Fagang Hu

With the vigorous development of the pet economy, an in-depth investigation into consumers’ purchase intention of pet products is crucial to the development of the industry. Based on the SOR (Stimulus-Organism-Response) theory, this paper constructs a research model of consumers’ purchase intention of pet products and puts forward the following hypotheses: external stimuli such as product factors positively affect emotional responses; external stimuli such as product factors positively affect cognitive evaluation; and emotional responses and cognitive evaluation positively affect purchase intention respectively. Data were collected through questionnaire design, and empirical analysis was conducted by means of descriptive statistics, confirmatory factor analysis, multiple linear regression and other methods. The empirical results show that marketing activities enhance confidence in consumption decisions, purchase situations improve users’ sense of pleasure, product factors strengthen cognitive rationality, marketing activities optimize consumption risk assessment, purchase situations improve the judgment of scheme feasibility, and both consumers’ emotions and cognition exert a positive driving effect on purchase intention. This paper enriches the application of the SOR theory in the field of pet product consumption, and provides a scientific basis for enterprises to optimize product design, formulate marketing strategies and enhance consumers’ purchase intention.

The low-carbon transformation of the manufacturing industry is a key path to balance climate goals and industrial competitiveness. This systematic review critically analyzes 145 studies from 2012 to 2025 to explore the low-carbon transformation. Findings show that low-carbon city pilots reduce manufacturing carbon intensity via fiscal and tech expenditures; industrial internet and additive manufacturing reshape low-carbon production, with digital and green process innovations driving emission reduction. Yet, bottlenecks exist: SMEs face digital adaptation and green financing constraints; excessive digitalization causes energy rebound; high-carbon industries’ deep decarbonization is hindered by unproven large-scale economic feasibility of low-carbon tech, alongside policy-technological disconnection, and green finance structural contradictions. This study proposes core solutions: dynamic policy adjustment mechanisms, multi-dimensional SME support systems, and technology–economy coupling evaluation models. It establishes research coordinates for academia, designs policy tools for decision-makers, and provides a technological framework for industrial deep decarbonization, offering global references for balancing climate goals and manufacturing competitiveness.

Shared bicycle systems are widely promoted as sustainable urban mobility solutions due to their potential for resource sharing and emission reduction. However, assessments of their sustainability performance often rely on aggregate usage indicators, providing limited insight into how shared mobility assets are actually utilized across time and space. From a circular economy perspective, uneven utilization patterns may undermine resource efficiency and long-term infrastructure sustainability. This study examines shared bicycle systems as circular urban infrastructure by analyzing temporal and spatial patterns of resource utilization during a public holiday period. Using large-scale shared bicycle order data from Shenzhen during the Labor Day holiday, the study investigates how demand is distributed within daily cycles and across urban space, with particular attention to concentration and inequality in usage. The results reveal pronounced temporal and spatial concentration of shared bicycle trips. A substantial proportion of trips is concentrated within a limited number of peak hours, while spatial usage remains highly clustered in specific urban zones. Importantly, these concentration patterns persist even during peak demand periods, indicating limited temporal and spatial elasticity of the system under stress conditions. These findings suggest that the sustainability of shared bicycle systems depends not only on overall demand levels, but also on the structure of resource utilization. By highlighting distributional inefficiencies in time and space, this study contributes to ecological economics and management research on circular urban infrastructure and offers practical insights for the governance and operation of shared mobility systems.

Rapid economic development has exacerbated environmental degradation, particularly because of carbon dioxide emissions. To address these issues, China has proposed economic transformation from high-speed to high-quality development to achieve carbon peak and neutrality. Regional collaborative carbon emission reduction is critical for sustainability. Therefore, measuring regional carbon emission reduction capacity and the collaborative development level is imperative. This study employed provincial- and city-level data (2014–2023) from the Yangtze River Delta to assess regional collaborative carbon emission reduction capacity. Evaluation model of carbon emission reduction capacity was constructed based on five perspectives: economic development, carbon emission, carbon transfer, carbon sink, and industrial development. The entropy weighting method was employed to assign index weights, which was then integrated with a composite system synergy degree model. The subsystem order parameters and the composite system’s order degree were utilized to assess carbon emission reduction and collaborative trends. Results revealed that (1) overall carbon emission reduction capacity in the Yangtze River Delta constantly improved; (2) provincial economic development strengthened while carbon emissions declined; (3) carbon transfer fluctuations decreased; (4) technology and carbon sinks improved; (5) industrial development fluctuated or declined; and (6) interregional carbon emission reduction cooperation remained stable and improved. This research offers a theoretical and scientific reference for formulating low-carbon development strategies in similar regions.

