Task-technology Fit Model Research Articles

Task-Technology Fit and Technology Acceptance Model Application to Structure and Evaluate the Adoption of Social Media in Academia

The purpose of this article was to reduce the dissimilarities in the literature regarding the use of social media for training and its impact on students’ academic performance in higher education institutions. The main method of data collection for task-technology fit (TTF) and the technology acceptance model (TAM) was a questionnaire survey. This research hypothesizes that TTF applied to social media for learning will affect technology, task, and social characteristics that in turn improve students’ satisfaction and students’ academic performance. It also posits that the behavioral intent to use social media for learning will affect comprehension efficiency, ease of use, and enjoyment, all of which also improve students’ satisfaction and students’ academic performance. The data collection questionnaire was conducted with 162 students familiar with social media. Quantitative structural equation modeling was employed to analyze the results. A significant relationship was found between technology, task, and social features with TTF for utilizing social media for academic purposes, all of which fostered student enjoyment and improved outcomes. Similarly, a clear relationship was found between comprehension efficiency, ease of use, and enjoyment with behavioral intentions to utilize social media for academic purposes that positively affected satisfaction and achievement. Therefore, the study indicates that TTF and behavioral intentions to use social media improve the active learning of students and enable them to efficiently share knowledge, information, and discussions. We recommend that students utilize social media in pursuit of their educational goals. Educators should also be persuaded to incorporate social media into their classes at higher education institutions.

Understanding the Sustainable Usage Intention of Mobile Payment Technology in Korea: Cross-Countries Comparison of Chinese and Korean Users

Mobile payment (m-payment) enables consumers to perform their payment tasks via a mobile technology platform. In this study, we summarized, evaluated, and expanded upon the literature about m-payment usage intention by synthetically integrating the advantages of three information systems theories into an integrated model, which details the complementary relationship between the objective measures, subjective perception of m-payment services, and m-payment technology–task fit characteristics. Based on a sample of 908 individuals in two different Kakaopay user groups (467 Chinese Kakaopay users in Korea and 441 local Korean Kakaopay users) and the three-model integrated optimization, we integrated the unified theory of acceptance and use of technology model (UTAUT), the information systems success model (D&M ISS), and the task-technology fit model (TTF), considering moderating variables (Chinese and Korea experienced consumers) and multi-group analysis. We chose the factors influencing Chinese and Korean consumers’ usage intention as the research objects, and ultimately achieved our purpose of more accurately predicting consumer behavior patterns to expand the scale of potential Chinese consumers. The empirical results theoretically contribute to academic and practical solutions for the Korean m-payment product and help technology suppliers to stimulate the sustainable growth of Korean mobile payment consumer groups in Korea.

THE ACCEPTABILITY OF PARTICIPATORY BANKING PRODUCTS BY SMES: A CONCEPTUAL FRAMEWORK

Designed to contribute to the development of the real economy, the Islamic banking sector has grown significantly in the world during the last 40 years due to its ethical, religious and solidarity dimensions. It is set up to boost the banking system, to meet the needs of unmet customers and to give new hope to Small and Medium Enterprises (SMEs) facing difficulties in accessing conventional bank financing. Islamic banks can contribute to the development of these companies and satisfy their financial needs. This article discusses the different factors influencing the decision of SME managers to adopt financing by participatory banks products. In this sense, the conceptual model presented is intended to study the level of acceptability of the participatory banks products by the SMEs starting from the application of the decomposed theory of planned behavior and the task-technology fit model.

Integrating TTF and IDT to evaluate user intention of big data analytics in mobile cloud healthcare system

ABSTRACTWith the rapid development of mobile technology and cloud computing, observers have recognised the vast potential for mobile cloud healthcare systems in individualised preventive healthcare. Using a mobile cloud healthcare system and big data analysis, this study aids young users in preventive healthcare against diabetes. It also integrates the Task-Technology Fit (TTF) and Innovation Diffusion Theory (IDT) models to evaluate user intentions to use the system, and tests this model using data collected from 423 young people. Results show that task-technology fit is significantly affected by task characteristics and technology characteristics, and also user intention of using the mobile cloud healthcare system is affected by task-technology fit, complexity, and relative benefits. However, observability has no significant effect on user intentions of using the mobile cloud healthcare system. These findings provide some interesting theoretical insights into the usage of the mobile cloud healthcare system. The direct effects of TTF and IDT on young users′ intention of using the mobile cloud healthcare system are shown. This study thus makes an important contribution by highlighting the role that TTF and IDT may have in affecting use of the mobile cloud healthcare system.

How does task-technology fit influence cloud-based e-learning continuance and impact?

