Technology Adoption Model Research Articles

Effects of Technical Capacity on Utilization of Information Systems in County Governments in Kenya

The purpose of this study is to examine the impact of staff technical capacity on utilization of information systems in revenue management in county governments in Kenya. This study employed a Technology Adoption Model to describe the motivating factors behind adoption of new technology and how human actions are guided on the same. Descriptive research design was carried out at the County Government of Nakuru offices. The questionnaires were distributed among 351 staff in Revenue Management by means of stratified random sampling technique. Correlation and regression analysis were used to test the direct and indirect effects of the staff technical capacity on utilization of information systems in revenue management. The findings of this research shows that staff technical capacity has a positive impact on the utilization of management information systems in revenue management.

A General-Equilibrium Model of Labor-Saving Technology Adoption: Theory and Evidences from Robotic Milking Systems in Idaho

Automatic milking systems (AMSs) have become increasingly common in the US in the past few years. Recent surveys from Idaho, one of the largest dairy-producing states, as well as from other states and countries, suggest that: 1. among farms adopting robotic milking systems, few are reporting less labor usage after adopting this labor-saving technology; 2. small farms rather than large farms are adopting (or more interested in adopting) robotic milking systems. In this article, we propose a series of new modeling strategies, which introduces the role of general-equilibrium effects to explain these new stylized facts. We show that: first, farms adopting labor-saving technology may, in fact, use more labor to compensate for the loss in the value of labor; second, when smaller farms experience more labor efficiency gains or value their leisure time (or off-farm income) more, they are more likely than larger farms to adopt the new technology. We contribute to the technology-adoption literature in two important ways. First, to our knowledge, this is the first article that introduces general-equilibrium effects to the technology-adoption literature. Second, this is also the first article that provides a theoretical perspective to explain the stylized facts in the adoption of robotic milking systems.

Developing a Validated Instrument to Measure Students' Active Learning and Actual Use of Information and Communication Technologies for Learning in Saudi Arabia's Higher Education.

Higher education authorities have supplied information and communication technologies (ICTs) to guarantee that students use ICT to improve their learning and research outputs. ICT, on the other hand, has been proven to be underused, particularly by students. Therefore, we aimed to develop a new model to measure students’ active learning and actual use of ICT in higher education. To investigate this issue, the technology acceptance model and constructivism learning theory were verified and applied to evaluate university students’ use of ICT for active learning purposes. The participants in the study were 317 postgraduate and undergraduate students from four faculties at King Faisal University who consented to take part. The research data were analyzed using structural equation modeling (AMOS-SEM). Three specific components were used: the technology adoption model, constructivism learning, and active learning using ICT. The findings revealed that: (a) using ICTs for students’ interactivity, engagement, expected effort, subjective norm, and perceived ease of use has a direct positive impact on perceived enjoyment and usefulness; (b) perceived enjoyment and usefulness has a direct positive impact on active learning, attitude toward use, and behavioral intention to use ICTs; (c) active learning has a direct positive impact on attitude toward use, behavioral intention to use ICTs; and (d) active learning has a direct positive impact on attitude. Moreover, the results showed the mediator factors’ values positively “R square,” active learning (0.529), attitude toward use (0.572), behavioral intention to use (0.583), and actual ICT use (0.512) in higher education. Therefore, the results of the hypotheses developed a validated instrument to measure students’ active learning and actual use of ICTs in higher education in Saudi Arabia.

Developing a human-organization-technology fit model for information technology adoption in organizations

Some information technologies (ITs) are better adopted than others and even the same IT may be adopted differently even in similar organizations. Existing old-fashioned theories which focused on one or several of technical, managerial, personnel factors cannot fully explain the phenomenon. This paper proposes human-organization-technology (HOT) fit as an overarching concept to explain the IT adoption heterogeneity in organizational technology management. The HOT fit model includes the characteristics and bi-party relationships of the human, organization, and technology dimensions. The model can be further used to holistically evaluate the HOT fit, diagnose the HOT configuration, and strategize organization adaptation directions iteratively. It provides a genuine theoretical perspective to investigate IT adoption in society.

