Vai trò trung gian của nhận thức tính hữu ích lên mối quan hệ giữa chất lượng hệ thống thông tin kế toán và sử dụng hệ thống thông tin kế toán

ERP, so improving the quality of AIS should focus on: - Continue to improve processes and procedures in the process of collecting, processing, storing data and providing information to different users, creating ease of access and use the sys- tem. These procedures should be specific in writing and stored in the system with system docu- mentation tools such as data flow diagrams and flowcharts for each of the different processing processes, but have full approval. - Increased AIS connectivity further with other systems in the enterprise through the help of processing software. Orientation and apply technology effectively in accounting and manage- ment, creating convenience and ease in using the system. - Control the ERP software evaluation and selection process in AIS, regularly update new software versions and suit business needs, to ensure flexibility, integration, and customization requirements and high control over software. According to the survey results on the use of ERP systems, there are 2 groups of ERP software used by enterprises, which are domestic and foreign software. For domestic software, although the cost is lower, it is necessary to pay attention to control and integration features to contribute to improving the quality of AIS. - Further improve the quality of data of enterprises and business operations of enterprises, create a diverse and scaled data warehouse to serve the needs of data mining and analysis to sup- port more useful information for administrators. - Improve the quality of IT infrastructure, regularly monitor and manage computer systems, peripheral devices, and communications to promptly detect problems and risks and take appro- priate corrective measures. Strengthening network security solutions, especially in the case of information transfer on computer networks. When the AIS on the computer platform has stable operation and effective management, the quality of AIS will be enhanced. - Improving the quality of AIS will contribute to improving the quality of accounting in- formation, currently most businesses have applied IT in accounting, although the level of IT ap- plication in accounting is not the same, but basically businesses are applying accounting software and ERP system in accounting work and enterprise management. The level of IT application will affect the way of collecting, processing data and providing accounting information, thus affecting risks as well as the management and control of AIS. The awareness and assessment of the possi- bility of errors and frauds for AIS in the computer environment, thereby having important control procedures, will contribute to improving the quality of AIS. In AIS control, it is necessary to focus on general control and application control, general control including control activities re- lated to the entire processing system and affecting all processing application systems in business. 1070 INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Application control includes the implementation policies and procedures that affect a specific application system and performance in AIS. These two controls are established and coordinated will help ensure the entire AIS operates effectively and efficiently. 5.3. Limitations and future research Although the initial purpose of evaluating the mediating role of perceived usefulness AIS in the relationship between AIS quality and usage AIS has been achieved, this study also has some of the limitations First, the survey is mainly in Ho Chi Minh City and a neighboring province, so the gener- ality of the study is not high and may be certain limited. In addition, the study used convenient sampling by sending questionnaires directly or via email to survey subjects. Therefore, further studies should conduct additional surveys in different regions of the country and have a classifi- cation of survey subjects. Second, according to the TAM model, there may be many external factors influencing the perceived usefulness of IS. Further studies need to develop additional factors influencing the per- ceived usefulness of AIS such as individual characteristics, subjective standards and the organi- zation support in the operation of the AIS. Third, it is possible to learn and apply more relevant background theories in AIS to build research models and use some more moderating, mediating variables in relationships between research concepts and the usage AIS. REFERENCES Amoako-Gyampah, K. (2007),‘Perceived usefulness, user involvement and behavioral intention: an empirical study of ERP implementation’, Computers in Human Behavior, 23(3), 1232-1248. Amoako-Gyampah, K., & Salam, A. F. (2004), ‘An extension of the technology acceptance model in an ERP implementation environment’, Information & management, 41(6), 731-745. Bagozzi, R. P., Yi, Y., & Nassen, K. D. (1998). Representation of measurement error in marketing variables: Review of approaches and extension to three-facet designs. Journal of Econometrics, 89(1-2), 393-421. Calisir, F., Altin Gumussoy, C., & Bayram, A. (2009), ‘Predicting the behavioral intention to use enterprise resource planning systems: An exploratory extension of the technology accept- ance model’, Management research news, 32(7), 597-613. Cheng, Y. M. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research. Davis, F. D. (1989), 'Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology',MIS Quarterly, 13(3), 319-339. Delone, W. H., & McLean, E. R. (2003), 'The DeLone and McLean model of information systems success: a ten-year update', Journal of management information systems, 19(4), 9-30. 1071 INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Delone, W. H. & Mclean, E. R. (2016). Information systems success measurement. Foundations and Trends® in Information Systems, 2(1),1-116. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable v ariables and measurement error: Algebra and statistics. Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the association for information systems, 4(1), 7. Hair Jr, J. F., Sarstedt, M., Matthews, L. M., & Ringle, C. M. (2016). Identifying and treat- ing unobserved heterogeneity with FIMIX-PLS: part I–method. European Business Review. Hassanzadeh, A., Kanaani, F., & Elahi, S. (2012). A model for measuring e-learning systems success in universities. Expert Systems with Applications, 39(12), 10959-10966. Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial management & data systems. Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic management journal, 20(2), 195-204. Lee, S., & Heo, C. Y. (2009). Corporate social responsibility and customer satisfaction among US publicly traded hotels and restaurants. International Journal of Hospitality Manage- ment, 28(4), 635-637. Liu, Y., Li, H., & Carlsson, C. (2010). Factors driving the adoption of m-learning: An em- pirical study. Computers & Education, 55(3), 1211-1219. Iivari, J. (2005). An empirical test of the DeLone-McLean model of information system success. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 36(2), 8-27. Mamić Sačer, I., Žager, K., & Tušek, B. (2006). Accounting information system’s quality as the ground for quality business reporting. In IADIS International conference, e-commerce 2006 (p. 59). Mohammadi, H. (2015). Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49, 191-207. Nunnally, J. C., & Bernstein, I. H. (1994), Psychological theory, MacGraw-Hill, New York. Nwankpa, J., & Roumani, Y. (2014), 'Understanding the link between organizational learn- ing capability and ERP system usage: An empirical examination', Computers in Human Behavior, 33, 224-234. Nwankpa, J. K. (2019). ERP systems benefit realization and the role of ERP-enabled ap- plication integration. In Advanced methodologies and technologies in business operations and management (pp. 802-815). IGI Global. Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: models, dimensions, measures, and interrelationships. European journal of information systems, 17(3), 236-263. 1072 INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Rajan, C. A. & Baral, R. (2015), 'Adoption of ERP system: An empirical study of factors influencing the usage of ERP and its impact on end user', IIMB Management Review, 27(2), 105- 117. Reynolds, G. W., & Stair, R. M. (2018). Principles of information systems. Cengage Learning. Romney, M. B., & Steinbart, P. J. (2018). Accounting Information Systems. Fourteenth. Saadé, R., & Bahli, B. (2005), 'The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model', Information & management, 42(2), 317-327. Seddon, P., & Kiew, M. Y. (1996). A partial test and development of DeLone and McLean's model of IS success. Australasian Journal of Information Systems, 4(1). Tilahun, M. (2019). A Review on Determinants of Accounting Information System Adop- tion. Science Journal of Business and Management, 7(1), 17-22. Uzoka, F. M. E., Abiola, R. O., & Nyangeresi, R. (2008). Influence of product and organi- zational constructs on ERP acquisition using an extended technology acceptance model. Interna- tional Journal of Enterprise Information Systems (IJEIS), 4(2), 67-83. Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and tech- nology acceptance. Information systems research, 16(1), 85-102. 1073 INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020