The deep integration and innovative development of the logistics and manufacturing industries (LMDIIs) are crucial for reducing costs, increasing efficiency, and advancing manufacturing. To assess the development level and performance of the LMDIIs, we construct an evaluation index system, calculate the weights using the CRITIC method, and measure the comprehensive level of the LMDIIs using the TOPSIS method. We evaluate the coupling coordination of the LMDIIs and conduct a ridge regression analysis of their performance, using Anhui Province, China, as a case study. The results show that the comprehensive level of the LMDIIs in Anhui Province is low. The highest values for the logistics and manufacturing industries from 2013 to 2022 indicate great development potential. The coupling level is fluctuating upwards, and the coupling degree is growing slowly. The performance impact coefficients of the LMDIIs on the digital intelligence development of the manufacturing industry and the profit levels of the two industries indicate a significant promoting effect. However, the performance coefficient for the low-carbon transformation of the logistics industry is negative, indicating a restraining effect. Hence, we propose countermeasures and suggestions to further promote the LMDIIs and provide theoretical and methodological support for their research and management.

To delve into the interrelationship between the green transformation of industry and the economy’s high-quality development, to promote the coordinated development of industrial carbon emission efficiency and digital economy, to expand the scope and research ideas related to economic and social sustainable development, and to provide scientific reference for the low-carbon sustainable development of regional economy, this article introduced a data-centric methodology for evaluating the collaborative advancement of both industrial enterprises’ carbon emission efficiency and the digital economy. To accurately gauge the carbon footprint of industrial enterprises, models focusing on carbon emissions as well as carbon emission intensity were employed. To enhance the precision of evaluation outcomes and mitigate biases stemming from subjective weighting factors, we employed the entropy weight method to objectively assign weights to each indicator. Furthermore, the super-efficient slack-based model (SBM) can solve the problem that the conclusions are biased, due to the different radial. Subsequently, a carbon-emission efficiency slack-based measure model, and models for coupling degree and coupling-coordination degree were formulated. Anhui, as a central province in China, is also an important province in the Yangtze River Delta integration development. Coordinated development of its carbon emission efficiency and digital economy has important implications for the sustainable economy advancements of other regions in China, and even other countries or regions in the world. Therefore, Anhui was selected to be the empirical research sample. The results showed that the comprehensive levels of these two systems followed an increasing trend, while the digital economy lagged. Their coupling degree fluctuated and reached its highest point in 2021, whereas their coupling-coordination degree increased, showing high coupling and low coordination overall. This study proposes specific countermeasures and suggestions for the relevant decision-makers.

With the proposal of the goal of “carbon peak, carbon neutrality”, the concept of environmental protection has become increasingly popular. To explore the characteristics and influencing factors of consumers’ green consumption behavior against a dual-carbon background, this study proposed research variables and hypotheses about green consumption behavior and influencing factors. With the research purpose, research variables, and hypotheses, a questionnaire was designed. Consumers in Anhui Province were chosen as research samples. SPSS26.0 was employed to conduct reliability and validity analysis, correlation analysis, and stepwise linear regression analysis of the questionnaire data to evaluate the factors affecting consumers’ green consumption behavior; through these measures, it was verified that there existed a significant relationship between green consumption behavior and the influencing factors of purchase motivation, channel factor, consumer innovation, and price factor. And it was also verified that the influence of incentive factors and psychological factors was not significant. Based on this, the current study proposes countermeasures and suggestions for setting up environmental awareness, reducing the price of green products, expanding green consumption channels, and stimulating consumer innovation.

Regional synergy innovation capability is an important driving force in promoting the sustainable and high-quality development of the regional economy. Taking the regional innovation development panel data of the Yangtze River Delta integration region from 2010 to 2019 as a sample, this study constructs an evaluation index system of regional synergy innovation capability, weights the index using the entropy weight method, and measures the capability of the Yangtze River Delta integration region (three provinces and one city) using the composite system synergy degree model. The empirical results show that the synergy of regional synergy innovation in the Yangtze River Delta integration has increased steadily, but there is still much room for improvement. Anhui has great potential for synergy innovation with Jiangsu, Zhejiang, and Shanghai. Therefore, this study proposes countermeasures and suggestions for the high-quality development of Anhui’s synergy innovation capability under the integration of the Yangtze River Delta. This study provides theoretical and methodological support for enhancing regional synergy innovation capability and provides decision support for the sustainable and high-quality development of the regional economy.

1. The DEFECTS of the research further explore the uncertainty of the ecological environment under low-carbon governance and its impact on the quantity and intensity of carbon emissions from the theoretical and experimental perspectives. WHETHER THE...