Technology Adoption Intention Research Articles

Trust and Religiosity: Integrating Technological Acceptance Factors into the Extended Unified Theory of Acceptance and Use of Technology (UTAUT) Model for Zakat Online Payment Systems

The aim of this study is to examine the adoption of digital zakat payment platforms among micro-entrepreneurs, incorporating trust and religiosity into the Unified Theory of Acceptance and Use of Technology (UTAUT) model. This research extends the traditional UTAUT framework by integrating trust and religiosity as additional determinants of technology adoption intention, alongside the model's core constructs of performance expectancy and social influence. Primary data for this study was gathered through a digital survey disseminated to 110 micro-entrepreneurs in the state of Kedah, all of whom are actively registered with the Malaysian Company Commission (SSM), under the auspices of the Ministry of Domestic Trade, Cooperatives, and Consumerism (KPDNKK). The methodological approach is rooted in structural equation modelling, which facilitates a rigorous empirical analysis of the relationships between technological constructs and user intention. The results reveal that trust and performance expectancy, along with social influence, significantly impact micro-entrepreneurs’ intentions to engage with online zakat payment systems. Interestingly, despite the religious nature of zakat, religiosity did not emerge as a significant predictor in the context of this digital payment adoption. This insight suggests that while religious obligation drives the act of zakat itself, it is the technological aspects of trust and anticipated performance that influence the preference for digital payment methods over traditional ones. This research provides valuable implications for zakat institutions and policymakers aiming to foster the digitalization of religious financial transactions. By highlighting key factors that influence digital adoption, the study underscores the potential for zakat management bodies to innovate and promote digital solutions that align with micro-entrepreneurs' expectations and trust requirements. Ultimately, this study charts a path forward for enhancing digital inclusivity in religious financial practices, marking a transition from conventional to modern, technology-enabled means of fulfilling zakat obligations.

Adoption Intention of Blockchain Technologies for Sustainable Supply Chain Management in Indian MSMEs

This study explores the determinants of the intention to adopt blockchain technology for sustainable supply chain management in Indian micro, small, and medium enterprises. Different from existing studies that advocate the use of socio-technical theory for blockchain technologies, we develop a new theoretical framework, called “SOS,” based on a review of the existing literature. This is an adaptation of the technology–organization–environment framework that examines the measures and scales from socio-technical, organizational, and sustainability contexts. We use ADANCO 2.3.2 for variance-based structural equation modeling. The results show that two of the nine hypotheses are negatively significant, while the rest are positive. In our context, social sustainability and computer self-efficacy are strongly negatively significant for the adoption intention of blockchain technology in our context. Software quality and environmental sustainability are strongly positively significant. Meanwhile, collaboration, economic sustainability, and relative advantage mediated by experience are positively significant. Our study contributes to the literature by offering a new theoretical framework, fresh insights from the Indian industry, and several recommendations to practitioners.

Effects of managers' environmental consciousness and digital expertise on their technology adoption intentions

Environmental consciousness and digital competence are sought-after characteristics of managers by many organisations today. The digital expertise of organisations is considered a critical capability that drives their digitalisation strategies. Also, values and beliefs towards environmental sustainability influence their attitudes towards achieving environmental performance. By integrating the three 'big' adoption theories of DoI, TAM and UTAUT, along with decision-making literature, this study empirically investigates the effects of the digital expertise and environmental consciousness of managers on their intention to adopt Industry 4.0 technologies. We used an online survey with 172 managers from Australian firms using the PLS-SEM method for data analysis. The results show that managers’ environmental consciousness and digital expertise significantly and positively affect their intention to adopt Industry 4.0 technologies. Their perceived usefulness of technologies partially mediates the relationships between digital expertise and intention to adopt and between environmental consciousness and intention to adopt. The mediation roles of perceived ease of use, perceived visibility and social influence were not empirically confirmed. Integrating adoption theories with domain-specific knowledge-based decision-making is a novel theoretical approach adopted in the study. The key contribution is to the Industry 4.0 technology adoption literature by empirically confirming the effects of domain-specific knowledge expertise and environmental consciousness on the intention to adopt. Its practical implications lie in the confirmation that organisations benefit from their investment in the digital skill development of managers and environmentally conscious managers.

