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Green residences have enormous potential for energy savings, emission reduction, and other comprehensive benefits, and their growth is crucial to achieving China's carbon neutrality and carbon peaking targets. Nevertheless, at the moment, the national green residence is impacted by complicated factors at several levels, including government agencies, green residence builders, and green residence consumers, which results in the low-quality development of domestic green residences overall. As of 2020, 94% of all labeled green residences are design-label residences that can only be achieved during the design stage, while less than 10% are operational-label residences with stronger energy and emission-saving benefits. This causes the phenomenon of "green residences on the planning" to be serious. In order to accomplish the promotion of high-quality development of green residences and to promote green residences in China, this paper analyzes the influencing factors of green residence promotion from the multi-level perspective of macro-landscape signals, meso-collective agent green residences, and micro-individual agent consumers, based on the multi-level perspective (MLP) framework of sustainability theory. The paper subsequently builds a simulation model of green residence promotion using the agent-based system dynamics modeling method. Additionally, Jiangsu Province's green residence promotion data are chosen for analogue simulation experiments, and the simulation results are also used to analyze the success conditions as well as the path to green residence promotion. This study demonstrates that (1) the agent-based simulation model of dynamics for the green residence promotion system has high reference value for the simulation of the promotion of green residences, and the model can clearly simulate the impact of micro-individual agent–consumer factors on the promotion of green residences; (2) in order to promote green residences, exterior landscape signals must be continuously improved; the stronger the landscape signals, the quicker the development of operationally labeled green residences; (3) priority is given to the development of two-star design-labeled green residences before 2035, and three-star operationally labeled residences will occupy the majority of the market after 2040. Meanwhile, the duration of landscape signals and the change in behavioral preferences of individual agents must be maintained for a long time. [ABSTRACT FROM AUTHOR]

In the past decades, resource shortage and environmental degradation due to rapid economic development have become a severe challenge while limiting China's regional sustainable and coordinated development. This paper provides a case study of Jiangsu Province in China employing the coupling coordination model and geo-detector model to seek solutions for realizing the region coordinated development from the interaction of technological innovation (TI ), industrial upgrading (IU ) and eco-environment (EE ). This study reaches the following conclusions. (1) The coupling coordination degree (D ) of TI - IU - EE system (TIIUEES) in Jiangsu Province was general in the stage of mild unbalance. (2) The D value exhibited a positive evolutionary trend in time series. However, the backwardness of EE constrained the regional coordination development, which led to the slow and small growth with fluctuation. (3) Spatially, the D value generally conformed to a gradient distribution from south to north, which was caused by regional internal extremely unbalanced development. (4) Economic benefits had a decisive effect on the coordinated development in TIIUEES, and the interaction of two factors could gain an "enhanced, bilinear" or even "enhanced, nonlinear" result. This study contributes to exploring the driving determinants of D value in TIIUEES based on the description of the temporal and spatial features and providing a credible reference for future research and decision-makers. [ABSTRACT FROM AUTHOR]

This paper takes Jiangsu as an example to measure the carbon emissions from the electric power industry from 2002 to 2017, builds an extended STIRPAT model to quantify its driving factors, and uses the Monte Carlo method to simulate the evolution of carbon emissions in multiple scenarios from 2018 to 2030. The results show that: (1)Population scale, urbanization level, GDP per capita, industrial added value, and electricity consumption intensity promote the increase of carbon emissions in the electric power industry. (2)Trade openness and the transmission level of other provinces play a role in reducing carbon emissions. (3)Under the baseline scenario and the green development scenario, the carbon emissions of the electric power industry have shown a continuous growth trend, but the growth rate of carbon emissions has slowed down significantly under the green development scenario. [ABSTRACT FROM AUTHOR]

