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This study aims to evaluate the users’ behavioral intention toward the acceptance and adoption of digital payment FinTech services in India. The study also compares the differences in Gen Y and Gen Z’s intention to adopt digital payment FinTech services.

The present study adopted both the unified theory of acceptance and use of technology (UTAUT) and the technology acceptance model (TAM) as its theoretical base and also added financial literacy and customer satisfaction. The data was analyzed by applying structural equation modeling using SmartPLS 4.

The outcomes of the study imply that customer satisfaction, effort expectancy and performance expectancy had a significant effect on behavioral intention. Moreover, effort expectancy, performance expectancy and perceived enjoyment had a significant influence on customer satisfaction, and effort expectancy and performance expectancy is significantly influenced by perceived enjoyment, while self-efficacy significantly influenced perceived enjoyment. Also, financial literacy does not moderate the relationship between effort expectancy, performance expectancy, facilitating condition and behavioral intention. Furthermore, the association of effort expectancy → customer satisfaction; perceived enjoyment → customer satisfaction; and perceived enjoyment → effort expectancy is moderated by age factor.

This study contributes by developing a more cohesive and unified model for assessing users’ behavioral intention toward acceptance and adoption of FinTech services by adopting constructs from the UTUAT and TAM and incorporating financial literacy and customer satisfaction to expand and enhance the theoretical prospect of the existing literature.

Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping.

Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model.

The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping.

This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.

In recent times, mobile banking has become the best alternative for transactions associated with payments like bills, fees, and peer-to-peer payments. Therefore, the pace of adoption is increasing day after other. However, the numbers of customers are not equal to the expectations as there are several challenges and threats hindering in the way of excellence and growth of mobile banking. Therefore, this chapter has been written purposively to address all the elements that are associated with the use of mobile banking with special emphasis on Pakistan and other developing sides of Asia. In fact, concern towards Asian sides is mandatory as the continent has the massive charm to attract users towards the use of mobile banking, but there is a need for proper policy and concern from stakeholders in order to give a push to the technology, which is fruitful for society, environment, as well as economy. The study includes an in-depth discussion on factors that need attention to make the study implicative and thorough for conducting further research in the field of Fin-Tech and mobile banking.

Buying online has become a widespread and common activity for consumers, and, for many organizations, e-commerce has become a very profitable alternative to sell their products and services, also allowing them to leverage their strategy in new geographical markets immediately. Although the literature on the subject is comprehensive, there is a gap in identifying the holistic constructs that are the determinants of consumers' choice of an online store. This research resorts to an exploratory study, based on a nonsystematic literature review, seeking to identify these constructs. The results obtained allowed us to identify the following constructs: consumer behavior, customer experience, web content, catalog, terms and conditions, customer support, perceived value, trust, security and privacy, satisfaction, and loyalty. Customer experience, satisfaction, and loyalty constructs stand out from a strategic perspective.

Using the technology acceptance model (TAM), this study investigates factors influencing the adoption of cryptocurrency in Bangladesh.

Data were collected from 346 members of the general public through a structured web survey using snowball sampling. Structural equation modeling was used to analyze the data and assess the reliability and validity of the measurement model.

The results show that knowledge of cryptocurrency, benefits of use (perceived usefulness), attitude and challenges all have a significant impact on the adoption of cryptocurrency.

This study was conducted in a single country, relied on self-reported data and used a cross-sectional design, which limits the ability to draw causal inferences. Future research could explore the factors that influence the adoption of cryptocurrency in different countries and regions and incorporate additional variables to provide a more comprehensive understanding of the drivers of intention to use cryptocurrency.

This study contributes to understanding the factors driving the adoption of and intention to use technology-based services, providing insights that can inform the design and implementation of future technology-based services.

The present study’s aims are twofold: 1) to contribute to theory development by accounting for both personality and trust in the conceptualization of technology acceptance using the technology acceptance model (TAM) as the theoretical framework; and 2) to explore the influence of ChatGPT-integrated chatbots on tourism behavior.