Based on the S–O–R theory adoption intention of blockchain technology in libraries: a two-stage analysis SEM–PLS and ANN

PurposeBlockchain, a groundbreaking technology that recently surfaced, is under thorough scrutiny due to its prospective utility across different sectors. This research aims to delve into and assess the cognitive elements that impact the integration of blockchain technology (BT) within library environments.Design/methodology/approachUtilizing the Stimulus–Organism–Response (SOR) theory, this research aims to facilitate the implementation of BT within academic institution libraries and provide valuable insights for managerial decision-making. A two-staged deep learning structural equation modelling artificial neural network (ANN) analysis was conducted on 583 computer experts affiliated with academic institutions across various countries to gather relevant information.FindingsThe research model can correspondingly expound 71% and 60% of the variance in trust and adoption intention of BT in libraries, where ANN results indicate that perceived possession is the primary predictor, with a technical capability factor that has a normalized significance of 84%. The study successfully identified the relationship of each variable of our conceptual model.Originality/valueUnlike the SOR theory framework that uses a linear model and theoretically assumes that all relationships are significant, to the best of the authors’ knowledge, it is the first study to validate ANN and SEM in a library context successfully. The results of the two-step PLS–SEM and ANN technique demonstrate that the usage of ANN validates the PLS–SEM analysis. ANN can represent complicated linear and nonlinear connections with higher prediction accuracy than SEM approaches. Also, an importance-performance Map analysis of the PLS–SEM data offers a more detailed insight into each factor's significance and performance.

Conceptual framework to explore artificial intelligence technology (AIT) readiness and adoption intention in records and information management (RIM) practices: a proposal

Conceptual framework to explore artificial intelligence technology (AIT) readiness and adoption intention in records and information management (RIM) practices: a proposal

Immersive escapes: examining the impact of personality traits, perceived enjoyment, flow and trust on virtual reality technology adoption intentions in an emerging market

Immersive escapes: examining the impact of personality traits, perceived enjoyment, flow and trust on virtual reality technology adoption intentions in an emerging market

Investigating the intention and behavior of vegetable farmers to adopt IoT technology: survey—based evidence from China

A key instrument for upgrading China’s agriculture is the Internet of Things (IoT). To solve the problem of IoT technology promotion, farmers’ intentions to adopt IoT technology must be transformed into behavior, and their intentions and behaviors must be unified. The multivariate logistic model was used to analyses the factors influencing farmers’ intention to adopt IoT technology and behavioral deviation based on survey data of vegetable farmers in Jiangxi Province. The ISM model was used to investigate the relationship and hierarchy between the factors influencing farmers’ intention to adopt IoT technology and behavioral deviation. The findings revealed that first, a significant deviation exists between vegetable farmers’ IoT technology adoption intention and behavior, with 72.69% of those surveyed having the intention to adopt, but did not follow through. Second, among the 12 factors confirmed as remarkably influencing the deviation, expected return is the most superficial factor; intermediate influencing factors include vegetable price volatility, adoption cost, credit support, related knowledge and skills, and technology maturity; secondary factors include social capital, whether vegetables are registered trademarks, planting scale, planting method, and IoT related equipment supply; and age is the deepest root factor.

Role of perceived risks and perceived benefits on consumers behavioural intention to use Buy-Now, Pay-Later (BNPL) services

Purpose Perceived risk and benefits have been proposed as crucial elements in consumers’ technology adoption intention. Therefore, this study aims to use the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, with perceived risks and benefits, to explore how they affect consumers’ Buy-Now-Pay-Later (BNPL) behavioural intention. Design/methodology/approach An online survey was conducted among 537 users of BNPL. Partial least square structural equation modelling analysis was performed to examine the hypothesized relationships. Findings The study found that perceived benefits, performance expectancy, effort expectancy, habit and social influence increase consumers’ behavioural intention towards BNPL. In contrast, perceived risk reduces the consumer’s intention to use. Additionally, the study revealed that consumers’ intention towards BNPL services positively affects their usage. Practical implications The lack of information makes consumers hesitant to use BNPL. Therefore, marketers should optimize facilitating conditions, such as user-friendly interfaces, accessible resources and efficient customer support, which should be the business strategy of BNPL service providers to ensure a seamless user experience. Originality/value The research empirically investigates the effect of perceived benefits on consumer behavioural intention. This contribution is crucial because while there was speculation about benefits as a driving force to consumers’ adoption intention, there was a lack of sufficient empirical evidence to support it.

