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Exploring the intrinsic connection between the ecological environment and the digital economy and empirically testing how the level of digital economic development affects the ecological environment. Using the entropy weighting method to analyze the weights of the indicators in the digital economic development level and ecological environment system to explore the factors that have the greatest impact on the ecological environment in the indicator system of the digital economic development level so as to deepen the theoretical understanding of the relationship between the level of development of the digital economy and the ecological environment. Explore the regional heterogeneity of the level of development of the digital economy to promote the healthy development of China’s ecological environment proving the difference in the level of development of the digital economy in the east west and central regions of China and the difference in the effect on the ecological environment.

Based on the panel data of 30 provinces in China from 2013 to 2021 this paper fits the index system of digital economy development level with three factors. A digital infrastructure digital industry and digital application combines environmental pollution and energy consumption to construct ecological environment indicators and explored the impact of digital economy development level on the ecological environment by using the entropy weight method and the random effect model.

The findings indicate that the degree of digital economic development has a positive and significant impact on promoting the healthy development of the ecological environment, in which the digital industry has the greatest impact on the ecological environment. Meanwhile, the improvement of industrial structure also has a positive effect on the improvement of the ecological environment, whereas the level of human capital inhibits the healthy development of the ecological environment, and the governmental support fails to effectively and significantly promote the improvement of the ecological environment. Furthermore, the empirical research indicates that the level of digital economy development has obvious regional heterogeneity on the healthy development of the ecological environment: the eastern and central regions have a significant effect, while the western region has a less significant effect.

Although domestic and foreign scholars and experts have conducted sufficient studies on the ecological environment and the development level of digital economy respectively, there are few studies on the empirical analysis of the positive significance and regional heterogeneity of the impact of the development level of digital economy on the ecological environment, which can be supplemented and referred to in this study. At the same time, it also provides intellectual support for our country to achieve high-quality development of digital economy and efficient governance of ecological environment.

Oppositional brand loyalty poses a challenge to the management of virtual communities. This study aims to categorize these loyalty behaviors into positive (willingness to pay a price premium and brand evangelism) and negative (schadenfreude and anti-brand actions) dimensions. It then explores how customer engagement and moral identity influence these dimensions in the context of brand competition.

Structural equation modeling was conducted to analyze the main and moderating effects, using survey data obtained from 498 valid responses out of a total of 636 responses from Xiaomi's virtual communities.

The results indicate that customer engagement significantly influences all four dimensions of oppositional brand loyalty. The relationship between customer engagement and brand evangelism is notably stronger among customers with a strong moral identity. Conversely, the effects of customer engagement on schadenfreude and anti-brand actions are attenuated for these customers.

Anchored in theories of brand tribalism, social identity and brand polarization, this study bifurcates oppositional brand loyalty into directions of preference and antagonism, empirically showcasing moral identity's moderating effect. It contributes to the literature on antagonistic loyalty and moral identity, offering strategic insights for companies to navigate schadenfreude and anti-brand actions in online communities.

This study investigated four different economic level areas of China (Shanghai, Shandong, Shaanxi, and Guizhou) to analyze the eastern and western urban and rural media service status at different development stages. This set of data comes from the comparison of regional urban and rural areas and indicates the various aspects of differences in the survey area, including the media use habits, media resources, media consumer demand, evaluation of media services, the role of media in public life, public knowledge level, and so on. On analyzing data comprehensively, one thing can be found that there is a positive correlation between the public media contact degree and the public knowledge level. The media plays an extremely important role in public life and regional public knowledge gap between urban and rural areas exists. Furthermore, this gap is positively correlated to the media resources and media exposure. The trend of media using on mobile phone and computer in urban areas increases significantly greater than in rural areas. Then, how to narrow the urban–rural and regional public knowledge gap and reduce the negative impact of the digital divide will be an important urgent task.

The purpose of this paper is to summarize the advances in grey system theory research and various application achievements in science and engineering. At the same time, it commemorates the 40th anniversary of the birth of grey system theory and the 10th anniversary of Grey Systems–Theory and Application.

Firstly, the innovations of theoretical research in grey system theory were summarized and some of the widely recognized new results are briefly described. By searching and combing the research results of grey system theory in China national knowledge infrastructure (CNKI) database and Web of Science by Institute for Scientific Information (ISI), this paper shows the rapid development trend of grey system theory in the past 40 years, and the successful applications of grey system theory in the fields of social sciences, natural sciences and engineering technologies.

More than 227 thousands literature were found by input 10 phrases such as grey system, grey number and sequence operator etc. in CNKI database. After entering the new century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year and more than 15 thousands papers have been included per year since 2014. Grey system method and model are widely used in physics, chemistry, biology and other fields of natural science, as well as transportation, electric power, machinery and other fields of engineering technology, and a large number of valuable results have been achieved.

It can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development and high-level talent training from tens of thousands of literatures marked with important national science and technology projects and a large number of grey system literatures published by China’s double first-class universities and double first-class discipline construction universities.

Both innovations of theoretical research and practical application play important role in the growth of new theory. The innovations of theoretical research provide methods and tools for practical application, which is conducive to improve application efficiency and broaden application fields. A large number of practical applications needs have become the source of theoretical innovation and the solid background for the birth of theoretical innovation achievements.

