Developing a general extended UTAUT model for M-payment adoption

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.

The influence mechanism analysis on the farmers' intention to adopt Internet of Things based on UTAUT-TOE model

Internet of Things (IoT) technologies are widely recognized as one of the most important infrastructures for economic development and technological innovation. By analyzing the influencing factors of vegetable farmers' intention to adopt agricultural IoT, it helps to formulate effective IoT promotion policies and accelerate the realization of agricultural modernization. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology-Organization-Environment (TOE) theory, this study constructed for the first time a mechanism model of the influence of vegetable farmers' intention to adopt IoT, expanding the scope of current research on agricultural IoT and revealing the intrinsic influence mechanism of farmers' adoption of IoT technologies. In this study, 357 quantitative data were obtained by a questionnaire survey, and structural equation modeling was used to test the direct and indirect effects of each factor on vegetable farmers' intention to adopt IoT. The results show that almost all variables in TOE have significant direct impacts on the intention, while no variables in UTAUT have significant direct impacts. Among variables in TOE, government support and complexity are the two most important elements influencing the intention. Although the interactions among variables in TOE and UTAUT are also found, the indirect effects of variables are non-significant. Therefore, it is proposed to reduce the complexity of operation and use of IoT technologies; improve rural information infrastructure and compatibility of IoT platforms and devices; and governments should increase subsidies, and incentives to promote the use of IoT in agriculture and agricultural practices.

AI Chatbots in Chinese higher education: adoption, perception, and influence among graduate students-an integrated analysis utilizing UTAUT and ECM models

This study is centered on investigating the acceptance and utilization of AI Chatbot technology among graduate students in China and its implications for higher education. Employing a fusion of the UTAUT (Unified Theory of Acceptance and Use of Technology) model and the ECM (Expectation-Confirmation Model), the research seeks to pinpoint the pivotal factors influencing students' attitudes, satisfaction, and behavioral intentions regarding AI Chatbots. The study constructs a model comprising seven substantial predictors aimed at precisely foreseeing users' intentions and behavior with AI Chatbots. Collected from 373 students enrolled in various universities across China, the self-reported data is subject to analysis using the partial-least squares method of structural equation modeling to confirm the model's reliability and validity. The findings validate seven out of the eleven proposed hypotheses, underscoring the influential role of ECM constructs, particularly "Confirmation" and "Satisfaction," outweighing the impact of UTAUT constructs on users' behavior. Specifically, users' perceived confirmation significantly influences their satisfaction and subsequent intention to continue using AI Chatbots. Additionally, "Personal innovativeness" emerges as a critical determinant shaping users' behavioral intention. This research emphasizes the need for further exploration of AI tool adoption in educational settings and encourages continued investigation of their potential in teaching and learning environments.

Willingness to accept metaverse safety training for construction workers based on extended UTAUT

Safety training (ST) is essential in avoiding unsafe behavior of construction workers. With the rise of metaverse technology, metaverse safety training (MST) has gradually become a new model to guide construction workers in safety production. An in-depth study of construction workers' willingness to accept the metaverse safety training (WAMST) helps improve its effectiveness, but studies need to pay more attention to it. This study constructs a conceptual model of WAMST for construction workers, and the influencing factors of WAMST are explained based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT). It established a Structural equation modeling to verify the relationship between influencing factors. An example verifies the feasibility of the model. The results show that the framework significantly contributes to the willingness of construction workers to participate and improves safety awareness. Specifically, performance expectancy, effort expectancy, social influence, and convenient conditions significantly affect the construction workers' willingness to accept. Convenient conditions have a direct effect on actual behavior. Willingness to accept plays a mediating role between performance expectancy and actual behavior. Perceived trust moderates the effect between willingness to accept and actual behavior, and the force of positive interpretation increases proportionally. It confirms how to improve the safety capacity of construction workers and provides references for governments, enterprises, and projects to formulate ST strategies.

Unveiling digital transformation: Investigating technology adoption in Vietnam's food delivery industry for enhanced customer experience

Digital platforms are increasingly playing a crucial role in the digital transformation process, enabling small and medium-sized enterprises to gain a competitive advantage and achieve their business objectives. This research study aims to extend the Technology Acceptance Model by incorporating the Stimulus-Organism-Reaction theory to gain a comprehensive understanding of the factors influencing satisfaction, continued intention to use, and positive electronic word-of-mouth (eWOM) in the context of Food Delivery Apps (FDAs). A quantitative approach was employed, and data were collected through a survey administered to 346 FDA users. The results reveal that both Information quality and Task-technology fit have a positive impact on satisfaction and continued intention to use. Additionally, satisfaction was found to have the greatest influence on continued intention to use and positive eWOM, with information quality exerting the most significant impact on satisfaction. Furthermore, the study findings demonstrated that promotion has a significant impact on generating positive eWOM. This study makes a substantial contribution to the existing literature by providing valuable insights into the factors influencing FDA usage and their impact on satisfaction, continued intention to use, and positive eWOM. It serves as a foundation for further research in this emerging field and offers practical implications for stakeholders involved in the development, management, and utilization of FDAs.

