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The retail industry is experiencing a marketing transformation through the use of augmented reality (AR), particularly in beauty products. Customer engagement and integration with digital tools are critical tools to enhance positive predisposition toward their platform leading to better visibility. This study explores how user experience (UX) and interactivity (INT) influence attitudes toward AR applications, with a focus on the moderating role of cognitive enjoyment (CGE). Data were collected through online platforms from 310 young female students and professionals familiar with AR technology in online shopping. The analysis was performed using partial least squares structural equation modeling (PLS-SEM), with constructs adapted from established scales to fit the study's needs. Results indicate that positive UXs and high levels of interaction significantly enhance attitudes toward AR apps. Furthermore, CGE was found to be a significant moderator, amplifying the effects of UX and interaction on user attitudes. These findings extend existing theories of technological acceptance to the use of AR in retail, suggesting that enhancing UX and interactivity, while emphasizing the enjoyable aspects of AR, can foster more positive attitudes and potentially increase adoption rates. This study contributes valuable insights into the strategic use of AR technology in retail environments, offering implications for designers and marketers aiming to enhance consumer engagement through innovative digital tools.

This paper aims to explore the causal relationship of user-generated content (UGC) on trust in UGC (TUGC), destination image (DI) and tourist visit intention (VI) guided by the stimulus-organism-response (SOR) theory. This work further examined the mediating effect of TUGC and DI between UGC and VI.

Data were collected through online and personal-administered surveys and randomized sampling. This work employed partial least squares structural equation modeling (PLS-SEM) to test the proposed model empirically.

In line with the SOR Theory, this work found UGCs that induce positive emotions and connection to the users motivate VI rather than UGCs that are predominantly factual. Furthermore, UGCs are considered reliable, authentic and less biased than brand-generated content. The findings of this work contribute to the theoretical understanding of UGC to VI in a destination.

This work proposes that destination marketers prioritize UGC that evokes positive emotions and connections with users, as it is more effective in encouraging VI. Strategies such as incentivizing content creators, improving online presence and engaging influencers can maximize UGC. Enhancing online traffic quality, visibility and interaction and implementing content policies are crucial for UGC's effectiveness. Marketers should align destination products with tourists' interests and collaborate with influencers for affiliate marketing to increase tourist-generated UGC. Furthermore, improved connectivity encourages UGCs about the destination.

In tourism marketing, UGC has become a valuable information source for tourists in making informed travel decisions. UGC is a tourist-generated content that offers factual information and authentic experiences through images, videos or text posted through social media platforms. UGC is considered more reputable than travel firms and the mainstream media as an information source. Due to the limited works on UGC in the literature, the influence of UGC on tourists' VIs has remained unexplored at the time of writing. This work bridges this gap by empirically examining the impact of UGC on Gen Z tourists' VI guided by the SOR theory.

This study aims to determine barriers to innovation and to develop a quantitative model for the barrier to innovation in Vietnamese construction organizations of different sizes.

A literature review and discussions with experienced practitioners were implemented to determine barriers to innovation in construction organizations. The rank-based non-parametric test analyzed collected data from a questionnaire survey to examine if there were significant differences between the three groups of organizations, including small, medium and large construction organizations. The fuzzy synthetic evaluation (FSE) technique was employed to develop barrier indexes (BIs) for organizations of different sizes in Vietnam.

The findings showed 17 barriers to innovation which were categorized into four groups, including organizational, human resources, economic and market barriers. Statistical analysis revealed significant differences regarding barriers to innovation between small, medium and large construction organizations in Vietnam. The post hoc test highlighted barriers to innovation differently separated into two groups: SMEs and large construction organizations. The FSE analysis integrated the identified barriers into the comprehensive BIs for SMEs and large construction organizations. The FSE analysis illustrated that the organizational barrier is the most critical barrier for SMEs. On the other hand, the market barrier received the most significant attention in large construction organizations.

This research is one of the first integrated barriers to innovation into a comprehensive formulation. The indexes provide the decision-makers with a practical and reliable tool to evaluate barriers to innovation in construction organizations of different sizes.

This study investigates the digital competence (DC) of undergraduate students, considering three key dimensions: use of Information and Communication Technologies (ICT) resources, knowledge about ICT resources, and attitude towards ICT. We also examined the relationship between these aspects in order to build a DC assessment framework.

