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Nghiên cứu được thực hiện nhằm xem xét vai trò trung gian của nhận thức tính hữu ích của hệ thống thông tin kế toán đối với mối quan hệ giữa chất lượng hệ thống thông tin kế toán (AIS) và sử dụng Hệ thống thông tin kế toán trong môi trường ứng dụng hệ thống hoạch định nguồn lực doanh nghiệp (ERP) tại các doanh nghiệp tại Việt Nam. Mời các bạn cùng tham khảo!

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Nội dung Text: 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

  1. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 THE MEDIATING ROLE OF PERCEIVED USEFULNESS ON THE RELATIONSHIP BETWEEN QUALITY OF ACCOUNTING INFORMATION SYSTEM AND USAGE ACCOUNTING INFORMATION SYSTEM 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 TS. Lương Đức Thuận; ThS. Trương Thị Thu Hương Trường Đại học Kinh tế TP.HCM thuanluongktkt@ueh.edu.vn Abstract The study was conducted to examine the mediating role of perceived usefulness of Ac- counting Information System on relationship between quality of accounting information system (AIS) and usage of Accounting Information System in application enterprise resource planning (ERP) in enterprises in Viet Nam. Formal research samples of 104 subjects, including account- ants and managers involved in the use AIS in the ERP. Research data were collected primarily through questionnaire survey (July, 2019 – September, 2019) and then it is used to analyze de- scriptive statistics and perform hypothesis tests. The result shows that perceived usefulness do not plays a mediating role in the relationship between quality of accounting information system and the usage of accounting information system. There is significant direct effect but not signif- icant indirect effect. Keywords: Quality of Accounting Information System, Perceived usefulness of Accounting Information System, Usage of Accounting Information System. Tóm tắt Nghiên cứu được thực hiện nhằm xem xét vai trò trung gian của nhận thức tính hữu ích của hệ thống thông tin kế toán đối với mối quan hệ giữa chất lượng hệ thống thông tin kế toán (AIS) và sử dụng Hệ thống thông tin kế toán trong môi trường ứng dụng hệ thống hoạch định nguồn lực doanh nghiệp (ERP) tại các doanh nghiệp tại Việt Nam. Mẫu nghiên cứu chính thức gồm 104 đối tượng, bao gồm cả nhân viên kế toán và nhà quản lý tham gia vào việc sử dụng AIS. Dữ liệu nghiên cứu được thu thập chủ yếu thông qua khảo sát bảng câu hỏi (từ tháng 7 năm 2019 đến tháng 9 năm 2019) và sau đó được sử dụng để phân tích thống kê mô tả và thực hiện kiểm định giả thuyết. Kết quả cho thấy nhận thức tính hữu ích không đóng vai trò trung gian trong mối quan hệ giữa chất lượng hệ thống thông tin kế toán và sử dụng hệ thống thông tin kế toán. Có sự ảnh hưởng trực tiếp đáng kể nhưng sự ảnh hưởng gián tiếp là không đáng kể. Từ khóa: Chất lượng Hệ thống thông tin kế toán, Nhận thức tính hữu ích của hệ thống thông tin kế toán, Sử dụng hệ thống thông tin kế toán. 1061
  2. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 1. Introduction In the field of AIS research, the use of AIS is considered a new issue attracting the research interest of researchers. According to the Technology Acceptance Model (TAM) of Davis (1989), information system usage (IS) behavior is understood as the usage process of the system users when they realize the usefulness and the ease of use of a new system or technology. In addition, in DeLone & McLean’s successful IS model, the use of the system is mentioned, which is the extent and way in which employees use the IS capabilities and to engage in behavior of usage IS need a quality IS. The usage AIS played a crucial role which enhance company’s value added by providing internally generated financial statements that would help the company to make better and efficient strategic plan. Regarding the research on decisions or behaviors using IS, using enterprise resource plan- ning system (ERP), a lot of research has been done and mainly based on the Technology Accept- ance Model TAM. The TAM model was first introduced by Davis in 1989, up to now there are many different versions of the TAM model to reinforce and further improve the applicability of this model in the assessment of attitudes and behavior of usage information technology, usage IS. Researches in the world and in the country have used successful IS theory and TAM model to measure and evaluate the factors affecting the behavior of using