PurposeAccording to expectation–confirmation model (ECM) and task-technology fit (TTF) model, the purpose of this paper is to examine the role of TTF in students’ cloud-based e-learning continuance and evaluate whether TTF affects students’ perceived impact on learning of the cloud-based e-learning system within the educational institution.Design/methodology/approachSample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 500 questionnaires were distributed in the campus, and 391 (78.2 percent) usable questionnaires were analyzed using structural equation modeling in this study.FindingsThis study’s results verified that both task characteristics and technology characteristics affected students’ perceived TTF, which significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, and these in turn directly or indirectly led to their continuance intention of the system and perceived impact on learning; essentially, the results strongly supported the research model integrating ECM and TTF model via positioning key constructs as the drivers with all hypothesized links being significant.Originality/valueThis study contributes to an understanding of the TTF in explaining students’ cloud-based e-learning continuance that is difficult to explain with only their utilitarian perception of the cloud-based e-learning system, and further places considerably more emphasis upon students’ perceived impact on learning greatly driven by their TTF in the system. Thus, this study’s empirical evidence on incorporating ECM and TTF model can shed light on the outcome for cloud-based e-learning continuance and enhance better understanding of a richer post-adoption model.

An integrated model for m-banking adoption in Saudi Arabia

PurposeThe purpose of this paper is to identify and examine the most important factors that could predict the Saudi customer’s continued intention towards adoption of mobile banking.Design/methodology/approachThe proposed conceptual model was based on the technology acceptance model (TAM) and task-technology fit (TTF) model. This is also expanded by considering two additional factors: perceived privacy and perceived security. By using a self-administered questionnaire, the data were collected from a convenience sample of Saudi banking customers from different parts of Saudi Arabia.FindingsThe main results based on structural equation modelling analyses supported the impact of perceived privacy, perceived security, perceived usefulness and TTF on the customers’ continued intention to use mobile banking.Research limitations/implicationsThe moderation influence of the demographic factors (i.e. age, gender, income level, educational level) was not tested. The data were also collected using a self-report questionnaire; however, it would be more accurate to utilise more statistics from the bank database about the users of m-banking.Originality/valueThis study represents a worthy attempt to test such novel technology (m-banking) in the KSA where there is a scarcity of literature. A considerable theoretical contribution was also made by integrating the TTF model with the TAM in addition to consider privacy and security in one single model. Moreover, considering both perceived privacy and security in the current model creates an accurate picture about the adoption of m-banking especially as there are a limited number of m-banking studies that have considered privacy and security alongside the TTF model and TAM in the same model.

Extending a TAM–TTF model with perceptions toward telematics adoption

Purpose The purpose of this paper is to examine a framework integrating the technology acceptance model (TAM), individuals’ task–technology fit (TTF) and perceptions toward adopting automobile telematics devices. Design/methodology/approach This study integrated the TAM with TTF to understand individual perceptions of a technology’s value. In addition, the intrinsic motivational factors toward technology usage, including positive perceptions (perceived enjoyment, personal innovation and perceived uniqueness) and negative perceptions (perceived risk and performance gap), were considered in the model. Furthermore, the moderating effect of driving experience was examined. Findings The perceived usefulness (PU) of telematics as well as perceived ease of use (PEOU) affected drivers’ adoption intentions. PEOU had a greater effect on adoption intentions than PU, and technology characteristics had a greater effect on TTF than task characteristics. Moreover, individuals’ perceptions of perceived enjoyment and uniqueness affected PU and PEOU. The negative perceptions of perceived risk and performance gap affected PU and PEOU, respectively. Furthermore, driving experience significantly weakened the relationship between PU and intentions. Originality/value Telematics is a niche market due to the development of the Internet of Things, but users’ adoption intentions remain unknown. This study constructed a more comprehensive model and tested the impacts of certain variables on telematics adoption, with driving experience as a crucial moderator.

Investigating Employee Performance Impact with Integration of Task Technology Fit and Technology Acceptance Model: The moderating role of self-efficacy

This study sheds light on the relationship between technology factors and employee performance impact. The current study develops an integrated technology model underpinned task technology fit (TTF) and technology acceptance model (TAM) to investigate employee performance impact in Saudi public organisations. This study goes a step further and examined the moderating effect of self-efficacy between internet usage and employee satisfaction. Structural equation modelling (SEM) was used for statistical analysis. Findings revealed that altogether technology acceptance model and task technology fit explained R2 54.7% variance in internet usage and R2 60.9% variance in employee performance. Results also confirmed that self-efficacy moderate the relationship between internet usage and employee satisfaction. This study is unique as it contributes to information system literature and confirmed two-well known technology theories (TTF and TAM) with relation to employee performance impact.

