English
19(10)2024
Ý định tiếp tục sử dụng phần mềm tại nơi làm việc trong bối cảnh chuyển đổi số: Tích hợp sự phù hợp giữa công nghệ - nhiệm vụ vào lý thuyết về tính liên tục của công nghệ
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Trường Đại học Công nghiệp Thành phố Hồ Chí Minh, Thành phố Hồ Chí Minh ,
Việt Nam
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Trường Đại học FPT, Thành phố Hồ Chí Minh ,
Việt Nam
Ngày nộp: 19-02-2024
Ngày duyệt đăng: 18-03-2024 Ngày xuất bản: 16-05-2024
Tóm tắt
Chỉ số JEL
Từ khóa
Trích dẫn:
Bui, K. T., & Tran, H. T. (2024). Ý định tiếp tục sử dụng phần mềm tại nơi làm việc trong bối cảnh chuyển đổi số: Tích hợp sự phù hợp giữa công nghệ - nhiệm vụ vào lý thuyết về tính liên tục của công nghệ [Investigating the intention to continue using software at work in digital transformation context: Integrating task - technology fit into technology continuance theory]. Tạp chí Khoa học Đại học Mở Thành phố Hồ Chí Minh – Kinh tế và Quản trị Kinh doanh, 19(10), 3-16. 10.46223/HCMCOUJS.econ.vi.19.10.3252.2024
Tài liệu tham khảo
Abd Ghani, M., Rahi, S., Yasin, N. M., & Alnaser, F. (2017). Adoption of internet banking: Extending the role of Technology Acceptance Model (TAM) with e-customer service and customer satisfaction. World Applied Sciences Journal, 35(9), 1918-1929.
Ajitha, A., Cha, J. Y., & Jayanty, K. (2022). E-banking: An empirical study on customer satisfaction. Journal of System and Management Sciences, 12(4), 27-38. doi:10.33168/JSMS.2022.0402
Al-Rahmi, W. M., Yahaya, N., Aldraiweesh, A. A., Alamri, M. M., Aljarboa, N. A., Alturki, U., & Aljeraiwi, A. A. (2019). Integrating technology acceptance model with innovation diffusion theory: An empirical investigation on students’ intention to use E-learning systems. IEEE Access, 7, 26797-26809.
Alturki, U., & Aldraiweesh, A. (2023). Integrated TTF and self-determination theories in higher education: The role of actual use of the massive open online courses. Frontiers in Psychology, 14, Article 1108325. doi:10.3389/fpsyg.2023.1108325
Alyoussef, I. Y. (2023). Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3), Article e13751. doi:10.1016/j.heliyon.2023.e13751
Baskaran, S., Lay, H. S., Ming, B. S., & Mahadi, N. (2020). Technology adoption and employee’s job performance: An empirical investigation. International Journal of Academic Research in Economics and Management Sciences, 9(1), 78-105.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 201-214. doi:10.2307/3250921
Bui, K. T., & Tran, K. (2021). Online project management service adoption intention: An integration of technology acceptance model and task-technology fit theory. Paper presented at 2021 IEEE International Conference on Computing (ICOCO), Kuala Lumpur, Malaysia.
Chou, S. W., Min, H. T., Chang, Y. C., & Lin, C. T. (2010). Understanding continuance intention of knowledge creation using extended expectation - confirmation theory: An empirical study of Taiwan and China online communities. Behaviour & Information Technology, 29(6), 557-570.
Daneji, A. A., Ayub, A. F. M., & Khambari, M. N. M. (2019). The effects of perceived usefulness, confirmation and satisfaction on continuance intention in using Massive Open Online Course (MOOC). Knowledge Management & E-Learning: An International Journal, 11(2), 201-214. doi:10.34105/j.kmel.2019.11.010
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
Foroughi, B., Iranmanesh, M., Kuppusamy, M., Ganesan, Y., Ghobakhloo, M., & Senali, M. G. (2023). Determinants of continuance intention to use gamification applications for task management: An extension of technology continuance theory. The Electronic Library, 41(2/3), 286-307.
Franque, F. B., Oliveira, T., Tam, C., & Santini, F. D. O. (2021). A meta-analysis of the quantitative studies in continuance intention to use an information system. Internet Research, 31(1), 123-158.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213-236. doi:10.2307/249689
Hair Jr., J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Washington D.C., DC: Sage Publications.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (Vol. 8). Hampshire, UK: Cengage Learning.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. London, UK: Sage Publications.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. doi:10.1007/s11747-014-0403-8
Hossain, M. A., & Quaddus, M. (2012). Expectation-confirmation theory in information system research: A review and analysis. In Y. K. Dwivedi, M. R. Wade & S. L. Schneberger (Eds.), Information systems theory: Explaining and predicting our digital society, vol. 1 (pp. 441-469). New York, NY: Springer New York.
Huang, L. C., Shiau, W. L., & Lin, Y. H. (2017). What factors satisfy e-book store customers? Development of a model to evaluate e-book user behavior and satisfaction. Internet Research, 27(3), 563-585.
