Conceptualizing task-technology fit and the effect on adoption – A case study of a digital textbook service

Rai, Ranvir Singh; Selnes, Fred

doi:10.1016/j.im.2019.04.004

Cited by 68 publications

(47 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The key challenge here lies in conceptualising the task environment as a construct for user adoption of the technology. Existing research literature related to the adoption of digital technologies talks about technology fit as a measure of efficiency and not effectiveness; while efficiency relates to doing the task better or faster than others or in an optimal manner, effectiveness relates to doing the right tasks in close alignment with goals and objectives (Rai and Selnes 2019). For example, if students gain confidence that digital classroom-based learning will not only improve their learning but also improve their grades, secure recognition among the potential employers and top universities, as well as enable better access to the faculty, then they are likely to be better motivated to continue digital-classroombased learning.…”

Section: Theoretical Background and Related Studiesmentioning

confidence: 99%

“…Though many researchers agree that smartphones and information technology have revolutionised the learning process, the impact of a technology-based virtual learning system has been found to be minimal (Chow and Shi 2014;Lee 2010;Ouyang et al 2017;Rai and Selnes 2019). The point of the argument is that, although there is an increasing level of initial acceptance for e-learning courses and specialisations among students, the completion percentage for e-learning courses is meagre.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Examining continuance intention in business schools with digital classroom methods during COVID-19: a comparative study of India and Italy

Chauhan

Goyal

Bhardwaj

et al. 2021

Behaviour & Information Technology

View full text Add to dashboard Cite

This study investigates and compares the continuance intention of full-time business school students and faculty in India and Italy who moved from traditional pedagogy style to the digital classroom due to the COVID-19 pandemic. The study integrates the Expectation Confirmation Model (ECM) and Task-Technology Fit (TTF) to examine their continuance intention. Survey data was collected from 396 business school students and 130 faculty members from India and Italy and analysed using SmartPLS 3 software. The study found that perceived usefulness, satisfaction, and task-technology fit significantly impact the continuance intentions of students and faculty. Multigroup analysis of students indicates that Italian students are more driven by task-technology fit as compared to Indian students in their continuance intention; in comparison, Indian students rely more on gaining experience and knowhow on technology. Finally, the multigroup study of faculty suggests that Italian educators have a comparatively stronger orientation towards the fit between digital classroom technology and a portfolio of related tasks. In comparison, their Indian counterparts rely more on the perceived usefulness of technology. The strength of relationship between task-technology fit and continuance intention is comparatively lower for faculty as compared to students in both countries. Finally, implications for theory and practice are discussed.

show abstract

Section: Theoretical Background and Related Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Examining continuance intention in business schools with digital classroom methods during COVID-19: a comparative study of India and Italy

Chauhan

Goyal

Bhardwaj

et al. 2021

Behaviour & Information Technology

View full text Add to dashboard Cite

show abstract

“…storage, data aggregation, analysis, data management and surveillance) applied to a variety of technological aspects that met the needs of individuals in BDA technology. Task and technologies also have a huge effect on the TTF capacity to predict success of users hailing from digital textbook service study (Rai & Selnes, 2019). If the individual demands for success were not met; creative information technology and program would be inopportune (Zhou, Lu & Wang, 2010).…”

Section: 33task-technology Fit (Ttf) Modelmentioning

confidence: 99%

“…Accordingly, we conclude that the successful implementation of BDA by public agencies depends substantially on balancing technology with the user role requirements, which previous researchers have not examined. In their survey, Rai and Selnes (2019) conceptualized TTF and even the integration of technology with a number of related tasks that help in achieving the development goal in an organization.…”

Section: 33task-technology Fit (Ttf) Modelmentioning

confidence: 99%

“…non-routines, coexistence, data access, and quantitative data analytics). TTF capability is derived from Task and technology to predict users' performance from various perspectives (Rai & Selnes, 2019). Innovative software and system technology would be unsuccessful if the performance criteria for a given task were not met (Shahbaz et al 2019).…”

Section: Hypothesismentioning

confidence: 99%

See 1 more Smart Citation

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

Sahid

Sani

Noordin

et al. 2021

JIEM

View full text Add to dashboard Cite

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.

show abstract

Understanding consumers' purchase intention in virtual reality commerce environment

Hsiao

Lin

2023

J of Consumer Behaviour

View full text Add to dashboard Cite

Virtual reality (VR) has developed rapidly and drawn the attention of businesses. E‐commerce practitioners have used VR to improve business performance and satisfy consumers' needs by enhancing the shopping experience and increasing purchase intention. To explore the effects of VR shopping platforms on purchase intention, this study developed a theoretical framework on the basis of task–technology fit. The framework comprises technological characteristics and user needs (intrinsic and extrinsic motivation) and can be used to investigate perceived needs–technology fit and identify factors affecting intention to purchase on VR platforms. This study distributed an online questionnaire and received 336 responses. Analysis was performed using partial least squares structural equation modeling. The results suggested that purchase intention is stronger when perceived needs–technology fit is closer. Hedonic needs play a vital role in perceived needs–technology fit. In terms of technological characteristics, relative advantage, and service compatibility strongly affect perceived needs–technology fit. In addition, feelings of spatial presence, a key component of VR, positively affect relative advantage, service compatibility, and trialability and negatively affect complexity. The implications of the findings are also discussed.

show abstract

Conceptualizing task-technology fit and the effect on adoption – A case study of a digital textbook service

Cited by 68 publications

References 40 publications

Examining continuance intention in business schools with digital classroom methods during COVID-19: a comparative study of India and Italy

Examining continuance intention in business schools with digital classroom methods during COVID-19: a comparative study of India and Italy

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

Understanding consumers' purchase intention in virtual reality commerce environment

Contact Info

Product

Resources

About