Visual Analytics Adoption in Business Enterprises

Visual analytics is increasingly being recognized as a source of competitive advantage. Yet, limited research has examined the factors deriving it organizational adoption. By integrating the technology acceptance model (TAM) with the task-technology fit (TTF) model, this research developed a model for visual analytics adoption in business enterprises. To test the research model, data was collected through a questionnaire survey distributed to 400 business professionals working in a variety of industries in Jordan. Collected data were tested and analyzed using structural equation modeling (SEM) technique. Findings of this research confirmed the applicability of the integrated TAM/TTF model to explain the key factors that affect the adoption of visual analytics systems for work-related tasks. Specifically, the results of this research demonstrated that the task, technology, and user characteristics are fundamental and influential antecedents of TTF, which in turn has a significant positive effect on the perceived usefulness and perceived ease of use of visual analytics systems. Additionally, there are significant positive effects from perceived usefulness and perceived ease of use toward users' intention to adopt visual analytics systems, and a firm relationship between perceived ease of use and perceived usefulness of visual analytics systems. Together all these constructs explain 59.9% of the variance in user's intention to adopt visual analytics systems at the workplace. Findings of this research provide several important implications for research and practice, and thus should help in the design and development of more user-accepted visual analytics systems and applications.

Technology in the Classroom: Teachers’ Technology Choices in Relation to Content Creation and Distribution

Aim/Purpose: Teachers are being asked to integrate mobile technologies into their content creation and distribution tasks. This research aims to provide an understanding of teachers taking on this process and whether the use of technology has influenced their content creation and distribution in the classroom. Background: Many claim that the use of technology for content creation and distribution can only enhance and improve the educational experience. However, for teachers it is not simply the integration of technology that is of prime concern. As teachers are ultimately responsible for the success of technology integration, it is essential to understand teachers’ viewpoints and lived technology experiences. Methodology: The Task-Technology Fit (TTF) model was used to guide interpretive case study research. Six teachers were purposively sampled and interviewed from a private school where a digital strategy is already in place. Data was then analysed using directed content analysis in relation to TTF. Contribution: This paper provides an understanding of teachers’ mobile technology choices in relation to content creation and distribution tasks. Findings: Findings indicate that teachers fit technology into their tasks if they perceive the technology has a high level of benefit to the teaching task. In addition, the age of learners and the subject being taught are major influencers. Recommendations for Practitioners: Provides a more nuanced and in-depth understanding of teachers’ technology choices, which is necessary for the technology augmented educational experience of the future. Recommendations for Researchers: Provides an unbiased and theoretically guided view of mobile technology use with content creation and distribution tasks. Impact on Society: Teachers do not appear to use technology as a de facto standard, but specifically select technology which will save them time, reduce costs, and improve the educational experiences of their learners. Future Research: A mixed-method approach, including several diverse schools as well as learners would enrich the findings. Furthermore, consideration of hardware limitations and lack of software features are needed.

A hybrid model for exploring the antecedents of cloud ERP continuance

PurposeThis study aims to propose a hybrid model based on expectation–confirmation model (ECM), DeLone and McLean IS success model and task-technology fit (TTF) model to examine whether quality factors and TTF as the antecedents to user beliefs can affect organizational users’ continuance intention of cloud enterprise resource planning (ERP).Design/methodology/approachSample data for this study were collected from end-users of cloud ERP working in companies in Taiwan. A total of 370 questionnaires were distributed in the 37 sample companies, and 315 (85.1 per cent) usable questionnaires were analyzed using structural equation modeling in this study.FindingsThis study’s findings indicated that users’ perceptions of system quality, information quality and TTF all contributed significantly to their satisfaction, confirmation and perceived usefulness (PU) of cloud ERP, which in turn directly or indirectly led to their continuance intention of cloud ERP; that is, the results strongly supported the hybrid model integrating ECM, DeLone and McLean IS success model and TTF model with all hypothesized links being significant.Originality/valueEmpirically, this study’s research model capturing ECM, DeLone and McLean IS success model and TTF model has significantly shed light on the possible formulation of a richer post-adoption model. Noteworthily, considerably more attention should be paid to the fit between information-related characteristics and cloud ERP users’ work goals and needs, while TTF, based on both system-related and information-related technology characteristics, significantly contributes to users’ satisfaction, confirmation and PU, which together directly or indirectly explain their intention to continue using cloud ERP.

