The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value

Explaining subscription intention for video streaming platforms in China: Integrating the UTAUT2 model, perceived value theory, and S-O-R theory

PURPOSE

This study examines the factors influencing the intention to subscribe to video streaming platforms in China through integrating the extended unified theory of acceptance and use of technology (UTAUT2), perceived value theory, and stimulus-organism-response (S-O-R) theory.

DESIGN/METHODOLOGY/APPROACH

A quantitative study was conducted to test the hypothesized relationships among the constructs using partial least squares structural equation modeling (PLS-SEM). The sample included 506 viewers of video streaming platforms.

FINDINGS

The results showed that performance expectancy, effort expectancy, social influence, and hedonic motivation had a positive relationship with subscription intention in video streaming platforms. Additionally, perceived value mediated these relationships. Also, habit was positively related to subscription intention. Finally, the attractiveness of alternatives moderated the relationship between perceived value and subscription intention of video streaming platforms in China.

ORIGINALITY/VALUE

This study introduces a moderated mediation mechanism to explain the intention to subscribe to video streaming platforms in China, utilizing the UTAUT2 model, perceived value theory, and S-O-R theory.

Exploring farmers' psychological perspectives on multimedia-based agro-advisory services

Agro-advisory through multimedia plays a crucial role for improving farmers' access to information and serves as a ready reckoner for the stakeholders to make better and informed decisions. Although there is existing research on multimedia-based agro-advisory services (MAS), there remains a significant gap in understanding the psychological factors that affect their usage behaviour (UB), especially among agricultural stakeholders. This demands further investigation through region-specific studies to comprehensively address this gap and devise target-based interventions for their uptake. The current study developed a conceptual model by adapting a well-established framework of the Unified Theory of Acceptance and Use of Technology (UTAUT) to elucidate the psychological elements that impact agricultural stakeholders' MAS usage behaviour. The developed model included constructs such as effort expectancy (EE), self-efficacy (SE), credibility (CR), risk perception (RP), and perceived benefit (PB), which was evaluated using exploratory and confirmatory factor analysis followed by the covariance-based Survey Weighted Structural Equation Modeling (SWSEM) approach from the responses of 225 farmers from Indo-Gangetic plains of India. The findings suggested that EE, SE, and CR of the sources of MAS are the significant determinants of the perceived benefits of MAS with Comparative Fit Index = 0.942, Tucker-Lewis Index = 0.933, and RMSE of Approximation = 0.063 and SRMR = 0.069 and perceived benefit is positively associated with usage behaviour of MAS. The outcomes contribute to the literature on MAS and offer valuable insights for the researchers, policymakers, academicians, and extension advisory service providers.

Privacy Relevance and Disclosure Intention in Mobile Apps: The Mediating and Moderating Roles of Privacy Calculus and Temporal Distance

In digital societies, users' privacy decisions not only affect personal information security and application sustainability, but also profoundly influence the formulation and enforcement of relevant laws. However, existing research mainly adopts a dichotomous perspective of rationality and bounded rationality, lacking an integrated framework to explain the complexity of users' privacy decisions. Therefore, this study integrates privacy calculus theory and Psychological Distance Theory within the Elaboration Likelihood Model (ELM) framework to explore their mediating and moderating roles in the relationship between perceived privacy relevance and disclosure intention. To achieve the research objectives, we employed the vignette method to design an online survey with a 2 (perceived relevance: low vs. high) × 2 (temporal distance: near vs. distant) between-subjects design, ultimately collecting 293 valid responses. The conclusions are as follows: (1) perceived relevance positively affects users' privacy disclosure intention, and perceived benefits and perceived risks play a partial mediating role between them; (2) contrary to individuals' common preference for near temporal distance (immediate rewards), distant temporal distance (delayed rewards) have a more pronounced enhancing effect on the positive relationship between perceived relevance and perceived benefits; (3) the results excluded the influence of control variables such as gender, age, and education level on privacy disclosure intention. This study not only proposes an integrated analytical framework, revealing that users' privacy decisions are jointly influenced by both rational and irrational factors, but also provides practical insights for application developers and regulatory agencies. Finally, we also discuss the limitations of this study and directions for future research.

A Study on Customer Behavior in Online Dating Platforms: Analyzing the Impact of Perceived Value on Enhancing Customer Loyalty

Customer loyalty is critical for organizations to gain market share and maintain a sustained competitive advantage. However, no study has yet explored customer loyalty in online dating platforms. Perceived value theory suggests that perceived value is a key predictor of customer loyalty. Accordingly, this research constructed a conceptual model drawing on a multidimensional perspective of perceived value to explore customer loyalty in online dating platforms and investigated the mediating role of satisfaction. By quantitatively analyzing 352 customers who had experienced online dating platforms and utilizing structural equation modeling (SEM) to examine the relationships among propositions, the research demonstrated a strong positive correlation between perceived value, satisfaction, and loyalty, and a notable indirect impact on loyalty through satisfaction. In addition, the experiential value dimension of perceived benefits had the most positive and substantial influence on perceived value, while the perceived risk dimension of perceived sacrifice had the most negative and notable impact on perceived value. The results of the study provide designers, managers, and vendors of online dating platforms with valuable insights into customer behavior and practical recommendations for improvement, helping them to develop more effective strategies to enhance market competitiveness and ensure the sustainability of their platforms.

Modelling the effects of perceived system quality and personal innovativeness on the intention to use metaverse: a structural equation modelling approach

The metaverse, an interactive and immersive 3D virtual environment, has recently become popular and is widely used in several fields, including education. However, the successful use of metaverse relies on the extent to which users intend to adopt and use it. Close examination of this critical issue reveals a lack of research that examines the effects of certain factors on users' intentions toward using metaverses. Thus, this study extends the technology acceptance model by integrating two constructs-perceived system quality and students' personal innovativeness. Using a survey to collect data, 164 responses were received from students at the University of Ha'il in Saudi Arabia. Two steps in structural equation modelling (SEM) using the AMOS software were applied to analyse the data and test the research hypotheses. The results revealed that perceived system quality had a significant effect on students' intentions to use metaverses through perceived ease of use. Furthermore, personal innovativeness had a significant effect on students' intentions through the perceived usefulness of the metaverse. In addition, perceived usefulness affected students' intentions to use a metaverse. Surprisingly, perceived ease of use had an insignificant effect on students' intentions to use the metaverse. Although the proposed model and its findings contribute to the technology acceptance model (TAM) literature, the study's practical value is significant because it can help educational policymakers and authorities to understand the effect of each factor and plan future strategies. Additionally, the findings of this study can assist practitioners, designers, and developers in designing and promoting the utilisation of metaverses.

