Exploring technology adoption measures among academicians and its influence on their research practices and performance

The advent of technology may dramatically alter academic research and performance. This study uses the Unified Theory of Adoption and Use of Technology (UTAUT) and Task-Technology Fit (TTF) theories to examine how technology adoption influence Research Performance conducted with sample size of 1,35...

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Bibliographic Details
Main Authors: Indrajit Doddanavar, Mr. Amit Subramanyam, Vijaylaxmi Dombar, Lakshmi Subramanyam, Latha B R, Chandana H S
Format: Article
Language:English
Published: Italian e-Learning Association 2024-10-01
Series:Je-LKS: Journal of E-Learning and Knowledge Society
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Online Access:https://www.je-lks.org/ojs/index.php/Je-LKS_EN/article/view/1136038
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Summary:The advent of technology may dramatically alter academic research and performance. This study uses the Unified Theory of Adoption and Use of Technology (UTAUT) and Task-Technology Fit (TTF) theories to examine how technology adoption influence Research Performance conducted with sample size of 1,354 South Indian private institution Assistant Professors, with perception as a moderating factor. The research uses Structural Equation Modelling (SEM) with SmartPLS 4.0 to reveal that Performance Expectancy (PE) greatly influence Behavioral Intention (BI) to adopt technology. Higher Performance Expectancy (PE) leads to a stronger intention to use technology. Effort Expectancy (EE) also boosts BI, emphasizing the role of usability in setting user intentions. Technology adoption depends on Social Influence (SI), along with peer and social norms affect BI. Effective technology adoption requires Facilitating Conditions (FC) and enough resources and infrastructure. Task Characteristics (TC) and Technology Characteristics (TCh) greatly alter Task-Technology Fit (TTF), which enhances research procedures. TTF improves research practices but hurts research performance, demonstrating that improved techniques do not necessarily translate to better performance ratings, highlighting the intricacy of task-technology compatibility and research results.
ISSN:1826-6223
1971-8829