Information Sharing in a Cross-Border E-Commerce Supply Chain Under Tax Uncertainty

ABSTRACT

This study explores the optimal information-sharing strategy in a cross-border e-commerce supply chain with uncertain tax rates, in which an overseas manufacturer invests in product quality and a cross-border e-retailer holds private demand information. By establishing a game-theoretical model, we investigate the e-retailer’s motivation for sharing information with the overseas manufacturer and further explore the role of information sharing under tax uncertainty. Our results show that when quality elasticity is high, the e-retailer chooses to share its information voluntarily. However, under medium quality elasticity, the e-retailer shares information voluntarily only when the probability of the high tax rate is below a certain threshold. Moreover, the e-retailer could be more likely to share information under higher tax uncertainty. When quality elasticity is low, the e-retailer is unwilling to share information, but the overseas manufacturer can design a contract to incentivize the e-retailer to share information to realize a win–win outcome. Finally, we reveal that information sharing can mitigate the negative effect of tax fluctuation on the e-retailer’s profit. These findings provide useful implications for cross-border e-retailers on how to formulate information-sharing strategies under tax uncertainty arising from trade policy adjustment. Our study also supplements the information-sharing literature by discussing tax uncertainty, which is an important factor affecting the operation of cross-border e-commerce supply chain.

KEY WORDS:

• AND PHRASES: Supply chain management
• cross-border e-commerce
• information sharing
• tax uncertainty

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Supplemental data

Supplemental data for this article can be accessed on the publisher’s website

Notes

1. The coefficient of variation of the tax rate $\sigma /\mu =\mathrm{\Delta }\sqrt{\beta \left(1-\beta \right)}/\left(\beta \left(t_L+\mathrm{\Delta }\right)+\left(1-\beta \right)t_L\right)$, which can evaluate the level of tax uncertainty, is monotone increasing in $\mathrm{\Delta }$.

Additional information

Funding

This work is supported by the National Natural Science Foundation of China [grant numbers 72072016 and 71572020].

Notes on contributors

Xumei Zhang

Xumei Zhang ([email protected] corresponding author) is a professor at the School of Economics and Business Administration, Chongqing University, China. Her research interests include e-commerce, supply chain management, and operations management. Her work has been published in European Journal of Operational Research, International Journal of Production Economics, International Journal of Production Research, International Transactions in Operational Research, Applied Mathematical Modelling, Journal of the Operational Research Society, and others. Dr. Zhang’s research has been supported by the National Natural Science Foundation of China and the National Key Research and Development Program.

Xiaoyu Zha

Xiaoyu Zha ([email protected]) is a Ph.D. student of operations management at the School of Economics and Business Administration, Chongqing University, China. Her research interests include electronic commerce and supply chain management.

Haiyue Zhang

Haiyue Zhang ([email protected]) is a researcher at the School of Economics and Management, Chongqing Jiaotong University, China. Her papers have appeared in Electronic Commerce Research and Applications and International Transactions in Operational Research.

Bin Dan

Bin Dan ([email protected]) is a professor at the School of Economics and Business Administration, Chongqing University, China. His research interests include supply chain management, e-commerce, and platform strategy. His publications have appeared in European Journal of Operational Research, International Journal of Production Economics, International Journal of Production Research, Electronic Commerce Research and Applications, Computers & Industrial Engineering, and others. Dr. Dan’s research was supported by the Major Program of the National Social Science Foundation of China.