Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal

Engineering students' perceptions and actual use of AI-based math tools for solving mathematical problems

The immediate advancement of AI technologies as educational technology revolutionized the learning environment of students; contributing to their academic performance will require an understanding of the factors that influenced the acceptance of AI tools. Insufficient studies were seen from literature review that focused on the integrated factors that influenced the perception of acceptance and actual usage of AI-based math tools among engineering students. The objective of this study was to evaluate the variables that influenced the engineering students' perceptions of adoption and actual academic use of AI-based math tools as academic assistance. This study identified the determinants of behavioral, technology use, and motivation by utilizing the higher-order Unified Theory of Acceptance and Use of Technology (UTAUT3), self-determination theory, and the variable trust to examine the behavioral intention influencing adoption of AI tools. A total of 565 valid respondents were analyzed through purposive sampling using structural equation modeling. The results revealed that hedonic motivation, perceived competence, performance expectancy, and habit are the most significant indicators of both students' behavioral intentions and actual use of AI-based math tools. The outcome indicated that students are more inclined to utilize AI tools when they find them engaging and are convinced that they can employ them efficiently and incorporate the tools in their academic routines. From the result, perceived autonomy was deemed insignificant to behavioral intentions, suggesting that students utilize AI tools for functionality and benefits in their academic performance rather than the adaptability of the tools. The outcome of the study may be considered evaluating the behavioral intention and adoption of the students towards innovative AI tools. The results in this study could be extended and applied to the assessment of factors in educational technology studies. Proper ethical use, managerial implications, and theoretical contributions were also discussed after obtaining the output of this study - deeming AI math tools as guide and resource among students and not as a substitute for solutions on mathematical problems.

The trust paradox: An exploration of consumer psychology and behavior in cross-border shopping using E-commerce mobile applications

This study explores consumer psychology and behavior in cross-border e-commerce mobile applications, with a specific focus on the interrelationships among trust, perceived risk, satisfaction, and behavioral intention. The findings emphasize the pivotal role of satisfaction as a mediating variable, which effectively mitigates uncertainty and enhances behavioral intention within the cross-border shopping context. Furthermore, the research identifies a "trust-risk paradox," wherein increased trust does not invariably lead to a reduction in perceived risk, thereby challenging conventional theoretical assumptions. While perceived risk exhibits a limited direct influence on behavioral intention, its substantial indirect effect through satisfaction underscores the intricate nature of consumer decision-making processes. Utilizing empirical data from Taiwanese consumers, this study provides critical insights into the structural relationships among these constructs, offering both practical implications for CBEC platform strategies and contributions to theoretical development. By investigating the dynamic interactions in cross-border consumer behavior, this research advances the understanding of high-uncertainty markets and establishes a solid foundation for future scholarly inquiry.

The experiences of the elderly regarding the use of rehabilitation assistive technologies: a directed qualitative content analysis

PURPOSE

The elderly population faces reduced levels of health and performance, which necessitates the use of rehabilitation assistive technologies to maximize functional independence in daily activities. This study aimed to explain the experiences of the elderly regarding the use of rehabilitation assistive technologies based on the Unified Theory of Acceptance and Use of Technology.

METHODS

The present study was a qualitative study of the type of content analysis that was conducted in the city of Hamadan in 2022. Participants included 20 elderly aged 60 years or above who were selected as a purposive sample and subjected to individual semi-structured in-depth interviews. Data were analyzed using directed qualitative content analysis based on Hsieh and Shannon's approach. Data were coded using MAXQDA software (MAXQDA Analytics Pro 2020, VERBI GmbH Berlin).

RESULTS

According to the results, 260 primary codes were extracted, and they were classified into five predetermined categories of the Unified Theory of Acceptance and Use of Technology, including performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention, as well as two new categories of technology anxiety and perceived need for technology. After extracting 260 primary codes based on the Unified Theory of Acceptance and Use of Technology, 75 sub-categories were identified in 14 main categories.

CONCLUSION

The themes obtained from the study indicate the necessity of providing the required conditions to maintain the complete independence and health of the elderly and strengthen their morale. The results can be helpful in the development of support strategies for family members, healthcare providers, and policymakers.

Chinese Consumers' Attitudes toward and Intentions to Continue Using Skill-Sharing Service Platforms

The sharing economy has rapidly transformed traditional consumption patterns worldwide. The emergence of skill-sharing services-which allow individuals to share their skills, abilities, and time through online platforms-has recently garnered attention. In China, the demand for skill-sharing services continues to grow, as these services effectively meet consumer needs. To understand this growing demand, this study aims to explore users' attitudes and intentions toward the use of skill-sharing service platforms in the Chinese market. A survey was conducted that incorporated 500 Chinese users who had used skill-sharing service platforms over the previous three months. A total of 409 datasets were analyzed, using structural equation modeling and multiple group analysis, in AMOS 24.0. The results showed that performance expectancy, effort expectancy, social influence, facilitating conditions, and self-efficacy positively influenced users' attitudes toward skill-sharing services, while privacy, functionality, and safety risks negatively affected these attitudes. Users' attitudes toward skill-sharing services significantly enhanced their intentions to continue using them, with the level of trust playing a crucial moderating role between attitude and the intention to continue using these services. These findings provide a significant theoretical and practical foundation for the further development of skill-sharing service platforms, the optimization of marketing strategies, and future research.

