* احمدپور، احمد؛ باقریان، رقیه؛ باقریان، عباس (1388). امکان سنجی بکارگیری زبان گزارشگری تجاری قابل توسعه در شرکتهای پذیرفته در بورس اوراق بهادار تهران، فصل نامه بورس، شماره6، 31-70.
* باقریان، عباس (1386). بورس الکترونیک، استانداردها و شبکههای هوشمند نظارتی، ماهنامۀ بورس، 1: 40-61.
* بزرگاصل،موسی و ولیپوررکنی،جمال (1385) .آشناییبا مفاهیم وکاربردزبانگزارشگری تجاریگسترشپذیر. فصلنامۀ حسابدار رسمی، 3(8 و 9): 83-90.
* جواد امانی ساری بگلو، مسعود غلامعلی لواسانی، جواد اژه ای و هیمن خضری آذر (1390). رابطه ارزش های فرهنگی و متغیرهای فردی با میزان استفاده از رایانه در دانشجویان. مجله علوم رفتاری، 5 (1): 1-10.
* سبحانی نژاد، مهدی، نوروزی، علی؛ امانی، جواد؛ حیات، علیاصغر (1389). تبیین نقش حمایت سازمانی، تجربه، اضطراب و خودکارآمدی رایانه در پیش بینی کاربست رایانه. مجله مطالعات روانشناسی تربیتی، 7 (11): 45-68.
* شیخ شعاعی، فاطمه و علومی، طاهره (1389). بررسی عوامل مؤثر بر پذیرش فناوری اطلاعات توسط کتابداران کتابخانههای دانشکدههای فنی دانشگاههای دولتی شهر تهران. کتابداری و اطلاع رسانی، جلد ۱۰ شماره3، 33-9.
* عربمازار یزدی، محمد (1383). گزارشگری مالی در عصر تجارت الکترونیکی، مجموعه سخنرانیها و مقالات همایش گزارشکری مالی، تحولات پیش روی، انجمن حسابداران خبرۀ ایران، دیماه 1383، 77-97.
* فردمال، جواد؛ جواد کشوری، کامران (1393). تعیین روایی و پایایی ابزار ارزیابی کاربردپذیری یک نرمافزار تحت وب. مجله ارگونومی، 2(3): 57-69.
* منصوری، فریده(1385). گزارشگری مالی ـ حسابرسی و آینده. فصلنامۀ حسابرس، شمارۀ 35، 72-75.
* نیکبخت، محمدرضا؛ گل کار، راحله (1390). بررسی عوامل موثر بر پذیرش زبان توسعه پذیر گزارشگری مالی در شرکت ملی پتروشیمی ایران و شرکتهای تابعه، فصل نامه بررسی های حسابداری و حسابرسی، شماره 66، 81-94.
* نیکومرام، هاشم؛ شکاری، ناصر (1389). ارتباط گزارشگری مالی قابل توسعه با ویژگیهای کیفی اطلاعات حسابداری از دیدگاه حسابداران ارشد شرکتهای پذیرفته شده در بورس اوراق بهادار. حسابداری مدیریت، 3 (6): 77-87.
* هومن، حیدر علی (1387). مدل یابی معادلات ساختاری با کاربرد نرم افزار لیزرل. تهران: انتشارات سمت.
* Akour, I. (2006). Factors influencing faculty computer Literacy and use in Jordan: A multivariate analysis. Doctoral Dissertation, Louisiana Tech University.
* Al-Qeisi, K., Dennis, C., Alamanos, E., & Jayawardhena, C. (2014). Website design quality and usage behavior: Unified theory of acceptance and use of technology. Journal of Business Research, 67(11), 2282-2290.
* Baldwin, A. A., & Trinkle, B. S. (2011). The impact of XBRL: A Delphi investigation. The International Journal of Digital Accounting Research, 11(17), 1-24.
* Baleghi-Zadeh, S., Ayub, A. F. M., Mahmud, R., & Daud, S. M. (2014). Behaviour Intention to Use the Learning Management: Integrating Technology Acceptance Model with Task-Technology Fit. Middle-East Journal of Scientific Research, 19, 76-84.
* Baran, K. S., & Stock, W. G. (2015, July). Interdependencies between acceptance and quality perceptions of social network services: the standard-dependent user blindness. In Proceedings of the 9th International Multi-Conference on Society, Cybernetics and Informatics (IMSCI 2015) (pp. 12-15).
* Bergeron. (2003).Essentials of XBRL. Financial reporting in the 21st century, Wiley, Hoboken, NJ.
* Boritz, J.E & W.G, No. (2003a). Business reporting with WML: XBRL (Extensible Business Reporting Language). The Internet Encyclopedia, John Wiley, New York.
* Chang, S. C., & Tung, F. C. (2008). An empirical investigation of students' behavioural intentions to use the online learning course websites. British Journal of Educational Technology, 39(1), 71-83.
* Chau,P.Y., & Hu, P. J. H. (2001). Information technology acceptance by individual professionals: A model comparison approach*. Decision Sciences, 32(4), 699-719.
* Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
* Doll,W.J. (1985). Avenues for top management involvement in successful MIS development. MIS quarterly, 17-35.
