Evolutionary game analysis and simulation with system dynamics for behavioral strategies of participants in crowd logistics

ABSTRACT

Crowd logistics is believed to be an innovative idea that can solve the dilemma lying in the scattered transportation resources and unstable demands of urban freight transport. However, the negative interactions among the participants have left crowd logistics an unstable development. In order to reveal the interactions, which occur under the bounded rationality and discover influencing factors to participants’ strategy selections, this article develops the system evolutionary game model and system dynamics model. Also, it investigates how tripartite participants respond to the governance policies under static and dynamic scenario. The simulation results show that dynamic scenario has a better performance in restraining strategy fluctuations among the participants. Under the dynamic scenario, the strategy combination of participants eventually converges to the evolutionarily stable strategy. The probability that shippers adopt “price-exploitation” strategy is positively correlated with extra profits while negatively correlated with the upper bond of the penalties. The profits are the key factor affecting the willingness of drivers joining crowd logistics platform (CLP).

KEYWORDS:

• Crowd logistics
• urban freight transport
• evolutionary game theory
• system dynamics

Disclosure statement

The authors declare no conflict of interest.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. In March 2015, the Chinese government unveiled Internet Plus, an action plan expected to push forward the Chinese economy. The plan aims to integrate mobile Internet, cloud computing, big data, and the internet of Things with traditional industries. ‘Internet + Logistics’ means to apply those technologies to logistics industry.

2. The ‘price-exploitation’ behavior of shippers is actually a price-cutting behavior. Most of the platform will offer the recommended prices for shippers based on the transport distance and the size of the vehicle, which weakens the bargaining power of shippers to some extent. However, drivers are still vulnerable to ‘price-exploitation’ from shippers in many ways. For example, the shipper may ask the driver to load and unload the goods for free, not pay subsidies for some dangerous freight, or call a minivan to transport the goods that need a medium truck, etc.

3. For example, CLPs invest fund to adjust the operation in a way that can alleviate the conflict of interest between shippers and drivers, improve the rules and regulations to restrain the improper behavior of users, and constantly update the APP.

4. ‘Join platform’ means that the drivers will stay in current platform. ‘Disengage platform’ means that drivers will join other platforms, work for traditional logistics companies, or work for themselves.