With today's rapid economic growth, the role of agriculture in production and life has come to the forefront. Many problems in China's agricultural economy have seriously constrained the vitality of Chinese agriculture. Therefore, it is necessary to further strengthen the study of an agricultural economy, inject new impetus into an agricultural development, develop targeted solutions, and lay a solid foundation for the sustainable development of China's agricultural economy. Therefore, in this paper, based on the theory of sustainable development of an agricultural economy, this paper constructs a sustainable agricultural development index system in Jiangsu province from five aspects of the DPSIR model: driving force, pressure, state, impact and response and uses principal component analysis to make a comprehensive evaluation of the level of sustainable agricultural development in Jiangsu province from 2010 to 2016. The analysis results show that Jiangsu's agricultural economy is overall better and steadily improving, and it has made a huge leap in the seven-year period from 2010 to 2016, showing better sustainability. We found that the state subsystem exposed some social problems after analyzing the subsystem, and if relevant measures are not taken in time to solve the emerged problems, it will affect the other subsystems and the sustainability of the agricultural economy. [ABSTRACT FROM AUTHOR]

Background: This paper seeks to assess the sustainability of the reformed maternity insurance system and the extent to which China's current maternity insurance system can support different levels of fertility incentives in the future. Our findings will serve as a reference for countries in a similar demographic predicament and those about to face it. Methods: This study used a combination of qualitative and quantitative methods. In the qualitative assessment, we used a grounded theory model to generalize the factors influencing the sustainability of maternity insurance funds. For the quantitative analysis, we used a novel and comprehensive system dynamics model to visualize the status of the combined operation of maternity and health insurance. Data are mainly derived from the historical data of the Statistical Yearbook of Jiangsu Province and the National Bureau of Statistics of China. Results: In the short term, fertility incentive payments can be set to motivate people to have children. It is therefore recommended that when the scope of the fertility incentive policy is limited to two children, and an average amount above RMB 10 000 could be set, it would be prudent to set the amount at a level not exceeding RMB 10 000 when the scope of the fertility incentive policy is for all newborns. In the long term, a system of incentives for childbirth should be built from education policy, house price regulation, tax relief and childcare services. Conclusion: Our research not only highlights the significance of improving the resilience of maternity insurance by combining maternity insurance and health insurance funds, but also suggests a way to economically incentivize beneficiaries to have children so as to mitigate the decline in China's birth rate and cope with the crisis of an ageing population. [ABSTRACT FROM AUTHOR]

Entrepreneurship plays an important role in developing the agricultural sector and increasing opportunities for farmers to promote sustainable livelihoods. The study aims to enhance discussion and gain an in-depth understanding of farm entrepreneurship in the context of sustainability in China. We conducted a case study of five farmers practicing organic farming through semi-structured face-to-face interviews. The analysis shows that organic farms enhance sustainability through many economic, social and environmental contributions. Additionally, emerging societal awareness of healthy foods and the increasing demand for organic products are among the most important opportunities contributing to the growth of organic farming. Despite this, farm entrepreneurship among organic farms faces many challenges, such as land use rights, lack of business networks and government subsidies. However, the government is the main player in promoting sustainability practices among entrepreneurs and society through agricultural policy development and promotion of organic products. We believe that this paper is the first attempt to study organic farm entrepreneurship in China from an entrepreneurs' viewpoint. The conclusions could have potential implications and guidelines for promoting organic agriculture policies in national and international contexts. The conclusions have significant implications and potential guidelines for promoting sustainability in national and international contexts. [ABSTRACT FROM AUTHOR]

With the rapid development of the marine economy, the demand for marine resources development and the pressure on marine environmental protection are gradually increasing. It is critical to evaluate and analyze the driving forces of marine sustainable development in order to promote the coordinated development of the marine economy, resources and environment. Taking Jiangsu Province of China as an example, this paper constructs an evaluation index system for marine sustainable development from the three aspects of marine economy, resources and environment, and calculates the weight of the variation coefficient for each indicator. Based on the grey relational model, the average value of the relational degree, calculated by the average value method of correlation coefficients and the weighting method, is then used to evaluate the status of marine sustainable development in this province. The comprehensive index model is used to analyze the dynamic trend of the evolution of marine sustainable development. The driving forces of marine sustainable development are analyzed by the path analysis method combined with the average values of the grey relational degree for each indicator. This analysis found that the marine sustainable development in 2016 and 2012 was good, the situation in 2007 was bad, and the remaining years were intermediate. Compared with the previous years, the optimal conditions of 2008 and 2012 were obvious. The main driving factors of marine sustainable development are cargo throughput of coastal ports, economic losses caused by storm surges in coastal areas, the area of marine nature reserves in coastal areas, coastal wind power generation capacity, and marine biodiversity. [ABSTRACT FROM AUTHOR]

