Technology Readiness And Acceptance Model Research Articles

Understanding physicians' adoption intentions to use Electronic Health Record (EHR) systems in developing countries: an extended TRAM approach

PurposeThe success of an Electronic Health Record (EHR) system is determined by the numerous facilitators and obstacles that influence physicians' intentions toward using these technologies. This study examines physicians' intentions to use EHR by applying the extended technology readiness and acceptance model (TRAM) factors, the result demonstrability, colleagues' opinions, perception of external control, and organizational support.Design/methodology/approachConvenience sampling was used to collect data from physicians in Egypt (n = 520). To evaluate the model's hypotheses, this study used the partial least squares structural equation modeling (PLS-SEM) method with WarpPLS.7.FindingsThe results revealed that positive TR factors (innovativeness and optimism) positively affect perceived usefulness and ease of use, while negative TR factors (discomfort and insecurity) negatively impact perceived usefulness and ease of use. Furthermore, the result demonstrability and colleagues' opinions positively influence perceived usefulness, while the perception of external control and organizational support positively influence perceived ease of use. In addition, significant relationships between perceived ease of use and usefulness and adoption intention were identified.Originality/valueThis is the first study to apply the TRAM to understand physicians' adoption intentions to use EHR systems. Moreover, this study determined the different roles of positive and negative TR affecting physicians' cognition regarding using EHR systems.

Testing the Intention of Employees in Local Government to Adopt Blockchain Technology in Accounting Information Systems (AIS)

Research aims: This study aims to determine the intention of local government employees to adopt blockchain technology in Accounting Information Systems (AIS) using the Technology Readiness and Acceptance Model (TRAM) theory. Design/Methodology/Approach: The research participants were individuals employed in Regional Apparatus Organizations (RAOs) in Yogyakarta Special Region Province who were selected through a purposive sampling technique. Data were collected using a questionnaire and analyzed utilizing the Partial Least Square method. Research findings: The results revealed that the perceived usefulness of blockchain technology in AIS was determined by comfort, optimism, and security from fraud. Meanwhile, the perceived ease of use was determined by comfort, innovation, and security from fraud. These results also found that perceived usefulness and perceived ease of use positively influenced the intention of local government employees to use blockchain technology in AIS. Theoretical contribution/Originality: This research contributes to validating the TRAM theory in the context of blockchain technology adoption in AIS in local governments. Practitioner/Policy implication: The research findings offer valuable insight for relevant authorities, namely the Indonesian Ministry of Home Affairs, Ministry of Communication and Information, and local government entities, to prepare for implementing blockchain technology in AIS in local government. Research limitation/Implication: The study was conducted using quantitative methods with a limited sample size.

Exploring The Factors Affecting Consumer Preparedness For Smart Home Technology In Indonesia

SSmart home technology is becoming more popular globally, including in Indonesia. However, its adoption is still early, mainly due to the public's limited awareness of this technology. This study uses the Technology Readiness and Acceptance Model (TRAM) to assess individuals' readiness to embrace smart home technology. This research was conducted using SEM PLS with 271 respondents selected through purposive sampling, using 34 questions with a 5-point Likert scale. Positive outlook and user-friendliness have a role in how people value smart home technology, according to the study's findings. Optimism, inventiveness, and discomfort all affecthow easy something is to use. Anxiety and unease can play a role in how we interpret danger. Smart home technology adoption is influenced by factors such as its perceived value, simplicity of use, and cost significantly and positively.

Factors Affecting Technological Readiness and Acceptance of Induction Stoves: A Pilot Project

