Search

AbstractThis study investigates the correlation between government environmental reporting and tourism development. The former is measured as the percentage of the words in the sentences in which the environmental terms are located in government work reports, which reflects the government’s environmental agenda. The analysis reveals that environmental reporting exerts an inverted U-shaped curve impact on tourism development. Such an impact is mediated by economic pressure and environmental pollution, while the economic level and tourism resource endowment act as moderators. Specifically, economic growth pressure and tourism resource endowment enhance the curve’s steepness and shift the curves’ inflection points to the left and right, respectively. Additionally, the study confirms a spatial spillover effect of environmental reporting on tourism development but with limited economic significance. These findings provide insights into the nonlinear link between environmental reporting and tourism development and offer valuable implications for both theory and practice. [ABSTRACT FROM AUTHOR]

This paper examines the necessary and sufficient influence of the innovation environment, which incorporates various innovation variables, on IGTFP from a configurational standpoint. This paper utilizes fuzzy qualitative comparative analysis and necessary condition analysis methodologies. A total of 11 models are found to be driven by the innovation environment for IGTFP. Technological output is necessary for IGTFP and thus a fundamental factor in various models. The effects of wages and human capital on IGTFP are also relatively significant. Longitudinally, there is no consistent innovation environment-driven model. This paper reveals the intricate associations between the innovation ecosystem and IGTFP while elucidating the mechanism of variable effects on IGTFP influenced by varying spatio-temporal environments, which significantly amplifies current comprehension of the mean effect link between the two. Concurrently, the article furnishes methodological direction for subsequent investigation into the complexity of the relationships between relevant variables. [ABSTRACT FROM AUTHOR]

Abstract This paper examines the various channels through which the tourism ecosystem can affect green development, utilizing a configurational approach to identify underlying mechanisms. Fuzzy-set qualitative comparative analysis and necessary condition analysis are employed. The findings reveal that tourism does not act as either a necessary component or bottleneck to green development. Four models of tourism-driven high green development are identified including migration-based, growth-based, government-led tourism-driven, and government-led non-tourism-driven. Additionally, the causal relationship between tourism and green development is apparent primarily in less economically-developed regions. The study affirms the asymmetric causal impact of tourism on green development and presents a systematic and in-depth understanding of the asymmetric multivariate pathways that tourism can use to promote green development. These findings represent a significant contribution to the current literature and offer new perspectives for the field of sustainable tourism research. [ABSTRACT FROM AUTHOR]

Emissions trading schemes (ETS) area is a leading climate policy instrument worldwide and have been widely discussed and researched. However, few studies to date focus on the nexus of ETS and income inequality, an important socioeconomic phenomenon. To fill this gap, taking China as an example, this paper discusses the influence of ETS on income inequality and its dynamic changes using a time-varying differences-in-difference model combined with a propensity score matching approach. The results demonstrate that China's pilot ETS has contributed to reducing income inequality. Various robustness tests support this conclusion. Moreover, the strength of ETS's contribution to reduction in income inequality gradually increases over time. We further analyze the mediating effects of carbon intensity, energy consumption, industrial structure, and technological innovation. ETS reduces income inequality by reducing coal consumption. The regional heterogeneity analysis shows that, unlike in other regions, ETS has a positive impact on income inequality (i.e. it increases it) in the eastern region in China due to its optimized energy structure and relatively complete, open, and flexible economy system. The paper discusses the above findings and their policy implications. It is also designed to promote research on ETS and to diversify research perspectives of income inequality from both theoretical and practical aspects. Evidence from China's pilot experience with ETS shows that it contributes significantly to balancing income distribution and alleviating the increasingly acute social conflicts caused by income inequality. This provides new theoretical and decision support for the promotion of ETS in the future. The energy revolution driven by ETS promotes income redistribution, which is conducive to income equality. Governments should enforce the constraints of ETS on power generation companies; guide capital to invest more in the non-thermal power industry, especially the renewable energy power sectors; and guide and regulate the income distribution in new power sectors. Governments' revenue from ETS can and should be used to further redistribution of income and to reduce income inequality. A higher number of free quotas and a lower carbon price could be imposed on low-profit or labor-intensive industries to reduce their emission costs. [ABSTRACT FROM AUTHOR]

