AutoCAD: Examination of Factors Influencing User Adoption - Publication - MOST Wiedzy

Search

AutoCAD: Examination of Factors Influencing User Adoption

Abstract

The primary purpose of the research is to examine and validate determinants of user intention to use AutoCAD software, utilising the constructs from prior studies in a more integrated model. The paper proposes a revised Technology Acceptance Model (TAM) for measuring the adoption of AutoCAD. In the study, a latent construct PPA (perceived physical accessibility) was added to the proposed research model as a new determinant of AutoCAD adoption. An online survey of AutoCAD users was conducted to collect data. This data was empirically used to test the proposed research model. The Structural Equation Modelling (SEM) technique was used to evaluate the causal model, and the confirmatory factor analysis was performed to examine the reliability and validity of the measurement model. The study results show that user behavioural intention to use AutoCAD is significantly affected by three determinants: perceived usefulness, perceived ease of use and perceived physical accessibility of the software. This finding contributes to an expanded understanding of the factors that promote acceptance of AutoCAD software. Moreover, the main contribution of this study is to verify the impact of the added PPA variable on the behavioural intention to use and the actual use of AutoCAD, and also to create measurement scales for this new latent variable in TAM.

Citations

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Details

Category:
Articles
Type:
artykuły w czasopismach
Published in:
Engineering Management in Production and Services no. 12, pages 45 - 56,
ISSN: 2543-6597
Language:
English
Publication year:
2020
Bibliographic description:
Baj-Rogowska A.: AutoCAD: Examination of Factors Influencing User Adoption// Engineering Management in Production and Services -Vol. 12,iss. 1 (2020), s.45-56
DOI:
Digital Object Identifier (open in new tab) 10.2478/emj-2020-0004
Bibliography: test
  1. Agarwal, R., & Prasad, J. (1998). A conceptual and opera- tional definition of personal innovativeness in the domain of information technology. Information Sys- tems Research, 9(2), 204-215. open in new tab
  2. Ahmad, S. Z., & Khalid, K. (2017). The adoption of M- government services from the user's perspectives: Empirical evidence from the United Arab Emirates. Journal of Information Management, 37(5), 367-379. open in new tab
  3. Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, United States: Prentice-Hall.
  4. Akkucuk, U. (Ed.) (2014). Handbook of Research on Devel- oping Sustainable Value in Economics. Finance and Marketing. United States: IGI Global. open in new tab
  5. Bazelais, P., Doleck, T., & Lemay, D. J. (2017). Investigating the predictive power of TAM: A case study of CEGEP students' intentions to use online learning technolo- gies. Education and Information Technologies, 23(1), 93-111. doi: 10.1007/s10639-017-9587-0 open in new tab
  6. Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. In: K. A. Bollen & J. S. Long (Eds.), Testing structural equation models. Newbury Park, United States: Sage Publications. open in new tab
  7. Changchit, C., & Chuchuen, C. (2018). Cloud computing: An examination of factors impacting users' adoption. Journal of Computer Information Systems, 58(1), 1-9. open in new tab
  8. Charles, V., & Kumar, M. (2014). Performance Measure- ment and Management. Cambridge, United King- dom: Scholars Publishing.
  9. Chintalapati, N., & Daruri, V. S. K. (2016). Examining the Use of YouTube as a Learning resource in higher ed- ucation: Scale development and Validation of TAM model. Telematics and Informatics, 34(6), 853-860. doi: 10.1016/j.tele.2016.08.008 open in new tab
  10. Culnan, M. J. (1985). The Dimensions of Perceived Acces- sibility to Information: Implications for the Delivery of Information Systems and Services. Journal of the American Society of Information Sciences, 36, 302-308. open in new tab
  11. Davis, F. D. (1986). A Technology Acceptance Model for Em- pirically Testing New End-User Information Systems: Theory and Results. Cambridge, United States: MIT Sloan School of Management.
  12. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease Of Use, And User Acceptance Of Information Technology. MIS Quarterly, 13(3), 319-340. doi: 10.2307/249008 open in new tab
  13. Davis, F. D. (1993). User Acceptance of Information Tech- nology: System Characteristics, User Perceptions and Behavioral Impacts. International Journal of Man-Machine Studies, 38(3), 475-487. doi: 10.1006/ imms.1993.1022 open in new tab
  14. Davis, F. D., Bagozzi, R., & Warshaw, P. (1989). User ac- ceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003. open in new tab
  15. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Re- search. Reading, United States: Addison-Wesley.
  16. Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18, 39-50. open in new tab
