Task-technology Fit Model Research Articles

Examining the Prediction of Contact-Tracing App Adoption Using an Integrated Theoretical Model and Hybrid Approach Analysis

Covid-19 contact-tracing applications (CTAs) offer enormous potential to mitigate the surge of positive coronavirus cases, thus helping stakeholders to monitor high-risk areas. This study hypothesized an integrated model which comprises the technology acceptance model (TAM), privacy calculus theory (PCT), and task-technology fit (TFF) model. The hypothesized is use to better understand behavioral intention towards using the Tawakkalna mobile CTA. This study performed structural equation modeling (SEM) analysis as well as artificial neural network (ANN) analysis to validate the model, using survey data from 309 users of CTAs in the Kingdom of Saudi Arabia (KSA). The findings revealed that perceived ease of use and usefulness has positively and significantly impacted behavioral intention of Tawakkalna mobile CTA. Similarly, task features and mobility positively and significantly influence task–technology fit, and significantly affecting the behavioral intention of the CTA. However, the privacy risk, social concerns, and perceived benefits of social interaction are not significant factors. The findings provide adequate knowledge of the relative impact of key predictors of the behavioral intention of the Tawakkalna contact-tracing app.

Examining internet banking user’s continuance intention through the lens of technology continuance theory and task technology fit model

Purpose The long-term success of internet banking (IB) services is connected with continuous use. Therefore, examining factors which influence IB user continuance intention is important. Grounded in technology continuance theory, bank transparency and task technology fit (TTF) model, the purpose of this study is to develop a unified technology continuance model to investigate IB user continuance intention. Design/methodology/approach The research model was empirically tested with 348 responses. Respondents included in this study had prior experience with IB services. For hypotheses testing, the structural equation modelling approach was used. Findings Findings indicate that the research model has substantial power in explaining IB user continuance intention. Importance performance matrix analysis revealed that bank transparency had the highest importance in determining IB user continuance intention. Therefore, factors like user satisfaction and perceived usefulness have shown a medium level of importance in determining IB user continuance intention. Satisfaction is influenced by perceived usefulness and confirmation and established a significant impact on IB user continuance intention. Practical implications The findings of this research are useful for bank managers and policymakers to develop and design IB services according to user’s expectations. Results demonstrate that expectation confirmation and perceived usefulness are antecedents of IB user satisfaction and IB user continuance intention. In addition to that bank, transparency has shown a significant effect on user expectation and IB user continuance intention. These findings established that accuracy in sharing bank information and clarity in transaction charges encourage the user to continue the use of IB services. Originality/value The current study develops a unified technology continuance model based on the TTF model and technology continuance theory and investigates IB user continuance intention. Moreover, bank transparency is added in the technology continuance model and established a significant impact towards user expectation confirmation and continuance intention. These findings contribute to the limited body of research in the context of IB user continuance intention and enrich information system literature.

Factors Influencing the Adoption Intention of Blockchain and Internet-of-Things Technologies for Sustainable Blood Bank Management

Owing chiefly to the lack of suitable technology solutions, India is experiencing both shortage and wastage of blood units. In addressing such a challenge, we explore the unique role of Blockchain and Internet-of-things technologies in the overall blood supply chain management as an appropriate technology solution. Our study employs an integrated Task-Technology Fit and Technology Acceptance Model to empirically test and identify key factors influencing the adoption intention of the Blockchain and Internet-of-things enabled system. With the need to preserve donor and recipient data integrity and data privacy, the respective state and national health departments strictly regulate blood banks. Accordingly, our study also explores the role of government in supporting and overseeing security concerns in the future adoption of the Blockchain and Internet-of-things technologies. Finally, a solution based on the Blockchain and Internet-of-things technologies to ensure the sufficient availability of blood units at the national level is envisioned.

