Adoption Intention Research Articles

Ambiguity aversion and the adoption of no-tillage technology: evidence from a field experiment in China

PurposeThis article aims to study the influence of ambiguity aversion on the adoption of conservation tillage technology by taking no-tillage technology as an example.Design/methodology/approachThis article accurately elicits farmers’ ambiguity aversion in real situations through a field experiment designed with monetary incentives, empirically analyzing the impact of ambiguity aversion on the adoption behavior related to agricultural technology.FindingsAmbiguity aversion significantly reduces the probability of farmers’ adoption of NT technology. Empirical results show that when ambiguity aversion of farmers increases by 1 unit, the probability of adopting NT technology decreases by 2.2%, which corresponds to a 15.3% sample mean. Mechanism analysis indicates that ambiguity aversion obviously hinders farmers’ technology adoption intention and social trust, thereby inhibiting the likelihood of adopting NT technology. The heterogeneity analysis demonstrates that farmers with lower education levels and older age groups are more sensitive to the influence of ambiguity aversion. However, ambiguity aversion has a less pronounced impact on large-scale farmers.Originality/valueThis paper provides two primary contributions. First, different from existing research focusing on agricultural technology adoption under deterministic conditions, this paper presents the research in the context of an uncertain probability distribution, exploring the impact of ambiguity aversion on farmers’ technology adoption. Second, to the best of our knowledge, this paper is the first study to investigate the mechanism through which ambiguity aversion inhibits agricultural technology adoption.

Emotional attachment and resistance to change in the use of technology: A study among Chinese university music teachers.

While technology adoption has received widespread attention in teaching, little research has been conducted on the impact of emotional attachment and resistance to change on technology adoption by teachers, especially in the field of music. This study adopted an extended technology acceptance model to examine music teachers' technology adoption in the context of Chinese university teaching. These results suggest that music teachers in the Chinese universities have positive attitudes toward the use of technology in music education. Their technology using intention was based significantly on the perceived usefulness, their own attitudes toward technology, emotional attachment, and resistance to change. These variables explain 89% of the variance in music teachers' technology adoption intention. Additionally, music teachers' emotional attachment related considerably to the perceived usefulness of technology and resistance to change which proved to be a significant precursor to perceived ease of use. Pedagogical suggestions are provided to improve design thinking and technology adoption for music teachers.

AI Chatbots in Fintech Sector: A Study Towards Technological Convergence

The Fintech industry, particularly banks, has witnessed a profound transformation with the integration of artificial intelligence chatbots, redefining customer experience and engagement. As Fintech firms increasingly integrate AI chatbots into their platforms, understanding customer perceptions becomes paramount for strategic decision-making and sustained success. To unravel the complexities of this convergence, a holistic examination is needed, encompassing not only the technological aspects but also the strategic dimensions that underpin competitive advantage. In this context, the role of intellectual property, particularly patents, emerges as a critical factor shaping the innovation landscape. This study aims to comprehensively investigate customers' perceptions towards AI chatbots in the Fintech industry, with a specific focus on technological convergence. The study seeks to analyze the impact of cuttingedge AI chatbot technologies, including those protected by patents, on user attitudes and overall customer experience within the dynamic fintech landscape. This study provides a comprehensive review of 40 empirical studies on AI chatbots in the fintech industry, particularly the banking sector, featuring patented innovations using the PRISMA methodology. Study outcomes illustrate emerging themes related to consumer behavior and response to financial chatbots in terms of acceptance and adoption intention. Additionally, four key factors that influence how people perceive, anticipate, and engage with fintech chatbots, namely satisfaction, trust, anthropomorphism, and privacy are explored. In conclusion, the finance industry's effective integration and broad use of AI chatbots is dependent on the convergence of four factors: satisfaction, privacy, trust, and anthropomorphism. Current study offers a strong basis for analysing and resolving the obstacles to AI chatbot acceptance and deployment in the financial sector by addressing all these elements extensively. This exploration of technological convergence in fintech industry by analyzing customers' behavior and response to financial chatbots not only contributes to a comprehensive understanding of its intricacies but also serves as a foundation for development and deployment of user-centric fintech chatbots.

