Tecnologías relacionadas con Internet en la profesión de auditor: Una revisión bibliométrica de la WOS de las últimas tres décadas y un mapa de la estructura conceptual
Internet Related Technologies in the auditing profession: A WOS bibliometric review of the past three decades and conceptual structure mapping
Resumen
La investigación sobre las tecnologías relacionadas con Internet en la profesión de auditor ha crecido sustancialmente en las últimas tres décadas; sin embargo, está muy fragmentada. Este estudio pretende sintetizar y ofrecer una visión global de esa literatura. Utilizando técnicas bibliométricas y de análisis de contenido, este estudio proporciona una visión exhaustiva de la investigación sobre las tecnologías relacionadas con Internet en la profesión de auditor. El estudio utilizó bibliografía de la base de datos Web of Science que abarca tres décadas, desde 1990 hasta 2019. Se recuperaron y utilizaron para el análisis un total de 236 documentos académicos, escritos por 478 autores de 102 fuentes. Se utilizaron HistCite y Biblioshiny en R para ejecutar el análisis de citas y redes. Se identificaron las revistas influyentes, las instituciones, los artículos de tendencia y las colaboraciones importantes en red. Se utilizó el acoplamiento bibliográfico en un software de visualización de datos (VOSviewer) y el análisis de contenido en Excel para identificar las siguientes seis grandes corrientes de investigación: (1) el uso de big data en la profesión de auditoría, (2) el impacto de las tecnologías relacionadas con Internet en la auditoría continua, (3) los impactos de las tecnologías relacionadas con Internet en la calidad y la eficiencia de la auditoria, (4) el impacto de las tecnologías relacionadas con Internet en la detección del fraude y la evaluación del riesgo, (5) blockchain y la profesión de auditoria y (6) la auditoría en la nube y los sistemas de apoyo a la auditoría. También se proporcionaron posibles vías de investigación importantes e implicaciones prácticas de la investigación.
Descargas
Citas
Abbasi, A., Albrecht, C., Vance, A., & Hansen, J. (2012). Metafraud: a meta-learning framework for detecting financial fraud. Mis Quarterly, 36(4), 1293-1327. https://doi.org/10.2307/41703508
Alles, M., & Gray, G. L. (2016). Incorporating big data in audits: Identifying inhibitors and a research agenda to address those inhibitors. International Journal of Accounting Information Systems, 22, 44-59. https://doi.org/10.1016/j.accinf.2016.07.004
Alles, M. G. (2015). Drivers of the Use and Facilitators and Obstacles of the Evolution of Big Data by the Audit Profession. Accounting Horizons, 29(2), 439-449. https://doi.org/10.2308/acch-51067
Alles, M. G., Kogan, A., & Vasarhelyi, M. A. (2002). Feasibility and economics of continuous assurance. Auditing: A Journal of Practice & Theory, 21(1), 125-138. https://doi.org/10.2308/aud.2002.21.1.125
Alon, I., Anderson, J., Munim, Z. H., & Ho, A. (2018). A review of the internationalization of Chinese enterprises. Asia Pacific Journal of Management, 35(3), 573-605. https://doi.org/10.1007/s10490-018-9597-5
Amin, H.M.G. and Mohamed, E.K.A. (2016), "Auditors’ perceptions of the impact of continuous auditing on the quality of Internet reported financial information in Egypt", Managerial Auditing Journal, 31(1), 111-132. https://doi.org/10.1108/MAJ-01-2014-0989
Appelbaum, D. (2016). Securing Big Data Provenance for Auditors: The Big Data Provenance Black Box as Reliable Evidence. Journal of Emerging Technologies in Accounting, 13(1), 17-36. https://doi.org/10.2308/jeta-51473
Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big Data and Analytics in the Modern Audit Engagement: Research Needs. AUDITING: A Journal of Practice & Theory, 36(4), 1-27. https://doi.org/10.2308/ajpt-51684
Appelbaum, D., Kozlowski, S., Vasarhelyi, M. A., & White, J. (2016). Designing CA/CM to fit not-for-profit organizations. Managerial Auditing Journal, 31(1), 87-110. https://doi.org/10.1108/MAJ-10-2014-1118