Factors that impacted mobile-payment adoption in China during the COVID-19 pandemic

The Unified Theory of Acceptance and Use of Technology (UTAUT) is a potential paradigm for explaining technology adoption and can be applied to a wide range of scenarios. During the COVID-19 (C-19) outbreak in China, mobile-payment platforms (Mpayment) were used extensively in everyday life because they allowed people to avoid direct and indirect connections during transactions, adhere to social-distancing guidelines, and support social-economic stabilization. By exploring the technological and psychological variables that influenced user Mpayment-adoption intentions during the C-19 pandemic, this study broadens the literature on technology adoption in emergency circumstances and expands the UTAUT. A total of 593 complete samples were collected online, with SPSS used for data analysis. The empirical findings reveal that performance expectancy, trust, perceived security, and social influence all had a significant influence on Mpayment acceptance during the C-19 outbreak, with social distancing having the greatest impact, followed by fear of C-19. Interestingly, perceived-effort expectancy had a negative influence on payment acceptance. These findings suggest that future studies should apply the expanded model to different countries and areas to investigate the impact of the C-19 pandemic on Mpayment acceptance.

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.

A novel multi-attribute decision-making for ranking mobile payment services using online consumer reviews

The onset of the COVID-19 pandemic has changed consumer usage behavior towards mobile payment (m-payment) services. Consumer usage behavior towards m-payment services continues to increase due to access to usage experiences shared through online consumer reviews (OCRs). The proliferation of massive OCRs, coupled with quick and effective decisions concerning the evaluation and selection of m-payment services, is a practical issue for research. This paper develops a novel decision evaluation model that integrates OCRs and multi-attribute decision-making (MADM) with probabilistic linguistic information to identify m-payment usage attributes and utilize these attributes to evaluate and rank m-payment services. First and foremost, the attributes of m-payment usage discussed by consumers in OCRs are extracted using the Latent Dirichlet Allocation (LDA) topic modeling approach. These key attributes are used as the evaluation scales in the MADM. Based on an unsupervised sentiment algorithm, the sentiment scores of the text reviews regarding the attributes are calculated. We convert the sentiment scores into probabilistic linguistic elements based on the probabilistic linguistic term set (PLTS) theory and statistical analysis. Furthermore, we construct a novel technique known as probabilistic linguistic indifference threshold-based attribute ratio analysis (PL-ITARA) to discover the weight importance of the usage attributes. Subsequently, the positive and negative ideal-based PL-ELECTRE I methodology is proposed to evaluate and rank m-payment services. Finally, a case study on selecting appropriate m-payment services in Ghana is examined to authenticate the validity and applicability of our proposed decision evaluation methodology.

Predicting Fintech Innovation Adoption: the Mediator Role of Social Norms and Attitudes

Digital innovation is challenging the traditional way of offering financial services to companies; the so-called Fintech phenomenon refers to startups that use the latest technologies to offer innovative financial services. Within the framework of the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA), the primary purpose of this paper is to develop a causal-predictive analysis of the relationship between Subjective Norms, Attitudes, and Perceived Behavioral Control with the Intention to Use and Behavioral Use of the Fintech services by companies. Partial Least Squares Structural Equation Modeling methodology was used with data collected from a survey of 300 companies. Our findings support the TRA and TPB models and confirm their robustness in predicting companies' intention and use of Fintech services. Financial technology innovators must understand the processes involved in users' adoption to design sound strategies that increase the viability of their services. Studying the antecedents of behavioral intention to adopt Fintech services can greatly help understand the pace of adoption, allowing these players to attract and retain customers better. This study contributes to the literature by formulating and validating TPB to predict Fintech adoption, and its findings provide useful information for banks and Fintech companies and lead to an improvement in organizational performance management in formulating marketing strategies.

Research on elderly users' intentions to accept wearable devices based on the improved UTAUT model

Introduction

As the proportion of the world's elderly population continues to increase, wearable devices can provide ideas for solving a series of problems caused by population aging. Therefore, it is of great significance for the development of intelligent elderly care and the improvement of the quality of elderly care services to explore the factors that influence the intention of elderly users to accept wearable devices.

Methods

An improved unified theory of acceptance and use of technology (UTAUT) model is constructed from the perspective of elderly individuals, and new parameters are added, including four factors related to wearable devices, including performance expectancy, perceived cost, hedonic value and aesthetic appeal, and three factors related to elderly individuals, including personal physiological conditions, health anxiety and personal innovativeness in information technology. The data analysis was accomplished with the partial least square regression structural equation modeling.

Results

The findings of this study revealed that performance expectancy, perceived cost, hedonic value and aesthetic appeal all have significant impact on elderly users' intention to use wearable devices. Furthermore, personal innovativeness in information technology, personal physiological condition, and intention to use all have significant impact on elderly users' actual usage behavior of wearable devices. However, there is no obvious relationship between health anxiety and actual usage behavior.

Discussion

Elderly adults' attention to wearable devices plays an important role in the development of the wearable device-related industry chain, which provides management suggestions for stakeholders.

Understanding e-satisfaction, continuance intention, and e-loyalty toward mobile payment application during COVID-19: an investigation using the electronic technology continuance model

This research examined the determinants of e-satisfaction, continuance intention, and e-loyalty regarding the use of mobile payment applications (MPAs). It developed and validated the electronic technology continuance model (e-TCM) integrating a psychological factor (perceived threats), e-satisfaction, circumstantial factor (perceived anxiety), and the dimensions of quality. Using a questionnaire, data was collected from 455 respondents and analyzed using structural equation modeling. The influences of information quality, service quality, system quality, perceived usefulness, and confirmation on both e-satisfaction and continuance intention are found positive. However, perceived threats and perceived anxiety do not influence e-satisfaction but influence continuance intention. Moreover, e-satisfaction positively impacts continuance intention and e-loyalty; and continuance intention positively impacts e-loyalty. This research evidences the roles of perceived threat, e-satisfaction, perceived anxiety, and the dimensions of quality on customers’ e-satisfaction, continuance intention and e-loyalty, using the integrated framework comprising the health belief model, expectation–confirmation model, and information systems success model. The findings of this research can guide MPA services providers, online businesses, industry analysts, suburban consumers, and respective government authorities when MPA usage is concerned during any unprecedented crisis such as the COVID-19 pandemic.

