How to cite this paper
Rawashdeh, B & Rawashdeh, A. (2021). Factors influencing the usage of XBRL tools.Management Science Letters , 11(4), 1345-1356.
Refrences
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
Al-Rawashdeh, A. A. (2011). Diffusion of xbrl innovation model of adoption and usage. Universiti Utara Malaysia.
Alfin, R., Alhabsji, T., & Umar Nimran, S. (2013). Effect of service quality and product quality to corporate image, customer’s satisfaction and customer’s trust. IOSR Journal of Business and Management, 9(6), 1-9.
Alkhatib, E. a., Ojala, H., & Collis, J. (2019). Determinants of the voluntary adoption of digital reporting by small private companies to companies house: Evidence from the uk. International Journal of Accounting Information Systems, 34, 100421.
Almaiah, M. A., Alamri, M. M., & 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.
Althunibat, A., Zahrawi, A. A., Tamimi, A. A., & Altarawneh, F. H. (2019). Measuring the acceptance of using enterprise resource planning (erp) system in private jordanian universities using tam model. International Journal of Information and Education Technology, 9(7).
Ansary, M. E., Oubrich, M., Orlando, B., & Fiano, F. (2020). The determinants of xbrl adoption: A meta-analysis. International Journal of Managerial and Financial Accounting, 12(1), 1-24.
Asiati, D. I., Umar, H., & Sitinjak, T. (2019). The effects of service quality, image and trust on satisfaction and its impact on syari¡¯ ah bank customer loyalty in palembang. Business and Economic Research, 9(1), 295-316.
Baby, A., & Kannammal, A. (2020). Network path analysis for developing an enhanced tam model: A user-centric e-learning perspective. Computers in Human Behavior, 107, 106081.
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986, 23-28.
Bao, J. (2015). The impacts of e-service quality on customers’ repurchase intention in platform online retailing: An empirical investigation. Paper presented at the Wuhan International Conference on E-Business 2015 Proceedings.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological bulletin, 107(2), 238.
Bland, J. M., & Altman, D. G. (1997). Statistics notes: Cronbach's alpha. Bmj, 314(7080), 572.
Blankespoor, E. (2019). The impact of information processing costs on firm disclosure choice: Evidence from the xbrl mandate. Journal of Accounting Research, 57(4), 919-967.
Carter, L., Shaupp, L. C., Hobbs, J., & Campbell, R. (2011). The role of security and trust in the adoption of online tax filing. Transforming Government: People, Process and Policy.
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.
Chouhan, V., & Goswami, S. (2015). An analysis of xbrl adoption in india using technology acceptance model. IUP Journal of Information Technology, 11(3).
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
DeLone, W. H., & McLean, E. R. (2016). Information systems success measurement. Foundations and Trends® in Information Systems, 2(1), 1-116.
Efimova, O., Rozhnova, O., & Gorodetskaya, O. (2019). Xbrl as a tool for integrating financial and non-financial reporting. Paper presented at the The 2018 International Conference on Digital Science.
Fei, H., Huan, W., & Zi, Y. (2017). Empirical study on measuring the information satisfaction of online xbrl financial reports. Communication of Finance and Accounting, 2017(31), 6.
Gaskin, J., & Lim, J. (2016). Model fit measures. Gaskination’s StatWiki, 1-55.
Gitau, M. W. (2016). Application of the utaut model to understand the factors influencing the use of web 2.0 tools in e-learning in kenyan public universities. University of Nairobi.
Hair Jr, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2010). Sem: An introduction. Multivariate data analysis: A global perspective, 5(6), 629-686.
Handoko, B. L., Ariyanto, S., & Warganegara, D. L. (2018). Perception of financial auditor on usage of computer assisted audit techniques. Paper presented at the 2018 3rd International Conference on Computational Intelligence and Applications (ICCIA).
Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
Ilias, A., Ghani, E. K., Baidi, N., & Abdul, R. (2020). Xbrl adoption: An examination on the malaysian business reporting system (mbrs). Humanities, 8(2), 202-214.
Khechine, H., Raymond, B., & Augier, M. (2020). The adoption of a social learning system: Intrinsic value in the utaut model. British Journal of Educational Technology.
Lakovic, T., Rondovic, B., Backovic-Vulic, T., & Ivanovic, I. (2018). The determinants of xbrl adoption: An empirical study in an emerging economy. Paper presented at the European, Mediterranean, and Middle Eastern Conference on Information Systems.
Liu, C., Luo, X. R., & Wang, F. L. (2017). An empirical investigation on the impact of xbrl adoption on information asymmetry: Evidence from europe. Decision Support Systems, 93, 42-50.
Manrai, R., & Gupta, K. P. (2020). Integrating utaut with trust and perceived benefits to explain user adoption of mobile payments Strategic system assurance and business analytics (pp. 109-121): Springer.
Miladinovic, J., & Hong, X. (2016). A study on factors affecting the behavioral intention to use mobile shopping fashion apps in sweden.
Muchlis, F., Primadyan, M., Shauki, E. R., & Diyanty, V. (2019). Xamining xbrl early adopters: A study of determinants and value relevance. Paper presented at the Asia Pacific Business and Economics Conference (APBEC 2018).
Nourallah, M., Strandberg, C., & Öhman, P. (2019). Understanding the relationship between trust and satisfaction on mobile bank application. Paper presented at the Proceedings of the 2019 3rd International Conference on E-commerce, E-Business and E-Government.
Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of retailing, 57(3), 25–48.
Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020). Understanding consumer adoption of mobile payment in india: Extending meta-utaut model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54, 102144.
Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115-143.
Petersen, F., Jacobs, M., & Pather, S. (2020). Barriers for user acceptance of mobile health applications for diabetic patients: Applying the utaut model. Paper presented at the Conference on e-Business, e-Services and e-Society.
Pinsker, R. E., & Felden, C. (2016). Professional role and normative pressure: The case of voluntary xbrl adoption in germany. Journal of Emerging Technologies in Accounting, 13(1), 95-118.
Rahi, S., Mansour, M. M. O., Alghizzawi, M., & Alnaser, F. M. (2019). Integration of utaut model in internet banking adoption context. Journal of Research in Interactive Marketing.
Rawashdeh, A., & Selamat, M. H. (2013). Critical success factors relating to the adoption of xbrl in saudi arabia. Journal of International Technology and Information Management, 22(2), 4.
Rogers, E. M. (1983). Diffusion of innovations (1983): New York: Free Press.
Roloff, M. E. (1981). Interpersonal communication: The social exchange approach.
Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of consumer research, 15(3), 325-343.
Taiwo, A. A., Mahmood, A. K., & Downe, A. G. (2012). User acceptance of egovernment: Integrating risk and trust dimensions with utaut model. Paper presented at the 2012 international conference on computer & information science (ICCIS).
Taylor, D. G., & Strutton, D. (2010). Has e-marketing come of age? Modeling historical influences on post-adoption era internet consumer behaviors. Journal of business research, 63(9-10), 950-956.
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.
Tohang, V., & Lan, M. (2017). The impact of adoption of xbrl on information risk in representative countries of scandinavian region. Jurnal Keuangan dan Perbankan, 21(4), 197342.
Uyob, R. B., Bahador, K. M. B. K., & Noh, N. S. B. (2019). The determinants factors of accounting practitioner’s attitude towards the use of malaysian business reporting system (mbrs). International Journal of Business and Management, 3(5), 01-10.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Wrycza, S., Marcinkowski, B., & Gajda, D. (2017). The enriched utaut model for the acceptance of software engineering tools in academic education. Information systems management, 34(1), 38-49.
Wu, L., & Chen, J.-L. (2005). An extension of trust and tam model with tpb in the initial adoption of on-line tax: An empirical study. International Journal of Human-Computer Studies, 62(6), 784-808.