Appelbaum, D. A., Kogan, A., & Vasarhelyi, M. A. (2018). Analytical procedures in external auditing: A comprehensive literature survey and framework for external audit analytics. Journal of Accounting Literature, 40, 83-101. https://doi.org/10.1016/j.acclit.2018.01.001
Apriliyanti, I. D., & Alon, I. (2017). Bibliometric analysis of absorptive capacity. International Business Review, 26(5), 896-907. https://doi.org/10.1016/j.ibusrev.2017.02.007
Ardianto, A., & Anridho, N. (2018). Bibliometric analysis of digital accounting research. International Journal of Digital Accounting Research, 18, 141-159. https://doi.org/10.4192/1577-8517-v18_6
Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
Austin, A. A., Carpenter, T., Christ, M. H., & Nielson, C. (2018). The Data Analytics Journey: Interactions among Auditors, Managers, Regulation, and Technology. Available at SSRN: https://ssrn.com/abstract=3214140 or https://dx.doi.org/10.2139/ssrn.3214140
Bierstaker, J., Janvrin, D., & Lowe, D. J. (2014). What factors influence auditors' use of computer-assisted audit techniques? Advances in Accounting, 30(1), 67-74. https://doi.org/10.1016/j.adiac.2013.12.005
Bierstaker, J. L., Burnaby, P., & Thibodeau, J. (2001). The impact of information technology on the audit process: an assessment of the state of the art and implications for the future. Managerial Auditing Journal, 16(3), 159-164. https://doi.org/10.1108/02686900110385489
Brown-Liburd, H., Issa, H., & Lombardi, D. (2015). Behavioral implications of Big Data's impact on audit judgment and decision making and future research directions. Accounting Horizons, 29(2), 451-468. https://doi.org/10.2308/acch-51023
Brown-Liburd, H., & Vasarhelyi, M. A. (2015). Big Data and audit evidence. Journal of Emerging Technologies in Accounting, 12(1), 1-16. https://doi.org/10.2308/jeta-10468
Brown, C. E., Wong, J. A., & Baldwin, A. A. (2007). A review and analysis of the existing research streams in continuous auditing. Journal of Emerging Technologies in Accounting, 4(1), 1-28. https://doi.org/10.2308/jeta.2007.4.1.1
Cao, M., Chychyla, R., & Stewart, T. (2015). Big Data Analytics in Financial Statement Audits. Accounting Horizons, 29(2), 423-429. https://doi.org/10.2308/acch-51068
Chen, W., Zhang J., & Jiang Y. (2007) One Continuous Auditing Practice in China: Data-oriented Online Auditing(DOOA). In: Wang W., Li Y., Duan Z., Yan L., Li H., Yang X. (eds), Integration and Innovation Orient to E-Society Volume 2. IFIP International Federation for Information Processing, vol 252. Boston, MA: Springer, https://doi.org/10.1007/978-0-387-75494-9_63
Chiu, V., Liu, Q., Muehlmann, B., & Baldwin, A. A. (2019). A bibliometric analysis of accounting information systems journals and their emerging technologies contributions. International Journal of Accounting Information Systems, 32, 24-43. https://doi.org/10.1016/j.accinf.2018.11.003
Chiu, V., Liu, Q., & Vasarhelyi, M. A. (2014). The development and intellectual structure of continuous auditing research. Journal of Accounting Literature, 33(1-2), 37-57. https://doi.org/10.1016/j.acclit.2014.08.001
Chou, D. C. (2015). Cloud computing risk and audit issues. Computer Standards & Interfaces, 42, 137-142. https://doi.org/10.1016/j.csi.2015.06.005
Cockcroft, S., & Russell, M. (2018). Big Data Opportunities for Accounting and Finance Practice and Research. Australian Accounting Review, 28(3), 323-333. https://doi.org/10.1111/auar.12218
Cong, Y., Du, H., & Vasarhelyi, M. A. (2018). Technological disruption in accounting and auditing. Journal of Emerging Technologies in Accounting, 15 (2), 1–10. https://doi.org/10.2308/jeta-10640
Coyne, J. G., & McMickle, P. L. (2017). Can blockchains serve an accounting purpose? Journal of Emerging Technologies in Accounting, 14(2), 101-111. https://doi.org/10.2308/jeta-51910
Curtis, M. B., & Payne, E. A. (2008). An examination of contextual factors and individual characteristics affecting technology implementation decisions in auditing. International Journal of Accounting Information Systems, 9(2), 104-121. https://doi.org/10.1016/j.accinf.2007.10.002
Dagilienė, L., & Klovienė, L. (2019). Motivation to use big data and big data analytics in external auditing. Managerial Auditing Journal, 34(7), 750-782. https://doi.org/10.1108/MAJ-01-2018-1773