The Effect of the COVID-19 Pandemic on the Mobile Messaging Application Among Millennials in Public Universities in Malaysia

Mobile messaging apps are currently a popular method in Malaysia for communicating while on the go, owing to its convenience, reliability, and contact-free feature of mobile application. Fueled by mobile internet and smartphone growth, mobile messaging apps have become a strong force in the mobile app sector, offering users an alternative to SMS-based texting paired with social media elements and enhanced features, such as group chats and photo sharing. The study was anchored using the unified theory of acceptance and use of technology 2 theory. A survey with 150 respondents and PLS analysis is used to determine the antecedents of mobile application continuance usage during the COVID-19 pandemic. The results revealed that there is an influence in the usage of mobile messaging apps among the younger generation in Malaysian public university students during the COVID-19 pandemic. The main implication shows that mobile application among young generations in public universities has become popular. The convenience usage of the internet has turned the world into a global village.

Resistance of Traditional SMEs in Using Digital Payments: Development of Innovation Resistance Theory

The impact of the pandemic has also affected the sustainability of traditional traders. One of the merchants’ efforts in overcoming the effect of COVID-19 is to make transactions with digital payments, both in-store purchases and through online media. This study is aimed at determining user resistance with the innovation resistance theory (IRT) approach based on two main approaches, namely, functional and psychological barriers. The unit of analysis in this study is a traditional clothing market trader who uses digital payments to process transactions. This study uses a qualitative method with a case study approach in Indonesia’s traditional clothing market through in-depth interviews of eight respondents. The results of this study prove that the clothing market sword uses digital payments when conducting transactions directly to consumers and for the needs of traders in supporting their business activities such as bill payments and purchases to suppliers. Most buyers complain about the risk barrier on the security and privacy factor, especially when they experience delays in information when processing transactions, causing more efforts to make complaints. The research contributes to the development of IRT theory, especially in the context of technology such as digital payments. The results of this study can also be helpful for service providers and the government in making strategies and policies that can protect users, especially buyers and sellers, in adopting digital payments.

Adoption of social media-based knowledge-sharing behaviour and authentic leadership development: evidence from the educational sector of Pakistan during COVID-19

Purpose

This research paper aims to explore the influence of social media–based knowledge-sharing intentions (SMKI) on prospective authentic leadership development (ALD) to deal with the future crisis. In the existing literature, to the best of the authors’ knowledge, there is no significant empirical evidence to test the relationship between SMKI and ALD. Thus, this study contributes to the growing literature regarding the role of SMKIs, ALD, social media–based knowledge-sharing behavior (SMKB) and facilitating conditions (FCs). However, in this study, the authors developed a conceptual framework based on technology adoption and leadership theory. It was used to identify preservice educational leaders’ SMKIs and their effect on ALD to deal with an educational crisis during the COVID-19 pandemic. Furthermore, SMKIs are strengthening ALD, directly and indirectly, using SMKB and FCs.

Design/methodology/approach

In this study, the higher education students are considered preservice leaders who were enrolled in educational leadership and management programs. However, this study’s target population and sample are students enrolled in educational leadership and management programs. Therefore, higher education students are considered preservice educational leaders. Therefore, a multilevel questionnaire survey approach was adopted to collect data from preservice educational leaders (n = 451 at Time 1 and n = 398 at Time 2) enrolled in education departments in the selected universities in Pakistan. A total of 398 survey questionnaires were finalized with a return ratio of 89%. The partial least square structural equation modeling with SmartPLS 3.2.8 was used for the data analysis.

Findings

This research found that SMKIs are positively and significantly connected with ALD. This study also confirms that SMKB significantly and positively mediates the relationship between SMKIs and ALD. Therefore, this study concludes that preservice educational leaders were ready to adopt SMKB.

Practical implications

Social media–based knowledge sharing can be helpful to develop authentic leadership among preservice educational leaders during a crisis. Preservice educational leaders as authentic leaders can prove to be an asset in dealing with the COVID-19 pandemic crisis.

Originality/value

This research integrated the technology adoption model and leadership theory to provide empirical evidence of SMKIs’ direct and indirect influence on ALD through social media–based knowledge-sharing actual use behavior by preservice educational leaders during the COVID-19 pandemic. Moreover, the moderated mediating effect of the FCs was also studied in the relationship between SMKIs and actual user behavior as well as ALD.

Understanding the key drivers in using mobile payment among Generation Z

Purpose

This quantitative study aims to examine the determinants that impact the behavioral intention to use mobile payment (m-payment) among Generation Z (Gen Z) customers in Indonesia.

Design/methodology/approach

The theoretical model comprises seven latent variables: effort expectancy, performance expectancy, social influence, facilitating conditions, promotional activities, perceived security and behavioral intention. In addition, the two moderating factors of education and gender are used to investigate the significant effect of the determinants on intention to adopt m-payment. This study obtained the final data size of 430 respondents. The data analysis is conducted using structural equation modeling.

