|
1. 方妙玲和劉博民 (2016)。員工自我導向學習與工作績效之關聯性研究。服務業管理評論,14,49-75。 2. 李勇輝 (2017)。學習動機、學習策略與學習成效關係之研究–以數位學習為例。經營管理學刊,14,68-86。 3. 杜瑞澤、邱淑萍、莊立文和朱維政 (2013)。遠距教學之線上學習成效影響因子之研究。文化創意產業研究學報,3(4),157-166。 4. 吳玫瑩和莊涵芬 (2015)。台灣便利商店員工使用數位學習平台的學習成效之研究。Journal of Data Analysis,10(6),27-49。 5. 林士平、洪淑萍和蔡佩思 (2019)。運用UTAUT模型探討不同產品類型行動適地性廣告之用戶接受度。科技管理學刊,24(2),61-86。 6. 林育如 (2021)。互動科技應用展示設計課程之情境教學策略研究。藝見學刊,22,37-60。 7. 林信志、湯凱雯和賴信志 (2010)。以科技接受模式探討大學生學習以網路教學系統製作數位教材之意圖和成效。數位學習科技期刊,2(1),60-78。 8. 林素鉁和趙正敏 (2021)。民眾對行動健康照護採用行為意圖之決定因素? 擴展UTAUT模式。管理資訊計算,10(2),10-23。 9. 林進財、陳瑞全和陳啟斌 (2007)。E-learning學習績效運用模糊法評估。資訊管理學報,14(2),247-271。 10. 施智婷、陳旭耀和黃良志 (2011)。主管管理職能提升:自我導向學習與知覺組織支持的交互效果。臺大管理論叢,22(1),135-164。 11. 陳成恩、蘭卉、侯均穎和張玲嘉 (2021)。體育教師專業能力對國小學生學習滿意度與學習成效之影響。休閒運動健康評論,10(1),17-30。 12. 張書瑋 (2019a)。會計人的數位轉型大調查。會計研究月刊,409,64-75。 13. 張書瑋 (2019b)。從學校教育到職場實務:一場會計人的數位變革,你起跑了嗎?。會計研究月刊,409,76-84。 14. 張夢凡和張松山 (2010)。自我導向學習與繼續進修意願之探討–以滿意度為中介變項之實證研究。工業科技教育學刊,3,33-40。 15. 曾瑞譙 (2009)。電腦輔助教學軟體使用後之效益分析–科技接受模式的觀點與應用。新竹教育大學教育學報,26(2),127-163。 16. 黃曉雯 (2019)。CPA查核眼:新世代數位審計。會計研究月刊,407,66-74。 17. 黃曉雯 (2020)。零接觸革命打造企業數位DNA:專訪安侯建業聯合會計師事務所資訊長陳秋正、人資長張淑瑩。會計研究月刊,418,75-77。 18. 廖珮妏 (2015)。從量化與質化研究信效度探討社會科學領域的研究品質。中華科技大學學報,62,69-88。 19. 廖珮妏、余鑑和于俊傑 (2012)。應用整合型科技接受模式與創新擴散通用模型於企業導入數位學習之多層次分析。電子商務學報,14(4),657-687。 20. 鄧運林 (1995)。成人教學與自我導向學習。臺北市:五南圖書出版。 21. 蘇金輝 (2021)。現象為本學習結合社會實踐對自我導向之影響。通識學刊:理念與實務,9(1),49-87。 22. PGi樺鼎 (2022)。跨行業通用的部門流程。 https://www.perform-global.com/product-uipath/#1628147678016-6c90968d-a0f8 (2022年4月19日)。
23. Abbad, M. M. (2021). Using the UTAUT model to understand students’ usage of e-learning systems in developing countries. Education and Information Technologies, 26(6), 7205-7224. 24. Adams, S. (2006). An introduction to learning outcomes: A consideration of the nature, function and position of learning outcomes in the creation of the European higher education area. EUA Bologna Handbook: Making Bologna Work, 4, 2-22. 25. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. 26. Al-Adwan, A. S., Al-Madadha, A., and Zvirzdinaite, Z. (2018). Modeling students’ readiness to adopt mobile learning in higher education: An empirical study. International Review of Research in Open and Distributed Learning, 19(1), 221-241. 27. Alam, M. Z., Hoque, M. R., Hu, W., and Barua, Z. (2020). Factors influencing the adoption of mHealth services in a developing country: A patient-centric study. International Journal of Information Management, 50, 128-143. 28. Almaiah, M. A., Alamri, M. M., and Al-Rahmi, W. (2019). Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education. IEEE Access, 7, 174673-174686. 29. Alonderienė, R., and Suchotina, N. (2017). The impact of self-directed learning on work performance of lawyers. Organizations and Markets in Emerging Economies, 8, 165-176. 30. Al-Saedi, K., Al-Emran, M., Ramayah, T., and Abusham, E. (2020). Developing a general extended UTAUT model for m-payment adoption. Technology in Society, 62, 101293. 31. Automation Anywhere. (2020). Global research reveals world’s ‘most hated’ office tasks. https://www.automationanywhere.com/company/press-room/global- research-reveals-world-s-most-hated-office-tasks (2022, February 28). 32. Automation Anywhere. (2022a). What is robotic process automation (RPA)?. https://www.automationanywhere.com/rpa/robotic-process-automation (2022, March 27). 33. Automation Anywhere. (2022b). Explore RPA and intelligent automation solutions across industries, teams, and technologies. https://www.automationanywhere.com/solutions (2022, April 17). 34. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. 35. Bonham, L. A. (1989). Self-directed orientation toward learning: A learning style. Self-Directed Learning: Emerging Theory and Practice. University of Oklahoma: Oklahoma Research Center for Continuing Professional and Higher Education. 36. Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10, 1652. 