In 2022, through the state electricity company, the Indonesian government launched a pilot experiment to cut imports of liquefied petroleum gas by giving program packages to 1,000 families in five districts in Surakarta. Objectives: Using the technology readiness and acceptance model (TRAM), this study examined the elements influencing the readiness and acceptability of the induction stove program in Surakarta. Method/Analysis: The empirical findings from a 389-respondent survey showed that the program’s public acceptance was supported by favorable technological preparedness, including elements like innovation and optimism. Findings: Perceived use, enjoyment, usefulness, cost level, and confirmation were all factors that affected participants' happiness and willingness to continue using induction stoves and participating in the program. Interestingly, acceptability, general contentment, and the willingness to use induction stoves were not always affected by issues like discomfort and insecurity. Additionally, this research emphasized how crucial the social context is for successfully implementing a program and embracing new technologies. Novelty:This is the first study that concurrently identifies, assesses, and analyzes the integration of factors impacting technology readiness and acceptance (TRAM) into the community's intention to continue participating in the induction stove conversion program. These empirical results offer practical guidance for stakeholders in induction stove conversion projects, particularly in developing nations, and also add to a theoretical understanding of TRAM factors. Doi: 10.28991/ESJ-2023-07-06-04 Full Text: PDF

User Technology Readiness and Acceptance of Mobile Human Resources Information Application


 
 
 The Mobile Human Resource Application was developed to provide convenience for users. However, in the implementation phase, they have not been used by all users. There are several reasons users do not use the application, namely, employees often forget because they are not ready to use new applications, employees often fail to absent because there are some bugs at the beginning of implementation where the support team is not ready to help users and the employees’ insecurity when making a presentation using the face and location. The purpose of this study is to conduct empirical testing of the factors that influence the readiness and acceptance of users of the Mobile Human Resources Application. The Technology Readiness and Acceptance Model (TRAM) integrates technology readiness with technology acceptance into one model. TRAM is used to determine the effect of technology readiness on acceptance of the perceived ease of use factor and perceived usefulness will affect the intention to use. The result of the study showed that the Innovativeness and Perceived Ease of Use significantly influenced user technology readiness and acceptance of mobile human resources information application. Innovativeness dimensions of technology readiness have positive and significant effects on perceived ease of use. Perceived ease of use dimensions of technology acceptance has positive and significant effects on perceived usefulness and intention to use Mobile Human Resources.
 
 

Combining technology readiness and acceptance model for investigating the acceptance of m-learning in higher education in India

PurposeThe study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning in teaching and learning, including its acceptance.Design/methodology/approachA structured questionnaire was administered to open and distance learning (ODL) students in Odisha, India, to assess their readiness and acceptance of m-learning. 665 valid responses were collected, and collected data was analysed using statistical packages for social sciences (SPSS) and SmartPLS.FindingsThe findings of the study reveal that optimism contributes positively to perceived ease of use (PEOU) and perceived usefulness (PU) of m-learning (β = 7.921, p < 0.001; β = 2.123, p < 0.05), whereas innovativeness positively contributes to PEOU of m-learning (β = 2.227, p < 0.05), but not PU of m-learning. ODL student's optimism improves his/her PEOU and PU of m-learning, but innovativeness improves only his/her PEOU. Further, the impact of innovativeness is higher than that of optimism in the TRAM and innovativeness is the strong predictor to adopt m-learning. It also shows that the PU of m-learning positively influences behavioural intention to use m-learning (β = 4.757, p < 0.001). Integrating technology readiness (TR) with technology acceptance model (TAM) to predict students' acceptance of m-learning is very useful.Practical implicationsThe paper will help decision-makers to adopt and use m-learning in higher educational institutions.Originality/valueThis paper is the first to explore the readiness and acceptance of m-learning in higher education in India.

The Usage of Digital Health Technology Among Older Adults in Hong Kong and the Role of Technology Readiness and eHealth Literacy: Path Analysis

