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As the global emphasis on environmental consciousness intensifies, many corporations claim to be environmentally responsible. However, some merely partake in “greenwashing” – a facade of eco-responsibility. Such deceptive behavior is especially prevalent in Chinese heavy-pollution industries. To counter these deceptive practices, this study aims to use machine learning (ML) techniques to develop predictive models against corporate greenwashing, thus facilitating the sustainable development of corporations.

This study develops effective predictive models for greenwashing by integrating multifaceted data sets, which include corporate external, organizational and managerial characteristics, and using a range of ML algorithms, namely, linear regression, random forest, K-nearest neighbors, support vector machines and artificial neural network.

The proposed predictive models register an improvement of over 20% in prediction accuracy compared to the benchmark value, furnishing stakeholders with a robust tool to challenge corporate greenwashing behaviors. Further analysis of feature importance, industry-specific predictions and real-world validation enhances the model’s interpretability and its practical applications across different domains.

This research introduces an innovative ML-based model designed to predict greenwashing activities within Chinese heavy-pollution sectors. It holds potential for application in other emerging economies, serving as a practical tool for both academics and practitioners.

The findings offer insights for crafting informed, data-driven policies to curb greenwashing and promote corporate responsibility, transparency and sustainable development.

While prior research mainly concentrated on the factors influencing greenwashing behavior, this study takes a proactive approach. It aims to forecast the extent of corporate greenwashing by using a range of multi-dimensional variables, thus providing enhanced value to stakeholders. To the best of the authors’ knowledge, this is the first study introducing ML-based models designed to predict a company’s level of greenwashing.

The purpose of this paper is to give a critical review of the City-State Theory by Wan Chin of Hong Kong. Chin is referred to as the “Father of Hong Kong Independence,” and his two books about the City-State Theory of Hong Kong are popular among the netizens in Hong Kong as a new model of Hong Kong-China (People’s Republic of China (PRC)), in which Hong Kong is considered a city-state and should be fully segregated from the PRC other than in seeking its help in military and diplomatic functions. This paper will aim to review his works with the view of nationalism and nativism theories.

This paper uses nationalism theories with particular focus on Benedict Anderson’s Imagined Communities and theories on American nativism. Then an effort is made to compare these theories against Chin’s arguments on his City-State Theory. This paper also compares his theories against China’s state-nationalism raised by Professors He and Guo.

This paper concludes that Chin advocates a “Hong Kong Nationalism,” a blend of traditional Chinese culture and moral values (he used the term Huaxia), but with a Western influence, into a typical Hong Kong culture. His theory fits into Anderson’s arguments of allowing Hong Kong citizens to imagine Hong Kong as a nation, through the “ramparts” of the city-state. His nativist advocacies also have shown strong nationalistic sentiments. He argues that China should be built in the Hong Kong model before the PRC intervention.

Despite his fame, this paper is the first comprehensive academic paper to review Chin’s theories. This paper introduced the notion of “ramparts” and how this has become the backbone of Chin’s nationalism advocacies.

In this chapter, we utilize qualitative and quantitative data from a yearlong study in four urban Chinese middle schools to investigate the learning environments for girls at these schools; the behavior and performance of girls and boys in these environments; and what factors impact that behavior and performance. This study particularly focuses on socialization through moral education and the examination system as two sources of authority motivating students’ behavior and performance in school. In the analysis, girls attending three co-educational schools are compared with girls attending one single-sex school, and outcomes for girls are also considered alongside those of boys in the co-educational institutions. Findings indicate that although moral education is particularly emphasized by teachers at the all-girls school, female misbehavior and engagement with teachers is no different for girls attending the single-sex school compared to girls in co-educational schools. Furthermore, differences in outcomes between females and males across schools transcend school-level differences for misbehavior and engagement. However, at the same time, girls at all co-educational schools report higher Chinese and English grades compared to their math and science grades, whereas all-girls school students report no such differences in grades. In regression analysis, socialization variables appear to explain more about students’ misbehavior, whereas the desire to progress to higher levels of schooling explains more about grades and engagement with teachers. That said, socialization variables including moral attitude and attachment to teachers matter more for girls’ math and science grades and their engagement with teachers as compared to boys. This research provides a rare comparative look at education for urban Chinese students and offers new insights about what matters most for girls’ behavior and performance in school.

The banking industry plays a key role in China's financial industry. In the past decade, the speed of the development of China's commercial banks has gradually declined. Commercial banks with different ownership structures also have certain differences in terms of operating efficiency, and their monetary policies are often different. Therefore, the authors study the impact of ownership structure on the efficiency of commercial banks under different monetary policies. This study also provides relevant reference opinions with regard to the healthy, sustainable and stable development of China's banking industry.

