User Adoption Research Articles

There’s (not) an App for that: situating smartphones, Excel and the techno-political interfaces and infrastructures of digital solutions for COVID-19

This paper focuses on the operational-infrastructural puzzles of mHealth via COVID-19 Contact Tracing Apps (CTA). Significant literature exists on user adoption of the platformisation of public health during the pandemic, but there has been limited consideration of how those responsible for implementing CTA design, deployment, and use of public health infrastructures did so. We redress this imbalance by exploring some of the politics and practicalities of offering CTA as technical ‘solutions’ to pandemic problems. Our work adds to previous comparative analyses of mHealth by drawing on data from key actors across government, industry, and civil society involved in designing and implementing CTA into public health across 5 jurisdictions: Australia, Canada, New Zealand, Singapore, and the United Kingdom. While CTA research often frames tensions around efficacy and adoption (e.g. privacy trade-off), we find hidden infrastructural tensions within a situation of political and technical constraints in the ‘back end’ of the platformisation of public health. The paper offers new insights to pandemic politics by shifting questions from digital contact tracing and pandemic surveillance interfaces to understanding CTA as infrastructures of public health. While CTA user-software interactions produce certain research questions, querying the infrastructural complexity of digital public health projects require and produce a different set of data and knowledge.

Retraction notice: Uses and gratifications of metaverse: understanding the user adoption factors through a mixed-method approach

Retraction notice: Uses and gratifications of metaverse: understanding the user adoption factors through a mixed-method approach

Campus Heaven: AI-Powered Student Accommodation and Services Hub

The growing demand for student accommodations has led to inefficiencies in finding reliable housing near educational institutions. "Campus Heaven" aims to bridge this gap by leveraging AI and ML to provide a seamless accommodation and service hub for students. This paper explores the need, architecture, methodologies, and implementation details of the proposed system. The system integrates machine learning for sentiment analysis on reviews, an AI chatbot for assistance, and a comprehensive services module for student necessities. Key findings indicate that the platform improves user satisfaction by offering reliable service options and fostering community interaction among students. However, challenges related to user adoption and data privacy are noted. Future enhancements could include expanding service offerings and improving community engagement features

Exploring the ‘Dark Side’ of AI‐Powered Digital Assistants: A Moderated Mediation Model of Antecedents and Outcomes of Perceived Creepiness

ABSTRACTArtificial intelligence‐powered digital assistants (DAs) offer benefits, but their downsides can hinder user adoption and limit market potential. Although research exists on users' experiences with DAs, less is known about how user characteristics influence perceptions of a ‘dark side’—perceived creepiness. This study explores how perceived creepiness, user characteristics (uncertainty avoidance), and anxieties triggered by DAs (privacy concerns and technology anxiety) relate to distrust and disengagement from DAs. Based on the stressor‐strain‐outcome and person‐environment fit models, a research model was proposed and tested using survey data from 509 DA users analysed with Amos version 29 software. The results reveal that privacy concerns, uncertainty avoidance, and technology anxiety positively influence perceived creepiness and distrust of DAs, leading to disengagement. Moreover, uncertainty avoidance moderates these relationships, with users higher in uncertainty avoidance experiencing a stronger link between privacy concerns/technology anxiety and perceived creepiness. Importantly, the study shows indirect effects mediated by perceived creepiness, with uncertainty avoidance further moderating these indirect relationships. These findings contribute to literature by highlighting the interplay between user characteristics, DA‐induced anxieties, perceived creepiness, and user disengagement with DAs.