Although digital health technologies (DHTs) help many people maintain a healthy life, including those of advanced age, these technologies are of little use to older adult populations if they are not being adopted in daily life. Thus, it is critical to identify ways to help older adults recognize and try new technologies and maintain their use of them to maximize the benefits of these technologies in a digital-based society. Our study aimed (1) to assess the current usage of DHT among older adults in Hong Kong and (2) to examine how high and low levels of eHealth literacy in this group affects the relationship between the Technology Readiness and Acceptance Model (TRAM) and attitudes and intention toward DHT. A total of 306 adults over 60 years of age in Hong Kong participated in this study. After conducting confirmatory factor analysis to validate the measurement model, the hypothesized model was tested using structural equation modeling. Optimism was significantly related to perceived usefulness, while optimism, innovativeness, and discomfort were significantly associated with perceived ease of use. Both perceived usefulness and perceived ease of use were significantly linked to attitude toward the use of DHTs. Meanwhile, attitude significantly predicted usage intention. Additionally, the results revealed the differences in the relationships of the TRAM between participants with high and low levels of eHealth literacy. The influence of optimism and innovativeness on perceived ease of use was stronger for the higher-level group than for the lower-level group, and the influence of discomfort for the higher-level group was much weaker. The findings provided partial support for the impact of eHealth literacy on encouraging older adults to use DHT and obtain health benefits from it. This study also suggests providing assistance and guidelines for older adults to narrow the aging-related technology gap and to further explore the associations of eHealth literacy, the TRAM, and actual behaviors.

The new wave of AI-powered luxury brands online shopping experience: The role of digital multisensory cues and customers’ engagement

Academic literature retains a dearth of empirical evidence of the cutting-edge aspect of artificial intelligence (AI)-powered digital assistance and digital multisensory cues, despite the prospect of these factors on real-life customers' luxury brand online shopping experience. Thus, the aim of this study is to examine the significant pathway and effects of AI-powered digital assistance toward customers’ luxury brand online shopping experience. Drawing on S–O-R (Stimulus, organism, and response) and TRAM (Technology Readiness and Acceptance Model) paradigm, a multi-method research design was deployed to investigate constructs. Firstly, semi-structured interviews were utilized to explore customers' online behavior under the luxury brands and information technology aspect. Secondly, survey data were collected and analyzed by using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The PLS-based analysis of quantitative data confirmed the exploratory insights of qualitative findings, establishing the connections of AI-powered digital assistance, customer engagement, and customers' luxury brand online shopping experience. Research findings also suggest that customer engagement plays a mediation role in the relationship between AI-powered digital assistance and customers' luxury brand online shopping experience. Besides, digital multisensory cues moderate the relationship between AI-powered digital assistance and customer engagement. Further, fsQCA complements the findings of PLS-SEM that reveal the significant combination of factors that lead to the perceptions of customers' luxury brand online shopping experience.

Artificial intelligence (AI) acceptance in primary care during the coronavirus pandemic: What is the role of patients' gender, age and health awareness? A two-phase pilot study.

Artificial intelligence (AI) is steadily entering and transforming the health care and Primary Care (PC) domains. AI-based applications assist physicians in disease detection, medical advice, triage, clinical decision-making, diagnostics and digital public health. Recent literature has explored physicians' perspectives on the potential impact of digital public health on key tasks in PC. However, limited attention has been given to patients' perspectives of AI acceptance in PC, specifically during the coronavirus pandemic. Addressing this research gap, we administered a pilot study to investigate criteria for patients' readiness to use AI-based PC applications by analyzing key factors affecting the adoption of digital public health technology. The pilot study utilized a two-phase mixed methods approach. First, we conducted a qualitative study with 18 semi-structured interviews. Second, based on the Technology Readiness and Acceptance Model (TRAM), we conducted an online survey (n = 447). The results indicate that respondents who scored high on innovativeness had a higher level of readiness to use AI-based technology in PC during the coronavirus pandemic. Surprisingly, patients' health awareness and sociodemographic factors, such as age, gender and education, were not significant predictors of AI-based technology acceptance in PC. This paper makes two major contributions. First, we highlight key social and behavioral determinants of acceptance of AI-enabled health care and PC applications. Second, we propose that to increase the usability of digital public health tools and accelerate patients' AI adoption, in complex digital public health care ecosystems, we call for implementing adaptive, population-specific promotions of AI technologies and applications.