The acceptability and effectiveness of artificial intelligence-based chatbot for hypertensive patients in community: protocol for a mixed-methods study

BACKGROUND

Chatbots can provide immediate assistance tailored to patients' needs, making them suitable for sustained accompanying interventions. Nevertheless, there is currently no evidence regarding their acceptability by hypertensive patients and the factors influencing the acceptability in the real-world. Existing evaluation scales often focus solely on the technology itself, overlooking the patients' perspective. Utilizing mixed methods can offer a more comprehensive exploration of influencing factors, laying the groundwork for the future integration of artificial intelligence in chronic disease management practices.

METHODS

The mixed methods will provide a holistic view to understand the effectiveness and acceptability of the intervention. Participants will either receive the standard primary health care or obtain a chatbot speaker. The speaker can provide timely reminders, on-demand consultations, personalized data recording, knowledge broadcasts, as well as entertainment features such as telling jokes. The quantitative part will be conducted as a quasi-randomized controlled trial in community in Beijing. And the convergent design will be adopted. When patients use the speaker for 1 month, scales will be used to measure patients' intention to use the speaker. At the same time, semi-structured interviews will be conducted to explore patients' feelings and influencing factors of using speakers. Data on socio-demography, physical examination, blood pressure, acceptability and self-management behavior will be collected at baseline, as well as 1,3,6, and 12 months later. Furthermore, the cloud database will continuously collect patients' interactions with the speaker. The primary outcome is the efficacy of the chatbot on blood pressure control. The secondary outcome includes the acceptability of the chatbot speaker and the changes of self-management behavior.

DISCUSSION

Artificial intelligence-based chatbot speaker not only caters to patients' self-management needs at home but also effectively organizes intricate and detailed knowledge system for patients with hypertension through a knowledge graph. Patients can promptly access information that aligns with their specific requirements, promoting proactive self-management and playing a crucial role in disease management. This study will serve as a foundation for the application of artificial intelligence technology in chronic disease management, paving the way for further exploration on enhancing the communicative impact of artificial intelligence technology.

TRIAL REGISTRATION

Biomedical Ethics Committee of Peking University: IRB00001052-21106, 2021/10/14; Clinical Trials: ChiCTR2100050578, 2021/08/29.

Exploring the recycled water acceptance based on the technological perspective of UTAUT2: a hybrid analytical approach

Introduction

The development of advanced sewage technologies empowers the industry to produce high-quality recycled water, which greatly influences human's life and health. Thus, this study investigates the mechanism of individuals' adoption of recycled water from the technology adoption perspective.

Methods

Employing the mixed method of structural equation modeling and artificial neural network analysis, we examined a research model developed from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) framework. To examine the research model, this study employs a leading web-survey company (Sojump) to collect 308 valid samples from the residents in mainland China.

Results

The structural equation modeling results verified the associations between the six predictors (performance expectancy, effort expectancy, social influence, facilitating conditions, environmental motivation, and price value), individuals' cognitive and emotional attitudes, and acceptance intention. The artificial neural network analysis validates and complements the structural equation modeling results by unveiling the importance rank of the significant determinants of the acceptance decisions.

Discussion

The study provides theoretical implications for recycled water research and useful insights for practitioners and policymakers to reduce the environmental hazards of water scarcity.

Analytic and heuristic process for prudent antimicrobial use in animals: What are triggers and how do they work?

The over and misuse of antimicrobials in animal agriculture causes a prevailing crisis for humans, animals, and the environment. From the One Health approach perspective, the formation process of adopting prudent antimicrobial use (AMU), once established, can be used to mitigate this crisis. The study aimed to determine the analytic-based and heuristic-based process that evoked prudent AMU among animal farmers by synthesis of stimulus-organism-response framework and dual-system theory and to explore gender differences on risk-benefit trade-offs. A structural equation model was employed to test the proposed hypotheses with field survey data from 1100 small-scale farmers. The results reveal that for the analytic-based process, social influence, antimicrobial-related threats, and self-efficacy are all salient stimuli having indirect effects on intention via the two organisms of perceived risks and perceived benefits. For heuristic-based process, farmers' altruistic value orientations are positively associated with intention. An interesting fact is that threat awareness has two opposite effects on intention, namely, the suppression effect and the enhancement effect. Moreover, the negative effect of perceived risks on intention is greater among female farmers, compared to male counterparts. These findings provide valuable insights for the forming of theory-based intervention strategies to perfect China's national action plan.

Determinants of satisfaction and continuance intention towards online food delivery service users in Indonesia post the COVID-19 pandemic

The COVID-19 pandemic has resulted in behavioural changes in the way people consume food in Indonesia, because people tend to use online food delivery (OFD) services to order food after the pandemic. In line with this, application-based OFD service providers in Indonesia such as GoFood, GrabFood, ShopeeFood, and others are growing year after year, creating competition among OFD service providers. On the other hand, now that the COVID-19 pandemic condition has begun to improve, people may return to ordering food in the traditional manner, namely by visiting restaurants directly without using the OFD service application. As a result, it may jeopardize the stability of the OFD service business. As a result, the purpose of this study is to investigate the factors that influence the satisfaction and intent of OFD service users in Indonesia to continue using OFD services in the future. The Unified Theory of Acceptance and Use of Technology (UTAUT2), Expectancy Confirmation Model (ECM), online review, online rating, and online tracking were all combined to do structural equation modeling (SEM) using the PLS-SEM approach. Data were gathered using an online poll of 325 respondents who have used OFD services. According to the findings of the structural model analysis, effort expectancy, hedonic motivation, price-saving orientation, and confirmation all have a direct impact on the level of satisfaction of OFD service users. Meanwhile, performance expectancy, habit, online review, and satisfaction all influence the intention to continue using OFD services. The findings of this study can be used as a reference for OFD service providers as a service improvement strategy, as well as to expand the literature on consumer behaviour regarding OFD services and provide a foundation for future research.

