Asia pacific journal of information systems

The Korea Society of Management Information Systems (한국경영정보학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluation of Factors Affecting the Use of the Accounting Information System Using the TAM Model: A Field Study in Algerian Firms

  • Widad Benzine (University of Badji Mokhtar of Annaba) ;
  • Ahcene Tiar (Faculty of Economic, Commercial and Management Sciences)
  • Received : 2022.01.29
  • Accepted : 2022.05.11
  • Published : 2022.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

The accounting literature abounds with many studies concerning the organizational and technical aspects of the AIS to simulate progress in the business environment. However, few studies have focused on the role of individual factors in overcoming resistance to change and maximizing the value of using the system. Therefore, this study aims to shed light on user beliefs by evaluating the factors that affect the use of the AIS using a developed TAM. A total of 132 subjects participated in this study, in which the questionnaire was used as a data collection tool and AMOS was used to test the model. The results showed that subjective norm, training and experience were the most important previous factors that affect the perceptual factors represented in usefulness, ease of use and the inevitability of change, which all had an impact on the continuance intention to use the AIS among users in Algerian firms. This study shed light on the importance of assessing individual factors rather than focusing only on the ways to develop AIS or researching for new technologies and the costs of this investment because this will increase the chances of success in using the system.

Keywords

References

  1. Abduljalil, K. M., and Zainuddin, Y. (2015). Integrating technology acceptance model and motivational model towards intention to adopt accounting information system. International Journal of Management, Accounting and Economics, 2(5), 346-59.
  2. Adams, J., Khan, H. T. A., and Raeside, R. (2014). Research Methods for Business and Social Science Students (2nd ed.). SAGE Publications.
  3. Agarwal, R., and Prasad, J. (1997). The Role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582. https://doi.org/10.1111/j.1540-5915.1997.tb01322.x
  4. Aggelidis, V. P., and Chatzoglou, P. D. (2009). Using a modified technology acceptance model in hospitals. International Journal of Medical Informatics, 78(2), 115-126. https://doi.org/10.1016/j.ijmedinf.2008.06.006
  5. Ajibade, P. (2018). Technology acceptance model limitations and criticisms: Exploring the practical applications and use in technology-related studies, mixed-method, and qualitative researches. In Library Philosophy and Practice.
  6. Ajzen, I. (1991). The theory of planned behavior. Handbook of Theories of Social Psychology: (Volume 1, 50, 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
  7. Al-Smadi, M. O. (2012). Factors affecting adoption of electronic banking: An analysis of the perspectives of banks' customers. International Journal of Business and Social Science, 3(17), 294-309.
  8. Al Muala, A., AL Ziadat, M., Albarq, A. N., and AL-Majali, M. (2013). Applications of structural equation modeling (SEM) in humanities and science researches. 4th Global Islamic Marketing Conference, 01-10.
  9. Alamin, A., Yeoh, W., Warren, M., and Salzman, S. (2015). An empirical study of factors influencing accounting information systems adoption. 23rd European Conference on Information Systems, ECIS 2015, 1-11 .
  10. Allahyari, A., Garabaghi, F., and Ramazani, M. (2012). Examine the effect of social factors on information technology acceptance in accounting profession by using TAM model. Global Journal of Management and Business Research, 12(11), 41-46.
  11. Alsamydai, M. J. (2014). Adaptation of the technology acceptance model (TAM) to the use of mobile banking services. International Review of Management and Business Research, 3(4), 2016-2028.
  12. Ambad, S. N. A., and Wahab, K. A. (2016). The relationship between corporate entrepreneurship and firm performance: Evidence from malaysian large companies. International Journal of Business and Society, 17(2), 259-280.
  13. Ammi, H. (2019). Villes et developpement economique en Algerie. Universite de Toulon.
  14. Amoako-Gyampah, K., and Salam, A. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information and Management, 41(6), 731-745. https://doi.org/10.1016/j.im.2003.08.010
  15. Ayache, Z., and Ghennam, N. (2014). Al-awamil almuathira fi istikhdem nidham almalumet fil-sharikat aldjazairia: dirasat namudhaj TAM welmakhatir almutasawira PR [Factors affecting the use of the information system in Algerian firms: A study of the TAM model and the perceived risks PR]. Journal of Financial, Accounting and Managerial Studies (JFAMS), 1(1), 160-75.
