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Predicting the Intention to Use a Web‐Based Learning System: Perceived Content Quality, Anxiety, Perceived System Quality, Image, and the Technology Acceptance Model
Author(s) -
Calisir Fethi,
Altin Gumussoy Cigdem,
Bayraktaroglu Ayse E.,
Karaali Demet
Publication year - 2014
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20548
Subject(s) - lisrel , psychology , quality (philosophy) , structural equation modeling , applied psychology , anxiety , usability , technology acceptance model , automotive industry , social psychology , computer science , engineering , machine learning , human–computer interaction , philosophy , epistemology , psychiatry , aerospace engineering
The aim of this study is to determine the factors affecting blue‐collar workers’ intention to use a web‐based learning system in the preimplementation phase in the automotive industry. For that purpose an extended technology acceptance model (TAM) is proposed, which included factors such as image, perceived content quality, and perceived system quality as additions to the basic model. Data collected from 546 blue‐collar workers were used to test the proposed research model by using Linear Structural Relations software LISREL, Version 8.54. The findings of the study indicate that perceived usefulness is the strongest predictor of behavioral intention to use a web‐based learning system. In addition, a high proportion of perceived usefulness is explained by perceived content quality, and perceived ease of use is explained by perceived system quality and anxiety.