The Perceived Satisfaction in Utilizing Learning Management System among Engineering Students during the COVID-19 Pandemic: Integrating Task Technology Fit and Extended Technology Acceptance Model

Online education has become the norm for higher education institutions (HEIs) during this COVID-19 pandemics. HEIs are required to implement a fully online learning system that is structured and readily accessible with the assistance of a learning management system (LMS), including in developing countries such as the Philippines. This study aims to assess factors that positively influence the perceived satisfaction of engineering students when using the LMS during the COVID-19 pandemic in the Philippines. Additionally, it aims to integrate two models: Task Technology Fit (TTF) and Technology Acceptance Model (TAM), with added variables such as the content of the learning management system, social presence, and social space. Upon deploying the convenience sampling, a total of 1011 engineering students responded in the online survey, which consisted of 81 questions. Structural equation modeling (SEM) showed that the Task Technology Fit was positively influenced by technology, individual, and task characteristics. Moreover, behavioral intention to use LMS was positively influenced by perceived usefulness and perceived ease of use. Furthermore, Task Technology Fit had a significant direct effect on behavioral intention to use LMS, which subsequently led to perceived satisfaction. This study is among the first to explore factors affecting perceived satisfaction among engineering students in using the LMS in the Philippines during the COVID-19 pandemic. To evaluate the perceived satisfaction of students in using the learning management system, future works can be extended and the model can be applied in other countries.

Factors Influencing the Adoption Intention of Blockchain and Internet-of-Things Technologies for Sustainable Blood Bank Management

Owing chiefly to the lack of suitable technology solutions, India is experiencing both shortage and wastage of blood units. In addressing such a challenge, we explore the unique role of Blockchain and Internet-of-things technologies in the overall blood supply chain management as an appropriate technology solution. Our study employs an integrated Task-Technology Fit and Technology Acceptance Model to empirically test and identify key factors influencing the adoption intention of the Blockchain and Internet-of-things enabled system. With the need to preserve donor and recipient data integrity and data privacy, the respective state and national health departments strictly regulate blood banks. Accordingly, our study also explores the role of government in supporting and overseeing security concerns in the future adoption of the Blockchain and Internet-of-things technologies. Finally, a solution based on the Blockchain and Internet-of-things technologies to ensure the sufficient availability of blood units at the national level is envisioned.

An Empirical Research on the Construction of a Government Website Public Satisfaction Index Model in China

With proliferated applications of the internet and world wide web, people are increasingly interacting with government websites. It is therefore significant to measure satisfaction on government systems from citizen's perspective. While general customer satisfaction index (CSI) models have received much attention from researchers, few studies are conducted to evaluate public satisfaction on government websites. The extent to which traditional CSI models can be extended to investigate public satisfaction on government websites remains unclear. On analysis of CSI, technology acceptance model (TAM), and task-technology fit (TTF) model, this study constructs a government website public satisfaction index (GWPSI) model and provides an empirical study by adapting GWPSI model in the context of G2C e-government. Structural equation modeling (SEM) is applied to data collection and processing with questionnaires collected from users of the government website of Guangdong Province in China. The findings provide several important implications for e-government research and practice.

Adopting task technology fit model on e-voting technology

<span>E</span><span>-voting is a tool to support the voting process starting from recording, voting, and counting votes using electronic devices. E-voting promises a faster voting process, reduced budget costs, lost votes due to damaged ballot papers during the voting process, and others. E-voting is also used in high school student council elections. Young people are more computer literate (computer literacy) and interested in using new technology (e-voting) than adults and older people. This study aims to determine the suitability of e-voting in the SMA OSIS election to the user's task support using the task-technology fit (TTF) model. The data analysis used is multiple regression analysis. This analysis is used to determine the effect of the independent variables on the dependent variable with a significance level of 5%. The results of this study indicate that the 4 formulated hypotheses can be accepted and the students of SMK Muhammadiyah 1 Bantul feel the suitability of technology support when voting using e-voting in the selection of the high school student council.</span>

Investigating the Impact of Critical Factors on Continuous Usage Intention towards Enterprise Social Networks: An Integrated Model of IS Success and TTF

Due to the outbreak of COVID-19, many people have to accept remote working. However, as COVID-19 has been effectively controlled in China, remote office services provided by enterprise social networks (ESNs) is no longer a necessary choice of users. There has not yet been any referential research for ESN enterprises concerning how to encourage users willing to use ESNs continuously. Therefore, the purpose of this research is to identify the critical factors of ESN continuous usage intention to make up the research gap of ESN continuous usage intention and to help enterprises address the issue of sustained growth. This research combines elements of the task technology fit (TTF) model and D&M information systems success (ISS) model, explaining the continuous usage intention of ESN users. The empirical analysis results are based on the sample data of 668 Chinese respondents with experience in ESNs use and analyzed using structural equation modeling (SEM). Results show that task technology fit, performance expectancy and the satisfaction degree have a significant influence on continuous usage intention of ESNs. The research findings can provide the theoretical basis for sustained development and follow-up research of the ESN industry.