중국 여행사 모바일 앱 사용의도에 영향을 미치는 요인에 관한 연구 : 기술수용모형과 과업기술적합의 통합모형을 적용하여

The purpose of this study is to understand the relationship among factors affecting the intention of using mobile APPs based on the theoretical foundations of the Technology Acceptance Model (TAM) and the Task Technology Fit (TTF) Model. A survey was conducted targeting Chinese tourists who had experienced mobile APPs. A total of 505 questionnaires were analyzed using the structural equation model. The findings of this research are presented as follows: First, task technology fit of Chinese travel agencies’ mobile APPs has significant influence on behavioral intention. Second, perceived usefulness and perceived ease of use of Chinese travel agencies’ mobile APPs has a significant effect on behavioral intention. Third, task technology fit has significant effect on perceived usefulness and perceived ease of use.

Exploring the Determinants of MOOCs continuance intention

In our current information-based society in which knowledge is a fundamental asset to production, the capability to utilize information and produce knowledge with the use of information technology (IT) has become essential to learning. Massive Open Online Courses (MOOCs) have recently been introduced in light of such changes and are recognized as an alternative to open education. MOOCs’ capabilities are being acknowledged in lifelong education in terms of reeducation and knowledge sharing, and also in terms of improving teaching quality, and improving university students’ levels of creativity and integrated thinking by supporting high-level content and teaching. Therefore, this study presents an extended research model that combines information system (IS) continuance and task-technology fit models. Our study researches previous literature, revealing factors of continuous use after accepting MOOCs from the learner’s perspective, and analyzes the model empirically. The ideal environment for MOOCs learners is evaluated, and a strategic approach to the successful settlement and diffusion of MOOCs is presented based on this study’s findings.

Synergy between green supply chain management and green information systems on corporate sustainability: an informal alignment perspective

At the corporate level, green innovation is essential for environment protection and sustainable development. Green supply chain management (GSCM) and green information system (GIS) are two important pillars of green innovation. This study investigates the possible alignment between them in terms of the synergistic effect on corporate sustainability. Based on the task-technology fit model, GSCM and GIS can be viewed as the task- and technology-side endeavors. The extant conceptualization of the fit between a task and a technology assumes their interdependence, but efficiency-oriented GSCM and technology-driven GIS are relatively independent from each other as they can be carried out separately. Formed on the basis of spontaneous employee participation in both, their alignment is rather informal than formal. Unlike the regular task-technology fit from a top-down arrangement, such a bottom-up alignment is not the necessary condition for GSCM and GIS to take effects, but adds to their direct impacts on green innovation outcome in a one-plus-one-greater-than-two manner. Survey observations gathered from over 300 organizations in China confirm that the informal alignment between GSCM and GIS enhances economic, operational, environmental and social performances on top of their primary contributions. The findings regarding the synergy between GSCM and GIS on corporate sustainability provide researchers and practitioners helpful insights on how to optimize green innovation effectiveness.

Does culture influence m-banking use and individual performance?

We show evidence on the influence of culture on m-banking use and individual performance, by using a combination of the task-technology fit (TTF) model and two of Hofstede’s cross-cultural dimension scales: uncertainty avoidance and individualism. On the basis of a sample of 204 m-banking users, we show that individualism moderates the relationship between TTF and use, and uncertainty avoidance moderates the relationship between TTF and individual performance. The remaining constructs, which represent the core of the TTF model, can still empirically explain TTF, use, and individual performance of m-banking. Strategies grounded in these factors are suggested for m-banking service providers to better attract and retain users.

Impact of BYOD on organizational commitment: an empirical investigation

PurposeBring your own device (BYOD) refers to employees utilizing their personal mobile devices to perform work tasks. Drawing on the job demands-resources (JD-R) model and the task-technology fit (TTF) model, the purpose of this paper is to develop a model that explains how BYOD affects employee well-being (through job satisfaction), job performance self-assessment, and organizational commitment through perceived job autonomy, perceived workload and TTF.Design/methodology/approachSurvey data from 400 full-time employees in different industry sectors in Mauritius were used to test a model containing 13 hypotheses using confirmatory factor analysis and structural equation modeling.FindingsThe SEM results support the hypothesized model. Findings indicate that BYOD indirectly affects job satisfaction, job performance and organizational commitment via job demands (perceived workload), job resources (perceived job autonomy) and TTF. Further, job resources influences job demands while TTF predicted job performance. Finally, job satisfaction and job performance self-assessment appear to be significant determinants of organizational commitment.Practical implicationsThe findings are congruent with the JD-R and TTF models, and confirm that BYOD has an impact on job satisfaction, job performance self-assessment and organizational commitment. This could inform organizations’ policies and practices relating to BYOD, leading to improved employee well-being, performance and higher commitment.Originality/valueThe expanded model developed in this study explains how employee well-being, performance and organizational commitment are affected by BYOD, and is one of the first studies to investigate these relationships.