Bringing AI into Teaching: Understanding Vietnamese Teachers’ Perspectives and Pedagogical Challenges

Artificial Intelligence (AI) is reshaping education across the Asia-Pacific, yet its integration depends on teachers’ readiness and perspectives. This study explores AI adoption among Vietnamese teachers, a critical lens for the region’s digital education reforms, using the Unified Theory of Acceptance and Use of Technology (UTAUT). Through Structural Equation Modeling (SEM) and Latent Dirichlet Allocation (LDA), we analyzed responses from 246 teachers nationwide. Results show attitude strongly predicts adoption intention, with privacy and ethical concerns shaping acceptance, though fears of AI dependence hinder uptake. Uniform challenges across urban-rural and STEM-non-STEM contexts suggest systemic barriers in Vietnam’s education system. Teachers foresee AI as a pedagogical assistant but highlight insufficient training and privacy risks as key obstacles. These findings underscore the need for Asia-Pacific-relevant policies—AI literacy programs, ethical governance, and equitable access—to foster sustainable integration. This research informs regional educational policy by offering a Vietnam-centric model for balancing technological innovation with pedagogical integrity, addressing shared challenges in the Asia-Pacific’s digital transformation.

Fuzzy Logic-Based Decision Support System for Adoption of Industry 4.0 Predictive Maintenance by Manufacturing Industries

In the context of Industry 4.0, predictive maintenance enhances operational efficiency by optimizing processes, minimizing downtime, and improving cost-effectiveness. However, implementing predictive maintenance requires a systematic approach due to its complexity. This study collected expert input from 15 food and beverage manufacturing industries located in Dar es Salaam, Tanzania, using a purposive sampling technique. Six representatives were selected from each industry, and their opinions were analyzed using MATLAB 7.6 through a fuzzy logic inference system. The analysis focused on key factors influencing Industry 4.0 technology adoption for predictive maintenance, including adoption intention (strategic decision, equipment data, perceived benefit) and perceived usefulness (organizational culture, risk perception, external pressure). The results indicate that when strategic decision-making (technical function) is at 20%, equipment data quality at 15%, and perceived benefit (flexibility) at 25%, the adoption intention of the technology drops to 10%. The fuzzy logic system used techniques such as fuzzification, inference, and aggregation to assess the feasibility of predictive maintenance adoption. The model was validated and refined to ensure accuracy and relevance, offering decision support for maintenance planning and resource allocation. This Fuzzy Logic- Based Decision Support System provides a structured approach to overcoming the complexities of adopting predictive maintenance in Industry 4.0, helping manufacturing industries improve their operational efficiency and competitiveness.

An Empirical Study of AI Financial Advisor Adoption Through Technology Vulnerabilities in the Financial Context

ABSTRACTFinancial institutions are increasingly employing artificial intelligence (AI) solutions to optimize their financial advice and services for consumers. However, consumers have demonstrated reluctance toward adopting AI technology goods, and the intermediary psychological mechanism of adoption intention in the financial service context is unclear. Using the theoretical lens of technology affordances and constraints, this article proposes the concept of consumer technology vulnerability (CTV) as the mediating mechanism in the affordance–adoption process of AI financial advisors (AFAs). Meanwhile, consumer innovativeness and self‐efficacy are investigated as individual traits that moderate perceptions and psychological impacts of AI affordances. Specifically, the study first conceptualizes AI affordances in a product innovation context by reviewing the burgeoning literature on AI to date. This is followed by a US‐based survey (N = 616), which shows the positive indirect effects of information optimization, customizability, and human‐likeness on AFA adoption intention through CTV. Self‐efficacy and consumer innovativeness are found to enhance the positive effects of AI affordances on AFA adoption intention through CTV but diminish the impact of human‐likeness on CTV. These findings highlight, for the first time, the mediating role of CTV in new technology adoption. This will help technology innovators and financial institutions to identify how consumers perceive and adopt different AI affordances, and therefore to better incorporate AI characteristics into financial product innovations.

Retraction notice: 360 VR adoption intention in tourism: approach of protection motivation theory

Retraction notice: 360 VR adoption intention in tourism: approach of protection motivation theory

Fit for the future: Examining the impact of task-technology fit on bank employee intentions to use FinTech

Background: FinTech revolutionizes banking by transforming traditional practices, making it crucial to understand how bank employees adopt these innovations for enhanced operational effectiveness. Aim: This study examines the intention to use FinTech among employees, utilising an integrated task-technology fit (TTF) and technology acceptance model (TAM). Unlike previous studies, it examines the influence of TTF at three levels (underfit, overfit and ideal fit) on TAM and the intention to use FinTech from the perspectives of bank employees. Setting: The research focuses on three major banks in Ethiopia, a developing economy with growing FinTech adoption in the banking sector. Method: The study employed a quantitative research method, gathering data via a questionnaire survey of 213 bank employees in Ethiopia. The analysis was conducted using structural equation modelling via Smart-PLS software. Results: The findings reveal that an ideal fit significantly and positively impacts perceived usefulness, ease of use and intention to adopt FinTech. Underfit negatively influences perceived usefulness, while overfit shows no significant impact on perceived usefulness, ease of use or adoption intention. In addition, perceived usefulness directly and significantly affects the intention to use FinTech. Conclusion: FinTech adoption in banks is optimised when the technology is ideally suited to employees’ tasks. Excessive or insufficient task-technology alignment can hinder FinTech adoption in the emerging economy context. Contribution: The study advances theoretical understanding by integrating TTF and TAM, introducing the concept of varying TTF levels. It also broadens the framework’s application to emerging economies, offering practical insights for optimising FinTech adoption in banking.