Measurement of Doctoral Students’ Intention to Use Online Learning: A SEM Approach Using the TRAM Model

Measurement of Doctoral Students’ Intention to Use Online Learning: A SEM Approach Using the TRAM Model

FACTORS INFLUENCING THE FARMERS’ BEHAVIORAL INTENTIONS OF FARMER CARDS IN SUMENEP REGENCY

Many factors cause the issue of fertilizer subsidies. One of them is about the implemented system has not been running optimally. The Farmer Card is an innovation to obtain subsidized fertilizers. The innovation has many obstacles, including the lack of awareness and knowledge of farmers’ human resources (HR) in understanding the innovations’ usefulness. The study’s objective was to determine the factors influencing the acceptance of the Farmer Card based on the Technology Readiness and Acceptance Model (TRAM). Primary data were gained from the farmers by taking a simple random sampling method using the Hair formula for as many as 115 farmers using Farmer Card in Kabupaten Sumenep. The data were analyzed using the quantitative descriptive method through the Partial Least Square (PLS) technique. The study’s objective was to determine the effect of optimism, innovativeness, discomfort, insecurity, perceived usefulness, and perceived ease of use on behavioral intention to use in technology readiness with a p-value of 0.000 (<0.05). The test results show that the variables of optimism (H1 and H2), discomfort (H5), perceived usefulness (H9), and perceived ease of use (H10) have a significant effect on behavioral intention to use Farmer Card. Testing the effect of innovativeness (H3 and H4), discomfort (H6), and insecurity (H7 and H8) showed a p-value of 0.091; 0.259; 0.127; 0.853; 0.385 (> 0.05) means that it has no significance. For the Farmer Card program to be successful, it is recommended to enhance cooperation further and shared views among the farmers and stakeholders.

Readiness and Acceptance of Farmer Cards to Farmers in Sumenep Regency

The Farmer’s Card becomes one of the requirements to get the subsidized fertilizer as a tool of access to banking services integrated into an E-wallet or ATM (Automatic Teller Machine). The new technology indicates the problem found in the field, which is the lack of awareness and knowledge of the farmers who own the Farmer’s Card in understanding the function of each feature provided by the Card. This research is conducted to analyze the readiness and the acceptance factors of the farmers who own the Farmer’s Card toward the interest of using the Farmer’s Card in the Sumenep Regency. The Technology Readiness and Acceptance Model (TRAM), which is the collaboration of the Technology Readiness Index (TRI) and Technology Acceptance Model (TAM), is being used to analyze the interest in the use of the Farmer’s Card. Quantitative data is collected through interviews with structured questionnaires that refer to the previous research indicators on the Technology Readiness and Acceptance Model (TRAM). The sample was conducted on 140 farmers who own the Farmer’s Card. The analysis was performed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) through the SmartPLS software. The results of the hypothesis show that the function or the advantage of the Farmer’s Card has a direct and significant influence on the interest of the farmers in using the Farmer’s Card. On the other hand, the simplicity of using the Farmer’s Card is considered insignificant and challenging for the farmers. The Farmer’s Card program can be successful. It is suggested that the government and the farmers, who own the Farmer’s Card, need to approach and improve their communication through intensive guidance. Keywords: readiness, acceptance, farmer's card, PLS-SEM, subsidized fertilizer

Gym users: an enabler in creating an acceptance of sports and fitness wearable devices in India

PurposeThere are two-fold objectives to this research. First is to analyse the importance of technology readiness (TR) for the users in using sports and fitness wearable devices in India. And second is to explore if gymnasium (gym) users are much more technologically ready as compared to non-gym users to use sports and fitness wearable devices.Design/methodology/approachThe study uses technology readiness and acceptance model (TRAM) to examine the users' intention to use sports and fitness wearable devices. Data from a survey of 907 respondents from India were collected and partial least squares (PLS)-structural equation modelling (SEM) technique was used to empirically examine it.FindingsThe outcomes reveal that innovativeness and optimism have a positive influence on perceived ease of use (PEOU) and perceived usefulness (PU), and insecurity and discomfort have a negative influence on PEOU and PU. Both PEOU and PU act as important determinants in the user's intention to use sports and fitness wearable devices. The multi-group analysis (MGA) suggests that gym users tend to exhibit more positive intention towards using sports and fitness wearable devices and show higher probability of using the wearable devices relative to non-gym users.Originality/valueThere are hardly any studies on intention to use sports and fitness wearable devices in India. The current research tries to understand the intention behind the gym users and non-gym users to use sports and fitness wearable devices. The outcomes of the research will help the marketers to align their promotional campaign based on the new segmentation variable “gym-user/non-gym user”. The research also highlights the importance of TR in the use of sports and fitness wearable devices in India.

