Factors Affecting the Intention in Using the EXPRESS Program of Accountants in Higher Education
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Published:
Apr 30, 2020
Keywords:
Intention/ EXPRESS System Program/ Accountant in Higher Education
Main Article Content
Abstract
The EXPRESS program is a program that responds well to the needs of users through the preparation of accounting information, but the program still has difficulty learning so it affects the intention of use. The objectives of this research were to 1) study level of intention to use the EXPRESS program and 2) to study factors that influence the intention in choosing the EXPRESS system of accountants in higher education. The survey and collecting data was conducted by using 693 stratified random samplings from students in accounting scholars at Rajamangala University of Technology Rattanakosin to answer the questionnaires. The data was analyzed by using the structural equation model with the highest probability method. The finding found that 1) the intention of choosing to use the program over all was at the highest level. When considering each aspect, it was at the highest level in all aspects, and 2) factors that influence the intention to use the program, including data quality perception, system quality perception in using experience, and perception of the ease in using the program positively affected the perception in benefits in the use and also the perception in benefits in the use and perception of the ease in using the program positively affected the attitude of using the program. In addition, perception of the ease in using the program that reflected through the attitude of using the program and the norm of the reference group would have a positive effect on the intention of using the program and also send positive results to the program usage behavior respectively.
Article Details
Section
Research Articles
บทความที่ปรากฏในวารสารนี้ เป็นความรับผิดชอบของผู้เขียน ซึ่งสมาคมนักวิจัยไม่จำเป็นต้องเห็นด้วยเสมอไป การนำเสนอผลงานวิจัยและบทความในวารสารนี้ไปเผยแพร่สามารถกระทำได้ โดยระบุแหล่งอ้างอิงจาก "วารสารสมาคมนักวิจัย"
References
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Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey, Prentice-Hall.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: From cognition to behavior Heidelberg: Springer. pp.11-39.
Boyd, T.C. and Mason, C.H. (1999). The link between attractiveness of ‘extra brand’ attributes and the adoption of innovations. Journal of Academy of Marketing Science, 27(3), 306-319.
Chang, I. C., Hwang, H. G., Hung, W. F., and Li, Y. C,. (2007). Physicians’ Acceptance of Pharmacokinetics-Based Clinical Decision Support Systems, Expert Systems with Applications, 33(2), pp. 296-303.
Chen, L. D. (2008, January). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6(1), pp.32–52.
Davis, F. D. (1989, September). Perceived usefulness, perceived ease of use and user acceptance of information technology. Management Information Systems Research Center, University of Minnesota, 13(3), pp.319-340.
Dadayan, L., & Ferro, E. (2005). When technology meets the mind: A comparative study of the technology acceptance model. International conference on electronic government, 35 (91), 137-144.
Duangdara, P. (2015). Factors that are important for the selection of accounting software program of the establishments in Amphoe Mueang, Pattani. Nakhon Ratchasima. Journal of Business Administration The Association of Private Higher
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Featherman, M. S., & Pavlou, P. A. (2003, October). Predicting E–Services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), pp.45–47.
Fishbein, M. & Ajzen, I. (1975). Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Westy. Reading, MA.
Fliegel, F.C. and J.E. Kivlin. (1966). Attributes of Innovations as Factors in Diffusion. American Journal of Sociology. 72 (3): 235-248.
Gefen, D. & Straub, D.W. (1997). Gender differences in the perception and use of E-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389.
Holak, S.L. and D.R. Lehmann. (1990). Purchase intentions and the Dimensions of Innovation: An Exploratory Model. Journal of Product Innovation management. 7, March, 59-73.
He, F. & Mykytyn, P. (2007, February-June). Decision Factors for the Adoption of an Online Payment System by Customers. International Journal of E-Business Research, 3(4), pp.1-32
Karahanna, E., and Straub, D. W.(1999). The Psychological Origins of Perceived Usefulness and Perceived Ease-of-Use, Information & Management. (35), , pp. 237-250.
Kim, G. S., Park, S. B., & Oh, J. (2008, April-June). An examination of factors influencing consumer adoption of short message service(SMS). Psychology & Marketing, 25(8), pp.769-786.
Kim. C., & Baylor, A. L. (2008). A Virtual Change Agent: Motivating Pre-service Teachers to Integrate Technology in Their Future Classrooms. Educational Technology & Society, 11 (2), 309-321.
Mitchell, R. & Carson, R.T. (1989). Using surveys to value public goods: the title contingent valuation method. washington D.C. Resources for the Future, United States of America.
Miville, N. D. (2005). Factors influencing the diffusion of innovation and managerial adoption of new technology. Nova Southeastern University; 1191. DAI, 66 (02A), 131-675.
