Dynamic Pricing Strategy in the Sharing Economy: Principles, Benefits, and Applications

1. What is Dynamic Pricing Strategy

In this article, dynamic pricing strategy is discussed exclusively within the context of the sharing economy.

After Uber introduced and applied dynamic pricing, market validation has allowed us to revisit its origin, development, advantages, disadvantages, and applications.

Dynamic pricing does not have a strict definition, but it reflects the core economic concept of supply‑demand equilibrium.

Thus a simple definition is: in a given market environment, price adjustments are made by supply and demand sides to reach a balance point.

Dynamic pricing is not a new concept; the addition of algorithms, intelligence, and big data makes it appear novel, yet it is widely used in everyday life and affects everyone.

A simple example: during the Chinese New Year, vegetable prices rise because supply drops; in an internet‑enabled market, such changes happen faster and more agile.

2. Why Use Dynamic Pricing Strategy

Every method or technology is created to solve a specific problem; when developing a product, we must consider solutions and select the optimal one.

From Uber’s perspective, the problem is driver shortage during peaks or adverse weather, leading to passengers being unable to get a ride.

Free market, ignore the issue.

Purchase vehicles and hire drivers.

Sign agreements with individual drivers or other transport providers to obtain capacity.

Use scheduling strategies to mobilize drivers on the platform.

The first three options are either unrealistic or conflict with Uber’s C2C sharing‑economy model, leaving scheduling as the viable solution.

Scheduling can be broken down into several concrete actions:

Notify passengers during peaks that no cars are available and suggest alternative transport or waiting.

Notify drivers that a high‑demand area needs service, offering rewards or penalties.

Allow passengers to increase their fare to attract drivers.

The first option does not solve the problem; the second introduces incentives but may cause poor experience or increased costs; Uber chose the third option—asking passengers to pay more, which is the basic form of dynamic pricing.

3. Economic Foundations of Dynamic Pricing

Dynamic pricing is feasible because it aligns with core economic principles, such as people responding to incentives.

A simple model shows supply (drivers) increasing with higher prices (yellow line) and demand (passengers) decreasing with higher prices (green line).

Assumptions:

The normal price between points M1 and M2 is 40 yuan, achieving equilibrium A.

Bad weather reduces drivers, shifting the supply curve upward; price rises to reach a new equilibrium A1, with some passengers dropping out.

During holidays, passenger demand rises; higher prices attract more drivers, reaching equilibrium A2.

When both driver shortage and demand surge occur, the intersection of the two shifted curves yields a new equilibrium, reflecting more drivers joining and some passengers abandoning the service.

These dynamics illustrate the supply‑demand core, and when platform subsidies, commissions, or rewards are added, the curves become more complex, potentially causing inefficiencies.

4. Advantages and Disadvantages

With theoretical support, we evaluate the pros and cons.

Advantages

The platform automatically adjusts via technology, maximizing driver participation and order fulfillment.

Informed users may shift travel times to avoid peaks, creating smoother demand.

Self‑scheduling reduces platform operational costs, as each participant contributes to system efficiency.

Disadvantages

Higher prices cause some users to switch to alternative transport, leading to user churn.

The solution cannot guarantee every passenger gets a ride; it is not a perfect approach.

5. Applicable Cases

Typical scenarios where dynamic pricing can be applied include:

1. Shared Bicycles

Most shared‑bike operators own the assets (B2C) and do not fit the C2C sharing model discussed.

2. Express Delivery and Errand Platforms

Platforms like Renren Express, campus‑based DaDa, and Dada operate with C2C supply and demand, making them suitable for dynamic pricing. For example, a campus platform may start with a base price of around 3 yuan and adjust based on local supply‑demand.

3. Crowdsourcing Task Platforms

Platforms such as Zhubajie and MaShi currently use bidding; dynamic pricing could be layered on top, though factors like team experience and ability also influence pricing.

6. Conclusion

Dynamic pricing embodies the intersection of technology and economics, offering a solution to real‑world problems. By continuously refining the strategy, markets can become more rational and balanced.