Growth in environmental sustainability has prompted the logistics industry to seek sustainable development, and carbon tax policies are considered an effective approach to reducing carbon emissions. This study investigates the optimization of sustainable transportation and inventory under a carbon tax policy and explores effective methods for coordinating the interests of governments and enterprises. The results can provide insights into sustainable logistics for decision-making by enterprises and policy-making by governments. We first examine a Stackelberg game model and design an iterative solution to optimize sustainable transportation and inventory under the carbon tax policy. We then establish a three-stage dynamic game model to optimize the wholesale price, carbon tax rate, and proportion of sustainable investment shared by the government. Furthermore, we perform a simulation to identify the optimal solution of the three-stage game, and we compare the simulation results with a numerical example. The results indicate that a carbon tax policy can improve social welfare and the sustainability of transportation and inventory but could hinder corporate profits. An appropriate sustainable investment-sharing strategy could compensate for the shortcomings of the carbon tax policy and result in positive outcomes for governments and enterprises.
Carbon policies and consumer environmental consciousness are effective motivators that drive enterprises to adopt sustainability technology. To provide enterprises insights into sustainable investment and inventory-transportation decision-making and governments insights into policy-making, this study investigates integrated inventory-transportation scheduling considering consumer environmental consciousness and sustainability technology under carbon cap, tax, and cap-and-trade policies. We first examined sustainability that extends the economic order quantity (EOQ) models, simultaneously taking into account the comprehensive emission model, consumer environmental consciousness, and carbon policies. We then optimized the sustainability level and EOQ using the simulation method. Furthermore, we performed a regression analysis on the carbon policy effects on sustainability level, profit, and emission. Moreover, using the regression models, we estimated and discussed the optimal policy parameters from the perspective of social welfare maximization. The results indicate that the carbon cap-and-trade policy is superior to carbon cap and tax policies. Under carbon cap and tax policies, the tougher the carbon policy, the higher the sustainability level and the lower the profit and carbon emission. Meanwhile, under the carbon cap-and-trade policy, the carbon trading price is the decisive factor that affects the sustainability level, enterprises’ profit, and carbon emission; the carbon cap has a positive regulatory effect on profit.
We explored how donation relates to patient satisfaction with the quality of process and outcome in an online healthcare service. Using a dataset of 496,723 patient consultation records collected from ChunyuDoctor, which is among the largest of the Chinese mobile healthcare applications,
we conducted a multiple regression and found that patient satisfaction with both process and outcome jointly influenced their donation. We also found that higher quality satisfaction levels meant paying patients were more likely to donate than were free patients. Our results also showed satisfaction
with the quality of the process and the outcome had an equal impact on patient donation for the free patients, but the impact of process quality was greater than that of outcome quality for the paying patients, suggesting the importance of enhancing the quality of the process in an online
healthcare service. Implications of the findings are discussed.
As a major cause of global warming, carbon emissions have become a considerable concern in society. In this paper, the authors examine logistics network design considering the carbon emission reduction preferences of decision-makers. To investigate the effects of carbon reduction preferences on carbon emissions, the authors first develop two optimization models with the objectives of optimizing carbon emissions and operation costs, respectively. Subsequently, the authors analyze the effects of the emission reduction preferences of decision-makers on logistics network design at both the strategic and tactical levels. Moreover, the authors propose coordination mechanisms for carbon emissions and operation costs in logistics network design. The results indicate that emission reduction preferences significantly affect carbon emissions and operation costs in logistics network design, especially at the strategic level.
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