Adoption intention of blockchain technology among women entrepreneurs

Adoption intention of blockchain technology among women entrepreneurs

Ability first or opportunity first in the m-health era? A hybrid SEM-ANN approach

PurposeThe purpose of this study is to propose and test a model to explain users’ intention to adopt m-health devices and divide the importance of antecedents for users to adopt m-health devices based on the stimulus-organism-response (S-O-R) framework.Design/methodology/approachThis research conducted an online survey with m-health app users and collected 562 valid responses. A hybrid SEM-ANN approach was employed to evaluate the research model and hypotheses.FindingsThe results show that motivation (M), opportunity (O), and ability (A) affect users’ flow experience and loyalty and further affect their adoption intention of m-health technology. Opportunity plays a more critical role in m-health adoption intention than ability.Originality/valueThis study comprehensively examined the factors that affect users’ deep engagement and m-health adoption from the perspective of MOA. It used the hybrid SEM-ANN method to divide the critical role of motivation, opportunity and ability, providing a new analysis approach for studying information technology (IT) behavior.

Developing a Model of Actual Adoption Technology and Innovation for Health in Thailand

The medical hub industry is one of the industries that use new technologies and innovations as a mechanism to drive the economy in the future. With advances in technology, innovation, and personalized health, it plays an important role in supporting health care and livelihoods. Health promotion, prevention and treatment of disease, and physical rehabilitation are necessary to ensure good health and safety in life. The objective of this study is to develop a causal relationship model of the actual adoption of technology and innovation for health in Thailand and to check the consistency of the causal relationship. The research data was collected by an online questionnaire from 800 people who had used technology and innovation for health while living in Thailand from a simple sampling using a causal relationship model and a structural equation (SEM). This research has noted relationships between health belief, ease of use, credibility, consumer innovation, perceived usefulness, and attitude toward use that have a direct positive correlation with the adoption intention and actual adoption of technology and innovation. Additionally, the results also reveal that perceived credibility is one of the most important predictors of the intention to actually adopt healthcare technology and innovation. 
 
 Received: 17 May 2023 / Accepted: 26 July 2023 / Published: 5 September 2023

Two Decades of M-Commerce Consumer Research: A Bibliometric Analysis Using R Biblioshiny

The aim of this study is to consolidate the state of mobile commerce consumer research from 2001 to 2022. Based on a systematic literature review employing a bibliometric technique, this study not only reports the significant contributions of authors and their affiliations but also discusses the evolution of m-commerce research over the last two decades. Examination of annual production trends revealed that publications were on the rise all along; the year 2022 clocked the highest number of publications (53 documents), which further reinforces that the research on this domain is in its blooming season. China is the most contributing country in terms of the number of publications and citations received, followed by the USA. The author Keng-Boon Ooi has been the most productive researcher; his studies continue to be the foundation on which m-commerce consumer research continues to thrive. The analysis of scientific mapping revealed that, although many studies were carried out on mobile commerce adoption intention, the focus of the researchers lately shifted towards studying continuous use intention (since 2018). Further, it was observed that the base theory, the Technology Acceptance Model, which has been widely used for determining antecedents of technology adoption intention, is losing its significance and is being overtly replaced by the Unified Theory of Acceptance and Use of Technology. While the topics “trust, loyalty, satisfaction, mobile banking, UTAUT, continuance intention, perceived enjoyment, and COVID-19” were identified as mother (engine) themes, the keywords “privacy, self-efficacy, social influence, TAM, attitude, and intention to use” became diminishing themes. The following topics have been identified as emerging themes: “Mobile social commerce, Mobile payment, Mobile marketing, Omnichannel, Fintech, and Live streaming commerce”. This study provides useful insights to potential researchers.

Research on the Adoption Behavior Mechanism of BIM from the Perspective of Owners: An Integrated Model of TPB and TAM

How to expand an owner’s market demand for BIM and fundamentally mobilize an owner’s application enthusiasm is of great significance to the high-quality development and effective promotion of BIM. Taking the Theory of Planned Behavior (TPB) as the basic framework and integrating the Technology Acceptance Model (TAM), we build a theoretical model of an owner’s adoption behavior mechanism for BIM technology. The theoretical model is tested by the partial least squares structural equation model (PLS-SEM). The research results show that the perceived usefulness of BIM technology by an owner is the most significant factor that affects the owner’s behavioral intention to apply BIM technology. The influence of attitude on behavioral intention is very weak and not significant. Subjective norms can significantly and positively affect an owner’s adoption intention. The perceived ease of use has a positive impact on the adoption intention of BIM technology, but its role is very limited. The adoption intention of an owner can positively affect adoption behavior and has a direct driving effect. The research results can improve the relevant research on BIM, encourage an owner to actively participate in the development process of BIM, and further promote the comprehensive promotion and application of BIM.

