The digital economy is becoming increasingly important in the field of carbon governance. However, there is little literature examining the relationship between the digital economy and clean energy ...development. This paper aims to fill this gap by exploring the relationship between the digital economy and clean energy and its spatial effects. We explored the effects of the digital economy using adouble fixed effects model and a spatial econometric model using 276 cities in China from 2011 to 2019 as the original data. We find that the digital economy can drive clean energy development. Technological innovation and city bank loans play an important mediating role in this. Second, we find that market-driven amplifies the positive effects of the digital economy compared with government intervention, and the effects of the digital economy are different under different regions. Finally, we find that the digital economy can drive clean energy not only in local cities, but also indirectly in neighboring cities. These facts suggest that the digital economy is an important way to drive clean energy development and thus effectively achieve sustainable development. Our study provides new ideas for building digital economy and clean energy development in emerging developing countries such as China.
The entropy-weighting method (EWM) and variation coefficient method (VCM) are two typical diversity-based weighting methods, which are widely used in risk assessment and decision-making for natural ...hazards. However, for the attributes with a specific range of values (RV), the weights calculated by EWM and VCM (abbreviated as
and
) may be irrational. To solve this problem, a new indicator representing the dipartite degree is proposed, which is called the coefficient of dipartite degree (CDD), and the corresponding weighting method is called the dipartite coefficient method (DCM). Firstly, based on a large amount of statistical data, a comparison between the EWM and VCM is carried out. It is found that there is a strong correlation between the weights calculated by the EWM and VCM (abbreviated as
and
); however, in some cases the difference between
and
is big. Especially when the diversity of attributes is high,
may be much larger than
. Then, a comparison of the DCM, EWM and VCM is carried out based on two case studies. The results indicate that DCM is preferred for determining the weights of the attributes with a specific RV, and if the values of attributes are large enough, the EWM and VCM are both available. The EWM is more suitable for distinguishing the alternatives, but prudence is required when the diversity of an attribute is high. Finally, the applications of the diversity-based weighting method in natural hazards are discussed.
Quality of urban environment directly affects people health, and it is important to understand the real-time status of urban air quality. Air quality monitoring, data analysis, and visualization can ...grasp the concentration data of air pollutants in cities. In view of the current air quality monitoring using digital displays, it is difficult for users to intuitively determine the air pollution level with unsatisfied interaction mode of the data query. Using the real-time monitoring data of 23 observation points in Beijing, the work based on Google Earth applied Keyhole Markup Language (KML) for the visualization of air monitoring data. The interactive query makes it easier for users to query air quality, and gradually varied color can visually highlight the air quality level. Visualization of data has stronger expression (more images and more intuitive) than the original data table, which is beneficial for further analysis of data.
Coordinated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a significant improvement of TOPSIS, which take into account the coordination level of attributes in the ...decision-making or assessment. However, in this study, it is found that the existing coordinated TOPSIS has some limitations and problems, which are listed as follows. (1) It is based on modified TOPSIS, not the original TOPSIS. (2) It is inapplicable when using vector normalization. (3) The calculation formulas of the coordination degree are incorrect. (4) The coordination level of attributes is interrelated with the weights. In this paper, the problems of the existing coordinated TOPSIS are explained and revised, and a novel coordinated TOPSIS based on coefficient of variation is proposed to avoid the limitations. Comparisons of the existing, revised, and proposed coordinated TOPSIS are carried out based on two case studies. The comparison results validate the feasibility of the proposed coordinated TOPSIS.
To alleviate the increasingly serious environmental problems, the environmental governance of relevant firms has received widespread attention. In this paper, based on panel data of Chinese listed ...firms from 2010–2019, we use the dynamic panel model to verify the non-linear relationship between internationalization and green innovation performance. The dynamic panel threshold model is also constructed to estimate the threshold effect of subsidies between internationalization and green innovation performance. The results show that there is a “U” relationship between internationalization and green innovation. Subsidies can help firms cross the inflection point earlier, and internationalization positively affects green innovation output only when the subsidy exceeds the threshold (16.994). Considering the heterogeneity issue, our study finds that the subsidy threshold for internationalization is bigger for state-owned, non-coastal enterprises, and enterprises with environmental information disclosure compared to other enterprises. In addition, when across the subsidy threshold, state-owned, non-coastal enterprises, and enterprises without environmental information disclosure are better able to stimulate green innovation output. This provides evidence and policy directions for other emerging developing countries.
•The effects of the entropy weight on TOPSIS are analyzed.•The entropy weight enhances the function of the PA in decision-making or evaluation.•The entropy weight is conducive to increase the ...dipartite degree of the RC.•The entropy weight reduces the comprehensiveness of the RC.•The entropy-based TOPSIS with adjustable weight coefficient is proposed.