Findings

The results substantiate the significance of promotional activities, perceived security, performance expectancy, effort expectancy and social influence, on the behavioral intention to accept m-payment systems. Gender is revealed to significantly moderate two constructs: social influence and promotional activities, on the m-payment usage intention. Meanwhile, education moderates the effect of perceived security on behavioral intention.

Originality/value

This research is expected to fill the gap because only a few studies discuss the determinants affecting m-payment usage in Indonesia, especially among Gen Z-ers. Furthermore, the new findings associated with the role of two moderating factors become important practical implications because most of the prior studies often ignore the moderating factors.

Student use of digital libraries during COVID-19: structural equation modelling in Indonesian and Malaysian contexts

Purpose

This paper aims to examine the determinants that drive digital library use by university students in Indonesia and Malaysia during COVID-19. A proposed model based on the unified theory of acceptance and use of technology model-2 was implemented.

Design/methodology/approach

A pilot study was conducted prior to the main data collection to examine the reliability of the instrument. For the structural model assessment, 1,168 responses were analysed through partial least square structural equation modelling (PLS-SEM) and importance and performance analysis (IPMA). A t-test was also conducted to support the main findings.

Findings

Most hypotheses are confirmed by the significant results reported through the PLS-SEM. The strongest determinant of behavioural intention is habits. Digital library use is most significantly predicted by behavioural intention. Through IPMA, habits are reported to be the most important determinant for behavioural intention. Performance expectancy obtains the highest performance in the IPMA procedure. Behavioural intention and digital library use are significantly different based on the respondents’ location.

Originality/value

This study addresses the research gap (comparative studies between two countries) by evaluating digital library use among students in two universities in Indonesia and Malaysia during COVID-19. Findings could facilitate policymakers with insights into digital library use determinants and initiate effective and efficient policies to improve digital library use, especially during school closures due to certain situations or conditions.

Study of the factors influencing the use of MyData platform based on personal health record data sharing system

Background

The application of telemedicine and electronic health (eHealth) technology has grown in importance during the COVID-19 pandemic, and a new approach in personal data management and processing MyData, has emerged. Data portability and informational self-determination are fundamental concepts of MyData. This study analysed the factors that influence acceptance of the MyData platform, which, reflects the right to self-determine personal data.

Methods

The study involved participants having experience using the MyData platform, and the key factors of the unified theory of acceptance and use of technology were used in the research model (performance expectancy, effort expectancy, social influence, facilitation condition and behavioural intention to use). The questionnaire comprided 27 items, and system usage log data were used to confirm that behavioural intention to use affected actual use behaviour through structural equation modeling.

Results

In total, 1153 participants completed the survey. The goodness of fit in the structural equation model indices indicates that the data fit the research model well. Performance expectancy, social influence, and facilitating conditions had direct effects on behavioural intention to use. We used system usage log data to confirm that behavioural intention to use positively affected actual use behaviour. The impact of the main factors in the unified theory of acceptance and use of technology was not moderated by age or gender, except for performance expectancy.

Conclusions

This study is the first to examine the factors influencing the use of the MyData platform based on the personal health record data sharing system in Korea. In addition, the study confirmed the use behaviour of the MyData platform utilising the system’s actual usage log for each function and analysing the effect of the intention of use on actual use. Our study serves as a significant foundation for the acceptance of data portability and sharing concepts. It also lays the foundation for expanding the data economy and ecosystem in the pandemic era.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01929-z.

Determinants of mobile apps adoption by retail investors for online trading in emerging financial markets

Purpose

The purpose of this study is to investigate the influence of mobile applications on investment decisions by retail investors in stocks and mutual funds. This study focuses on how mobile technologies are applied on mobile apps by retail investors for e-trading in emerging financial markets.

Design/methodology/approach

The study explored predictive relevance for the adoption behavior of retail investors under the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Further, goal contagion theory was applied to investigate the adoption behavior of investors towards e-trading. An adapted questionnaire was used to collect the date from April to June 2021 and data analysis was performed on 507 usable responses. The methodology adopted in this study is variance based partial least square structural equational modelling (PLS-SEM). Additionally, the study explains important and performing constructs based on the response of retail investors towards mobile app usage for investment decisions.

Findings

The study shows that effort expectancy, performance expectancy followed by perceived return were the primary determinants of behavioral intentions to use mobile applications by retail investors for e-trading. Further, habit of investors determined the adoption behavior of investors towards mobile apps. Additionally, the study revealed that perceived risk is not an important aspect for retail investors in comparison to perceived return.

Research limitations/implications

The study in future can address to the aspect of personality traits of retail investors for technology adoption for investment decisions. Further investigation is required on addressing unobserved heterogeneity of retail investors towards technology adoption process in emerging financial markets.

Practical implications

The study provides theoretical and practical implications for retail investors, financial advisors and technology companies to understand the behavioral pattern and mobile apps adoption behavior of retail investors in emerging financial market. The findings in the study will help broking firms to sensitize their clients for effective use of their respective mobile apps for e-trading purposes. The study will strengthen the knowledge of financial advisors to understand investment behavior of retail investors in emerging financial markets.

Originality/value

This study unfolds a novel framework of research to understand the technology adoption pattern of retail investors for e-trading by mobile applications in emerging financial markets. The present study provides significant understanding in the domain of technology adoption by retail investors under behavioral finance environment.

