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The purpose of this paper is to investigate the moderating role of cultural factors (concern for face and stability of attribution) in the relationships among service recovery quality, postrecovery satisfaction and repurchase intention. Based on the politeness theory, this paper proposes a theoretical model for understanding how concern for face and stability of attribution may affect collectivists’ consumption behavior.

Data were collected in a field survey of 600 Hong Kong consumers who had experienced a telecommunications service failure. Partial least squares structural equation modeling (PLS-SEM) was used to test the theoretical hypotheses.

A cultural factor of concern for face is found to negatively moderate the relationship between service recovery quality and postrecovery satisfaction. Face also positively influences the relationship between postrecovery satisfaction and repurchase intention. Another cultural factor, stability of attribution, is found to negatively moderate the relationship between service recovery quality and postrecovery satisfaction and to negatively moderate the relationship between postrecovery satisfaction and repurchase intention.

This study contributes to the understanding of the relevance of concern for face and stability of attribution in collectivists’ consumption behavior. The findings have significant implications for managers in a position to exploit the cultural value mechanisms of collectivist consumers.

To the best of the authors’ knowledge, this has been the first research to examine the impact of concern for face and stability of attribution among service recovery quality, postrecovery satisfaction and repurchase intention.

As technology increasingly integrates into the restaurant industry, avatar servers present a promising avenue for promoting healthier dining habits. Grounded in the halo effect theory and social comparison theory, this study aims to delve into the influence of avatars' appearance, humor and persuasion on healthier choices and customer satisfaction.

This paper comprises three experimental studies. Study 1 manipulates avatar appearance (supermodel-looking vs normal-looking) to examine its effects on perceived attractiveness, warmth and relatability. These factors influence customer satisfaction and healthy food choices through the psychological mechanisms of social comparison and aspirational appeal. Studies 2 and 3 further refine this theoretical model by assessing the interplay of appearance with humor (presence vs absence) and persuasion (health-oriented vs beauty-oriented), respectively.

Results suggest that avatars resembling supermodels evoke stronger aspirational appeal and positive social comparison due to their attractiveness, thus bolstering healthier choices and customer satisfaction. Moreover, humor moderates the relationship between appearance and attractiveness, while persuasion moderates the effects of appearance on social comparison and aspirational appeal.

This research bridges the halo effect theory and social comparison theory, offering insights enriching the academic discourse on technology’s role in hospitality.

The findings provide actionable insights for managers, tech developers and health advocates.

Despite its significance, avatar design research in the hospitality sector has been overlooked. This study addresses this gap, offering a guideline for crafting attractive and persuasive avatars.

Motivated by the significant role of uncertainty in affecting investment decisions and China's economic leadership in Asia, this paper investigates the predictive role of exposure to Chinese economic policy uncertainty at the individual stock level in large Asian markets.

We estimate the monthly uncertainty exposure (beta) for each stock and then employ the portfolio-level sorting analysis to investigate the relationship between the China’s uncertainty exposure and the future returns of major Asian markets over multiple trading horizons. The raw returns of the high-minus-low portfolios are then adjusted using conventional asset pricing models to investigate whether the relationship is explained by common risk factors. Finally, we check the robustness of the portfolio-level results through firm-level Fama and MacBeth (1973) regressions.

Applying portfolio-level sorting analysis, we reveal that exposure to Chinese uncertainty is negatively related to the future returns of large stocks over multiple trading horizons in Japan, Hong Kong and India. We discover this is unexplained by common risk factors, including market, size, value, profitability, investment and momentum, and is robust to the specification of stock-level Fama and MacBeth (1973) regressions.

Our analysis demonstrates the spillover effects of Chinese economic policy uncertainty across the region, provides evidence of China's emerging economic leadership, and offers trading strategies for managing uncertainty risks.

The findings of the study significantly improve our understanding of stock return predictability in Asian markets. Unlike previous studies, our results challenge the leading role of the US by providing a new intra-regional return predictor, namely, China’s uncertainty exposure. These results also evidence the continuing integration of the Asian economy and financial markets. However, contrary findings for some Asian markets point toward certain market-specific features. Compared with market-level research, our analysis provides deeper insights into the performance of individual stocks and is of particular importance to investors and other market participants.

