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The global construction industry faces both challenges and opportunities from electronic waste (e-waste). This study aims to present a bibliometric analysis and comprehensive literature assessment on e-waste in concrete construction materials.

This study studies 4,122 Scopus documents to examine garbage generation in different countries and inventive ways to integrate e-waste into construction as a sustainable strategy. This study lists famous researchers and their cooperation networks, demonstrating a robust and dynamic area with a surge in research output, notably from 2018 to 2022. Data is visually represented using VOS Viewer to show trends, patterns and study interests throughout time.

The findings imply that e-waste can improve construction materials’ mechanical characteristics and sustainability. The results are inconsistent and suggest further optimization. e-Waste into construction has garnered scientific interest for its environmental, life cycle, and economic impacts. This field has great potential for improving e-waste material use, developing sophisticated prediction models, studying environmental implications, economic analysis, policy formulation, novel construction methods, global cooperation and public awareness. This study shows that e-waste can be used in sustainable building. It stresses this area’s need for research and innovation. This lays the groundwork for using electronic trash in buildings, which promotes a circular economy and environmental sustainability.

The findings underscore the critical role of ongoing research and innovation in leveraging e-waste for sustainable building practices. This study lays the groundwork for integrating e-waste into construction, contributing to the advancement of a circular economy and environmental sustainability.

The social implications of integrating e-waste into construction are significant. Using e-waste not only addresses environmental concerns but also promotes social sustainability by creating new job opportunities in the recycling and construction sectors. It fosters community awareness and responsibility towards sustainable practices and waste management. Additionally, this approach can reduce construction costs, making building projects more accessible and potentially lowering housing prices.

This research contributes to the field by offering a bibliometric analysis and comprehensive assessment of e-waste in concrete construction materials, highlighting its global significance.

This study aims to identify individuals' biases while making investment decisions and explore how these biases can be incorporated into a robo-advisory platform to help mitigate these biases. This paper identifies eight investment-related behavioral biases: mental accounting, gambler’s fallacy, hindsight, regret aversion, disposition, trend-chasing, loss aversion and herding.

This study uses primary data from 263 respondents across various age groups, of which approximately 50 were wealth management professionals in the UAE. A random sampling method from probability sampling is employed to gather the primary data. The identified biases serve as dependent variables; the age and income of individuals serve as the independent variables.

Age and income are significantly related to mental accounting, herding, gambler fallacy and loss aversion. Existing studies on behavioral finance demonstrate that individuals who make investment decisions are susceptible to cognitive fallacies, leading to nonrational investment decisions.

By studying these biases affecting individuals of varying ages and income levels, wealth management professionals can tailor their financial robo-advisory services to address these biases and help clients build wealth with consistent investment.

This study uses survey-based sampling in the context of the UAE; hence, the data and analysis represent originality.

Transparency is one of the finest characteristics of blockchain technology. As blockchain’s technical enablers are traceable and irreversible, transparency allows for more confidence in the system. This study aims to apply and extend the theoretical model of the unified theory of acceptance and use of technology (UTAUT2) by empirically investigating the factors (performance expectancy, price value, facilitating conditions, hedonic motivation, habit, social influence and effort expectancy) that influence users’ perceived transparency of blockchain-as-a-service for e-voting and its effect on adoption intention; to investigate the mediating effect of perceived blockchain transparency on the relationship between UTAUT2 antecedents and intention to use blockchain-based e-voting technology; and to investigate Generations Z and Y’s perceptions of how blockchain technology can be implemented to the current e-voting system.

The authors primarily used the MTurk crowdsourcing platform to host their online survey and collected 251 valid responses from their targeted participants, which the authors analyzed using Smart PLS 4.0.

The findings revealed that users’ perceived expectancy, hedonic motivation, facilitating conditions, habit and price value positively influence the perceived transparency of blockchain-as-a-service for e-voting. This, in turn, positively influences adoption intention. In addition, users’ perceived transparency positively mediates the relationship between UTAUT2 factors (perceived expectancy, hedonic motivation, facilitating conditions, habit and price value) and the adoption intention of blockchain-based e-voting.

By empirically investigating the factors that enhance users’ perceived transparency of blockchain-as-a-service for e-voting, this study contributes to the UTAUT2 model literature. It also investigates the impact of this perceived transparency on the adoption intention and illustrates its mediating role in the UTAUT2 model through a segmentation approach. Finally, the authors address the significant implications of the findings, including how their research contributes to the transparency literature by emphasizing the significance of transparency in blockchain technology.

Limited studies in the mobile payment segment have attempted at understanding the factors that resist customers from using financial apps or mobile payment services (MPSs). This study aims at identifying the barriers from online customer reviews and examine how these barriers affect customers’ negative emotions (anger, fear, sadness), customer ratings and recommendation intentions.

This study, divided into three phases, has adopted a text-mining based mixed-method approach on 14,043 reviews present in Google PlayStore or App Store pages about financial apps used in India.

Phase 1 identified barriers like, “bad user experience”, “UPI failure”, “trust issues”, “transaction delays” from the reviews. Phase 2 found that “bad user experience” and “UPI failure” trigger both “anger” and “sadness”. “Transaction delays” and “money lost in transaction” stimulate “fear”. From the IRT stance, in Phase 3 this study has found that barriers like, “transaction error”, “UPI failure” (usage), “bad user experience” (image) and “trust issues” (tradition) have a significant negative impact on both customer ratings and recommendation intention.

The current study contributes to the existing literature on MPSs by identifying barriers from user generated content. Additionally, this study has also examined the impact of the barriers on customers’ negative emotions and recommendation intention.