This article examines the tourism economic dynamics under the carbon intensity target policy with macroeconomic uncertainty. Using a novel multi-sector dynamic stochastic general equilibrium model, this article presents the impulse responses of the tourism economy to productivity shocks and carbon intensity target shocks in terms of output, employment, and consumption. The results show that, generally, productivity shocks have positive effects while carbon intensity target shocks negatively affect the tourism aggregate economy. The reduced carbon intensity target offsets these positive effects as well as enlarging these negative effects. Furthermore, the effects of exogenous shocks vary significantly across tourism sectors. As a whole, tourism-related transport and accommodation sectors are the most affected. In addition, different carbon intensity targets mean the different volatility and persistence of the effects of exogenous shocks. This study contributes to a better understanding of tourism economic dynamics under a specific emissions policy, thereby contributing to relevant decision-making. [ABSTRACT FROM AUTHOR]

This study examined the relationship between government environmental governance (GEG) and regional green development. The findings suggest that GEG boosts green innovation by promoting the "innovation compensation effect" while inhibiting regional green development due to increased environmental costs, supported by the "compliance cost effect". The relationship between GEG and regional green development is moderated by economic development and environmental pollution in an inverted U-shaped pattern. When economic development and environmental pollution are at lesser levels, the positive effect of GEG amplifies as economic growth and environmental pollution ascend. However, if economic growth and environmental pollution continue to escalate, the positive impact of GEG will lose its strength. In low-carbon pilot cities, GEG negatively affects regional green development, whereas the opposite effect is seen in non-pilot cities. Regardless, there is an inverted U-shaped moderating impact of economic development or environmental pollution in both low-carbon pilot and non-pilot cities, yet the inflection point varies across regions. This paper offers an original perspective by creating a theoretical link between green development and environmental governance and emphasizes the significance of a nonlinear viewpoint when examining the relationship between variables in the regional green development process, thereby expanding our understanding of green development phenomena. [ABSTRACT FROM AUTHOR]

This paper examined the economic impacts of China's emissions trading system (ETS), implemented in 2013, in terms of gross domestic product (GDP) and per capita GDP. The methodology drew on a difference-in-differences (DID) method using dynamic panel data for 30 provincial regions. The estimation results show that implementing an ETS policy has statistically significant negative effects on economic growth. When considering the additional control variables, these effects are still statistically significant. Furthermore, these negative impacts increase over time with respect to both GDP and per capita GDP. The counterfactual tests confirm the robustness of our DID estimation results. The specific influence mechanism of China's ETS policy was finally discussed. Our findings provide a quantitative decision-making support for popularizing ETS policy in China. Based on our DID model, empirical investigations of the ETS policy, especially concerning economic growth in other regions would produce prolific contributions to the literature. [ABSTRACT FROM AUTHOR]

Since the beginning of the 21st century, accompanied by the tremendous achievements of China's economic growth is an increasingly severe income gap between the rich and the poor. Based on panel data from 2000 to 2018, this study systematically examined the relationship among transport infrastructure, economic growth, carbon emissions, and income inequality in China, using the panel vector autoregressive model estimated by the generalized method of moments. We further divided China into three regions to investigate the regional heterogeneity of these relationships. The results show a long‐run equilibrium relationship between transport infrastructure, economic growth, carbon emissions, and income inequality. Income inequality in the previous year significantly affects that in the current year positively. Whether at the national or regional level, economic growth affects income inequality negatively. For the national sample, the highway reduces income inequality, while the railway increases income inequality. For both the subsamples and the national sample, carbon emissions significantly increase income inequality and are the Granger test cause for income inequality. Furthermore, we discuss some of the possible mechanisms of these results. Our findings generate policy implications for reducing income inequality in regard to economic growth, transport infrastructure, and carbon emissions. [ABSTRACT FROM AUTHOR]