This paper mainly uses the two-stage data envelope analysis (DEA) model under meta-frontier and group frontier to study the deposit and loan efficiency changes of 16 banks from 2007 to 2014 under ownership structure heterogeneity. Furthermore, the model introduces the balance parameters between deposits and loans, in order to realize the mathematical abstraction description of macro-monetary policy.

First, based on bank efficiency analysis, the paper finds that most banks' loan efficiency is higher than their deposits. Second, the paper concludes that different monetary policies have little effect on bank deposit and loan efficiency, while ownership heterogeneity has a significant impact on bank performance. Finally, through the decomposition of the sources of inefficiency in bank performance, this paper finds that management and technology are two factors that affect the inefficiency of banks.

The authors work contributes to the existing literature in the following ways: First, to the best of the authors’ knowledge, this is the first attempt to use the DEA model to study the relationship between monetary policies and bank supply chain efficiency. The results may provide additional managerial implications for the banking industry from the perspective of monetary policies. The result is helpful in terms of explaining how and why banks should strengthen risk management, as well as how to deal with non-performing loans in management terms and finally, why banks should make financial technology innovations in technology terms.

Due to significant differences between urban and rural areas in terms of geographical environment, building scale, resident culture, social organization and other aspects, the post-disaster recovery and reconstruction models for both exhibit substantial variation. This study identifies critical strategic issues that must be addressed in housing reconstruction in the context of different social structures of urban–rural “integration” and urban–rural “dualization” to achieve the goal of “building back better” in the future.

By taking the experience of the 5.12 Wenchuan earthquake and the Taiwan 9.21 earthquake as a reference, this study provides a thematic analysis and systematic summary of the entire process of post-disaster housing reconstruction.

A successful housing reconstruction process should actively engage disaster-affected populations through participatory institutional design. Providing a diverse housing reconstruction model can coordinate the interests of the government, the market and affected individuals, promoting harmony of residential, productive and ecological functions. However, it can also lead to the division of existing communities.

This research relies on existing literature, government publications, academic studies and news reports, which may carry inherent biases or omissions. Future research can benefit from conducting more extensive and long-term post-reconstruction surveys to assess the sustained impact of recovery efforts while also considering additional data sources to ensure comprehensive and unbiased analyses.

With the support of post-disaster reconstruction policies, diverse changes in land use can lead to urban and rural spatial pattern reform and sustainable regional development, providing a reference for formulating optimal strategies.

This study carries significant societal implications by addressing critical strategic issues in housing reconstruction within varying urban–rural social structures. It highlights the importance of engaging affected populations through participatory design and harmonizing government, market and individual interests. The research introduces strategies for activating rural construction land quotas and creating new funding sources, promoting sustainable regional development. Its findings contribute to post-disaster reconstruction models, offering valuable insights for policymakers and stakeholders, ultimately leading to more effective and inclusive recovery efforts and benefiting disaster-prone areas worldwide.

This research primarily investigates the market circulation patterns of urban and rural land under different social structures, delves into the strategies for sources of housing reconstruction funding, along with an assessment of their effectiveness.

Based on the typical service supply chain (SSC) structure, the authors construct the model of e-tailing SSC to explore the coordination relationship in the supply chain, and big data analysis provides realistic possibilities for the creation of coordination mechanisms.

At the present stage, the e-commerce companies have not yet established a mature SSC system and have not achieved good synergy with other members of the supply chain, the shortage of goods and the greater pressure of express logistics companies coexist. In the case of uncertain online shopping market demand, the authors employ newsboy model, applied in the operations research, to analyze the synergistic mechanism of SSC model.

By analyzing the e-tailing SSC coordination mechanism and adjusting relevant parameters, the authors find that the synergy mechanism can be implemented and optimized. Through numerical example analysis, the authors confirmed the feasibility of the above analysis.

Big data analysis provides a kind of reality for the establishment of online SSC coordination mechanism. The establishment of an online supply chain coordination mechanism can effectively promote the efficient allocation of supplies and better meet consumers' needs.

The authors examined the influence of perceived value on consumer attitude and purchase intention (PI) and the relationship between attitude and PI towards sustainable luxury products (SLP) in China.

An online survey was conducted with 935 consumers of luxury fashion in mainland China. Structural equation modelling was applied to measure and analyse the relationship between values (i.e. hedonic values, social values, and value for money) and consumer attitude and PI.

Consumers' multidimensional values positively affected their attitude. Social values and value for money had a significant positive effect on PI towards SLP. However, hedonic values had no effect on PI.