  16. Azam, M. S., Quaddus, M., and Rahim, M. (2010). How experience affects technology acceptance: A quest for ICT development strategies in Bangladesh. Proceedings of 2010 13th International Conference on Computer and Information Technology, ICCIT 2010, 289-294.
  17. Benzine, W., and Tiar, A. (2021). The adoption of accounting information system in Algerian firms: An assessment of users' perceptions and intentions. Economic and Management Research Journal, 15(01), 137-156.
  18. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921
  19. Bhattacherjee, A., and Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. Management Information Systems, 28(2), 229-254. https://doi.org/10.2307/25148634
  20. Bhatti, T. (2007). Exploring factors influencing the adoption of mobile commerce. Journal of Internet Banking and Commerce, 12(3), 231-2311.
  21. Brown, S. A., Massey, A. P., Montoya-Weiss, M. M., and Burkman, J. R. (2002). Do I really have to? User acceptance of mandated technology. European Journal of Information Systems, 11(4), 283-295. https://doi.org/10.1057/palgrave.ejis.3000438
  22. Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming. In Structural Equation Modeling With AMOS (3rd ed.). Routledge, Taylor & Francis Group.
  23. Cao, D., Li, H., and Wang, G. (2014). Impacts of isomorphic pressures on BIM adoption in construction projects. Journal of Construction Engineering and Management, 140(12), 04014056.
  24. Collier, J. E. (2020). Applied Structural Equation Modeling Using Amos: Basic to Advanced Techniques. Routledge.
  25. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319-339. https://doi.org/10.2307/249008
  26. Davis, F. D., and Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: Three experiments. International Journal of Human Computer Studies, 45(1), 19-45. https://doi.org/10.1006/ijhc.1996.0040
  27. Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
  28. Davoodi, S., Akbarpour, L., and Hadipour, E. (2021). Investigating the effects of subjective norms and trialability on english teachers' attitude toward the use of technology. Vision: Journal for Language and Foreign Language Learning, 9(2), 159-172 . https://doi.org/10.21580/vjv10i17431
  29. De Luna, I. R., Liebana-Cabanillas, F., Sanchez-Fernandez, J., and Munoz-Leiva, F. (2019). Mobile payment is not all the same: The adoption of mobile payment systems depending on the technology applied. Technological Forecasting and Social Change, 146 (September 2018), 931-944. https://doi.org/10.1016/j.techfore.2018.09.018
  30. Diatmika, I. W. B., Irianto, G., and Baridwan, Z. (2016). Determinants of behavior intention of accounting information systems based information technology acceptance. Imperial Journal of Interdisciplinary Research, 2(8), 125-138.
  31. DiMaggio, P. J., and Powell, W. W. (1983). The iron cage revisited institutional isomorphism and collective rationality in organizational fields. Advances in Strategic Management, 17, 143-166. https://doi.org/10.1016/S0742-3322(00)17011-1
  32. Diouani, H., and Graa, A. (2021). L'impact des facteurs externes sur l'utilite percue des nouvelles technologies dans les PME de la region Oranaise [The impact of external factors on the perceived usefulness of new technologies in SMEs in the Oranian region]. The Journal of Economic Integration, 9(4), 817-832.
  33. Fendouchi, R. (2013). Muhadidat istikhdam tiknulujia almalumat walitisalat fi alaitisal altanzimi: Dirasat hala li saidal fi elmidya [Determinants of ICT Use in Organizational Communication: The case study of Saidal in Medea]. University of Algiers 3.
  34. Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
  35. Furness, C. D. (2010). Group Information Behavioural Norms and the Effective Use of a Collaborative Information System: A Case Study. University of Toronto.
  36. Gardner, C., and Amoroso, D. L. (2004). Development of an instrument to measure the acceptance of internet technology by consumers. Proceedings of the Hawaii International Conference on System Sciences, 37(C), 4143-4152.
  37. Gefen, D., and Straub, D. (2000). The relative importance of perceived ease of use in is adoption: A study of e-commerce adoption. Journal of the Association for Information Systems, 1, 1-30. https://doi.org/10.17705/1jais.00008
  38. Gogus, C. G., and Ozer, G. (2014). The roles of technology acceptance model antecedents and switching cost on accounting software use. Journal of Management Information and Decision Sciences, 17(1), 1-24.