The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a classical multi-attribute decision-making method, which is widely used in various fields for decision-making or evaluation. The entropy method (EM) is frequently used in determining attribute weights for TOPSIS, and the weight determined by the EM is always called entropy weight (EW). In this paper, based on a large number of data and theoretical analysis, the effects of the EW on TOPSIS are analyzed. It is found that the EW can enhance the function of the attribute with the highest diversity of attribute data (DAD) as well as weaken the function of the attributes with a low DAD in decision-making or evaluation. Sometimes the EW even causes the decision-making or evaluation result to be seriously affected by the attribute with the highest DAD (called primacy attribute, abbreviated as PA). Since the EW can enhance the function of the PA in decision-making or evaluation, it is conducive to increase the dipartite degree of the relative closeness (RC), but reduces the comprehensiveness of the RC, and may even lead to unreasonable decision-making or evaluation result. In order to adjust the effects of the EW on TOPSIS, the entropy-based TOPSIS with adjustable weight coefficient is proposed in this paper. Some discussions on the application of the proposed method are also given.
•Normalization affects the decision result of the entropy-based TOPSIS method.•Normalization is not necessary for the entropy method.•Vector normalization and sum normalization are applicable for ...TOPSIS method.•It is not appropriate to combine the entropy method and TOPSIS method.
In this paper, the frequently used normalization methods for the entropy method (EM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) when these two methods are used in combination with each other are summarized. Taking information entropy (IE) as an indicator to measure the diversity of attribute data (DAD), the effects of normalization on the entropy-based TOPSIS method are analyzed. It is found that normalization can affect the decision result by affecting the DAD, while the DAD affects the contribution of attributes to the distance of each alternative from the ideal solution and the negative ideal solution, manifested in that the higher the DAD is, the bigger the contribution of the attribute will be. It is proved that vector normalization (VN) and sum normalization (SN) will not change the DAD, whereas min-max normalization (MMN) not only will change the DAD, but also may cause the appearance of numerous zero values, finally resulting in the fact that the calculated results of IE cannot represent the diversity of raw data. Therefore, normalization is not suggested for the EM, and VN is suggested for TOPSIS method. Some discussions on the combinability between the EM and TOPSIS method are also given as well as the applicability of different normalization methods in TOPSIS method.
Tumor cells are characterized as redox-heterogeneous intracellular microenvironment due to the simultaneous overproduction of reactive oxygen species and glutathione. Rational design of ...redox-responsive drug delivery systems is a promising prospect for efficient cancer therapy. Herein, six paclitaxel-citronellol conjugates are synthesized using either thioether bond, disulfide bond, selenoether bond, diselenide bond, carbon bond or carbon-carbon bond as linkages. These prodrugs can self-assemble into uniform nanoparticles with ultrahigh drug-loading capacity. Interestingly, sulfur/selenium/carbon bonds significantly affect the efficiency of prodrug nanoassemblies. The bond angles/dihedral angles impact the self-assembly, stability and pharmacokinetics. The redox-responsivity of sulfur/selenium/carbon bonds has remarkable influence on drug release and cytotoxicity. Moreover, selenoether/diselenide bond possess unique ability to produce reactive oxygen species, which further improve the cytotoxicity of these prodrugs. Our findings give deep insight into the impact of chemical linkages on prodrug nanoassemblies and provide strategies to the rational design of redox-responsive drug delivery systems for cancer therapy.
The unprecedented expansion and development of high-speed rail (HSR) in China provides a unique opportunity and a new way of thinking for addressing the problem of urban-rural wealth disparities. In ...this paper, I examine the impact of the introduction of HSRs on the income disparity between urban and rural residents in China. Using panel data from 285 prefecture-level cities from 2004 to 2018, in this paper I employ the double-difference method to assess the impact of HSR on the income gap between urban and rural populations and the mechanism of its action; furthermore, I explore the influence of HSR on urban residents' per capita disposable income and rural residents' per capita net income, as well as the impact of HSR on the flow of elements such as labor and capital. My research findings reveal that the introduction of HSR has greatly widened the income gap between urban and rural residents; however, there is heterogeneity between different East, Central, and West regions, as well as between different levels of cities. A further mechanism study finds that HSR lowers farmers' per capita net income, raises urban residents' per capita disposable income, and widens the urban/rural income gap via mechanisms such as facilitating the interregional mobility of labor and capital factors. Therefore, it is necessary to comprehensively assess the economic effects brought about by HSR, strengthen the construction of urban-rural transport networks, and improve support for rural areas, so as to promote the coordinated development of inter-regional and urban-rural areas.
Existing digital transformation research has focused on economic and environmental performance, which few studies directly explored the relationship between digital transformation and innovation. ...Based on the innovation factor perspective, we explored the relationship between digital transformation and innovation by using firm data between 2009 and 2019. The findings are as follows: (1) The corporate digital transformation was measured through based on textual analysis methods and it was found that digital transformation can promote corporate innovation. (2) Knowledge flow, technical personnel, R&D investment, and innovation awareness are important mediating paths. (3) In the innovation quantity dimension, the mediating role of innovation awareness is greater. And in the innovation quality dimension, the mediating role of technicians is greater. (4) Digital transformation has a greater impact on innovation of non-SOEs, non-high-tech enterprises and non-heavily polluting enterprises, alleviating the gap between different types of firms. The results of this paper alleviate the concerns of digital transformation in developing countries such as China and provide experiences and evidence for them to promote Industry 4.0 and sustainable innovation.
PDF