Patrick Y.K.Chau. (1996, September). An empirical investigation on factors affecting the acceptance of CASE by systems developers. Information & Management, 30(6), pp.269-280
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004, June-October). Acceptance of online banking: An extension of the technology acceptance model. Consumer Internet Research, 14(3), pp.224–235.
Rigopoulos, G., & Askounis, D. (December 2007). A TAM framework to evaluate users’perception towards online electronic payments. Journal of Internet Banking and Commerce, 12(3), 1-6.
Prakobtum, B. (2013). The study of online social network acceptance of students: a case study of Bangkok University. Drurakij Pundit university research center, 27(81), 93-108. [In Thai]
Roca, J. C., Garcia, J. J., & Vega, J. J. D. L. (2009, December). The importance of perceived trust, security and privacy in online trading systems information. Management & Computer Security, 17(2), pp.96-113.
Rogers, E.M. (1983). Diffusion of Innovations. 3rd ed. New York: The Free Press.
__________. (1995). Diffusion of Innovations. 4th ed. New York: The Free Press.
__________. (2003). Diffusion of Innovations. 5th ed. New York: Free Press A Division of Simon & Schuster, Inc.
Stuart, W.D. (2000). Influence of sources of communication, user characteristics and innovation characteristics on adoption of a communication technology (Doctoral Dissertation, The university of Kansas, 2000). Proquest Digtial Dissertations (UMI No. AAT 9998115).
Szajna, B. (1996). “Empirical Evaluation of the Revised Technology Acceptance Model,”Management Science. (42:1), pp. 85-92.
Suh, B., & Han, I. (2003, January). The impact of customer trust and perception of security control on the acceptance of electronic commerce. International Journal of Electric Commerce, 7(3), pp.135–161.
Tanurak, W., Jinandej, N., and Mejaisai, P. (2017). Influence of attitude on use and factors related to behavior, intention in using technology of Thai industrial wholesalers and retailers. Journal of the Researchers Association, 22(1) : 41-53. [In Thai]
Teo, T. (2011, December). Factors influencing teachers’ intention to use technology: Model development and test. Computer & Education, 57(4), pp. 2432-2440.
Venkatesh, V. & Davis, F.D. (2000, December). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), pp.342–365.
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.
Venkatesh, V., & Bala, H. (2008, April). Technology acceptance model 3 and a research agenda on interventions, Decision Science, 39(2), pp.273–315.
Warshaw, P.R., Bagozzi, R.P. & Davis, F.D. (1989, August). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), pp.982-1003.
Wetxels,M. & Schepers, J. (2007, January-June). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects, Information & Management, 44(8), pp.90-103.
Wang,Y.S., Lin,H. and Larn P. (2006, June). Predicting consumer intention to use mobile service. Information Systems Journal, 16(2), pp.157-179.
ปัทมาวดี ดวงดารา. (2558). ปัจจัยที่มีความสำคัญต่อการเลือกใช้โปรแกรมสำเร็จรูปทางการบัญชีของสถานประกอบการในเขตอำเภอเมือง จังหวัดนครราชสีมา. วารสารวิชาการบริหารธุรกิจสมาคมสถาบันอุดมศึกษาเอกชนแห่งประเทศไทย (สสอท.) 4 (1).
วนิดา ตะนุรักษ์ นรพล จินันท์เดช และประยงค์ มีใจซื่อ. (2560). อิทธิพลของทัศนคติต่อการใช้งานและปัจจัยที่เกี่ยวข้องต่อพฤติกรรมความตั้งใจในการใช้เทคโนโลยีของพนักงานอุตสาหกรรมการค้าส่งและค้าปลีกไทย. วารสารสมาคมนักวิจัย, 22(1) : 41-53.
Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey, Prentice-Hall.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: From cognition to behavior Heidelberg: Springer. pp.11-39.
Boyd, T.C. and Mason, C.H. (1999). The link between attractiveness of ‘extra brand’ attributes and the adoption of innovations. Journal of Academy of Marketing Science, 27(3), 306-319.
Chang, I. C., Hwang, H. G., Hung, W. F., and Li, Y. C,. (2007). Physicians’ Acceptance of Pharmacokinetics-Based Clinical Decision Support Systems, Expert Systems with Applications, 33(2), pp. 296-303.
Chen, L. D. (2008, January). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6(1), pp.32–52.
Davis, F. D. (1989, September). Perceived usefulness, perceived ease of use and user acceptance of information technology. Management Information Systems Research Center, University of Minnesota, 13(3), pp.319-340.
Dadayan, L., & Ferro, E. (2005). When technology meets the mind: A comparative study of the technology acceptance model. International conference on electronic government, 35 (91), 137-144.