Evaluating the sustainable use of mobile payment contactless technologies within and beyond the COVID-19 pandemic using a hybrid SEM-ANN approach

Purpose

While there is an abundant amount of literature studies on mobile payment adoption, there is a scarce of knowledge concerning the sustainable use of mobile payment contactless technologies. As those technologies are mainly concerned with security and users' trust, the question of how security factors and trust can influence the sustainable use of those technologies within and beyond the COVID-19 pandemic is still unanswered. This research thus develops a theoretical model based on integrating the protection motivation theory (PMT) and the expectation-confirmation model (ECM), extended with perceived trust (PT) to explore the sustainable use of mobile payment contactless technologies.

Design/methodology/approach

The developed model is evaluated based on data collected through a web-based survey from 523 users who used contactless payment technologies. Unlike the existing literature, the collected data were analyzed using a hybrid structural equation modeling-artificial neural network (SEM-ANN) technique.

Findings

The data analysis results reinforced all the proposed relationships in the developed model. The sensitivity analysis results showed that PT has the largest impact on the sustainable use of mobile payment contactless technologies with 97.2% normalized importance, followed by self-efficacy (SE) (77%), satisfaction (72.1%), perceived vulnerability (PV) (48.9%), perceived usefulness (PU) (48.2%), perceived severity (PS) (40.7%), response efficacy (RE) (28.7%) and response costs (RCs) (24.1%).

Originality/value

The originality of this research lies behind the development of an integrated model based on PMT and ECM to understand the sustainable use of mobile payment contactless technologies. The study provides several managerial implications for decision-makers, policy-makers and service providers to ensure the sustainability of those contactless technologies within and beyond the COVID-19 pandemic.

Investigating antecedents of mobile payment systems’ decision-making: a mediated model

Purpose

The increase in mobile telephone penetration has offered new opportunities for technology to improve payment operations all over the world. Little research has examined the issues related to the decision-making (DM) of mobile payment systems usage in the Jordanian context. The purpose of this study is to examine the factors that may have an influence on the adoption of mobile payment systems. This study has empirically tested the expanded unified theory of acceptance and use of technology (UTAUT2) together with awareness (AW), trust (TR), security (SE) and privacy (PR) as independent variables to explain the mobile payment system adoption in Jordan.

Design/methodology/approach

In total, 270 employees participated in a field survey questionnaire from the public sector in Amman city, the capital city of Jordan. Data were analyzed through a quantitative approach of partial least squares–structural equation modeling.

Findings

The results mainly showed that the determinants of DM to use mobile payment system are price value, social influence, performance expectancy, AW and TR. All of these determinants explained 60.2% of the variation of DM. In total, 72.2% has been explained as the TR to use m-payment system by SE and PR. Furthermore, the results revealed that TR mediates the association between SE as well as PR and the DM to use mobile payment system.

Originality/value

Interestingly, these new variables were found to be important and contribute to the UTAUT2 model. Consequently, the decision-makers in the Central Bank of Jordan should consider all these factors when re-upgrading a Jordan Mobile Payment system in the near future.

Consumers’ Intention to Adopt m-payment/m-banking: The Role of Their Financial Skills and Digital Literacy

The adoption of mobile payment (m-payment) and mobile banking (m-banking) is low in several countries, despite its associated benefits. The present study examines the impact of Pakistani consumers’ financial skills and digital literacy on their intention to adopt m-payment/m-banking using the Technology Acceptance Model (TAM). The data were collected from 454 individual smartphone users residing in Punjab province via an online and offline questionnaire survey. Structural equation modeling was used to analyze the consumers’ data. The results endorse that (1) their financial skills have no association with intention to adopt but through perceived usefulness; (2) their digital literacy bridges a strong association with intention and through perceived ease of use. Furthermore, this study discusses the theoretical and practical implications of the findings, as well as limitations and future directions.

Salleh MF, Salameh AA, Makhbul ZKM. Predicting the Mass Adoption of eDoctor Apps During COVID-19 in China Using Hybrid SEM-Neural Network Analysis

Technology plays an increasingly important role in our daily lives. The use of technology-based healthcare apps facilitates and empowers users to use such apps and saves the burden on the public healthcare system during COVID-19. Through technology-based healthcare apps, patients can be virtually connected to doctors for medical services. This study explored users' intention and adoption of eDoctor apps in relation to their health behaviors and healthcare technology attributes among Chinese adults. Cross-sectional data were collected through social media, resulting in a total of 961 valid responses for analysis. The hybrid analysis technique of partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) analysis was applied. The obtained results revealed the significant influence of eDoctor apps in terms of usefulness, compatibility, accuracy, and privacy on users' intention to use eDoctor apps. Intention and product value were also found to suggestively promote the adoption of eDoctor apps. This study offered practical recommendations for the suppliers and developers of eHealth apps to make every attempt of informing and building awareness to nurture users' intention and usage of healthcare technology. Users' weak health consciousness and motivation are notable barriers that restrict their intention and adoption of the apps. Mass adoption of eDoctor apps can also be achieved through the integration of the right technology features that build the product value and adoption of eDoctor apps. The limitations of the current study and recommendations for future research are presented at the end of this paper.

Provoking Actual Mobile Payment Use in the Middle East

Monetary transactions have advanced into a portable, simple, and comfortable process. Regardless of the advantages of a versatile method of disbursement, the global take-up ratio is inadequate. Consequently, greater insight into the factors that influence acceptance by stakeholders is fundamental for industrialists and scholars. This study analyses the goals and real purpose behind portable disbursement by unifying the definition of its concept, which consolidates the “Mobile Technology Acceptance Model” and the “Theory of Planned Behaviour” as well as an updated profound variable that is more synergistic. The new framework incorporated 12 factors influenced by the user’s insight and was analysed by collecting data based on the PLS-SEM condition mix-mode. Identifying the impact of versatile methods of disbursement will shape essential business choices and the community and will change current lifestyles into contactless ones. This article demonstrates the connection between innovative factors and human preferences concerning the use of portable disbursement. Interestingly, we embrace this uniqueness for an incorporated framework that consolidates MTAM as well as the TPB.