Effect of Cashless Management on Revenue Collection Efficiency: A Case of Kisumu County Government, Kenya

The purpose of this study was to investigate the effect of cashless management on revenue collection efficiency: A case of Kisumu County Government. The study aimed at determining the level of electronic point of sale on efficiency of revenue collection. Whether electronic point of sale enhanced easy payment of revenues and improved the revenue collection in the County, whether it enhanced transparency in service delivery. Revenue collection is a fundamental constituent of fiscal policy and administration in any economy. County Governments in Kenya experience a myriad of financial challenges, key among them being low revenues. The budget director's audit reports for fiscal years 2016/2017 and 2017/2018 showed that Kisumu County's revenue was significantly lower than target, especially due to revenue leakage. In addition, in the 2018/2019, its internal revenues fell below the budgeted figure for the same financial year. To counter these losses, the County Government embarked on a cashless payment system in revenue collection. This was to be achieved by computerizing the tax collection system from the Local Authority's Integrated Financial Operations Management System (LAIFORM) to the integrated Financial Management Information System (FMIS). The overall goal was to explore the impact of the cashless payment system and management on the efficiency of tax collection in Kisumu County. The research adopted Technology Adoption Model theory by Davis (1986) and Planned behavior theory by Ajzen (1991). A case study research design which is an intensive description and a holistic analysis of a bounded case was adopted. The study targeted all the 200 staff members from revenue departments at Kisumu County and sampled 60. Stratified sampling technique was utilized. The research utilized secondary and primary data. The primary data was acquired through opened and closed-ended questionnaires distributed among the sampled staff while secondary data was obtained from the County revenue Office financial records. The collected data were analyzed using descriptive statistics and inferential statistics. Descriptive statistics involved the use of mean, mode, standard deviation, frequency, and percentage. Pearson's correlation and ANOVA were utilized to show the relationship between the independent variable (cash management) and the dependent variable (efficiency in revenue collection). The qualitative data from the open-ended questionnaire were analyzed according to the goal setting theme and was presented in the form of tables, charts and graphs. The study findings revealed that use of electronic point of sale enhances easy payment of revenues, improved and increased efficiency of the revenue collection in the County and enhanced transparency in service delivery for customs authority. The study recommended it is essential to create awareness of the existence of the system, how it works, and its benefits among taxpayers to enhance its use and raise compliance level.

To download or not to download? Spatial and temporal neural dynamics across the brain regions when deciding to download an app

Technology adoption is one of the most important research streams in the field of IS. However, it has largely been studied with endpoint models rather than process models. In this research, we attempt to develop a process model for technology adoption using fMRI (functional Magnetic Resonance Imaging) techniques. fMRI techniques allow us to directly investigate the cognitive process of technology adoption instead of using mental representations such as perceived usefulness and perceived ease of use. We measure the brain activities of 22 students from a major western US university while they are making the decision to download or not download apps using a novel temporal neural correlate analysis. The research finds that the download decision is a complex process that includes the visual regions of the brain, the anterior cingulate cortex, the middle temporal gyrus and many other regions. The practical implication is that there are many points of intervention to influence the download decision. In particular, the visual features of app presentation seem to be a very important consideration.

Extended contextual validation of stakeholder approach to firm technology adoption: moderating and mediating relationships in an innovation eco-system