Predicting m-health acceptance from the perspective of unified theory of acceptance and use of technology

Addressing the growing popularity of mobile health (m-Health) technology in the health industry, the current study examined consumers' intention and behaviour related to the usage of digital applications based on the unified theory of acceptance and use of technology (UTAUT). In particular, this study quantitatively assessed the moderating role of perceived product value and mediating role of intention to use m-Health application among Indonesians. This study adopted a cross-sectional design and collected quantitative data from conveniently selected respondents through an online survey, which involved 2068 Telegram users in Indonesia. All data were subjected to the analysis of partial least square- structural equation modeling (PLS-SEM). The obtained results demonstrated the moderating effect of perceived product value on the relationship between intention to use m-Health application (m-health app) and actual usage of m-Health app and the mediating effects of intention to use m-Health app on the relationships of perceived critical mass, perceived usefulness, perceived convenience, perceived technology accuracy, and perceived privacy protection on actual usage of m-Health app. However, the intention to use m-Health app did not mediate the influence of health consciousness and health motivation on the actual usage of m-Health app. Overall, this study's findings on the significance of intention to use m-Health app and perceived product value based on the UTAUT framework serve as insightful guideline to expand the usage of m-Health app among consumers.

Modelling the mass adoption of mobile payment for e-hailing services using SEM-MGA

Secured financial transactions can now be conveniently made via mobile devices for various products and services, such as e-hailing. However, limited research exists on the factors influencing the adoption of mobile payments specifically for e-hailing services, despite the growing interest in mobile payments in China. This cross-sectional study quantitatively assessed the influence of perceived usefulness, perceived ease of use, social influence, facilitating conditions, perceived security, and lifestyle compatibility on the intention to adopt and the actual adoption of mobile payment for e-hailing services. An online self-administered survey was conducted, involving 413 respondents from China. The results revealed a significant positive influence of perceived ease of use, social influence, facilitating conditions, and perceived security on the intention to adopt mobile payment. Additionally, the study found that the intention to adopt mobile payment positively influenced the actual adoption of mobile payments. Meanwhile, perceived usefulness and lifestyle compatibility demonstrated an insignificant influence on the intention to adopt mobile payments. Subgroup analysis further revealed gender-based differences, indicating that the influence of the intention to adopt mobile payment on the adoption of mobile payment for e-hailing services varied significantly between male and female respondents. Furthermore, the influence of facilitating conditions on the intention to adopt mobile payment for e-hailing services also differed significantly among respondents of different age groups. These findings contribute to a better understanding of the factors influencing the adoption of mobile payment for e-hailing services and provide insights for service providers and policymakers in promoting its adoption.

A machine learning ensemble approach to predicting factors affecting the intention and usage behavior towards online groceries applications in the Philippines

The emergence of e-commerce platforms, especially online grocery shopping, is heightened by the COVID-19 pandemic. Filipino consumers started to adapt online due to the strict quarantine implementations in the country. This study intended to predict and evaluate factors influencing the intention and usage behavior towards online groceries incorporating the integrated Protection Motivation Theory and an extended Unified Theory of Acceptance and Use of Technology applying machine learning ensemble. A total of 373 Filipino consumers of online groceries responded to the survey and evaluated factors under the integrated framework. Artificial Neural Network that is 96.63 % accurate with aligned with the result of the Random Forest Classifier (96 % accuracy with 0.00 standard deviation) having Perceived Benefits as the most significant factor followed by Perceived Vulnerability, Behavioral Intention, Performance Expectancy, and Perceived. These factors will lead to very high usage of online grocery applications. It was established that machine learning algorithms can be used in predicting consumer behavior. These findings may be applied and extended to serve as a framework for government agencies and grocers to market convenient and safe grocery shopping globally.

Gravitating towards Fintech: A study on Undergraduates using extended UTAUT model

One of the most pressing issues affecting people worldwide is the accessibility of financial services in the wake of the COVID-19 outbreak. While peoples' adoption of technological advancements has spiraled over time, the acceptance of Fintech services edged up for instilling resilience during the pandemic. Hence, the study aims at exhuming the Fintech adoption for sustainable financial inclusion among young undergraduate users through the Unified Theory of Acceptance and Use of Technology (UTAUT) model. To test the model, the researchers obtained data from 375 undergrads. The study adopted the Structural Equation Modelling (SEM) approach in AMOS software to examine the determinants that affect the users to embrace Fintech services. The findings revealed that performance expectancy, effort expectancy, and facilitating conditions significantly influence the students' intention to use Fintech, whereas, the users' facilitating condition and behavioral purposes positively influence them to use the financial technology. Interestingly, the social influence and personal innovativeness did not affect their intention to accept and adopt Fintech. Therefore, the study results will help explore the expectations, preferences, and actual level of use of Fintech among undergraduates and contribute to the escalation of Fintech use, leading to sustainable financial inclusion.

Role of Incentives in the Use of Blockchain-Based Platforms for Sharing Sensitive Health Data: Experimental Study

BACKGROUND

Blockchain is an emerging technology that enables secure and decentralized approaches to reduce technical risks and governance challenges associated with sharing data. Although blockchain-based solutions have been suggested for sharing health information, it is still unclear whether a suitable incentive mechanism (intrinsic or extrinsic) can be identified to encourage individuals to share their sensitive data for research purposes.

OBJECTIVE

This study aimed to investigate how important extrinsic incentives are and what type of incentive is the best option in blockchain-based platforms designed for sharing sensitive health information.

METHODS

In this study, we conducted 3 experiments with 493 individuals to investigate the role of extrinsic incentives (ie, cryptocurrency, money, and recognition) in data sharing with research organizations.