Jin, Z., & Lim, C. K. (2021). Structural relationships among service quality, systemic characteristics, customer trust, perceived risk, customer satisfaction and intention of continuous use in mobile payment service. Journal of System and Management Sciences, 11(2), 48-64. doi:10.33168/JSMS.2021.0204
Khan, I. U., Hameed, Z., Yu, Y., Islam, T., Sheikh, Z., & Khan, S. U. (2018). Predicting the acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory. Telematics and Informatics, 35(4), 964-978.
Kim, J. H., Kim, M. S., Hong, R. K., & Ko, J. W. (2019). Continuous use intention of corporate mobile sns users and its determinants: Application of extended technology acceptance model. Journal of System and Management Sciences, 9(4), 12-28. doi:10.33168/jsms.2019.0402
Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309-320.
Liébana-Cabanillas, F., Singh, N., Kalinic, Z., & Carvajal-Trujillo, E. (2021). Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: A multi-analytical approach. Information Technology and Management, 22(2), 133-161. doi:10.1007/s10799-021-00328-6
Lin, W. S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. International Journal of Human-Computer Studies, 70(7), 498-507.
McLean, G., Osei-Frimpong, K., Al-Nabhani, K., & Marriott, H. (2020). Examining consumer attitudes towards retailers’ m-commerce mobile applications - An initial adoption vs. continuous use perspective. Journal of Business Research, 106, 139-157. doi:10.1016/j.jbusres.2019.08.032
Meher, J. R., & Mishra, R. K. (2021). Evaluation of perceived benefits and employee satisfaction through knowledge management practices. Global Knowledge, Memory and Communication, 71(1/2), 86-102. doi:10.1108/gkmc-11-2020-0181
Mosquera, A., Ayensa, E., Murillo, Y., & Pascual, C. (2018). Identifying omnichannel customer segments regarding the perceived usefulness, shopping enjoyment, and social influence. Paper presented at 2018 Center for Business & Industrial Marketing, Madrid, Spain.
Nagadeepa, C., Pushpa, A., Mukthar, K. J., Rurush-Asencio, R., Sifuentes-Stratti, J., & Rodriguez-Kong, J. (2024). User’s continuance intention towards banker’s chatbot service - A technology acceptance using SUS and TTF model. In Digital technology and changing roles in managerial and financial accounting: Theoretical knowledge and practical application (pp. 65-77). Leeds, UK: Emerald Publishing Limited.
Pandey, N., Tripathi, A., Jain, D., & Roy, S. (2020). Does price tolerance depend upon the type of product in e-retailing? Role of customer satisfaction, trust, loyalty, and perceived value. Journal of Strategic Marketing, 28(6), 522-541.
Rahi, S., Khan, M. M., & Alghizzawi, M. (2021). Extension of Technology Continuance Theory (TCT) with Task Technology Fit (TTF) in the context of Internet banking user continuance intention. International Journal of Quality & Reliability Management, 38(4), 986-1004.
Rauniar, R., Rawski, G., Yang, J., & Johnson, B. (2014). Technology Acceptance Model (TAM) and social media usage: An empirical study on Facebook. Journal of Enterprise Information Management, 27(1), 6-30.
Raza, S. A., Umer, A., & Shah, N. (2017). New determinants of ease of use and perceived usefulness for mobile banking adoption. International Journal of Electronic Customer Relationship Management, 11(1), 44-65.
Rienties, B., Giesbers, B., Tempelaar, D., Lygo-Baker, S., Segers, M., & Gijselaers, W. (2012). The role of scaffolding and motivation in CSCL. Computers & Education, 59(3), 893-906.
Samar, S., Ghani, M., & Alnaser, F. (2017). Predicting customer’s intentions to use internet banking: The role of Technology Acceptance Model (TAM) in e-banking. Management Science Letters, 7(11), 513-524.
Soria-Barreto, K., Ruiz-Campo, S., Al-Adwan, A. S., & Zuniga-Jara, S. (2021). University students intention to continue using online learning tools and technologies: An international comparison. Sustainability, 13(24), Article 13813.
Sun, S., Law, R., & Zhong, L. (2021). Mobile payment failure during travel. Journal of China Tourism Research, 17(1), 73-89.
Tu, Y. F., Hwang, G. J., Chen, J. C. C., & Lai, C. (2021). University students’ attitudes towards ubiquitous library-supported learning: An empirical investigation in the context of the Line@ Library. The Electronic Library, 39(1), 186-207.
Wan, L., Xie, S., & Shu, A. (2020). Toward an understanding of university students’ continued intention to use MOOCs: When UTAUT model meets TTF model. Sage Open, 10(3), 1-15. doi:10.1177/2158244020941858
Wu, L., Chiu, M. L., & Chen, K. W. (2020). Defining the determinants of online impulse buying through a shopping process of integrating perceived risk, expectation-confirmation model, and flow theory issues. International Journal of Information Management, 52, Article 102099.
Yang, Z., Sun, J., Zhang, Y., Wang, Y., & Cao, L. (2017). Employees’ collaborative use of green information systems for corporate sustainability: Motivation, effort and performance. Information Technology for Development, 23(3), 486-506.
Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20-34.
Zhanyou, W., Dongmei, H., & Yaopei, Z. (2020). How to improve users’ intentions to continued usage of shared bicycles: A mixed method approach. PLoS One, 15(2), Article e0229458. doi:10.1371/journal.pone.0229458
© The Author(s) 2024. This is an open access publication under CC BY NC licence.