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This study aims to extend the cognitive appraisal theory by developing and validating a conceptual framework to illustrate how travelers' behavioral intention is generated via a multi-stage evaluation of health-related variables.

SEM and moderator analysis were conducted to examine the theoretical framework (post-intervention event travel intention) and to investigate how the appraisal process differs across travelers with various attitudes toward vaccination.

This study found that cruise travel intention was positively influenced by the perceived hedonic value and perceived trustworthiness and negatively influenced by perceived infection risk. Furthermore, whereas perceived hedonic value, perceived trustworthiness and perceived risk of infection were all predicted by crisis management, the dimensions of crisis management operated differently. In addition, vaccination attitudes amplified the unfavorable effect of perceived risk on intention.

Drawing on the CAT, this study developed and validated a conceptual framework to integrate crisis management with customers' behavioral intentions. This study extends existing cruise travel intention theory by demonstrating how post-pandemic travelers' behavioral intention is generated via a multi-stage appraisal-reappraisal process based on the evaluations of infection risks and cruise line crisis management.

The purpose of this study is to explore the process of initial sensemaking that organizational members activate when they reflect on AI adoption in their work settings, and how the perceived features of AI technologies trigger sensemaking processes which in turn have the potential to influence workplace learning modes and trajectories.

We adopted an explorative qualitative and interactive approach to capture free fantasies and imaginative ideas of AI among people within the industry. We adopt a conceptual perspective that combines theories on initial sensemaking and workplace learning as a theoretical lens to analyze data collected during 23 focus groups held at four large Swedish manufacturing companies. The data were analyzed using the Gioia method.

Two aggregated dimensions were defined and led to the development of an integrated conceptualization of the initial sensemaking of AI technology adoption. Specifically, sensemaking triggered by abstract features of AI technology mainly pointed to an exploitative learning path. Sensemaking triggered by concrete features of the technology mainly pointed to explorative paths, where socio-technical processes appear to be crucial in the process of AI adoption.

This is one of the first studies that attempts to explore and conceptualize how organizations make sense of prospective workplace learning in the context of AI adoption.

This study aims to ascertain the intentions of risk managers to use artificial intelligence in performing their tasks by examining the factors affecting their motivation.

The study employs an integrated theoretical framework that merges the third version of the technology acceptance model 3 (TAM3) and the unified theory of acceptance and use of technology (UTAUT) based on the application of the structural equation model with partial least squares structural equation modeling (PLS-SEM) estimation on data gathered through a Likert-based questionnaire disseminated among Italian risk managers. The survey reached 782 people working as risk professionals, but only 208 provided full responses. The final response rate was 26.59%.

The findings show that social influence, perception of external control and risk perception are the main predictors of risk professionals' intention to use artificial intelligence. Moreover, performance expectancy (PE) and effort expectancy (EE) of risk professionals in relation to technology implementation and use also appear to be reasonably reliable predictors.

Thus, the study offers a precious contribution to the debate on the impact of automation and disruptive technologies in the risk management domain. It complements extant studies by tapping into cultural issues surrounding risk management and focuses on the mostly overlooked dimension of individuals.

Yet, thanks to its quite novel theoretical approach; it also extends the field of studies on artificial intelligence acceptance by offering fresh insights into the perceptions of risk professionals and valuable practical and policymaking implications.

This study aims to address the challenge many organizational leaders face in fostering workforce cohesion. Focusing on the context of sports club volunteering, this study investigates how leaders can enhance group cohesion among volunteers. The study findings provide valuable insights applicable across various work settings.

Through a multilevel design, this study examined the role of autonomy–supportive and structuring leadership in shaping social and task cohesion within volunteer teams at the group level. In total, 557 volunteers nested within 52 nonprofit sports clubs situated in the Flemish region of Belgium were involved in this study, providing a robust foundation for our analysis.

This research revealed that regular volunteers form “true groups”, exhibiting substantial between-group variance in social and task cohesion and a strong within-group consensus. Additionally, the findings underscored the significance of autonomy–supportive leadership in fostering cohesion, demonstrating a positive relation with social and task cohesion at the group level.

This study demonstrates that volunteer teams, like work teams in the for-profit sector, actively engage in interpersonal exchanges within their organization, which help shape their collective sense of unity and alignment with common objectives. Leaders can enhance these interactions by fostering an autonomy–supportive environment where members feel empowered to share their perspectives and ideas. Additionally, the findings suggest that the nature of the task and the specific context can influence which leadership style is most effective, with the provision of structure also playing a role. With these insights, leaders in diverse organizational settings can effectively nurture the development of cohesive groups.