RESULTS

The findings highlight that offering different incentives is insufficient to encourage individuals to use blockchain technology or to change their perceptions about the technology's premise for sharing sensitive health data. The results demonstrate that individuals still attribute serious risks to blockchain-based platforms. Privacy and security concerns, trust issues, lack of knowledge about the technology, lack of public acceptance, and lack of regulations are reported as top risks. In terms of attracting people to use blockchain-based platforms for data sharing in health care, we show that the effects of extrinsic motivations (cryptoincentives, money, and status) are significantly overshadowed by inhibitors to technology use.

CONCLUSIONS

We suggest that before emphasizing the use of various types of extrinsic incentives, the users must be educated about the capabilities and benefits offered by this technology. Thus, an essential first step for shifting from an institution-based data exchange to a patient-centric data exchange (using blockchain) is addressing technology inhibitors to promote patient-driven data access control. This study shows that extrinsic incentives alone are inadequate to change users' perceptions, increase their trust, or encourage them to use technology for sharing health data.

Predicting the intention and adoption of wearable payment devices using hybrid SEM-neural network analysis

This study aims to examine the mediating effect of the intention to use wearable payment devices (WPD) between perceived ease of use (PE), perceived usefulness (PU), social influence (SI), perceived trust (TR), and lifestyle compatibility (CM) on the adoption of WPD. Examination was made on the moderating effect of age and gender to improve the understanding of the adoption of WPD as a new payment system. Empirical data was collected through an online survey from 1094 respondents in Malaysia. Furthermore, this study employed dual-stage data analysis through partial least squares structural equation modelling (PLS-SEM) to test the causal and moderating effects, including artificial neural network (ANN) to examine the predictive power of the selected model. As a result, it was found that PE, PU, TR, and CM had a significant positive influence on the intention to use WPD. Furthermore, facilitating conditions and the intention to use WPD exhibited strong positive impacts on the adoption of WPD among Malaysian youth. The intention to use WPD positively and significantly mediated all predictors of adoption of WPD. Following that, ANN analysis confirmed high prediction accuracy of the data fitness. Overall, the findings for ANN highlighted the importance of PE, CM, and TR on the intention to adopt WPD and the impact of facilitating conditions on the adoption of WPD among Malaysian youth. Theoretically, the study extended UTAUT with two additional determinants (e.g., perceived trust and lifestyle compatibility), which were found to have significant influences on the intention to use WPD. The study results would be able to help payment service providers and the smart wearable device industry offer an innovative spectrum of products and present effective marketing tactics to encourage the prospective consumers of Wearable Payment Devices in Malaysia.

Privacy Risk Assessment of Smart Home System Based on a STPA-FMEA Method

Although the smart home industry is rapidly emerging, it faces the risk of privacy security that cannot be neglected. As this industry now has a complex combination system involving multiple subjects, it is difficult for the traditional risk assessment method to meet these new security requirements. In this study, a privacy risk assessment method based on the combination of system theoretic process analysis-failure mode and effect analysis (STPA-FMEA) is proposed for a smart home system, considering the interaction and control of 'user-environment-smart home product'. A total of 35 privacy risk scenarios of 'component-threat-failure-model-incident' combinations are identified. The risk priority numbers (RPN) was used to quantitatively assess the level of risk for each risk scenario and the role of user and environmental factors in influencing the risk. According to the results, the privacy management ability of users and the security state of the environment have significant effects on the quantified values of the privacy risks of smart home systems. The STPA-FMEA method can identify the privacy risk scenarios of a smart home system and the insecurity constraints in the hierarchical control structure of the system in a relatively comprehensive manner. Additionally, the proposed risk control measures based on the STPA-FMEA analysis can effectively reduce the privacy risk of the smart home system. The risk assessment method proposed in this study can be widely applied to the field of risk research of complex systems, and this study can contribute to the improvement of privacy security of smart home systems.

Extending UTAUT2 with knowledge to test Chinese consumers' adoption of imported spirits flash delivery applications

Despite the rapid growth in sales of imported spirits in the Chinese market, consumers are struggling to easily buy high-quality imported spirits with favorable price. The imported spirits flash delivery applications are proposed to provide Chinese consumers with high-quality services delivered within a few hours. This study extends UTUAT2 with knowledge, risk and innovativeness to identify factors influencing Chinese consumers' use of flash delivery services for imported spirits. With the help of service providers, 315 valid questionnaires were collected and an empirical study was carried out. Findings suggest that social influence, habit, innovativeness and knowledge all have significant effects on usage. In particular, knowledge has significant moderating effects on relationships between social influence, habit, innovativeness and usage. This research is supposed to help imported spirits flash delivery providers to further expand the market, and will be of great help to the investment decisions of multinational spirits manufacturers in China.

Factors influencing the adoption intention of using mobile financial service during the COVID-19 pandemic: the role of FinTech

Access to financial services is regarded as one of the most pressing issues confronting communities worldwide sequel to the COVID-19 pandemic. In this regard, FinTech applications such as mobile financial service (MFS) play an essential role in building resilience during the pandemic. Hence, the aim of the study is to investigate the role of MFS platforms in economic resilience by empirically evaluating the determinants that influence the intention of Bangladeshi users toward adopting MFS platforms during the COVID-19 pandemic, through an extension of the Unified Theory of Acceptance and Use of Technology (UTAUT). Using the core structures of the UTAUT, the theoretical model was constructed based on the consumption attributes of financial services such as perceived value, as well as additional situational factors from the extended valence framework, including risk and trust. To test the model, data was obtained from 227 potential MFS users in Bangladesh with the aid of a structured questionnaire survey. Subsequently, the Structural Equation Modeling (SEM) approach was used to analyze the data. The findings showed that social influence, perceived trust, and perceived value are strongly related to the intention of users to adopt MFS platforms, whereas, perceived risk, performance expectancy, and effort expectancy were observed to influence users' perceived value of the MFS platforms during the COVID-19 pandemic. Interestingly, the study results indicated that the users' perceived risk did not influence their intention to adopt MFS platforms during the pandemic. Therefore, the suggested adoption of the MFS framework during and after the pandemic could contribute to the existing research on the adoption of information technology (IT) through the expansion of the UTAUT, in which the performance and effort expectancy of users influence their intention to indirectly adopt MFS through perceived value. Finally, the significant policy implications and future research directions are further addressed.

