PurposeThe purpose of this paper is to examine the effects of energy technological innovation on carbon emissions in China from 2001 to 2016.Design/methodology/approachConditional mean (CM) methods are first applied to implement our investigation. Then, considering the tremendous heterogeneity in China, quantile regression is further employed to comprehensively investigate the potential heterogeneous effect between energy technological innovation and carbon emission intensity.FindingsThe results suggest that renewable energy technological innovation has a significantly positive effect on carbon emission intensity in lower quantile areas and a negative effect in higher quantile areas. Contrarily, fossil energy technological innovation exerts a negative correlation with carbon emission intensity in lower quantile areas and a positive effect on carbon emission intensity in higher quantiles areas.Originality/valueConsidering that energy consumption is the main source of CO2 emissions, it is of great importance to study the impact of energy technological innovation on carbon emissions. However, the previous studies mainly focus on the impact of integrated technological innovation on carbon emissions, ignoring the impact of energy technological innovation on carbon emissions mitigation. To fill this gap, we construct an extended STIRPAT model to examine the effects of renewable energy technological innovation and fossil energy technological innovation on carbon emissions in this paper. The results can provide a reference for the government to formulate carbon mitigation policies.

Green energy technology innovation (GETI) is a crucial path to achieve sustainable development. However, few studies have examined the determinants of GETI, especially from the perspective of environmental regulation. To fill this gap, this study investigates the impact of environmental regulation on GETI using the panel data of 30 provinces in Mainland China from 2001 to 2018. We first measure GETI by the latest IPC codes and patent data, and then adopt a dynamic spatial Durbin model (DSDM) to examine the relationship between environmental regulation and GETI. The main conclusions are summarized as follows: (1) There is a significant inverted U-shaped relationship between environmental regulation and GETI; (2) heterogeneity analysis shows that the inverted U-shaped correlation not only exists between environmental regulations and different types of GETI, but also exists between environmental regulations and GETI in different regions. Moreover, the results also show that the spatial spillover effect and path-dependent effect exist in all cases. The findings can provide reference for policymakers to formulate more precise environmental policies. That is, environmental policies in a province should be formulated based on its position on the inverted U-shaped curve. More specifically, when it is on the left side of the inflection point, it is reasonable to strengthen environmental policies, and when it is on the right side of the inflection point, appropriate relaxation of environmental policies should be considered.

The evaluation and selection process can be regarded as a complex multiple criteria decision analysis (MCDA) problem which involves various interaction relationships among criteria under high uncertain environment. In addition, the decision-makers are always bounded rational in the risk decision-making process. However, the current robot evaluation and selection approach seldom considers the decision-maker’s risk preference and interactive criteria under high uncertain environment. Thus, the purpose of this paper is to develop a hybrid MCDA approach for solving the robot evaluation and selection problem. In the proposed framework, the interval type-2 fuzzy set is used to express the uncertain evaluation information provided by decision-makers. Next, the distance measure of interval type-2 fuzzy numbers is developed to determine the fuzzy measure of each criterion. Then, the extended prospect theory based on developed Choquet integral is proposed to evaluate and prioritize the robot by considering the decision-maker’s risk preference and interactive criteria. Finally, a case study of robot evaluation and selection in the auto industry is selected to exemplify the application of the proposed framework. After that, comparison and sensitivity studies are conducted to further demonstrate the robustness, effectiveness, and reasonableness of the developed approach.

How should the public administrative department direct the diffusion of public opinions in a not-in-my-backyard (NIMBY) crisis? This paper first analyzes the macroevolutionary characteristics of the public opinion associated with a NIMBY crisis. We then examine the perceptive interactions among individuals towards NIMBY projects from a microscopic perspective and develop an evolutionary game model (i.e., replicator dynamics) to describe the interactions among individuals. We also use information entropy and dynamic equations to construct an interaction entropy model and a dynamic equation to capture administrative-department-led public opinion. Through examining the existence and stability of the evolutionary equilibrium of these models, we analyze the evolution of NIMBY public opinion.

The characteristics of large-scale constructions, such as multi-agent, multi-stage and multi-target have brought great difficulties to improve the construction's performance.This paper builds a computational experiment model of the incentive mechanism, and simulates the behavioral strategies of all participants by using computational experiment artificial system. The experiment results show that: the incentive mechanism of performance audit can optimize the project's performance to a certain extend; in the single-period audit, the subcontractors are more sensitive to the incentive level, and show a strong risk aversion characteristic; while in the multi period audit, the incentive level lose effectiveness on improving the constructions' performance, it's more critical to take the individual's equity preference into consideration.