Improving energy conservation efficiency is one of the prerequisites for China's manufacturing industry to transform and upgrade. Jiangsu province which presents the maximum economic volume in manufacturing and its economic status in eastern China is comparable to Shanghai. Research on the sustainable development capacity of Jiangsu's manufacturing industry gives important guidance for upgrading the manufacturing industry all over China. The core of China's manufacturing transition to a manufacturing power is to enhance its independent innovation capabilities to improve energy efficiency and its position in the global value chain. Therefore, it is important to study the impact of technological factor on energy conservation potential and the transformation and upgrading of manufacturing. In this paper, multivariate regression research method combined with risk analysis is developed to explore the influence of the research and development factor on energy conservation while introducing macroeconomic variables. Additionally, energy conservation of manufacturing in Jiangsu province in 2020 and 2025 based on historical data from 1985 to 2015 is predicted. Compared with the business-as-usual scenario, the advanced scenario could reduce by 44.07 Mtce and 87.60 Mtce in 2020 and 2025, respectively. Thus, the results indicate that there is much room for improvement in terms of the energy efficiency for Jiangsu province. [ABSTRACT FROM AUTHOR]

This paper, through a case study of the Gengche Township in north Jiangsu (Subei), unveils how a less-favored region breaks out of the old industry path of waste recycling and processing and embarks on a green new one specializing in E-commerce. Drawing on key concepts in evolutionary economic geography, we propose a conceptual framework that addresses how entrepreneurial agents enact the processes of asset modification at multiple scales for new green path development in a rural context. Based on on-site interviews and survey, our analysis reveals that rural lead entrepreneurs and state elites pioneered and opened windows of opportunities for change, then legitimized by the state with wider support towards old path breaking. These state interventions enforce the bottom-up process of new green path development. In this process, extra-regional knowledge linkages and assets help facilitate the E-commerce development. It is concluded that rural new path development processes are not only contingent on local pre-conditions but are tempo-spatially dependent on collective actions of entrepreneurial multi-actors in identifying, transplanting and modifying local and non-local assets. The Gengche case demonstrates that rural new green path development in China requires the formation of strong system-level rural agency engaging in multi-scalar asset modification. • The transformation trajectory of Gengche, a previous poverty township, was investigated. • Rural lead entrepreneurs and state elites pioneered and opened windows of opportunities for change. • State interventions enforce the bottom-up process of new green path development. • Extra-regional knowledge linkages and assets help facilitate the E-commerce development. [ABSTRACT FROM AUTHOR]

Rural areas are at the forefront of achieving sustainable development goals, and elite actors tend to be the most influential local decision-makers in rural development. Nevertheless, improving the effectiveness of governance by elites and avoiding or redressing "elite capture" remain key challenges for sustainable rural development globally. This research integrates a large-scale quantitative dataset consisting of 604 villages in seven counties of Jiangsu province in China with qualitative data from eight villages in three out of the seven counties to examine whether and how collective action mediates the correlation between rural elites and rural development. Our quantitative analysis using multiple regression and path analysis indicates that collective action is a mediator, but it is more influential in linking governing elites than in linking economic elites with rural development. Our case studies with interviews further illuminate that collective action fuels rural development by improving resource reallocation and resource-use efficiency with the participation of both elites and non-elites. Innovative collective action designs that leverage a reputation effect to foster reciprocity norms promote the participation of elites while discouraging elite capture. Additionally, this research contributes to longstanding debates in commons governance about the role of authority interventions: we find evidence justifying the benefits of authority in catalyzing and sustaining collective action while also corroborating the critical role of democratization in improving rural governance by elites. [ABSTRACT FROM AUTHOR]

