Impact of fuel-efficient technology on automotive and fuel supply chain under government intervention: A case study

Abstract

• Uses stochastic demand for green/non-green cars with known/unknown distribution. • Government intervenes in car supply chain using subsidy taxation and customer loans. • Two-way demand leakage applied for green/non-green cars. • Analyzes impact of fuel-efficient technology on fuel consumption in internal market. Transportation is one of the most influential factors in greenhouse gas emissions and global warming. This paper studies a network with an automotive supply chain that includes one supplier and one manufacturer next to a fuel supply chain consisting of a fuel manufacturer, operating under government intervention. The car manufacturer sells its green and non-green products under the dual-channel system with stochastic demand and demand leakage. To decrease greenhouse gas emissions, the car manufacturer invests in fuel-efficient technology for green products to reduce car fuel consumption. Moreover, due to increasing public awareness of environmental issues, the supplier invests in greening efforts to provide raw materials for fuel-efficient cars. The fuel manufacturer determines the fuel price under the government supervision and the government considers subsidies to support it. The fuel manufacturer has the opportunity to export the surplus fuel to other markets at a higher price. The government supports the production of fuel-efficient cars with two policies of subsidy-taxation and granting loans to customers. By doing so, the car manufacturer improves the level of fuel-efficient technology and the greening efforts of the supplier are increased. Additionally, the amount of fuel consumption in the internal market is reduced and the fuel manufacturer can export more fuel to the external market. As a result, the profit of all members increases simultaneously and environmental conditions improve. This model is studied under two scenarios for the distribution function of stochastic part of demand: (1) the Stackelberg scenario with complete information as a uniform distribution function and (2) the Nash scenario with partial information on a distribution-free approach. Some numerical examples based on real cases are provided to examine the capability of the proposed models. Finally, some sensitivity analyses are applied to the main parameters to extract several in-depth managerial concepts.