The path to cashless transaction: A study of user intention and attitudes towards quick response mobile payments

This study explores the factors influencing users' behavioral intentions, attitudes and actual adoption of quick response (QR) mobile payment in the least developed country (LDC) of Bangladesh, by extending the original unified theory of acceptance and use of technology (UTAUT) model. The study conducts a mixed-methods investigation by combining the partial least squares (PLS) and focus group discussion (FGD) methods to empirically evaluate the research model and cross-validate the findings. Using purposive sampling, data were gathered from 412 respondents, followed by 10 respondents who took part in the FGD, who all met the sample criteria. The study findings indicate that performance expectancy, effort expectancy, and social influence significantly positively influence users' behavioral intention, while self-concept, perceived self-efficacy, and habit substantially influence their attitudes towards using QR mobile payments. The findings also confirm a positive effect of users' attitudes toward using QR mobile payment on both behavioral intention and actual use, and a positive effect of behavioral intention on the actual use of QR mobile payments. These findings offer several important theoretical and managerial implications.

Analysis of college students' attitudes toward the use of ChatGPT in their academic activities: effect of intent to use, verification of information and responsible use

BACKGROUND

In recent years, the use of artificial intelligence (AI) in education has increased worldwide. The launch of the ChatGPT-3 posed great challenges for higher education, given its popularity among university students. The present study aimed to analyze the attitudes of university students toward the use of ChatGPTs in their academic activities.

METHOD

This study was oriented toward a quantitative approach and had a nonexperimental design. An online survey was administered to the 499 participants.

RESULTS

The findings of this study revealed a significant association between various factors and attitudes toward the use of the ChatGPT. The higher beta coefficients for responsible use (β=0.806***), the intention to use frequently (β=0.509***), and acceptance (β=0.441***) suggested that these are the strongest predictors of a positive attitude toward ChatGPT. The presence of positive emotions (β=0.418***) also plays a significant role. Conversely, risk (β=-0.104**) and boredom (β=-0.145**) demonstrate a negative yet less decisive influence. These results provide an enhanced understanding of how students perceive and utilize ChatGPTs, supporting a unified theory of user behavior in educational technology contexts.

CONCLUSION

Ease of use, intention to use frequently, acceptance, and intention to verify information influenced the behavioral intention to use ChatGPT responsibly. On the one hand, this study provides suggestions for HEIs to improve their educational curricula to take advantage of the potential benefits of AI and contribute to AI literacy.

Informing existing technology acceptance models: a qualitative study with older persons and caregivers

New technologies can help older persons age in place and support their caregivers. However, they need to be accepted by the end-users to do so. Technology acceptance models, such as TAM and UTAUT and their extensions, use factors like performance expectancy and effort expectancy to explain acceptance. Furthermore, they are based on quantitative methods. Our qualitative study investigates factors fostering and hindering acceptance among older persons and their caregivers for a variety of assistive technologies, including wearables, ambient sensors at home with and without cameras and social companion robots. The goal of this paper is twofold: On the one hand, it investigates the factors of technology acceptance models in a qualitative setting. On the other hand, it informs these models with aspects currently overlooked by them. The results reveal that performance expectancy and effort expectancy are relevant for acceptance. We also find that reliability, anxiety around technology and different social aspects have an influence on acceptance of assistive technology in aged care for all end-user groups. Our findings can be used to update current technology acceptance models and provide in-depth knowledge about the currently used factors.

Investigating the acceptance intentions of online shopping assistants in E-commerce interactions: Mediating role of trust and effects of consumer demographics

Online shopping has various advantages, such as convenience, easy access to information, a greater variety of products or services, discounts, and lower prices. However, the absence of salespeople's personalized assistance decreases the online customer experience. Business-to-consumer e-commerce companies are increasingly implementing online shopping assistants (OSAs), interactive and automated tools used to assist customers without salespeople's assistance. However, no comprehensive model of OSA acceptance in e-commerce exists, including constructs from multiple information system disciplines, sociopsychology, and information security. This study aims to fill these gaps by empirically investigating consumers' intention to accept OSAs from a functional, social, relational, and security perspective. It identifies OSA acceptance factors in e-commerce through an extensive literature review and expert opinion. A research model is proposed after identifying structural relationships among the study's variables from the literature. The study employs partial least squares-structural equation modeling (PLS-SEM) to validate the proposed model empirically. The results indicate that anthropomorphism, attitude, ease of use, enjoyment, privacy, trust, and usefulness are crucial determinants of acceptance variables. There are significant moderating effects of respondents' gender and education on OSA acceptance. The study's results have substantial implications for academia, extending and validating the Technology Acceptance Model (TAM) for OSA acceptance in e-commerce. The study will help e-commerce marketers develop optimal adoption strategies when implementing OSAs on social media platforms.