This study investigates how the complexity of sentiment in online reviews affects perceived helpfulness. Analyzed over 730,000 reviews from Tripadvisor.com, the research explores how information overload and increased cognitive load impact consumer decision-making.

This study applied the BERT deep learning model to analyze sentiment complexity in online reviews. Based on cognitive load theory, we examined two key factors: the number of attributes mentioned in a review and the variation in sentiment valence of across attributes to evaluate their impact on cognitive load and review helpfulness.

The results show that a higher number of attributes and greater variation in sentiment valence increase cognitive load, reducing review helpfulness. Reviewers’ expertise and review readability further moderate these effects, with complex or expert-written reviews worsening the negative impact.

This research introduces a method for measuring attribute-level sentiment complexity and its impact on review helpfulness, emphasizing the importance of balancing detail with readability. These findings provide a foundation for future studies on review characteristics and consumer behavior.

Research on customer-perceived relationship value (CPRV) in business-to-business (B2B) markets has flourished over the past two decades. This paper aims to meta-analytically take stock of this research stream. It creates a comprehensive overview of the theoretical bases of CPRV research and establishes CPRV in its nomological network. The latter includes relationship benefits and sacrifices, offer quality, trust, switching costs, satisfaction, commitment, loyalty and salience of alternatives. Meaningful boundary conditions of the links to and from CPRV emerge from this research.

To locate suitable primary studies for inclusion in this meta-analysis, a comprehensive literature search was performed. Selection criteria ensured that only suitable B2B samples were included. Meta-analytical random and mixed-effects models were performed on a sample of k = 83 independent data sets from 94 primary publications, with a total n = 22,305.

All constructs are strongly related to CPRV in the expected direction, except for switching costs and salience of alternatives with a moderate relationship and relationship sacrifices with a non-significant mean association. Firm type (manufacturing, non-manufacturing), key informant role (purchaser, non-purchaser), supplier offering type (goods, services) and measurement approach (reflective, formative) function as boundary conditions in the moderation analysis.

This study is one of the very rare meta-analyses that draws exclusively from B2B marketing primary studies. It summarizes and solidifies the current theoretical and empirical knowledge on CPRV in business markets. The novel inclusion of boundary conditions offers additional insight over primary studies and makes for interesting new research directions.

Thriving brand communities are inseparable from engaged members and their word-of-mouth behavior. The purpose of this paper is to investigate which customer experience elevates customer engagement and consequent word-of-mouth intention in online brand communities, and how.

From the perspective of service ecosystem theory, a framework with several hypotheses was proposed. The model was verified with structural equation modeling based on questionnaire data collected from smartphone communities in China.

Empirical results indicate that customer experience promotes community engagement, and further enhances word-of-mouth intention. Furthermore, the mediating effect of community engagement in the relation between customer experience (social support and flow) and word-of-mouth intention has been verified.

This paper informs practitioners about the importance of experience co-creation with community members in brand and community promotion, and provides several implications to encourage more engaged customers with fostering pleasant customer experiences.

This study contributes to the theory of service ecosystem by empirical examination of its several propositions in a brand community context. The paper extends the present theory with the discussion of the mediation effect of community engagement in the continuing value co-creation process.

As the grey systems theory has been widely used in the field of sustainable development (SD) research, in the following, a short literature overview will be put forward, starting from the usage of these theories in the economic development, social inclusion and environmental protection contributions to the evolving process of SD during 2011–2021. The purpose of this paper is to identify some key studies from all the SD areas in which the grey systems can be used in order to open and to bring the researchers to new domains in which they can reveal their interest and in which they can successfully use the methods offered by the grey systems theory.

Using the search engine offered by the Google Scholar and the Web of Science (WoS), a literature review has been performed for the grey systems applications on SD research on both grey relational analysis (GRA) and grey forecasting. In addition, some grey evaluation theories – clustering evaluation models and grey target decision models – have also been presented.

Many grey models are widely used in the field of SD. Compared with other methods such as grey prediction, grey evaluation and decision-making model, GRA technology is the most used method, and the research using this method is more than three times that of all other methods.

The present paper identifies some of the most representative examples in which the grey system theory (GST) has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.

The present paper focuses on the SD applications in which GST has been successfully used, bringing to the reader a general overview on this field and, in the same time, enables new research perspectives.

The paper aims to investigate whether or not a firm’s capital structure can interact with past stock returns to affect future stock returns. Specifically, the authors examine whether or not capital structure can help improve momentum profit.

The authors use the US common stocks data from 1965 to 2022 to empirically examine the impact of capital structure on momentum profit.

When capital structure is measured either as the ratio of debt to asset or the ratio of liability to asset, we all find out that momentum strategies tend to be more profitable for stocks with large capital structure.

Besides documenting the empirical evidence of the impact of capital structure on momentum profit, the authors also present a simple explanation for their empirical results and show that their finding is consistent with the behavioral finance theory that characterizes investors’ increased psychological bias and the more limited arbitrage opportunity when the estimation of firm value becomes more difficult or less accurate.