The COVID-19 pandemic had amplified feelings of isolation and alienation, particularly among school-aged children. The pandemic-related social distancing policies had led to a marked decline in students’ physical and social well-being, potentially fostering a sense of apathy among them. Upon returning to the “normal” in late 2022, a Chinese martial arts Outreach Program was launched in over 50 schools in Hong Kong, involving the entire student body and teachers at each school. This paper aims to explore the potential role of sports in enhancing student well-being in post-COVID times and as a societal response to the evolving sociopolitical landscape in Hong Kong, using the program as a case study.

Using ethnographic immersion, participant observation and semi-structured interviews, the study examines how the program sought to overcome the challenges students were facing during the pandemic through Chinese martial arts instruction and the teaching of traditional Chinese values.

The findings of this study reveal that the objectives of the Chinese martial arts Outreach Program not only centered on students’ immediate personal well-being but also entailed broader goals of advancing national education. The program’s design, which integrated sports and national education, emerged as a response to the pandemic and the sociopolitical transformations in Hong Kong, particularly following the implementation of the National Security Law.

The findings will deepen the understanding of how sport has been politicized as a means to respond to the societal changes in Hong Kong, especially after the pandemic.

Polycentricity has become a crucial spatial development strategy. This paper aims to clarify the impact and mechanism of polycentric spatial structure on the urban–rural income gap, provide better countermeasures to narrow it and make development suggestions for cities of different scales.

Based on the panel data of Chinese cities from 2010 to 2019, this paper empirically examines the specific impact of polycentric spatial structure on the urban–rural income gap by utilizing a two-way fixed effects model.

The results show that the polycentric spatial structure is favorable for reducing the urban–rural income gap, and upgrading the industrial structure and improving transportation infrastructure are important mechanisms. Moreover, the role of polycentric spatial structure is more significant in large cities. However, in small and medium-sized cities, the role of polycentric spatial structure is not significant.

The limitations of this study include two main aspects. One is that this paper only analyzes the mediating effect of industrial structure and transport infrastructure, and we do not examine other mechanisms. The second is that due to data availability, this paper uses data from 2010 to 2019, and the research period can be further extended in future studies.

This study has policy implications for building a polycentric city network and also provides insights into the planning of cities of different scales.

The polycentric spatial structure is important for narrowing the urban–rural income gap, especially in large cities. Improvement of transportation infrastructure and upgrading of industrial structure are important mechanisms. However, the polycentric spatial structure does not play a significant role in small and medium-sized cities. Thus, the polycentric spatial structure is not suitable for every kind of city. Relevant departments should carry out urban planning according to local conditions.

As a critical concern of urban planning, polycentricity significantly affects the urban–rural income gap. Relevant studies have analyzed the impact of polycentric spatial structure on regional income disparity, and few studies have focused on the relationship between polycentric spatial structure and the urban–rural income gap. Using city panel data in China, this paper explores the impact of polycentric spatial structure on the urban-rural income gap. Meanwhile, we test the mediating role of transportation infrastructure improvement and industrial structure upgrading. This study broadens the analysis of the urban–rural income gap’s influencing factors and provides a path reference for narrowing the urban–rural income gap.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

Industry 4.0 (I4.0), the Fourth Industrial Revolution, integrates Big Data analytics, blockchain, cloud computing, digitisation and the Internet of Things to enhance supply chain (SC) activities and achieve sustainable growth through dynamic capabilities (DCs). This approach equips businesses with the necessary tools to optimise their operations and remain competitive in a dynamic business environment. The value proposition of a business encompasses a wide range of activities that add value at each stage. By leveraging DCs, a firm can achieve innovation, gain a competitive advantage and enhance its adaptability. Conversely, effective value chain management can amplify the influence of a firm's DCs on SC sustainability, by reducing waste, optimising resource utilisation and fostering strategic partnerships. This mutually beneficial connection takes the form of a dynamic interaction in which I4.0 technologies act as a catalyst to help organisations become more resilient, adaptive and responsive. The adoption of these technologies denotes a comprehensive approach to business shift, not merely technical integration. I4.0 has an impact on several organisational disciplines outside of manufacturing, from automation and efficiency advantages to quality enhancements. This chapter offers an extensive literature review to explore the level of SC sustainability that a business can achieve by combining its DCs and implementing strategic I4.0 adoption. The function of value chain management in moderating the effects of I4.0 and DCs on SC sustainability is also assessed. This study proposes a theoretical model that is grounded in the insights extracted from the literature review.