Decoding the Role of Gender in the Relationship Between the Online Payment System and SME Performance: A Case Study Investigating an Emerging Economy—Bangladesh

This research examines the moderating role of gender on the adoption of online payment systems (OPS). It also explores the impact of using OPS on the performance of SMEs in an emerging economy, using the Technology Acceptance Model (TAM) and Resource-Based View (RBV). The results indicate that male SME owners (entrepreneurs) are more likely to focus on perceived usefulness, whereas female SME entrepreneurs are more likely to focus on perceived ease of use while adopting OPS, according to data obtained from 302 SMEs in Bangladesh through face-to-face surveys. The results also report that the use of OPS has a considerable positive effect on SMEs' performance. The study's findings will add to the scarce research on the impact of using OPS on business performance in the context of SMEs in emerging economies, in addition to enhancing the OPS adoption literature from a gendered lens.

Factors Affecting Intention of Consumers in Using Face Recognition Payment in Offline Markets: An Acceptance Model for Future Payment Service

Face recognition payment (FRP), an innovative financial technology service, is a recently developed mode of payment service that has garnered attention in the offline market, particularly in China. However, studies examining the adoption of FRP by consumers are scarce. Therefore, this study proposed a causal model built on the Unified Theory of Acceptance and Use of Technology, and key predictors related to the intention of using FRP were identified. The structural equation model-based results obtained from 305 Chinese participants demonstrated that the intention was most affected by relative advantage. In addition, performance expectancy, effort expectancy, social influence, and perceived risk also had a significant impact. However, trust was found to not significantly affect consumers’ intentions, despite it negatively influencing perceived risk. Thus, the results of this study are expected to provide a set of guidelines for companies regarding the implementation of FRP.

Do biometric payment systems work during the COVID-19 pandemic? Insights from the Spanish users' viewpoint

Technological developments are changing how users pay for goods and services. In the context of the COVID-19 (coronavirus disease 2019) pandemic, new payment systems have been established to reduce contact between buyer and seller. In addition to the pandemic, the future is payment processing is also uncertain due to the new EU security regulations of the Payment Services Directive (PSD2). Biometric payments one option that would guarantee the security of transactions and reduce the risk of contagion. This research analyses the intention to recommend the use of the mobile phone as a tool for collecting payments in a shop using iris reading as a biometric measure of the buyer. The moderating effect of the fear of contagion in the proposed relationships was also analysed. An online survey was carried out, which yielded a sample of 368 respondents. The results indicate that the main antecedents of intention to use, which precedes intention to recommend, are perceived trust, habit, personal innovativeness and comfort of use. Additionally, the moderating effect of COVID-19 was checked among users with a higher perception of risk. The results obtained have interesting implications for purchase management among manufacturers and retailers.

My video game console is so cool! A coolness theory-based model for intention to use video game consoles

With the outbreak of COVID-19, the video game console market is thriving again. In this study, we attempted to explore users' intention to use video game consoles by developing a causal model mainly based on coolness theory and the technology acceptance model. To better illustrate user experience for video game consoles, we added several concepts to the causal model, including hedonic motivation, system and service quality, perceived cost, and game variety. Through examining survey-based data from 360 Koreans, we discovered that the model had a high explanatory power for users' intention to use video game consoles. The key findings were as follows: First, among the components of coolness theory, individuals' attitude toward consoles was significantly related to subcultural appeal and originality, but not to attractiveness. Second, originality positively influenced subcultural appeal significantly. Overall, this study implied that the novel coolness theory is effective for exploring user experience regarding of specific devices and services.

University Accounting Students and Faculty Members Using the Blackboard Platform during COVID-19; Proposed Modification of the UTAUT Model and an Empirical Study

The current COVID-19 pandemic has changed education systems in most countries: some have shut down whilst others, especially in the higher education sector, have introduced electronic/distance learning systems, such as Blackboard platforms. The current study aimed to identify and test the factors that influence accounting students’ and faculty members’ Blackboard platform use during the pandemic. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was extended and modified by adding four new variables: perceived risk, mobility, self-efficacy and self-managed learning. This was done to generate an understanding of people’s usage traits. This is the main contribution of the article: the extension of UTAUT in this context and the consideration of online learning in a pandemic environment situation. Pandemics oppose sustainability from numerous contexts. Measures which counteract sustainability risks associated with pandemics, such as use of technology, are critical risk management instruments and are, thus, important for consideration. Through an online survey, the data was gathered from accounting students and faculty staff in an accounting department at Jazan University, Saudi Arabia. Structural equation modelling (SEM) was used to analyse the data and examine the hypotheses. This study confirmed the hypotheses concerning the influence of the Blackboard platform on mobility, self-efficacy and self-managed learning. This article contributes to the existing UTAUT model by extending our understanding of the influence of factors to use Blackboard platforms. Moreover, the results have practical implications for policymakers, practitioners, online learning product providers and teaching staff looking to develop efficient strategies concerning learning-related information technologies.

