Search results

This paper aims to estimate the values of environmental efficiency of each province in China. Subsequently, it analyzes the changes of total factor productivity (TFP) before and after taking the environmental factors into account. Finally, the paper measures the effect of the components of environmental TFP on the convergence of economic growth.

The environmental control variables are taken as output variables and combined with a traditional data envelopment analysis model to build an environmental TFP Index. The growth of environmental TFP is compared among regions and the differences are analyzed. Furthermore, the decomposed components (advances in environmental technology and environmental technical efficiency) are used for regression analysis with labor productivity.

The environmental efficiency of most provinces in China has improved although some regions' efficiency remains low in Northeastern China. The value of environmental TFP is higher and more fluctuant during the period of 1997-2009 than that of traditional TFP. Technical efficiency has a convergence effect on economic growth of regions/provinces, but, after adding environmental factors, it turns into a divergence effect.

Because of data limitations, this paper does not consider the impacts of human capital and other factors on in the convergence analysis on economic. Neither does it consider the use of panel data to analyze the convergence of economic growth and validate the conclusions. These are potential further research directions.

The study confirms that improvements in environmental technologies play a dominant role in enhancing China's environmental TFP. Furthermore, it demonstrates that China's economic growth largely depends on technological progress. This finding, that China's economic growth depends on advances in environmental technology, implies that China should strive to improve its capacity for technological innovation.

The paper measures the value of environmental efficiency in the China's provinces and analyzes the relationship between pollution and economic development in each province. Panel data are used to compare the difference among environmental TFP, environmental factors and traditional TFP. The convergence of economic growth is analyzed in respect of environmental control variables.

With the fierce competition in the cold chain logistics market, achieving and maintaining excellent customer satisfaction is the key to an enterprise's ability to stand out. This research aims to determine the factors that affect customer satisfaction in cold chain logistics, which helps cold chain logistics enterprises identify the main aspects of the problem. Further, the suggestions are provided for cold chain logistics enterprises to improve customer satisfaction.

This research uses the text mining approach, including topic modeling and sentiment analysis, to analyze the information implicit in customer-generated reviews. First, latent Dirichlet allocation (LDA) model is used to identify the topics that customers focus on. Furthermore, to explore the sentiment polarity of different topics, bi-directional long short-term memory (Bi-LSTM), a type of deep learning model, is adopted to quantify the sentiment score. Last, regression analysis is performed to identify the significant factors that affect positive, neutral and negative sentiment.

The results show that eight topics that customer focus are determined, namely, speed, price, cold chain transportation, package, quality, error handling, service staff and logistics information. Among them, speed, price, transportation and product quality significantly affect customer positive sentiment, and error handling and service staff are significant factors affecting customer neutral and negative sentiment, respectively.

The data of the customer-generated reviews in this research are in Chinese. In the future, multi-lingual research can be conducted to obtain more comprehensive insights.

Prior studies on customer satisfaction in cold chain logistics predominantly used questionnaire method, and the disadvantage of which is that interviewees may fill out the questionnaire arbitrarily, which leads to inaccurate data. For this reason, it is more scientific to discover customer satisfaction from real behavioral data. In response, customer-generated reviews that reflect true emotions are used as the data source for this research.

The purpose of this paper is to examine the factors that influence older adults' intention to use virtual fitting room technology during the COVID-19 pandemic based on the extended technology acceptance model (TAM).

An online survey was conducted with a sample of older adults from 60 to 90 years old (n = 819). A structural equation modeling was conducted to test a proposed research model.

The results revealed that older adults' behavioral intentions were positively influenced by perceived usefulness and ease of use, and fear of infection during the pandemic was significantly related to the perceived usefulness. Fit concern was not significantly related to perceived usefulness of virtual fitting room technology.

This research extends the TAM by adding antecedents to perceived usefulness in explaining older adults' adoption of virtual fitting technology.