Antecedents of trust and customer loyalty in online shopping: The moderating effects of online shopping experience and e-shopping spending

This paper determines the antecedents of trust (i.e., perceived ease of use [PEoU], privacy concerns [PC], perceived security [PS], product variety [PV], and on-time delivery [OD]) and customer loyalty (CL) in online retailing. A questionnaire was developed using scales validated in prior e-commerce studies to measure these factors in the conceptual model. Data were collected in an online survey from a non-probability judgement sample of online shoppers between the ages of 18 and 65 years old, who provided informed consent for participation in the survey. Data were analysed via structural equation modeling (SEM) on AMOS version 28. The ethical approval certificate was issued by the College of Business and Economics Research Ethics Committee (CBEREC). The results indicate that customer trust (CT) in online shopping relies on OD, PS, PV, and PEoU, but not PC. CT, followed by OD and PV, significantly impacts CL. The results show that trust mediates the relationship between OD, PS, and PV, and CL. Online shopping experience and e-shopping spending significantly moderate the impact of PV on trust. The impact of OD on CL is significantly moderated by the online shopping experience. This paper validates a scientific approach to coexisting effects of these key forces that e-retailer practitioners can use to gain trust and build CL. Research that validates this valuable knowledge is absent in the literature, as the factors were measured disjointedly in prior studies. This study offers originality by validating these forces in online retailing in South Africa.

The dual effect of digital communication reinforcement drivers on purchase intention in the social commerce environment

The paper draws on the theory of planned behavior (TPB) to investigate the dual effect of digital communication reinforcement drivers: positive (i.e., interactivity, argument quality, hedonic motivation, and perceived enjoyment online) and negative (i.e., intrusive concerns and privacy concerns) on purchase intention. This paper also examines the mediation effect of perceived usefulness and the moderation effect of habit. Using a time-lag approach, 490 responses were collected from Pakistan's social media users and then analyzed using SmartPLS v.3.2.8. Findings showed that interactivity, argument quality, and privacy concerns significantly affected purchase intention. Furthermore, perceived usefulness was partially mediated, and habit was discovered to be a significant moderator in liking perceived usefulness with enjoyment online and purchase intention. This paper advances TPB understanding and develops an integrated model for businesses to better understand customer physiology on social commerce platforms through effective contributions in theory and practice.

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.

The adoption of remote work platforms after the Covid-19 lockdown: New approach, new evidence

With the aim of providing further insights into the driving factors influencing behavioral intentions and expectations to use remote work after the Covid-19 lockdown, this study draws on an enhanced version of the technology acceptance model to analyze the determinants and moderating factors of remote work platform use. From an analysis of quantitative data collected from questionnaires and qualitative data from interviews with employees of Chinese firms in the service sector, we conclude that post-lockdown adoption of remote work is explained by three main variables: behavioral intention, behavioral expectation and facilitating conditions, but demographic characteristics and factors related to the specific features of remote work all nevertheless moderate the relationships in our model. In addition to gender, the generational gap and behavioral tendency should be taken into consideration to improve employee acceptance rates.

Will Smart Improvements to Child Restraints Increase Their Popularity?

In developing countries, child safety seat use remains low, which contributes to the consistently high rate of child injuries and deaths in traffic accidents. In order to protect the safety of child passengers, it is necessary to improve the public acceptance of child restraints. We improved the shortcomings of the traditional child restraints by adding some new features: 1, tightening Isofix automatically; 2, using temperature sensing, a high-temperature alarm, automatic ventilation, and cooling; 3, using pressure sensing, if the child is left alone it will set off the car alarm; 4, voice control to adjust the angle of the backrest; 5, the seat can be folded into the trunk. These functions make human-computer interaction more humane. The authors collected changes in parental acceptance of child restraints using the interview method and questionnaires. We found that acceptance increased significantly after making intelligent improvements to the child restraints. The authors used the Technology Acceptance Model to identify the key caveats influencing users' use of intelligent child restraints. Performance expectations, effort expectations, social influence, convenience, and hedonic motivation positively and significantly impacted the willingness to use intelligent child restraints, so the authors suggest that these points should be emphasized when promoting the product. The current study findings have theoretical and practical implications for smart child restraint designers, manufacturers, sellers, and government agencies. To better understand and promote child restraint, researchers and marketers can analyze how people accept child restraint based on our research model.

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.

Can Your Smartphone Make You a Tourist? Mine Does: Understanding the Consumer’s Adoption Mechanism for Mobile Payment System

Payment through mobile phones is a vital breakthrough in the arena of online businesses and e-commerce. The purpose of this study was to investigate the determinants, enablers, and barriers involved in the success or failure of the mobile payment system (MPS) for the travel industry. The study employs the constructs operationalized from coping theory, unified theory of acceptance and use of technology (UTAUT 2), and innovation resistance theory (IRT). The data has been collected from the 378 travelers who have used MPS for travel bookings for the first time. The customers of various travel agencies have been approached using an online questionnaire. Data has been analyzed using Statistical Package for Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) version 26. The analysis revealed several interesting findings. All of the direct hypotheses for coping theory constructs were accepted except for the mediating role of satisfaction. However, the factors of UTAUT 2 and IRT revealed very thought-provoking findings, questioning various obvious perceptions. The findings of the study can be used by the media agencies, hotels, and travel and tourism departments of the governments, especially in the context of developing nations.

Technology Adoption in the Digital Entertainment Industry during the COVID-19 Pandemic: An Extended UTAUT2 Model for Online Theater Streaming

While the digitalization of products and services in the entertainment industry has gained momentum in the last decades, online theater streaming is a relatively new phenomenon boosted by the COVID-19 restrictions, which created new market opportunities—and demand—for theaters’ online presence. This study investigates a new online platform providing theater streaming services in Hungary from a customer-centric, technology acceptance point of view. The survey-based study is designed to examine which factors of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model are—and were—relevant in the under-researched live performance art sector of the digital entertainment industry under the unprecedented, coercive conditions of pandemic lockdowns. The results of the partial least squares structural equation modeling (PLS-SEM) show that habit is the most influential factor of theater webcasting adoption (before hedonic motivations and price value), suggesting that the new habits formed during the COVID-19 lockdowns might serve as a basis of a sustainable digital business model for theatres in the post-pandemic era as well. The analysis also tested for potential generational differences between cohorts of users, finding no significant ones, which suggests that, under this specific set of social, technology and market conditions, all generations react similarly and are equally relevant for widening the customer base. Keeping in mind some limitations (self-reported and cross-sectional data), these empirical results can not only enrich the scientific body of knowledge but can also serve as the basis of future marketing and communication strategies developed by partitioners.