Recognizing the importance of Robo-advisors in digital financial services, this paper aims to analyse the users’ perception and acceptability of artificial intelligence (AI) in digital investment solutions using an extended “Technology Acceptance Model” (TAM).

The model is tested using 454 online valid responses received from Indian Fintech users via direct path analysis, mediation and moderation.

The study’s findings show that trust, perceived usefulness and perceived risk all significantly impact users’ attitudes towards Robo-advisors. In contrast, ease of use and social influence did not impact users’ attitudes statistically. Furthermore, the results indicate that their attitudes and ease of use influence users’ intentions to adopt Robo-advisors. Moreover, the moderation effect of gender partly supports the overall model. Specifically, in the path between attitudes and their antecedents, gender plays a role in influencing the relationships among these variables. This aligns with preliminary research in the field, providing additional insight into how gender may moderate the factors influencing users’ attitudes and intentions regarding Robo-advisory services.

This research study also reveals that trust, perceived risk, ease of use and demographic factors influence the adoption of Robo-advisory services. It is functional, but its sample selection is not probabilistic and overly emphasizes gender. Future research should use probabilistic sampling, other demographic factors and experience and situational factors. Also, it is necessary to examine how convenient and satisfying it is to communicate with service providers. Filling these gaps will improve the knowledge of consumer behaviour in the context of Fintech adoption and develop the current research.

This study posits that perceived usefulness, trust, perceived risk and ease of use remain core determinants of adopting Robo-advisory services. So, to improve the level of trust of users, it is necessary to develop security measures, data clarity and quality and customer support. Enhancing ease of use by incorporating better interface gestures is always beneficial for increasing the number of users and their level of satisfaction. As identified in previous studies, practical solutions will be achieved by pursuing the increased use of technology while leveraging AI for personal services and minimizing perceived risks, which will strengthen more advanced security measures as well as sufficiently clear communication.

The paper aims to extend the TAM by incorporating measures of trust and social influence to identify the factors that drive the adoption of Robo-advisors. In doing so, the paper may contribute to developing a more comprehensive understanding of the factors that shape consumers’ attitudes and intentions towards these technologies. Moreover, the paper appears to examine the moderating effect of gender on attitude and its predictors, which could provide insights into how gender characteristics may impact the adoption of Robo-advisors.

This article explores brand positioning and authenticity within the global-local continuum, utilizing the evolution of the Italian rock band, Måneskin, as a case study.

Employing Greimas’s (1987) semiotic framework, I analyze social media and media articles on Måneskin’s success, unveiling consumer perceptions of global, local and intermediate brand positionings and related authenticity dimensions. I particularly uncover a narrative centered on “global” versus “local” brand positioning and their counterparts (i.e. “not global” and “not local”), forming a semiotic square.

In the “global” perception, the band is evaluated in terms of conforming to global standards, while, in the “local” understanding, the emphasis shifts to connections to local roots. In the “glocalization” perspective (global and local), the band’s activities are assessed concerning an integration between global conformity and local connections. The “glalienation” viewpoint (neither global nor local) is related to consistency, in the sense of being unique and avoiding a commitment to either global or local values. The data also highlight issues of inconsistency regarding brand positioning’s contradictions, such as the band’s incoherently merging local and non-local elements.

The proposed structural semiotics approach enriches previous theories by examining authenticity within global-local dynamics, offering insights into various authenticity dimensions and their interplay. It underlines shifts in authenticity perceptions and challenges binary brand positioning, advocating for strategic placement across the global-local continuum. Moreover, it emphasizes leveraging cultural elements and semiotics to effectively communicate authenticity.

This study aims to establish a comprehensive framework for adopting mobile-based artificial intelligence (AI) services in Tanzanian manufacturing small and medium enterprises (SMEs).

The methodology involved conducting a literature review and using the combination of Mobile Services Acceptance Model and Innovation Diffusion Theory (IDT) as a theoretical foundation. This synthesis delves into the current knowledge on technology adoption, organizational behavior and innovation diffusion, creating a solid conceptual basis. Expert review was used for framework validation to ensure the framework's accuracy.