Acceptance of clinical decision support systems in Saudi healthcare organisations

Applications of clinical decision support systems (CDSS) have become essential for physicians seeking to make appropriate decisions. The implementation of CDSS, however, is complicated if the factors affecting physician’s acceptance are not recognised. This study aims to explore the various factors that may influence the acceptance of CDSS in Saudi Arabia. A qualitative method was used to collect data from interviews with 54 GPs, with interviews conducted in three stages. The study then integrated the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-Technology Fit (TTF) models to communicate the findings. It is suggested that all factors of both UTAUT and TTF influence acceptance of CDSS by GPs, with the sole exception of the social influence factor. Some additional factors were also discovered by means of in-depth interviews, including accessibility, patient satisfaction, informativeness (increased knowledge), connectedness (informing patients), communication and shared knowledge, privacy and security, and perceived risk (functional performance risk and time risk). The study thus offers a new insight of the factors influencing GPs’ acceptance of CDSS.

Interaction design for security based on social context

Social context is a vital component of Human-Computer Interaction (HCI) design for security; however, there is little discussion about how to provide security functions based on the social context. This study examines the fit between security design and social contexts in mobile payment applications by investigating preferences and perceptions of security design based on the task-technology fit model and the technology acceptance model. To approach the fit of security design in different social contexts, this study followed the approach proposed by design science research and employed a full factorial design experiment. We developed two interfaces—a customizable interface without feedback information and a customizable interface with feedback information—and asked participants to modify security settings in the interfaces according to social contexts, conduct payment transactions, and report their perceptions of security and usability in four payment scenarios. The observed behaviors in relation to security settings and perceptions revealed the fit for security settings and feedback design in different social contexts. Implications were provided to allow insights for security design in mobile payment transactions according to social contexts.

I want to learn more! Integrating technology acceptance and task–technology fit models for predicting behavioural and future learning intentions

PurposeConstant and frequent technological changes within organizations call for further scholarly attention, as behavioural intentions need to be coupled also with future learning intentions to predict the present and prospective individual adaptations and performance. This study, grounded on the technology acceptance model, aims to examine the association between training opportunities and behavioural and future learning intentions also taking into account the role of task–technology fit as a moderator.Design/methodology/approachA survey was carried out within a single organization in the water processing sector on a sample of 200 workers who recently experienced a technological change through the adoption of System Application and Product in data processing. A moderated–mediation model was estimated through regression analyses with bootstrapping.FindingsThe results were consistent with study hypotheses. In particular, task–technology fit amplified the positive association between perceived ease of use and training opportunities as well as the indirect effect of this latter on both behavioural and future learning intentions through perceived ease of use and perceived usefulness. In sum, the hypothesized moderated–mediation model was confirmed.Originality/valueThree novelty factors of this study can be stressed: it is among the few studies carried out on Italian workers in the realm of technology adoption, it expanded the technology acceptance model by including traditional behavioural intentions and future learning intentions as outcome variables and it integrated the task–technology fit perspective within the technology acceptance model.

An Examination of How Social and Technological Perceptions Predict Social Media News Use on WeChat

ABSTRACT The decision to use a particular social media application for news is affected by many factors, but less is understood is how a platform’s technological features promote or impede people’s social media news use. A structural equation model derived from the Unified Theory Acceptance and Use of Technology and Task-Technology Fit models were applied to investigate what social and technological perceptional factors explain people’s news use behaviors within the context of WeChat. Results showed an application’s technological features (i.e., technology characteristics and task-technology fit) played a significant role in predicting multiple social media news use behaviors. We put forth a theoretical model that predicts social media news use based on the results.