Exploring Intention toward Using an Electric Scooter: Integrating the Technology Readiness and Acceptance into Norm Activation Model (TRA-NAM)

The issues of renewable energy, energy crisis, and carbon reduction have caught people’s attention all over the world, and governments have put forth greater effort to proactively solve these problems. Electric transportation not only benefits the environment, but can also utilize renewable energy to prevent an energy crisis. Based on previous theoretical strands of the literature, this research integrates the technology readiness and acceptance model (TRAM) into the norm activation model (NAM) and proposes an integrated model denoted as TRA-NAM. It takes TRA-NAM as our theoretical foundation and aims to explore the effect of technology readiness and awareness of consequence on the intention toward using an electric scooter (ES). The results display that technology readiness positively influences perceived usefulness and perceived ease of use and further improves consumers’ intention toward adopting ES. In addition, personal norm mediates the relationship between awareness of consequence and intention to adopt ES. This study offers the integrated TRAM-NAM model in order to understand the crucial factors affecting consumers’ intention to adopt electric vehicles (EVs). Overall, this research fills the gap in the field of government policies and transportation and proposes ponderable suggestions, in particular that if they want to encourage or attract consumers to drive an ES, they should not overlook the effect of technology readiness and awareness of consequence.

Exploring Students’ Perceived Attitude on Utilizing a Biofeedback System for Anxiety Awareness during Academic Examination Activities

The presented paper examines the students’ adoption of the use of a cost-effective biofeedback system for anxiety awareness in parallel to examination activities. Human anxiety is classified by evaluating bio-signals related to skin conductance, skin temperature and heart rate. The participants of the research were 44 students who were taking examinations in the form of synchronous online tests in the classroom for one of their courses. At first, the usability of the biofeedback system was examined using the system usability scale (SUS). The statistical analysis indicated that the examined system usability is quite satisfactory. Then, the study attempted to investigate the relationships between the students’ technology readiness personality dimensions, perceptions of usability, and the usefulness of the presented system by exploiting the technology readiness and acceptance model (TRAM). The results showed that the students’ optimism and attitude towards using the system are significant factors that affect the model’s relationships. The examined relationships are presented via a path model.

AI Acceptance in Primary Care during COVID-19: A Two-Phase Study of Patients’ Perspective

Artificial Intelligence (AI) is steadily entering and transforming the healthcare and primary care domains. We observe AI-based applications assisting physicians in disease detection, medical advice, triage, clinical decision-making, diagnostics and digital health. Recently literature explored the physicians’ perspective about the potential impact of future technology on key tasks in primary care. However, limited attention has so far been paid to the patients’ perspective about AI acceptance in primary care, specifically during COVID-19 pandemic. Addressing this research gap, we employed a two-phase mixed methods approach to investigate the criteria for patients’ readiness to use AI-based primary care applications by analyzing key factors that affect the adoption of medical technology. First, we conducted a qualitative study which comprised of 18 semi-structured interviews. Second, based on the Technology Readiness and Acceptance Model (TRAM), we conducted an online survey (n=447). Study results indicate that respondents who score high on innovativeness have a higher level of readiness to use AI-based technology in primary care during COVID-19. Surprisingly, we found that patients’ health awareness and socio-demographic factors such as age, gender and education are not significant predictors of AI-based technology acceptance in primary care. Therefore, we suggest exploring the effects of population-specific promotions and individual impediments to speed-up the adoption of AI-based technology in primary care in order to raise usability in complex digital healthcare ecosystems.