An Inferential Statistical Analysis of the Key Factors Influencing the Adoption of New Technology by MEEC (MICE) Organizers in Thailand

Purpose: The aim of this study is to examine the adoption of new technology within the Meetings, Exhibitions and Conventions sector in Thailand. Theoretical framework: An adapted version of the diffusion of innovation theory combined with variables from the Technology Acceptance Model (TAM) is used to define the key variables upon which data is gathered. Design/methodology/approach: The study reviews the MEEC/MICE sector in Thailand and its importance, the existing level of the adoption of new technology and the government plan to encourage further adoption. An online survey of 302 MEEC/MICE Organizers is analysed using stepwise Multiple Linear regression to estimate the attitude of the organizers toward new technology and which factors have the greatest influence on their intention to adopt new technology further. Findings: The results indicate that 85% of the study participants are currently adopting MEEC/MICE technological innovation in one way or another, and 99.6% are of the opinion that they will adopt it in the future. The study also indicates that the business environment, of which government policy is a major factor, can have an influence on both the attitude and the adoption intention of technology, but that their own attitude to technology is the factor with most weight and that the respondent’s attitude to new technology is mostly influenced by their employees’ capability. Research, Practical & Social implications: The Thai government is attempting to change the Thai economy from a manufacturing economy to a high value advanced economy. The further adoption of new technology in this important sector is a vital part of this attempt. Originality/value: The study is the first study in Thailand to use inferential statistical analsyis to estimate the most important factors determining MEEC/MICE operators’ adoption of new technology.

Investigating blockchain technology adoption intention model in halal food small and medium enterprises: moderating role of supply chain integration

ABSTRACT Blockchain infrastructures’ promising benefits and tremendous growth revolutionised supply chain; especially for the highly concerned industry with integrity issues such as halal food. Drawing on the technology, organisation, environment framework and diffusion of innovation theory, this study investigates the factors that affect halal food SMEs (HFSMEs). The questionnaires covering 500 halal-certified SMEs were conducted in Malaysia. The results showed that the theory of diffusion of innovation (DOI) and technological-organisational-environmental (TOE) model was tested with 175 respondents, showing top management support, trialability, external support, and competitive pressure are the critical factors influencing HFSMEs’ intention to adopt BT. In contrast, relative advantage, compatibility, complexity, uncertainty and security, observability, organisational readiness, and government regulations show no effect on intention. In addition, supply chain integration (SCI) is a moderating factor in diffusing BT.

The Impacts of Role Overload and Role Conflict on Physicians’ Technology Adoption

Technology adoption is an important solution for physicians to increase work efficiency, and thus deal with role conflict among their multiple job roles. Prior studies have not investigated how multiple job roles and role conflict influence physicians’ technology adoption intentions. Based on role strain theory and role identity theory, we present a model of physicians’ technology adoption intentions to support their primary (clinical care) versus secondary (teaching or research) job roles. We test the model using surveys with 156 physicians at nine medical schools in Korea. The results of our data analysis largely support our hypotheses. Role overload in each of their job roles increases role conflict between any pair of associated roles. Furthermore, role conflict between a physician’s primary and secondary role is affected more by role overload in the secondary role than by overload in the primary role. Moreover, the impact of role conflict on technology adoption intentions is also influenced by the hierarchical relationship between two roles. This study contributes to technology adoption research by demonstrating how physicians’ job characteristics affect technology adoption.

Impact of Digital Platform Organization on Reducing Green Production Risk to Tackle COVID-19: Evidence from Farmers in Jiangsu China

The agricultural organization based on digital platforms in C2F (Company–Platform–Farmers) may be an effective way to reduce the increased risk of green production caused by the COVID-19 pandemic, but the specific mechanism and impact involved are unclear. Applying risk cognition and decision theory, we built the theoretical framework on platform organization, pandemic risk, perception value, and green production continuity, and ascertained the impact effects and path using the PLS-SEM method. We found that the risk of COVID-19 overflow had a significant impact on farmers’ green production continuity by mediating perception value, especially regarding reduced green technology adoption intention and increased cost of living. Utilizing perfect platform value cognition, participation co-operation, access and benefit distribution, and safeguard and restraint measures of platform organization in C2F, we offered a new approach to reduce the green production risks caused by COVID-19, such as material and labor shortages, financial pressure, sales channel blockages, and price volatility. We explained the behavior-moderating motivation of farmers with different risk preferences and subjective norms in relation to tackling COVID-19. We should aim to perfect the functions of digital platform organizations to optimize the benefit linkages in C2F, accelerate farmers’ digitization ability cultivation to increase the cognitive risk level, and strengthen the policy guidance of COVID-19 prevention to reduce the influence of farmers’ subjective norms.