Continuance Intention of University Students and Online Learning during the COVID-19 Pandemic: A Modified Expectation Confirmation Model Perspective

The prevalence of COVID-19 has changed traditional teaching modes. For many teachers, online learning effectively compensated for the absence of traditional face-to-face instruction. Online learning can support students and schools and can create unique opportunities under emergency management. Educational institutions in various countries have launched large-scale online course modes in response to the pandemic. Additionally, online learning during a pandemic differs from traditional online learning modes. Through surveying students in higher education institutions, educational reform under emergency management can be explored. Therefore, university students were surveyed to investigate their continuance intention regarding online learning during the pandemic. Expectation confirmation theory was extended using the task-technology fit model to ascertain whether the technical support of promoting online learning helped student’s complete course learning tasks during the pandemic and spawned a continuance intention to use online learning in the future. Data were collected through online questionnaires. A total of 854 valid responses were collected, and partial least squares structural equation modeling was employed to verify the research hypotheses. The results revealed that the overall research framework largely explained continuance intention. Concrete suggestions are proposed for higher education institutions to promote online learning modes and methods after the COVID-19 pandemic.

Promoting e-banking actual usage: mix of technology acceptance model and technology-organisation-environment framework

ABSTRACT The purpose of this study is evaluating new decision factors which affecting users’ behaviour intention and actual usage towards e-banking. In this research, the TOE framework is integrated with TAM theory as the novelty to fill up the hole of TAM theory and past researches. The proposed Model is tested in an Iranian bank. Partial least squares is applied to examine inter-correlations among the model’s constructs. The results indicate that task-technology fit model and technical service innovation as technology context positively affects e-banking actual usage and task and technology characteristics positively affect task-technology fit. User integration and perceived size as organisation context positively influence users’ behaviour intention and actual usage, respectively. Furthermore, initial trust model as environment context positively influences users’ behaviour intention. Structural assurance positively affects initial trust, but social influence and bank reputation effect is rejected. Also, culture-technology fit and government support as environment context positively influences e-banking actual usage.

What Drives the Adoption of the Blockchain Technology? A Fit-Viability Perspective

ABSTRACT Blockchain technology has the promise of transforming security and trust in digital transactions. However, concerns about technical complexity and the benefits of deployment have blunted its adoption. We examine factors that influence managerial intention to adopt blockchain technology. We extend the fit-viability model (FVM) and develop a value-based technology adoption model through an empirical study of 242 managers mostly in medical and financial industries. Managers in such organizations are likely to consider fit and viability in adopting blockchain technology to store and protect data. Drawing upon Fit-Viability and Task-Technology Fit models, and the Unified Theory of Acceptance and Use of Technology (UTAUT), we test a model with Partial Least Squares (PLS) to assess managers’ intention to adopt blockchain technology. Our findings indicate that functional and symbolic benefits have positive impact on managers’ assessment of task-technology fit. Furthermore, viability is an important criterion in adopting blockchain technology.

Assessing the Effectiveness of Smartphone Usage to Interact with Learning Materials in Independent Learning Outside of Classrooms among Undergraduate Students

Clearly, the smartphone is increasingly playing a greater role in everyday life, thus providing opportunities to evaluate how well the use of the smartphone meets the requirements of undergraduate students in independent learning outside of a classroom setting. This study used the task-technology fit (TTF) model to explore the effectiveness of smartphone usage to interact with learning materials in independent learning outside of classrooms, the need for smartphone support, and the fit of devices to tasks as well as performance. First, the study used interviews, observation, and survey data to identify what are the most important constructs of smartphones that stimulate students to interact with learning materials in independent learning outside of classrooms. Based on the findings from the exploratory study and Task Technology Fit theory, we postulated the Navigation design, Ergonomic design, Content support, and Capacity as the essential dimension of the smartphone construct. Then, we proposed a research model and empirically tested hypotheses with the structural model analysis. The results reveal a significant positive impact of task and technology on TTF for smartphone usage to interact with learning materials in independent learning outside of classrooms; it also confirmed the TTF and performance have a direct effect on actual use.

Determinants factors of intention to adopt big data analytics in Malaysian public agencies