IS. Thus, the combination of successful IS theory and TAM model will help to see the inter- action between AIS quality and the behavior of using AIS through users’ perception in the system about the usefulness of AIS. In this study, applies a combination of successful IS theory and TAM model in explaining the mediating role of perceived usefulness of AIS in the relationship between AIS quality and usage AIS. 2. Literature review and research model 2.1. Literature review 2.1.1. Quality of Accounting Information System The views on the quality of AIS are mainly based on the view of the quality of IS imple- mented in previous studies and analyzed from the quality point of view of the information systems model by DeLone & McLean. According to DeLone & McLean, 2003, system quality is associ- ated with success and they use a scale of quality of information system consistent with the de- veloped model, including: ease of use, system functions, reliability, flexibility, data quality, portability, integration, and materiality. In the successful information systems model, DeLone & McLean (2003) proposed that the success of the information system is considered through six factors, namely: (1) system quality, (2) quality of information, (3) quality of service, (4) use of the system, (5) user satisfaction and (6) net benefit. Information system quality is concerned with measuring the desirable system characteristics: availability, validity, reliability, adaptability, and response time. In the study of Peter et al (2008) on measuring the success of information systems in relation to models, aspects, building scales and relationships, the author said that the quality of information systems shows desirable system properties such as ease of use, flexibility, relia- bility, ease of understanding, system sophistication and response time. On the basis of the concept of the quality of the information system, there are many opin- 1062
  3. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 ions of many authors on the quality of the accounting information system, because in terms of the intrinsic relationship, the accounting information system is also an information system and also has all the characteristics of an information system. Specifically: iThe quality of accounting information comes from the implementation of quality ac- counting information systems. The quality of accounting information systems is the integration of the quality of hardware, software, people, engineering and technology networks, databases and user satisfaction (Sacer et al, 2006). Some authors have described the quality of the account- ing information system through the following characteristics: efficiency, usefulness, efficiency, user satisfaction. iThe concept of quality in the accounting information system is that a reliable accounting information system will create information quality (Romney & Steinbart, 2018). The effectiveness of an accounting information system is a measure of the success in meeting established goals, or user satisfaction (Reynolds & Stair, 2018). According to them, the quality of accounting infor- mation systems is often flexible, efficient, accessible and timely. 2.1.2. Perceived Usefulness of Accounting Information System According to Davis (1989); Saade & Bahli (2005), perceived usefulness is the belief in improving work performance by using new technology, using specific information system. Stu- dents who perceived usefulness of a system have a stronger aptitude for acceptance (Lee et al. 2009; Liu et al, 2010). Perceived usefulness is the primary determinant of intention to use (Cheng 2012). People believe that using AIS can lead to positive results as well as more favorable in- tentions and attitudes when using such technologies and systems. Perveived usefulness most likely leads to improved productivity and users’ motives or behavior. Thus, the perceived use- fulness of AIS is the degree to which the accountants believe that using AIS will improve their work performance. 