Impact Technology Factors on Trust and Intent to Use QRIS

Electronic payment systems have become an important part of modern life, driven by rapid advancements in digital technology. One such innovation is the QRIS (Quick Response Code Indonesian Standard) payment system, developed by Bank Indonesia to simplify and unify various electronic payment services. This study explores the influence of key technological factors in users’ intentions to adopt QRIS, with trust acting as a mediating variable. Using the Technology Acceptance Model (TAM), the research investigates how perceived ease of use, perceived usefulness, and security/privacy affect users’ willingness to adopt QRIS. Trust identified as a critical link between these technological factors and adoption intention. The study aims develop a conceptual framework that highlights trust as a mediator in QRIS adoption. This article provides insights into user experiences, prior studies on QRIS technology, and the implications of its adoption. The findings are intended to help both current and prospective users understand the benefits of QRIS, while emphasizing the importance of building trust to drive wider acceptance.

Determinants of smart contract adoption in supply chains: a UTAUT-based PLS-SEM analysis

Abstract This study explores the factors that influence employees’ intention to use distributed ledger-based smart contracts in supply chains, addressing a gap in current research by applying the Unified Theory of Acceptance and Use of Technology (UTAUT) to this emerging technology within logistics contexts. Based on a quantitative survey of employees in German supply chain companies, the study measured constructs such as performance expectancy, effort expectancy, and social influence. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), the findings reveal that performance expectancy is a key driver of behavioural intention. In contrast, effort expectancy and social influence have no significant impact. Additionally, demographic variables such as gender, age, experience, and voluntariness do not moderate these relationships. These results highlight the central role of perceived performance benefits in shaping adoption intentions. As the first study to apply an adoption framework to smart contract use specifically in supply chains, it offers valuable insights into the socio-technical dynamics of technology acceptance at the employee level. The findings suggest that supply chain managers should focus on communicating and demonstrating performance gains, supporting adoption through pilot implementations, and providing targeted training initiatives to encourage the integration of smart contracts in operational processes.

Intergenerational technology adoption barriers in Indonesian family-owned MSME: A multi-level structural equation modeling analysis

The digital transformation of Micro, Small, and Medium Enterprises (MSME) in Indonesia faces unique challenges in family owned businesses, where intergenerational dynamics significantly influence technology adoption decisions. This study examines how generational differences create barriers to technology adoption in Indonesian family owned MSME using a multilevel structural equation modeling approach. Using a multi-generational dyadic design with 350 family owned MSME representatives from two or more generations (N=700), we investigated the relationships between generational gaps, family harmony, and digital adoption intentions. Data were collected through structured interviews across traditional industries including textiles, food processing, and handicrafts. The results revealed that family harmony significantly mediates the relationship between generational gaps and technology adoption intentions (β=0.42, p<0.001), while communication quality moderates this relationship (β=0.28, p<0.01). Younger generations’ technology advocacy proves more effective when combined with respect for older decision-making authority, suggesting that successful digital transformation requires culturally sensitive approaches that honor traditional family hierarchies while embracing technological innovation. This study contributes a theoretically grounded framework for understanding technology adoption in family businesses within collectivist cultures, offering practical implications for policymakers and business consultants in designing digital transformation programs for MSME.

The Role of Perceived Benefits, Installations, and Government Initiatives in Influencing Solar Energy Adoption Intentions at the Household Level in Jakarta

This study investigates the factors that influence the intention to adopt solar energy at the household level in Jakarta. As urban energy demands increase and environmental concerns intensify, renewable energy technologies, particularly solar power, offer a sustainable alternative. The research primarily focuses on three key drivers: perceived benefits, installation-related aspects, and the role of government initiatives. Using a structured survey questionnaire, data were gathered from residents across various housing areas in Jakarta. The questionnaire assessed respondents’ awareness of renewable energy, perceptions of its advantages, perceived ease or complexity of installation, and the impact of governmental policies or incentives. The results of the analysis indicate that perceived benefits—such as long-term cost savings and environmental advantages—have a strong and statistically significant effect on adoption intentions. Government initiatives, including subsidies, public campaigns, and regulatory support, also play a critical role in shaping household decisions. Installation factors, although slightly less influential, still contribute meaningfully, particularly in terms of ease of access to reliable installation services and associated upfront costs. These findings highlight the importance of a multi-faceted approach to increasing residential solar energy adoption. Specifically, they underscore the need for government efforts to enhance public awareness and provide financial incentives, as well as the importance of ensuring accessible and user-friendly installation processes. The insights from this study can inform energy policymakers, private sector stakeholders, and urban planners in crafting effective strategies that support a greener and more sustainable urban energy landscape in Jakarta.