  17. Groß, M. (2018). Heterogeneity in consumers' mobile shopping acceptance: A finite mixture partial least squares modelling approach for exploring and char- acterising different shopper segments. Journal of Re- tailing and Consumer Services, 40, 8-18. open in new tab
  18. Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2010). Multivariate Data Analysis. Prentice Hall International.
  19. Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A. L. M. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS Quar- terly, 21(3), 279-305. open in new tab
  20. Karahanna, E., Agarwal, R., & Angst, C. M. (2006). Recon- ceptualizing compatibility beliefs in technology ac- ceptance research. MIS Quarterly, 30(4), 781-804. open in new tab
  21. King, W. R., & He, J. (2006). A meta-analysis of the tech- nology acceptance model. Information and Manage- ment, 43(6), 740-755. open in new tab
  22. Lai, V. S., & Li, H. (2000). Technology acceptance model for internet banking: An invariance analysis. Informa- tion and Management, 42(2), 373-386. open in new tab
  23. Liébana-Cabanillas, F., Ramos de Luna, I., & Montoro-Ríos, F. J. (2015). User behaviour in QR mobile payment sys- tem: the QR Payment Acceptance Model. Technology Analysis & Strategic Management, 27(9), 1031-1049. doi: 10.1080/09537325.2015.1047757 open in new tab
  24. Lim, W. M. (2018). Dialectic Antidotes to Critics of the Technology Acceptance Model: Conceptual, Meth- odological, and Replication Treatments for Behav- ioural Modelling in Technology-Mediated Environ- ments. Australasian Journal of Information Systems, 22, 1-11. doi: 10.3127/ajis.v22i0.1651 open in new tab
  25. Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Manage- ment, 38, 217-230. open in new tab
  26. Park, E., Cho, Y., Han J., & Kwon, S. J. (2017). Comprehensive Approaches to User Acceptance of Internet of Things in a Smart Home Environment. IEEE Internet of Things Journal, 4(6), 2342-2350. open in new tab
  27. Park, S. Y. (2009). An Analysis of the Technology Accep- tance Model in Understanding University Students' Behavioral Intention to Use e-Learning. Educational Technology & Society, 12(3), 150-162. open in new tab
  28. Przechlewski, T. (2012). Modelowanie satysfakcji, użyteczności i wykorzystania oprogramowania Open Source [Mod- eling the satisfaction, usability and use of Open Source software]. open in new tab
  29. Gdańsk, Poland: Wydawnictwo Uniwersy- tetu Gdańskiego.
  30. Rice, R. E., & Shook, D. (1988). Access to, Usage of, and Outcomes from an Electronic Message System. ACM Transactions on Office Information Systems, 6(3), 255-276. open in new tab
  31. Sangi, N., Shuguang, L., & Sangi, A. R. (2018). Robustness of factors influencing social media usage/adoption amongst SMEs in developing countries: A case of Pakistan. ACM International Conference Proceeding Series, 103-109. doi: 10.1145/3183586.3183600 open in new tab
  32. Sobh, T. (ed.), (2010). Innovations and Advances in Computer Sciences and Engineering. Switzerland: Springer Science & Business Media. open in new tab
  33. Teo, T. S. H., Lim, V. K. G., & Lai, R. Y. C. (1999). Intrinsic and extrinsic motivation in internet usage. Omega, 27(1), 25-37. open in new tab
  34. Thong, J. Y. L., Hong, W., & Tam, K. (2002). Understanding user acceptance of digital libraries: What are the roles of interface characteristics, organizational context, and individual differences? International Journal of Human-Computer Studies, 57, 215-242. open in new tab
  35. Ul Hassan, M., Iqbal, A., & Iqbal, Z. (2018). Factors affect- ing the adoption of internet banking in Pakistan: An integration of technology acceptance model and theory of planned behaviour. International Journal of Business Information Systems, 28(3), 342-370.
  36. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. De- cision Sciences, 39(2), 273-315. open in new tab
  37. Venkatesh, V., & Davis, F. D. (1996). A Model of the Ante- cedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27(3), 451-481. doi: 10.1111/ j.1540-5915.1996.tb01822.x open in new tab
  38. Venkatesh, V., & Davis, F. D. (2000). A theoretical exten- sion of the technology acceptance model: four lon- gitudinal field studies. Management Science, 46(2), 186-204. open in new tab
  39. Venkatesh, V., Morris, M. G., Davis G. B., & Davis F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478. open in new tab
  40. Wai I. S. H., Ng S. S. Y., Chiu D. K. W., Ho K. K. W., & Lo P. (2018). Exploring undergraduate students' usage pattern of mobile apps for education. Journal of Librarianship and Information Science, 50(1), 34-47. open in new tab
  41. Wu, J. H., & Wang, S. C. (2005). What drives mobile com- merce? An empirical evaluation of the revised tech- nology acceptance model. Information and Manage- ment, 42, 719-729. open in new tab
  42. Zarantonello, L., & Pauwels-Delassus, V. (2015). The Handbook of Brand Management Scales. New York, United State: Taylor & Francis Group. open in new tab
Verified by:
Gdańsk University of Technology

seen 12 times

Recommended for you

Meta Tags