2.1.3. Usage Accounting Information System The behavior of usage IS according to the TAM model is influenced by the perceived use- fulness of IS (Davis, 1989). According to these theories, using IS is the behavior of the user to manipulate IS during the operation on a regular basis, repeating and expected to continue in the future. The view of usage IS has been inherited and used in many studies on choosing and using an ERP system (Nwankpa, 2019). Using ERP refers to how users use ERP features to perform tasks and run jobs (Nwankpa & Roumani, 2014). If the process of usage IS fails or the user does not use it correctly, the system will develop serious problems, usage AIS is understood as a user using AIS components and tools including using using software in processing, participating in using prodedures and processes in the system and under the supervision of system security control procedures. Usage Information system increased performances and operations efficiency espe- cially in large companies and as well good management of resources and better control of ex- penditure, budgeting and forecasting. Accounting information systems also provide information on both actual and budgeted data which would help companies to establish, plan and control op- erations (Tilahun, 2019). Studying the usage AIS in this topic and the factor affecting the usage AIS to explain the actual usage AIS in Vietnamese enterprises. 1063
  4. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 2.2. Reasearch model and Hypothesis 2.2.1. The relationship between quality AIS and perceived usefulness AIS Accounting Information System quality represents the quality characteristics of a system and should satisfy the user of the system. Academic studies on the IS quality have shown that the IS quality includes conceptual components: ease of use; full features; reliable; flexibility; inte- gration; easy research; response time (DeLone & McLean, 2003; Iivari, 2005; Peter et al., 2008; Seddon & Kiew, 1996). Researches on the IS quality and the quality of ERP systems show that the quality of the ERP system is one of the important factors affecting user satisfaction, affecting the use of the system. The model of Wixom & Todd (2005) and research of Uzoka et al (2008) show that the IS quality the quality of ERP affects the perceived usefulness of the system. In ERP, this is explained from the point of view of the users of information system. When the user of the system is convinced that the system is qualitative through its characteristics, the user be- lieves it is a good and useful system. Accordingly, if AIS has quality characteristics, it will help AIS users to recognize the quality characteristics of that system and influence their perception of usefulness, which in turn affects their usage AIS. Based on the above arguments, the research hypothesis is given as follows: H1: Quality AIS has a positive effect on perceived usefulness of AIS. 2.2.2. The relationship between quality AIS and usage AIS System quality refers to the quality of the performance of the information system and its functionality (DeLone & McLean, 2016). System quality can be defined as the desirable charac- teristics provided by an information system (Petter et al, 2008). System quality is the key factor for the success of the information systems (Delone and McLean, 2016). From a different view- point, Hassanzadeh et al (2012) noted that the system quality affects learners’ satisfaction and intention to use, leading to enhanced learner usage of the elearning system. Mohammadi (2015) found that system quality is the key predictor of satisfaction and intention to use. This leads to the following hypothesis: H2: Quality AIS has a positive effect on the usage AIS 2.2.3. The relationship between perceived usefulness of AIS and usage AIS Starting from the TAM model, the perception of the usefulness of information system is formed and studied in most studies on ERP application in enterprises. Davis (1989) defines per- ceived usefulness as the degree to which a person believes using a particular system will improve productivity. The TAM model recognizes that use system is determined by the behavioral inten- tion to use a system, where the intention to co-use the system is determined by an individual’s attitude towards using the system and perceptions about the usefulness of the system, when they realize the usefulness of the system, it leads to improving the efficiency of the work and the mo- tivation of users (Davis, 1989). Researches on ERP application in recent years have applied the TAM model in the explanation of ERP applications in enterprises all show that the perception of the usefulness of ERP affects the behavior of using ERP (Amoako- Gyampah, 2007; Amoako- Gyampah & Salam, 2004). In this study, the author inherits the research of applying TAM model in ERP research and considered for a specific AIS to test the hypothesis of the impact of perceived 1064
