Factors of the Technology Acceptance Model for Construction IT
Source abstract
Abstract
The use of information technology is spreading in the construction field. However, the use of information technology in the construction field does not conform to the requirements and characteristics of users who use information technology. This fact is blindly accepted by the government and client demands, which is an impediment to the dissemination of information technology in the construction field. To improve the use of information technology in the construction field, this study analyzes the factors of acceptance of information technology according to the characteristics of users who use information technology in the construction field based on Davis’ technology acceptance model. As a result of the analysis, we found that if users consider IT in the construction industry easy to use, spontaneous attitude and behavioral intention are to be expected. Moreover, acceptance type, educational satisfaction, usage enjoyment, and usage experience are the factors that impact perceived usefulness, and educational satisfaction and usage enjoyment impact perceived ease of use as well. This study aims to derive factors that maximize the approachability and usefulness of users through the use of a technology acceptance model in construction prior to the application of new information technology in the construction field.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Technology Adoption and User Behaviour
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Architecture, Sahmyook University, Seoul 01795, Korea
Hanyang Corporation, Seoul 05836, Korea
Funding
the National Research Foundation of Korea(NRF)
References (30)
Show source-provided references
1. Moon, J.H., and Song, B.K. (2003). PMIS Solutions in the Korean Construction Industry, Construction & Economy Research Institute of Korea.
2. JBKnowledge (2017). 2017 The 6th Annual Construction Technology Report, JBK Consulting.
3. Sichel, D.E. (1997). The Computer Revolution: An Economic Perspective, Brookings Institution.
4. An empirical assessment of a modified technology acceptance model10.1080/07421222.1996.11518128 ↗
5. Perceived usefulness, perceived ease of use, and user acceptance of information technology10.2307/249008 ↗
6. TAM or just plain habit: A look at experienced online shoppers10.4018/joeuc.2003070101 ↗
7. The theory of planned behavior10.1016/0749-5978(91)90020-T ↗
8. A survey on user attitudes and behavioral intention for identifying preventive campaign measures for illegal online downloading
9. The theory of planned behavior: The effects of perceived behavioral control and self-efficacy10.1111/j.2044-8309.1995.tb01058.x ↗
10. A study on the effects of organizational culture and job characteristic on public service motivation in the police
11. Individual differences and MIS success: A review of the empirical literature10.1287/mnsc.25.10.966 ↗
12. Pratkans, A.R., Breckler, S.J., and Greenward, A.G. (1989). On the Power and Functionality of Attitudes: The Role of Attitude Accessibility, Attitude structure and function, Lawrence Erlbaum Associates.
13. Testing the determinants of microcomputer usage via a structural equation model10.1080/07421222.1995.11518061 ↗
14. A feedback model to understand information system usage10.1016/S0378-7206(98)00026-3 ↗
15. Using perceived ease of use and perceived usefulness to predict acceptance of the World Wide Web10.1016/S0169-7552(98)00028-2 ↗
16. Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage10.2307/3250951 ↗
17. Rogers, E.M. (1995). Diffusion of Innovations, Free Press.
18. An Exploratory Field Study of Differences in Information Technology Use Between More- and Less-Innovative Middle Managers10.1016/S0378-7206(99)00006-3 ↗
19. The use of spreadsheets in organizations: Determinants and Consequences10.1016/S0378-7206(96)00008-0 ↗
20. Diffusion of e-mail: An organizational learning perspective10.1016/S0378-7206(96)01070-1 ↗
21. Integrating perceived playfulness into expectation-confirmation model for web portal context10.1016/j.im.2004.04.003 ↗
22. The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance10.1016/j.ijhcs.2006.05.001 ↗
23. Determinants of user acceptance of digital libraries—An empirical examination of individual differences and systems characteristics10.1080/07421222.2002.11045692 ↗
24. Applying the technology acceptance model and flow theory to online consumer behavior10.1287/isre.13.2.205.83 ↗
25. Empirical evaluation of the revised technology acceptance model10.1287/mnsc.42.1.85 ↗
26. Developing and testing a global model to explain the adoption of websites by users in rural tourism accommodations10.1016/j.ijhm.2012.02.005 ↗
27. User acceptance of wireless short messaging services: Deconstructing perceived value10.1016/j.im.2006.10.005 ↗
28. The application of technology acceptance model(TAM) on health tourism e-purchase intention predictors in Thailand
29. A theoretical integration of user satisfaction and technology acceptance10.1287/isre.1050.0042 ↗
30. Van de Ben, A.H., and Ferry, D.L. (1980). Measuring and Assessing Organizations, Wiley.