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.

Cross-Countries Comparison Toward Digital Currency Acceptance: Integrating UTAUT2 Into ITM

In the context of digital monetary market integration, the importance of cross-border digital currency research is receiving prominent attention. This study integrated Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and initial trust factors (ITM) into an integrative framework, which synthetically complemented the objective measures and subjective insights of digital currencies. The results indicated the integrated framework, which verified its robustness predicting the acceptance and recommendation intention of digital currency. By analyzing the two different features of digital currencies, this research puts forward a set of targeted solutions to ensure that users of Chinese and Korean digital currencies make a long-term policy for the sustainability, eventually benefitting the cross-border digital monetary transactions and economic cooperation in Asia, which leads the world to the sustainable development in the digital currencies field.

Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities

Privacy disclosure is one of the most common user information behaviors in online health communities. Under the premise of implementing privacy protection strategies in online health communities, promoting user privacy disclosure behavior can result in a “win–win” scenario for users and online health communities. Combining the real situation and evolutionary game theory, in this study, we first constructed an evolutionary game model of privacy disclosure behavior with users and online health communities as the main participants. Then, we solved the replication dynamic equations for both parties and analyzed the evolutionary stable strategies (ESSs) in different scenarios. Finally, we adopted MATLAB for numerical simulations to verify the accuracy of the model. Studies show that: (1) factors such as medical service support and community rewards that users receive after disclosing their private personal information affect user game strategy; and (2) the additional costs of the online health communities implementing the “positive protection” strategy and the expected loss related to the privacy leakage risk affect the online health communities’ game strategy. In this regard, this paper puts forward the following suggestions in order to optimize the benefits of both sets of participants: the explicit benefits of users should be improved, the internal environment of the communities should be optimized, the additional costs of the “positive protection” strategy should be reduced, and penalties for privacy leakages should be increased.

The effects of extrinsic reward that affect a user's continuous intention to use a fitness application

Fitness application service providers are offering rewards, such as points to users as incentives for service use. However, it is questionable whether this reward offering is an effective measure for persuading consumers to use fitness applications continuously. This study examines how reward affects continued use of fitness applications. An online survey was conducted on 268 people who actually used the fitness application. Respondents were divided into two groups at random, an extrinsic reward group and a non-extrinsic reward group, to check the effects of the rewards. Structural equation modeling was used for data analysis. Factors influencing a user's continuous intention to use fitness applications will vary depending on whether rewards are provided. For the extrinsic reward group, perceived enjoyment and perceived privacy protection were significant variables to continue use of a fitness application. However, for the non-extrinsic reward group, monetary value was a significant variable. For continuous use of a fitness application, if rewards are provided, it is necessary to emphasize intrinsic factors such as fun rather than extrinsic factors such as savings and cost. On the other hand, without rewards, it is necessary to highlight extrinsic factors rather than intrinsic factors.

Investigating Customer Behavior of Using Contactless Payment in China: A Comparative Study of Facial Recognition Payment and Mobile QR-Code Payment

Emerging technologies have made tremendous changes in people’s daily lives, and they have profoundly influenced their economic and consumption activities. Recently, the COVID-19 pandemic has also drastically increased individuals’ usage of contactless payment technologies, such as mobile and facial recognition payments, which has accelerated the transformation of digital transaction services in China. In this study, the findings show that perceived usefulness, perceived ease of use, and service security can affect the perceived value and user satisfaction of using contactless payment. Moreover, a higher perceived value and satisfaction level may encourage more post-adoption behaviors, such as continuous and habitual usage of contactless payment methods or encouraging others to use contactless payment methods via word-of-mouth; however, perceived value did not have a direct effect on continuous usage. In addition, there are certain differences in user behavior depending on whether facial recognition payment or mobile QR-code payment is used. For QR-code payment users, overall, their satisfaction and post-adoption behaviors are more strongly bonded with each other compared with the behaviors of facial recognition payment users. This study has generated more information and insight into the transformation of digital payment and can help managers align their strategies more efficiently in the post-pandemic era.

The Antecedents of Willingness to Adopt and Pay for the IoT in the Agricultural Industry: An Application of the UTAUT 2 Theory

This paper aims to examine the factors influencing the willingness of Bangladeshi farmers to adopt and pay for the Internet of Things (IoT) in the agricultural sector by applying the theoretical framework of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2). To this end, the study employed a quantitative research methodology and obtained data from 345 farmers from the northern districts of Bangladesh. Using a cross-sectional survey design and convenience sampling method, a study of premium fruit growers was undertaken to assess IoT use in agriculture, and the primary survey data were analyzed using the Structural Equation Modeling (SEM) approach via AMOS 26. The study confirmed that effort expectancy, performance expectancy, facilitating condition, hedonic motivation, government support, price value, personal innovativeness, and trust influence the willingness of Bangladeshi farmers to adopt the IoT. Additionally, predictors such as trust and willingness to adopt were observed to influence the willingness to pay for the IoT, while the construct ‘performance expectancy’ produced no effect. The study also revealed that the willingness to adopt moderates the association between performance expectancy, price value, and willingness to pay for the IoT. This research has novel implications because it investigates the behavior of rural customers with respect to innovation adoption, which in this case is the IoT in agriculture. It outlines precise reasons for the willing adoption of the IoT in agriculture, which will, in turn, assist marketers of IoT technology in the design of appropriate marketing strategies to increase acceptance in rural areas. Using the proposed model that incorporates farmers’ willingness to pay, this empirical study takes the first step in examining whether farmers in a developing economy such as Bangladesh will adopt and pay for the IoT.

