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The Metaverse, an emergent Web 3.0 platform, offers users immersive virtual reality experiences. This study employs a case study approach to explore the concept of sustainability within the Metaverse. It examines the environmental, social, and economic implications of virtual interactions and the role of sustainable technologies in shaping user behavior and virtual economies. Through selected case studies, the research provides insights into the potential and challenges of integrating sustainable practices in the Metaverse, with implications for stakeholders ranging from policymakers to end-users.

This paper aims to investigate the relationship between tourism efficiency at the city level and the quality of life (QOL) of residents. It focuses on assessing whether more efficient tourism cities in China, from an economic standpoint, also offer a higher quality of life for their residents.

A sample of 40 Chinese cities from 2010 to 2019 is analyzed. The study first employs Data Envelopment Analysis to construct a production technology and estimate the technical tourism efficiency of each city. Subsequently, a nonparametric statistical test of independence is applied yearly to explore potential relationships between the cities’ tourism efficiency rankings and their residents’ QOL. This latter is measured by constructing an index for each city following the OECD framework.

The findings of the study are mixed, revealing no clear relationship between tourism efficiency and residents’ quality of life within the analyzed period. This suggests a complex interplay between economic efficiency in tourism and the broader social and environmental factors contributing to QOL.

This study enhances the literature on tourism efficiency by investigating the relationship between tourism efficiency and QOL, an aspect frequently overlooked in efficiency evaluations. Our approach offers a comprehensive understanding of the interplay between economic performance in the tourism sector and the social well-being of city populations. To the best of the authors’ knowledge, this is the first instance where such a relationship has been explored at the city level within the Chinese context.

This study aims to analyse what factors influence ethnic minority group (EMG) college students’ attitudes towards promoting online start-ups and how their different attitudes impact their final online start-up behaviours on the live streaming platform. Based on the COM-B behaviour changing model and the theory of liberal and conservative attitudes, the research model has been established in this study, and it divides influencing factors into the environmental opportunity unit and personal capability unit.

To test relationships among the environmental opportunity, personal capability and personal attitude units, the partial least squares path modelling and variance-based structural equation modelling have been applied on the SmartPLS. Meanwhile, this study considers the regional difference between China’s developed and less-developed regions and promotes multi-group analysis based on it.

Research results show that the online start-up opportunity and capability positively affect EMG college students’ liberal attitudes but reduce EMGs’ conservative attitudes. Meanwhile, this study finds four significant differences, such as the path between conservative attitude and EMG students’ online start-up behaviour and the path between online start-up capability and conservative attitude.

This paper analyses the relationship between influencing factors and EMG students’ online start-up attitudes based on the COM-B behaviour changing model, contributing to the theoretical implications. Meanwhile, considering the impact of regional differences, this paper promotes the multi-group analysis and compares EMG college students from developed regions and others from less-developed areas.

Mental health issues negatively affect employees’ quality of life and employers’ bottom line. Consequently, ensuring well-being in the workplace is becoming a high priority from a strategic human resource management perspective. Drawing on basic psychological needs theory, we propose that proactive personality will be related to mental well-being through satisfaction of basic psychological needs. In addition, drawing on the trait-by-trait interactions perspective, we expect the mediated relationship to be moderated by conscientiousness.

We tested our research model using data collected from 185 employees using a three-wave time-lagged design.

Proactive personality related to mental well-being indirectly, via psychological need satisfaction, and this indirect relationship was stronger at higher levels of conscientiousness.

Ensuring mental well-being of employees is critical to achieving a competitive advantage. Support for the mediating role of need satisfaction suggests that organizations can tailor interventions aimed at influencing the more malleable mediating variable, psychological need satisfaction, compared to relatively stable personality traits.

We contribute to theory by testing a theoretical explanation for how and why personality affects mental well-being. Another theoretical contribution is demonstrating that mental well-being results from a combination of personality traits, with a trait-by-trait perspective fitting the data better than an unconditional trait model.

The purpose of this study is to investigate starch mucor (SM) in potassium iodide (KI) as corrosion inhibitor of aluminium in hydrochloric acid (HCl) medium.

The SM in KI was characterized by gravimetric, scanning electron microscopy, electrochemical impedance spectroscopy measurements, potentiodynamic polarization and gas chromatography-mass spectrometer techniques. The inhibition efficiency was optimized using response surface methodology.