Modelling the mass consumption potential of Plant Based Meat: Evidence from an emerging economy

The rising demand for plant-based meat (PBM) has the potential to minimize environmental degradation and save the lives of numerous animals. Furthermore, the intention to consume eco-friendly products triggers people to consume PBM. However, it is essential to understand the factors that influence consumer intentions and actual PBM consumption to enhance its adoption. By incorporating the Theory of Consumption Value, this study examines the impact of health consciousness, health motivation, personal innovativeness, perceived critical mass, perceived cost, and perceived product value on the intention to consume PBM. The impact of intention to consume PBM on actual consumption is also analyzed. Furthermore, the mediating role of the intention to consume PBM in the relationship between these factors and actual consumption behavior is investigated. Using a cross-sectional research design, 978 responses were obtained from Indonesia. The data were analyzed using partial least squares structural equation modelling (PLS-SEM). The results showed that health motivation, perceived critical mass perceived cost, and perceived product value were significant predictors of the intention to consume PBM. However, health motivation and personal innovation had insignificant effects on the intention to consume PBM. Moreover, the intention to consume PBM translated into actual consumption behavior. Furthermore, the intention to consume PBM significantly mediated the relationship between actual consumption behavior and factors other than health motivation, personal innovation, and perceived product value. The findings offer valuable insights for industry, policymakers, and producers interested in PBMA markets in developing focused marketing strategies, improving consumer perceptions, and addressing barriers, such as perceived costs to promote PBM consumption, particularly in emerging markets. Integrating the theory of consumption value and PLS-SEM provides a comprehensive understanding of the underlying dynamics and sheds light on the unique factors driving PBM consumption behavior.

A longitudinal study on artificial intelligence adoption: understanding the drivers of ChatGPT usage behavior change in higher education

As the field of artificial intelligence (AI) continues to progress, the use of AI-powered chatbots, such as ChatGPT, in higher education settings has gained significant attention. This paper addresses a well-defined problem pertaining to the critical need for a comprehensive examination of students' ChatGPT adoption in higher education. To examine such adoption, it is imperative to focus on measuring actual user behavior. While measuring students' ChatGPT usage behavior at a specific point in time can be valuable, a more holistic approach is necessary to understand the temporal dynamics of AI adoption. To address this need, a longitudinal survey was conducted, examining how students' ChatGPT usage behavior changes over time among students, and unveiling the drivers of such behavior change. The empirical examination of 222 Dutch higher education students revealed a significant decline in students' ChatGPT usage behavior over an 8 month period. This period was defined by two distinct data collection phases: the initial phase (T1) and a follow-up phase conducted 8 months later (T2). Furthermore, the results demonstrate that changes in trust, emotional creepiness, and Perceived Behavioral Control significantly predicted the observed change in usage behavior. The findings of this research carry significant academic and managerial implications, as they advance our comprehension of the temporal aspects of AI adoption in higher education. The findings also provide actionable guidance for AI developers and educational institutions seeking to optimize student engagement with AI technologies.

An empirical investigation on actual usage of educational app: Based on quality dimensions and mobile self-efficacy

The intention of this research is to analyze the actual use of educational app by Chinese students for learning purpose. Based on DeLone & McLean (D&M) this study proposes and tests a research model which analyzes the actual use of educational apps using data collected from the 357 Chinese students. Structural equation modeling (SEM) was applied to examine the hypothesis. Findings specify that information quality, system quality, service quality, mobile self-efficacy, and personal innovativeness is considerably associated to intentions to use educational app which eventually influences actual usage of educational apps. Additionally, trust in educational apps strengthens the connection between intentions to use educational apps and actual use of educational apps by students for learning purposes. However, the perceived risk indicated an insignificant association between intention to use educational apps and actual use of educational apps. This study contributes to DeLone & McLean (D&M) model by examing the moderating role of perceived risk, trust in an educational app.

Exploration of the acceptability of different behaviors of an autonomous vehicle in so-called conflict situations

The acceptability of autonomous vehicles is an important issue for car manufacturers. The subject of this work attempts to address this issue in the context of conflict situations in urban environments. We present the results of a preliminary study that was conducted to investigate the effects of the driving mode and context on the acceptability of the behavior of an autonomous vehicle. We thus measured acceptability on 30 drivers confronted with three driving modes (defensive, aggressive, and transgressive) as well as different situations constituted by the most common urban intersections in France. We then formulated hypotheses on the effects that the driving mode, the context, or the socio-demographic characteristics of the passengers may have on their acceptability of the autonomous vehicle behavior. In the context of our study, the driving mode of the vehicle was the most influential parameter on the level of acceptability assessed by the participants. The type of intersection used did not result in a significant difference, nor did the socio-demographic characteristics studied. The results of these works allow an interesting first approach and lead us to guide our future works on the study of the parameters involved in the driving modes of autonomous vehicles.

Exploring chatbot trust: Antecedents and behavioural outcomes

An awareness about the antecedents and behavioural outcomes of trust in chatbots can enable service providers to design suitable marketing strategies. An online questionnaire was administered to users of four major banking chatbots (SBI Intelligent Assistant, HDFC Bank's Electronic Virtual Assistant, ICICI bank's iPal, and Axis Aha) in India. A total of 507 samples were received of which 435 were complete and subject to analysis to test the hypotheses. Based on the results, it is found that the hypothesised antecedents, except interface, design, and technology fear factors, could explain 38.6% of the variance in the banking chatbot trust. Further, in terms of behavioural outcomes chatbot trust could explain, 9.9% of the variance in customer attitude, 11.4% of the variance in behavioural intention, and 13.6% of the variance in user satisfaction. The study provides valuable insights for managers on how they can leverage chatbot trust to increase customer interaction with their brand. By proposing and testing a novel conceptual model and examining the factors that impact chatbot trust and its key outcomes, this study significantly contributes to the AI marketing literature.