  39. Gopalakrishna-Remani, V., Jones, R. P. J., and Wooldridge, B. R. (2016). Influence of institutional forces on managerial beliefs and healthcare analytics adoption. Journal of Managerial Issues, 28(3/4), 191-204.
  40. Gourine, H. K., Abbou, A., and Benyoucef, A. (2019). Tatbiq tiknulujia almalumat fil jazayir bayn muhadidat alqabul wa muqawamat altaghyiri: Dirasa maydania [The Application of Information Technology in Algeria between Determinants of Acceptance and Resistance to Change: A field study]. Regional Studies Journal, 13(41), 07-34.
  41. Granlund, M. (2009). On the Interface between Accounting and Modern Information Technology. Turku School of Economics.
  42. Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2014). Multivariate Data Analysis (7th ed.). Pearson Education Limited.
  43. Hong, I. B. (2018). Social and personal dimensions as predictors of sustainable intention to use facebook in Korea: An empirical analysis. Sustainability (Switzerland), 10(8), 1-16. https://doi.org/10.3390/su10082856
  44. Hong, S. J., Thong, J. Y. L., and Tam, K. Y. (2006). Understanding continued information technology usage behavior: A comparison of three models in the context of mobile internet. Decision Support Systems, 42(3), 1819-1834. https://doi.org/10.1016/j.dss.2006.03.009
  45. Hooper, D., Coughlan, J., and Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53-60.
  46. Howard, N. (2016). Technology Acceptance, Organisational Change and Autonomous Motivation: Reducing the Crowding-Out Effect in the Non-Profit Sector By. University of Tasmania.
  47. Hubona, G. S., and Kennick, E. (1996). The influence of external variables on information technology usage behavior. Proceedings of the 29th Annual Hawaii International Conference on System Sciences, 4, 166-175.
  48. Huy, P. Q., and Phuc, V. K. (2019). Intention for adopting management accounting system: An empirical research of exploration to public non-business generating agencies. International Journal of Recent Technology and Engineering, 8(3S2), 343-351.
  49. Igbaria, M., Zinatelli, N., Cragg, P., and Cavaye, A. L. M. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS Quarterly, 279-301.
  50. Jackson, J. D., Yi, M. Y., and Park, J. S. (2013). An empirical test of three mediation models for the relationship between personal innovativeness and user acceptance of technology. Information and Management, 50(4), 154-161. https://doi.org/10.1016/j.im.2013.02.006
  51. Jan, P. T., Lu, H. P., and Chou, T. C. (2012). The adoption of e-learning: An institutional theory perspective. Turkish Online Journal of Educational Technology, 11(3), 326-343.
  52. Jeffrey, D. A. (2015). Testing the technology acceptance model 3 (TAM 3) with the inclusion of change fatigue and overload, in the context of faculty from Seventh- day Adventist Universities: A revised model. In Dissertations. Andrews University.
  53. Jeong, H. (2011). An investigation of user perceptions and behavioral intentions towards the e-library. Library Collections, Acquisition and Technical Services, 35(2-3), 45-60. https://doi.org/10.1080/14649055.2011.10766298
  54. Joshi, A., Kale, S., Chandel, S., and Pal, D. (2015). Likert Scale: Explored and explained. British Journal of Applied Science & Technology, 7(4), 396-403. https://doi.org/10.9734/BJAST/2015/14975
  55. Jooriaby, M. E., Khadyar, S., and Azadihiar, K. (2020). The study of institutional pressures effects on accountants' intentions of accounting information system adoption: Empirical evidence of unified theory of acceptance and use of technology. Journal of Accounting Advances, 12(1), 27-63
  56. Karahanna, E., Agarwal, R., and Angst, C. M. (2006). Reconceptualizing compatibility beliefs technology acceptance. MIS Quarterly, 30(4), 781-804. https://doi.org/10.2307/25148754
  57. Karahanna, E., and Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-of-use. Information and Management, 35(4), 237-250. https://doi.org/10.1016/S0378-7206(98)00096-2
  58. Karahanna, E., Straub, D. W., and Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly: Management Information Systems, 23(2), 183-213. https://doi.org/10.2307/249751
  59. Karimi, J., and Konsynski, B. (2003). The Information technology and management infrastructure strategy: Globalization and information management strategies. In R. D. Galliers and D. E. Leidner (Eds.), Strategic Information Management: Challenges and strategies in managing information systems, (3rd ed). London.