PurposeThe need for context-specific adoption models led to the development of the firm technology adoption model (F-TAM) model. Among small to medium-scale enterprises (SMEs); however, firm-level factors were rather insignificant in engendering SME level adoption of technological innovation. This study aims to examine the effect of firm size and other moderating and mediating factors on the relationships between personal, firm, societal and technological factors proposed in the stakeholder-oriented F-TAM among SMEs.Design/methodology/approachA research instrument was developed, reviewed by experts, and pilot tested with a sample of 25 respondents. Data were purposively collected from four hundred (400) SMEs and analyzed with partial least squares structural equation modeling (PLS-SEM).FindingsThe study discovered that employees, societal and technological factors moderate the relationship between firm factors of adoption and firm adoption. Without these moderating effects, firm factors of adoption would have been insignificant at the SMEs’ level of organizational technology adoption. The study further discovered that firm size, as well as risk propensity, also affect the relationships proposed in the model.Research limitations/implicationsData was collected on voluntary adoption from the most cosmopolitan area of a developing country. It, therefore, needs further contextual validation across the country and different countries.Practical implicationsThe engagement of innovations in firms must be planned with employees and society as major stakeholders.Originality/valueThe significance of this finding is the study’s emphasis on an eco-system approach for examining the phenomenon of innovation adoption. To the best of the authors’ knowledge, this study is the first to examine the effect of firm characteristics on is proposed eco-system of stakeholders.

Combining Deep Neural Network and PLS-SEM to Predict Patients’ Continuity with Telemedicine

This study aims to adapt the Expectation Disconfirmation Theory and Technology Adoption Model to unveil provocative roles in patients’ satisfaction cognitions and subsequent continuity behaviors pertaining to telemedicine services in rural Bangladesh. A quantitative research model is developed and validated using a two-staged deep neural network and partial least squares structural equation modeling approach. The findings of this study provide evidence that five salient determinants; expectations, disconfirmation, performance, usefulness, and ease of use dominantly contribute to predicting patients’ satisfaction concerning continuity with telemedicine. This contributes to health informatics and behavioral literature by clarifying the complex interplay between patients’ satisfaction and determinants of continuity behavior in telemedicine’s domain. The findings provide novel insights into predictions of complex patients’ attitudes toward telemedicine continuity, and dynamic changes in adoption trends thereby assisting health professionals, global health experts, policymakers, and IS community in making higher quality informed decisions for people-centered future models of care.

What influences patients' continuance intention to use AI-powered service robots at hospitals? The role of individual characteristics

AI-powered service robots have gradually developed into popular self-service agents in the health care industry. Though prior research has investigated what affects individuals' adoption of AI-powered service robots in the service industry, few have considered patients' continuance intention for AI-powered service robots at hospitals from the perspective of patients' characteristics. Drawing on the Technology Adoption Model and individual characteristics (i.e., trust in technology and independent personality), we develop a framework testing the factors influencing patients' continuance intention (CI) for AI-powered service robots at hospitals with Intelligent Guide Robots as an example. The model is validated using PLS-SEM analysis and data from 543 patients of a 3-A hospital in Eastern China. The study finds that patients' trust in AI techniques and independent personality positively influence their perception of usefulness (PU), ease-of-use (PEOU), and enjoyment (PE), respectively. Moreover, PU, PEOU, and PE are significant predictors of CI toward AI-powered service robots. PEOU and PE partially mediate the relationship between trust/independent personality and CI. The findings imply that organizations in the healthcare could try their best to increase users' trustworthiness toward AI techniques. In addition, developers could continuously upgrade AI-powered service robots to improve patients’ PE and PEOU.

The Influences of Marketing Activities and Personal Competence on the Intention to Adopt Digital Banking

Purpose: This study discusses the relationship between variables on bank customers' adoption of digital banking. Comprehensively, this study aims to determine the customer's interest in using Digital Banking based on the Technology Adoption Model (TAM) theory with Bank Marketing Activities (BMA) and Bank's Personal Competence (BPC) variables.
 Methods: This study uses a quantitative approach with 271 respondents. The analysis technique in this study is the Structural Equation Model (SEM) using the IBM AMOS 26 program.
 Results: The results of this study found three main results. First, BMA and BPC can increase interest in using digital banking if only by creating factors of perceived ease of use and perceived usefulness in the minds of customers. Perceived ease of use will arise if the bank's digital application has clear instructions and does not cause a burden during use. Meanwhile, perceived usefulness will occur if digital applications can improve performance and accelerate customer work. Second, BPC is proven to be more effective in increasing perceived ease of use. Meanwhile, BMA has relatively the same effectiveness in influencing perceived ease of use and perceived usefulness. Third, bank marketing, which is considered the most important, is personnel experience, service alertness in assisting the use of new technology, and conveying dissatisfaction. Meanwhile, the competencies of bank personnel that are considered a priority are the response to customer needs and requests, the ability to solve problems quickly, and ethical and enthusiastic personnel.
 Implication: This research can expand studies related to technology adoption theory with relatively few marketing functions. Managerially, this research provides several insights regarding bank services that must be a priority and competence of bank personnel to increase the use of digital banking.

