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A court of mist and fury
Though Feyre now has the powers of the High Fae, her heart remains human, but as she navigates the feared Night Court's dark web of politics, passion, and dazzling power, a greater evil looms--and she might be key to stopping it.
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A study on the cognitive-consumption behavior of sports content on OTT media platforms: applying the extended technology acceptance model (E-TAM)
The purpose of this study is to provide basic data for the establishment of sustainable sports content and communication marketing strategies of effective OTT platforms by applying the extended technology acceptance model to clarify the causal relationship between the perceived usefulness, perceived ease of use, perceived enjoyment, perceived interactivity, usage intention, and usage behavior of users who watch OTT platform sports content. To achieve this purpose, 303 viewers with experience watching OTT platform sports content were used for the analysis. The data analysis methods were frequency analysis, correlation analysis, confirmatory factor analysis, and structural equation modeling analysis using SPSS 21.0 and AMOS 18.0. The results of this study are as follows. First, perceived usefulness was found to have no significant effect on usage intention. Second, perceived ease of use was found to have a significant effect on usage intention. Third, perceived enjoyment was found to have a significant effect on usage intention. Fourth, perceived interactivity was found to have a significant effect on usage intention. Fifth, usage intention was found to have a significant effect on usage behavior. Therefore, the intention of using OTT platform sports content will be to become a sustainable industry in terms of media business.
Journal Article
When predictors of outcomes are necessary: guidelines for the combined use of PLS-SEM and NCA
PurposeThis research introduces the combined use of partial least squares–structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) that enables researchers to explore and validate hypotheses following a sufficiency logic, as well as hypotheses drawing on a necessity logic. The authors’ objective is to encourage the practice of combining PLS-SEM and NCA as complementary views of causality and data analysis.Design/methodology/approachThe authors present guidelines describing how to combine PLS-SEM and NCA. These relate to the specification of the research objective and the theoretical background, the preparation and evaluation of the data set, running the analyses, the evaluation of measurements, the evaluation of the (structural) model and relationships and the interpretation of findings. In addition, the authors present an empirical illustration in the field of technology acceptance.FindingsThe use of PLS-SEM and NCA enables researchers to identify the must-have factors required for an outcome in accordance with the necessity logic. At the same time, this approach shows the should-have factors following the additive sufficiency logic. The combination of both logics enables researchers to support their theoretical considerations and offers new avenues to test theoretical alternatives for established models.Originality/valueThe authors provide insights into the logic, assessment, challenges and benefits of NCA for researchers familiar with PLS-SEM. This novel approach enables researchers to substantiate and improve their theories and helps practitioners disclose the must-have and should-have factors relevant to their decision-making.
Journal Article
Adoption of AI-based chatbots for hospitality and tourism
Purpose
This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.
Design/methodology/approach
To understand the customers’ behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis.
Findings
As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager’s commitment to providing travel planning services using AI-based chatbots.
Practical implications
This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers.
Originality/value
This study contributes theoretically by extending the TAM to provide better explanatory power with human–robot interaction context-specific constructs – PTR, PNT, ANM and TXN – to examine the customers’ chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots’ adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.
Journal Article
Understanding University Students’ Adoption of ChatGPT: Insights from TAM, SDT, and Beyond
Aim/Purpose: The aim of this study is to explore the factors that influence higher education students’ adoption of ChatGPT by incorporating constructs from the Technology Acceptance Model (TAM) and Self-Determination Theory (SDT) with trust, social influence, and personal innovativeness. Background: Even though the use of ChatGPT has become more popular among university students, there is no clear evidence about the reasons that would make them adopt or abstain from using such a tool. Methodology: The study utilized a survey that was answered by 150 university students registered in the faculty of engineering at a public university. The survey was developed by Google Forms and focused on how useful and easy they think ChatGPT is, their motivations, trust, social influence, innovativeness, and their readiness to use it. Statistical analysis was performed using SPSS 26 and Smart-PLS4, with the latter being particularly useful due to the study’s complex model and adherence to sample size criteria. Contribution: This research provides fresh insights into how students perceive and start using modern AI tools like ChatGPT. It also helps educators and policymakers understand how to integrate AI technologies into education better to make learning more effective. Findings: The study reveals that students are more likely to adopt ChatGPT if they perceive it as useful and easy to use. External motivation and social influence significantly impact students’ behavioral intentions to use ChatGPT, while trust also plays a crucial role. Intrinsic motivation, however, does not significantly affect behavioral intention. The strongest predictor of actual use is behavioral intention, indicating that students who intend to use ChatGPT are highly likely to do so. Personal innovativeness is another significant factor influencing both behavioral intention and actual use. Recommendations for Practitioners: Educators and policymakers should focus on enhancing the perceived usefulness, ease of use, trust, social influence, and innovativeness related to ChatGPT to increase its adoption in educational settings. Recommendation for Researchers: Future research should explore additional psychological and contextual factors that may influence the adoption of ChatGPT and other similar technologies among students. Impact on Society: Understanding the factors that influence the adoption of ChatGPT can help in developing strategies to integrate such tools effectively in education, potentially improving learning outcomes and digital literacy among students. Future Research: Further studies should examine the long-term effects of ChatGPT usage on students’ learning outcomes and investigate the adoption patterns in different educational contexts and disciplines.
