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The study explores how mobile governance affects the administrative burden on older adults, focusing on learning, psychological and compliance costs.

Using attribution theory, the research employs a quantitative research design, utilizing surveys to gather data from 516 older adults across three cities in China: Quzhou, Wuhan and Shanghai. The study examines how intrinsic factors and extrinsic factors of m-government interfaces impact older adults’ administrative burden.

Perceived complexity increases learning, psychological and compliance costs for older adults. Personalization and high-quality information decrease these costs, enhancing user satisfaction. Visual appeal decreases anxiety and psychological costs.

This research links attribution theory with m-government’s administrative burden on older adults, offering new insights into optimizing m-government to serve older adults better.

In the modern financial landscape, Artificial Intelligence (AI) is gaining prominence, offering significant economic advantages. This research paper aims to investigate the impact of Behavioural Biases (BB) such as Overconfidence Bias (OCB), Fear of Missing Out (FOMO), Herding Bias (HB) and Regret Aversion Bias (RAB) on Investment Decision-Making (IDM). Additionally, it explores how the AI-led Adoption of Digital Advisory Services (ADAS) moderates these biases among Gen Z investors in India.

The study utilized a convenience sampling method, gathering 457 responses from Gen Z investors in India through an online survey questionnaire. The data was analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM).

The results confirm a significant relationship between OCB, FOMO, HB and RAB on IDM. The study also found that ADAS significantly moderated the relationship between FOMO and IDM, as well as between HB and IDM. However, the moderation effect of ADAS was not supported for the relationships between OCB and IDM, and RAB and IDM.

This research offers valuable insights for academics, individual investors, fintech companies and policymakers. It highlights how behavioural biases affect IDM and underscores the importance of AI-enabled digital services in helping Gen Z investors recognize and manage these biases. Policymakers can use these insights to establish standards for AI use, ensuring regulatory compliance and promoting ethical conduct in AI-driven investment decisions.

The novelty of this study lies in its conceptual approach, particularly in examining the moderation role of ADAS in addressing behavioural biases among Gen Z investors.

This study investigates the factors influencing the saving behaviour of Chinese Generation Z (Gen Z) through Internet wealth management (IWM) services. It adopts the unified theory of acceptance and use of technology (UTAUT) as the theoretical framework, focusing on key determinants such as performance expectancy (PE), effort expectancy (EE), social influence (SI) and facilitating conditions (FC). The research also explores the mediating role of the intention to save via IWM and its subsequent influence on actual saving behaviour.

The hypotheses were assessed using data collected from 274 Gen Z users in China. The data were analysed using the partial least squares structural equation modelling.

The results suggest that the formation of intention among Gen Z to save through IWM services is directly affected by factors such as PE, EE, SI and FC. Intention to save via IWM positively influences actual saving behaviour. Mediation analysis further confirms the mediating role of intention to save via IWM in these relationships.

The findings have direct implications for financial institutions and policymakers engaged in promoting the practice of saving via IWM services among Gen Z, thereby fostering a culture of proactive financial management and encouraging saving behaviour.

The study contributes to the existing literature by being among the first to examine Gen Z’s IWM adoption as a personal saving tool through the theoretical lens of the UTAUT.

This paper aims to investigate the effects of macroprudential policies in Brazil on the banking sector.

Autoregressive models with distributed lags (ADL) are estimated to verify whether such regulatory measures affected the volume of credit, the banking spread and the concentration index of the five largest Brazilian banks. In addition to the variables of interest, monthly macroeconomic data from 2011 to 2021 are considered.

Our results suggest that macroprudential policies are effective in reducing credit volume. More importantly, our findings highlight two possible adverse effects of these instruments. Firstly, macroprudential tightenings are associated with increases in bank spread. Secondly, tightening measures contribute to increasing bank market concentration.

These findings are useful for the scientific literature that investigates the regulation of the financial system by providing empirical evidence of the effects of Brazilian macroprudential measures on investors, policymakers and other economic agents whose well-being is associated with economic stability.

This study aims to investigate how fear of missing out (FOMO) mediates the relationship between cryptocurrency adoption intention and investment behavior among young Indians, using the extended unified theory of acceptance and use of technology.

The data were collected by using survey items on cryptocurrency adoption intention, investment behavior and FOMO derived from existing literature on information systems and cryptocurrencies. A total of 384 Indian participants completed an online questionnaire. The collected data was analyzed using PLS-SEM.

The findings indicate that facilitating conditions, social influence, effort expectancy and price value play important roles in cryptocurrency adoption. All hypothesized paths were significant, except for perceived risk. Furthermore, the study highlights that FOMO acts as a mediator between adoption intention and investment behavior.

This study makes a valuable addition to the literature by empirically exploring the influence of FOMO on the adoption of cryptocurrencies for investment purposes. The results provide valuable insights to crypto developers and exchanges regarding the diffusion of adoption in emerging markets. In addition, policymakers can gain meaningful insights into the influence of government regulations and FOMO on impulsive cryptocurrency behavior.

The purpose of this study is to examine factors influencing consumers’ intention to purchase Halal cosmetics through the lens of theory of consumption values (TCV).