Enhancing User Experience during Organizational Transformation: Effective Change Management and User Adoption Strategies

Enhancing User Experience during Organizational Transformation: Effective Change Management and User Adoption Strategies

Artificial Intelligence Comic Strip (AICS) Generators: A Review of Subscription Models, Pricing, and User Satisfaction

This study investigates the evolution of Artificial Intelligence Comic Strip (AICS) platforms by analyzing their pricing strategies, subscription models, and user satisfaction. Fifteen leading platforms were systematically selected based on popularity, unique features, and diverse user groups, including beginners, educators, and professionals. They employed user feedback and platform analysis to evaluate pricing models and their impact on accessibility and retention. Key findings revealed five dominant pricing strategies: freemium models, tiered subscriptions, credit-based systems, pay-per-use options, and customizable services. While freemium models effectively introduce users to the platforms, high subscription fees and complicated credit systems often hinder user retention. User feedback indicated dissatisfaction with unclear pricing structures and limited affordability, particularly in regions with financial constraints. Adaptive pricing models incorporating user engagement metrics and regional economic factors were identified as potential solutions to enhance accessibility. Platforms combining affordability with robust features achieved better satisfaction rates and broader user adoption. Additionally, the study highlighted the importance of transparent communication and simplified interfaces to address barriers for non-expert users. This study underscores the need for AICS platforms to adopt inclusive pricing and user-centric designs. By doing so, they can attract a diverse audience, encourage creative participation, and strengthen their market position. These findings contribute to understanding how AICS platforms can balance user satisfaction and revenue generation while fostering creative expression and democratizing storytelling tools.

An extension of Trust and TAM model with TPB in the adoption of digital payment: An empirical study in Vietnam

Background Digital payment systems are pivotal in the digital economy, relying on the interplay between internet technology and e-vendors. This study seeks to explore acceptance behaviors regarding digital payments by employing an extended version of the Trust and Technology Acceptance Model (TAM) and incorporating the Theory of Planned Behavior (TPB). Methods We conducted a qualitative analysis using interview data from 509 respondents and applied Structural Equation Modeling (SEM) to evaluate the relationships between key variables. The extended model allows for a comprehensive examination of both technological and trust-related factors influencing adoption. Results Our analysis revealed that all standardized path coefficients were positively significant, except for the path from perceived usefulness (PU) to attitude (ATT). The findings confirm that while digital payments are primarily driven by Internet and communication technologies, addressing trust-related issues is essential for enhancing user adoption. The TAM identifies perceived usefulness and perceived ease of use, alongside trust, as critical factors affecting behavioral intention. In the TPB framework, trust significantly impacts digital payment adoption through mediators such as attitude, perceived behavioral control, and subjective norm. Conclusions This study enhances our understanding of the factors influencing digital payment adoption, emphasizing the need to address both technological and trust issues. The insights gained provide valuable recommendations for increasing the use of digital payment systems, particularly in the Northern mountainous regions of Vietnam, thereby fostering greater financial inclusion and economic growth.

The future of human experience: the drivers of user adoption of the metaverse

The future of human experience: the drivers of user adoption of the metaverse

UNIFIED PAYMENT INTERFACE: REVOLUTIONIZING MODERN PAYMENT SYSTEMS

This paper examines the Unified Payment Interface (UPI), a cutting-edge payment system introduced in India by the National Payments Corporation of India. UPI is a mobile-centric, real-time interbank payment platform designed to transform and democratize digital payments in the country. The study delves into the evolution of India's payment systems and provides a comprehensive analysis of UPI's technology, focusing on its architecture and security framework through empirical and theoretical literature. UPI stands out as a major advancement compared to existing payment systems, offering benefits such as reduced costs, user-friendly interfaces, faster settlement times, and robust security measures. With its modular API-based architecture, UPI fosters the creation of innovative solutions for both consumers and businesses. Although still in its early stages, the development of merchant-focused UPI solutions holds the potential to significantly enhance user adoption. By integrating a broader section of the population into the digital economy, UPI could play a pivotal role in advancing financial inclusion in India. KEYWORDS: Mobile payments, Real Time Payments, Unified Payment Interface, Digital payments

The Influence of Service Failure on Mobile Banking Usage and Its Relation to User Satisfaction