This study shows that the factors influencing the adoption of mobile-based AI services in Tanzanian manufacturing SMEs include perceived usefulness, perceived ease of use, context, personal initiatives and characteristics, trust, infrastructure, cost, mobility, power distance, compatibility, observability and trialability.

The framework provides valuable insights tailored to Tanzanian sociocultural and economic nuances. However, its generalizability is limited due to its specificity to Tanzanian manufacturing SMEs.

The framework outlined in this research provides SME leaders, policymakers and technology implementers with valuable guidance to make informed decisions during the adoption process.

This study introduces a novel lens for understanding technology adoption. This study's focus on the Tanzanian context and its nuanced examination of contributing factors add to its originality and practical significance.

The metaverse is a virtual world where users can communicate with each other in a computer-generated environment. The use of metaverse technology has the potential to revolutionize the way businesses operate, interact with customers, and collaborate with employees. However, several obstacles must be addressed and overcome to ensure the successful implementation of metaverse technology. This study aims to examine the implementation of metaverse technology in the management of an organization's supply chain, with a focus on predicting potential barriers to provide suitable strategies.

Covariance-based structural equation modeling (CB-SEM) was used to test the model. In addition, artificial neural network modeling (ANN) was also performed.

The CB-SEM results revealed that a firm's technological limitations are among the most significant barriers to implementing metaverse technology in the supply chain management (SCM). The ANN results further highlighted that the firm's technological limitations are the most crucial input factors, followed by a lack of governance and standardization, integration challenges, poor diffusion through the network, traditional organizational culture, lack of stakeholder commitment, lack of collaboration and low perception of value by customers.

Because metaverse technology has the potential to provide organizations with a competitive advantage, increase productivity, improve customer experience and stimulate creativity, it is crucial to discuss and develop solutions to implementation challenges in the business world. Companies can position themselves for success in this fascinating and quickly changing technological landscape by conquering these challenges.

This study provides insights to metaverse technology developers and supply chain practitioners for successful implementation in SCM, as well as theoretical contributions for supply chain managers aiming to implement such environments.

Adaptability and integration (ADI) are the core ingredients for environmentally sustainable construction (ESC), which preserves the ecology from unsupported human activities. However, the approach is lagging in developing countries, which has led to studying the influence of ADI on the adaptive capacity of small- and medium-scale construction organisations.

The research employed a quantitative methodology, collecting 400 responses as a sample size. A construct of 14 influential factors concerning ADI within the Ghanaian small and medium-scale construction industry was developed. The data obtained from participants underwent analysis using SPSS version 26. The validity of the study’s findings was assessed by applying structural equation modelling (SEM) within the AMOS software.

It was evident that innovation advancement and ongoing training and evaluations significantly influence ADI for adaptive capacity. Moreover, the system internally and vulnerability (SIV) and perceived need for implementation (PNI) sub-scales were the main latent components for best construction practices.

Ghana’s small- and medium-scale construction organisations have yet to fully recognise the importance of ADI in enhancing adaptive capacity for the best ESC. However, the results indicated that ADI constructs will significantly influence implementation outcomes to ensure ESC.

The originality of this research also resides in identifying how ADI affect small- and medium-scale construction organisation’s ability to ensure ecologically sustainable building practices.

The primary purpose of this study is to investigate the influence of tourists' perceived value, satisfaction and behavioral intention on the development of Lipu Yi costume culture to promote the development of intangible cultural tourism and better construct a model of the influencing factors of Lipu Yi costumes in the development of intangible cultural heritage tourism.

The study site is the intangible cultural district of Panzhihua, Sichuan Province, China. This study examines the interrelationships between tourists' perceived value of experience, behavioral intention and satisfaction as the tourists relate to Lipu Yi costume and intangible cultural heritage tourism. A sample of 225 tourists who had visited Panzhihua at least once was selected for the study.

All seven of the survey's hypotheses were supported. Therefore, this study concludes that tourists' perceived value, satisfaction and behavioral intention directly affect the development of intangible cultural tourism and significantly positively impact the growth of Lipu Yi costumes culture. Descriptive analysis, confirmatory factor analysis (CFA) and structural equation modeling (SEM) investigation methods were used.

This paper analyzes tourists' perceived value of Lipu costume culture and tourists' satisfaction and behavioral intention during the tourism process. This study provides a more in-depth understanding of the relationship between Lipu Yi costume and non-heritage tourism factors. Practical methods and approaches are sought to further develop Lipu Yi costume non-heritage tourism.