Extending UTAUT with national identity and fairness to understand user adoption of DCEP in China

The introduction of digital currency electronic payment (DCEP) by the Central Bank of China is conducive to the central bank's timely grasp of macroeconomic dynamics and the internationalization of RMB. As DCEP is one of the first digital currencies issued by the central bank to be used on a large scale internationally, it is necessary to conduct research on its user adoption. Therefore, this research extends the unified theory of acceptance and use of technology (UTAUT) to explore factors affecting the adoption of DCEP. The researchers cooperated with city banks that have started to use DCEP, and distributed questionnaires to users in the lobbies of these banks. A total of 295 valid questionnaires were empirically examined with Smart-PLS. The results indicate that perceived fairness, habits, social influence and national identity have significant effects on usage, with p values less than 0.05. National identity is shown to be a significant moderator of the relationships between perceived fairness, habit, perceived risk and usage, with p values less than 0.05. National identity is shown to have no moderating effect between social influence and usage, with a p value greater than 0.05. This research provides the central bank and the government with suggestions to increase user enthusiasm and reduce user perceived risks, thereby promoting the widespread use of DCEP.

Assessing the Effects of the COVID-19 Pandemic on M-Commerce Adoption: An Adapted UTAUT2 Approach

The COVID-19 pandemic has impacted consumers’ lives and their shopping patterns, leading them towards mobile commerce. To address current shopping circumstances, an adapted UTAUT2 model aims to integrate trust and perceptions of the effects of the COVID-19 pandemic on consumers’ behavioral intention to rely on m-commerce during this period. The study proposes a research model which is investigated with the help of structural equation modelling in AMOS. Using the framework of a cross-sectional study, data were collected from an emerging market in Romania, where internet speed ranks 4th worldwide and where the yearly increase in internet and social media users is approximately 10%. By using confirmatory factor analysis and structural equation modelling, the research validates the applicability of UTAUT2 in examining consumers’ behavioral intent of using m-commerce during a pandemic. Hedonic motivation is the strongest predictor of consumers’ behavioral intentions to continue using m-commerce. The findings contribute to understandings of consumers’ behavior with m-commerce in an emerging market, extending knowledge based on the adapted UTAUT2 model and allowing for comprehension of the key role of trust and social influences in affecting consumers’ perceptions of the COVID-19 outbreak in relation to shopping patterns.

Are there any key factors that encourage food delivery applications use during the COVID-19 pandemic in Thailand and the role of HRM?

BACKGROUND: Recently, because of the COVID-19 pandemic, customer sentiment has evolved as the new “normal” for food consumption—as it affects customer behavioral change, including the way customers eat. Therefore, understanding customer demands and needs will help food delivery aggregators and retailers produce sustainable, competitive advantage and drive profitability. OBJECTIVE: This paper aims to investigate the determinant factors of Thai consumers’ intention to use on-demand food delivery applications. METHODS: Convenient random sampling was used to gather data from 250 participants who have used food delivery applications in Thailand and Amos version 23 to test model validity and the hypotheses. RESULTS: The results show that satisfaction is critical for the intention to use food delivery applications. Social influence, trust, convenience, and application quality were found to play an essential role in meeting the needs of satisfaction toward the intention to use, and application quality is the most important. However, habit showed a negative relationship, and price value was found to have a nonsignificant impact on satisfaction. CONCLUSIONS: Food delivery aggregators should ensure the quality of application updates and efficiency and that users have the best quality experience to maintain customer satisfaction. However, customers are also concerned about their health and safety, which has altered their purchasing behavior. Therefore, restaurant players should add a third delivery system that optimize online ordering and delivery.

Perceptions of users and non-users of an early contact tracing mobile application to fight COVID-19 spread: a value-based empirical investigation

Purpose

The purpose of this study is to describe a comparative study of the perceptions of users and non-users of an early contact tracing application helping to prevent the spread of the COVID-19 pandemic. The unprecedented incidence of this disease warrants investigating theoretically the use of mobile contact tracing applications as a promising approach to curtail its transmission.

Design/methodology/approach

A consumption value-based model of the adoption and use of a contact tracing mobile application was built and tested through a cross-sectional survey conducted with 2 samples (of 309 already users and 306 non-users) in the Province of Alberta, Canada.

Findings

Utilitarian and social values together with health information seeking and perceived critical mass drive the use of the application while perceived privacy risk is an obstacle to usage for both users and non-users.

Research limitations/implications

Study participants self-assessed their risk category of potential exposure to the COVID-19 virus, and this was a subjective measure including an emotional component.

Practical implications

No major differences in the approaches targeting users and non-users of a mobile contact tracing application to encourage its adoption and use are necessary.

Social implications

Additional efforts are required to convey to people information on the benefits and current rate of use of such an application and to mitigate privacy risk concerns.

Originality/value

Overall, the study offers theoretical and practical contributions that may help improve the adoption and usage of contact tracing applications addressing the COVID-19 pandemic or other possible public health crises.

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.

Factors Impacting Mobile Banking in India: Empirical Approach Extending UTAUT2 with Perceived Value and Trust

The aim of this research is to study the factors impacting usage of mobile banking (mBanking) by consumers in India. The study adopts the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) with Social Value (SV), Monetary Value (MV), Emotional Value (EV), Quality Value (QV), Trust and the moderation effect of gender. Online and offline survey methods were used to collect primary data from 457 Indian consumers using mBanking. SPSS AMOS was utilized to empirically validate the conceptual model, test research hypothesis and moderation effect. The factors effort expectancy (EE), monetary value (MV), emotional value (EV), quality value (QV) and trust (TR) were found to be significant on behavioural intent (BI), whereas performance expectancy (PE) and social value (SV) were not found to be significant. Banking organizations can formulate strategies to attract new consumers and continue to engage in retaining consumers in using these influencing factors to adopt mBanking and other related mobile financial services (MFS). The study integrates perceived value components and trust with UTAUT2 to form a comprehensive model for examining mBanking adoption.

Are satisfied customers willing to pay more for extra services?