The explosive expansion of the internet has changed the way banks communicate with their clients. MyBCA, a mobile banking (m-banking) application, is designed to meet the needs of customers who prefer banking from home. This study aims to analyze the impact of m-banking service failures on MyBCA user adoption and satisfaction. 390 respondents participated in this quantitative study, with data analysis using SMARTPLS 3.1. Results show that m-banking adoption is significantly affected by functional, system, information, and service failures. In addition, the use of m-banking was also found to have a significant influence on use satisfaction towards m-banking. Despite functional failures, users still use m-banking frequently. System failures, such as technical glitches, have a significant impact on usage. In contrast, information failures have less impact than other failures. Service failures, such as transaction errors, also have a major impact on usage. This study uses MBFM to analyze the interrelationships between service failures, m-banking adoption, and user satisfaction, providing important insights for the future development of m-banking services. The results of this study can be used as a basis for designing more targeted service quality improvement strategies, with a priority on improving the core features that are most frequently used by users

Survey of Artificial Intelligence Model Marketplace

The rapid advancement and widespread adoption of artificial intelligence (AI) across diverse industries, including healthcare, finance, manufacturing, and retail, underscore the transformative potential of AI technologies. This necessitates the development of viable AI model marketplaces that facilitate the development, trading, and sharing of AI models across the pervasive industrial domains to harness and streamline their daily activities. These marketplaces act as centralized hubs, enabling stakeholders such as developers, data owners, brokers, and buyers to collaborate and exchange resources seamlessly. However, existing AI marketplaces often fail to address the demands of modern and next-generation application domains. Limitations in pricing models, standardization, and transparency hinder their efficiency, leading to a lack of scalability and user adoption. This paper aims to target researchers, industry professionals, and policymakers involved in AI development and deployment, providing actionable insights for designing robust, secure, and transparent AI marketplaces. By examining the evolving landscape of AI marketplaces, this paper identifies critical gaps in current practices, such as inadequate pricing schemes, insufficient standardization, and fragmented policy enforcement mechanisms. It further explores the AI model life-cycle, highlighting pricing, trading, tracking, security, and compliance challenges. This detailed analysis is intended for an audience with a foundational understanding of AI systems, marketplaces, and their operational ecosystems. The findings aim to inform stakeholders about the pressing need for innovation and customization in AI marketplaces while emphasizing the importance of balancing efficiency, security, and trust. This paper serves as a blueprint for the development of next-generation AI marketplaces that meet the demands of both current and future application domains, ensuring sustainable growth and widespread adoption.

Factors Influencing the Intention to Use ECNY and Its Driving Mechanisms: Based on the Theory of Planned Behavior and Technology Acceptance Model

Central banks across major economies are actively engaging in research, pilot programs, and the implementation of central bank digital currencies (CBDCs). Despite these efforts, consumer interest in digital currencies such as ECNY (Digital Yuan) issued by the People’s Bank of China remains relatively low within the personal consumption market. To address this, the study examines key factors shaping residents’ willingness to adopt ECNY.The research introduces a conceptual framework incorporating Policy Driving, Service Quality, Trust, Satisfaction, Perceived Usefulness, and Use Intention as critical variables. By applying theories of planned behavior and technology acceptance, it delves into how these elements influence the intention to use ECNY. Findings indicate that all the identified factors, including Policy Driving, Service Quality, Trust, Satisfaction, and Perceived Usefulness, significantly impact users' willingness to adopt ECNY. Among these, Policy Driving emerged as the most influential determinant. Additionally, the analysis highlights interrelations among Service Quality, Satisfaction, Trust, and Perceived Usefulness, demonstrating their interconnected roles in shaping user adoption behavior. These insights contribute substantial theoretical value by illuminating the dynamics underlying ECNY adoption, offering actionable strategies for enhancing its implementation. Furthermore, this study extends its relevance by providing practical recommendations for accelerating the adoption of CBDCs globally, underscoring their potential for advancing digital financial ecosystems worldwide.