A structured questionnaire was administered to students from several universities in Vietnam in order to assess their DC. A PLS analysis was conducted based on data from 551 valid responses.

Statistical analyses showed that the DC of students was quite low. The findings certify that knowledge of ICT resources is a total intermediate variable in the impact of attitude towards ICT on the use of ICT resources by students.

Our findings provide important implications for policymakers and teachers' insights for authorities, universities, and scholars to develop strategies for DC of students in higher education.

This study is the first to explore the DC assessment framework for students in higher education in an emerging market, Vietnam.

Switching to green energy is a crucial step in achieving carbon neutrality. This study aims to explore what motivates people to use green energy and how much more people are willing to pay for green energy.

Grounded on the value–attitude–intention hierarchy, this study proposes that environmental consciousness as a human value influences attitudes including attitude toward environmental issues and attitude toward ecosocial benefits while attitudes, information and knowledge about green energy and quality and price of green energy influence people’s intention to use green energy. Data were collected from 342 Chinese adults.

Results showed that environmental consciousness significantly and positively influenced attitudes while attitude toward environmental issues had the greatest effect on people’s intention to use green energy, followed by quality and price of green energy. About 44% respondents were willing to pay 2.5% to <5% more money for green energy.

This study extended the use of value–attitude–intention hierarchy to investigate what motivates people to use green energy. Specifically, this study demonstrated that quality and price, and knowledge and information also significantly shaped people’s intention to use green energy significantly.

This study utilised Mehrabian and Russel's stimulus-organism-response (SOR) model to investigate the inter-relationship between perceived social media information qualities (IQ) of online UGC, destination image, perceived travel risk and behavioural intentions.

A total of 255 responses from international tourists were collected. The data collection via an online survey was performed from October 2020 to February 2021. The study model and hypotheses were examined using partial least squares-structural equation modelling (PLS-SEM).

The result indicated that social media intrinsic, representational, and social IQ significantly influenced tourists perceived cognitive image, while only contextual and social IQ significantly predicted the perceived affective image. This study also confirms the significant effect of cognitive image on the affective image. In addition, the authors found that both destination image components, cognitive and affective, significantly affect tourists' behavioural intentions. However, surprisingly, tourists' perceived travel risk did not moderate the effect of destination image components on behavioural intentions.

This study contributes to the body of knowledge by extending Mehrabian and Russel's SOR model in the tourism behaviour context.

From a practical perspective, this study proves that UGC significantly affects destination image and plays an integral part in luring tourists to visit a destination.

Previous research in this area is limited, making this study particularly novel. This study represents one of the initial attempts to evaluate the dimensions of information quality in UGC on social media and online review platforms, particularly within the field of tourism. Treating online travel UGC seriously could assist organisations in leveraging tourist behaviour and enhancing destination image.

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.

The main purpose of this chapter is to study and analyze the impact of metaverse (mixed reality) on health tourism in the major tourist destinations in India and the global market. This chapter is made as a case study with detailed mentions of factors for tourism promotion for metaverse, sustainability, and crisis management. This chapter has tried to explain the role of the metaverse in tourism marketing and the cognitive level of influence the metaverse possesses among tourists which makes them prefer repeated visits. Also, the chapter tried to assess the existing conditions in the tourism industry which positively or negatively impact the health sector due to the role of metaverse. This chapter ends with giving inspirational notes to future researchers to examine the conceptual understanding of metaverse as a major tool for destination tourism emphasizing health, wellness, and happiness.

This study aims to investigate the impact of geopolitical risk (GPR) on supply chain concentration (SCC) and the roles of operational capabilities and resources in this relationship.

Secondary longitudinal data from multiple sources is collected and combined to test for a direct impact of GPR on SCC. We further examine the moderating effects of firms’ operational capabilities and resources (i.e. firm resilience, operational slack and cash holding). Fixed-effect regression models are applied to test the hypotheses, followed by a series of robustness tests to check the consistency of the results.

Consistent with the tenets of resource dependence theory, our analysis reveals a significant negative impact of GPR on SCC. Moreover, we find that this adverse effect is attenuated for firms with higher levels of resilience, more operational slack and greater cash holdings. Further analysis suggests that maintaining a diversified supply chain base during heightened GPR is associated with a firm’s improved financial performance.

This study contributes to the supply chain management (SCM) literature by integrating GPR into the supply chain risk management framework. Additionally, it demonstrates the roles of diversification and operational resources in addressing GPR-induced challenges.