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By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.

First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.

Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.

This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.

Sustainable consumption is a crucial route to sustainable tourism. Hence, the purpose of this study is to investigate the individual and combined effect of social learning and eco-labels on the green hotel selection.

This study used a between-subject online experimental method with 199 respondents, which is used only in around 15% of published tourism articles. Additionally, this method provided reliability and control features.

Social learning and eco-labels individually could not influence tourists to select green hotels. However, the interaction of positive performance social learning with eco-labels could potentially influence tourists' green hotel selection. Therefore, internalizing green hotel performance from trusted sources and external validation bring behavioral changes among tourists to select green hotels. This study offers a new social learning-based model for understanding sustainable consumption.

This study can use various other types of social influences and can be expanded to other green settings.

This study provides policy and promotion formulation insights to hotel managers and sustainable tourism promoters to market green hotels.

Away from the traditional theory, this study bridges the gap between social learning of performance from relatable sources, assurance from governing entities and sustainable consumption. The interaction effect of social influence and eco-label on green hotel selection is a novel finding. Also, this study introduces various levels of social learning to the discussion of sustainable consumption.

该研究对 199 名受访者使用了主题间在线实验方法, 仅在大约 15% 的已发表旅游文章中使用。此外, 这种方法提供了可靠性和控制功能。

可持续消费是可持续旅游的重要途径。因此, 本研究调查了社会学习和生态标签对绿色酒店选择的个体和综合影响。

单独的社会学习和生态标签不能影响游客选择绿色酒店。然而, 积极绩效社会学习与生态标签的相互作用可能会影响游客对绿色酒店的选择。因此, 从可信赖的来源和外部验证中内化绿色酒店绩效, 会带来游客选择绿色酒店的行为变化。该研究为理解可持续消费提供了一种新的基于社会学习的模型。

该研究可以使用各种其他类型的社会影响, 并可以扩展到其他绿色环境。

它为酒店经理和可持续旅游推广者提供了政策和促销制定的见解, 以推销绿色酒店。

与传统理论不同, 本文填补了相关来源的绩效社会学习、管理实体的保证和可持续消费之间的研究空白。社会影响和生态标签对绿色酒店选择的交互作用是一个新的发现。此外, 它还将不同层次的社会学习引入到可持续消费的讨论中。

El estudio utilizó un método experimental online entre sujetos con 199 encuestados, utilizado sólo en alrededor del 15% de los artículos de turismo publicados. Además, este método ofrecía características de fiabilidad y control.

El consumo sostenible es una vía crucial para el turismo sostenible. Por ello, este estudio investiga el efecto individual y combinado del aprendizaje social y las etiquetas ecológicas en la selección de hoteles ecológicos.

El aprendizaje social y las ecoetiquetas por separado no pudieron influir en los turistas para que seleccionaran hoteles ecológicos. Sin embargo, la interacción del aprendizaje social del rendimiento positivo con las ecoetiquetas podría influir potencialmente en la selección de hoteles ecológicos por parte de los turistas. Por lo tanto, la interiorización del rendimiento de los hoteles ecológicos a partir de fuentes de confianza y la validación externa provocan cambios de comportamiento entre los turistas para seleccionar hoteles ecológicos. El estudio ofrece un nuevo modelo basado en el aprendizaje social para entender el consumo sostenible.

El estudio puede utilizar otros tipos de influencias sociales y puede ampliarse a otros entornos ecológicos.

Proporciona ideas para la formulación de políticas y promociones a los directores de hoteles y a los promotores del turismo sostenible para comercializar hoteles ecológicos.

Se aleja de la teoría tradicional y tiende un puente entre el aprendizaje social de los resultados a partir de fuentes relacionadas, la garantía de las entidades gobernantes y el consumo sostenible. El efecto de la interacción entre la influencia social y la etiqueta ecológica en la selección de hoteles ecológicos es un hallazgo novedoso. Además, introduce varios niveles de aprendizaje social en el debate sobre el consumo sostenible.

This paper aims to explore the critical factors which affect the quality of preschool education service so that targeted and effective measures to improve service quality can be put forward.

Evidential theory is applied to aggregate experts’ knowledge, and a fuzzy cognitive map (FCM) model of preschool education service quality is established to further carry out a simulation for inference, thus figuring out the critical factors to improve service quality.

The simulation results show that the main body of supervision and environment of governments and policies are two critical factors affecting the quality of preschool education service. More emphasis should be put on these two aspects, and corresponding measures can be put forward so as to ensure the quality of preschool education service.

This paper proposes a new model based on FCM and evidential theory to study the factors affecting preschool education service quality.

The effect of board intellectual capital on non-profit organizational performance in non-western, less developed economies has been an important yet under-researched area. Given that the institutional and business relationships of a board account for the majority of board intellectual capital, the purpose of this paper is to fill the previously mentioned research gap by addressing how the interactions of the two relationships of board directors influence Chinese philanthropic foundation performance.