Purpose: This research objective was to analyze factors affecting IT practitioners’ behavioral intentions in adopting (BDA) using a combination of Initial Trust Model (ITM), Unified Theory Of Acceptance And Use Of Technology (UTAUT) AND Task-Technology Fit (TTF) Model acceptance models.Design/methodology/approach: Using a cross sectional survey, empirical data were collected. A total of 200 questionnaires were obtained and screened. 14 insufficient answers were subsequently discarded leaving 186 valid structured data review questionnaires. Data was analizad using the Partial Least Square Modeling of Structural Equations due to one of the best software for verifying structured data on structural equations modeling (SEM).Findings: Our findings show that two key factors determine behavioral intention to adopt BDA in government agencies. Firstly, the assumption that the technology is going to produce great results raises the expectation of performance. TTF was the second determinant factor. Surprisingly, Initial trust, on the other hand, had not been considered to be a key determinant of behavioural intention and was found to be adversely related to the BDA intentionResearch limitations/implications: These findings identify the crucial model, that would be useful to IT officers in public agencies in making investment choices and designing non-adopter-friendly outreach strategies because they have more barriers to acceptance than adopters and lead adopters in the reward ladder.Practical implications: The findings suggest significant recommendations and consequences for BDA systems practitioners and application developers, which could coincide with the successful implementation of BDA systems. This research gives practitioners an initial way to incorporate and endorse BDA activities in their organization to make the most of the advantages of revolutionary technology, particularly within public agencies.Originality/value: This study's model is helpful and promotes a theory for further BDA research. By utilizing the model, existing public agencies can know their own BDA capability, centered around activities with specifically tailored outcomes, organization dynamics, resources, skills and potential services.

Investigating e-wallet adoption of COVID19 intra-period among Malaysian youths': Integrated task-technology fit and technology acceptance model framework

As embodied in Malaysia's Vision 2020, Malaysia aims to become a cashless country. Therefore, the existing statistical data indicated that the e-wallet adoption rate remains at a low percentage. It has been a barrier for Malaysia in achieving the aims to become a cashless country. The use of e-wallet was also expected to rise amidst the Covid-19 pandemic; to optimize an intervention for the Covid-19 outbreak. Thus, the current study investigates the factors that correlate with the intention to use e-wallet during the Covid-19 pandemic. This study is designed using a quantitative approach through cross-sectional data. A total of 160 Malaysian youths participated and collected by using an online survey. Further, the Task-Technology Fit (TTF) model and Technology Acceptance Model (TAM) were integrated into this study with an extended variable, namely, perceived credibility. The analysis results showed that Individual-Technology Fit, Task-Technology Fit, Perceived Usefulness, Perceived Ease of Use and Perceived Credibility were significantly correlated to Covid19 intra-period e-wallet adoption. In conclusion, a considerable theoretical contribution was demonstrated by integrating TTF-TAM and Perceived Credibility in a single integrated model. The constructs in the TTF model (i.e., Individual-technology fit and task-technology fit) has positively related to the constructs in the TAM model (i.e., perceived usefulness and perceived ease of use). This study is useful to stakeholders and provides enhanced directions to meet market needs by understanding and predicting e-wallet user's post-pandemic behavior, thereby helping service providers attract new users and retain their existing users.

Extending the Task-Technology Fit (TTF) Model to E-Textbook Usage by Students and Instructors

Companies produce increasing numbers of textbooks in electronic format (e-textbooks) for use by students and instructors. One would be remiss, however, to think that university bookstores are not filled with hard copies of textbooks; many students and instructors still insist on using traditional paper copy textbooks. Many models exist to explain the factors that influence whether users adopt new technologies. The majority of this research, however, focuses on a single user group or isolated new technologies in the academic domain, such as learning management systems or digital video tools. The study extends the Task-Technology Fit (TTF) model to explore how both students and instructors use e-textbooks. New items were added to existing constructs of access, task technology fit, and perceived ease of use. The authors propose a new model and test the impact of perceived ease of use, access to technology, and the task technology fit on performance by both students and instructors. The results of factor analysis and structural equation modeling are reported.

Investigating the effect of learning management system transition on administrative staff performance using task-technology fit approach

Educational institutions are adopting learning management systems (LMS) to facilitate teaching and learning processes. During the last few years, many Universities have started upgrading their existing LMS by shifting to advance LMS. This shift requires students, academic as well as administrative staff to get acquainted with the functioning of the new system at the earliest, as any change in the system may impact their performance. The transition from old to new LMS requires time and affects the performance of users, especially administrative staff performance. The present study tries to investigate the effect of the transition on the performance of the administrative staff. The task-technology fit (TTF) model was adopted as the theoretical framework for the study. The data analysis was done using the PLS-SEM, to test the hypothesized relationships. The findings of the study confirm that mere usage of the new technology did not improve the performance rather, the task and technology characteristics need to be coordinated appropriately.