Search

Accurate assessment of the sustainable development level is crucial to providing reasonable and effective management recommendations. However, analysis with a single scale can only reflect the sustainable status at a specific level. In this study, a multi-scale analysis of sustainability was conducted via the three-dimensional Ecological Footprint (EF) model in the Yangtze River Delta (YRD). Moreover, driving factors of sustainability were analyzed using the Multi-scale Geographically Weighted Regression model (MGWR). The conclusions include: (1) the development of YRD showed an unsustainable trend from 2014 to 2021, with per capita EF decreasing from 5.769 ha/cap to 5.283 ha/cap. The provincial sustainability is ranked as follows, from being the most sustainable to the least: Anhui Province > Jiangsu Province > Zhejiang Province > Shanghai City. (2) Based on dual indicators of EF depth and size, 41 cities were categorized into nine groups. The dominant type is always Medium size-Low depth (ML) and High size-Low depth (HL) type cities from 2014 to 2021. From the perspective of city scale, the sustainability of five cities weakened, while seven cities showed improvements. (3) Output value of primary industry (OVPI) and population (POP) were always the dominant factors affecting EF, but showed positive and negative correlations respectively. OVPI changes from north-south symmetric type to central symmetric type, while POP changes from central symmetric type to north-south symmetric type. This paper aims to comprehensively assess the sustainable development status from agglomeration-province-city perspectives, and its findings can provide a reference for similar regions with unbalanced development status between ecology and production. • The sustainability of the world-class urban agglomeration was assessed via the three-dimensional ecological footprint model. • More comprehensive and accurate analysis results based on multi-scale analysis. • The four patterns of influencing mechanism are revealed based on the MGWR model. • The combination analysis of dual indicators was adopted to classify the sustainability of 41 cities. [ABSTRACT FROM AUTHOR]

To achieve its carbon peak and neutrality targets, China is in need of balancing environmental and economic sustainability; In addition, whether environmental regulations can gain economic dividends while protecting the environment is particularly important. Based on the data of A-share listed companies in Shanghai and Shenzhen from 2012 to 2021, this study takes China's environmental fee-to-tax as a quasi-natural experiment, and adopts the difference-in-difference-in-differences model to evaluate the impact of environmental tax on enterprises' total factor productivity (ETFP). The results show that the environmental fee-to-tax significantly hinders the growth of ETFP. Further, this negative impact mainly stems from the fact that the reform prompts enterprises to choose strategic innovation and conduct greenwashing behavior. Furthermore, when considering enterprises' heterogeneity, we find that enterprises with large scale, high investment efficiency, state ownership, high market competitiveness and located in western regions are more resistant to policy shocks. This paper provides reliable empirical evidence and useful policy implications for further formulating environmental tax policies to accomplish the "win-win" goal for both the environment and the economy. [ABSTRACT FROM AUTHOR]

[Display omitted] • A comprehensive method was used to explore the improvement path of water environmental carrying capacity (WECC) from both subsystem and index levels. • WECC in the YREB was generally low without upward trend and showed no spatial autocorrelation. • WECC of the downstream in the YREB was higher than that of upstream and midstream. • Coupling coordination among subsystems is a necessary condition for higher WECC. • Proportion of ecological environment water consumption has the largest restriction on WECC improvement in the YREB. Improving water environmental carrying capacity (WECC) is pivotal to support water sustainability and continued economic development. The improvement pathways of WECC based on both subsystem coupling and driving factors have not yet been identified. Therefore, taking the Yangtze River Economic Belt (YREB) as a case study, this paper firstly constructed a set of scientific comprehensive evaluation index system of WECC based on the coupling system of water resources-water environment-society-economy. Secondly, the improved catastrophe progression method was properly introduced to dynamically evaluate the level of provincial WECC from 2010 to 2018. Finally, the coupling coordination degree (CCD) and obstacle factor diagnosis model were creatively combined to identify the main influencing factors of WECC. The main findings were as follows: (1) The WECC of the YREB was generally low at the provincial and subsystem levels without any obvious upward trend. In comparison, the WECC was higher in Shanghai City, Zhejiang Province and the lower reaches of the YREB. (2) The CCD among the four subsystems was generally low in the YREB. Meanwhile, there was a significant positive correlation between the CCD and WECC in each provincial area, and thus the low CCD was a vital reason for the low WECC in the YREB. (3) Overall, the economic subsystem had the highest restriction on WECC improvement in the YREB, while that of the water resources subsystem had the least. Seen from the mean, the top five obstacle factors of WECC were proportion of ecological environment water consumption, urbanization rate, per capita GDP, proportion of tertiary industry and water consumption per unit of GDP respectively. Furthermore, the rankings of main obstacle factors showed a certain time fluctuation. In general, it could be found out that the CCD of subsystems and main obstacle factors should be focused on simultaneously when improving regional WECC. Additionally, this study has provided a new analytical framework for identifying the pathways of improving WECC, which is also applicable to find the improvement pathways for stability and safety of other complex systems. [ABSTRACT FROM AUTHOR]

In a shopping mall, it's a common phenomenon that brands enter and exit. Studying the brand's entry and connection in the mall's ecological chain is an important factor in judging whether the brand can develop sustainably in the mall. Based on the analysis of 724,685 consumers' consumption data from one International Shopping Center in Shanghai, China, this paper conducts the social network analysis, builds a brand network map, and examines brand connection through visual analysis and cohesion subgroup analysis. Empirical results indicate that brand awareness, product category, brand positioning, and consumer characteristics are the major factors that influence brand connection. The sensitivity analysis is further conducted based on the singular value decomposition (SVD). Furthermore, these four factors have a positive impact on the sustainable development of the brand after entering and a mathematical model is established to determine whether a brand should be settled in a certain shopping mall. This research is the first to study the factors affecting the sustainable development of brands in the shopping mall ecological chain. Using big data technology to provide brand selection guidance for shopping malls from a micro perspective. [ABSTRACT FROM AUTHOR]

Agricultural sector is the basic industry supporting the construction and development of national economy. With the continuous deterioration of agricultural pollution, measuring and understanding agricultural total factor productivity (AGTFP) is the important premise to achieve agricultural green development and clean production. Regarding carbon emissions and agricultural non-point source pollution (ANSP) as undesired outputs, this paper applies a three-stage Data Envelopment Analysis (DEA) method combined with the Slack-Based Measure (SBM) model to eliminate the influences of environmental factors and random errors and explore the real AGTFP of 30 provinces in China from 2000 to 2017.On this basis, the spatial distribution and dynamic changes of AGTFP before and after adjustment are further discussed to seek the underlying reasons. The empirical results demonstrate that AGTFP is lower when carbon emissions and ANSP are both considered, and it decreases from east to west in StageⅠbut the Northeast region surpasses the East to achieve the highest productivity after removing the interferences. Moreover, China's AGTFP has been restricted by the external environment, and superior external environment disguises the poor management efficiency of Beijing and Shanghai. Therefore, some policy implications to balance agricultural environment and economic development are proposed. [Display omitted] • Non-point source pollution and CO 2 are integrated to measure agricultural green efficiency. • A three-stage SBM-DEA approach is employed to calculate the real agricultural green total factor productivity. • Different environmental factors have different effects on the slack of agricultural inputs. • China's agricultural green total factor productivity is restricted by the external environment. [ABSTRACT FROM AUTHOR]