Dai, J. (2017). Three essays on audit technology: audit 4.0, blockchain, and audit app. Doctoral Thesis, Rutgers University-Graduate School-Newark. Retrieved from https://doi.org/doi:10.7282/T3RN3BZ9
Dai, J., & Vasarhelyi, M. A. (2017). Toward blockchain-based accounting and assurance. Journal of Information Systems, 31(3), 5-21. https://doi.org/10.2308/isys-51804
DaSilva, C. M., Trkman, P., Desouza, K., & Lindič, J. (2013). Disruptive technologies: a business model perspective on cloud computing. Technology Analysis & Strategic Management, 25(10), 1161-1173. https://doi.org/10.1080/09537325.2013.843661
Davis, J. T., Massey, A. P., & Lovell II, R. E. (1997). Supporting a complex audit judgment task: An expert network approach. European Journal of Operational Research, 103(2), 350-372. https://doi.org/10.1016/S0377-2217(97)00125-2
Dillard, J. F., & Yuthas, K. (2001). A responsibility ethics for audit expert systems. Journal of Business Ethics, 30(4), 337-359. https://doi.org/10.1023/A:1010720630914
Dillon, T., Wu, C., & Chang, E. (2010). Cloud computing: issues and challenges. Paper presented at the 2010 24th IEEE international conference on advanced information networking and applications. https://doi.org/10.1109/AINA.2010.187
Dong, W., Liao, S., & Zhang, Z. (2018). Leveraging financial social media data for corporate fraud detection. Journal of Management Information Systems, 35(2), 461-487. https://doi.org/10.1080/07421222.2018.1451954
Dowling, C., & Leech, S. A. (2014). A Big 4 firm's use of information technology to control the audit process: How an audit support system is changing auditor behavior. Contemporary Accounting Research, 31(1), 230-252. https://doi.org/10.1111/1911-3846.12010
Earley, C. E. (2015). Data analytics in auditing: Opportunities and challenges. Business Horizons, 58(5), 493-500. https://doi.org/10.1016/j.bushor.2015.05.002
Eining, M. M., Jones, D. R., & Loebbecke, J. K. (1997). Reliance on decision aids: An examination of auditors’ assessment of management fraud. Auditing: A Journal of Practice & Theory, 16(2), 16-19.
El‐Masry, E. H. E., & Reck, J. L. (2008). Continuous online auditing as a response to the Sarbanes‐Oxley Act. Managerial Auditing Journal, 23(8), 779-802. https://doi.org/10.1108/02686900810899527
Elam, J. J., & Mead, M. (1990). Can software influence creativity? Information Systems Research, 1(1), 1-22. https://www.jstor.org/stable/23010961
Elliott, R. K. (2002). Twenty‐first century assurance. Auditing: A Journal of Practice & Theory, 21(1), 139-146. https://doi.org/10.2308/aud.2002.21.1.139
Eulerich, M., & Kalinichenko, A. (2018). The current state and future directions of continuous auditing research: An analysis of the existing literature. Journal of Information Systems, 32(3), 31-51. https://doi.org/10.2308/isys-51813
Favaretto, M., De Clercq, E., & Elger, B. S. (2019). Big Data and discrimination: perils, promises and solutions. A systematic review. Journal of Big Data, 6(1). https://doi.org/10.1186/s40537-019-0177-4
Fischer, M. J. (1996). “Real-izing” the benefits of new technologies as a source of audit evidence: An interpretive field study. Accounting, Organizations and Society, 21(2-3), 219-242. https://doi.org/10.1016/0361-3682(95)00005-4
Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big data techniques in auditing research and practice: Current trends and future opportunities. Journal of Accounting Literature, 40, 102-115. https://doi.org/10.1016/j.acclit.2017.05.003
Gonzalez, G. C., Sharma, P. N., & Galletta, D. F. (2012). The antecedents of the use of continuous auditing in the internal auditing context. International Journal of Accounting Information Systems, 13(3), 248-262. https://doi.org/10.1016/j.accinf.2012.06.009
Griffin, P. A., & Wright, A. M. (2015). Commentaries on Big Data's Importance for Accounting and Auditing. Accounting Horizons, 29(2), 377-379. https://doi.org/10.2308/acch-51066
Guo, F., Ye, G., Hudders, L., Lv, W., Li, M., & Duffy, V. G. (2019). Product placement in mass media: a review and bibliometric analysis. Journal of Advertising, 48(2), 215-231. https://doi.org/10.1080/00913367.2019.1567409