Prior studies focus mainly on the influence of ETS on energy consumption, carbon emissions, and the economy; however, the effects on energy consumption and output structure still need to be discovered. This study employs a time-varying difference-in-differences approach to test whether China's ETS significantly affects energy structure represented by coal, oil, and natural gas consumption and renewable energy output. The results show that the ETS policy significantly reduced China's coal and oil consumption and increased natural gas consumption and renewable energy output. Besides, the influence of ETS on energy structure becomes increasingly significant over time. The results demonstrate that energy investment mediates the effects of ETS on energy consumption and output structure, and industrial structure mediates the effects on coal and fossil consumption. In addition, as economic development increases, the negative effects of ETS on coal and oil consumption decrease, the positive effect of ETS on natural gas consumption increases, and the positive effect of ETS on renewable energy output decreases. As the share of the secondary sectors increases, the negative effect of ETS on coal and oil consumption decreases, the positive effect of ETS on natural gas consumption decreases, and the contribution of ETS to renewable energy output increases. [ABSTRACT FROM AUTHOR]

In support of an ambitious target to reduce carbon intensity by from 40 to 45 percent by the year 2020, as proposed by numerous leaders around the globe, various industries in China have come to think of carbon emissions reduction as an important part of their overall corporate strategy. As an energy-intense economic sector (Gössling, 2013), tourism is thus expected to play an important role in reducing CO 2 emissions in China. However, low-carbon tourism in most destinations, and especially in newly-emerging tourism destinations, is being neglected to some extent. Examples of this neglect can be found in such areas as China's Chengguan District of Lhasa, which has ambitions to become a world tourism centre. This study develops a fuzzy Delphi-ANP approach to suggest which low-carbon tourism strategy should be adopted in Chengguan District in the coming years. Applying our approach, we find that the priorities of low-carbon tourism strategies in Chengguan District are: first, economic development (0.1965), secondly, environmental construction (0.1593), and finally, social support (0.1442). Specifically, the importance of the indicators for tourism carbon intensity, low-carbon transportation, education regarding a low-carbon environment, carbon sink density and sewage treatment are stressed in this paper, in order to call for the immediate implementation of low-carbon tourism development in Chengguan District. [ABSTRACT FROM AUTHOR]

Although the sustainable development philosophy has been widely recognized, it is still necessary to weigh the economic, environmental and social implications of tourism development. The decision is often difficult involving typically complex multi-criteria decision making problems. This study aims to contribute a theoretical framework and approach for the determination of top priorities in tourism development and making decisions based upon that approach. Taking Xizang as a case, this study explores the means to weigh and realize tourism development goals during the ‘13th Five-Year Plan’ period, using the analytic network process within a goal programming model. Results show that there are 10 criteria and nine decision variables determined in Xizang's sustainable tourism development and the priorities in Xizang's tourism development should be: 1) economic goals, 2) social goals, and 3) environmental goals. In addition, using the analytic network process-goal programming model, this paper provides the solution of the decision problem for two years, namely 2016 and 2020, and discusses the significance of the results. This study concludes that in a newly-emerging tourism but otherwise economically and socially backward region like Xizang, considering the economy first and the environment last is both appropriate and practicable. It is suggested that Xizang's tourism managers should implement specific strategies to raise the GDP, encourage higher levels of consumption by tourists and appropriately restrict the growth in the number of tourist coming to the area. Other goals should be to improve tourism research and the treatment of tourism employees and provide more support for tourism enterprises. The interdisciplinary approach from a systems perspective used in this study can be used to judge, queen and select numerous goals and criteria to make decisions in sustainable tourism development. [ABSTRACT FROM AUTHOR]

The purpose of this study is to employ a nonlinear dynamic evaluation method to assess the tourism sustainability of Tibet Autonomous Region (TAR), China, a new emerging tourism destination. The methodology draws on system dynamics and Back Propagation (BP) neural network. According to 7 setting principles, this study identifies 13 tourism sustainability indicators including conventional tourism income, tourism resources stock, pollution stock, etc., as well as specific residents’ tourism cognition, seasonal difference, accessibility, etc. Then a system dynamics model including the 13 indicators (variables) and other relevant auxiliary variables is established. Based on the numerical simulation, using a three layers BP neural network optimized by genetic algorithm and particle swarm algorithm, this study evaluates the future sustainability dynamically and compares the sustainability evolution from 2014 to 2050 under different development strategies. The research results not only provide information useful for the dynamic control and scientific management of the future sustainable tourism development, but also provide a systems approach to evaluate regional tourism sustainability. [ABSTRACT FROM AUTHOR]

