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The host–guest molecules are often used in various fields and applications. This paper aims to discuss the role of host–guest complexes in the textile industry, focusing on calixarenes as a potential adsorbent for hazardous dyes. The paper begins with an introduction to nanotechnology and its many uses, including textiles.

The risks associated with the utilisation of dyes and its adverse effects on the environment are then also highlighted. This paper also discusses the structure and characteristics of calixarenes and their potential use as an adsorbent to extract toxic metals from aqueous solutions. The paper also explains the molecular structure of calixarenes, especially the ability of its upper and lower rims, which can be altered to yield derivatives with various selectivities for diverse guest ions and small molecules. In addition, the application of various host–guest molecules in the textiles industry to extract dyes also had been discussed.

In conclusion, the paper highlights the essential in establishing a systematic review on the significance of selective adsorbents, such as calixarenes, to isolate particular targets from diverse matrices in the textile industry.

Only discussing several applications for several host–guest molecules.

The paper concisely describes various host–guest molecule applications in the textile industry, with each molecule being elaborated upon in detail.

This research investigation aims to explore the factors that affect purchasing behaviour among consumers in India in the context of green electronic products with the aid of the extended theory of planned behaviour (TPB) by incorporating two additional constructs, namely environmental concern and ethical obligation.

The current research adopted a quantitative methodology, utilising a survey (questionnaire) to gather data from respondents residing in Delhi-NCR, India. A convenience sampling technique was used to select these respondents. Both online and offline modes were used to collect the data. Moreover, to evaluate the theoretical foundation of the investigation, the researchers employed PLS-SEM (partial least square structural equation modelling) on 346 useable samples.

The outcome reveals that attitude, subjective norm and perceived behaviour control (PBC) are significant predictors, supplementary constructs such as environmental concern are not significant predictors, whereas ethical obligation is a substantial predictor of purchase intention. Consumer purchase behaviour, in turn, is influenced by consumer purchase intention.

The outcome of this research could help the country’s legislators formulate policies and programs related to current environmental problems faced by our planet. Marketers could understand the factors that drive consumers' purchasing behaviour towards green electronic products and design effective marketing strategies accordingly. Thus, by enhancing the company’s green image, marketers of green products may potentially increase future purchases, all of which contribute to solving worldwide environmental problems.

This research confirms the usefulness of TPB in understanding Indian consumers' purchasing intention and behaviour towards green electronic products. It further extends the TPB by showing that new components, environmental concerns and ethical obligations influence Indian consumers' purchasing intentions and behaviour. Moreover, prior studies mostly used both additional constructs for green products. Current research used specific types of green products, i.e. green electronic products, as very few studies are available on these products that apply TPB, which makes this study novel. In contrast to previous research that primarily examined purchase intention, this study takes a further step by investigating the connection between intentions and consumers' purchase behaviour. It establishes intention as a precursor to behaviour, specifically towards green electronic products. Additionally, this study introduces new constructs and explores the Indian context, significantly contributing to the existing literature.

Purpose: This study quantitatively assesses the impact of ESG profile on equity value and risk, as well as identifies potential differences occurring in different sectors, based on the data of the Nasdaq Nordic market.

Methodology: To reach this purpose, (i) the stock return and volatility analysis is being conducted (using the methods of paired sample t-test, correlation, etc.), and (ii) panel data models with constant, fixed and random effects are being constructed. The analysis is based not only on the company’s ESG performance but also on a cross-sectoral approach.

Findings: The results revealed that although ESG factors appeared to have a significant impact in most of the constructed models, the impact of these factors varies depending on the sector.

Implications: This research provides a comprehensive and comparative approach to the importance of the ESG profile for investment performance and therefore can be useful both for impact investors making investment decisions in dynamic global financial markets and for companies developing or reforming their ESG strategies.

Limitations: Due to the problem of data availability, the cross-sectoral comparison was performed based on the limited number of sectors. In addition, the limited availability of ESG data in the analysed market did not allow the use of additional methods to assess the impact of ESG.

Future Research: Expanding the data sample and assessing the impact of a company’s ESG profile not only in different sectors but also in different phases of the economic cycle might be the direction for future research.

The purpose of this study is to explore the factors influencing viewers’ engagement intention in travel live streaming (TLS) from a perceived value perspective.