Salt rock from salt lakes can serve as a cost-effective material for subgrade filling, as demonstrated in projects like the Qarhan Salt Lake section of the Qinghai-Tibet Railway and the Qarhan Salt Lake section of the G215 Highway. This state-of-the-art paper aims to summarize the engineering properties of salt rock filling and present the advances of its utilization.

This paper collects and analyzes laboratory and field data of salt rock filling from previous studies to present a comprehensive analysis of the engineering properties and utilization of salt rock fillings.

Salt rock primarily contains minerals such as halite and glauberite, which contribute to its unique phase-changing behavior under varying environmental conditions, impacting its mechanical properties. Salt rock filling shrinks when in contact with vapor or unsaturated brine and expands under cooling or evaporation. Its use is particularly recommended for arid regions, with specific restrictions depending on the structure type. This paper discusses suggested countermeasures to mitigate these issues, as well as key quality acceptance indices for salt rock filling compaction. Moisture content after air-drying is recommended as a crucial parameter for construction quality control.

This review aims to support future research and engineering practices in salt rock subgrade applications.

Against the background of actively promoting the reform of mixed ownership in China, this study regards government ownership in private sector enterprises (PSEs) as an important political connection mechanism and examines private holding listed companies in high-polluting industries that sold China A-shares from 2012 to 2019.

Using regression models such as Tobit and negative binomial estimation, the research empirically examines the impact of government ownership in PSEs on the corporate fulfillment of their environmental responsibilities.

Government ownership can effectively promote PSEs to fulfill their environmental responsibilities. Government ownership, as a corporate-level political connection mechanism, enables the government to provide firms with more environmental protection subsidies and environmental tax incentives, encouraging firms to fulfill their environmental responsibilities. When considering the policy risks faced by PSEs, government ownership effectively reduces the impact of policy uncertainty on firms’ fulfillment of environmental responsibilities. Additionally, verifying the economic development level of the city in which the firm is located makes the positive impact of government ownership on fulfillment of environmental responsibilities of PSEs in regions with lower economic development levels more significant.

Unlike existing studies that generally use the personal political identity of entrepreneurs to measure the political connections of PSEs, this study regards government ownership in PSEs as an important political connection mechanism. It provides a useful reference for China to formulate environmental protection policies for PSEs.

China’s rural elderly care system faces significant challenges in addressing the needs of an ageing population, particularly in resource-limited areas. This study aims to critically examine the rural mutual aid elderly care model in China through the lens of active ageing principles. It explores how this model tackles elder care challenges in rural areas by emphasising health, participation and security, aiming to assess its effectiveness in reducing care costs while fostering self-reliance and mutual assistance.

A qualitative research methodology was used, focusing on document analysis to explore the rural mutual aid elderly care model within an active ageing framework. The study reviewed policy documents, academic literature and organisational records, using thematic analysis to understand the historical context, policy evolution and institutional support for this model.

The research identifies a significant shift from traditional passive care models to those grounded in active ageing principles. The rural mutual aid model, centring on health, participation and security, enables elderly individuals to engage in self-help and mutual assistance, thereby enhancing autonomy and reducing dependency. Key success factors include strong community networks and culturally resonant support systems. However, challenges such as resource limitations and regional disparities suggest areas for further improvement.

The reliance on document analysis may not fully capture the experiences of elderly participants or account for regional variations in the model’s implementation. Future research could incorporate mixed methods, including interviews or case studies, for a more nuanced understanding of elderly care in rural China. The findings emphasise the need for scalable and adaptable policies to enhance the model’s effectiveness and support culturally appropriate care strategies.

The research presents significant implications for policymakers and practitioners regarding the rural mutual aid elderly care model. It emphasises the need for scalable policies that address resource limitations and enhance community engagement to improve care effectiveness. Key implications include promoting financial and social sustainability by fostering self-reliance among older adults, prioritising active ageing initiatives to enhance quality of life and community cohesion and adopting localised strategies that consider regional disparities. Moreover, these findings offer a blueprint for other countries facing similar ageing challenges, advocating for a culturally sensitive and community-driven approach to elderly care across East Asia.