5G service refers to the mobile services build on the 5th generation telecommunication technology. It enhances end users’ experiences of the mobile internet surfing significantly. The high bandwidth of 5G technologies offers vendors opportunities to provide more value-added services to their customers and therefore improve the revenue. However, the competition in this market is intensive. In order to survive and finally get some payback, the vendors need to analysis the acceptance of 5G services from their consumers’ perspective. In this paper, we use the extended TAM model to investigate the 5G service acceptance in China. We conducted a survey to testify our model and got the results to support our argument. Our study has both theoretical contribution to the people who would like to do research in this area and practical contribution to managers who would like to provide 5G services to their customers.

What Factors Affect a User’s Intention to Use Fitness Applications? The Moderating Effect of Health Status: A Cross-Sectional Study

Objective

Fitness applications are becoming a tool for users who want to exercise and diet. This study examines what factors affect users’ intention to use fitness applications and how they depend on users’ health status.

Methods

An online survey was conducted on 428 potential fitness application users from South Korea. For this study, the extended unified theory of acceptance and use of technology (UTAUT2) was applied, and structural equation models were used for the data analysis.

Results

The results showed that for potential fitness application users, performance expectancy, effort expectancy, hedonic motivation, and perceived privacy protection were significant variables; however, social influence was insignificant. Factors influencing users’ intention to use fitness applications will vary depending on health status.

Conclusion

This study provides the following implications for health researchers, fitness application designers, and marketers. When trying to use fitness application, values such as performance expectancy, effort expectancy, hedonic motivation, and perceived privacy protection should be emphasized. In particular, for users with chronic diseases, the performance expectancy of fitness apps is more critical than any other factor.

Factors influencing the young physicians’ intention to use Internet of Things (IoT) services in healthcare

The Internet of Things (IoT) enabled technologies to have proliferated due to their abilities to capture and exchange quality information. This empirical study aims to investigate the factors influencing the intention to use IoT services in healthcare by young physicians. An integrated model based on the theory of planned behaviour (TPB) and diffusion of innovations (DOI) theories are drawn upon and analyzed through a Structural Equation Modelling (SEM) with importance-performance map analysis (IPMA). Data were collected through a structured survey questionnaire. The results indicated that behavioural intention to use IoT in healthcare services vastly affected by the attitude and value co-creation. Attitude was found to be a principal determinant followed by the relative advantage towards behavioural intention to use IoT services. The novelty of this empirical study is that the proposed integrated model provides a meaningful application of the young physicians’ intention to use IoT in healthcare in developing countries.

A New Integrated FUCOM–CODAS Framework with Fermatean Fuzzy Information for Multi-Criteria Group Decision-Making

Smartphones have become an inevitable part of every facet of modern society. The selection of a particular smartphone brand from multiple options that are available is a complex and dynamic decision-making problem, involving multiple conflicting criteria that are associated with imprecise asymmetric information imposed by the uncertainty of the consumers. In this paper, we propose a novel hybrid full consistency method (FUCOM) and a combinative distance based assessment (CODAS) based on the multi-criteria group decision-making (MAGDM) framework in the Fermatean fuzzy (FF) domain for smartphone brand selection. We derive the criteria using the UTAUT2 (unified theory of acceptance and ese of technology) model. A group of 15 decision makers (DMs) participated in our study. We compare 14 leading smartphone brands in India and find that the brands having superior features of a good quality and selling a brand image at a affordable price outperform other smartphones. To check the validity of our framework, we compare the results using extant multi-criteria decision-making (MCDM) models. We observe our model provides a consistent solution. Furthermore, we carry out a sensitivity analysis for ascertaining the robustness and stability of the results generated by our model. The results of the sensitivity analysis show that our proposed framework delivers a stable and robust solution.

Understanding the determinants of e-wallet continuance usage intention in Malaysia

The present research aims to investigate the determinants of e-wallet continuance usage intention in Malaysia using extending Technology Continuance Theory (TCT) via examining four variables, namely price benefit, trust, habit, and operational constraints. This paper adopts a quantitative approach to collect data with non-probability sampling using the purposive sampling technique. An online survey was conducted and a total of 379 respondents submitted their answers. The obtained results have shown that continue use of e-wallet is not affected by perceived usefulness (PU) and trust. However, there is a significant influence associated with perceived ease of use (PEU), PU, and satisfaction toward user’s attitude that, in turn, substantially impacts the users’ intention to continue to use e-wallet. This is one of the prior studies exploring Malaysian's intention to continue using e-wallet, using the TCT model as the research framework, and through examining four variables adopted from the literature, including price benefit, habit, trust, and operational constraints. The practical implications for the service providers and policymakers from the present findings can be used to develop strategies to gain a sustainable, competitive advantage, and promote continuous intention of e-wallet usage.

Benefits or Risks: What Influences Novice Drivers Regarding Adopting Smart Cars?

Level 4 autonomous vehicles (AVs) are smart vehicles that can move between two different points without any human interference. In 2018, the Saudi Arabian ban on female drivers was finally lifted, resulting in a large number of novice women drivers of different ages. The Kingdom might therefore be considered a risky place to drive, but AVs would help novices to reduce their fear of driving and reduce accidents. Previous studies focused narrowly on those who already had sufficient driving experience and held a valid driving license, but there were no studies on the adoption of smart cars by novice drivers. Based on a literature search, no studies had used a net valence model (NVM) for the adoption of AVs to understand their benefits/risks. Therefore, this study proposed an adoption model for AVs using an NVM to identify the benefit and risk factors that have an impact on beginner drivers’ adoption of autonomous vehicles. A survey method was applied using the purposive sampling technique. Data were collected from 1400 female Saudi novice drivers who had experience with driving AVs. Data analysis was performed using Smart PLS Version 3. The results showed that individuals tended to ignore potential risks and focus instead on the potential benefits of using AVs. Performance expectancy, enjoyment, and effort expectancy were found to be positively related to the perceived advantages. On the other hand, the perceived risk as a construct did not have an impact on beginner drivers’ adoption of autonomous vehicles. Therefore, the major theoretical contribution of this study was the formation of a new NVM model by incorporating three more constructs, which were social influence, personal innovativeness, and alternatives. Finally, the enhanced NVM model could assist AV developers in identifying the expected benefits and drawbacks of AV adoption.