Al-Rawashdeh, A. A. (2011). Diffusion of xbrl innovation model of adoption and usage. Universiti Utara Malaysia.
Alfin, R., Alhabsji, T., & Umar Nimran, S. (2013). Effect of service quality and product quality to corporate image, customer’s satisfaction and customer’s trust. IOSR Journal of Business and Management, 9(6), 1-9.
Alkhatib, E. a., Ojala, H., & Collis, J. (2019). Determinants of the voluntary adoption of digital reporting by small private companies to companies house: Evidence from the uk. International Journal of Accounting Information Systems, 34, 100421.
Almaiah, M. A., Alamri, M. M., & 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.
Althunibat, A., Zahrawi, A. A., Tamimi, A. A., & Altarawneh, F. H. (2019). Measuring the acceptance of using enterprise resource planning (erp) system in private jordanian universities using tam model. International Journal of Information and Education Technology, 9(7).
Ansary, M. E., Oubrich, M., Orlando, B., & Fiano, F. (2020). The determinants of xbrl adoption: A meta-analysis. International Journal of Managerial and Financial Accounting, 12(1), 1-24.
Asiati, D. I., Umar, H., & Sitinjak, T. (2019). The effects of service quality, image and trust on satisfaction and its impact on syari¡¯ ah bank customer loyalty in palembang. Business and Economic Research, 9(1), 295-316.
Baby, A., & Kannammal, A. (2020). Network path analysis for developing an enhanced tam model: A user-centric e-learning perspective. Computers in Human Behavior, 107, 106081.
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986, 23-28.
Bao, J. (2015). The impacts of e-service quality on customers’ repurchase intention in platform online retailing: An empirical investigation. Paper presented at the Wuhan International Conference on E-Business 2015 Proceedings.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological bulletin, 107(2), 238.
Bland, J. M., & Altman, D. G. (1997). Statistics notes: Cronbach's alpha. Bmj, 314(7080), 572.
Blankespoor, E. (2019). The impact of information processing costs on firm disclosure choice: Evidence from the xbrl mandate. Journal of Accounting Research, 57(4), 919-967.
Carter, L., Shaupp, L. C., Hobbs, J., & Campbell, R. (2011). The role of security and trust in the adoption of online tax filing. Transforming Government: People, Process and Policy.
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.
Chouhan, V., & Goswami, S. (2015). An analysis of xbrl adoption in india using technology acceptance model. IUP Journal of Information Technology, 11(3).
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
DeLone, W. H., & McLean, E. R. (2016). Information systems success measurement. Foundations and Trends® in Information Systems, 2(1), 1-116.
Efimova, O., Rozhnova, O., & Gorodetskaya, O. (2019). Xbrl as a tool for integrating financial and non-financial reporting. Paper presented at the The 2018 International Conference on Digital Science.
Fei, H., Huan, W., & Zi, Y. (2017). Empirical study on measuring the information satisfaction of online xbrl financial reports. Communication of Finance and Accounting, 2017(31), 6.
Gaskin, J., & Lim, J. (2016). Model fit measures. Gaskination’s StatWiki, 1-55.
Gitau, M. W. (2016). Application of the utaut model to understand the factors influencing the use of web 2.0 tools in e-learning in kenyan public universities. University of Nairobi.
Hair Jr, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2010). Sem: An introduction. Multivariate data analysis: A global perspective, 5(6), 629-686.
Handoko, B. L., Ariyanto, S., & Warganegara, D. L. (2018). Perception of financial auditor on usage of computer assisted audit techniques. Paper presented at the 2018 3rd International Conference on Computational Intelligence and Applications (ICCIA).
Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
Ilias, A., Ghani, E. K., Baidi, N., & Abdul, R. (2020). Xbrl adoption: An examination on the malaysian business reporting system (mbrs). Humanities, 8(2), 202-214.
