The development modes of inland ports: theoretical models and the Chinese cases

ABSTRACT

This paper examines the development modes of inland ports based on the economic models and the Chinese empirical cases. After reviewing the recent policies in China, four modes, i.e., the government-driven mode, the seaport-driven, the market-driven mode and the corridor-effect mode, are established to describe the development of Chinese inland ports from the perspective of the driving forces. Moreover, we setup an economic model to compare them and conclude that (1) the seaport-driven mode promotes the larger inland port than the corridor-effect mode and the market-driven mode; (2) if the marginal capacity investment cost is low or the efficiency of the inland port is high enough, the corridor-effect mode leads to higher social welfare than the market-driven mode and the seaport-driven mode; (3) whether the government-driven mode promotes the larger inland port and higher social welfare than the other modes depends on the positive externality from the inland port to the social welfare; (4) The ‘Go west’ policy and the Belt and Road Initiative (B&R) promote the inland port capacity under all modes. Whether the Free Trade Zone (FTZ) and the port integration promote the inland port capacity depends on the port efficiency improvement after the implementation of these policies.

KEYWORDS:

• Inland port
• development mode
• B&R
• FTZ
• port integration
• economic model

Acknowledgments

The authors would like to thank the anonymous referees and the editor for their very helpful comments and suggestions.

Disclosure statement

Author Shiyuan Zheng declares that he has no conflict of interest. Author Qiang Zhang declares that he has no conflict of interest. Author Wouter Beelaerts van Blokland declares that he has no conflict of interest. Author Rudy R. Negenborn declares that he has no conflict of interest.

Notes

1. There are many terminologies in the literature with the similar meanings as inland port, e.g., dry port, inland terminal. In this paper, we use the definition proposed in the review paper by (Witte, Wiegment, and Ng 2019) and uniformly use the ‘inland port’ to represent all these facilities.

2. The 1000^th CRE (train X8024) was launched on May 13^th, 2017, from Yiwu to Madrid.

3. This policy is mainly used in the FTZs now and will be promoted to all Chinese customs in 2020. See http://www.bjkab.gov.cn/myDoInfo/front/article/1482114117424777.html.

4. Some studies provide the similar statements as ours. E.g., in the review paper of Wan, Zhang, and Li (2018), they summarize the impacts of the FTZ and the increase of the efficiency in inspection and customs clearance on a port’s inland terminal. They point out that these policies have the equivalent effects as the increase in the corridor capacity, which can increase the inland port efficiency finally.

5. Other papers, e.g., Alvarez-SanJaime et al. (2015), also discuss the similar issue. They point out that the integration of a seaport and an inland transporter may cause the congestion in the seaport to increase and thereby reduce its efficiency. However, their definition of integration (the integration of a seaport and an inland transporter) is different with ours (the integration of a seaport and an inland port). Moreover, the reasons are different. In Alvarez-SanJaime et al. (2015), the seaport undertakes a vertical integration pricing strategy (i.e., letting the per unit distance price in the inland transport be 0) to increases its throughput, which causes more congestion and lower efficiency. Note that the lower efficiency in their paper is caused by the increase of the port throughput and the marginal congestion cost is unchanged. In our paper, the improvement of the inland port efficiency is caused by the reduction of the marginal congestion cost because of the port integration policies. Therefore, the conclusion in Alvarez-SanJaime et al. (2015) is not contradictory with our analysis.

6. In (3), the term ${\theta }_{C}q/K_C$ and the term ${\theta }_{I}q/K_I$ are the cargo delay costs in the coastal port and inland port, respectively. The delay cost should be positive, which leads to ${\theta }_C$ and ${\theta }_I$ being positive.

7. The linear demand function is obtained from the utility-maximizing behavior consumers (or port users here) with quadratic additively separable utility function, which is commonly used in economics (Singh and Vives 1984). Moreover, it enables us to obtain the closed form solutions which are easy to analyze. The form of the delay costs in (3) can satisfy the basic properties of the delay costs (Wan, Zhang, and Li 2018) and easy to solve.

8. In our model, each player’s decision variable is his charge. If the marginal operation costs of the seaport and the inland port are considered, we only need to add them to the optimal charges of each decision makers. Thus, their constant marginal operation costs have no substantial impacts on the results.

9. The detailed derivation process and the proofs of the following propositions and corollaries are presented in Appendix.

Additional information

Funding

This work was supported by Chinese Ministry of Education (MOE) Project of Humanities and Social Sciences [grant number: 18YJCZH255], and National Science Foundation of China [grant number: 71774109, 71704103].