Factors influencing the adoption of cashless transactions during COVID-19: an extension of enhanced UTAUT with pandemic precautionary measures

This paper aims to extend the enhanced “unified theory of acceptance and use of technology (UTAUT)” model with pandemic precautionary measures (PPM) to examine the variables that influence the adoption of “cashless transactions (CLT)” during pandemic periods such as COVID-19. For this purpose, this research polled 363 people from 15 zones of Chennai City, India. Utilizing the responses, the relationship between components was explored using a PLS-SEM approach in two distinct research models to examine the influence of PPM in the enhanced UTAUT. The results indicate that the model with PPM (model 2) exhibited an improvement over the model without PPM (model 1) in the variance explained of behavioural intention from 77.3 to 82%. Further, in model 1, performance expectation is the most potent predictor of individuals’ intentions to use CLT, and in model 2, performance expectations deteriorated slightly in its ability and PPM became the most potent predictor. Furthermore, these findings reveal that the PPM-included enhanced UTAUT has significantly strengthened its ability to explain behavioural intent to adopt CLT. Thus, this research model has the potential to be of great use in investigating the adoption of CLT in any epidemic period.

Understanding the adoption context of China's digital currency electronic payment

Central banks worldwide have started researching and developing central bank digital currencies (CBDCs). In the digital economy context, concerns regarding the integrity, competition, and privacy of CBDC systems have also gradually emerged. Against this backdrop, this study aims to evaluate users' willingness to use China's digital currency electronic payment (DCEP) system, a digital payment and processing network, and its influencing factors by comprehensively considering and comparing the characteristics of cash and third-party payment services. Combining the push-pull-mooring framework (PPM) and task-technology fit (TTF) theory, we discuss the scenarios and mechanisms that may inspire users' DCEP adoption intention through an empirical study. The results reveal that privacy concerns regarding the original payment methods and technology-task fitting level of DCEP positively impact users' willingness to adopt DCEP. The technical characteristics of DCEP, users' payment requirements, and government support positively affect users' adoption intention by influencing the task-technology fitting degree of DCEP. Switching cost significantly and negatively impacts adoption intention, whereas relative advantage exhibits no significant effect. This research contributes to a better understanding of the factors that influence switching intentions and the actual use of DCEP, and provides policy guidance on promoting the efficiency and effectiveness of DCEP.

Getting Connected to M-Health Technologies through a Meta-Analysis

The demand for mobile e-health technologies (m-health) continues with constant growth, stimulating the technological advancement of such devices. However, the customer needs to perceive the utility of these devices to incorporate them into their daily lives. Hence, this study aims to identify users' perceptions regarding the acceptance of m-health technologies based on a synthesis of meta-analysis studies on the subject in the literature. Using the relations and constructs proposed in the UTAUT2 (Unified Theory of Acceptance and Use of Technology 2) technology acceptance model, the methodological approach utilized a meta-analysis to raise the effect of the main factors on the Behavioral Intention to Use m-health technologies. Furthermore, the model proposed also estimated the moderation effect of gender, age, and timeline variables on the UTAUT2 relations. In total, the meta-analysis utilized 84 different articles, which presented 376 estimations based on a sample of 31,609 respondents. The results indicate an overall compilation of the relations, as well as the primary factors and moderating variables that determine users' acceptance of the studied m-health systems.

Examining trust, self-efficacy, and technology acceptance in the Philippines’ e-commerce sectors

Despite intensified use of information and communication technologies (ICTs) supporting increased demand for online services, some entities are still unable to take full advantage of their benefits. This is mostly due to differing degrees of ICT adoption and of appreciation of what ICTs can do. This research, utilizing a UTAUT-based theoretical framework integrated with trust, self-efficacy, perceived risk, anxiety, and utilitarian and hedonic motivations, provides additional insights on the contextual differences that are present within e-commerce use. Analyzing data from 997 Philippine respondents across websites and mobile apps and across retail, banking, food services, and tourism booking organizations through structural equation modeling (SEM) yielded consistently favorable influences of self-efficacy and hedonic motivations, as well as interesting insights on the factors influencing attitudes and intentions towards using these e-commerce platforms. These results open several theoretical and practical implications and suggestions emphasizing a more directed, rather than blanket, approach in managing e-commerce technologies depending on the context.

Moderating Role of Perceived Trust and Perceived Service Quality on Consumers’ Use Behavior of Alipay e-wallet System: The Perspectives of Technology Acceptance Model and Theory of Planned Behavior

The advancement of e-wallet systems, including Alipay, has led consumers to embrace digital payment with financial technologies. Yet, limited research focused on the usage of e-wallets in the context of emerging economies. This research is aimed at investigating the predictors of consumers’ use behavior of the Alipay e-wallet system in an emerging market and moderating role of perceived trust and perceived service quality on this relationship. The technology acceptance model (TAM) and the theory of planned behavior (TPB) were applied as the guiding principle. Data gathered via online surveys among 378 Malaysian Alipay users were analyzed using the partial least square-structural equation modeling (PLS-SEM) approach. The results reveal that all hypotheses were significant towards consumers’ intention to use Alipay in an emerging market except for the moderating role of perceived trust. Perceived usefulness was the strongest predictor factor towards consumers’ intention to use Alipay in an emerging market. This is followed by perceived ease of use. They heavily emphasize the superiorities of Alipay over other e-wallet systems such as efficiency and convenience for conducting financial activities. This study contributes to the existing literature by proposing a comprehensive integrated research model. The research outcome can serve as a guideline for service providers towards enhancing consumers’ adoption of e-wallets for digital payment with financial technologies.