The target population for this study was travelers who previously used technology (website/ app) to plan their holiday abroad. An online survey questionnaire created with Google Forms was distributed via a panel company (iPanel). A screening question was included to filter out respondents who have not previously used technological means to plan their holiday abroad. A panel company (iPanel) was hired to collect data from a convenience sample of 305 Israeli tourists who met the above criterion between August 22 and 27, 2023, and were at least 18.

A significant and positive relationship was observed between trust in ChaptGPT and perceived usefulness. Furthermore, a significant and positive association was observed between perceived ease of use and intentions to use ChatGPT-integrated chatbots to plan future holidays. Post hoc analyses suggest that perceived ease of use mediates the relationship between extraversion and trust, trust mediates the relationship between perceived ease of use and perceived usefulness and age moderates the relationship between perceived ease of use and behavioral intentions.

Data was collected from a convenience sample of Israeli travelers. Hence, generalizations to other countries, nationalities and cultures should be treated carefully; the study is cross-sectional and thus represents respondents’ beliefs and behavioral intentions at a particular time; and the study is based on one of several theoretical frameworks that can be used to conceptualize behaviors associated with using AI by tourists.

The findings of the present study point to the importance of accounting for tourists’ personal factors, such as personality and age, in developing AI products in the tourism industry. chief executive officers and relevant shareholders would benefit from conducting market research to obtain insights into the factors that may enhance or hamper tourists’ adoption of AI-based technology for planning their holidays abroad.

Previous work falls short of accounting for personality traits and trust in a single model using the TAM framework. To the best of the authors’ knowledge, this is the first study empirically investigating tourism behavior related to ChatGPT based chatbots as a tool to plan future holidays abroad. Furthermore, the possible role of age as a moderating variable was overlooked in past research.

本研究的目标有两个：1）采用技术接受模型作为理论框架, 通过考虑技术接受概念化中的个性和信任来促进理论发展; 2）探讨ChatGPT集成的聊天机器人对旅游行为的影响。

本研究的目标人群是以前使用技术（网站/应用程序）计划出国度假的旅行者。使用 Google Forms 创建的在线调查问卷通过小组公司 (iPanel) 分发。其中包含一个筛选问题, 以筛选出之前未使用技术手段计划出国度假的受访者。聘请了一家调查公司（iPanel）来收集 305 名以色列游客的便利样本数据, 这些游客在 2023 年 8 月 22 日至 27 日期间符合上述标准, 且年龄至少为 18 岁。

在 ChaptGPT 的信任度和感知有用性之间观察到显着且积极的关系。此外, 观察到易用性与使用集成 ChatGPT 的聊天机器人来计划未来假期的意向之间存在显着且正相关的关系。事后分析表明, 感知的易用性调节了外向性和信任之间的关系; 信任调节感知易用性和感知有用性之间的关系, 年龄调节感知易用性和行为意愿之间的关系。

以前的工作未能在单个模型中使用技术接受模型框架来解释个性特征和信任。这是第一项实证研究, 调查与 ChatGPT 集成聊天机器人相关的旅游行为, 作为规划未来出国度假的工具。此外, 过去的研究忽视了年龄作为调节变量的可能作用。

1）数据是从以色列旅行者的便利样本中收集的。因此, 应该谨慎对待对其他国家、民族和文化的概括; 2）该研究是横断面的, 因此代表了受访者在特定时间的信念和行为意愿; 3）该研究基于几个理论框架之一, 该框架可用于概念化游客使用 ChatGPT 集成聊天机器人来计划未来出国度假的意向。

本研究的结果表明, 在开发用于旅游业的基于 ChatGPT 的聊天机器人时, 考虑游客的个人因素（例如个性和年龄）的重要性。首席技术官和相关股东将受益于进行市场研究, 以深入了解可能增强或阻碍游客采用基于 ChatGPT 的聊天机器人来规划未来出国度假的因素。

Los objetivos del presente ossib son dos: 1) contribuir al ossibleo de la teoría incorporando la personalidad y confianza en la conceptualización de la aceptación de la tecnología empleando el Modelo de Aceptación de la Tecnología como marco teórico; 2) analizar la influencia de los chatbots integrados en ChatGPT en el comportamiento turístico.