Consumer acceptance of retail service robots

Building on Technology Readiness and Acceptance Model(TRAM), the study aimed to examine how technology readiness affects consumers’ perceptions of ease of use, usefulness, and risk, which in turn predict their intention to use retail service robots. Specifically, the study proposed that technology readiness motivators (optimism and innovativeness) would influence perceived ease of use and usefulness, while technology readiness inhibitors (discomfort and insecurity) would affect perceived risk. The study further examined if the perception factors (ease of use, usefulness, and risk) contribute to intention to use retail service robots. A survey method was used with data collected from Korean consumers. The final sample size was 418. The data was analyzed using structural equation modeling. Findings of the study revealed that technology readiness motivators positively affected perceived ease of use and usefulness while innovativeness had no impact on usefulness. All the inhibitors increased perceived risk. Lastly, as hypothesized, perceptions of ease of use, usefulness, and risk predicted intention to use retail service robots. This study extended the retail technology literature by applying and validating TRAM to the context of consumer acceptance of retail service robots. The study further helped marketers and retailers by highlighting the importance of technology readiness in improving consumer perceptions and responses towards retail service robots.

The role of technology readiness in individuals' intention to use health and fitness applications: a comparison between users and non-users

PurposeThe purpose of this study is to examine individuals' decisions to use health and fitness apps by applying the extended technology readiness and acceptance model (TRAM), which combines technology readiness (TR), the technology acceptance model (TAM) and perceived enjoyment (PEN). Moreover, this study explores the differences between users and non-users regarding their intentions to use health and fitness apps.Design/methodology/approachData collection (n = 206) was conducted using convenience sampling from four large universities in South Korea. The data were analysed by partial least squares structural equation modelling (PLS-SEM) using SmartPLS 3.0.FindingsThe results revealed that positive TR positively affects perceived ease of use (PEOU), perceived usefulness (PU) and PEN, while negative TR had a negative impact only on PEN. Furthermore, the significant relationships between PEOU, PU and PEN were identified. In addition, multigroup analyses indicated that the relationships between positive TR and PEN, between PEN and PEOU, between PEOU and PU, and between PU and behavioural intention were positively stronger for app users.Originality/valueThis study initially applied the TRAM to understand individuals' behavioural intentions to use health and fitness apps. Moreover, this study identified the distinct roles of positive and negative TR affecting individuals' cognition regarding using health and fitness apps. The differences in the psychological processes between app users and non-users offer insights and implications for practitioners.

Combination of e-readiness models to assess based on system approaches at cooperatives in Indonesia

The 4.0 industrial revolution, on the one hand, will open opportunities for the domestic product market to compete internationally and vice versa. Business competition is so tight, the existence of free markets and advances in information technology, robotics, artificial intelligence, transportation, and communication are rapid, giving changes quick on the economy. The way to adapt to the outlook and the ability to project change in the environment and be able to determine the right strategy for this change is a must for organizations that are committed to survival as in Cooperatives in Indonesia. Regarding this problem, there are several e-readiness models that have been developed to test readiness or ability to provide platforms, comparisons, and estimates including TRAM (Technology Readiness and Acceptance Model) and several variables namely business content and institutional contexts that influence the model. The results show that the TRAM 2.0 model and E readiness are related to each other. The E-readiness model has 2 success factors for The McLeod and MacDonell’s projects as attributes used for readiness input. From the correlation process, added a new factor, called Business Content, Institutional Context so that the E-readiness model has 8 factors.

An Empirical Study on the Intention to Use Open Banking in India

This article examines the use intention of open banking technology in the context of an emerging economy like India using the theoretical framework of Technology Readiness and Acceptance Model (TRAM). To study the use intention for open banking in India, a primary survey was conducted among 945 customers using a structured questionnaire. The PLS-SEM technique was used to analyze the data. Findings – The results show that Optimism (OPM) contributes positively to the Perceived Ease of Use (PES) and Perceived Usefulness (PUF) of the open banking technology. Innovativeness (INO) of the customers is a significant predictor of PES and PUF. It was found that Discomfort (DCF) negatively contributes to PES and PUF; however, it significantly influences PES and has no significant influence on PUF. Insecurity (INT) is negatively significant to PUF and it has no significant influence on PES. It is observed that PES positively contributes to PUF. The results show that PES and PUF are significant predictors of Perceived Customer Value (PCV). PCVs contribution to the Use Intention (UNT) is significantly positive for open banking technology. The stickiness to traditional banking moderates the relationship between PCV and UNT for open banking.