The sample was drawn from first-tier cities in China, and the results cannot be generalised. The authors examined three dimensions of consumption values. Future research should consider additional markets, values, and influencing factors.

Luxury companies should understand Chinese consumers' diverse values and develop sustainable products that meet consumers' principles. These principles increase the perceived value of the products and thereby guide luxury brands to make marketing strategies to increase sales.

This is the first empirical study to use the theory of perceived value scale (PERVAL) to understand consumer behaviour regarding SLP in China.

The purpose of this study is to undertake an evaluation of the resilient capacity of the infrastructure systems in the city of Wuhan. This evaluation focuses on the ability of the infrastructure to cope with extreme weather from multiple dimensions and to propose effective interventions against such risks.

This research draws on a review and synthesis of the theory of resilience and adopts the literature induction method to build an evaluation index for five urban systems, namely: roads; water supply and drainage; energy and power; urban disaster reduction; and communications. Index data from the period of 1990–2019 are combined with the views of experts from Wuhan and analyzed using principal component analysis (PCA) to calculate the weightings of the five urban systems. A fuzzy comprehensive evaluation method is then used to investigate the resilient capacity of these five urban infrastructure systems in the city.

Generally, the results show that the resilience of the infrastructure systems in Wuhan are at a high level. Based on the results, the communications and roads systems are found to have higher levels of resilience, while the disaster mitigation system is found to have a relatively low level of resilience. Recommendations are suggested to help improve resilience and prioritize investments in the development of the city's infrastructure systems.

The development of these specific indicators and quantitative requirements have not been studied in detail, so a more comprehensive, systematic evaluation of quantitative indicators and methods of urban infrastructure resilience is still required. In addition, the research on the resilience of urban infrastructure under extreme weather is still in its infancy, and it is essential to further increase the quantitative assessment of the resilience of urban infrastructure under construction. This will also be indispensable information in the subsequent implementation of a resilient planning process.

This research builds a rigorous and reliable evaluation model that avoids any subjective bias in the results and represents a new approach to evaluate the resilience of the infrastructure systems in the city of Wuhan, which could be applied to other cities.

Contextual cues have become a hot research topic in the field of mobile consumer behavior, owing to the continuous rise of digital marketing. However, the complex online shopping scene makes it challenging to directly identify the association between the characteristics of contextual cues and consumer behavior. Presently, few studies have only systematically extracted and refined the types and characteristics of contextual cues. The purpose of this study is to explore the types and mechanisms of contextual cues in online shopping scenarios.

This study uses the word2vec algorithm, grounded theory and co-occurrence cluster method, along with online shopping word-of-mouth (WOM) text and consumer behavior theory, in order to explore different types of contextual cues and its efficiency from 5,619 comment corpus.

This study puts forward the following conclusions. (1) From the perspective of online shopping, contextual cues comprise aesthetic perception cues, value perception cues, trust-dependent cues, time perception cues, memory attention cues, spatial perception cues, attribute cues and relationship cues. (2) Based on the online shopping scenarios, contextual cues and their interaction effects exert an effect on consumer satisfaction, recommendation, purchase and return behavior.

The study conclusions are helpful to further reveal the deep association between contextual cues and consumer behavior in the process of online shopping, thus providing practical and theoretical enlightenment for enterprises to not only effectively reshape the scene but also promote the consumers' active purchase behavior.

This study aims to determine the key indicators affecting the resilience of the construction supply chain to flooding and calculate the resilience of the urban construction supply chain in three cases city.

This study combines expert opinions and literature review to determine key indicators and establish a fuzzy EWM-GRA-TOPSIS evaluation model. The index weight was calculated using the entropy weight method, and GRA-TOPSIS was used for comprehensive evaluation.

The results of the study show that the three cities are ranked from the high to low in order of Hangzhou, Hefei and Zhengzhou.

The innovative method adopted in this study comprising EWM-GRA-TOPSIS reduced the influence of subjectivity, fully extracted and utilized data, in a way that respects objective reality. Further, this approach enabled the absolute and relative level of urban construction supply chain resilience to be identified, allowing improvements in the comprehensiveness of decision-making. The method is relatively simple, reasonable, understandable, and computationally efficient. Within the approach, the entropy weight method was used to assign different index weights, and the GRA-TOPSIS was used to rank the resilience of the construction supply chain in three urban cities. The development of resilience provides a robust decision-making basis and theoretical reference, further enriching research methods, and having strong practical value. The study serves to improve risk awareness and resilience, which in turn helps to reduce losses. It also provides enhanced awareness regarding the future enhancement of supply chain resilience for urban construction.