La población objetivo de este ossib fueron los viajeros que anteriormente utilizaban tecnología (página web/aplicación) para planificar sus vacaciones en el extranjero. Se distribuyó un cuestionario online creado con Google Forms a través de una empresa de paneles (iPanel). Se incluyó una pregunta de selección para filtrar a los encuestados que no habían utilizado previamente medios tecnológicos para planificar sus vacaciones en el extranjero. Se contrató a una empresa de paneles (iPanel) para recopilar datos de una muestra de conveniencia de 305 turistas israelíes que cumplieron el criterio anterior entre el 22 y el 27 de ossib de 2023, y con una edad ossib de 18 años.

Se identificó una relación ossibleon y ossible entre la confianza en ChaptGPT y la utilidad percibida. Además, se evidenció una asociación ossibleon y ossible entre la facilidad de uso percibida y la intención de ossible chatbots integrados en ChatGPT para planificar futuras vacaciones. Los análisis post-hoc sugieren que la facilidad de uso percibida media la relación entre la ossibleon y la confianza; la confianza media la relación entre la facilidad de uso percibida y la utilidad percibida, y la edad modera la relación entre la facilidad de uso percibida y las intenciones de comportamiento.

1) los datos se recopilaron de una muestra de conveniencia de viajeros israelíes. Por tanto, las generalizaciones a otros países, nacionalidades y culturas deben tratarse con cuidado; 2) el ossib es transversal y, por tanto, representa las creencias y las intenciones de comportamiento de los encuestados en un momento determinado; 3) el ossib se basa en uno de los diversos marcos teóricos que pueden emplearse para conceptualizar la intención de los turistas de ossible chatbots integrados en ChatGPT para planificar futuras vacaciones en el extranjero.

Los resultados del presente ossib señalan la importancia de tener en cuenta los factores personales de los turistas, como la personalidad y la edad, en el ossibleo de chatbots basados en ChatGPT para su uso en la industria turística. Los directores de tecnología y los stakeholders relevantes se beneficiarían de investigación de mercado para obtener información sobre los factores que pueden mejorar o dificultar la adopción de chatbots basados en ChatGPT por parte de los turistas para planificar futuras vacaciones en el extranjero.

Los trabajos anteriores no tienen en cuenta los rasgos de personalidad y la confianza en un único modelo utilizando ossible TAM. Este es el primer ossib que investiga empíricamente el comportamiento turístico relacionado con los chatbots basados en ChatGPT como herramienta para planificar las futuras vacaciones en el extranjero. Además, en investigaciones anteriores no se ossible el ossible papel de la edad como variable moderadora.

The COVID-19 pandemic has resulted in a brand-new phenomenon in customer consumption patterns. This resulted from heightened health awareness brought on by the COVID-19 epidemic. There is a dearth of appropriate health psychology perspectives in the existing study examining the effect of COVID-19 on consumers’ use of crowdsourced logistics (CL) platforms. In order to provide unique and thorough insights into how consumer health concerns can affect consumers’ subjective views and their decisions to use CL, this study combines the health belief model and the technology acceptance model.

Five hundred valid responses from an online survey that was created and administered in Singapore were analysed using structural equation modelling.

The findings show that all of the suggested constructs have a favourable influence on consumers’ intentions to use CL. The suggested model also demonstrates high explanatory power, with perceived usefulness serving as the primary driver, followed by perceived ease of use and self-efficacy.

The study advances previous academic research on CL and offers guidance to CL companies and lawmakers for promoting sustainable and secured last-mile delivery.

This research aims to build on the pre-existing corpus of literature through the integration of the technology acceptance model (TAM) and usage habit to more accurately capture the determinants associated with social media addiction among university students. This study seeks to delineate how usage habit and TAM may be used as predictors for addiction potential, as well as provide greater insight into current trends in social media usage across this population demographic.

A cross-sectional research design was employed to investigate the determinants of social media addiction among university students in Malaysia at the onset of their tertiary education. A self-administered survey, adapted from prior studies, was administered to a sample of 217 respondents. The hypotheses on social media addiction were subsequently tested using a partial least squares structural equation modeling (PLS-SEM) approach.

