Journal Menu
Submit Manuscript via ScholarOne

EURASIA Journal of Mathematics, Science and Technology Education
Volume 13, Issue 6 (July 2017), pp. 2181-2195

DOI: 10.12973/eurasia.2017.01220a

Downloaded 66 times.

Research Article

Published online on May 09, 2017

How to reference this article?

 

A Study of Using Technology Acceptance Model and Its Effect on Improving Road Pavement Smoothness in Taiwan

Long-Sheng Huang & Chung-Fah Huang

Abstract

Using the technology acceptance model (TAM) as its theoretical foundation, this study intends to explore the use of Travelling Beam devices in road engineerings in Taiwan and offer suggestions based on its findings to encourage industry willingness for device deployment resulting in improving road pavement smoothness in Taiwan. The study subjects were pavement smoothness device operators in Taiwan. A total of 107 valid questionnaires were returned. The questionnaire results were analyzed using descriptive statistics, confirmatory factor analysis and structural equation modeling. Study results show that more training/support and perceived ease of use can lead to more willingness to use travelling beam devices and consequentially help improve pavement smoothness. Structural equation modeling (SEM) analysis results also indicate training/support, perceived ease of use and attitude will give users’ positive attitudes towards use of travelling beam devices.

Keywords: technology acceptance model (TAM); pavement smoothness; profilograph devices; confirmatory factor analysis (CFA); structural equation modeling (SEM)


References
  1. AASHTO PP49(2007), Certification of Inertial Profiling Systems.
  2. AASHTO (1962), The AASHTO Road Test Report 5, Pavement Research, HRB Special Report 61E.
  3. Agarwal, R., and Prasad, J. (1999), Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361-391.
  4. ASTM E950(2004), Standard Test Method for Measuring the Longitudinal Profile of Traveled Surfaces with an Accelerometer Established Inertial Profiling Reference.
  5. Bentler, P. M. (1990). Comparative Fit Indexes in Structural Models. Psychological Bulletin, 107(2), 238-246.
  6. Carry, W. N. & Irick, P.E. (1960), The Pavement Serviceability Performance Concept, Highway Research Bulletin 250.
  7. Chau, P.Y., (1996). An empirical assessment of a modified technology acceptance model, Management Information Systems. 13(2), 185-204.
  8. Davis, F. D. (1989), Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13(3), 319-340.
  9. Fishbein, M and I. Ajzen. (1975), Believe, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Addison-Wesley Publishing company.
  10. Haas, R., Hudson, R., and Zaniewki, J., (1994), Moderm Pavement Management, Kieger Publishing Company.
  11. Harris, N.K., Gonzalez, A., Obrien, E.J., McGetrick, P.(2010), Characterisation of pavement profile heights using accelerometer readings and a combinatorial optimisation technique, Journal of Sound and Vibration, 329(5), 497-508.
  12. Joao, L.V., Jaime, C.F., Pinho, A.C.M., Elisabete,F. (2010), 3D surface profile equipment for the characterization of the pavement texture – TexScan, Mechatronics, 20(6), 674-685.
  13. Kim, S., Ceylan, H., Gopalakrishnan, K. (2007), Initial smoothness of concrete pavements under environmental loads, Magazine of Concrete Research, 59(8), 599-609.
  14. King, W. R., and He, J. (2006), A meta-analysis of the technology acceptance model, Information & Management, 43(6), 740-755.
  15. Lin, J., Richard, L., Li, J.,  Chen, X.(2004), Measurement of Concrete Highway Rough Surface Parameters by an X-Band Scatterometer, IEEE Transactions on Geoscience & Remote Sensing, 42(6), 1188-1196.
  16. Losa, M.,and Leandri, P., (2011), The reliability of tests and data processing procedures for pavement macrotexture evaluation, International Journal of Pavement Engineering12(1), 59-73.
  17. Morris, M.G., & Dillon, A. (1997), How user perceptions influence software use, decision support systems, IEEE Software, 58-65.
  18. Ong, C. S., Lai, J. Y., and Wang, Y. S. (2004), Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies, Information & Management, 41(6), 795-804.
  19. Ongel, A., Lu, Q., Harvey, J., (2009), Frictional properties of asphalt concrete mixes, Transport, 162(1), 19-26.
  20. Szajna, B., (1996), Empirical evaluation of the revised technology acceptance model, Management Science, 42(1), 85- 92.
  21. Wang, K., and Li, Q. (2011), Pavement Smoothness Prediction Based on Fuzzy and Gray Theories, Computer-Aided Civil & Infrastructure Engineering, 26(1), 69-76.
  22. Shambhavi Impex, An ISO 9001:2008 certified company, (2003), http://www.shambhaviimpex.com/profile.html