Human Resource Professionals' Intention to Use and Actual Use of Human Resource Information Systems

Human resource information systems (HRISs) are widely used and have a strategic impact on organizations. The fundamental objective of this paper is to reveal the predominant antecedents affecting their adoption and implementation by replicating the unified theory of acceptance and use of technology (UTAUT) model from a South Asian emergent country perspective. The study collected data from human resource professionals employed in manufacturing and service companies located in Bangladesh, which were analyzed by employing partial least squares-based structural equation modeling software. It was revealed that performance expectancy, social pressure, and facilitation conditions significantly influence the intention to use and the actual use of HRIS, but that user’s effort expectancy had no significant impact. The study contributes by enriching the previous findings and validating the results based on relevant literature. Furthermore, managerial implications, the limitations of the study and suggested future study directions are presented.

Factors Driving the Purchase of Mobile-Phone Top-Ups Services on Social Commerce Based on a Modified UTAUT Theory

This study explored the factors influencing the behavioral intention of Chinese citizens to purchase mobile-phone top-up services on social commerce from the perspective of WeChat users. The UTAUT was applied as the theoretical framework for the research. A questionnaire instrument was used to acquire the research data from 477 respondents. The data analysis was undertaken by the use of Smart PLS by employing the structural equation modeling (SEM) technique. The results indicate that performance expectancy had a direct significant impact on the purchase of mobile phone top-ups on social commerce. In addition, effort expectancy, electronic word of mouth (eWOM), peer influence, and trust in mobile phone top-up services were respectively positive predictors of both performance expectancy and purchase intentions of mobile phone top-up services on social commerce. Further, the results demonstrate that security was significant in moderating the impact of trust in mobile phone top-up services on the purchase of mobile phone top-up services on social commerce.

Can COVID-19 pandemic influence experience response in mobile learning?

The mass spreading of COVID-19 has changed the paradigm of the education industry. In China and many other nations, universities have introduced compulsory remote education programs such as mobile learning (m-learning) to prevent public health hazards caused by the pandemic. However, so far, there is still a lack of understanding of student's learning experience responses in compulsory m-learning programs. As such, there is a necessity to explore the factors and mechanisms which drives students' experience. This paper evaluates the influence of both pedagogy and technology on learner's compulsory m-learning experience response (ER) by extending the mobile technology acceptance model (MTAM) during the COVID-19 pandemic. An online self-administered questionnaire was used to collect the data, which was then analysed through SmartPLS 3.2.9. Importance-performance matrix analysis was applied as a post-hoc procedure to gauge the importance and performance of the exogenous constructs. The results revealed that perceptions of m-learning's learning content quality, user interface, and system's connectivity affect the perceived mobile usefulness and easiness which in turn affects ER. This paper validates MTAM in the field of education by integrating MTAM with pedagogy and technology attributes under a social emergency setting such as the COVID-19 pandemic. In addition, the current research explains users' ER rather than behaviour intention which is commonly adopted in past studies.

Factors That Determine the Adoption Intention of Direct Mobile Purchases through Social Media Apps

In the last few years, a number of social media e-business models including the social networking giants of Facebook, Pinterest and Instagram have offered direct purchase abilities to both their users and the involved enterprises. Hence, individuals can buy directly without having to leave the social media website. At the same time, there is a significant increase in the number of online purchases through mobile devices. To add to this, nowadays, the vast majority of internet users prefer to surf via their smartphone rather than a desktop PC. The aforementioned facts reveal the abilities and potential dynamics of Mobile Social Commerce (MSC), which is considered not only the present but also the future of e-commerce, as well as an area of prosperous academic and managerial concern. In spite of its several extant abilities and its booming future, MSC has been little examined until now. Therefore, this study aims to determine the factors that impact smartphone users’ behavioral intention to adopt direct purchases through social media apps in a country where these kinds of m-services are not yet available. In specific, it extends the well-established Unified Theory of Acceptance and Use of Technology (UTAUT) model with the main ICT facilitators (i.e., convenience, reward and security) and inhibitors (i.e., risk and anxiety). The suggested conceptual model aims to increase the understanding on the topic and strengthen the importance of this major type of MSC. Convenience sampling was applied to gather the data and Structural Equation Modeling (SEM) was then performed to investigate the research hypotheses of the proposed conceptual model. The results show that performance expectancy exerts a positive impact on behavioral intention. Furthermore, all ICT facilitators examined do impact significantly on smartphone users’ decision to adopt direct mobile purchases through social media apps, whereas anxiety exerts a negative effect.

Modeling the Factors that Influence Ghanaian Entrepreneurs to Adopt e-Commerce

This study investigated the factors that influence Ghanaian entrepreneurs to adopt e-commerce. Cross-sectional data was gathered from 520 entrepreneurs in the most populous and industrious regions in Ghana. The unified theory of acceptance and use of technology (UTAUT) was employed to effectively understand the unexplored phenomenon of e-commerce adoption among Ghanaian entrepreneurs. Partial Least Square-Structural Equation Modeling (PLS-SEM) was used to test the hypothesized relationships. The findings indicate that performance expectancy, effort expectancy, and social influence (SI) positively and significantly influenced the behavioral intention (BI) to adopt e-commerce. Facilitating conditions (FC) and BI had a significant positive relationship with the adoption of e-commerce.