  5. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 usefulness of AIS on the usage AIS. In addition, according to the research model, AIS quality af- fects the perceived usefulness of AIS, perceived usefulness AIS affects the usage AIS. Therefore, it can be seen that perceived usefulness AIS can act as a mediating role in the relationship between AIS quality and the usage AIS. Thus, the hypotheses offer: H3: Perceived usefulness AIS has a positive effect on the usage AIS H4: Perceived usefulness AIS plays a mediating role in the relationship between AIS quality and the usage AIS. Figure 2.1. Research model 3. Research method 3.1. The Instrument In this study, the author carried out quantitative research method. The important content in quantitative research is a detailed questionnaire with information about the scales related to the measurement of PU according to the scale of Davis (1989); Calisir et al (2009); Rajan & Baral (2015), specifically, the PU scale includes 6 observed variables (PU1 to PU6), the ASU scale includes 5 observed variables (ASU1 to ASU5) from the scale of DeLone & McLean (2016). The scale quality of AIS variable is a result scale, including 9 observed variables (ASQ1 to ASQ9), measuring the quality of AIS, selected by the author from the study of DeLone & McLean (2016). These observed variables are measured on a 5-point Likert scale (1: Strongly disagree; 5: Strongly agree). 3.2. Sampling The data collection tool in the study is a questionnaire, the author conducts direct and in- direct survey of individuals who using directly AIS and individuals participating in using AIS in the ERP environment. The research is mainly conducted in enterprises in Ho Chi Minh City and some other provinces from July to September, 2019. Sample 104 was chosen according to the non-probability method, with this approach, the author has collected the necessary sample size for the study. The sample of 104 surveyed individuals included: 71 accountants (68.3%) and 33 managers who used AIS (31.7%), 37 male (35.6%) and 67 women (64.4%). Number of respondents aged from 30 to 40 accounts for the highest proportion of 62 people (59.6%). Professional qualifica- tions accounting for the highest proportion are university (69.2%), followed by postgraduate 1065
  6. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 (20.2%) and college 10.6%. Work experience of employees accounts for the highest rate from 5 to 10 years (43.3%), work experience of less than 5 years accounts for 38.5% and work experience over 10 years has the rate 18.3%. 4. Data analysis and Results 4.1. The measurement model This paper used the partial least squares (PLS) technique in SmartPLS to analyze data. Fol- lowing the two-stage analytical procedure of PLS, the measurement model was examined before analyzing the structural model. We assessed the reliability and validity of constructs in the meas- urement model by examining indicator reliability, internal consistency reliability, convergent va- lidity, and discriminant validity. Five items were eliminated due to insufficient factor loadings or cross-factor loadings (< 0.5). They were one item for Usage Accounting Information system (ASU1), four items for Ac- counting Information system quality (ASQ4, ASQ6, ASQ7, and ASQ9). Convergent validity is verified through assessing using average variance extracted (AVE). In PLS, it is comparable to the proportion of variance explained in factor analysis (value form 0 to 1). In this study, the loading of each item significant at the p < 0.001 level, shows good con- vergent validity. In addition, table 4.1 shows that the average variance extracted (AVE) of each construct excesses 0.5 (Fornell and Larcker, 1981), thus displaying sound convergent validity. Table 4.1 shows two criteria for inside consistencies including composite reliability (CR) and Cronbach’s alpha. As advocated by Hair et al (2016), all the constructs had a Cronbach’s alpha over 0.7. A CR of all the constructs was also higher than 0.70, implying high internal con- sistency (Nunnaly & Bernstein 1994). Table 4.1. Measurement model Items Loadingsa AVEb CRc Rho_Ad Accounting Quality Information ASQ1 0.824 0.583 0.875 0.824 System ASQ2 0.771 ASQ3 0.723 ASQ5 0.754 ASQ8 0.743 Usage Accounting Information ASU2 0.866 0.787 0.937 0.954 System ASU3 0.912 ASU4 0.898 ASU5 0.872 1066