Value Chain Digitalisation and Adoption Intention by Proactive land Acquisition Strategy (Plans) for Farmers in Nigeria

Value Chain Digitalisation and Adoption Intention by Proactive land Acquisition Strategy (Plans) for Farmers in Nigeria

Understanding Consumers’ Adoption Behavior of Driverless Delivery Vehicles: Insights from the Combined Use of NCA and PLS-SEM

The rapid development of autonomous driving technology has been a key driver for the emergence of driverless delivery vehicles. To promote wider adoption, it is essential to address consumers’ concerns about safety and reliability, leverage psychological factors, and implement supportive policies that encourage technology adoption while ensuring public safety and privacy. Therefore, it is necessary to explain and predict consumers’ behavior and intention to adopt driverless delivery vehicles. To this end, this study extends the Technology Acceptance Model (TAM) to include technological complexity and perceived trust. This study evaluates the model by applying necessary condition analysis (NCA) and partial least squares structural equation modeling (PLS-SEM) to analyze data from 579 respondents from Jiangsu Province, China. This study explores the sustainability implications of autonomous delivery vehicles, highlighting their potential to reduce environmental impact and promote a more sustainable transportation system. The outcomes indicate that perceived ease of use (PEU), attitude, perceived trust, technological complexity (TECOM), and perceived usefulness (PU) are significant determinants and necessary conditions of consumers’ intention to adopt driverless delivery vehicles. Perceived trust and TECOM had a significant and indirect influence on consumers’ intention to adopt driverless delivery vehicles via PU and PEU. Perceived trust and technological complexity had a substantial impact on consumers’ adoption intention of driverless delivery vehicles. The study recommends that managers work closely with regulators to ensure their technologies meet all local standards and regulations. It also recommends its potential to reduce carbon emissions, improve energy efficiency, and contribute to a more sustainable transportation system.

Integration of the Theory of Planned Behavior, Regulatory Pressures, Environmental Awareness, and Economic Perception in Influencing the Intention to Adopt Material Value Conservation Principles

This study investigates the key factors influencing the intention of plastic-based medical device manufacturers in Indonesia to adopt Material Value Conservation (MVC) principles in sustainable product design. Using the Theory of Planned Behavior (TPB) as a foundation, this research integrates environmental awareness, regulatory pressures, knowledge of MVC, perceived ease of adoption, and perceived economic value to develop a comprehensive analytical model. A quantitative survey was conducted with 70 manufacturers located in the Greater Jakarta area, and the data were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The findings indicate that attitude, subjective norms, and perceived behavioral control have a significant direct effect on adoption intention, while regulatory pressure and knowledge of MVC influence intention indirectly through mediating constructs. Although environmental awareness and technical knowledge are high among respondents, perceived economic value remains the most significant barrier due to concerns over initial implementation costs. The study's novelty lies in its empirical extension of TPB within the context of circular economy adoption in the healthcare manufacturing sector. It provides practical implications for policymakers, particularly in low- and middle-income countries, to enhance sustainability through targeted incentives and regulatory frameworks. This research contributes to the academic literature by demonstrating the interaction between psychological, institutional, and economic variables in shaping green manufacturing intentions in an industry with high environmental impact.

Assessing teachers’ readiness and perceived usefulness of AI in education: an Estonian perspective

This study explores teachers’ readiness and perceptions regarding the integration of artificial intelligence (AI) tools in education. The study was conducted among 3,848 Estonian teachers. Given AI’s transformative potential in enhancing teaching effectiveness, automating administrative tasks, and supporting personalized learning, it is critical to assess whether teachers are equipped to effectively utilize these technologies. Utilizing a comprehensive framework informed by human-centered approaches, this research investigates teachers’ familiarity, attitudes, perceived usefulness, and readiness to implement AI-driven tools in educational settings. A survey conducted among teachers reveals a balanced perspective characterized by interest, openness, and awareness of both opportunities and potential risks associated with AI. Findings indicate significant predictive relationships between perceived usefulness and readiness, as well as attitudes toward AI tools and actual adoption intentions. Teachers’ confidence and perceived relevance of AI in educational contexts emerge as key factors facilitating their willingness to engage with AI technology. Conversely, factors such as AI anxiety and limited training opportunities are identified as barriers to effective implementation. The study underscores the need for targeted professional development programs, ethical guidelines, and policy support to enhance teachers’ readiness and facilitate the responsible integration of AI into educational practices.

