The impact of human capital on green economic efficiency: evidence from 280 prefectural cities in China.

Balancing economic growth with resources and the environment to achieve sustainable development is a key issue in the development of all countries, and researchers are trying to find feasible development paths. The aim of this study is to examine the impact of human capital levels on green economic efficiency (GEE) and the underlying mechanisms in 280 prefecture-level cities in China and covering the 2003-2019 period. In addition, we calculate GEE including undesired outputs based on a super-efficiency slack-based measure (SBM) model, and we construct panel regression and moderating effect models for empirical studies. The results of the baseline regression study show that the improvement in the human capital level contributes to the GEE of prefecture-level cities. Among the control variables, the economic development level, foreign direct investment (FDI), city size, and the science and technology innovation (STI) level positively affect GEE, while industrialization and environmental regulation negatively affect GEE. The study results concerning the mechanism of action indicate that industrial structure upgrading plays a positive moderating role. That is, industrial structure upgrading can strengthen the effect of human capital on GEE, which is further clarified. This study suggests that government policies must favor the cultivation of high-level human capital, especially in the environmental protection industry, and that talent support strategies should be differentiated between regions to promote industrial structure upgrading and human capital matching through green technology development. Modern human capital theory reveals the important role of human capital in improving economic efficiency and provides new ideas for achieving sustainable development. This paper explores the role of human capital in improving the GEE based on the human capital perspective, which is important for research on the pathways to achieve sustainable development.

The Spatial Spillover Effect of Clean Energy Development on Economic Development: A Case of Theoretical and Empirical Analyses from China.

Does clean energy development (CED) have a spatial spillover effect on economic growth (EG)? Using the panel data of 30 provincial administrative units from 2000 to 2019 in China, this study empirically investigates the spatial spillover effect of CED on EG. From the perspective of the supply side rather than the consumption side, using the spatial Durbin model (SDM), the study finds that CED does not have a significant impact on EG, while there is an apparent positive spillover effect of CED on EG in China, meaning that CED in one province can boost EG in the surrounding provinces. Theoretically, this paper provides a new perspective for studying the relationship between CED and EG. In practice, it provides a reference for further improving the government's future energy policy.

Does Clean Energy Use Have Threshold Effects on Economic Development? A Case of Theoretical and Empirical Analyses from China.

Increasingly serious energy security and environmental problems have become the main constraints to China's economic development. Therefore, it is critical to explore the threshold effect of clean energy use on China's economic growth. Based on the panel data of 30 Chinese provinces from 2000 to 2019 and using energy intensity (EI) as the threshold variable, this study adopts a panel threshold model to explore the threshold effect of clean energy development on the economy. Empirical results indicate that clean energy has a significant threshold effect on economic development, with the threshold value of EI being 0.7655. When EI is less than 0.7655, clean energy development has a more positive effect on economic growth. When the EI exceeds 0.7655, the impact is significantly positive but with a smaller coefficient. EI weakens the role of clean energy development in promoting economic growth. After 2015, the EI of most provinces in the sample was below the threshold value, which indicates that in recent years, with the economic cost of developing clean energy decreasing, the role of clean energy development in promoting the economy has become more significant. Therefore, we propose policy implications to better promote the effect of clean energy development in promoting economic growth.

Influence of emotion on purchase intention of electric vehicles: a comparative study of consumers with different income levels.

Promoting electric vehicles (EVs) adoption has become one of the important paths for countries around the world to address climate change and accelerate the transformation of energy system for achieving sustainable development. As one of the important psychological factors, the research on the explanatory power of emotions to EVs purchase intention is still insufficient. This paper collected 400 valid questionnaires all around China. By incorporating emotions and moral norms into the Theory of Planned Behavior (TPB) model, this study used structural equation model to estimate the impact of positive anticipated emotion (PAE), negative anticipated emotion (NAE), and moral norms together with TPB elements on EVs purchase intention. In order to explore the heterogeneity effect of the above factors on EVs purchase intention among consumers of different income groups, we divided the total sample into high-income subsample and low-income subsample according to the household monthly disposable income. We concluded as follows: for the total sample, PAE has the greatest impact on EVs purchase intention, followed by attitude, NAE, and perceived behavioral control (PBC). In particular, the purchase intention of high-income consumers mainly depends on NAE, while the purchase intention of low-income consumers mainly depends on PAE. Additionally, PBC has more significant impact on EVs purchase intention of high-income group. Finally, targeted policy implications are proposed to promote EVs purchase.

Is Green Spread? The Spillover Effect of Community Green Interaction on Related Green Purchase Behavior.

In the era of digital economy and mobile internet, many platforms or brands have built various online or offline green communities to guide customers or fans to engage in green interactions. Obviously, community green interaction can enhance brand emotional value and enhance customer stickiness, but whether community green interaction can further have a spillover effect on related or other green purchase behaviors has become an important topic for the theoretical and practical departments. This paper selects the "Little Bear Fuel Consumption Community" as the research object. Based on the theoretical framework of "Green Interaction-Environmental Emotion-Related Green Purchasing Behavior", this paper examines the spillover effect and impact mechanism of community green interaction on consumers' related green purchasing behavior. This paper uses a structural equation model and bootstrapping method to test the causal relationship between variables. This study lasted for 6 months, and a total of 348 valid questionnaires were collected in this study. We used SPSS 25 and AMOS 24 for data analysis. The results showed that the two dimensions of community green interaction (community green information interaction and community green interpersonal interaction) have a positive spillover effect on consumers' related green purchase behavior; community green interaction can positively spill over to consumers' related green purchase behavior through the psychological path of environmental emotion; community green information interaction and community green interpersonal interaction have positive effects on consumers' positive and negative environmental emotions; positive and negative environmental emotions positively affect consumers' related green purchase behavior; and in the two paths of community green information interaction-related green purchase behavior and community green interpersonal interaction-related green purchase behavior, both positive environmental emotion and negative environmental emotion play a role of partial mediation; product involvement has a negative moderating effect on the path of "community green interaction-environmental emotion". This paper opens the "black box" of the diffusion mechanism of community green interaction and provides a new explanatory framework for the spillover effect of community green interaction on related green purchase behavior.