The upscaling of farming operations in China has been advancing rapidly in recent years. This trend is likely to increase the use of agricultural machinery inputs, and possibly also the use of chemical pesticides, which is already extremely high. The relationship between farm size and the intensity of chemical pesticide usage is a subject of debate, and little is known about the mechanisms that might underlie this relationship. In this paper, we apply an integrated framework of larger-scale farming, agricultural mechanization and the intensity of chemical pesticide usage to examine and quantify the mediating effect of agricultural mechanization on the relationship between larger-scale farming and the use of chemical pesticides. Results obtained by applying seemingly unrelated regression (SUR) considering two-way fixed-effects and mediation analysis to county-level data for Jiangsu Province (2002–2019) suggest that an increase of 1% in the ratio of scale of farming is related to a total decline of 0.070% in chemical pesticide usage per hectare of land. Mediation analysis subsequently identifies mechanical sowing/transplanting is the only mediating variable, through which an increase of 1% in the ratio of scale of farming reduces the unit consumption of chemical pesticides by 0.017%. [ABSTRACT FROM AUTHOR]

Owing to the publicity and externality of watershed governance, collaborative governance among cities has become an inevitable choice to improve watershed governance performance and promote sustainable development of watersheds. Existing studies have provided many enlightenment on promoting watershed collaborative governance (WCG), while most of them investigated WCG from single or several dimensions with scanty quantitative empirical studies. Against this background, this study aims to establish a comprehensive WCG research framework involving multiple phases and diverse actors to empirically measure the synergy degree of WCG. Specifically, this study constructs a WCG index system composed of resource investment, open cooperation, and performance supervision subsystems that involves actors of government, enterprise, and the public. Using the complex system synergy model, an empirical analysis is performed to evaluate the synergy degree of Taihu Basin collaborative governance among and within cities in Jiangsu province, China during 2014–2020. The results reveal that the Tai Basin collaborative governance among cities was still in the run-in adaptation stage, which was primarily constrained by the discrete open cooperation subsystems among cities. The synergy degree of Taihu Basin collaborative governance within cities presented significant differences. Several targeted implications are proposed according to the results. This study provides a comprehensive index system for synergy degree measurement of WCG and could offer effective guidance for policymakers to design effective strategies for improving WCG performance. [ABSTRACT FROM AUTHOR]

This paper draws upon smart growth theory to provide an analytical framework of "smart identification" for industrial land to be readjusted. Huai'an city, Jiangsu province, China, is selected as a case example for the developed framework. Unlike the identification method of efficiency orientation for stock industrial land, which emphasizes the core goal of input and output of production factors per unit area, the smart identification framework covers the five dimensions of industrial policy, urban planning, socioeconomic benefits, transportation convenience, and environment protection. The framework pays more attention to the characteristics of high-quality socioeconomic development, including innovation-driven, coordinated, and sustainable development. Industrial land blocks are used as the research unit. A total of 1,552 industrial land blocks are identified for readjustment, covering an area of 4,008.7 hm2 and accounting for 54.3% of the total industrial land area in Huai'an city; this shows that considerable potential exists for adjustment. We argue that the evaluation index selection of intensive industrial land use and the method by which industrial land is identified for readjustment is influenced by the stage of socioeconomic development. The smart identification method is more consistent with the connotation of high-quality development, and more conducive to revealing the current demand and change law of industrial land against the background of industrial transformation and upgrading, which is of great significance with regard to promoting the intensive use and spatial optimization of industrial land. [ABSTRACT FROM AUTHOR]