The virality of advertising content

PurposeThe study aims to examine “Advertisement content likeability” and its relationships with consumers' purchase and sharing intentions.Design/methodology/approachSecond-order factor analysis was applied. Structural equation modeling (SEM) was used to measure the moderating effects of technology adoption model, knowledge sharing and Internet maven traits on advertising content's virality.FindingsResults indicate the dimensional structure of ad content likeability that is relevant in predicting consumers' sharing and purchase intentions. Furthermore, the moderating effects of technology acceptance factors (perceived usefulness and ease-of-use), knowledge sharing motives (altruism, reputation and expected reciprocal benefits) and senders' Internet maven characteristics were also found on “Ad content likeability” and “sharing intentions.”Originality/valueThe study expands the theoretical horizon of factors that significantly increase an advertisement's velocity to become more viral.

MIGRANT

Password manager applications have the potential to alleviate password pain and improve password strength, yet they are not widely adopted. Password managers are dissimilar to other kinds of software tools, given that the leakage of the credentials they store could give a hacker access to all the individual's online accounts. Moreover, adoption requires a deliberate switch away from an existing (manual) password management routine. As such, traditional technology adoption models are unlikely to model password manager adoption accurately. In this paper, we propose and explain how we validated a theoretical model of smartphone password manager adoption. We commenced by carrying out exploratory interviews with 30 smartphone owners to identify factors that influence adoption. These were used to develop a model that reflects the password manager adoption process, building on migration theory. The proposed model, MIGRANT (MIGRation pAssword maNager adopTion), was validated and subsequently refined in a week-long study with 198 smartphone owners, combining self-report and observation to measure constructs. This study contributes to the information security behavioral literature by isolating the main factors that encourage or deter password manager adoption, and those that moor smartphone owners in their current practices, hindering switching. With this investigation, we introduce migration theory as a reference theory for future studies in the information security behavioral field.

Enhancing Effectiveness of E-Learning: Lessons from Technology Adoption Model

A number of policies, missions and programmes have been initiated to facilitate e-learning enabled by information and communication technologies (ICTs) over recent years both by central as well as state governments in order to enhance effectiveness of teaching-learning process. However, tangible outcomes of such initiatives have been limited so far due to a number of factors especially in government institutions. While in some cases the core reason has been availability, accessibility, adequacy and quality of ICT tools, in many cases intention to use such technologies by teachers has been found conspicuous by its absence. The present paper uses the theoretical framework of the Technology Acceptance Model (TAM) to deduce relevant lessons. The objective is not to deliberate on the nuances of the model but simply to pick out a few relevant constructs in light of the author’s own experience of technology adoption in the context of schools and colleges of Himachal Pradesh. After briefly outlining the key tenets of TAM, the paper articulates the rationale for adopting this model and finally discusses key lessons for increasing acceptance of such technologies among educational stakeholders. Since COVID 19 has already created a rationale for adopting technology-enabled learning methodologies, the recommendations of this paper are likely to improve the efficacy and effectiveness of current and future initiatives.