This study used a mixed-methods approach. In Study 1, 48 semistructured interviews were analyzed based on grounded theory and perceived value theory, and a research framework was established to investigate the impact of viewers’ engagement intentions in TLS. In Study 2, partial least squares structural equation modeling (PLS-SEM) was used to empirically validate survey data from 255 TLS viewers.

Through an analysis of the interview content, it was found that the expertise and interaction of the live streamer in TLS as well as the immersion, aesthetics and novelty of the live streaming scene are key influencing factors that affect the engagement of TLS viewers. This finding was confirmed through empirical research.

This research provides practical suggestions for live streamers, TLS platforms and local government to increase viewer engagement. Specifically, it provides methods and directions for the individual improvement of live streamers, further promotes the development and construction of the platform and underscores the importance of government initiatives in policy support and regulatory framework development.

This study focuses on the less-researched field of TLS. Using a mixed-methods approach combining interviews and PLS-SEM, this study explores the key factors that affect the engagement of TLS viewers based on the characteristics of live streamers and live streaming scenes.

Artificial Intelligence (AI) has revolutionized teaching and learning methods in higher education, especially in English language teaching and learning. This chapter contributes to the existing knowledge by exploring how AI has developed within the framework of teaching and learning of English, highlighting the challenges, dangers, and moral issues associated with its application. The typical classroom environment has significantly changed because of the integration of AI-powered tools and platforms in English instruction. Chatbots, automated grading systems, and language learning apps driven by AI have streamlined language education, increasing its effectiveness and accessibility. But these benefits accompany a variety of challenges and worries. Ethical concerns about data privacy, algorithmic biases, and the depersonalization of education arise as AI becomes more deeply ingrained in educational methods. Reliance on AI may inadvertently exacerbate educational disparities as long as learners' access to technology and its advantages remain unequal. In addition, significant thought must be given to the ethical ramifications of AI-generated content as well as the possible loss of human connection in language learning settings. This chapter examines these dangers and challenges and makes the case for a well-rounded strategy that maximizes AI's benefits while minimizing any potential downsides. Together, educators and legislators need to create moral guidelines that balance the potential of AI with human-centered learning experiences. To ensure responsible and fair AI integration and promote an inclusive learning environment that prioritizes students' holistic development while exploiting technology breakthroughs, comprehensive assessment of the associated obstacles, risks, and ethical issues is necessary.

Using energy economically and efficiently is essential to ensure national energy security, reduce greenhouse gas emissions, and preventing climate change. Household appliances consume considerable energy, so choosing energy-efficient is to consuming energy economically and efficiently. The research applies the extended theory of planned behavior (TPB) to empirically investigate factors affecting consumers’ purchase intention toward energy-efficient household appliances (EEHA) in Ho Chi Minh City (HCM). The chapter develops both qualitative and quantitative methods. The qualitative method is conducted with five in-depth interviews to get more consumer insight, verify the research model, and elaborate the questionnaire. The quantitative method with 300 consumers living in HCM is used to address the research question. The primary data are collected via a web-based questionnaire and analyzed by IBM SPSS Statistics 20 and Amos 20. The research indicates that attitude, subjective norm (SN), perceived behavioral control (PBC), past purchase experience (PPE), and economic benefit (EB) have significant positive impacts on consumers’ purchase intention. EB has the most significant impact. Nonetheless, consumers’ purchase intention is not significantly impacted by their level of environmental knowledge (EK). Besides, PPE and EBs positively impact attitude and indirectly affect purchase intention, while EK does not. Based on the empirical results, some recommendations are drawn for policymakers to promote energy-efficient household appliance consumption by citizens, thereby ensuring national energy security and promoting environmental protection. Implications to help manufacturers improve products in the right direction and make wise investment decisions and distributors/retailers to understand consumers in HCM are also suggested.

From the perspective of intangible knowledge resources, this paper clarifies the impact of managerial ability on the performance of overseas investment subsidiaries. It explains the dilemma that the rapid growth of overseas investment by enterprises in emerging markets has not brought about the corresponding expected performance.

This paper uses matching data between the parent companies and overseas subsidiaries of Chinese A-share listed companies from 2007 to 2022 to study the impact of managerial ability on the performance of overseas investment subsidiaries and its mechanism.

The results show that there is a significant positive correlation between managerial ability and the performance of overseas subsidiaries. However, the impact of managerial ability exhibits heterogeneous, which is more significant in non-state-owned enterprises, investments in high-income economies and M&A investment. Managerial ability promotes mainly the performance of overseas subsidiaries through R&D knowledge resources, marketing knowledge resources and internationalization experience; managerial ability significantly impacts the performance of overseas subsidiaries in the case of CEO two-job separation, low CEO shareholding level, the executive team with overseas background and female.