Hampton, C., & Stratopoulos, T. C. (2016). Audit data analytics use: An exploratory analysis. Available at SSRN: https://ssrn.com/abstract=2877358 or https://dx.doi.org/10.2139/ssrn.2877358
Ho, J. L. (1999). Technology and group decision process in going-concern judgements. Group Decision and Negotiation, 8(1), 33-49. https://doi.org/10.1023/A:1008686105218
Hu, K.-H., Chen, F.-H., & Tzeng, G.-H. (2018). CPA firm’s cloud auditing provider for performance evaluation and improvement: an empirical case of China. Technological and Economic Development of Economy, 24(6), 2338-2373. https://doi.org/10.3846/tede.2018.6619
Huerta, E., & Jensen, S. (2017). An Accounting Information Systems Perspective on Data Analytics and Big Data. Journal of Information Systems, 31(3), 101-114. https://doi.org/10.2308/isys-51799
Hunton, J. E., & Rose, J. M. (2010). 21st century auditing: Advancing decision support systems to achieve continuous auditing. Accounting Horizons, 24(2), 297-312. https://doi.org/10.2308/acch.2010.24.2.297
Issa, H., Sun, T., & Vasarhelyi, M. A. (2016). Research ideas for artificial intelligence in auditing: The formalization of audit and workforce supplementation. Journal of Emerging Technologies in Accounting, 13(2), 1-20. https://doi.org/10.2308/jeta-10511
Janvrin, D., Bierstaker, J., & Lowe, D. J. (2008). An examination of audit information technology use and perceived importance. Accounting Horizons, 22(1), 1-21. https://doi.org/10.2308/acch.2008.22.1.1
Janvrin, D. J., & Weidenmier Watson, M. (2017). “Big Data”: A new twist to accounting. Journal of Accounting Education, 38, 3-8. https://doi.org/10.1016/j.jaccedu.2016.12.009
Kogan, A., Alles, M. G., Vasarhelyi, M. A., & Wu, J. (2014). Design and evaluation of a continuous data level auditing system. Auditing: A Journal of Practice & Theory, 33(4), 221-245. https://doi.org/10.2308/ajpt-50844
Krahel, J. P., & Titera, W. R. (2015). Consequences of Big Data and formalization on accounting and auditing standards. Accounting Horizons, 29(2), 409-422. https://doi.org/10.2308/acch-51065
Kuhn Jr, J. R., & Sutton, S. G. (2010). Continuous auditing in ERP system environments: The current state and future directions. Journal of Information Systems, 24(1), 91-112. https://doi.org/10.2308/jis.2010.24.1.91
Li, H., Dai, J., Gershberg, T., & Vasarhelyi, M. A. (2018). Understanding usage and value of audit analytics for internal auditors: An organizational approach. International Journal of Accounting Information Systems, 28, 59-76. https://doi.org/10.1016/j.accinf.2017.12.005
Li, P., Chan, D. Y., & Kogan, A. (2016). Exception prioritization in the continuous auditing environment: A framework and experimental evaluation. Journal of Information Systems, 30(2), 135-157. https://doi.org/10.2308/isys-51220
Liu, M., Wu, K., & Xu, J. J. (2019). How Will Blockchain Technology Impact Auditing and Accounting: Permissionless versus Permissioned Blockchain. Current Issues in Auditing, 13(2), A19-A29. https://doi.org/10.2308/ciia-52540
Lombardi, D., Bloch, R., & Vasarhelyi, M. (2014). THE FUTURE OF AUDIT. Journal of Information Systems and Technology Management, 11(1), 21-32. https://dx.doi.org/10.4301/s1807-17752014000100002
Maditati, D. R., Munim, Z. H., Schramm, H.-J., & Kummer, S. (2018). A review of green supply chain management: From bibliometric analysis to a conceptual framework and future research directions. Resources, Conservation and Recycling, 139, 150-162. https://doi.org/10.1016/j.resconrec.2018.08.004
Malaescu, I., & Sutton, S. G. (2015). The reliance of external auditors on internal audit's use of continuous audit. Journal of Information Systems, 29(1), 95-114. https://doi.org/10.2308/isys-50899
Marques, R. P., & Santos, C. (2017). Research on continuous auditing: A bibliometric analysis. Paper presented at the 2017 12th Iberian Conference on Information Systems and Technologies (CISTI). https://doi.org/10.23919/CISTI.2017.7976048
Marson, S. M. (1997). A selective history of Internet technology and social work. Computers in Human Services, 14(2), 35-49. https://doi.org/10.1300/J407v14n02_03