Revising Technology Adoption Factors for IoT-Based Smart Campuses: A Systematic Review

Smart education and the sustainable development of smart campuses have drawn significant research attention. This is enabled by intelligent devices that are widely attracting massive applicability in personal and big business contexts and can increase efficiency and convenience. This paper aims to present a solution to address the lack of a proper adoption model for smart campus initiatives. The evaluation and synthesis of the literature were conducted by following the systematic literature review (SLR) procedure. The study’s findings revealed the taxonomy and IoT technologies leading to the wide adoption of IoT-based smart campuses. The technology adoption models and their corresponding variables help the authors identify and classify a suitable adoption framework for smart campuses. The limitations and challenges of adoption theories as they pertain to smart campuses are discussed. Finally, the study adapts perceived scalability, perceived replicability, perceived reliability, perceived privacy and security, perceived trust, the cost of deployment, usefulness, enjoyment, and technicality as adoption factors of sustainable smart campuses. This study offers practical and theoretical implications regarding the adoption and propagation of emerging smart campuses.

Factors affecting consumer behaviour to use e-wallets: an empirical study from Vietnam context

The purpose of this paper is to investigate the behaviour of using e-wallets (BE) and the factors affecting the use BE belonging to Vietnamese consumers. Research data is collected by sending online questionnaires to consumers who have been using e-wallets in Vietnam - people between the ages of 18 and 50 years old based on the convenient non-probability sampling method. The authors combine both qualitative and quantitative methods in our research to build and develop the research model. To take advantage of the theory of planned behaviour (TPB) and technology acceptance model (TAM), this research uses a combination of TPB and TAM models (C-TAM-TPB) to analyse two factors of the technology adoption model (perceived usefulness - PU and perceived ease of use - PE), the unified theory of acceptance, use of technology factor (social influence - SI), and perceived risk (PR). The research results show that (1) three factors that positively affect e-wallet usage (ranked in descending order) are the PE, SI, and PU and (2) PR does not affect Vietnamese consumer BE. Although the investigation and research on consumer behaviour are quite popular in Vietnam and around the world, the investigation documents the BE and the factors that determine it is still rare in Vietnam. Therefore, this study contributes to investigating and measuring the BE and the factors affecting it in Vietnam. In addition, the combined approach of the C-TAM-TPB model to estimate the influencing factors is a method rarely used in previous studies on consumer behaviour.

Investigating the drivers of wearable technology adoption for healthcare in South America

PurposeThis empirical study examines the drivers of consumer intention to adopt wearable technology for healthcare in a South American country. Specifically, it proposes and tests a model of nonuser consumer intention to adopt fitness trackers for healthcare purpose in Chile.Design/methodology/approachThis study draws on the technology acceptance framework UTAUT2 to develop and test a conceptual model of wearable technology adoption. Data were collected through an online survey applied to 470 nonusers of wearable technology in Santiago, Chile.FindingsFindings indicate that hedonic motivation, social influence and perceived usefulness have the strongest influence on intention to adopt fitness trackers in Chile for healthcare. In addition, health motivation is an indirect predictor of consumer's intention to adopt wearable technology through its effect on perceived usefulness.Practical implicationsThe study contributes to a better understanding of consumer intention to adopt wearable technology for healthcare objectives in a less developed country in South America. Findings are useful for wearable technology managers, retail business and public policymakers.Originality/valueDespite the vast growth and importance of wearable technology for healthcare purposes, academic research considering less developed countries is scarce, especially the South American region. The proposed model and findings can extend this research gap. Theoretical and managerial implications are discussed as well as implications for public policy.

Educational Technology Adoption: A systematic review.

During the past decades a respectable number and variety of theoretical perspectives and practical approaches have been advanced for studying determinants for prediction and explanation of user’s behavior towards acceptance and adoption of educational technology. Aiming to identify the most prominent factors affecting and reliably predicting successful educational technology adoption, this systematic review offers succinct account of technology adoption and acceptance theories and models related to and widely applied in educational research. Recognised journals of the Web of Science (WoS) database were searched with no time frame limit, and a total of 47 studies published between 2003 and 2021 were critically analysed. The key research findings revealed that in educational context a vast majority of selected studies explore the validity of Technology Acceptance Model (TAM) and its many different extensions (N=37), along with TAM’s integrations with other contributing theories and models (N=5). It was exposed that among numerous predictors, thematically grouped into user aspects, task & technology aspects, and social aspects, self-efficacy, subjective norm, (perceived) enjoyment, facilitating conditions, (computer) anxiety, system accessibility, and (technological) complexity were the most frequent predictive factors (i.e. antecedents) affecting educational technology adoption. Considering types of technologies, e-learning was found to be the most common validated mode of delivery, followed by m-learning, Learning Management Systems (LMSs), and social media services. The results also revealed that the majority of analysed studies were conducted in higher education environments. New directions of research along with potential challenges in educational technology acceptance, adoption, and actual use are discussed as well.