This paper introduces managerial ability as a critical intangible knowledge resource in the study of overseas investment performance, enriching and expanding the connotation and theoretical foundation of managerial ability. It clarifies the impact mechanism of managerial ability on overseas investment performance from three dimensions: R&D knowledge resources, marketing knowledge resources and internationalization experience. It provides new empirical evidence and management enlightenment for promoting overseas investment performance and high-quality development in emerging market countries.

This research aims to investigate the interplay between individuals’ health status and their level of trust in both smart health-care systems and health-care providers and how these factors influence the decision to use such systems.

Drawing upon institution-based trust and affordance theories, the authors developed and empirically examined a research model using a sample from a prominent US university.

The findings reveal that both types of trust, specifically trust in smart health-care systems and trust in health-care providers, positively influence the intention to use these systems. Additionally, the authors identified that health status plays a dual moderating role in this context. It positively moderates the relationship between trust in health-care system providers and the intention to use, suggesting that individuals with better health are more inclined to use smart health-care systems when trust in providers is high. Conversely, health status negatively moderates the relationship between trust in the system and the intention to use it. This implies that trust in the system exerts a more pronounced influence on the intention to use the system among individuals with lower health status. This heightened impact can be attributed to the increased necessity for the system’s benefits among this group.

While the power analyses suggest our sample size is sufficient, caution is warranted when interpreting the study’s conclusions. These results have substantial implications for researchers and providers of smart health-care systems. They underscore the intricate dynamics between trust, health status and technology use, offering valuable insights for future investigations in this domain. Furthermore, they guide the design and implementation of smart health-care systems, emphasizing the need to consider the nuanced influence of health status on trust and use intentions.

Past research has focused on individuals’ trust in understanding the adoption of smart health-care systems; however, it did not consider how individuals’ health status can moderate their trust and intention to adopt such systems. In this study, the authors close this gap by investigating the moderating role of health status in the relationships between two types of trust and intention to use smart health-care systems through the lens of institution-based trust theory and affordance theory.

The 6D pose estimation is a crucial branch of robot vision. However, the authors find that due to the failure to make full use of the complementarity of the appearance and geometry information of the object, the failure to deeply explore the contributions of the features from different regions to the pose estimation, and the failure to take advantage of the invariance of the geometric structure of keypoints, the performances of the most existing methods are not satisfactory. This paper aims to design a high-precision 6D pose estimation method based on above insights.

First, a multi-scale cross-attention-based feature fusion module (MCFF) is designed to aggregate the appearance and geometry information by exploring the correlations between appearance features and geometry features in the various regions. Second, the authors build a multi-query regional-attention-based feature differentiation module (MRFD) to learn the contribution of each region to each keypoint. Finally, a geometric enhancement mechanism (GEM) is designed to use structure information to predict keypoints and optimize both pose and keypoints in the inference phase.

Experiments on several benchmarks and real robot show that the proposed method performs better than existing methods. Ablation studies illustrate the effectiveness of each module of the authors’ method.

A high-precision 6D pose estimation method is proposed by studying the relationship between the appearance and geometry from different object parts and the geometric invariance of the keypoints, which is of great significance for various robot applications.

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the entire life cycle. And this research provides a comprehensive assessment model that incorporates the release of gaseous pollutants and particulate matter during the whole life cycle of C&DW, thereby contributing to a more holistic understanding of its impact on human health.

The research was conducted in two stages. Firstly, the quantitative model framework of pollutants emitted by C&DW was established. Three types of pollutants were considered, namely nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and inhalable particulate matter (PM10). Second, disability-adjusted life year (DALY) and willingness to pay (WTP) assessments were used to provide a monetary quantified health impact for pollutants released by C&DW.

The results show that the WTP value of PM10 is the highest among all pollutants and 8.68E+07 dollars/a, while the WTP value in the disposal stage accounts for the largest proportion compared to the generation and transportation stage. These findings emphasize the importance of PM10 and C&DW treatment stage for pollutant treatment.

The results of this study are of great significance for the management department to optimize the construction management scheme to reduce the total amount of pollutants produced by C&DW and its harm to human health. Meanwhile, this study fills the gap in existing research on the impact assessment of C&DW on human health throughout the whole life cycle, and provides reference and basis for future research and policy formulation.