  60. Khairi, M. S., and Baridwan, Z. (2015). An empirical study on organizational acceptance accounting information systems in Sharia banking. The International Journal of Accounting and Business Society, 23(1), 97-122.
  61. Khalifa, M., and Davison, R. M. (2006). SME adoption of IT: The case of electronic trading systems. IEEE Transactions On Engineering Management, 53(2), 275-284. https://doi.org/10.1109/TEM.2006.872251
  62. Kim, H., Ku, B., Kim, J. Y., Park, Y. J., and Park, Y. B. (2016). Confirmatory and exploratory factor analysis for validating the phlegm pattern questionnaire for healthy subjects. Evidence-Based Complementary and Alternative Medicine, 2016, 01-08. https://doi.org/10.1155/2016/2696019
  63. Kline, R. (2016). Principles and practice of structural equation modeling (4th ed.). The Guilford Press.
  64. Kothari, C. R. (2004). Research Methodology: Methods and Techniques. New Age International.
  65. Lee, K., Yan, A., and Joshi, K. (2010). Understanding the dynamics of users' belief in software application adoption. International Journal of Information Management, 31(2), 160-170.
  66. Lee, Y., Kozar, K. A., and Larsen, K. R. T. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12, 752-780. https://doi.org/10.17705/1CAIS.01250
  67. Legris, P., Ingham, J., and Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191-204. https://doi.org/10.1016/S0378-7206(01)00143-4
  68. Lewis, W., Agarwal, R., and Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge workers. MIS Quarterly, 27(4), 657-678. https://doi.org/10.2307/30036552
  69. Li, D., Ahn, J. S., Zhou, R., and Wu, B. (2009). A study on the influence of country image on purchase intention of Chinese consumers based on Fishbein's model of reasoned action: Focused on USA, Germany, Japan and South Korea. Frontiers of Business Research in China, 3(4), 621-646. https://doi.org/10.1007/s11782-009-0030-2
  70. Liang, H., Saraf, N., Hu, Q., and Xue, Y. (2007). Assimilation of enterprise systems: The effect of institutional pressures and the mediating role of top management. MIS Quarterly, 31(1), 59-87. https://doi.org/10.2307/25148781
  71. Limayem, M., Cheung, C., and Chan, G. (2003). Explaining information systems adoption and post-adoption: Toward an integrative model. ICIS 2003 Proceedings, 59.
  72. Linders, S. (2006). Using the technology acceptance model in determining strategies for implementation of mandatory IS. 4th Twente Student Conference on IT.
  73. Lule, I., Omwansa, tonny K., and Waema, T. M. (2012). Application of technology acceptance model (TAM) in M-Banking adoption in Kenya. International Journal of Computing and ICT Research, 6(1), 31-43.
  74. Mariani, M. G., Curcuruto, M., and Gaetani, I. (2013). Training opportunities, technology acceptance and job satisfaction: A study of Italian organizations. Journal of Workplace Learning, 25(7), 455-475. https://doi.org/10.1108/JWL-12-2011-0071
  75. Marler, J. H., Fisher, S. L., and Ke, W. (2009). Employee self-service technology acceptance: A comparison of pre-implementation and post-implementation relationships. Personnel Psychology, 62(2), 327-358. https://doi.org/10.1111/j.1744-6570.2009.01140.x
  76. Marshall, B., Mills, R., and Olsen, D. (2008). The role of religiosity in technology acceptance. Censorship, Surveillance, and Privacy, 12(2), 01-08.