The Influence of Electronic Word of Mouth (eWOM) on TikTok on Purchase Intention of Azarine Serum Beauty Products at Wahana Kosmetika Indonesia

In the current digital era, consumer perceptions and decisions can be influenced by social media, one of which is TikTok, in the dissemination of information through Electronic Word of Mouth (eWOM) which can influence consumer behavior. This study aims to analyze eWOM on TikTok towards the purchase intention of Azarine serum products using the Information Adoption Model (IAM) approach. This model examines how information quality, information quantity, and information credibility affect the usefulness of information which then has an impact on information adoption and purchase intention. This study was conducted with a quantitative approach, where data was collected by distributing questionnaires to respondents who were TikTok users and had been exposed to Azarine serum content. Data analysis used Structural Equation Modeling (SEM) based on Partial Least Square (PLS) with the help of SmartPLS software. The results showed that information quality did not have a positive and significant effect on the usefulness of information, while information quantity and information credibility had a positive and significant effect on the usefulness of information. Furthermore, the usefulness of information had a positive and significant effect on information adoption and information adoption had a positive and significant effect on purchase intention. These findings emphasize the importance of information characteristics in shaping consumer decisions and can be a reference for companies in designing more effective digital communication strategies on social media.

An interplay among digital transformation, AI adoption and inclusive education

PurposeDigital transformation (DT) seems imperative for higher education institutions (HEIs) to revolutionize traditional teaching and learning approaches. The present study aims to explore the key drivers of DT in higher education. Further, the impact of DT on AI adoption intention and inclusive education among students of Northern India is investigated.Design/methodology/approachTo design and validate the measurement scale for this study, advanced statistical techniques, including exploratory and confirmatory factor analyses alongside other statistical measures, were used using SPSS v.26 and SMART PLS-SEM (sample size – 300).FindingsThe findings reveal that all the factors (facilitating conditions, personal innovativeness, self-efficacy, users’ expectations and AI value creation) except effort expectancy have a significant positive impact on DT. The study corroborates that DT influences AI adoption intention and inclusive education.Practical implicationsBy reorienting the digital transformative journey towards AI-enabled inclusive education, HEIs can contribute immensely to the broader agenda of Sustainable Development Goals (SDGs), particularly those related to quality education, innovation and equality.Originality/valueThe present study is a novel attempt to comprehensively examine the diverse antecedents of DT and its impact on AI adoption and inclusive education and imparts deep insights on strategic management practices in higher education.

Corrigendum

Ho Ngoc Ninh, Mai Tien Huy, Lai Phuong Thao, Nguyen Tat Thang "ICT Adoption Intention Among Household-owned Tourism Businesses in the Era of Digital Transformation", 2025.https://doi.org/10.3311/PPso.40399When the above article was first published online some minor mistakes on page 6, Table 3 on page 8 remained. This has now been corrected in the online version. The correct version of page 6 and Table 3 is published in this paper.

Revolutionizing Digital Banking: Understanding Determinants and Barriers of Neo‐Banking Adoption Through the Lens of Behavioral Reasoning Theory

ABSTRACTThis study applies behavioral reasoning theory (BRT) to investigate the enablers and barriers to neo‐banking adoption. It offers nuanced insights into the factors that influence consumers' acceptance or rejection of this transformative financial services model. By employing a robust methodological approach, this research amalgamates the analytical power of PLS‐SEM (partial least squares structural equation modeling) and fsQCA (fuzzy‐set qualitative comparative analysis) approaches to explore the pathways of proposed effects and examine causal asymmetry. The data for this study were obtained by administering an online survey questionnaire to a sample of 546 digital banking customers. The study's findings indicate that adoption intentions are strongly influenced by the accessibility of neobanks and the cost savings associated with their services. Conversely, perceived security is also found to be an essential factor that shapes the attitude of Indian customers toward adopting neo‐banking. Findings also reveal the moderating role of self‐efficacy and trust in the link between reasons, attitude, and intention to adopt. The fsQCA results reinforce the PLS‐SEM findings and indicate four configurations leading to the high adoption of neo‐banking. The study provides strategic insights to refine marketing approaches and operational frameworks for neo‐banking, accelerating its growth in emerging economies.