The study’s findings significantly impact how ageing is perceived and managed in rural Chinese communities. The shift from traditional, passive elderly care models to those grounded in active ageing principles reflects a societal transformation in valuing and supporting older adults. By promoting health, participation and security, the rural mutual aid elderly care model creates inclusive environments where the elderly actively contribute to their well-being and that of others. This approach challenges perceptions of ageing as a decline, fostering autonomy and meaningful engagement, ultimately reducing social isolation and enhancing cohesion through strengthened intergenerational relationships and shared responsibilities.

This study contributes to the literature by focusing on the rural mutual aid elderly care model in China through active ageing principles, addressing a notable gap in the non-Western application of these concepts. The findings offer valuable recommendations for policymakers and practitioners, emphasising community-driven approaches to ageing challenges in rural areas.

This study investigates the effects of two types of self-disclosure by influencers (i.e. personal self-disclosure and professional self-disclosure) on followers’ parasocial relationships with them and online engagement with their content, which eventually affect followers’ purchase intentions.

This study collected data based on a cross-sectional survey of 823 social media users. Structural equation modeling analysis was used to test the overall structural model and the mediating roles of parasocial relationships and engagement.

This study reveals that influencers’ personal self-disclosure has a positive impact on followers’ parasocial relationships with them and online engagement with their content. Interestingly, the results indicate an inverted U-shaped relationship between influencers’ professional self-disclosure and followers’ parasocial relationships, as well as online engagement with the influencers’ content. Furthermore, followers’ parasocial relationships and engagement partially mediate the impact of influencers’ personal and professional self-disclosure on followers’ purchase intentions.

This study contributes to the literature by revealing the underlying mechanisms of the differential effects of influencers’ personal and professional self-disclosure on followers’ purchase intentions.

The findings will assist marketers in leveraging influencer-generated content to enhance influencer marketing effectiveness.

This research provides a better understanding of the potential linear and nonlinear effects of influencers’ self-disclosure on followers’ parasocial relationships and engagement in social media marketing.

The purpose of this study is to examine the spatial fluctuation spillover effect of green total factor productivity (GTFP) under the influence of Internet development.

Using panel data from 283 cities in China for the period 2003–2016, this paper explores the spatial fluctuation spillover effect of internet development on GTFP by applying the spatial autoregressive with autoregressive conditional heteroscedasticity model (SARspARCH).

The results of Moran's I test of the residual term and the Bayesian information criterion (BIC) value indicate that the GTFP has a spatial fluctuation spillover effect, and the estimated results of the SARspARCH model are more accurate than the spatial autoregressive (SAR) model and the spatial autoregressive conditional heteroscedasticity (spARCH) model. Specifically, the internet development had a positive spatial fluctuation spillover effect on GTFP in 2003, 2011, 2012 and 2014, and the volatility spillover effect weakens the positive spillover effect of internet development on GTFP. Moreover, Internet development has a significant positive spatial fluctuation spillover effect on GTFP averagely in eastern China and internet-based cities.

The results of this study provide digital solutions for policymakers in improving the level of GTFP in China, with more emphasis on regional synergistic governance to ensure growth.

This paper expands the research ideas for spatial econometric models and provides a more valuable reference for China to achieve green development.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

This study aims to provide a model to predict the service life of a thick organic coating.

A series of thin coating films are rapidly tested under the same exposure condition as the thick coating in its service condition by means of electrochemical impedance spectroscopy, scanning electron microscopy, energy dispersive spectroscopy and X-ray diffraction.

The validity of the model is successfully verified. The long-term protectiveness or service life of a thick organic coating can be rapidly predicted.

The prediction model does not require long-term experiments or any test that may alter the degradation mechanism of the thick coating.