  77. Mathieson, K., Peacock, E., and Chin, W. W. (2001). Extending the technology acceptance model: The influence of perceived user resources. Data Base for Advances in Information Systems, 32(3), 86-112. https://doi.org/10.1145/506724.506730
  78. Maulana, M. R. S., and Rufaidah, P. (2014). Co-creation of small-medium enterprises. Procedia - Social and Behavioral Sciences, 115, 198-206. https://doi.org/10.1016/j.sbspro.2014.02.428
  79. Mccoach, D. B. (2003). SEM Isn't just the schoolwide enrichment model anymore: Structural equation modeling (SEM) in Gifted Education. Journal for the Education of the Gifted, 27(1), 36-61. https://doi.org/10.1177/016235320302700104
  80. Misba, M. F. H., and Jailani. (2019). The Construct validity of skills for learning questionnaire to measure the skill gap in vocational high school. Advances in Social Science, Education and Humanities Research, 379, 132-137. https://doi.org/10.2991/assehr.k.191217.022
  81. Moore, G. C., and Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222. https://doi.org/10.1287/isre.2.3.192
  82. Moore, G. C., and Benbasat, I. (1996). Integrating diffusion of innovations and theory of reasoned action models to predict utilization of information technology by end-users. Diffusion and Adoption of Information Technology, (pp. 132-146). Springer, Boston, MA.
  83. Morris, M. G., Venkatesh, V., and Ackerman, P. L. (2005). Gender and age differences in employee decisions about new technology: An extension to the theory of planned behavior. IEEE Transactions on Engineering Management, 52(1), 69-84. https://doi.org/10.1109/TEM.2004.839967
  84. Nelson, R. R., and Cheney, P. H. (1987). Training end users: An exploratory study. MIS Quarterly: Management Information Systems, 11(4), 547-559. https://doi.org/10.2307/248985
  85. Ngadiman, Pambudi, D., Wardani, D. K., and Sabandi, M. (2017). Determinants of accounting information technology adoption in Syaria micro financial institutions. Asian Social Science, 10(14), 93-105.
  86. Olushola, T., and Abiola, J. O. (2017). The efficacy of technology acceptance model: A review of applicable theoretical models in information technology researches. Journal of Research in Business and Management, 4(11), 70-83.
  87. Park, S. Y., Nam, M. W., and Cha, S. B. (2012). University students' behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology, 43(4), 592-605. https://doi.org/10.1111/j.1467-8535.2011.01229.x
  88. Pearse, N. (2011). Deciding on the scale granularity of response categories of likert type scales: The case of a 21-point scale. Electronic Journal of Business Research Methods, 9(2), 159-171.
  89. Pentina, I., Koh, A. C., and Le, T. T. (2012). Adoption of social networks marketing by SMEs: Exploring the role of social influences and experience in technology acceptance. International Journal of Internet Marketing and Advertising, 7(1), 65-82. https://doi.org/10.1504/IJIMA.2012.044959
  90. Permana, I., Thomas, P., and Kardoyo. (2019). The Acceptance analysis of financial accounting standards for entities without public accountability (Fas-Ewpa) in Cirebon Regency Cooperatives using technology acceptance model (TAM). Journal of Economic Education, 8(2), 87-95.
  91. Premkumar, G., and Bhattacherjee, A. (2008). Explaining information technology usage: A test of competing models. Omega, 36(1), 64-75. https://doi.org/10.1016/j.omega.2005.12.002
  92. Rabaa'i, A. A. (2016). Extending the technology acceptance model (TAM) to assess Students' behavioural intentions to adopt an e-learning system: The case of moodle as a learning tool. Journal of Emerging Trends in Engineering and Applied Sciences, 7(1), 13-30.
  93. Rogers, A. D. (2016). Examining Small Business Adoption of Computerized Accounting Systems Using the Technology Acceptance Model. Walden University College.
  94. Schillewaert, N., Ahearne, M. J., Frambach, R. T., and Moenaert, R. K. (2000). The adoption of information technology in the sales force. Industrial Marketing Management, 34(4), 323-336.
  95. Segars, A. H., and Grover, V. (1993). Re-examining perceived ease of use and usefulness: A confirmatory factor analysis. MIS Quarterly: Management Information Systems, 17(4), 517-525. https://doi.org/10.2307/249590
  96. Shadfar, S., and Malekmohammadi, I. (2013). Application of structural equation modeling (SEM) in restructuring state intervention strategies toward paddy production development. International Journal of Academic Research in Business and Social Sciences, 3(12), 576-618. https://doi.org/10.6007/IJARBSS/v3-i12/472
  97. Shareia, B. (2016). Accounting information systems in developing countries. Journal of Business & Economic Policy, 3(1), 46-57.