A conceptual framework for technology-enabled and technology-dependent user behavior toward device mesh and mesh app

The device mesh and mesh app revealed by Gartner as the future strategic technology trend are able to predict people's need from their historic data, then provides the needed services or service innovation to support their activity engagement. However, many theories have identified that it is the motivation, rather than technology, that drives people to engage in activities or tasks. For this reason, this study builds a conceptual framework by integrating the extant logic and theories to explore how future technology would generate benefits for people. It integrates task-technology fit (TTF) model and motivation theory (mainly expectancy-value theory) to explain such technology user behavior. It also points out the difference between technology-enabled and technology-dependent user behavior and concludes that too much emphasis on the role of technology with too little attention on motivation would distort technology user behavior, and the role of technology as well.

Cloud Computing Fitness for E-Government Implementation: Importance-Performance Analysis

The means through which governments deliver services and the way they operate may be considerably enhanced through cloud computing. It can help to address e-government implementation challenges and revolutionize e-government systems in terms of cost savings and the professional use of resources. The aim of this paper is to analyze the importance and performance of the factors that influence the fitness of cloud computing for e-government implementation. This paper integrates the task technology fit model with the diffusion of innovation theory to address this issue. Yemeni public institutions were identified as sources for data collection and 292 information technology employees participated as sample respondents for a structured questionnaire. Security, compatibility, relative advantage, and tasks were the variables found to affect the fitness of cloud computing for e-government activities. However, no impact was seen from the standpoints of trialability and complexity of the technology. In terms of assessing the fitness of cloud computing for e-government services, a greater understanding among policy formulators was sought through the importance-performance matrix analysis (IPMA). The results of IPMA can help identifying areas for strategic focus to assess cloud computing as an alternative technology to implement e-government services.

Focus Section Health IT Usability: Applying a Task-Technology Fit Model to Adapt an Electronic Patient Portal for Patient Work.

Although electronic patient portals are offered by most health care organizations, poor usability and poor fit to patient needs may pose barriers to adoption. We collaborated with an academic hospital to conduct iterative user evaluation of a newly deployed portal designed to deliver inpatient data upon hospital discharge. Three evaluators applied heuristic usability evaluation and conducted 23 individual user testing sessions with patients with chronic disease or managing the care of family members with chronic disease. Evaluation and development/improvement were conducted iteratively. User testing and analysis of qualitative data were both conducted from the perspective of a task-technology fit framework, to assess the degree of fit between the portal and patient work. Ability to complete health information management tasks, perceived usability, and positive comments from users improved over the course of the iterative development. However, patients still encountered significant difficulties accomplishing certain tasks such as setting up proxy accounts. The problems were most severe when patients did not start with a clear understanding of tasks that they could accomplish. In exploring the portal, novice users frequently described anecdotes from their own medical history or constructed fictional narratives about a hypothetical patient. Chronic illness imposes a significant workload on patients, and applying a task-technology framework for evaluation of a patient portal helped improve the portal's fit to patient needs. However, it also revealed that patients often lack a clear understanding of tasks that would help them accomplish personal health information management. Portal developers may need to educate patients about types of patient work involving medical centers, in a way that developers of clinical information systems do not need to do. An approach to doing this might be to provide narratives about hypothetical patients.

Predicting the acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory

Online learning courses have expanded the educational landscape to distant and disadvantaged areas. Although such courses have generated extensive interest, there is as yet sparse literature evaluating the determinants of online course acceptance, especially in developing countries. Seeking to close this gap, this study examines the factors influencing students’ adoption of Massive Open Online Courses (MOOCs) in a developing country by applying an integrated framework incorporating the task-technology fit model, social motivation, and self-determination theory. In addition, the study investigates the moderating effect of perceived reputation on students’ adoption behavior. A self-administered survey was employed for data collection and valid responses from 414 participants were used for testing the proposed model. The data was analyzed using structural equation modeling through Smart-PLS. The results establish the significant contribution of task characteristics and technology characteristics in facilitating task-technology fit, and that the fit positively influences behavioral intentions. Moreover, social recognition, perceived competence, and perceived relatedness have positive and significant effects on the behavioral intentions of the students. This research also reveals that perceived reputation has an important moderating effect on the students’ usage behavior. The study results provide both practical and theoretical insights to enrich the understanding of the paradigm shift due to MOOCs and online education.