Climate change problems have become a worldwide concern. In response to containing global climate change, there has been a proliferation of theories and policies aimed at driving tourism towards 'low-carbon tourism'. The problem becomes even greater if turning to cities. Constructing a low-carbon tourism city requires a comprehensive understanding of urban low-carbon tourism development rather than solely focusing on targets limited to CO 2 emissions and energy reduction. However, much of the focus of research to date has not been on this key issue. Here this study constructed indicators to evaluate low-carbon tourism development in a tourism-based urban destination. A total of 33 indicators were identified using the fuzzy Delphi method. Then, the weights of these indicators were determined using the analytic network process. The evaluation model made it possible to convert the subjective qualitative characteristics of low-carbon tourism, the implied mutual influences between the numerous indicators, and development demands into integrated quantitative values to guide actual low-carbon tourism development. The presented research process and results could provide a reference for relevant policy making in tourism-based urban destinations worldwide. • This study evaluated the low-carbon development level in the TBUDs. • This study selected a total of 33 indicators through the FDM approach. • The weights of these indicators were determined using the ANP method. • This study took Lhasa and Guilin as the case study regions. • The evaluation model can be applicable for all the TBUDs worldwide. [ABSTRACT FROM AUTHOR]

The purpose of this study is to build an energy-emissions-economy dynamic stochastic general equilibrium model to examine the economic and environmental effects of the carbon tax and carbon intensity target. The model is calibrated to China's economy. The results show that both the carbon tax and carbon intensity target policies have a negative effect on China's economy and environment. However, the carbon tax exerts more negative effects on the economy and environment than the carbon intensity target. Moreover, the carbon tax shock lasts shorter than the carbon intensity target shock. The findings additionally indicate that the effects of the increase in the productivity of energy sectors are greater than those of the increase in the productivity of other sectors. Thanks to the low-carbon technology shock, China's carbon dioxide emissions will reduce and output will increase. Taken together, this study highlights the key policy implications associated with the results. • This study built an energy-emissions-economy DSGE model. • The impulse responses of China's output and CO 2 emissions were examined. • Both emissions policies could reduce CO 2 emissions and economic growth. • Low-carbon technology shock could reduce CO 2 emissions as well as increase output. [ABSTRACT FROM AUTHOR]

As the main climate policy, emissions trading scheme (ETS) has been proved by scholars to have significant impacts on carbon dioxide (CO 2) emissions and energy consumption reduction worldwide. However, existing studies have focused mainly on the simulated impacts of ETS and few studies have poured specific attention into the actual impacts and their dynamical change, which may lead to an ambiguous understanding of ETS's performance. Here, taking China as the case study, this study investigated the net dynamic impacts of ETS policy on low-carbon development with respect to CO 2 emissions, carbon intensity, energy consumption and energy intensity using a difference-in-differences method. The findings indicate that there is a positive relationship to some extent between carbon trading system and low-carbon transformation. The effect of ETS policy on low-carbon development will gradually increase over the time. When the variables population, gross domestic product, ratio of the secondary industry, technical level, and income level are controlled, these conclusions are also robust. In addition, common trend hypothesis and counterfactual test were used to confirm the reliability of the conducted difference-in-differences models. The findings are conductive to the future ETS policy-making and the research framework proposed in this study is also applicable to the assessment of global climate policy. • This study explores the low-carbon impacts of emissions trading scheme. • Difference-in-differences model are conducted base on emissions trading scheme. • Emissions trading scheme significantly negatively impacts low-carbon development. • All the difference-in-differences models pass the robustness test. • The findings provide experience reference for the further promotion of ETS policy. [ABSTRACT FROM AUTHOR]