Masli, A., Peters, G. F., Richardson, V. J., & Sanchez, J. M. (2010). Examining the potential benefits of internal control monitoring technology. The Accounting Review, 85(3), 1001-1034. https://doi.org/10.2308/accr.2010.85.3.1001
Moffitt, K. C., Rozario, A. M., & Vasarhelyi, M. A. (2018). Robotic process automation for auditing. Journal of Emerging Technologies in Accounting, 15(1), 1-10. https://doi.org/10.2308/jeta-10589
Moffitt, K. C., & Vasarhelyi, M. A. (2013). AIS in an age of Big Data. Journal of Information Systems, 27(2), 1-19. https://doi.org/10.2308/isys-10372
Moll, J., & Yigitbasioglu, O. (2019). The role of internet-related technologies in shaping the work of accountants: New directions for accounting research. The British Accounting Review, 51(6), 100833. https://doi.org/10.1016/j.bar.2019.04.002
Muehlmann, B. W., Chiu, V., & Liu, Q. (2015). Emerging technologies research in accounting: JETA's first decade. Journal of Emerging Technologies in Accounting, 12(1), 17-50. https://doi.org/10.2308/jeta-51245
Munim, Z. H., Dushenko, M., Jimenez, V. J., Shakil, M. H., & Imset, M. (2020). Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions. Maritime Policy & Management. https://doi.org/10.1080/03088839.2020.1788731
Murcia, F. D.-R., De Souza, F. C., & Borba, J. A. (2008). Continuous auditing: A literature review. Revista Organizações em Contexto, 4(7), 1-17. https://doi.org/10.15603/1982-8756/roc.v4n7p1-17
Murthy, U. S., & Geerts, G. L. (2017). An REA Ontology-Based Model for Mapping Big Data to Accounting Information Systems Elements. JOURNAL OF INFORMATION SYSTEMS, 31(3), 45–61. https://doi.org/10.2308/isys-51803
O'Leary, D. E. (2017). Configuring blockchain architectures for transaction information in blockchain consortiums: The case of accounting and supply chain systems. Intelligent Systems in Accounting, Finance and Management, 24(4), 138-147. https://doi.org/10.1002/isaf.1417
Perols, J. L., Bowen, R. M., Zimmermann, C., & Samba, B. (2017). Finding needles in a haystack: Using data analytics to improve fraud prediction. The Accounting Review, 92(2), 221-245. https://doi.org/10.2308/accr-51562
Pincus, M., Tian, F., Wellmeyer, P., & Xu, S. X. (2017). Do clients’ enterprise systems affect audit quality and efficiency? Contemporary Accounting Research, 34(4), 1975-2021. https://doi.org/10.1111/1911-3846.12335
Richins, G., Stapleton, A., Stratopoulos, T. C., & Wong, C. (2017). Big Data Analytics: Opportunity or Threat for the Accounting Profession? Journal of Information Systems, 31(3), 63-79. https://doi.org/10.2308/isys-51805
Riehmann, P., Hanfler, M., & Froehlich, B. (2005). Interactive sankey diagrams. Paper presented at the IEEE Symposium on Information Visualization, 2005. INFOVIS 2005. https://doi.org/10.1109/INFVIS.2005.1532152
Rikhardsson, P., & Dull, R. (2016). An exploratory study of the adoption, application and impacts of continuous auditing technologies in small businesses. International Journal of Accounting Information Systems, 20, 26-37. https://doi.org/10.1016/j.accinf.2016.01.003
Rozario, A. M., & Thomas, C. (2019). Reengineering the audit with blockchain and smart contracts. Journal of Emerging Technologies in Accounting, 16(1), 21-35. https://doi.org/10.2308/jeta-52432
Salijeni, G., Samsonova-Taddei, A., & Turley, S. (2019). Big Data and changes in audit technology: contemplating a research agenda. Accounting and Business Research, 49(1), 95-119. https://doi.org/10.1080/00014788.2018.1459458
Schmidt, P. J., Wood, J. T., & Grabski, S. V. (2016). Business in the cloud: Research questions on governance, audit, and assurance. Journal of Information Systems, 30(3), 173-189. https://doi.org/10.2308/isys-51494
Segal, B. (1995). A short history of Internet protocols at CERN. Professional webpage. April. http://ben.home.cern.ch/ben/TCPHIST.html
Singleton, T., & Singleton, A. J. (2005). Auditing headaches? Relieve them with CAR. Journal of Corporate Accounting & Finance, 16(4), 17-27. https://doi.org/10.1002/jcaf.20114
