490 "Online Booking Taxi Transport Certificates" and 367,248 "Shenzhen Taxi Driver's Certificates" have been issued. However, the average daily order volume of online ride-hailing bicycles is only about 12.9, and the average daily revenue has shown a downward trend compared with the beginning of the year.
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In an environment of involution, the low-price strategy was once a powerful tool for online ride-hailing platforms to seize the market, but it also caused a lot of controversy.
Problems such as opaque platform commissions, "black box" operation of dispatch algorithms, and insufficient social security for drivers continue to plague the industry. Data shows that the current online ride-hailing market has become saturated, and "monthly income exceeding 10,000 yuan" has become a thing of the past. Drivers in many places operate for an average of 9-13 hours a day, but their monthly net income is less than 4,000 yuan. The pressure of industry competition and the survival pressure of employees have increased significantly.
Faced with industry pain points and policy guidance, online ride-hailing platforms have recently taken adjustment measures. Since August this year, many leading platforms such as Didi, T3 Travel, and Caocao Travel have successively announced reductions in the maximum commission, and the commission ratio of some platforms has dropped to 22.5%-27%; AutoNavi has also promised to promote the upper limit of the commission ratio of cooperative platforms to not exceed 27%. These measures are seen as a positive response to drivers’ demands, but whether they can fundamentally improve drivers’ income status and balance the interests of platforms and practitioners remains to be seen in the long term.
In addition, on August 23, the National Development and Reform Commission and other three departments jointly issued the "Internet Platform Price Behavior Rules (Draft for Comments)", which accurately focused on prominent chaos such as forced price reductions and low-price dumping in the platform field. The regulatory scope of this rule not only covers the online ride-hailing industry, but also involves the "lowest price on the entire network" label competition that is common in e-commerce and other fields.
At the same time, the newly revised "Anti-Unfair Competition Law" further clarifies more stringent punishment measures: if a platform uses its data advantage to implement price manipulation, it may be fined up to 1% of its previous year's turnover.
From the perspective of functional positioning, the rules mainly clarify the "operational specifications" of the platform's price behavior and define "what to do"; the law focuses on delineating the "punishment standards" for the consequences of violations and clarifies "the penalty for making mistakes." The two cooperate with each other and work together to form an efficient regulatory force.