Search results

This study aims to explore the attitudes and perceptions of Chinese coffee consumers towards robot baristas, considering the proliferation of automated entities within China's coffee sector.

Employing the extended Technology Acceptance Model 2 as its theoretical framework, this research conducts in-depth interviews with 30 Chinese coffee consumers. The laddering technique is utilized, supplemented by video simulation. Thematic analysis is subsequently employed to scrutinize the data.

The findings delineate six pivotal themes encapsulating Chinese coffee consumers' perceptions of robot baristas – Perceived Introvert Friendliness, Perceived Novelty, Perceived Intellectual Discrepancies, Perceived Efficiency and Reliability, Perceived Emotional Disconnection, and Perceived Labour Market Disruption. Moreover, six motivational themes are identified - Social Status Boosting, Openness to Experience, Ease of Use, Tech-Driven Affordability, Reliable and Uncompromising Quality, and Resistance to Overbearing Service.

The study is limited by its focus on a specific cultural context. Future research could explore cross-cultural perspectives.

The findings of this study offer guidance on how to market and position robotic barista services to appeal to consumer preferences and drive adoption.

Understanding consumer perceptions of robotic baristas has broader social implications, particularly in terms of labour market disruption and the potential impact on traditional coffee professions. Businesses can navigate the social implications of automation more effectively and foster greater acceptance of technological innovations within society.

This study offers insights into the inclinations of Chinese coffee consumers, thereby facilitating informed decision-making and the formulation of effective strategies to expedite the adoption of robotic service.

This study aims to investigate the adoption of mobile wallet payment services among rural Omani millennials, with a focus on social factors, perceived security, trust considerations and the moderating role of technology self-efficacy in shaping attitudes and intentions towards adoption. It also explores the role of mobile wallets in advancing financial inclusion, aligned with Sustainable Development Goal 10 (Reduced inequalities).

A survey method was used with 544 randomly selected participants from rural Oman. The study used partial least squares structural equation modelling (PLS-SEM) to analyse relationships among the constructs, including subjective norms, perceived security, trust and self-efficacy.

The results support five hypotheses, confirming the influence of subjective norms, perceived security and technology self-efficacy on attitudes and intentions to adopt mobile wallets. Additionally, mobile wallet self-efficacy emerges as a significant moderator, enhancing the relationship between positive attitudes and behavioural intentions.

The study extends the technology acceptance model (TAM) by incorporating moderating variables such as technology self-efficacy and perceived security, offering theoretical contributions to digital payment adoption literature, especially in rural settings.

The findings underscore the need for trust-building efforts by service providers and collaborative strategies involving government incentives and promotions to foster mobile wallet adoption. Strengthening digital literacy and addressing security concerns are critical for promoting financial inclusion in rural communities.

This research contributes to promoting economic empowerment through mobile wallet adoption in rural Oman, offering valuable insights for policymakers and service providers aiming to reduce socio-economic disparities. By addressing the digital divide and supporting financial inclusion, the study supports the advancement of SDG 10 (Reduced inequalities) and fosters inclusive growth in underserved communities.

The metaverse is considered an evolution of the Internet, and it engages users with digital content more seamlessly due to its enhanced immersion and diverse applications. The current study examines factors affecting the intention to adopt the metaverse. Existing studies on metaverse were found insufficient in explaining users’ intention to adopt metaverse, for which the companies are investing vast amounts of money for its implementation. The study fills the research gaps in the literature and applies the UTAUT2 (Unified Theory Of Acceptance And Use of Technology) and PAD (Pleasure, Arousal, Dominance) theory in the SOR (Stimulus-Organism-Response) framework. The study proposes a conceptual model by including effort expectancy, hedonic motivation, social influence, security personalization as stimuli, arousal, dominance, pleasure, immersive experience and perceived value as organismic variables and intention to adopt metaverse as the response variable, with gender as a moderator.

The study used purposive non-probability sampling approach and total of 420 responses were collected to examine the model. The partial least squares (PLS) technique is used for data analysis using Smart PLS software.

The study’s findings suggest that social influence and immersive experience have the highest impact on perceived value which affects users’ intention to adopt metaverse. Results indicate that individuals perceive value on using metaverse when it provides enjoyment and fun as well as security. Hence, it is important to ensure not only that individuals feel hedonically motivated but also feel secured and exert less effort to use the metaverse.