A Conceptual Framework for the Adoption of Cloud Computing in a Higher Education Institutions

Today, with significant improvements of computing capacities, the world is witnessing significant technological advancements. Cloud computing especially, is increasingly becoming an advantageous tool, in developed countries especially, and these countries have invested substantially in cloud computing systems to enable the implementation of hi-tech advancements in many of their industries. On the other hand, in developing and underdeveloped countries, the adoption of cloud computing is still in the early stages; as can be observed, there has been some form of digital transformation of data systems in these countries. In Jordan, The factors affecting cloud computing adoption among higher education institutions were still underexplored, especially on the issues pertaining to cloud computing adoption. Therefore. Major factors with potential impact on user adoption of cloud computing were hence reviewed in this study. A conceptual framework of cloud computing adoption based on Extended Technology-Organizational-Environmental (TOE) framework by Tornatzky and Fleischer was proposed. The framework includes individual factors as the theoretical base for cloud computing adoption, to provide an inclusive comprehension on the factors that could affect behavioral intention and use of cloud computing.

AN ANALYSIS OFTHE DIGITAL TOOLS IMPACT ON HR PROCESS WITH SPECIAL REFERENCE TO SARTORIUS

This study examines the impact of digital tools on HR processes at Sartorius, a global leader in biopharmaceutical solutions, focusing on areas such as recruitment, onboarding, training, performance management, and employee retention. By leveraging quantitative surveys and qualitative interviews with HR professionals at Sartorius Nelamangala, the research highlights how tools like applicant tracking systems (ATS), human resource information systems (HRIS), and learning management systems (LMS) enhance operational efficiency, decision-making, and employee engagement. While digital tools streamline processes and foster collaboration, challenges such as technology integration, user adoption, and data privacy remain significant. To analyze the research used a T-TEST as a statistical tool. The study concludes with recommendations to address these issues, including targeted training, robust data security measures, and aligning technology implementation with organizational goals, emphasizing the transformative role of digital tools in driving HR excellence at Sartorius. Keywords: Digital tools, HR process, HR efficiency, Sartorius NelMangala, HR automation, talent management.

Validating IOT and Block Chain Adoption for Home Automation and Block less Solution for Robust Penetration

The motivation behind this comprehensive study is twofold, i.e. validation of UTAUT2 for both potential and actual users of IOT as well as proposing the incorporation of blockchain 3.0 (IOTA) and challenges as novel constructs in UTAUT2. This study helps academicians and practitioners understand the antecedents of IOT adoption and underpins the core areas that need attention to foster adoption. The study incorporates 750 plus responses from both actual and potential users of IOT from the entire Pakistan. Three hundred fifty actual users and 400 plus potential users participated in the study and analyzed using Smart PLS. Performance expectancy, facilitating conditions, price value, and challenges were strong predictors of usage. However, effort expectancy was a strong predictor of actual user adoption, and IOTA was a significant predictor in the case of potential user adoption. The study of the IOT market in Pakistan is pivotal owing to its enormous potential and interest in IOT manufacturers. Our study serves as a useful guide for practitioners in the allocation of marketing budgets and designing of IOT products. This study expands the extant UTAUT2 by incorporating novel variables relevant to the upcoming decade.

Quality of Public Services at PT. PLN (Persero) ULP Marisa

Purpose of this study is to explore aspects of the quality of electricity services through the PLN Mobile application at PT. PLN (Persero) ULP Marisa, which includes the process, SERVQUAL dimensions (Tangibles, Reliability, Responsiveness, Assurance, and Empathy), as well as determinant factors such as personal aspects, leadership, team, system, and situational context. The argument of this study is that the process of improving service quality through the use of the PLN Mobile application can increase customer satisfaction and overall service effectiveness in the ULP Marisa area, Pohuwato Regency. This study uses a descriptive qualitative method through the stages of observation, interviews, documentation, and data analysis. The results of the study indicate that the process aspect in the use of the PLN Mobile application has been attempted, but there are still obstacles in the form of low levels of customer understanding and limited digital literacy. The SERVQUAL dimension shows that tangibles, reliability, responsiveness, assurance, and empathy still need improvement in order to provide services that meet customer expectations. The personal, leadership, and team aspects reveal that collaboration between stakeholders and training to improve personnel competence are essential. The digital-based service system through PLN Mobile shows good potential but requires more intensive socialization to increase user adoption. Customer satisfaction can be increased by strengthening communication strategies and public education regarding the use of the PLN Mobile application. This study concludes that digital transformation through the PLN Mobile application requires strengthening in various aspects to achieve the goals of effective and efficient public services.