  98. Sharma, R., and Mishra, R. (2014). A review of evolution of theories and models of technology adoption. Indore Management Journal, 6(2), 17-29.
  99. Sharp, J. H. (2006). Development, extension, and application: A review of the technology acceptance model. Director, 23, 0-2.
  100. Shi, D., Lee, T., and Maydeu-Olivares, A. (2019). Understanding the model size effect on SEM Fit indices. Educational and Psychological Measurement, 79(2), 310-334. https://doi.org/10.1177/0013164418783530
  101. Siegel, D. M. (2008). Accepting technology and overcoming resistance to change using the motivation and acceptance model. University of Central Florida.
  102. Simon, S. J., Grover, V., Teng, J. T. C., and Whitcomb, K. (1996). The relationship of information system training methods and cognitive ability to end-user satisfaction, comprehension, and skill transfer: A longitudinal field study. Information Systems Research, 7(4), 466-490. https://doi.org/10.1287/isre.7.4.466
  103. Soudani, S. N. (2012). The usefulness of an accounting information system for effective organizational performance. International Journal of Economics and Finance, 4(5), 136-145. https://doi.org/10.5539/ijef.v4n5p136
  104. Sun, H., and Zhang, P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human Computer Studies, 64(2), 53-78. https://doi.org/10.1016/j.ijhcs.2005.04.013
  105. Tarcan, E., Varol, E. S., Kantarci, K., and Firlar, T. (2012). A study on Kazakh Academicians' Information technology acceptance. Bilig, 62, 205-230.
  106. Teo, H., Wei, K., and Benbasat, I. (2003). Predicting intention to adopt interorganizational linkages: An institutional perspective. MIS Quarterly, 27(1), 19-49. https://doi.org/10.2307/30036518
  107. Teo, T., and Noyes, J. (2011). An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modelling approach. Human Rights, 57(02), 1645-1653. https://doi.org/10.1016/j.compedu.2011.03.002
  108. Thakkar, J. J. (2020). Structural Equation Modelling: Application for Research and Practice (with AMOS and R). Springer.
  109. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365. https://doi.org/10.1287/isre.11.4.342.11872
  110. Venkatesh, V., and Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
  111. Venkatesh, V., and Davis, F. D. (2000). A Theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(02), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  112. Venkatesh, V., Morris, M. G., and Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision-making processes. Organizational Behavior and Human Decision Processes, 83(1), 33-60. https://doi.org/10.1006/obhd.2000.2896
  113. Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(03), 425-478. https://doi.org/10.2307/30036540
  114. Venkatesh, V., Thong, J. Y. L., Chan, F. K. Y., Hu, P. J. H., and Brown, S. A. (2011). Extending the two-stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Information Systems Journal, 21(6), 527-555. https://doi.org/10.1111/j.1365-2575.2011.00373.x
  115. Venkatesh, V., Thong, J. Y. L., and Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
  116. Wang, X., French, B. F., and Clay, P. F. (2015). Convergent and discriminant validity with formative measurement: A mediator perspective. Journal of Modern Applied Statistical Methods, 14(1), 83-106. https://doi.org/10.22237/jmasm/1430453400
  117. Weston, R., and Gore, P. A. (2006). A brief guide to structural equation modeling. The Counseling Psychologist, 34(5), 719-751. https://doi.org/10.1177/0011000006286345
  118. Wixom, B. H., and Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102. https://doi.org/10.1287/isre.1050.0042
  119. Wu, M. C., and Kuo, F. Y. (2008). An empirical investigation of habitual usage and past usage on technology acceptance evaluations and continuance intention. Data Base for Advances in Information Systems, 39(4), 48-73. https://doi.org/10.1145/1453794.1453801
  120. Yousafzai, S. Y., Foxall, G. R., and Pallister, J. G. (2007). Technology acceptance: A meta-analysis of the TAM: Part 1. Journal of Modelling in Management, 2(3), 251-280.
  121. Yucel, A., Gulbahar, U., and Yasemin, Y. (2013). Technology acceptance model: A review of the prior predictors. Ankara Universitesi Egitim Bilimleri Fakultesi Dergisi, 46(1), 89-109. https://doi.org/10.1501/Egifak_0000001275