Khechine, H., Raymond, B., & Augier, M. (2020). The adoption of a social learning system: Intrinsic value in the utaut model. British Journal of Educational Technology.
Lakovic, T., Rondovic, B., Backovic-Vulic, T., & Ivanovic, I. (2018). The determinants of xbrl adoption: An empirical study in an emerging economy. Paper presented at the European, Mediterranean, and Middle Eastern Conference on Information Systems.
Liu, C., Luo, X. R., & Wang, F. L. (2017). An empirical investigation on the impact of xbrl adoption on information asymmetry: Evidence from europe. Decision Support Systems, 93, 42-50.
Manrai, R., & Gupta, K. P. (2020). Integrating utaut with trust and perceived benefits to explain user adoption of mobile payments Strategic system assurance and business analytics (pp. 109-121): Springer.
Miladinovic, J., & Hong, X. (2016). A study on factors affecting the behavioral intention to use mobile shopping fashion apps in sweden.
Muchlis, F., Primadyan, M., Shauki, E. R., & Diyanty, V. (2019). Xamining xbrl early adopters: A study of determinants and value relevance. Paper presented at the Asia Pacific Business and Economics Conference (APBEC 2018).
Nourallah, M., Strandberg, C., & Öhman, P. (2019). Understanding the relationship between trust and satisfaction on mobile bank application. Paper presented at the Proceedings of the 2019 3rd International Conference on E-commerce, E-Business and E-Government.
Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of retailing, 57(3), 25–48.
Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020). Understanding consumer adoption of mobile payment in india: Extending meta-utaut model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54, 102144.
Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115-143.
Petersen, F., Jacobs, M., & Pather, S. (2020). Barriers for user acceptance of mobile health applications for diabetic patients: Applying the utaut model. Paper presented at the Conference on e-Business, e-Services and e-Society.
Pinsker, R. E., & Felden, C. (2016). Professional role and normative pressure: The case of voluntary xbrl adoption in germany. Journal of Emerging Technologies in Accounting, 13(1), 95-118.
Rahi, S., Mansour, M. M. O., Alghizzawi, M., & Alnaser, F. M. (2019). Integration of utaut model in internet banking adoption context. Journal of Research in Interactive Marketing.
Rawashdeh, A., & Selamat, M. H. (2013). Critical success factors relating to the adoption of xbrl in saudi arabia. Journal of International Technology and Information Management, 22(2), 4.
Rogers, E. M. (1983). Diffusion of innovations (1983): New York: Free Press.
Roloff, M. E. (1981). Interpersonal communication: The social exchange approach.
Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of consumer research, 15(3), 325-343.
Taiwo, A. A., Mahmood, A. K., & Downe, A. G. (2012). User acceptance of egovernment: Integrating risk and trust dimensions with utaut model. Paper presented at the 2012 international conference on computer & information science (ICCIS).
Taylor, D. G., & Strutton, D. (2010). Has e-marketing come of age? Modeling historical influences on post-adoption era internet consumer behaviors. Journal of business research, 63(9-10), 950-956.
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.
Tohang, V., & Lan, M. (2017). The impact of adoption of xbrl on information risk in representative countries of scandinavian region. Jurnal Keuangan dan Perbankan, 21(4), 197342.
Uyob, R. B., Bahador, K. M. B. K., & Noh, N. S. B. (2019). The determinants factors of accounting practitioner’s attitude towards the use of malaysian business reporting system (mbrs). International Journal of Business and Management, 3(5), 01-10.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Wrycza, S., Marcinkowski, B., & Gajda, D. (2017). The enriched utaut model for the acceptance of software engineering tools in academic education. Information systems management, 34(1), 38-49.
Wu, L., & Chen, J.-L. (2005). An extension of trust and tam model with tpb in the initial adoption of on-line tax: An empirical study. International Journal of Human-Computer Studies, 62(6), 784-808.