Enhancing Nurse-Robot Engagement: Two-Wave Survey Study

BACKGROUND

Robots are introduced into health care contexts to assist health care professionals. However, we do not know how the benefits and maintenance of robots influence nurse-robot engagement.

OBJECTIVE

This study aimed to examine how the benefits and maintenance of robots and nurses' personal innovativeness impact nurses' attitudes to robots and nurse-robot engagement.

METHODS

Our study adopted a 2-wave follow-up design. We surveyed 358 registered nurses in operating rooms in a large-scale medical center in Taiwan. The first-wave data were collected from October to November 2019. The second-wave data were collected from December 2019 to February 2020. In total, 344 nurses participated in the first wave. We used telephone to follow up with them and successfully followed-up with 331 nurses in the second wave.

RESULTS

Robot benefits are positively related to nurse-robot engagement (β=.13, P<.05), while robot maintenance requirements are negatively related to nurse-robot engagement (β=-.15, P<.05). Our structural model fit the data acceptably (comparative fit index=0.96, incremental fit index=0.96, nonnormed fit index=0.95, root mean square error of approximation=0.075).

CONCLUSIONS

Our study is the first to examine how the benefits and maintenance requirements of assistive robots influence nurses' engagement with them. We found that the impact of robot benefits on nurse-robot engagement outweighs that of robot maintenance requirements. Hence, robot makers should consider emphasizing design and communication of robot benefits in the health care context.

Algorithms in the court: does it matter which part of the judicial decision-making is automated?

Artificial intelligence plays an increasingly important role in legal disputes, influencing not only the reality outside the court but also the judicial decision-making process itself. While it is clear why judges may generally benefit from technology as a tool for reducing effort costs or increasing accuracy, the presence of technology in the judicial process may also affect the public perception of the courts. In particular, if individuals are averse to adjudication that involves a high degree of automation, particularly given fairness concerns, then judicial technology may yield lower benefits than expected. However, the degree of aversion may well depend on how technology is used, i.e., on the timing and strength of judicial reliance on algorithms. Using an exploratory survey, we investigate whether the stage in which judges turn to algorithms for assistance matters for individual beliefs about the fairness of case outcomes. Specifically, we elicit beliefs about the use of algorithms in four different stages of adjudication: (i) information acquisition, (ii) information analysis, (iii) decision selection, and (iv) decision implementation. Our analysis indicates that individuals generally perceive the use of algorithms as fairer in the information acquisition stage than in other stages. However, individuals with a legal profession also perceive automation in the decision implementation stage as less fair compared to other individuals. Our findings, hence, suggest that individuals do care about how and when algorithms are used in the courts.

Using the UTAUT model to analyze user intention to accept electronic payment systems in Serbia

This study applies The Unified Theory of Acceptance and Use of Technology (UTAUT) to explain the acceptance of electronic payment systems in Serbia. We used extended model that incorporates several external variables, such as perceived security, trust, privacy, convertibility and financial costs, along with basic UTAUT predictors. The sample comprised of 457 respondents. We applied structural equation modelling to develop the model and draw conclusions. The results showed that performance expectancy, perceived security, trust and social influence had strong positive effects on behavioral intention. Conversely, we found behavioral intention, convertibility and financial costs to be significant drivers of user behavior. We consider the inclusion of convertibility in the model and proving its significance to be the main practical implications of our research, and also suggest to be considered as a factor in models designed for countries with low purchasing power of national currency.

Technology Adoption and Human Resource Management Practices: The Use of Artificial Intelligence for Recruitment in Bangladesh

Artificial intelligence (AI) is now considered indispensable in undertaking operational activities, especially in the area of human resource analytics. However, in practice, the rate of the adoption of such modern algorithms in organisations is still in its early stages. Consequently, the primary objective of this study is to identify the main antecedents of the adoption of AI-based technologies in recruitment, using the lens of the unified theory of acceptance and use of technology (UTAUT) model, alongside perceived credibility and moderating variables, in the context of an emerging nation in South Asia, namely Bangladesh. Data were collected from 283 human resource professionals employed in different manufacturing and service firms in Bangladesh through the administration of a questionnaire, which was analysed by applying PLS-SEM. The outcomes of the study show that all the direct hypothesised relationships were found to be significant, apart from the extended variable of perceived credibility. However, no moderating effect of gender or firm size was found in any of the hypothesised propositions. Finally, policy implications and recommendations for future researchers are proposed.

