Offering subsidies to logistics providers and consignors

Abstract

Firms aim to achieve time-based competitiveness to reach their target market sooner and better to meet consumers’ changing demands and cater to rapidly changing markets. One efficient approach is to speed up logistics performance. To generate positive social externality in social welfare, the government can provide subsidies to faster—but also higher cost—logistics providers and encourage customers to choose these providers. This study examines the influence of government subsidies to railway logistics providers and consignors on market equilibrium. We find that subsidization affects the price, demand, and profits of logistics providers. However, the impact on demand and profits remains the same regardless of whether the subsidy is provided to the railway logistics provider or railway consignor. These results are consistent whether the transportation cost is subject to economics of scale or not. The profit of each logistics provider has a concave relationship with its own transportation time but a convex relationship with its competitor’s transportation time. The key factors that determine the optimal subsidy and its impact on social welfare include the unit operational cost of the railway logistics provider and the logistics provider's time-based differentiation and time values of consignors. In addition, the government provides the highest unit subsidy when the railway logistic provider optimizes its profit at the optimal transportation time. When customer demand is stochastic, we find both the fluctuation level of customers’ demand and the logistics providers’ risk attitude influence the government’s optimal subsidy amount. Providing an optimal subsidy helps to efficiently guide the competitive market and enhance social welfare.

Keywords:

• Subsidization
• logistics service provider
• time-based competitiveness
• social welfare

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is supported by NSF of China No: NSFC (71872051, 71472049, 71531005, 71629001, 91746302).