Search results

The emergence of cryptocurrency has developed a new payment system that is changing how financial transactions happen in hospitality. Consumers/travelers have started experimenting with cryptocurrency payments in hotels and restaurants. However, extant research is lacking in understanding the consumer adoption intention of cryptocurrency payments. This study investigates the intention to use cryptocurrency payments in the hospitality industry.

The conceptual model in this study is based on the Behavioral Reasoning Theory, and it explores the motivating and deterring factors influencing the adoption of cryptocurrency payments in the hospitality industry. A quantitative survey was conducted among 1,080 consumers to examine and confirm the model, with data being analyzed through the Partial Least Squares Structural Equation Modeling (PLS-SEM) method.

The outcome of this work showed that the “reasons for” positively influence and “reasons against” negatively influence consumers’ attitudes and use intentions. Consumers’ values of openness to change positively influence the “reasons for” and do not influence the “reasons against” and attitude toward the use of cryptocurrency payments.

This work contributes to practice by providing insights to customers (users/payee), hospitality managers (investors) and organizations/firms (receiving crypto payments) as well as to financial firms and the government.

This research contributes to cryptocurrency payment adoption and behavioral finance literature. The research uniquely provides the adoption and inhibiting factors for cryptocurrency payment in an integrated framework in the hospitality sector.

Social media has played a pivotal role in polarizing views on Russia–Ukraine conflict. The effects of polarization in online interactions have been extensively studied in many contexts. This research aims to examine how multiple social media sources may act as an integrator of information and act as a platform for depolarizing behaviors.

This study analyzes the communications of 6,662 tweets related to the sanctions imposed on Russia by using textual analytics and predictive modeling.

The research findings reveal that the tweeting behavior of netizens was depolarized because of information from multiple social media sources. However, the influx of information from non-organizational sources such as trending topics and discussions has a depolarizing impact on the user’s pre-established attitude.

For policymakers, conflict mediators and observers, and members of society in general, there is a need for (1) continuous and consistent communication throughout the crisis, (2) transparency in the information being communicated and (3) public awareness of the polarized and conflicting information being provided from multiple actors that may be biased in the claims being made about the conflict crisis.

While previous research has examined Russia–Ukraine conflict from a variety of perspectives, this is the first study to examine how social media might be used to reduce attitude polarization during times of conflict.

The study explores the potential barriers to data science (DS) implementation in organizations and identifies the key barriers. The identified barriers were explored for their interconnectedness and characteristics. This study aims to help organizations formulate apt DS strategies by providing a close-to-reality DS implementation framework of barriers, in conjunction with extant literature and practitioners' viewpoints.

The authors synthesized 100 distinct barriers through systematic literature review (SLR) under the individual, organizational and governmental taxonomies. In discussions with 48 industry experts through semi-structured interviews, 14 key barriers were identified. The selected barriers were explored for their pair-wise relationships using interpretive structural modeling (ISM) and fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analyses in formulating the hierarchical framework.

The lack of awareness and data-related challenges are identified as the most prominent barriers, followed by non-alignment with organizational strategy, lack of competency with vendors and premature governmental arrangements, and classified as independent variables. The non-commitment of top-management team (TMT), significant investment costs, lack of swiftness in change management and a low tolerance for complexity and initial failures are recognized as the linkage variables. Employee reluctance, mid-level managerial resistance, a dearth of adequate skills and knowledge and working in silos depend on the rest of the identified barriers. The perceived threat to society is classified as the autonomous variable.

The study augments theoretical understanding from the literature with the practical viewpoints of industry experts in enhancing the knowledge of the DS ecosystem. The research offers organizations a generic framework to combat hindrances to DS initiatives strategically.

In the online environment, consumers increasingly feel vulnerable due to firms’ expanding capabilities of collecting and using their data in an unsanctioned manner. Drawing from gossip theory, this research focuses on two key suppressors of consumer vulnerability: transparency and control. Previous studies conceptualize transparency and control from rationalistic approaches that overlook individual experiences and present a unidimensional conceptualization. This research aims to understand how individuals interpret transparency and control concerning privacy vulnerability in the online environment. Additionally, it explores strategic approaches to communicating the value of transparency and control.

An interpretivism paradigm and phenomenology were adopted in the research design. Data were collected through semi-structured interviews with 41 participants, including consumers and experts, and analyzed through thematic analysis.

