Impact of green loan concessions on manufacturer's product line strategy selection
Yanhong Si et al.
Abstract
We study the interaction between a bank and a capital‐constrained manufacturer in a Stackelberg framework, where the bank sets green credit concessions, and the manufacturer chooses its product line strategy. The manufacturer can either produce only green products (Strategy G) or offer both green and nongreen products with low/high nongreen price (Strategy L/H). Consumers differ in their willingness to pay for environmental responsibility () and perceive quality differences () between products. We develop analytical models to characterize the bank's lending decisions, the manufacturer's optimal pricing and product line strategies, and the resulting impacts on profits, environmental outcomes, and social welfare. Our results show that green credit concessions consistently increase green demand and the manufacturer's profits, but their effects on social welfare and environmental performance depend on the chosen strategy and key parameters such as green market size () and environmental impact discount (). With green credit concessions, Strategy L consistently reduces environmental impact while Strategy H does so when is low. When is low, strategies L and H can improve social welfare, while Strategy G does so with lower or moderate . Without concessions, the manufacturer prefers Strategy L or H when is small or moderate and shifts to Strategy G only when or is high. With concessions, the reduced capital cost expands the region where Strategy G is optimal, even with lower . These insights offer manufacturers clear strategic criteria for selecting optimal product line strategies under green financing, and guide banks in setting loan terms to align profitability with sustainability goals.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.