An integrated fuzzy model for evaluation and selection of mobile banking (m-banking) applications using new fuzzy-BWM and fuzzy-TOPSIS

Mobile technology has revolutionised various business processes. Banking is one of them. Traditional banking operations are gradually changing with the introduction of efficient mobile technologies. Mobile banking (m-banking) has recently emerged as an innovative banking channel that provides continuous real-time customer service. It is expected that the market for m-banking will expand in the near future. There are currently various types of m-banking applications in the market. However, ranking and selecting efficient applications is difficult due to the involvement of multiple factors. As of now, very few studies have reported the m-banking application selection framework, left scope for further research. The current study proposes an m-banking application selection model based on a combined fuzzy best–worst method (fuzzy-BWM) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy-TOPSIS). The research was carried out in several stages, beginning with the identification of potential factors and progressing to pair-wise comparisons and the final ranking of the applications. The fuzzy set theory was applied to handle the ambiguity of the decision maker. In the first stage, fuzzy-BWM was used to determine the weight of the factors. Further, fuzzy-TOPSIS was applied to rank the m-banking applications. The present study has adopted a new fuzzy BWM, which differs significantly from the existing fuzzy-BWM, to solve the nonlinearity problem of optimisation. The applicability of the proposed model has been demonstrated through a real-life case study. The efficacy of the model has been further examined by performing a sensitivity analysis. The study observed application functionality, convenience, and performance expectancy as significant factors in selecting an m-banking application, followed by performance quality, security, and compatibility. The proposed model can assist financial institutions and customers to overcome the challenges of choosing an appropriate m-banking application. The proposed model can be used to benchmark the m-banking applications in the market.

Mobile learning acceptance in social distancing during the COVID-19 outbreak: The mediation effect of hedonic motivation

M‐learning is a trending field in educational organizations, companies, and also for individual study. However, in some regions the ampleness of the phenomenon is not quantifiable or comparable due to the lack of an adequate framework and reliable metrics. Our research intends to make a little light by assessing the degree of m‐learning adoption in students at a moment when face‐to‐face education moved suddenly online due to the COVID‐19 outbreak's rapid and unpredictable spread. A new model relying on the Unified Theory of Acceptance and Use of Technology (UTAUT) was built to investigate and explain relationships between constructs. It reveals the key factors affecting technology adoption by considering hedonic motivation a mediator instead of an exogenous variable as in UTAUT2. Based on an analysis of 311 higher education learners, the way how performance expectancy, effort expectancy, social influence, and facilitating conditions influence directly or indirectly the behavioral intention is researched. The analysis was conducted employing partial least squares structural equation modeling. The strongest relationship is between hedonic motivation and behavioral intention followed by the one between perceived effectiveness and hedonic motivation. Age, gender, and experience moderate the model's relationships. Research contributes to theory development by successfully adjusting the original UTAUT model. Results indicate that universities may offer learners an enjoyable m‐learning experience by activating social support groups and inserting gameplay elements into the learning system.

Predicting Big Data Adoption in Companies With an Explanatory and Predictive Model

The purpose of this paper is to identify the factors that affect the intention to use Big Data Applications in companies. Research into Big Data usage intention and adoption is scarce and much less from the perspective of the use of these techniques in companies. That is why this research focuses on analyzing the adoption of Big Data Applications by companies. Further to a review of the literature, it is proposed to use a UTAUT model as a starting model with the update and incorporation of other variables such as resistance to use and perceived risk, and then to perform a neural network to predict this adoption. With respect to this non-parametric technique, we found that the multilayer perceptron model (MLP) for the use of Big Data Applications in companies obtains higher AUC values, and a better confusion matrix. This paper is a pioneering study using this hybrid methodology on the intention to use Big Data Applications. The result of this research has important implications for the theory and practice of adopting Big Data Applications.

Continuance intention of baby boomer and X generation as new users of digital payment during COVID-19 pandemic using UTAUT2

The emergence of social distancing and stay at home regulations during the COVID-19 pandemic directly affects people’s lifestyle, including baby boomers and X generation. Many of them have started using digital payments for online or offline transactions to minimize contact with others. This study aims to analyze the continuance intention of the baby boomers and X generation toward the use of digital payments using UTAUT2 (Unified Theory of Acceptance Technology). Data were collected from 320 users with an age range of 40–74 who had just started using digital payments during this pandemic. Structural equation modeling has been used to analyze the data. The result indicates that UTAUT indicators positively affect user satisfaction. User satisfaction positively affects inertia. Overall satisfaction and inertia positively affect continuance intention. Therefore, digital payment companies and banks with digital services can expand their target market beyond Millennials and pay more attention to the older generation like baby boomers and X generation. Managers can find the results of this study useful and beneficial to develop their marketing strategy and take advantage of this situation to increase digital payment users to a broader age range.

The disruptive mobile wallet in the hospitality industry: An extended mobile technology acceptance model

Given that the mobile wallet has become a disruptive innovation, especially in the Malaysian hospitality industry, this study investigates the adoption of mobile wallet in the hospitality industry among consumers. Different from the extant literature, this study extends the newly proposed mobile technology acceptance model with self-efficacy theory, critical mass theory, and flow theory to explain the behavioural intention to adopt. A self-administered questionnaire was utilised to collect data from mobile wallet users who have used a mobile wallet while dining out in restaurants and cafes. Other than technology self-efficacy and perceived critical mass, mobile usefulness, mobile ease of use, mobile self-efficacy, and perceived enjoyment were discovered to have a positive and significant association with the behavioural intention to adopt mobile wallet in the hospitality industry. The findings also suggested there were interrelationships between the constructs employed. Overall, the extended model was able to explain 61% of the variance in behavioural intention to adopt mobile wallet.