Additional energy demand is needed to accomplish the mega-projects of the Belt & Road Initiative (BRI). As energy consumption is one of the prime determinants of environmental degradation, the present study investigates the impact of energy inequalities on environmental degradation along with financial development. The entropy approach is applied to quantify the three energy consumption inequalities; average, between, and total energy consumption inequality respectively. The energy consumption inequality of BRI economies follows an uprising temporal trend. The estimates reveal that East Asia and South Asia have the highest and lowest energy consumption inequality among the BRI regions. Within regions, it is found that Central Asia has the lowest, and East Asia has the highest energy inequality among the BRI regions, respectively. Based on bootstrapping, the generalized least square (GLS) is applied to quantify the impact of energy consumption inequalities on environmental degradation along financial development. The energy inequalities have a statistically positive impact on environmental degradation in BRI regions, East Asia, Central Asia, the Middle East and North African region (MENA), and Southeast Asia respectively. In contrast, South Asian economies are sustaining environmental quality despite the energy consumption inequalities. Financial development also has a significantly major impact on environmental degradation in BRI, and its regions except for Central Asia, and MENA.

The agriculture sector has a 21 percent share in global CO2 emission. It is contributing the 40 percent share in the gross domestic product of OBORI (One Belt and One Road Initiative) economies. Therefore, the present work intends to evaluate the role of agriculture and forest on environmental degradation from 1980 to 2017 for OBORI economies. The cross-sectional dependence, and order of integration are checked by cross-sectional dependence and second-generation panel unit roots tests respectively. Afterwards, the Wester-Lund co-integration test infers the existence of co-integration between under-considered variables for OBORI region. The empirical results from Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) suggest that agriculture and energy demand cause to upsurge the environmental degradation. While, the forest is improving the environment quality. The authorities may consider the efficient energy utilizing, and eco-friendly techniques to overcome the deteriorating effects of energy usage and agriculture on environment respectively. The heterogeneous panel causality test infers a bidirectional causality between environmental degradation, finance, agriculture, and energy demand respectively.

Since the actual factors in the instant distribution service scenario are not considered enough in the existing distribution route optimization, a route optimization model of the instant distribution system based on customer time satisfaction is proposed. The actual factors in instant distribution, such as the soft time window, the pay-to-order mechanism, the time for the merchant to prepare goods before delivery, and the deliveryman’s order combining, were incorporated in the model. A multi-objective optimization framework based on the total cost function and time satisfaction of the customer was established. Dual-layer chromosome coding based on the deliveryman-to-node mapping and the access order was conducted, and the nondominated sorting genetic algorithm version II (NSGA-II) was used to solve the problem. According to the numerical results, when time satisfaction of the customer was considered in the instant distribution routing problem, the customer satisfaction increased effectively and the balance between customer satisfaction and delivery cost in the means of Pareto optimization were obtained, with a minor increase in the delivery cost, while the number of deliverymen slightly increased to meet the on-time delivery needs of customers.

Under the new situation of economic development in China, the logistics industry is facing unbalanced development regarding economic and environmental performance. From the enterprise level, this study investigated the sustainability of Chinese logistics based on the environmental assessment data envelopment analysis (DEA) model, and measured the unified efficiency of a logistics company under two different production arrangement strategies. The empirical measurement provides several findings. First, logistics enterprises give higher priority to operational benefits than environmental performance. Second, under the operational priority of production arrangement, small and medium-sized enterprises’ (SMEs) unified efficiency is better than a large enterprise, and private enterprises’ unified efficiency is better than state-owned enterprises. Moreover, the empirical study has further proved that the sustainability development of Chinese logistics is still at the primary stage; when facing trade-offs in the sustainability context, logistics companies still prioritize operational performance first. Therefore, transforming corporate strategy into an environmental sustainable priority and realizing logistics sustainability still has a long way to go, which is the backbone of realizing balanced development of both the economy and environment.