The findings identify key conceptual dimensions of transparency and control by adapting justice theory. They also reveal that firms can communicate assurance, functional, technical and social values of transparency and control to address consumer vulnerability.

This research makes the following contributions to the data privacy literature. The findings exhibit multidimensional and comprehensive conceptualizations of transparency and control, including user, firm and information perspectives. Additionally, the conceptual framework combines empirical insights from both experiencers and observers to offer an understanding of how transparency and control serve as justice mechanisms to effectively tackle the issue of unsanctioned transmission of personal information and subsequently address vulnerability. Lastly, the findings provide strategic approaches to communicating the value of transparency and control.

Digital voice assistants (DVAs) are revolutionising consumers’ interactions with technology and businesses. Whilst research on the adoption of these devices is rapidly expanding, few have explored post-adoption behaviour. To fill this gap, we investigate how functionality and human-like features shape customers’ emotions, engagement and loyalty towards DVAs.

The data were collected through a self-administered online survey from 509 DVA users. Structural equation modelling was employed for data analysis.

The results reveal that distinct human-like and functional factors of DVA independently explain customers’ positive emotions and engagement with DVAs. Positive emotions and engagement significantly impact customer loyalty to DVAs. The study shows that localisation of DVAs has a significant positive moderating influence on the service experience-customer engagement relationship but a negative moderating influence on the anthropomorphism-customer engagement relationship.

Unlike previous research, this study contributes to the literature by delving into post-adoption phenomena. It explains how DVAs’ human-like and functional attributes drive customers’ positive emotional responses, engagement and loyalty towards DVAs. The findings not only unveil new insights into the moderating role of localisation but also provide a crucial understanding regarding the boundary conditions of the influence of anthropomorphism and service experience on customer engagement.

This study investigates the impact of augmented reality (AR) on consumers’ shopping process, focusing on value creation, brand engagement and purchasing intents.

This quantitative deductive study analyzed 393 questionnaires through non-probability sampling. A cross-sectional timeframe was applied; data collection took place in May 2023 to provide a snapshot of Egyptian consumers’ responses to AR. Once the needed data were collected, statistical analyses were conducted through the statistical package for social science (SPSS).

This study shows that in the shopping process, AR vividness, interactivity and informativeness lead consumers to develop utilitarian values toward the technology, and AR interactivity generates hedonic values towards the technology. When consumers sense the hedonic and utilitarian values, it impacts consumers purchase intention. Hedonic value in AR leads to consumers’ brand content consumption and creation; utilitarian value in AR leads to consumers’ brand content consumption, contribution and creation.

AR developers, brand managers and marketers may use this study to understand the current AR landscape and consumer responses toward AR (value development, purchase intention and brand engagement). With these insights, they can make better strategic decisions that include AR usage in brand marketing tactics.

This study develops conclusions to grasp more clearly and in-depth why and how AR impacts consumers’ shopping process. This study addresses various literature gaps, enhancing the understanding of AR: the salient AR attributes that offer consumers hedonic and utilitarian values and how AR influences consumer behavior, specifically when it comes to the development of brand engagement and purchase intents.

This study aims to understand the acceptance of AI-curated fashion services among Chinese consumers by introducing consumer characteristics, such as fashion clothing involvement (FCI) and technological innovativeness (TI), as leading variables of the technology acceptance model (TAM). Furthermore, it aims to examine the impact of FCI and TI on attitudes towards AI-curated fashion services and the purchase intention of fashion products through perceived usefulness (PU), perceived ease of use (PEU), and perceived enjoyment (PE). Through this analysis, this study seeks to determine a marketing strategy that can support implementing AI-curated fashion services in the Chinese market.

This study used structural equation modeling to ascertain the results.

Regarding AI-curated fashion services' attributes, the analysis revealed that consumers' FCI did not significantly affect the PU and PE. However, FCI greatly impacted the PEU. In addition, consumers' interests in TI significantly affected PU and PE but did not significantly influence PEU, although PEU significantly affected PU. PU, PEU, and PE greatly impacted usage attitude. PU and usage attitude significantly affected purchase intention, whereas PE had no effect.

Through a practical survey of Chinese consumers, we investigated the impact of FCI and TI on the attitude and purchase intention of fashion products recommended by AI-curated fashion services.