This study employed a quantitative research methodology, collecting data from 185 respondents through an online questionnaire. The participants, selected via purposive sampling, were all current purchasers of cosmetics. The data were analyzed using partial least square structural equation modeling (PLS-SEM) with the assistance of IBM SPSS and SmartPLS software.

This research reveals that emotional value is the most substantial value predictor, followed by epistemic value, conditional value and functional value. Further, the moderation analysis shows that the effect of conditional value is strengthened when the consumer are from a higher social class.

This study reveals that consumption values with context-specific attributes directly impact consumer purchase intentions towards Halal cosmetics, while social class acts as a significant catalyst. This offers a fresh perspective that mitigates the traditional misconceptions about Halal cosmetics among Malaysians, highlighting the complexity and resilience of consumer adoption in this innovative sector.

This paper aims to establish a lattice Boltzmann (LB) method for solid-liquid phase transition (SLPT) from the pore scale to the representative elementary volume (REV) scale. By applying this method, detailed information about heat transfer and phase change processes within the pores can be obtained, while also enabling the calculation of larger-scale SLPT problems, such as shell-and-tube phase change heat storage systems.

Three-dimensional (3D) pore-scale enthalpy-based LB model is developed. The computational input parameters at the REV scale are derived from calculations at the pore scale, ensuring consistency between the two scales. The approaches to reconstruct the 3D porous structure and determine the REV of metal foam were discussed. The implementation of conjugate heat transfer between the solid matrix and the solid−liquid phase change material (SLPCM) for the proposed model is developed. A simple REV-scale LB model under the local thermal nonequilibrium condition is presented. The method of bridging the gap between the pore-scale and REV-scale enthalpy-based LB models by the REV is given.

This coupled method facilitates detailed simulations of flow, heat transfer and phase change within pores. The approach holds promise for multiscale calculations in latent heat storage devices with porous structures. The SLPT of the heat sinks for electronic device thermal control was simulated as a case, demonstrating the efficiency of the present models in designing and optimizing SLPT devices.

A coupled pore-scale and REV-scale LB method as a numerical tool for investigating phase change in porous materials was developed. This innovative approach allows for the capture of details within pores while addressing computations over a large domain. The LB method for simulating SLPT from the pore scale to the REV scale was given. The proposed method addresses the conjugate heat transfer between the SLPCM and the solid matrix in the enthalpy-based LB model.

New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.

Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.

The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.

The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.

The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.

This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.

This paper investigates the interplay among Finance-Accounting Digitalization (FAD), Advanced Finance-Accounting System (AFAS) and Accounting 2.0 and FinTech (AFT). It aims to elucidate how FAD impacts the adoption of AFAS, the evolution of AFT, and the ensuing sustainable evolution of finance and accounting practices.

A comprehensive survey was conducted from 2021 to 2023, involving 500 companies in Kosovo, spanning various sectors and sizes. The data were meticulously analyzed using SPSS and AMOS software, using structural equation modeling (SEM) to assess hypotheses, model fit and direct and indirect effects.

Significant relationships emerged between FAD, AFAS and AFT, highlighting the importance of computerized financial and accounting systems, the role of AFAS in achieving financial goals and the accessibility and adaptability of accounting data. In particular, the SEM analysis underscored a robust positive correlation between FAD and AFT, highlighting the transformative potential of digitalization. In addition, AFAS as a technological solution facilitates sustainability and operational efficiency. These findings provide crucial insights for future research and advocate for the use of digitalization to improve the efficiency of financial management.

The research is constrained by its focus on Kosovo’s companies, potentially limiting generalizability. Additionally, the study’s reliance on survey data might introduce response bias.

This research contributes to the literature by delineating the intricate relationships between FAD, AFAS and AFT, shedding light on their implications for financial and accounting practices. It underscores the transformative value of digitalization in these domains, offering novel perspectives for academic and managerial discourse.

This paper aims to analyze the impact of sustainability measures taken during the design and construction phases, by examining two categories of sustainability: energy efficiency and reducing carbon emissions and material selection and waste management. These aspects are examined from the perspectives of long-term building performance and maintenance practices, as well as user/tenant satisfaction.

This study includes a literature review related to the two topics under consideration, followed by a comparative case study analysis of four projects to determine practical validity. All case studies in this paper used a semi-structured survey with various project stakeholders, which helped the authors identify measures taken as well as obstacles and challenges during the process.

According to the four case studies, adequate attention should be paid to the two areas of interest during a project’s design and construction phases. Including case studies from around the world (four case studies from three different countries) offers insights into effective sustainability practices in building design and construction, providing instances of successful implementation and emphasizing the obstacles and potential when incorporating sustainability into the design and construction phases.

The findings also show that design and construction participants and companies should reduce waste generation and carbon emissions. In addition, they should make decisions on material selection to enhance projects’ sustainability and to contribute to creating a habitable planet for the future.

The influence of the design and construction phases on long-term project sustainability is of major importance and concern to users, owners, designers, contractors and facility managers. This study illustrates the necessity of including sustainability measures in the design and construction phases, highlighting the importance of sustainability in building design and construction through effective implementation techniques and interdisciplinary teamwork to realize sustainable goals.