* Efendi,J., Park, J. D., & Smith, L. M. (2014). Do XBRL filings enhance informational efficiency? Early evidence from post-earnings announcement drift. Journal of Business Research, 67(6), 1099-1105.
* Esen, M., & Özbağ, G. K. (2014). An Investigation of the Effects of Organizational Readiness on Technology Acceptance in e-HRM Applications. International Journal of Human Resource Studies, 4(1), Pages-232.
* Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
* Gardner, C., & Amoroso, D. L. (2004, January). Development of an instrument to measure the acceptance of internet technology by consumers. In System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on (pp. 10-pp). IEEE.
* Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS quarterly, 213-236.
* Grosu, V., Hlaciuc, E., Iancu, E., Petris, R., & Socoliuc, M. (2010). The role of the XBRL standard in optimizing the financial reporting. arXiv preprint arXiv:1002.3997.
* Hernández, B., Jiménez, J., & Martín, M. J. (2008). Extending the technology acceptance model to include the IT decision-maker: A study of business management software. Technovation, 28(3), 112–121.
* Hsu, C. L., Lu, H. P., & Hsu, H. H. (2007). Adoption of the mobile Internet: An empirical study of multimedia message service (MMS). Omega, 35(6), 715-726.
* Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587-605.
* Igbaria, M., Parasuraman, S., & Baroudi, J. J. (1996). A motivational model of microcomputer usage. Journal of management information systems, 127-143.
* Jaruwachirathanakul, B., & Fink, D. (2005). Internet banking adoption strategies for a developing country: the case of Thailand. Internet research, 15(3), 295-311.
* Karahanna, E., Agarwal, R., & Angst, C. M. (2006). Reconceptualizing compatibility beliefs in technology acceptance research. Mis Quarterly, 781-804.
* Kelemen, Z. D., Bényász, G., & Badinka, Z. (2014). A measurement based software quality framework. arXiv preprint arXiv:1408.3253.
* Kim, H. J., Mannino, M., & Nieschwietz, R. J. (2009). Information technology acceptance in the internal audit profession: Impact of technology features and complexity. International Journal of Accounting Information Systems, 10(4), 214-228.
* King, W.R.and Rodriguez . J.I.(1978) Evaluating MIS , MIS Quarterly.
* Klopping, I. M., & McKinney, E. (2004). Extending the technology acceptance model and the task-technology fit model to consumer e-commerce. Information technology learning and performance journal, 22, 35-48.
* Kuo, R. Z., & Lee, G. G. (2011). Knowledge management system adoption: exploring the effects of empowering leadership, task-technology fit and compatibility. Behaviour & Information Technology, 30(1), 113-129.
* Lee, Y. H., Hsieh, Y. C., & Hsu, C. N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees' intentions to use e-learning systems. Journal of Educational Technology & Society, 14(4), 124-137.
* Lin, J. C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & management, 45(1), 65-74.
* Lu, H. P., & Yang, Y. W. (2014). Toward an understanding of the behavioral intention to use a social networking site: An extension of task-technology fit to social-technology fit. Computers in Human Behavior, 34, 323-332.
* Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1-13.
* Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information systems research, 2(3), 173-191.
* Oh, J., & Yoon, S. J. (2014). Validation of Haptic Enabling Technology Acceptance Model (HE-TAM): Integration of IDT and TAM. Telematics and Informatics, 31(4), 585-596.
* Oppenheim, R. (2008). XBRL 101-Value for the Accounting Professional, Business Analyst Company Executive, CPA Practice. Forum.4
* Park, N., Rhoads, M., Hou, J., & Lee, K. M. (2014). Understanding the acceptance of teleconferencing systems among employees: An extension of the technology acceptance model. Computers in Human Behavior, 39, 118-127.
* Plumlee, R. D., & Plumlee, M. A. (2008). Assurance on XBRL for financial reporting. Accounting Horizons, 22(3), 353-368.
* Ramirez, D. E. (2014). Perceptions of a learning management system: Acceptance, usefulness, and usage among university undergraduate faculty (Doctoral dissertation, UNIVERSITY OF THE INCARNATE WORD).
* Rogers, E.M. (1983), Diffusion of Innovations, Free Press, NewYork, NY. PP211
* Ryu, M. H., Kim, S., & Lee, E. (2009). Understanding the factors affecting online elderly user’s participation in video UCC services. Computers in Human Behavior, 25(3), 619-632.
* Srite, M. (2000). The influence of national culture on the acceptance and use of information technologies: An empirical study. Doctoral dissertation, Florida State University.
* Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
* Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS quarterly, 125-143.
* Venkatesh, V., & Brown, S. A. (2001). A longitudinal investigation of personal computers in homes: adoption determinants and emerging challenges. MIS quarterly, 71-102.
* Workman, M. (2014). New media and the changing face of information technology use: The importance of task pursuit, social influence, and experience. Computers in Human Behavior, 31, 111-117.
* Zain, M., Rose, R. C., Abdullah, I., & Masrom, M. (2005). The relationship between information technology acceptance and organizational agility in Malaysia. Information & Management, 42(6), 829-839.
* Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767