  7. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Perceived PU1 0.878 0.803 0.961 0.953 Usefulness PU2 0.928 PU3 0.941 PU4 0.907 PU5 0.878 PU6 0.838 Item removed: indicator items are below 0.5: ASU1, ASQ4, ASQ6, ASQ7, ASQ9 a. All item loadings > 0.5 Indicates indicator Reliability (Hulland, 1999) b. All Average Variance Extracted (AVE) > 0.5 as Indicates Convergent Reliability (Bagozzi & Yi (1998); Fornell & Larcker (1981) c. All Composite reliability (CR) > 0.7 indicates Internal consistency (Gefen et al, 2000) d. All Cronbach’s alpha > 0.7 indicates Indicator Reliability (Nunnaly & Bernstein 1994) The discriminant validity is justified by three pieces of evidence including the HTMT cri- terion, Fornell – Larcker criterion and cross-loadings. Table 4.3 indicates that the square root of the AVE of each construct is higher than its highest correlation with any other construct (Fornell and Larcker, 1981). All HTMT of constructs are importantly smaller than 1 (Henseler et al, 2015) (Table 4.4). Those figures imply satisfactory discriminant validity. In addition, item loadings on corresponding constructs are higher than the cross-factor loadings (Table 4.2). Table 4.2. Indicator Item Cross Loading Quality Accounting Usage Accounting In- Perceived Usefulness Information System formation System ASQ1 0.824 0.325 0.593 ASQ2 0.771 0.407 0.428 ASQ3 0.723 0.342 0.496 ASQ5 0.754 0.225 0.525 ASQ8 0.743 0.296 0.579 ASU2 0.316 0.866 0.288 ASU3 0.357 0.912 0.32 ASU4 0.309 0.898 0.239 ASU5 0.449 0.872 0.503 PU1 0.633 0.366 0.878 PU2 0.663 0.411 0.928 PU3 0.603 0.369 0.941 PU4 0.543 0.306 0.907 PU5 0.61 0.336 0.878 PU6 0.639 0.378 0.838 1067
  8. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Table 4.3. Discriminant validity (Fornell and Larcker criterion) Quality Accounting In- Usage Accounting In- Perceived Usefulness formation System formation System Quality Accounting 0.764 Information System Usage Accounting In- 0.418 0.887 formation System Perceived Usefulness 0.69 0.406 0.896 Table 4.4. Discriminant validity (HTMT) Quality Accounting In- Usage Accounting In- Perceived Usefulness formation System formation System Quality Accounting Information System Usage Accounting In- 0.465 formation System Perceived Usefulness 0.774 0.405 4.2. The structural model Results of the PLS analysis indicate the explanatory power of the model as coefficients of determination (R2) of Accounting information system usage at 0.201, Perceived usefulness of AIS is medium at 0.476. In this paper, the goodness-of-fit index (GoF) was chosen to investigate the quality of the whole model. SRMR index < 0.1 so the data fits the model (Henseler et al, 2014). The value of VIF 0.05) do not significantly relate to Usage of Accounting Infor- mation system, unsupported H3. 1068
  9. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Table 4.5. Hypothesis testing: Bootraping Direct effect result Std Std 95% 95% ypothesis Relationship t-value Decision f2 Beta Error CI LL CI UL H1 ASQ —> PU 0.684 0.08 8.770*** Supported 0.91 0.546 0.803 H3 PU —> ASU 0.22 0.147 1.522 Unsupported 0.033 -0.029 0.458 H2 ASQ —> ASU 0.277 0.12 2.18* Supported 0.045 0.073 0.473 Note: *** p ASU 0.152 0.107 1.452 No -0.009 0.345 5. Conclusion and research implication 5.1. Conclusion From previous studies on usage IS, applying the successful IS model of DeLone & McLean and TAM model, the author has built a relationship model between quality of Accounting Infor- mation System, Perceived Usefullness and Usage Accounting Information System. The results show that the measurement scales of research concepts are highly reliable. The accepted hypothe- 1069
  10. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 ses include hypotheses H1 and H2, whereby the quality AIS has an impact on the perceived use- fulness of AIS and quality AIS that affects the usage AIS. However, perceived usefulness AIS does not act as a mediating variable in the relationship between AIS quality and the usage AIS. 5.2. Research Implication With the research results shows that the need to improve the quality of AIS in enterprises. AIS is now a system with the support of IT, mainly in the application environment of accounting software and 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
  11. 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
  12. 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
  13. 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
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