In this paper, we search to link changes in non-farm employment and agricultural mechanization to the emergence of large-scale farming in China. Based on county-level data for the Jiangsu Province from 2002 to 2016, we use spatial panel data techniques to understand how the increase in large-scale farming in one county is explained by changes in employment and mechanization in the county itself as well as by changes in the neighboring counties. Our results confirm the presence of substantial spatial spillover effects. The level to which large-scale farming is present and expanding in one county is positively associated with local non-farm employment and agricultural mechanization levels. A local higher non-farm employment ratio also contributes to an increase in large-scale farms in neighboring counties. Hence, if a local government intends to support large-scale farming, it can bank on the creation of non-farm employment and support agricultural mechanization in the county it governs. Also economic and policy changes in the neighboring counties will induce land use transition when non-farm employment is created. • Large-scale farm expansion is spatially correlated among neighboring counties. • Non-farm employment and agricultural mechanization promote local farm expansion. • Economic and employment structures show obvious spillover effects in this process. [ABSTRACT FROM AUTHOR]

As the world's largest inland shipping channel, the Yangtze River Economic Belt (YREB) is strategic to China's sustainable development where policymakers are increasingly emphasizing not only this region's economic development but also its CO 2 emission reduction targets. To achieve emission targets in the YREB region, it is essential to identify the driving forces of its CO 2 emissions. However, existing studies are not very refined and only examine the overall effects of drivers on CO 2 emission changes, while neglecting the sub-regional and sectoral level effects across China. More refined research, therefore, will provide better-targeted policies for emission reduction relevant to regional levels such as the YREB region. Towards this end, this paper integrates the methods of structural decomposition analysis and attribution analysis to demonstrate the driving forces, at both sub-regional and sectoral levels, for YREB's emission changes from 2002 to 2012. Our results reveal the following: (1) Jiangsu Province has always been the main regional source of increasing CO 2 emissions in the YREB, accounting for more than 20% of total CO 2 emission growth. (2) The Electricity and Heat Production and Supply sector is responsible for most of the increases in CO 2 emissions, both in 2002–2007 (609.8 Mt, 54.8%) and 2007–2012 (287.6 Mt, 34%). (3) During the period of 2007–2012, changes in per capita final demand were the primary driving force for the increases in CO 2 emissions, while changes in CO 2 emission intensity were the largest driving force for decreasing CO 2 emissions, respectively accounting for 179.9% and −119.4% of total emission changes in the YREB region. (4) Moreover, the effect of emission intensity mainly exists in the Electricity and Heat Production and Supply sector in the Jiangsu and Zhejiang provinces, accounting for respectively, 10% and 10.4% of the total effects across all economic sectors. Considering the diverse impacts of driving forces in different sub-regions and economic sectors, policymakers should apply more refined measures to utilize varying driving forces in different sub-regions and economic sectors towards sustainable development. • We analyze drivers of CO 2 emissions in the Yangtze River Economic Belt (YREB). • Drivers of CO 2 emissions are decomposed into both sub-regions and sectors. • Jiangsu province and three main sectors dominated CO 2 emissions in the YREB. • Intensity changes in Jiangsu's three sectors largely reduced YREB's emissions. [ABSTRACT FROM AUTHOR]

• Performance of airports relates to underlying patterns of economic development, airport size and aircraft used. • Airports have a high reduction potential of CO 2 emission, without a loss of economic performance. • Airport size, location, and linkage to the local economy are closely related to aircraft CO 2 emissions. • Different stakeholders have different impacts on adding to sustainable development. This paper analyzes aircraft CO 2 emissions (in both quantity and intensity per passenger) during landing and take-off cycles at nine different airports in Jiangsu province (China) over a ten-year time span (2007–2016). Our database is unique and very detailed in that we combine flight schedules, with aircraft type (engines) used, and landing-and-take-off cycles. We are particularly interested in how the spatial characteristics impact emission levels. To this end we estimate a CO 2 emission model taking the airport characteristics into account, and apply a spatial classification and autocorrelation model to distinguish between different types of airports and systems. Our analysis shows that: (1) there are strong spatial distribution differences between airports due to the patterns of economic development, airport size and aircraft used; (2) most airports have a high reduction potential of CO 2 emission, without a loss of economic performance; (3) significant spatial aggregation effects exist and are persistent during most observational years, which indicates a strong Matthew effect of CO 2 emission within Jiangsu province; and (4) airport size, linkage to the local economy, and airport location are closely related to aircraft CO 2 emissions. We also provide a number of recommendations to improve airport CO 2 emissions and add to sustainable development. [ABSTRACT FROM AUTHOR]