This paper evaluates intellectual capital (IC) within entrepreneurial environments, towards conceptualising the sequential role of education, its institutions in practice, and wider ecosystems. Well-established attributes of entrepreneurialism, such as idea generation, problem-solving, market expertise and risk awareness are commensurate to that of expected IC practices within enterprising organisations. However, scarce research has been undertaken concerning the confronting of IC practices and activities across collaborative, and sequential, multistakeholder partnerships and activities. This includes alignment to distinct stages of developmental entrepreneurialism inclusive of education and ecosystem support: knowledge exchange and training; mentoring the emergence of the start-up; strategically timing scale-ups; and continued navigation within networks while enduring change.

An integrative review of the relationship between IC, entrepreneurs and new ventures is undertaken to evaluate developmental IC practices as per this paper’s highlighted sequential stages, within entrepreneurial environments and organisational contexts.

Significant roles and responsibilities are evident among collaborative sectors, benefitting the entrepreneurial process and heightening the importance and emergence of IC within entrepreneurial environments. Exposure to enterprise-specific education and support emphasises the developmental human capital process of progressing and protecting ideas and ventures. Latterly, ecosystem engagement leads to consistent intrapreneurialism amongst employees and new venture partners, influencing structured IC systems and enterprising cultures and relational aspects of responsive branding of commercial activity and increased market agility.

Through presenting an attribute-based framework, this paper conceptualises sequential multistakeholder intervention of IC practices and organisational considerations within institutions, as well as guiding the developmental role of education in emboldening individuals and organisations through building IC and evidencing entrepreneurial thinking.

We aim to determine the subsidy mechanism that can help participants of green supply chain financing (GSCF) maximize their benefits. Then, the optimal subsidy mechanism is designed to promote the development of GSCF.

To better understand the impact of different government subsidy measures on the optimal strategy for GSCF, we treat the motivation of the participants in the supply chain as a cost–benefit decision-making process. Then, a Stackelberg game model is developed that accounts for consumers' green preferences and government subsidies. In addition, the factors influencing supply chain members' earnings are analyzed via computational experiments.

(1) When consumers 2019 green sensitivity reaches a certain threshold relative to that of core enterprises (CEs), the optimal order quantity of these enterprises is greater when the government subsidizes small and medium-sized enterprises (SMEs). Conversely, the optimal order quantity is greater when CEs are subsidized. (2) When the government subsidizes CEs, financial institutions (FIs) and SMEs at the same time, these forms of subsidies have a cumulative effect on the supply chain, and the supply chain and all participants generate the highest earnings.

We analyze the benefits of each participant of GSCF under different government subsidies and then determine the optimal subsidy measures.

The purpose of this study is to evaluate the tea stem natural dye was extracted from tea stem waste and applied to dyeing silk fiber, after which the properties of dyed samples were tested and analyzed.

The dyeing process was optimized using the response surface methodology (RSM) approach. Dyeing temperature, pH and time were chosen as variables and the color difference value as a response. The properties of dyed samples were tested and analyzed.

The optimized dyeing process was as follows: dyeing temperature 70°C, pH 3.5 and time 110 min. The K/S and color difference value of silk fiber dyed with the optimal process dye enzymatic oxidation with laccase was 1.4 and 27.8, respectively. The silk fiber dyed has excellent color fastness, antioxidant and antibacterial property, which greatly increases the added value of the dyed products. Furthermore, the optimized dyeing process did not significantly affect the strength properties and handle of the silk fiber.

Researchers have not used statistical analysis to optimize the process of dyeing process of silk fiber by tea stem natural dye enzymatic oxidation with laccase using response surface methodology. Additionally, this dyeing process was a low-temperature dyeing process, which not only saves energy consumption and reduces silk fiber damage but also obtains superbly dyeing results and biological functional properties, achieve the effects of waste utilization and clean dyeing.