37. Chen, C. H., Chen, K. Z., and Tsai, H. F. (2022). Did self-directed learning curriculum guidelines change Taiwanese high-school students’ self-directed learning readiness?. The Asia-Pacific Education Researcher, 31(4), 409-426. 38. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336. 39. Chin, W. W., and Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. Statistical Strategies for Small Sample Research, 1(1), 307-341. 40. Cooper, L. A., Holderness Jr, D. K., Sorensen, T. L., and Wood, D. A. (2019). Robotic process automation in public accounting. Accounting Horizons, 33(4), 15-35. 41. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319-340. 42. 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. 43. Dehnad, A., Afsharian, F., Hosseini, F., Arabshahi, S. K. S., and Bigdeli, S. (2014). Pursuing a definition of self-directed learning in literature from 2000–2012. Procedia-Social and Behavioral Sciences, 116, 5184-5187. 44. Deloitte. (2017). The robots are ready. Are you? Untapped advantage in your digital workforce. 45. Devarajan, Y. (2018). A study of robotic process automation use cases today for tomorrow’s business. International Journal of Computer Techniques, 5(6), 12-18. 46. Dey, S., and Das, A. (2019). Robotic process automation: Assessment of the technology for transformation of business processes. International Journal of Business Process Integration and Management, 9(3), 220-230. 47. Eulerich, M., Pawlowski, J., Waddoups, N. J., and Wood, D. A. (2022). A framework for using robotic process automation for audit tasks. Contemporary Accounting Research, 39(1), 691-720. 48. Fernandez, D., and Aman, A. (2018). Impacts of robotic process automation on global accounting services. Asian Journal of Accounting and Governance, 9(1), 127-140. 49. Fishbein, M., and Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. 50. Fisher, M., King, J., and Tague, G. (2001). Development of a self-directed learning readiness scale for nursing education. Nurse Education Today, 21(7), 516-525. 51. 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. 52.Fung, H. P. (2014). Criteria, use cases and effects of information technology process automation (ITPA). Advances in Robotics and Automation, 3(3), 1-11. 53. Gartner. (2020). Gartner says worldwide robotic process automation software revenue to reach nearly $2 billion in 2021. https://www.gartner.com/en/newsroom/press-releases/2020-09-21-gartner-says-worldwide-robotic-process-automation-software-revenue-to-reach-nearly-2-billion-in-2021 (2022, February 28). 54. Gartner. (2022). Robotic process automation (RPA). https://www.gartner.com/en/information-technology/glossary/robotic-process-automation-rpa (2022, March 17). 55. Gotthardt, M., Koivulaakso, D., Paksoy, O., Saramo, C., Martikainen, M., and Lehner, O. (2020). Current state and challenges in the implementation of smart robotic process automation in accounting and auditing. ACRN Journal of Finance and Risk Perspectives, 9, 90-102. 56. Guglielmino, L. M. (1977). Development of the self-directed learning readiness scale. Dissertation Abstracts International, 38, 64-67. 57. Hsu, C. L., Lin, Y. H., Chen, M. C., Chang, K. C., and Hsieh, A. Y. (2017). Investigating the determinants of e-book adoption. Program, 51(1), 2-16. 58. Huang, F., and Vasarhelyi, M. A. (2019). Applying robotic process automation (RPA) in auditing: A framework. International Journal of Accounting Information Systems, 35, 100433. 59. 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. 60. IEEE Corporate Advisory Group. (2017). IEEE guide for terms and concepts in intelligent process automation. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8070671. 61. Information Services Group. (2018). RPA in Europe: Enterprise plans, budgets and organizational impact. 62. Ivančić, L., Suša Vugec, D., and Bosilj Vukšić, V. (2019, September). Robotic process automation: systematic literature review. In 2019 International Conference on Business Process Management (pp. 280-295). Springer, Cham. 63. Jędrzejka, D. (2019). Robotic process automation and its impact on accounting. Zeszyty Teoretyczne Rachunkowości, 161(105), 137-166. 64. Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36. 65. Kettles, N., and Van Belle, J. P. (2019, August). Investigation into the antecedents of autonomous car acceptance using an enhanced UTAUT model. In 2019 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD) (pp. 1-6). IEEE. 66. Khalilzadeh, J., Ozturk, A. B., and Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460-474. 67. Kim, E. (2015). Effect of discussion activities and interactions with faculty to mediate self-directed learning capability on learning outcomes of college students. KEDI Journal of Educational Policy, 12(2), 173-196. 68. Kim, M., and Choi, D. (2018). Effects of self-directed learning readiness on academic performance and perceived usefulness for each element of flipped learning. Educational Technology International, 19(1), 123-151. 69. Kim, S., Lee, K. H., Hwang, H., and Yoo, S. (2015). Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital. BMC Medical Informatics and Decision Making, 16(1), 1-12. 70. Knowles, M. (1975). Self-directed learning: A guide for learners and teachers. New York: Association Press. 71. Kokina, J., and Blanchette, S. (2019). Early evidence of digital labor in accounting: Innovation with robotic process automation. International Journal of Accounting Information Systems, 35, 100431. 72. Kokina, J., Gilleran, R., Blanchette, S., and Stoddard, D. (2021). Accountant as digital innovator: Roles and competencies in the age of automation. Accounting Horizons, 35(1), 153-184. 73. Kwangware, G. (2021). Assessment of participants’ level of interest in accepting and adopting robotics process automation as a technology tool in the finance and insurance sector: A quantitative correlational study (Doctoral dissertation, Northcentral University). 74. Lacity, M., and Willcocks, L. (2015). Paper 15/07 robotic process automation: The next transformation lever for shared services. https://vdocuments.mx/paper-1507-robotic-process-automation-the-next-capabilities-derek-toone.html. 75. Lacity, M., Willcocks, L. P., and Craig, A. (2015). Robotic process automation: Mature capabilities in the energy sector. http://eprints.lse.ac.uk/64520/. 76. Leejoeiwara, B. (2013). Modeling adoption intention of online education in Thailand using the extended decomposed theory of planned behavior (DTPB) with self-directed learning. AU Journal of Management, 11(2), 13-26. 77. Lenz, E. R. (2010). Measurement in nursing and health research. New York: Springer Publishing Company. 78. Liew, B. T., Kang, M., Yoo, E., and You, J. (2013, June). Investigating the determinants of mobile learning acceptance in Korea. In 2013 EdMedia+innovate learning (pp. 1424-1430). Association for the Advancement of Computing in Education (AACE). 79. Loeng, S. (2020). Self-directed learning: A core concept in adult education. Education Research International, 4(5), 1-12. 80. Mbarek, R., and Zaddem, F. (2013). The examination of factors affecting e-learning effectiveness. International Journal of Innovation and Applied Studies, 2(4), 423-435. 81. Moffitt, K. C., Rozario, A. M., and Vasarhelyi, M. A. (2018). Robotic process automation for auditing. Journal of Emerging Technologies in Accounting, 15(1), 1-10. 82. 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. 83. Nunnally, J. C., and Bernstein, I. H. (1994). The assessment of reliability. Psychometric Theory, 3(1), 248-292. 84. Rahi, S., and Ghani, M. A. (2019). Investigating the role of UTAUT and e-service quality in internet banking adoption setting. The TQM Journal, 31(3), 491-506. 85. Rahi, S., Mansour, M. M. O., Alghizzawi, M., and Alnaser, F. M. (2019). Integration of UTAUT model in internet banking adoption context: The mediating role of performance expectancy and effort expectancy. Journal of Research in Interactive Marketing, 13(3), 411-435. 