Adoption of Mobile Wallets in Nepal: Examining the Influence of Trust and the Mediating Role of Security and Privacy

Purpose: This study investigates the impact of trust on the intention of using mobile financial services, focusing on mobile payment platforms. It also explores how security andprivacy mediates this relationship. Methodology: A quantitative research approach was employed, utilizing a structured questionnaire to collect data from 384 respondents. The data were analyzed using Structural Equation Modeling (SEM) to test the hypothesized relationships between trust, security, privacy, and the intentionto use the mobile payment platform. Findings: The results indicate that trust significantly influences users' intention to adopt the mobile payment platform whereas security and privacy concerns play crucial mediating roles. TheSEM analysis confirmed that the model fit indices were within acceptable ranges, supporting the robustness of the proposed model. Implications: For service providers, enhancing security and privacy features is essential for fostering trust and encouraging user adoption of mobile financial services, and it can be a key driver in the growth of digital finance. Originality/Value: The study contributes to the literature on digital finance by highlighting the intertwined roles of trust, security, and privacy in shaping consumer behavior, offering insights for both academia and industry practitioners.

Analisis Faktor-Faktor yang Mempengaruhi Minat Konsumen dalam Menggunakan Aplikasi Emaal pada Swalayan Basmalah Cabang Ngempit Kraton

This study examines the factors influencing consumer interest in using the Emaal application at Basmalah Supermarket, Ngempit branch. The research employs a descriptive qualitative approach, involving interviews with active users of the Emaal application. The findings reveal that key drivers include perceived usefulness, ease of use, transaction convenience, and transaction security. Consumers value features such as cashless payments, loyalty rewards, and the ability to track transaction histories. However, barriers such as limited consumer awareness, slow application response times, and competition with conventional payment methods also impact adoption. The study underscores the need for strategic marketing, consumer education, and technological optimization to enhance user adoption rates. These insights provide practical guidance for Basmalah in tailoring its digital marketing strategies to the needs of the Ngempit demographic.

Factors Influencing User Adoption of Social Commerce in the Metaverse: The Moderating Role of Technology Comfort, E-Word-of-Mouth, and Endowment Effect

Factors Influencing User Adoption of Social Commerce in the Metaverse: The Moderating Role of Technology Comfort, E-Word-of-Mouth, and Endowment Effect

The effect of trust on user adoption of AI-generated content

PurposeThe purpose of this study is to examine the effect of trust on user adoption of artificial intelligence-generated content (AIGC) based on the stimulus–organism–response.Design/methodology/approachThe authors conducted an online survey in China, which is a highly competitive AI market, and obtained 504 valid responses. Both structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) were used to conduct data analysis.FindingsThe results indicated that perceived intelligence, perceived transparency and knowledge hallucination influence cognitive trust in platform, whereas perceived empathy influences affective trust in platform. Both cognitive trust and affective trust in platform lead to trust in AIGC. Algorithm bias negatively moderates the effect of cognitive trust in platform on trust in AIGC. The fsQCA identified three configurations leading to adoption intention.Research limitations/implicationsThe main limitation is that more factors such as culture need to be included to examine their possible effects on trust. The implication is that generative AI platforms need to improve the intelligence, transparency and empathy, and mitigate knowledge hallucination to engender users’ trust in AIGC and facilitate their adoption.Originality/valueExisting research has mainly used technology adoption theories such as unified theory of acceptance and use of technology to examine AIGC user behaviour and has seldom examined user trust development in the AIGC context. This research tries to fill the gap by disclosing the mechanism underlying AIGC user trust formation.