Predicting the Intention to Use a Web‐Based Learning System: Perceived Content Quality, Anxiety, Perceived System Quality, Image, and the Technology Acceptance Model

Fethi Calisir; Cigdem Altin Gumussoy; Ayse E. Bayraktaroglu; Demet Karaali

doi:10.1002/hfm.20548

journal article Aug 28, 2014

Predicting the Intention to Use a Web‐Based Learning System: Perceived Content Quality, Anxiety, Perceived System Quality, Image, and the Technology Acceptance Model

Fethi Calisir Cigdem Altin Gumussoy Ayse E. Bayraktaroglu Demet Karaali

Human Factors and Ergonomics in Manufacturing & Service Industries Vol. 24 No. 5 pp. 515-531 · Wiley

View at Publisher Save 10.1002/hfm.20548

Abstract

AbstractThe 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.

Topics

No keywords indexed for this article. Browse by subject →

References

77

[1]

Abbad M. M. "Looking under the bonnet: Factors affecting student adoption of e‐learning systems in Jordan" International Review of Research in Open and Distance Learning (2009) 10.19173/irrodl.v10i2.596

[2]

10.1016/0749-5978(91)90020-t

[3]

10.1037/019251

[4]

10.1016/0022-1031(86)90045-4

[5]

Al‐alak B. A. "Measuring the acceptance and adoption of e‐learning by academic staff" Knowledge Management & E‐Learning: An International Journal (2011)

[6]

10.1037/0033-2909.103.3.411

[7]

10.2307/2392322

[8]

10.2307/2393203

[9]

10.1037/0033-2909.107.2.238

[10]

10.1016/j.chb.2008.01.001

[11]

10.1111/j.1467-8535.2007.00742.x

[12]

10.1016/j.compedu.2009.05.007

[13]

10.1016/j.ijnurstu.2006.11.011

[14]

10.1111/j.1365-2575.2010.00356.x

[15]

10.1108/10662240510590324

[16]

10.1016/j.im.2008.02.003

[17]

10.1016/j.jengtecman.2009.10.003

[18]

10.2307/249008

[19]

10.1006/imms.1993.1022

[20]

10.1287/mnsc.35.8.982

[21]

10.1287/isre.3.1.60

[22]

10.4135/9781849209359

[23]

10.1177/002224378101800104

[24]

10.1108/00197850210417528

[25]

Hair J. F. (1998)

[26]

Hamid A. A. "e‐learning: Is it the “e” or the learning that matters?" The Internet and Higher Education (2002)

[27]

10.1108/02640470710829569

[28]

10.1504/ijil.2006.008419

[29]

Jöreskog K. (2003)

[30]

10.1016/j.chb.2010.08.012

[31]

10.1016/j.im.2006.05.003

[32]

10.1016/j.chb.2009.02.006

[33]

10.1016/j.compedu.2009.06.014

[34]

10.1016/j.compedu.2012.10.001

[35]

10.1016/j.chb.2006.12.001

[36]

10.1016/j.compedu.2009.09.002

[37]

10.1108/14684520610706406

[38]

10.1016/s0378-7206(01)00143-4

[39]

Li Y. "An empirical study on behavioral intention to reuse e‐learning systems in rural China" British Journal of Educational Technology (2011)

[40]

10.1016/j.compedu.2006.09.007

[41]

10.1108/eum0000000005963

[42]

10.1016/j.compedu.2008.11.002

[43]

10.1016/s0378-7206(00)00059-8

[44]

Martin G. "Cross‐border higher education, who profits" Journal for Critical Education Policy Studies (2011)

[45]

10.1080/01449290600958965

[46]

10.1287/isre.2.3.192

[47]

Ndubisi N. O. "Factors of online learning adoption: A comparative juxtaposition of the theory of planned behavior and the technology acceptance model" International Journal on E‐Learning (2006)

[48]

10.1016/j.chb.2004.03.006

[49]

10.1016/j.im.2003.08.012

[50]

Park S. Y. "An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e‐learning" Educational Technology & Society (2009)

Showing 50 of 77 references

Cited By

126

Exploring Iranian english as a foreign language teachers’ acceptance of ChatGPT in english language teaching: Extending the technology acceptance model

Hoora Dehghani, Amir Mashhadi · 2024

Education and Information Technolog...

Research on the Influence of E-Learning Quality on the Intention to Continue E-Learning: Evidence from SEM and fsQCA

Hao Zheng, Yu Qian · 2023

Sustainability

Antecedents and consequences of behavioural intention to use virtual reality in tourism: Evidence from Gen-Y and Gen-Z consumers in Egypt

Zakaria Elkhwesky, Abuelhassan Elshazly Abuelhassan · 2023

Tourism and Hospitality Research

Faculty acceptance of the utilization of learning management systems in teaching

Moses K. Asamoah, Yaw Oheneba-Sakyi · 2023

E-Learning and Digital Media

Educational Technology Adoption: A systematic review

Andrina Granić · 2022

Education and Information Technolog...

The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence

Feridun Kaya, Fatih Aydin · 2022

International Journal of Human–Comp...

System Quality and Student’s Acceptance of the E-learning System: The Serial Mediation of Perceived Usefulness and Intention to Use

Maha Ismail Alkhawaja, Mutia Sobihah Abd Halim · 2022

Contemporary Educational Technology

New Schemes for Investment in of Small and Medium-Sized Enterprises of China: Role of Access to Finance, Innovation, and Sustainability

Xuelian Tang · 2022

Frontiers in Psychology

Technology acceptance model in educational context: A systematic literature review

Andrina Granić, Nikola Marangunić · 2019

British Journal of Educational Tech...

Decision to adopt online collaborative learning tools in higher education: A case of top Malaysian universities

Elaheh Yadegaridehkordi, Liyana Shuib · 2018

Education and Information Technolog...

Metrics

126

Citations

77

References

Details

Published: Aug 28, 2014
Vol/Issue: 24(5)
Pages: 515-531
License: View

Authors

F

Fethi Calisir

Industrial Engineering Department, Management Faculty Istanbul Technical University Macka Istanbul Turkey

C

Cigdem Altin Gumussoy

Industrial Engineering Department, Management Faculty Istanbul Technical University Macka Istanbul Turkey

A

Ayse E. Bayraktaroglu

Industrial Engineering Department, Management Faculty Istanbul Technical University Macka Istanbul Turkey

D

Demet Karaali

Mercedes‐Benz Turk A.S. Marketing Center Bahcesehir Istanbul Turkey

Cite This Article

Fethi Calisir, Cigdem Altin Gumussoy, Ayse E. Bayraktaroglu, et al. (2014). Predicting the Intention to Use a Web‐Based Learning System: Perceived Content Quality, Anxiety, Perceived System Quality, Image, and the Technology Acceptance Model. Human Factors and Ergonomics in Manufacturing & Service Industries, 24(5), 515-531. https://doi.org/10.1002/hfm.20548

Predicting the Intention to Use a Web‐Based Learning System: Perceived Content Quality, Anxiety, Perceived System Quality, Image, and the Technology Acceptance Model

You May Also Like