Patients' Intention to Adopt Fintech Services: A Study on Bangladesh Healthcare Sector

Advancement in technology has facilitated the shift toward new financial services. Numerous industries have undergone a digital transformation because of the expansion of cashless payment systems and other cutting-edge technologies. This study aimed to identify the factors that stimulate the patient's intention to adopt fintech services in the Bangladesh healthcare sector. To facilitate the study, data were collected through survey questionnaires from different hospitals and diagnostic centers patients. A total of 279 patients responded to the survey. The study employed structural equation modelling to analyze the data using SMART PLS 3.2.9. The results revealed that a significant relationship exists between perceived ease of use, social influence, facilitating conditions, personal innovativeness, and perceived trust in fintech services, and the adoption intention of the patients. The results of the study are beneficial to the healthcare sector and fintech companies who wish to make necessary arrangements to advance the growth of cashless fintech-based transactions.

Pleasure of paying when using mobile payment: Evidence from EEG studies

Mobile payment has emerged as a popular payment method in many countries. While much research has focused on the antecedents of mobile payment adoption, limited research has investigated the consequences of mobile payment usage relating to how it would influence consumer behaviors (e.g., purchase intention or willingness to pay). Here, we propose that mobile payment not just reduces the “pain of paying,” a traditional view explaining why cashless payment stimulates spending, but it also evokes the “pleasure of paying,” raising from the enhanced processing fluency in completing transactions. We tested this new conceptualization of “pleasure of paying” using EEG, complementing other behavioral measures. In two studies, we found that mobile payment effectively enhanced purchase likelihood (study 1, N = 66) and such an enhancement is generalizable to both hedonic and utilitarian products (study 2, N = 29). By employing EEG measures, we provided the first neural evidence of “pleasure of paying” in addition to the signal of “pain of paying.” Critically, we demonstrated that the “pleasure of paying” is a distinctive psychological mechanism that is induced by mobile payment usage and that the “pleasure of paying” joins the “pain of paying” to mediate the increased purchase intention. We discuss the contributions and implications of these results to the ongoing evolution of cashless payment societies.

Modelling the intention and adoption of cashless payment methods among the young adults in Malaysia

Purpose

Cashless payment is gradually replacing physical currency in almost every financial transaction across the world. Even though cashless payment methods have been available in Malaysia since a decade ago, their usage has remained relatively low in comparison to other countries. This study aims to analyse the elements that affect the Malaysian youth’s adoption intention and actual use of cashless payment by extending the unified theory of acceptance and use of technology (UTAUT) model with two key factors (perceived security [PS] and lifestyle compatibility [LC]).

Design/methodology/approach

Data were gathered online from 364 Malaysian youths and processed using partial least squares structural equation modelling.

Findings

The findings revealed that performance expectancy (PE), LC and PS had a positive and substantial effect on the intention to use cashless payment (ICP). In contrast, effort expectancy (EE) and social influence did not have any considerable influence on ICP. Furthermore, ICP had substantial mediating effects between the adoption of cashless payment (ACP) and PE, LC and PS. In the analysis of the moderating effect of age, gender, experience and voluntariness, only experience had moderating effects on the associations between PE and ICP and between FC and ACP.

Research limitations/implications

This study’s findings will be highly useful for marketers and the management as they plan their promotional and marketing tactics, with a focus on the factors that inspire customers to adopt cashless payments. Besides, architects and designers can benefit from the study results while designing and updating their services by consolidating consumers’ lifestyle standards as well as enhancing security features. Finally, governments may support service providers with security building through legislative measures and policy campaigns to strengthen the trustworthiness and mass adoption of contactless payment.

Originality/value

This study extended the UTAUT model with two new variables, i.e. PS and LC.

Resistance to innovation in low-income populations: The case of university students' resistance to using digital productivity applications

Innovation resistance research remains in its early stages. Efforts to define and comprehend consumer resistance to innovation necessitate in-depth studies that consider the contextual factors of resistance to innovation. To address this challenge, this research explored consumer resistance to innovation in a low-income population, namely, university students on financial support. The innovation under this study is the productivity applications provided for free by the University of Hail, Saudi Arabia, to all students. This study explores variables such as value barrier, risk barrier, tradition barrier, and image barrier and how they impact consumer resistance to innovation in a low-income population. We extend the theory by investigating the moderating roles of consumer characteristics (motivation, self-efficacy, emotion, and attitude toward existing products). The current study is based on an online survey of low-income students at a Saudi Arabian University; 258 cases were gathered. We found that all the direct effects of the variables (i.e., Value Barrier, Risk Barrier, Tradition Barrier, and Image Barrier) were positively related to consumer resistance to innovation. Importantly, consumer characteristics significantly moderate this relationship, as the relationship is stronger when the measurements for consumer characteristics are high.

Mobile wallet adoption intention amid COVID-19 pandemic outbreak: A novel conceptual framework

This research aims to explore adoption intention towards mobile wallet (m-wallet) amid COVID-19 outbreak using mediated-moderation framework. This study, in its uniqueness, utilises the stimulus-organism-response (S-O-R) theory as its theoretical base. The study investigated the effect of relative advantage, ease of effort, favourable infrastructure conditions, security considerations, and touch-free transactions on m-wallet adoption. The model includes perceived values as a mediator and perceived critical mass (PCM), promotional benefits (PBs) and users' demographics as moderators for deeper understanding of the phenomenon. A total of 327 responses were collected using purposive sampling method. The results revealed that relative advantage, favourable infrastructure conditions, security considerations and touch-free transactions exert a positive significant effect on m-wallet adoption intention. Further, except for ease of effort, perceived values mediate the association among antecedents and adoption intention and PCM, PBs and age found to be crucial moderators between perceived values and intention. This study enriches the existing literature on the adoption of m-wallet. Practically, this study helps marketers frame strategies to enhance the adoption and usage of m-wallet.