The study contributes to the existing literature on metaverse and extends its association with immersive experience and the theories applied. The fundamental qualities of metaverse that contribute to its immersive and enjoyable nature can influence users' behavioral responses. Our research emphasizes the importance of executives acknowledging the development of organismic experience within metaverse.

The insights derived from this study will serve to expand the knowledge of metaverse application developers, offering valuable guidance in incorporating these factors into their development processes. By prominently displaying security measures, metaverse brands can demonstrate their commitment to mitigating risks associated with virtual interactions. This includes clearly communicating the security protocols in place to protect user data and privacy and providing detailed information about security features can build trust and alleviate concerns.

The study highlights how the metaverse features affect individuals toward its adoption intent. Specifically, the study reveals that social influence and security affect the metaverse, further affecting the adoption intent of the metaverse. This has implications for enhancing customer relationships and value cocreation with different stakeholders. The research also recognizes that security measures are necessary for metaverse technology. These reactions could include placing regulations and standards in place to deal with the social and economic effects, making sure that data is collected and used ethically, and giving privacy and security measures priority.

This paper contributes to the body of knowledge as it is the first of its kind to explore and link immersive experience, pleasure and perceived value from the metaverse’s point of view to explore the user’s adoption intention. The study also contributes to the SOR framework with UTAUT2 and PAD theories by applying it to the metaverse context, which is used in limits.

The Metaverse holds vast amounts of user data, making it essential to address threats to its confidentiality, integrity and availability. These threats are not purely technological, as user actions and perceptions, shaped by psychological factors, can influence cybersecurity challenges. Thus, a holistic approach incorporating technological and psychological dimensions is crucial for safeguarding data security and privacy. This research explores users’ cybersecurity behavior in the Metaverse by integrating the technology threat avoidance theory (TTAT) and the theory of planned behavior (TPB).

The model was assessed using data collected from 746 Metaverse users. The empirical data were analyzed using a dual structural equation modeling-artificial neural network (SEM-ANN) approach.

The main PLS-SEM findings indicated that cybersecurity behavior is significantly affected by attitude, perceived behavioral control, subjective norms, perceived threat and avoidance motivation. The ANN results showed that perceived threat with a normalized importance of 100% is the most significant factor influencing cybersecurity behavior. The ANN results also showed that perceived severity with a normalized importance of 98.79% significantly impacts perceived threat.

The novelty of this research stems from developing a unified model grounded in TTAT and TPB to understand cybersecurity behaviors in the Metaverse. Unlike previous Metaverse studies that solely focused on measuring behavioral intentions or user behaviors, this study takes a step further by evaluating users’ cybersecurity behaviors. Alongside its theoretical insights, the study offers practical recommendations for software developers, decision-makers and service providers.

This work aims to develop a multi-step approach for the unified integration of 3D construction printing (3DCP) and building information modeling (BIM), allowing users to easily and automatically outline the instructions for 3D printing of buildings starting from BIM model and ensuring the wide spread of this new technology in Civil Engineering sector.

The proposed methodology exploits Revit for 3D modeling and BIM, using Dynamo as a programming interface for generating G-code.

The paper demonstrates how the proposed methodology can extract information from a BIM model to support building construction using digital fabrication techniques. This code guides the printer’s movements and operations, specifying the path, speed, layers and essential parameters to construct concrete structures layer by layer. It transforms digital designs into precise and efficient physical structures.

This work allows overcoming some of the current limitations associated with bridging BIM models to 3D construction printing. The proposed approach integrates BIM and 3DCP. If the model undergoes changes in the BIM model, the proposed system allows for automatic updates in the 3D printing files. Furthermore, the possibility offered by the proposed methodology to test the G-code on a scaled model allows for the correction of any errors before printing on a large-scale machine.

The novelty of the proposed approach is threefold: i) A new unified integration methodology for BIM and 3D construction printing is defined; ii) An example of a 3D printed building unit is modeled with BIM, incorporating various discipline models such as Architecture, Structure, and Mechanical, Electrical, Plumbing (MEP) systems; iii) The proposed approach allows for testing the G-code at scale before printing with a full-scale machine.