Strategic Offerings of Return Freight Insurance by Insurers in Monopolistic and Duopolistic Markets

With the rapid development of e-commerce, Return Freight Insurance (RFI) has emerged as a vital tool for retailers and customers to mitigate the financial burden posed by high return rates in online shopping. This paper investigates the strategic decision-making of RFI providers (insurers), examining whether they should offer fixed-compensation insurance at a lower price or full-coverage insurance at a higher price under varying market conditions. Specifically, we develop game-theoretic models to analyze insurers’ strategic decisions in both monopoly and duopoly markets, accounting for customer return cost and product mismatch probability heterogeneity. Our findings reveal that in a monopoly market, when customer return costs are relatively low and concentrated, insurers benefit from offering fixed compensation insurance (i.e., pre-set reimbursement amounts) at a lower price to attract a broader customer base. By contrast, when return costs are more dispersed and higher, full-coverage insurance (which reimburses actual freight costs) becomes more profitable, as the insurer can utilize its flexible pricing power to attract higher-paying customer segments. In a duopoly market, customer return cost heterogeneity significantly influences market equilibrium. When heterogeneity is high, full-coverage insurance dominates, as insurers can leverage precise market segmentation to justify higher premiums. Conversely, when return costs are more uniform, fixed compensation insurance is preferred for its affordability, appealing to a wider range of customers.

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Publication Details

Journal
Mathematics
Published
2025-06-02
DOI
https://doi.org/10.3390/math13111855
Primary Topic
Urban and Freight Transport Logistics
Type
article
Field-Weighted Citation Impact
0.00

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article

Strategic Offerings of Return Freight Insurance by Insurers in Monopolistic and Duopolistic Markets

Lucheng Huang, J. J. Qin, Yan Chen
Mathematics
Urban and Freight Transport Logistics
article

Strategic Offerings of Return Freight Insurance by Insurers in Monopolistic and Duopolistic Markets

Lucheng Huang, J. J. Qin, Yan Chen
article en

Abstract

With the rapid development of e-commerce, Return Freight Insurance (RFI) has emerged as a vital tool for retailers and customers to mitigate the financial burden posed by high return rates in online shopping. This paper investigates the strategic decision-making of RFI providers (insurers), examining whether they should offer fixed-compensation insurance at a lower price or full-coverage insurance at a higher price under varying market conditions. Specifically, we develop game-theoretic models to analyze insurers’ strategic decisions in both monopoly and duopoly markets, accounting for customer return cost and product mismatch probability heterogeneity. Our findings reveal that in a monopoly market, when customer return costs are relatively low and concentrated, insurers benefit from offering fixed compensation insurance (i.e., pre-set reimbursement amounts) at a lower price to attract a broader customer base. By contrast, when return costs are more dispersed and higher, full-coverage insurance (which reimburses actual freight costs) becomes more profitable, as the insurer can utilize its flexible pricing power to attract higher-paying customer segments. In a duopoly market, customer return cost heterogeneity significantly influences market equilibrium. When heterogeneity is high, full-coverage insurance dominates, as insurers can leverage precise market segmentation to justify higher premiums. Conversely, when return costs are more uniform, fixed compensation insurance is preferred for its affordability, appealing to a wider range of customers.

MathematicsVol. 13(11)
Macau University of Science and Technology (MO)
Macau University of Science and Technology
Openalex Percentile: Top 88%
Urban and Freight Transport Logistics
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Strategic Offerings of Return Freight Insurance by Insurers in Monopolistic and Duopolistic Markets — Lucheng Huang, J. J. Qin, et al. · Mathematics (2025) | TGRS Research Map | TGRS