The resource utilization of crop straw is related to the green development of agriculture and the development of the rural ecological environment. Given a background of tightening agricultural environmental constraints, realizing the effective utilization of straw resources has become a real-world problem in China urgently requiring a solution. Straw incorporation is an effective way to effectively utilize straw resources. This paper quantitatively analyzed the impact of household land endowment and environmental cognition on farmers' willingness to implement straw incorporation (FWSI) by using household survey data from Jiangsu Province in China and an ordered logit model. The results reveal that straw incorporation not only needs to be considered at the technical level but also needs to start with household land endowment and environmental cognition. There is a close relationship between household environmental cognition and FWSI, and thus improving environmental cognitive ability can promote FWSI. In contrast to farm size, plot area is an important factor influencing FWSI, and scale farmers are also more concerned about straw incorporation cost than other farmers. The government should provide relevant training to clarify the positive effect of farmers' environmental cognition on straw incorporation and enhance farmers' cognition of the value of straw incorporation in China. Considering the plot area and cost, the government should also vigorously encourage the transfer and integration of adjacent plots, expand the plot area, reduce the cost of straw incorporation for a single plot, and guide social funds toward research on straw purchasing and storage technology. Attention should also be paid to the demonstration role of scale farmers in straw incorporation. [ABSTRACT FROM AUTHOR]

This study used goal‐framing theory to test the impacts of hedonic, gain, and normative goals on green consumer behavior (GCB). Moreover, we explored the potential multiple mediation effects of perceived risk and lifestyle between goal frames and GCB. The participants were 2,340 Jiangsu residents in China. Structure equation modeling was used to examine the hypothesized association between the variables. The results revealed that hedonic and normative goals had significant impacts on GCB, whereas gain goal had no significant influence on GCB. Perceived risk had a significant negative effect on GCB. Lifestyle had a significant positive impact on GCB. In addition, perceived risk and lifestyle mediated the relationship between hedonic goal and GCB and normative goal and GCB, respectively. The current research helps gain a better understanding of the relationship and multiple mediating mechanisms between hedonic goal, gain goal, normative goal, perceived risk, lifestyle, and GCB in the field of sustainable development. Implications and recommendations for future research are discussed. [ABSTRACT FROM AUTHOR]

The phrase 'green cities' refers to an idealised and modernised urban development model that features harmonious development among the environment, ecology, society, culture, and the inhabitants of a city. Harmonious humanistic relations and green pathways have become predominant models in modern urban development. Green city construction has drawn considerable attention. However, the construction and development of green cities involves numerous problems. The various needs of different populations must be coordinated to foster the green development of a city. In this study, the analytic hierarchy process was used to classify factors related to green city construction into different levels. The scope of the empirical verification was eight cities alongshore the drainage area of the Jiangsu section of the Beijing–Hangzhou Canal. Data from 2009, 2014, and 2019 were selected for analysis. Both quantitative and qualitative analyses were performed using these data, and standards were established to serve as a reference for city administrators in the process of decision-making regarding green city construction. [ABSTRACT FROM AUTHOR]

We are facing the water shortage crisis. To realise sustainable development, we should improve water-use efficiency (WUE). In this study, a cloud–compound fuzzy matter element–entropy combined model was constructed to evaluate WUE. The Huai river basin (HRB) was selected as the study area. The cloud model was used to select some indices and build the comprehensive evaluation index system (CEIS), which included the overall, agricultural, industrial, domestic and environmental categories. The compound fuzzy matter element model was used to calculate the comprehensive indicators of WUE of the HRB and its regions. The weight of each index in the CEIS was determined using the entropy model. The results showed that WUE of the HRB had an upward trend on the whole because of the enhanced emphasis on water resources by the international and national governments. However, the regional difference was obvious. The WUE of Henan province was higher than that of Jiangsu province. The imbalance of regional WUE is an international problem. By analysing the difference among regions, research can provide a reference for the decision making of the water resources management department. [ABSTRACT FROM AUTHOR]