Modifying the technology acceptance model: The influence of perceived resources and organizational infrastructure

The Technology Acceptance Model (TAM) has been used in various settings to explain user acceptance of technology. The purpose of this study is to assess if the addition of the factor perceived management support in the technology acceptance model will explain user acceptance of e-learning systems in...

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Bibliographic Details
Main Author: Hernandez, Candice M.
Format: text
Language:English
Published: Animo Repository 2014
Online Access:https://animorepository.dlsu.edu.ph/etd_masteral/4673
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Institution: De La Salle University
Language: English
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Summary:The Technology Acceptance Model (TAM) has been used in various settings to explain user acceptance of technology. The purpose of this study is to assess if the addition of the factor perceived management support in the technology acceptance model will explain user acceptance of e-learning systems in a government organization. Survey respondents were 217 employees from the supervision group of a government financial institution, who currently use e-learning modules. Scales used were from previous studies on technology acceptance with Cronbachs alpha ranging from .76 to .98, with an original scale on perceived management support. Survey results were subjected to factor analysis, which yielded two new factors to be formed (perceived resources and organizational infrastructure) and combined several factors in the TAM (perceived ease of use &perceived management support and perceived usefulness & attitude towards use). Results were analyzed using path analysis which revealed poor fit with the current data and proposed research model (Fit Indices: 2/df = 26.984 CFI = .603 TLI (or NNFI) = .339 RMSEA = .395). A new model is presented with better fit with the current data (2/df = 2.28 CFI = .981 TLI (or NNFI) = .967 RMSEA = .074), integrating new factors perceived resources, organizational infrastructure, redefined perceived ease of use, and perceived benefits, however, this model failed to predict actual system use. Changing the focus from behavioral intention to attitude as the predictor of actual system use should be further investigated in future studies.