Usage habit was found to be a direct and strong predictor of this type of addiction, as well as all TAM variables considered in the research. Additionally, by integrating TAM with usage habit, the study revealed a comprehensive and multi-faceted understanding of social media addiction, providing an important insight into its complexity in the Malaysian context. Although several other factors have been identified as potential contributors to social media reliance and addictive behavior, it appears that usage habit is paramount in driving these addictive tendencies among university students.

This expanded model holds significant implications for the development of interventions and policies that aim to mitigate the adverse effects of social media addiction on students' educational and psychological well-being. The study illustrates the applicability of the TAM in examining addictive behaviors within emerging contexts such as the Malaysian higher education sector, thus contributing to the extant literature on the subject.

The integrated TAM and habit model is an effective predictor of social media addiction among young adults in developing countries like Malaysia. This highlights the importance of actively monitoring and controlling users' interactions with technology and media platforms, while promoting responsible usage habits. Educators can use these findings to create tailored educational programs to educate students on how to use technology responsibly and reduce their risk of becoming addicted to social media.

This study provides a unique perspective on social media addiction among university students. The combination of TAM and usage habit has the potential to shed significant light on how variables such as perceived usefulness (PU) and perceived ease of use (PEOU) may be associated with addictive behaviors. Additionally, by considering usage habit as an explanatory factor, this research offers a novel approach to understanding how addictions form over time.

Though widely recognized as essential for improving work performance across various domains, self-efficacy’s specific role in managing construction workforces remains understudied. This knowledge gap restricts our ability to uncover new factors that enhance workforce management effectiveness and ultimately boost construction labor productivity (CLP). To address this, our study proposes and tests a novel model. This model explores the impact mechanism of self-efficacy on CLP by investigating the mediating role of work motivation. By delving into this crucial yet underexplored area, we aim to provide valuable insights for construction project managers and researchers alike, paving the way for more effective workforce management strategies and consequently, improved CLP.

This study utilizes a mixed-method approach, incorporating both qualitative and quantitative methodologies. Data from 112 rebar workers at five construction sites in Vietnam underwent analysis using Cronbach’s alpha, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) to examine the novel research model.

The results indicate a positive and significant association between self-efficacy and CLP. Additionally, work motivation emerged as a full mediator in the relationship between self-efficacy and CLP. Specifically, individuals with higher self-efficacy set ambitious goals and invest more effort in their pursuit, leading to increased work motivation and, ultimately, heightened productivity levels.

The significant implications of the current study extend to construction managers and policymakers alike. Construction managers can leverage the findings to devise targeted interventions aimed at enhancing the self-efficacy and work motivation of their workforce, potentially resulting in noteworthy enhancements in CLP. Policymakers, too, can benefit from these findings by formulating policies that actively support the cultivation of self-efficacy and work motivation among construction workers. Such policies have the potential to foster a more productive and efficient construction industry, aligning with the broader goals of workforce development and industry enhancement.

This study expands existing knowledge by identifying the important role of self-efficacy in work performance enhancement and the mediating role of work motivation in terms of these relationships.

Mobile location-based service (m-LBS) seems like a new class of personalized service due to location positioning technologies. This work aims to investigate consumer readiness (RED) toward m-LBS based on integrating pull effect- and push effect-related factors into the technology acceptance model (TAM).

An online survey collected data from 423 participants, and the research framework was analyzed using structural equation modeling (SEM).

The results divulge that consumer RED is determined by TAM antecedents, including usefulness (USE) and ease of use (EOU). EOU motivates USE in m-LBS. Regarding pull effect-related factors, absorptive capacity (ABC) is the strongest positive factor influencing consumer RED to use m-LBS, followed by technology willingness (TWI) and innovativeness (INN). Moreover, INN, trust (TRU) and perceived risk (RIS) significantly influence USE and EOU.

This work endeavors to explicate customer RED toward m-LBS by incorporating some meaningful pull effect-related dimensions (i.e. ABC, TWI and INN) and pushing effect-related dimensions (i.e. RIS) into crucial antecedents rooted in TAM. Thus, the findings assist practitioners in developing marketing strategies by boosting pull effects and controlling push effects on customer engagement in m-LBS.