The result revealed that the inhibitor inhibited corrosion at a low concentration with the rate of inhibition increasing as the concentration of the inhibitor increased. The inhibition efficiency increases as the temperature was increased with slight incorporation of the inhibitor (SM in KI). This indicates that the corrosion control is both inhibitor (SM in KI) and temperature dependent.

The research results can provide the basis for using SM in KI as corrosion inhibitor of aluminium in HCL medium. Mixed-type inhibitor nature of SM was proved by cathodic and anodic nature of the polarization curves.

This paper aims to study the physical and chemical characteristics of inkjet titanium dioxide inks for cotton fabric digital printing.

Different dispersing agents through the reaction of glycerol monooleate and toluene diisocyanate were prepared and then performed by using three different polyols (succinic anhydride-modified polyethylene glycol PEG 600, EO/PO Polyether Monoamine and p-chloro aniline Polyether Monoamine), to obtain three different dispersing agents for water-based titanium dioxide inkjet inks. The prepared dispersants were characterized using FTIR to monitor the reaction progress. Then the prepared dispersants were formulated in titanium dioxide inkjet inks formulation and characterized by particle size, dynamic surface tension, transmission electron microscopy, viscosity and zeta potential against commercial dispersants. Also, the study was extended to evaluate the printed polyester by using the prepared inks according to washing and crock fastness.

The obtained results showed that p-chloro aniline Polyether Monoamine (J) and succinic anhydride modified polyethylene glycol PEG 600 (H) dispersants provided optimum performance as compared to commercial standards especially, particle size distribution data while EO/PO Polyether Monoamine based on dispersant was against and then failed with the wettability and dispersion stability tests.

These ink formulations could be used for printing on cotton fabric by DTG technique of printing and can be used for other types of fabrics.

The newly prepared ink formulation for digital textile printing based on synthesized polyurethane prepolymers has the potential to be promising in this type of printing inks, to prevent clogging of nozzles on the printhead and to improve the print quality on the textile fiber.

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

This paper aims to define the efficiency achieved by urban transport companies in Spain concerning the resources they use, considering the type of management used for implementation, public-private, and size.

This study consisted of an analysis of the efficiency of 229 public-private urban transport operators during the period 2012–2021 using Data Envelopment Analysis, the Malmquist Index and inference estimators to determine productivity, efficiency change into Pure Technical Efficiency Change (PTECH), and scale efficiency change.

Based on the efficiency analysis, the authors concluded that of the 229 companies studied, more than 35 were inefficient in all analysed periods. Considering the sample used, direct management is considered significantly more efficient. It cannot be concluded that the size of these companies influences their efficiency, as the data show unequal development behaviours in the studied years.

This study provides arguments on whether there is a significant difference between the two types of management in the urban transport sector. It also includes firm size as a study variable, which has not been previously considered in other studies related to urban transport efficiency. Efficiency should be a crucial factor in determining funding allocation in this sector, as it encourages operators to optimize and improve their services.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This research paper investigates the efficacy of artificial intelligence (AI)-powered Chatbot's in enhancing user engagement and satisfaction within various contexts. As organizations increasingly deploy Chatbot's to interact with users, understanding their impact on user experience becomes imperative. The study employs Smart partial least squares (PLS) as a robust analytical tool to assess the multifaceted dimensions of AI-powered Chatbot interactions. The research focuses on user engagement, examining the Chatbot's ability to captivate users and sustain their interest throughout interactions. Additionally, user satisfaction is explored to gauge the overall effectiveness of the Chatbot in meeting user expectations. The proposed model integrates key variables, including the Chatbot's responsiveness, conversational abilities, and problem-solving capabilities, to comprehensively evaluate its impact. The methodology involves collecting data from diverse user groups to ensure a representative sample. Smart PLS, a powerful structural equation modeling technique, is employed to analyze the relationships between the identified variables. The findings are expected to contribute valuable insights into the factors influencing user engagement and satisfaction in the context of AI-powered Chatbots. The implications of this research extend beyond theoretical understanding, offering practical recommendations for organizations seeking to optimize their Chatbot implementations. By leveraging Smart PLS, this study aims to provide a nuanced understanding of the intricate dynamics involved in AI-powered Chatbot interactions, ultimately guiding the development and deployment of more effective and user-centric conversational agents.