Building a Three-Level User Experience (UX) Measurement Framework for Mobile Banking Applications in a Chinese Context: An Analytic Hierarchy Process (AHP) Analysis

User experience (UX) has drawn the attention of the banking industry in the past few decades. Although banking systems have a complete service process to ensure financial safety for customers, the mobile banking UX has much potential to be improved. Most research in this field of study relies on existing criteria to describe a user’s experience. However, these criteria are focused more on usability measurement, which neglects to identify the requirements of end-users. Users are asked to give feedback on the provided application, limiting the scope of the user study. Therefore, this study uses mixed methods research and in-depth semi-structured interviews to collect end-user UX requirements to build a UX measurement framework of five main services transfers, including financial management, loans, account openings, and credit cards. This study uses an online survey to validate and revise the framework by applying analytic hierarchy process (AHP) analysis to quantify criteria. We interviewed 17 customers and collected 857 online validation surveys, and 400 customers attended the AHP analysis. As a result, this study proposes a three-level measurement framework for mobile banking applications in a Chinese context. The first-level criteria are scenario requirements (24.03%), data requirements (20.98%), and function requirements (54.99%). We hope that the framework will guide designers and researchers to design better user-friendly user interfaces and improve customer satisfaction rates in the future.

The Role of Personality and Top Management Support in Continuance Intention to Use Electronic Health Record Systems among Nurses

This study examines nurses' Continuance Intention (CI) to use electronic health records (EHRs) through a combination of three conceptual frameworks: the Unified Theory of Acceptance and Use of Technology (UTAUT), the theory of expectation-confirmation (ECT), and the Five-Factor Model (FFM). A model is developed to examine and predict the determinants of nurses' CI to use EHRs, including top management support (TMS) and the FFM's five personality domains. Data were collected from a survey of 497 nurses, which were analyzed using partial least squares. No significant relationship was found between TMS and CI. The study revealed that performance expectancy significantly mediated the influences of two different hypotheses of two predictors: agreeableness and openness to testing CI. A significant moderating impact of conscientiousness was found on the relationship between performance expectancy and CI and the relationship between social influence and CI. The findings of this study indicated that rigorous attention to the personality of individual nurses and substantial TMS could improve nurses' CI to use EHRs. A literature gap was filled concerning the mediating effects of performance expectancy on the FFM-CI relationship, and the moderation effects of Conscientiousness on UTAUT constructs and CI are another addition to the literature. The results are expected to assist government agencies, health policymakers, and health institutions all over the globe in their attempts to understand the post-adoption use of EHRs.

Predicting the intention to adopt wearable payment devices in China: The use of hybrid SEM-Neural network approach

Wearable payment devices (WPD) are gaining acceptance fast and transforming everyday life and commercial operations in China. Limited research works were conducted on customers’ adoption intentions to obtain a real image of the evolution of WPD in China. This study aims to investigate the effects of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Perceived Trust (PT), and Lifestyle Compatibility (LC) on the intention to adopt WPD among Chinese consumers by expanding unified theory of acceptance and use of technology with two impelling determinants (i.e. PT and LC). Using an online survey, empirical data were collected from 298 respondents in China. In a two-stage data analysis, partial least squares structural equation modelling (PLS-SEM) were employed to analyse the causal effects and associations between independent and dependent variables, whereas artificial neural networks (ANN) were used to evaluate the research model prediction capability. The (PLS-SEM) findings indicated that PE, SI, FC, HM, LC, and PT had substantial positive impacts on adoption intention, whilst EE had no impact on adoption intention among Chinese consumers. The ANN analysis proved the high prediction accuracy of data fitness, with ANN findings highlighting the importance of PT, FC, and PE on the intention to adopt WPD. It was suggested that the study findings assist WPD service providers and the smart wearable device industry practitioners in developing innovative products and implementing efficient marketing strategies to attract the existing and potential WPD users in China.

What insisted baby boomers adopt unified payment interface as a payment mechanism?: an exploration of drivers of behavioral intention

Purpose

The unified payment interface (UPI) is in its early stages of adoption for baby boomers. This study explores the factors affecting the behavioral intention of baby boomers to adopt UPI. UTAUT was adopted as theoretical lens of the study and extended with ubiquity, privacy risk and perceived security. The impact of an external factor – effect of COVID-19 was also examined in this study.

Design/methodology/approach

A consumer intercept survey was used to collect data from baby boomers via a self-administered structured questionnaire. Structural equation modeling was used to establish the relationships among latent variables. Further, using bootstrap re-sampling technique, the role of perceived security as a mediator between risk, ubiquity and behavioral intention was examined.

Findings

The study confirmed that COVID-19 was the most influential external factor for baby boomers to adopt UPI, followed by performance expectancy, social influence, ubiquity, effort expectancy and perceived security. Apropos of UPI adoption by baby boomers, privacy risk negatively influenced perceived security, whereas perceived security fully mediated the relationship between risk, ubiquity and behavioral intention.