Following Creswell's (2014) explanatory sequential mixed-methodology, a qualitative study (Study 1) was first conducted to pre-test the assumptions, and then a quantitative study (Study 2) was carried out based on a secondary database of 1,405 Chinese philanthropic foundations to further examine the hypotheses. Several regression models were built for analyzing the results.

Study 1 confirmed that Chinese philanthropic foundations gained greater revenues and hosted more public welfare activities by leveraging the reinforcing or complementary effects of board directors' intellectual capital to improve organizational performance. Study 2 further examined the hypotheses that the interactions of intellectual capital increased the total revenue and public welfare expenditure of the foundations; however, significant positive relationships were only identified in foundations at the local level, and no significant associations were found in those at the national level.

The research indicates that the intellectual capital of board directors may influence the performance of their philanthropic foundations. Thus, Chinese philanthropic foundations should be more aware of the importance of this influence when determining which candidates will join the board.

The study makes significant contributions to the existing knowledge of the development of non-governmental organizations; it incorporates the resource dependence theory and agency theory into understanding how the intricate interactions between the institutional and business relationships of board directors affect foundation performance and how the jurisdiction affiliations act as a boundary condition for such relationships in a non-western setting such as China.

This paper takes the seven overcapacity industries such as the textile industry, electricity and heat, steel, coal, automobile manufacturing, nonferrous metals and petrochemical industry as research objects and proposes a TOPSIS grey relational projection group decision method with mixed multiattributes, which is used for the ranking of the seven industries with overcapacity and provided relevant departments with a basis for decision-making.

First, an evaluation index system from four aspects is established. Secondly, the attributes of linguistic information are converted into two-dimensional interval numbers and triangular fuzzy numbers, and an evaluation matrix is constructed and normalized. This paper uses the AHP method to determine the subjective weights and uses the coefficient of variation method to determine the objective weights. Moreover, this paper sets up the optimization model with the largest comprehensive evaluation value to determine the combined weights. Finally, the TOPSIS grey relational projection method is proposed to calculate the closeness of grey relational projections and to rank them.

This paper analyzes the problem of overcapacity in seven industries with the TOPSIS grey relational projection method. The results show that the four industries of automobile manufacturing, textile, coal and petrochemical are all in serious overcapacity levels, while the three industries of steel, nonferrous metals and electric power are relatively in weak overcapacity level in the three years of 2016–2018. TOPSIS grey relational projection method ranks the overcapacity degree of the seven major overcapacity industries, making the relative overcapacity degree of each industry more clear and providing a reference for the government to formulate targeted policies and measures for each industry.

By using TOPSIS grey relational projection method to evaluate the overcapacity of the seven major overcapacity industries, on the one hand, it makes the relative overcapacity degree of each industry more clear, on the other hand, it can provides the basis for the government and decision-making departments. This helps them promote better the healthy and orderly economic development of the seven major industries and avoid resource waste caused by overcapacity.

This article solves the single evaluation method caused by the limited indicators in the past, combines TOPSIS and the grey relational projection method and applies it to the overcapacity evaluation of the industry, not only applies it to the evaluation of overcapacity for the first time but also involves novel problems and methods, which expands the scope of application of the model.

Walking-aid exoskeletons can assist and protect effectively the group with lower limb muscle strength decline, workers, first responders and military personnel. However, there is almost no united control strategy that can effectively assist daily walking. This paper aims to propose a hybrid oscillators’ (HOs) model to adapt to irregular gait (IG) patterns (frequent alternation between walking and standing or rapid changing of walking speed, etc.) and generate compliant and no-delay assistive torque.

The proposed algorithm, HOs, combines adaptive oscillators (AOs) with phase oscillator through switching assistive mode depending on whether or not the AOs' predicting error of hip joint degree is exceeded our expectation. HOs can compensate for delay by predicting gait phase when in AOs mode. Several treadmill and free walking experiments are designed to test the adaptability and effectiveness of HOs model under IG.

The experimental results show that the assistive strategy based on the HOs is effective under IG patterns, and delay is compensated totally under quasiperiodic gait conditions where a smoother human–robot interaction (HRI) force and the reduction of HRI force peak are observed. Delay compensation is found very effective at improving the performance of the assistive exoskeleton.

A novel algorithm is proposed to improve the adaptability of a walking assist hip exoskeleton in daily walking as well as generate compliant, no-delay assistive torque when converging.

With rapid urbanization, cities are facing various ecological and environmental problems. Living in harmony with nature is more important than ever. This paper aims to evaluate the ecosystem and ecological features of Azheke village, a key component of the Hani Rice Terraces World Cultural Heritage in China. The focus is on exploring effective ways to improve the relationship between humans and the natural environment through urban design in order to create a livable and sustainable city that can promote the development of sustainable smart urban ecology design.

