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Stackelberg pricing policy in dyadic capital-constrained supply chain considering bank's deposit and loan based on delay payment scheme

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In reality, supply chain member may apply for loan from bank when he \begin{document}$ \backslash $\end{document} she is capital-constrained, or may deposit idle capital to bank when he \begin{document}$ \backslash… Click to show full abstract

In reality, supply chain member may apply for loan from bank when he \begin{document}$ \backslash $\end{document} she is capital-constrained, or may deposit idle capital to bank when he \begin{document}$ \backslash $\end{document} she is well-funded. This study focuses on the Stackelberg pricing policy considering bank's deposit and loan based on delay payment scheme in a dyadic capital-constrained supply chain. First, the market demand is given, and then the profit functions of supply chain members are built. According to Stackelberg game, the four pricing models are constructed for four scenarios. By solving models, optimal pricing policies of supply chain members for each scenario can be determined. Finally, impacts of the interest rate for fixed deposit by installments, deposit rate and loan rate on optimal pricing policies are analyzed. The research results show that, in manufacturer capital-constrained situation, these rates can affect optimal pricing policies and profits; in retailer capital-constrained situation, deposit rate and loan rate have no effect on them, but the interest rate for fixed deposit by installments can still affect them. Our study provides a feasible way for supply chain members in pricing decision considering bank's deposit and loan based on delay payment scheme in a dyadic capital-constrained supply chain, and contributes to the theoretical research on the capital-constrained supply chain management and the management practice for capital-constrained supply chain members with bank' deposit and loan.

Keywords: chain; loan; supply chain; capital constrained

Journal Title: Journal of Industrial and Management Optimization
Year Published: 2020

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