Abstract
Fierce competition and the mandate for green development have driven cold chain logistics companies to minimize total distribution costs and carbon emissions to gain a competitive advantage and achieve sustainable development. However, the cold chain logistics literature considers carbon trading mechanisms in sharing economy, namely the joint distribution, is limited. Our research builds a Joint Distribution-Green Vehicle Routing Problem (JD-GVRP) model, in which cold chain logistics companies collaborate among each other to deliver cold chain commodities by considering carbon tax policy. Based on the real business data from four cold chain companies and 28 customers, a simulated annealing (SA) algorithm is applied to optimize the model. The results indicate that joint distribution is an effective way to reduce total costs and carbon emissions when compared with the single distribution. The total cost is positively correlated with the carbon price, while the carbon emissions vary differently when the carbon price increases. In addition, carbon quotas have no effect on the delivery path. This research expands cold chain logistics literature by linking it with joint distribution and carbon trading mechanisms. Moreover, this research suggests that cold chain logistics companies could enhance delivery efficiency, reduce the business cost, and improve competitiveness by reinforcing the collaboration at the industry level. Furthermore, the government should advocate the mode of joint distribution and formulate an effective carbon trading policy to better utilize social and industrial resources to achieve the balanced economic and environmental benefits.