Towards an understanding of consumers’ FinTech adoption: the case of Open Banking

PurposeThis study aims to identify key factors driving consumers' adoption of Open Banking. It extends the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating perceived risk, initial trust and financial literacy into an overarching conceptual model.Design/methodology/approachMeasurement items of the theoretical constructs included in the conceptual model were adapted from related literature and a set of hypotheses was developed. The hypotheses of the conceptual model were subsequently assessed with partial least squares structural equation modeling using a dataset of 456 Australian survey respondents.FindingsThe model has strong explanatory power with an R2 of 69.5%. Performance expectancy, effort expectancy, social influence and perceived risk are direct antecedents of consumers' usage intention of Open Banking. Social influence has a strong mediating effect on usage intention through performance expectancy. The effect of perceived risk is alleviated by effort expectancy and initial trust, while initial trust positively affects the effects of performance expectancy and effort expectancy on consumers' usage intention of Open Banking. Finally, financial literacy lowers initial trust towards Open Banking, possibly inducing consumer skepticism.Practical implicationsThe results suggest that practitioners should focus on performance expectancy as a primary driver of Open Banking adoption, while understanding the role of other drivers, such as social influence and perceived risk in developing marketing strategies. Policy makers are recommended to adopt a governance approach to build initial trust amongst consumers.Originality/valueThis research contributes by providing an integrated and comprehensive model for explaining consumers' FinTech adoptions by extending the existing technology adoption model UTAUT to the Open Banking domain and integrating perceived risk, initial trust and financial literacy, thereby advancing and enriching the conceptual horizon of the extant literature.

Extending the UTAUT2 Model with a Privacy Calculus Model to Enhance the Adoption of a Health Information Application in Malaysia

This study validates and extends the latest unified theory of acceptance and use of technology (UTAUT2) with the privacy calculus model. To evaluate the adoption of healthcare and e-government applications, researchers have recommended—in previous literature—the application of technology adoption models with privacy, trust, and security-related constructs. However, the current UTAUT2 model lacks privacy, trust, and security-related constructs. Therefore, the proposed UTAUT2 with the privacy calculus model is incorporated into four constructs: privacy concern, perceived risk, trust in the smart national identity card (SNIC), and perceived credibility. Results from a survey data of 720 respondents show that habit, effort expectancy, performance expectancy, social influence, hedonic motivation, and price value are direct determinants that influence behavioral intentions to use. Results also revealed that behavioral intentions, facilitating conditions, habits, perceived risks, and privacy concerns are direct predictors of ‘use behavior’. The authors also analyzed the interrelationships among the research constructs. The extended model may lead toward establishing better innovative e-health services to cover the desires of the citizens through the use of health information applications embedded in an all-in-one card.

Local leader's impact on adoption of renewable energy generation technology by rural communities in the Himalayan region

Sustained energy access to remote hilly regions is a challenge. Governments have made efforts to implement renewable energy solutions in these areas, but the acceptance of such technologies by local communities has not been easy. An action research was conducted to introduce a renewable energy technology for energy generation through pine needles to rural communities of Himalayan region. Based on the theoretical underpinning of the Unified Theory of Acceptance and Use of Technology this empirical study explored the determinants of behavioural intentions to adopt the specifically designed briquetting machine. Results show that in addition to effort expectancy and performance expectancy, local leader's influence also affects the community's intention to use the technology. However, perceived effort expectancy and performance expectancy mediate the relationship between the leader's influence and behavioural intention. Age was also found to be a moderating variable. This modified model of technology adoption has significance in policy making and implementation of similar renewable energy based development projects for mountainous community.