The Impact of Positive Emotional Appeals on the Green Purchase Behavior.

The practice of green consumption has become a common initiative of the international community. Existing studies have shown that emotional factors have an important impact on consumer behavior, but few scholars in the field of green consumption behavior have explored the relationship between positive emotions and green purchase behavior in specific dimensions. This study creatively put forward two dimensions and four kinds of positive emotional appeals which include the cherishing appeal, the yearning appeal, the proud appeal, and the admiring appeal. Through the conceptual model analysis based on the data, the effects of different four positive emotional appeals on consumers' perceived green value, perceived green responsibility, and green purchase behaviors were confirmed. The results indicated that the four kinds of positive emotional appeals, perceived green value, perceived green responsibility, and green purchase behavior were positively correlated. Perceived green responsibility and perceived green value have significant mediating effect on the relationship between positive emotional appeals and green purchase behaviors. Middle doctrine significantly moderates the relationship between positive emotional appeals (Cherishing VS. Yearning) and perceived green value.

Exploring the spatial pattern of renewable energy technology innovation: evidence from China.

Considering the obvious regional differences in China, research on the drivers for renewable energy technology innovation (RETI) needs to fully consider the spatial factors. Based on the expanded function of knowledge production, which includes the human capital, institutional quality, and industrial scale, and using panel data from 29 provinces during 2006-2017, this study examines the factors promoting RETI by employing spatial regression methods. The results show that RETI presents moderate spatial agglomeration and spatial heterogeneity. Human capital, enterprise R&D intensity, and research institution R&D intensity have a significant driving effect on the local RETI, and the university R&D intensity, institutional quality, and industrial scale have no significant contribution. Human capital is the most important factor driving the local RETI, and enterprise R&D intensity has the strongest spatial spillover effect on the RETI of the surrounding provinces. In addition, the R&D intensity of enterprises and research institutions can enhance the local RETI and also significantly promote RETI in surrounding provinces through the spatial spillover effect. In contrast, human capital has played a significant driving role in the local RETI, whereas its spatial spillover effect on the surrounding provinces is not obvious. Therefore, the direct and spatial spillover effects of enterprise R&D intensity and research institution R&D intensity should be fully considered in policy making. In addition, effective policies should be formulated to break the block division of human capital investment and to promote the optimized allocation of talented people in order to better promote RETI in China.

Greenhouse Gas Emission Transfer of Inter-Provincial Electricity Trade in China.

Inter-regional electricity trade is an important way to mitigate the imbalance between regional electricity generation and consumption. With the increasing amount of inter-regional electricity trade in China, the emission transfer problem is more severe. By using Quasi-Input-Output model, which can consider the ripple effect of electricity trade network, this study analyzed embodied greenhouse gas emissions of electricity trade among 30 provinces in China. Results indicated that, in 2017, the national transfer volumes of CO2, CH4, and N2O embodied in inter-provincial electricity trade were 603.25 Mt, 6803.81 t, and 9899.25 t, respectively. Emissions are mainly transferred from the eastern to the western regions, especially to those with high proportion of electricity generated from fossil fuels. The amount of emission transfer is not consistent with that of purchased electricity, since some regions are rich in clean energy. Although direct emission transfer plays the dominant role for most province, indirect emission transfer should also be noticed. Provinces with larger indirect emission transfer generally purchase electricity from provinces with a lot of electricity inflows. The findings could help policy makers coordinate regional energy utilization strategies and issue more effective emission reduction policies in the electricity industry.

Public Preference for Electric Vehicle Incentive Policies in China: A Conjoint Analysis.

In order to mitigate energy consumption and greenhouse gas emission in the transportation sector, countries around the world have generally adopted electric vehicles (EVs) as a new development direction of the automobile industry. Although the Chinese government has issued a series of incentive policies to promote EVs, the ownership of EVs is still insufficient due to low public purchasing enthusiasm. Thus, to better realize the promotion goal of EVs, public preference for EV incentive policies is worth investigating. Based on a large sample survey (N = 1039), this study investigated public preference for various incentive policies by using the conjoint analysis method. The results suggest that less than one third of consumers have a better understanding of the incentive policies, while more than half of the consumers know little about these policies. For consumers, the relative importance of different policy categories is ranked as follows: charging incentive policies, driving incentive policies, vehicle registering incentive policies, and purchasing incentive policies. As for different socio-demographic groups, consumers aged 26-30 years, with a monthly income higher than RMB 20,000, with high school, special secondary school, and masters (or above) educational levels regarded the relative importance of driving incentive policies as the highest; consumers from two-member families ranked purchasing incentive policies as the first one; consumers with a monthly income of RMB 15,001-20,000 and those from three-member families place registering incentive policies first; other consumers put charging incentive policies first. Based on the above results, this paper offers policy recommendations for improving consumer knowledge level of incentive policies as well as full consideration of their policy demands.