Journal Article
What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model
PurposeConsidering the ubiquity of FinTech services, the study proposes a research framework to examine FinTech adoption and use from the technology acceptance perspective by adding sub-constructs of technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT), ServPerf and WebQual 4.0. This study broadly classified these sub-constructs in three dimensions: adoption, behavior and technological and explores the relationship between these attributes. It also proposes that digital behavior (Internet experience and level of awareness) and demographic characteristics (age and gender) moderate the main relationships.Design/methodology/approachThe measurement scale for the study is developed through iterative discussion with domain experts. The data are collected from 439 active Internet users though a digital survey and analysis were done by applying structural equation modeling and multi-group analysis.FindingsPerceived usefulness and social influence are found to be the key determinant for behavior intention to use FinTech services, with social influence having significant negative influence. Actual use is significantly influenced by ease of use and social influence but is not determined by behavior intention and perceived usefulness. Behavioral attributes are significantly impacted by technological attributes and digital behavior. Also, age significantly affects the perception of security among older users.Practical implicationsThis study will help FinTech service providers to design FinTech services considering a wide spectrum of users. More consideration should be on enhancing the usefulness and security features to create social affirmations for the use of FinTech services. This will entice users for frequent use and attract nonusers to do their first online financial transaction.Originality/valueThe study adds to the technology acceptance literature by incorporating relevant technological and behavioral attributes and investigating the moderating effect of digital behavior and demographic characteristics. It contributes to the understanding of user beliefs and perceptions about actual use of FinTech services.
Journal Article
Corrigendum: Brucella suis ΔmapB outer membrane vesicles as an acellular vaccine against systemic and mucosal B. suis infection
[This corrects the article DOI: 10.3389/fimmu.2024.1501791.].
Journal Article
M2-TAM subsets altered by lactic acid promote T-cell apoptosis through the PD-L1/PD-1 pathway
The aim of the study was to investigate the effects of lactic acid on the phenotypic polarization and immune function of macrophages. The human monocyte/macrophage cell line, THP-1, was selected and treated with lactic acid. Immunofluorescence staining, laser confocal microscopy, reverse-transcription polymerase chain reaction (RT-PCR), western blot, siRNA, and ELISA analyses were used to observe changes in the levels of cluster of differentiation (CD)68, CD163, hypoxia inducible factor (HIF)-1α, and programmed death ligand-1 (PD-L1) as well as those of cytokines, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, interleukin (IL)-12, and IL-10. THP-1 macrophages and T cells were co-cultured in vitro to observe the changes in proliferation and apoptosis of T cells. The results showed that, lactic acid (15 mmol/l) significantly upregulated the expression of the macrophage M2 marker CD163 (P<0.05), cytokines, IFN-γ and IL-10, secreted by M2-tumor-associated macrophages (TAM, P<0.05), and HIF-1α and PD-L1 (P<0.05), and downregulated the expression of cytokines, TNF-α and IL-12, secreted by M1-TAM (P<0.05). Redistribution of M2-TAM subsets and PD-L1 expression was reversed after further transfection of THP-1 cells with HIF-1α siRNA (P<0.05). After co-culturing, T-cell proliferation was inhibited and apoptosis was promoted. In summary, modulation of lactic acid level can redistribute M2-TAM subsets and upregulate PD-L1 to assist tumor immune escape. The HIF-1α signaling pathway may participate in this process, revealing that macrophages, as 'checkpoints' in organisms, are links that connect the immune status and tumor evolution, and can be used as a target in tumor treatment.
Journal Article
Searching for New Technology Acceptance Model under Social Context: Analyzing the Determinants of Acceptance of Intelligent Information Technology in Digital Transformation and Implications for the Requisites of Digital Sustainability
Intelligent information technology (IIT) based on AI and intelligent network communication technology is rapidly changing the social structure and the personal lives. However, IIT acceptancefrom various perspectives still requires extensive research. The research question in this paper examines how five factors—psychological, technological, resource, risk perception, and value factors—influence IIT acceptance. Based on an analysis of survey data, it was first found that the acceptance rate of IIT itself was generally very high. Second, in terms of IIT acceptance, among twenty-five predictors, voluntariness (+), positive image of technology (+), performance expectancy (+), relative advantage (+), radical innovation (+), and experience of use (+) were found to have significant effects on the IIT acceptance. Third, in addition to technological factors, psychological factors and risk perception factors also played an important role in individuals’ decisions regarding IIT acceptance.
Journal Article