This study conducted a systematic literature review to answer the following research questions: (1) How does Azheke design achieve harmony between humans and nature? (2) What are the effective approaches to improve the relationship between humans and nature within urban ecosystems? (3) How can urban design learn and integrate from Azheke’s ecological features to improve the relationship between humans and nature?

Azheke sustains long-term human-nature harmony through traditional ecological knowledge (TEK) and efficient natural resource use. By incorporating biophilic design and nature-based solutions from Azheke, along with biodiversity-friendly urban planning, we can boost urban ecosystem health and create unique Azheke-inspired urban designs.

This research primarily focuses on the human-nature relationship, exploring design strategies based on biodiversity without delving into the interactions between other components of urban ecosystems, such as social-cultural and economic components.

This paper provides a new perspective and strategies for developing sustainable and smart urban ecology design. These findings can provide theoretical references for urban planners, designers and decision-makers.

One of the best ways to assist China is through infrastructure investment. China might become more resilient to natural calamities by pouring more money into its transport network. Analyzing the relationship between China's degree of planned expansion and the country's current network of transport hubs can help with city development estimates. A wide range of factors were taken into consideration while evaluating China's dominance and the caliber of its transportation infrastructure. Using a geographical autocorrelation model and a coupling coordination model, the dynamic link between China's adaptability and the caliber of its transportation infrastructure is examined.

China's northwest is underdeveloped in comparison to the southeast, which has a high level of resilience and development of its transportation infrastructure. The relationship between the levels of resilience upheld by China's transport infrastructure is suggested to be coordinated.

The authors find a positive geographical autocorrelation between the degree of coupling coordination and the degree of agglomeration, despite the fact that the distance between cities increases with time. They now believe that there is a connection between an area's population density and the degree of interspousal cooperation within. The consequence is an improvement in both national security and economic prosperity. The facilities for disaster management and transportation in China have received several proposals for improvement.

The authors' Practical Implications suggests that scale inefficiency is a major contributor to the relatively poor efficiency of China's primary inland river ports. Different types of inland river ports may have vastly different water system efficiencies. Input and output congestion at China's important interior river ports has reached 51%, making it very clear that massive amounts of valuable port resources are being wasted.

Many variables, such as climate and human error, affect the total amount of goods that can be moved via inner river ports. Ports situated either higher up or lower down the same canal may perform better or worse, respectively, depending on the circumstances.

The purpose of this paper is to develop a high-performance composite emulsion cement waterproof coating. The coating has excellent durability and is effective in protecting cement mortar substrates from harmful ions.

The polymer cement waterproof coatings with different emulsion compounding ratios were tested for mechanical properties and water resistance after alkali immersion, water immersion, thermal aging and UV aging, and the coatings were analyzed by infrared spectroscopy after aging to evaluate its durability. Meanwhile, the coating that presents favorable durability was applied to cement mortar test blocks. The protective effect of the coating on the test blocks was tested by immersion method, and X-ray diffraction analysis was performed on the eroded test blocks.

The coating with neoprene latex/acrylate latex weight ratio of 90/10 presents favorable durability and has superior overall performance. Besides, when it is applied to cement mortar blocks, the coatings effectively reduced the erosive effect of harmful ions on cement mortar blocks, resulting in much lower mass change ratios and less internal structural damage of the blocks significantly.

The obtained coating will be of great application potential for use in building waterproofing construction. Moreover, the coating can practically prevent chloride ions and sulfate ions from penetrating cement-based materials.

The fresh food supply chain industry faces significant challenges in risk management because of the complexity, immature development and unpredictable external environment of imported fresh food supply chains (IFFSCs). This study aims to identify specific risk factors in IFFSCs, demonstrate how these risks are transmitted within the system and provide an analytical framework for managing these risks.

A total of 15 risk factors for IFFSCs through extensive literature review and expert consultation are identified and classified into seven levels using interpretive structural modeling (ISM) to demonstrate the risk transmission path. Fuzzy Matrice d’Impacts Croises-Multiplication Appliance Classement (MICMAC) analysis is then used to analyze the role of each factor.

The interactions of the 15 identified risk factors of IFFSCs, classified into seven levels, are visualized using ISM. The fuzzy MICMAC analysis classifies the factors into four groups, namely, dependent, independent, linkage and autonomous factors, and identifies the relatively critical risk factors in the system.

The findings of this research provide a clear framework for enterprises operating in IFFSCs to understand the specific risks they may face and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the system to facilitate the formulation of appropriate mitigation measures.

This study provides enterprises in IFFSCs with a comprehensive understanding of how the risks can be effectively managed and a basis for further exploration. The theoretical model constructed is also a new effort to address the issues of risk in IFFSCs. The ISM and the fuzzy MICMAC analysis offer clear insights for researchers and enterprises to grasp complex concepts.