Song, X. P., Hu, Z. H., Du, J. G., & Sheng, Z. H. (2014). Application of machine learning methods to risk assessment of financial statement fraud: evidence from China. Journal of Forecasting, 33(8), 611-626. https://doi.org/10.1002/for.2294
Sun, T., Alles, M., & Vasarhelyi, M. A. (2015). Adopting continuous auditing: A cross-sectional comparison between China and the United States. Managerial Auditing Journal, 30(2), 176-204. https://doi.org/10.1108/MAJ-08-2014-1080
Sutton, S. G., Holt, M., & Arnold, V. (2016). “The reports of my death are greatly exaggerated”—Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60-73. https://doi.org/10.1016/j.accinf.2016.07.005
Tang, J., & Karim, K. E. (2019). Financial fraud detection and big data analytics–implications on auditors’ use of fraud brainstorming session. Managerial Auditing Journal, 34(3), 324-337. https://doi.org/10.1108/MAJ-01-2018-1767
Uyar, A., Kılıç, M., & Koseoglu, M. A. (2020). Exploring the conceptual structure of the auditing discipline through co‐word analysis: An international perspective. International Journal of Auditing, 24(1), 53-72. https://doi.org/10.1111/ijau.12178
Vasarhelyi, M. A., & Halper, F. B. (1991). The continuous audit of online systems. Paper presented at the Auditing: A Journal of Practice and Theory.
Vasarhelyi, M. A., Kogan, A., & Tuttle, B. M. (2015). Big Data in Accounting: An Overview. Accounting Horizons, 29(2), 381-396. https://doi.org/10.2308/acch-51071
Wang, Y., & Kogan, A. (2018). Designing confidentiality-preserving Blockchain-based transaction processing systems. International Journal of Accounting Information Systems, 30, 1-18. https://doi.org/10.1016/j.accinf.2018.06.001
Warren, J. D., Moffitt, K. C., & Byrnes, P. (2015). How Big Data Will Change Accounting. Accounting Horizons, 29(2), 397-407. https://doi.org/10.2308/acch-51069
Yermack, D. (2017). Corporate governance and blockchains. Review of Finance, 21(1), 7-31.
Yigitbasioglu, O. M. (2015). External auditors' perceptions of cloud computing adoption in Australia. International Journal of Accounting Information Systems, 18, 46-62. https://doi.org/10.1016/j.accinf.2015.09.001
Yoon, K., Hoogduin, L., & Zhang, L. (2015). Big Data as Complementary Audit Evidence. Accounting Horizons, 29(2), 431-438. https://doi.org/10.2308/acch-51076
Yu, T., Lin, Z., & Tang, Q. (2018). Blockchain: The introduction and its application in financial accounting. Journal of Corporate Accounting & Finance, 29(4), 37-47. https://doi.org/10.1002/jcaf.22365
Zhang, J., Yang, X., & Appelbaum, D. (2015). Toward effective Big Data analysis in continuous auditing. Accounting Horizons, 29(2), 469-476. https://doi.org/10.2308/acch-51070
Zhu, J., & Liu, W. (2020). A tale of two databases: the use of Web of Science and Scopus in academic papers. Scientometrics, 123, 321–335. https://doi.org/10.1007/s11192-020-03387-8
Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472. https://doi.org/10.1177/1094428114562629
Derechos de autor 2022 Revista de Contabilidad - Spanish Accounting Review
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Las obras que se publican en esta revista están sujetas a los siguientes términos:
1. Ediciones de la Universidad de Murcia (EDITUM) y ASEPUC conservan los derechos patrimoniales (copyright) de las obras publicadas, y favorece y permite la reutilización de las mismas bajo la licencia de uso indicada en el punto 2.
2. Las obras se publican en la edición electrónica de la revista bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. Permite copiar, distribuir e incluir el artículo en un trabajo colectivo (por ejemplo, una antología), siempre y cuando no exista una finalidad comercial, no se altere ni modifique el artículo y se cite apropiadamente el trabajo original. Esta revista no tiene tarifa por la publicación Open Access. ASEPUC y EDITUM financian los costes de producción y publicación de los manuscritos.
3. Condiciones de auto-archivo. Se permite y se anima a los autores a difundir electrónicamente la versión publicada de sus obras, ya que favorece su circulación y difusión y con ello un posible aumento en su citación y alcance entre la comunidad académica.
