Analysis of two financing modes in green supply chains when considering the role of data collection.

Purpose: More and more attention has been paid to the financing of small- and medium-sized enterprises (SMEs) and environmental protection. Many literatures have done detailed research on them; yet, few of them studied the interaction between corporate financing behaviors and environmental concerns. This study aims to incorporate the impact of the role of data collection into the mathematical model to explore the optimal financial and ordering strategies when considering environmental protection. Design/methodology/approach: A Stackelberg game modeling and backward induction methods are used to derive the optimal equilibrium solutions, using numerical experiments to further explore the influences of various financing strategies on the green degree of product and ordering policies. Findings: No matter which financing modes the capital-constrained retailer chooses, both the loan interest rate and order quantity considering environmental protection are larger than that without environmental protection concerns. As the retailer's initial capital increases, the optimal loan interest rates under various financing modes are all decreasing. The application of big data technology would promote the environmental protection of enterprises and increase the accuracy of financing decisions. Originality/value: This paper studies financing activities of a supply chain considering data collection and environmental protection behaviors, which provides meaningful guidance for the financing and environmental decision-making of enterprises. [ABSTRACT FROM AUTHOR]