Research limitations/implications

The study focused only on baby boomers and their intention to adopt UPI. Hence the results cannot be generalized to all age groups and are specific to the cohort.

Originality/value

The present study aims to establish research findings on predicting antecedents of adopting a newly introduced payment mechanism and an exemplary Indian digital innovation, UPI, by baby boomers. This study is first to empirically explore intention of baby boomers toward adoption of UPI.

Digital Marketing Enhancement of Cryptocurrency Websites through Customer Innovative Data Process

Today, more than ever, the popularity of decentralized payment systems has risen, creating an outbreak of new cryptocurrencies hitting the market. Unique websites have been staged for each cryptocurrency, where information and means for mining cryptocurrencies are available daily. People visit those cryptocurrency websites either from desktop or mobile devices. Thus, the impulsion for appropriate promotion of cryptocurrency websites and customer factors affecting it rises. The above process increases cryptocurrency organizations’ website visibility, raising the need for customer relationships and satisfaction optimization concerning organizations’ supply chain strategy. Research data were collected from 10 well-known cryptocurrency websites, regarding mobile and desktop devices, in 180 days, regarding on-site web analytics. Therefore, a model consisting of three stages was applied. Starting phase of the model pertains to statistical and regression analysis of cryptocurrency web analytics, followed by Fuzzy Cognitive Mapping and Agent-Based Model deployment. Throughout this study, methods for promoting cryptocurrency websites can be deduced from assessing specific website metrics and device preferences. Research results indicate that web analytics give a clearer image of customer behavior in cryptocurrency websites and, therefore, provide opportunities for further website optimization through increased web traffic and digital reputation.

Analyzing the Effect of People Utilizing Mobile Technology to Make Banking Services More Accessible

Many firms in the modern world utilize m-banking systems to communicate with their consumers. The word m-banking refers to a widespread method of providing financial services and localization to customers. Since m-banking is important to both banks and users, it has been included in numerous literary works. As a result, embracing financial services via the m-banking platform is critical. This article's technique is mostly descriptive research that investigates common views, current situations, modern tactics, tangible emerging consequences, etc. The main objective here is to analyze the benefits of this study by investigating the past. Since this article analyzes what exists and is descriptive, the data is being retrieved by conducting a cross-sectional survey method about different features that are relevant by sampling the population. The main aim of this study is to explore the adoption of mobile banking technology by consumers. Based on the values of different variables such as affective commitment (AC), transaction convenience (TC), perceived ease of use (PEU), perceived reliability (PR), pre and post benefits (PPB), service, system, and information quality (SSIQ), bank trust (BT), and profitability (P), the inter-relationship between them and the adoption of m-banking technique by the users in banking technology. The model is investigated by examining the hypothesis and identifying the relationship that exists between these different parameters. A simple linear regression method is implemented using the Statistical Package for the Social Sciences (SPSS) software.

Assessing Older Adults' Intentions to Use a Smartphone: Using the Meta-Unified Theory of the Acceptance and Use of Technology

Barriers to smartphone use often exist among older adults, and increasing smartphone use is beneficial to increasing older adults' quality of life. Studies of older adults' smartphone use intentions have mostly adopted the technology acceptance model or unified theory of acceptance and use of technology (UTAUT). However, these models have their limitations. A meta-UTAUT has been developed, but it has not been extensively verified with older adults. This study used the meta-UTAUT model to explore the influences on older adults' smartphone use intentions and behaviors. A total of 311 adults aged 60 to 75 years who had minimal experience with smartphones were recruited. They participated in a 16 h smartphone training and then completed a questionnaire. The results demonstrated that the meta-UTAUT model can predict older adults' smartphone use intentions and behaviors. Performance expectancy (PE) and social influence significantly influenced behavioral intention (BI) and attitude toward using smartphones (AT). PE was the strongest factor influencing BI. AT also affected BI. Although facilitating conditions did not significantly affect BI, they had a high influence on AT. To increase smartphone use among older adults, training can be implemented to teach smartphone skills and emphasize the benefits of using smartphones.

The effect of trust and its antecedents towards determining users' behavioral intention with voice-based consumer electronic devices

Advances in artificial intelligence (AI) have ushered in a new era of consumer electronic (CE) devices: the voice-based CE devices (VCED's). A striking feature that separates these from other CE devices are their anthropomorphic capabilities. While current CE research has given a strong focus on improving various technical and security aspects of the VCED's, not much efforts have been given to explore their diffusion and acceptance in the society. However, if the CE community is to progress then there is an urgent need to view these systems from a sociotechnical perspective and take the user perceptions into account for further product development. In this work we propose a novel research framework by incorporating Human Computer Interaction (HCI) theories and Para Social Relationship Theory for exploring the effect of trust on the behavioral intention of users towards VCED's, keeping in mind their human-like attributes. Data is analyzed using a Structural Equation Modelling approach from 675 users of VCED devices from two Asian countries. Results show that the functional aspects of performance and effort expectancy, and social aspects of presence and cognition affect the trust factor. Privacy concerns do not affect trust. Overall, the results suggest that users treat VCED's as social objects employing social rules while interaction that indicates a dual nature of anthropomorphic systems. Suitable suggestions are provided for CE researchers for future research.