Welcome to Francis Academic Press

International Journal of Frontiers in Sociology, 2025, 7(8); doi: 10.25236/IJFS.2025.070802.

Exploration of Legal Issues and Improvement Paths of Logistics Insurance Contracts

Author(s)

Haipeng Mo1, Shurui Xiao1, Anqiong Tan2, Xiaodong Wu2

Corresponding Author:
Haipeng Mo
Affiliation(s)

1Hainan Vocational University of Science and Technology, Haikou, China, 571126

2Sichuan Jindui Law Firm, Chengdu, Sichuan Province, China, 610213

Abstract

The vigorous development of the modern logistics industry has increasingly highlighted the importance of logistics insurance contracts. However, their unique compound characteristics have also given rise to a series of challenges in legal application. This paper aims to systematically analyze the core legal issues faced by logistics insurance contracts, mainly including the ambiguity of contract nature and legal application rules, the complexity of the determination of insurable interest and the insured subject, as well as the lack of fairness caused by standard clauses. In response to these issues, the study proposes corresponding paths for legal improvement, specifically including clarifying their legal positioning and application rules, innovating the mechanisms for determining insurable interest and the subject, and standardizing the content and interpretation principles of standard clauses. By exploring these paths, it is expected to provide theoretical reference and practical guidance for promoting the standardization and healthy development of the logistics insurance market.

Keywords

Logistics; Insurance Contract; Legal Issues; Improvement Paths

Cite This Paper

Haipeng Mo, Shurui Xiao, Anqiong Tan, Xiaodong Wu. Exploration of Legal Issues and Improvement Paths of Logistics Insurance Contracts. International Journal of Frontiers in Sociology (2025), Vol. 7, Issue 8: 12-17. https://doi.org/10.25236/IJFS.2025.070802.

References

[1] Dutta H, Nagesh S, Talluri J, et al. A solution to blockchain smart contract based parametric transport and logistics insurance[J]. IEEE Transactions on Services Computing, 2023, 16(5): 3155-3167.

[2] Azzone M, Barucci E, Moncayo G G, et al. A machine learning model for lapse prediction in life insurance contracts[J]. Expert Systems with Applications, 2022, 191: 116261.

[3] Dewi P, Aulia R N, Taufiqillah R. Customer churn prediction for life insurance using binary logistic regression[J]. Economic Reviews Journal, 2024, 3(3): 2289–2299.

[4] Bajar K, Kamat A, Shanker S, et al. Blockchain technology: a catalyst for reverse logistics of the automobile industry[J]. Smart and Sustainable Built Environment, 2024, 13(1): 133-178.

[5] Ding J F, Weng J H, Chou C C. Assessment of key risk factors in the cold chain logistics operations of container carriers using best worst method[J]. International Journal of Refrigeration, 2023, 153: 116-126.

[6] Banulescu‐Radu D, Yankol‐Schalck M. Practical guideline to efficiently detect insurance fraud in the era of machine learning: A household insurance case[J]. Journal of Risk and Insurance, 2024, 91(4): 867-913.

[7] Doherty E, Mellett S, Norton D, et al. A discrete choice experiment exploring farmer preferences for insurance against extreme weather events[J]. Journal of Environmental Management, 2021, 290: 112607.

[8] Halona I, Sokhatska O, Sokhatskyi O, et al. War as an influencing factor on the logistics management processes of foreign economic activity of enterprises[J]. Review of Economics and Finance, 2023, 21: 661-668.

[9] Yontar E. Challenges, threats and advantages of using blockchain technology in the framework of sustainability of the logistics sector[J]. Turkish Journal of Engineering, 2023, 7(3): 186-195.