Duangdara, P. (2015). Factors that are important for the selection of accounting software program of the establishments in Amphoe Mueang, Pattani. Nakhon Ratchasima. Journal of Business Administration The Association of Private Higher
Education Institutions. 4 (1): 9-21. [In Thai]
Featherman, M. S., & Pavlou, P. A. (2003, October). Predicting E–Services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), pp.45–47.
Fishbein, M. & Ajzen, I. (1975). Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Westy. Reading, MA.
Fliegel, F.C. and J.E. Kivlin. (1966). Attributes of Innovations as Factors in Diffusion. American Journal of Sociology. 72 (3): 235-248.
Gefen, D. & Straub, D.W. (1997). Gender differences in the perception and use of E-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389.
Holak, S.L. and D.R. Lehmann. (1990). Purchase intentions and the Dimensions of Innovation: An Exploratory Model. Journal of Product Innovation management. 7, March, 59-73.
He, F. & Mykytyn, P. (2007, February-June). Decision Factors for the Adoption of an Online Payment System by Customers. International Journal of E-Business Research, 3(4), pp.1-32
Karahanna, E., and Straub, D. W.(1999). The Psychological Origins of Perceived Usefulness and Perceived Ease-of-Use, Information & Management. (35), , pp. 237-250.
Kim, G. S., Park, S. B., & Oh, J. (2008, April-June). An examination of factors influencing consumer adoption of short message service(SMS). Psychology & Marketing, 25(8), pp.769-786.
Kim. C., & Baylor, A. L. (2008). A Virtual Change Agent: Motivating Pre-service Teachers to Integrate Technology in Their Future Classrooms. Educational Technology & Society, 11 (2), 309-321.
Mitchell, R. & Carson, R.T. (1989). Using surveys to value public goods: the title contingent valuation method. washington D.C. Resources for the Future, United States of America.
Miville, N. D. (2005). Factors influencing the diffusion of innovation and managerial adoption of new technology. Nova Southeastern University; 1191. DAI, 66 (02A), 131-675.
Patrick Y.K.Chau. (1996, September). An empirical investigation on factors affecting the acceptance of CASE by systems developers. Information & Management, 30(6), pp.269-280
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004, June-October). Acceptance of online banking: An extension of the technology acceptance model. Consumer Internet Research, 14(3), pp.224–235.
Rigopoulos, G., & Askounis, D. (December 2007). A TAM framework to evaluate users’perception towards online electronic payments. Journal of Internet Banking and Commerce, 12(3), 1-6.
Prakobtum, B. (2013). The study of online social network acceptance of students: a case study of Bangkok University. Drurakij Pundit university research center, 27(81), 93-108. [In Thai]
Roca, J. C., Garcia, J. J., & Vega, J. J. D. L. (2009, December). The importance of perceived trust, security and privacy in online trading systems information. Management & Computer Security, 17(2), pp.96-113.
Rogers, E.M. (1983). Diffusion of Innovations. 3rd ed. New York: The Free Press.
__________. (1995). Diffusion of Innovations. 4th ed. New York: The Free Press.
__________. (2003). Diffusion of Innovations. 5th ed. New York: Free Press A Division of Simon & Schuster, Inc.
Stuart, W.D. (2000). Influence of sources of communication, user characteristics and innovation characteristics on adoption of a communication technology (Doctoral Dissertation, The university of Kansas, 2000). Proquest Digtial Dissertations (UMI No. AAT 9998115).
Szajna, B. (1996). “Empirical Evaluation of the Revised Technology Acceptance Model,”Management Science. (42:1), pp. 85-92.
Suh, B., & Han, I. (2003, January). The impact of customer trust and perception of security control on the acceptance of electronic commerce. International Journal of Electric Commerce, 7(3), pp.135–161.
Tanurak, W., Jinandej, N., and Mejaisai, P. (2017). Influence of attitude on use and factors related to behavior, intention in using technology of Thai industrial wholesalers and retailers. Journal of the Researchers Association, 22(1) : 41-53. [In Thai]
Teo, T. (2011, December). Factors influencing teachers’ intention to use technology: Model development and test. Computer & Education, 57(4), pp. 2432-2440.
Venkatesh, V. & Davis, F.D. (2000, December). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), pp.342–365.
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.
Venkatesh, V., & Bala, H. (2008, April). Technology acceptance model 3 and a research agenda on interventions, Decision Science, 39(2), pp.273–315.
Warshaw, P.R., Bagozzi, R.P. & Davis, F.D. (1989, August). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), pp.982-1003.
Wetxels,M. & Schepers, J. (2007, January-June). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects, Information & Management, 44(8), pp.90-103.
Wang,Y.S., Lin,H. and Larn P. (2006, June). Predicting consumer intention to use mobile service. Information Systems Journal, 16(2), pp.157-179.