Technology Adoption and Promotion in the Age of Skepticism: Examining COVID-19 Mitigation through Technological and Human Factors

Expanding the theoretical framework of technology adoption and promotion, this study examined multi-domain predictors of the intention to adopt COVID-19-related mobile technology: technological (user-friendliness and privacy concern), human (relational and cultural), and situational (problem recognition, involvement recognition, and constraint recognition about the pandemic itself). An online survey (N = 745) of residents in a Southern U.S. city was conducted and analyzed using hierarchical ordinary least squares (OLS) regressions. Results showed that technology adoption intention was negatively related to privacy concern and positively related to trust in government. However, neither user-friendliness nor the cultural values of conformity and self-direction played a significant role. While interdependent self-construal was positively related to adoption intention, independent self-construal was not a significant predictor. Regarding situational perceptions, problem recognition and constraint recognition significantly predicted adoption intention, whereas involvement recognition did not. Theoretically, the study advances technology promotion literature by identifying multiple domains of barriers. Practically, it provides implications for promoting mobile technology in public health crises.

An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach

It has been a decade since the first extensive study on the internet's adoption and use was conducted. Circumstances have changed in the last decade internet has become an essential need for every human being. Socio-psychological, economic, and personal factors play a significant role in shaping human behaviour. But their role in shaping consumer behaviour toward 5G is still unexplored. In order to determine the impact of socio-psychological elements on 5G technology adoption intention, the study integrated curiosity, perceived value, functional value, and environmental awareness into UTAUT2 and analyzed how they interact. Instead of relying on linear models, this study employed a dual-stage SEM-ANN approach because customers' decision-making process to adopt new technology is complex. Valid responses from 840 respondents were collected, investigated, and ranked using the deep learning ANN approach. All predictors were found statistically significant except social influence. ANN sensitivity analysis revealed that newly integrated predictors (environmental awareness, curiosity) are surprisingly the most important predictors, followed by facilitating conditions and perceived satisfaction. SEM-ANN hybrid two-step deep learning approach explained 83.6% variance higher than the baseline model (UTAUT2). The study improved UTAUT2 by adding new variables and expanding its canvas to predict user technology adoption. This will show how consumers react to 5G services and help telecoms grow into new markets.

Challenges affecting bank consumers’ intention to adopt green banking technology in the UAE: a UTAUT-based mixed-methods approach

PurposeSustainability has become a global need for survival in every field since the side effects of financial development have resulted in environmental devastation. Green banking (GB) has been proposed as a way to reduce the carbon footprint caused by banking operations by promoting paperless financial services through the intensive use of technology. However, the adoption level of GB technology remains unsatisfactory among customers in the United Arab Emirates (UAE). Therefore, using the unified theory of acceptance and use of technology (UTAUT), this study aims to comprehensively investigate the challenges affecting the intention of bank consumers in the UAE to adopt GB technology.Design/methodology/approachThis study used exploratory sequential mixed-methods research. Preliminary semi-structured interviews were conducted with ten banking professionals using a purposive sampling technique to explore the challenges affecting consumers’ intention to adopt GB technology. Sequentially, the study tested various factors through a quantitative cross-sectional online survey of a sample of 332 bank customers and used the convenience sampling technique to obtain further empirical support for the research framework. Thematic content analysis using NVivo 11 was used for the qualitative data analysis. Meanwhile, partial least square structural equation modelling in Smart PLS 3.3 was used for the quantitative data analysis.FindingsThe qualitative analysis identified six new challenges affecting customers’ intention to adopt GB technology, including customer awareness, personal innovativeness, bank reputation, security and privacy, system quality and government support. The preliminary qualitative findings were confirmed mainly through quantitative data analysis, whereby customer awareness, personal innovativeness, system quality and bank reputation were found to significantly impact customers’ intention to adopt GB technology. However, the effects of security and privacy and government support were insignificant.Originality/valueTo the best of the authors’ knowledge, this study is the first to propose a comprehensive model that considers individual, technological, organisational and environmental factors to address the issue of customers’ low GB technology adoption rates in the UAE. Meanwhile, this study extends the UTAUT by integrating new factors. This paper is also among the first to investigate customers’ GB technology adoption intention using a mixed-methods approach, which combines the strengths of quantitative and qualitative methods within the same study to offer better insights than a single-method approach.