Why Are Shared Bike Services Raising Prices Simultaneously?
Shared bike operators in Beijing, Nanjing and Zhengzhou have lifted the base fare from 1.5 yuan per 30 minutes to about 1.9 yuan per hour, a roughly 30% increase that, according to market saturation, product homogeneity and short‑term supply rigidity, reflects tacit collusion and will mainly deter low‑frequency, short‑trip users.
Shared bike providers—Meituan, Didi Qingju and Hello—have recently adjusted their pricing in Beijing, Nanjing and Zhengzhou, raising the starting fare from 1.5 yuan per 30 minutes to roughly 1.88–1.99 yuan per 60 minutes, an increase of about thirty percent.
Why the three firms appear to raise prices together
Although the immediate reaction might be to suspect collusion, the article shows that the outcome can arise without explicit coordination. Three market conditions make a simultaneous price hike a rational equilibrium:
Stock : the market is saturated, with no new users to capture.
Homogeneity : bikes are interchangeable, so users are indifferent to the provider.
Short‑term supply rigidity : vehicle deployment is constrained by regulation, preventing rapid fleet expansion.
If one firm (A) raises its price first, price‑sensitive users shift to the unchanged firm (B). Because B cannot instantly add more bikes, demand exceeds supply, leading to shortages. The optimal response for B is to raise its price as well, restoring balance and even increasing profit. This convergence is described by Sheldon's "focal point" and "conscious parallelism" in The Strategy of Conflict , a form of tacit collusion that is not illegal.
How the price hike affects user behavior
The article models each travel mode’s "generalized cost" as time cost plus monetary cost. For the median 2.7 km ride (about ten minutes), walking is slower but free, while biking saves time at a monetary price. Users with a high time value (above 2 yuan per ride) will continue to bike; those who view the ride as a convenience of one or two minutes will find a 2 yuan price threshold decisive and may switch to walking.
Applying the Simpson‑Courtney elasticity rule (≈3 % price rise → 1 % demand drop) and a Boston experiment showing a 55 % demand surge when bike fees drop to zero, the article estimates that a thirty‑percent fare increase will reduce overall ridership by roughly ten percent, primarily among marginal, short‑trip users.
Membership cards as a second‑layer strategy
While raising per‑ride fees, the three operators simultaneously promote monthly passes. As the per‑ride price climbs, the breakeven point for a pass lowers, encouraging more users to purchase a card. Once a user holds a card, marginal ride cost becomes near zero, and the switching cost to another platform rises, effectively locking the user in.
Historical perspective and regulatory context
Before 2017, the market was in a growth phase; firms could only gain share by subsidizing rides, leading to near‑free or heavily discounted prices. When the market shifted to a saturated stock, the equilibrium moved from price wars to tacit price increases. Shared bikes occupy a "semi‑public" role: they enjoy private pricing freedom but use public road space, unlike buses that require governmental price approval.
According to the Chinese Bicycle Association (2025), the average ride is 2.7 km and lasts about ten minutes, meaning the extra half‑hour offered in the new pricing scheme is rarely used by the majority of short‑trip users.
Future outlook
Further price hikes are possible but limited by several factors: abundant substitutes (walking, public transit, e‑bikes), limited user price elasticity, and regulatory constraints on a semi‑public service. The next competitive battleground will likely focus on operational details—fleet dispatch, bike condition, and dispute handling—rather than pure price competition, as the pricing lever has largely reached its ceiling.
Key takeaway: The price increase is a rational response to a saturated, homogeneous market with constrained supply, and while overall demand remains relatively inelastic, the lowest‑frequency, shortest‑distance riders are the most vulnerable to churn.
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