86. Rana, S., Ardichvili, A., and Polesello, D. (2016). Promoting self-directed learning in a learning organization: tools and practices. European Journal of Training and Development, 40(7), 470-489. 87. Salloum, S. A., and Shaalan, K. (2018, September). Factors affecting students’ acceptance of e-learning system in higher education using UTAUT and structural equation modeling approaches. In 2018 International Conference on Advanced Intelligent Systems and Informatics (pp. 469-480). Springer, Cham. 88. Sethibe, T., and Naidoo, E. (2022). The adoption of robotics in the auditing profession. South African Journal of Information Management, 24(1), 1-7. 89. Stout, D. E. (2014). Pack-and-Go delivery service: A multi-component cost-volume-profit (CVP) learning resource. Accounting Education, 23(1), 75-94. 90. Syed, R., Suriadi, S., Adams, M., Bandara, W., Leemans, S. J., Ouyang, C., ... and Reijers, H. A. (2020). Robotic process automation: Contemporary themes and challenges. Computers in Industry, 115, 103162. 91. Tak, P., and Panwar, S. (2017). Using UTAUT 2 model to predict mobile app based shopping: Evidences from India. Journal of Indian Business Research, 9(3), 248-264. 92. Tan, P. J. B. (2013). Applying the UTAUT to understand factors affecting the use of English e-learning websites in Taiwan. Sage Open, 3(4), 1-12. 93. Taylor, S., and Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176. 94. Thompson, R. L., Higgins, C. A., and Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125-143. 95. UiPath. (2021). UiPath named a leader for the third time in Gartner magic quadrant. https://www.uipath.com/blog/rpa/gartner-magic-quadrant-rpa-report (2022, March 13). 96. UiPath. (2022a). What is robotic process automation?. https://www.uipath.com/rpa/robotic-process-automation (2022, February 27). 97. UiPath. (2022b). Build simple automation for everyday tasks. https://www.uipath.com/product/studiox (2022, March 13). 98. UiPath. (2022c). RPA solutions for your industry, department, and technologies. https://www.uipath.com/solutions (2022, April 17). 99. UiPath. (2022d). Putting people at the center of Ikano Bank with automation. https://www.uipath.com/resources/automation-case-studies/ikano-bank-puts-people-at-the-center-with-automation (2022, April 26). 100. 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(3), 425-478. 101. Venkatesh, V., Thong, J. Y., 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. 102. Wang, H., Tao, D., Yu, N., and Qu, X. (2020). Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF. International Journal of Medical Informatics, 139, 104-156. 103. Watson, M. W., and Dow, K. E. (2010). Auditing operational compliance: The case of employee long distance piracy. Issues in Accounting Education, 25(3), 513-526. 104. Welch, R., Alade, T., and Nichol, L. (2020). Using the unified theory of acceptance and use of technology (UTAUT) model to determine factors affecting mobile learning adoption in the workplace: A study of the science museum group. IADIS International Journal on Computer Science and Information Systems, 15(1), 85-98. 105. Wiley, K. (1983). Effects of a self-directed learning project and preference for structure on self-directed learning readiness. Nursing Research, 32(3), 181-185. 106. Willcocks, L. P., Lacity, M., and Craig, A. (2015). The IT function and robotic process automation. http://eprints.lse.ac.uk/64519/. 107. Williams, M. D., Rana, N. P., and Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): A literature review. Journal of Enterprise Information Management, 28(3), 443-488. 108. Williamson, S. N. (2007). Development of a self-rating scale of self-directed learning. Nurse Researcher, 14(2), 66-83. 109. Zhang, C. A., Dai, J., and Vasarhelyi, M. A. (2018). The impact of disruptivetechnologies on accounting and auditing education: How should the profession adapt?. The CPA Journal, 88(9), 20-26. |