Os Impactos Provenientes da Adoção de XBRL nos Fatores de Qualidade de Software: uma análise descritiva
DOI:
https://doi.org/10.5753/isys.2020.533Keywords:
Fatores de Qualidade de Software, Engenharia de Software, XBRL, Impactos de XBRLAbstract
XBRL (eXtensible Business Reporting Language) é uma tecnologia adotada atualmente por várias instituições governamentais e empresas ao redor do mundo. Muitos trabalhos relacionados ao seu uso e benefícios para as áreas financeira e contábil são encontrados na literatura. Entretanto, pouco se conhece dos seus benefícios para a Engenharia de Software. XBRL pode causar impactos nos processos de desenvolvimento de software financeiro, assim como nos fatores de qualidade de software. Logo, há necessidade de se identificar os impactos provenientes da adoção de XBRL nos processos de desenvolvimento de software financeiro e nos fatores de qualidade de software. Este artigo tem como objetivo identificar os impactos provenientes da adoção de XBRL nos fatores de qualidade de software. A identificação desses impactos poderá ajudar as empresas desenvolvedoras de software a conhecer melhor as vantagens relacionadas ao uso de XBRL, a aumentar a adoção de XBRL em outras empresas, o que, consequentemente, poderá contribuir com a melhoria da qualidade dos softwares desenvolvidos, facilitando a implementação de frameworks de qualidade dentro dessas instituições. Além disso, esse trabalho poderá contribuir com a identificação dos fatores de adoção da linguagem XBRL.
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Referências
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Davidson, A., Robinson, A. and Malthus, S. (2006). Knowledge and use of XBRL by Chartered Accountants in New Zealand.
Debreceny, R., Farewell, S., Piechocki, M., Felden, C. and Gräning, A. (2010). Does it add up? Early evidence on the data quality of XBRL filings to the SEC. Journal of Accounting and Public Policy, v. 29, n. 3, p. 296–306.
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Debreceny, R. S. and Gray, G. L. (2010). Data mining journal entries for fraud detection: An exploratory study. International Journal of Accounting Information Systems, v. 11, n. 3, p. 157–181.
Denzin, N. K. and Lincoln, Y. S. (2006). Introduction The Discipline and Practice of Qualitative Research. Handbook of Qualitative Research, p. 1–20.
Dyba, T. (2000). An Instrument for Measuring the Key Factors of Success in Software Process Improvement. Empirical Software Engineering, v. 5, p. 357–390.
Escobar-Rodríguez, T. and Gago-Rodríguez, S. (2012). “We were the first to support a major is innovation”. Research into the motivations of spanish pioneers in XBRL. Revista de Contabilidad, v. 15, n. 1, p. 91–108.
Feng, L., Chang, E. and Dillon, T. (2002). A semantic network-based design methodology for XML documents. ACM Transactions on Information Systems, v. 20, n. 4, p. 390–421.
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Gräning, A., Felden, C. and Piechocki, M. (2011). Status Quo and Potential of XBRL for Business and Information Systems Engineering. Business & Information Systems Engineering
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Hoffman, C. and Watson, L. (2009). XBRL for Dummies.
Hwang, J. S., Leem, C. S. and Moon, H. J. (2008). A study on relationships among accounting transparency, accounting information transparency, and XBRL. Proceedings - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008, v. 1, n. 0, p. 502–509.
Janvrin, D. and Mascha, M. F. (2010). The Process Of Creating XBRL Instance Documents: A Research Framework. The Review of Business Information Systems, v. 14, n. 2, p. 11–34.
Kautz, K. and Larsen, E. A. (1996). Quality assurance and software process improvement in Norway. In 4th International Conference on the Software Process.
Kimber, A., Angwin, M., Miles-Khan, S. and Backeberg, M. (2015). Emerging Technology Trends. p. 1–7.
Kitchenham, B. and Charters, S. (2007). Guidelines for performing Systematic Literature reviews in Software Engineering Version 2.3. Engineering, v. 45, n. 4ve, p. 1051.
Kitchenham, B. and Pfleeger, S. L. (2002). Principles of survey research part 4: questionnaire evaluation. ACM SIGSOFT Software Engineering Notes, v. 27, n. 3, p. 20.
Kloos, M., Hulstijn, J., Seck, M. and Janssen, M. (2014). XBRL-driven business process improvement: A simulation study in the accounting domain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
Liu, C., Luo, X., Sia, C. L., O’Farrell, G. and Teo, H. H. (2014). The impact of XBRL adoption in PR China. Decision Support Systems, v. 59, n. 1, p. 242–249.
Liu, C., Wang, T. and Yao, L. J. (2014). XBRL’s impact on analyst forecast behavior: An empirical study. Journal of Accounting and Public Policy, v. 33, n. 1, p. 69–82.
Marconi, M. and Lakatos, E. (2003). Fundamentos de metodologia científica.
McCall, J. a., Richards, P. K. and Walters, G. F. (1977). Factors in Software Quality. at’l Tech. Information Servicel, v. 1, 2 and 3, n. ADA049055, p. 689–1699.
Mendon, M. (2013). Gismália Marcelino Mendonça Manual de Normalização para Apresentação de Trabalhos Acadêmicos.
Mesquita, M., Salvador, U., Silva, C., et al. (2013). Similarity Evaluation Between Concepts Represented by XBRL. p. 1889–1910.
Petrillo, F., Dal, C., Freitas, S. and Pimenta, M. (2011). Interactive Analysis of Likert Scale Data using a Multichart Visualization Tool. IHC - Simpósio Brasileiro sobre Fatores Humanos em Sistemas Computacionais, p. 358–365.
Pinsker, R. and Li, S. (2008). Costs and benefits of XBRL adoption. Communications of the ACM, v. 51, n. 3, p. 47–50.
Recker, J. (2013). Scientific Research in Information Systems. 1th Editio ed. London: Springer.
Robertson, J. (2012). Likert-type scales, statistical methods, and effect sizes. Communications of the ACM, v. 55, n. 5, p. 6.
Shan, Y. and Troshani, I. (2014). Does XBRL benefit financial statement auditing? Journal of Computer Information Systems,
Silva, P. C. (2003). Explorando Linguagens de Marcação para Representaçaõ de Relatórios de Informações Financeiras. v. 1, p. 1–135.
Silva, P. C. and Cerqueira, M. (2016). COMING IMPACTS OF XBRL ADOPTION IN FINANCIAL SOFTWARE DEVELOPMENT PROCESSES AND SOFTWARE QUALITY FACTORS: A SYSTEMATIC MAPPING. [CONTECSI, Ed.]In CONTECSI USP - International Conference on Information Systems and Technology Management. . FEAUSP.
Srivastava, R. P. and Kogan, A. (2010). Assurance on XBRL instance document: A conceptual framework of assertions. International Journal of Accounting Information Systems, v. 11, n. 3, p. 261–273.
Stålhane, T., Borgersen, P. C. and Arnesen, K. (jul 1997). In search of the customer’s quality view. Journal of Systems and Software, v. 38, n. 1, p. 85–93.
Streiner, D. L. (2003). Being inconsistent about consistency: when coefficient alpha does and doesn’t matter. Journal of personality assessment, v. 80, n. 3, p. 217–22.
Troshani, I. and Lymer, A. (2011). Institutionalizing XBLR in the UK: An Organizing Vision Perspective. ECIS 2011 Proceedings, p. Paper 152.
Vieira, H. C., Castro, A. E. De and Shuch Junior, V. F. (2010). O uso de questionários via e-mail em pesquisas acadêmicas sob a ótica dos respondentes. In: XIII Seminários em Administração - SEMEAD, n. 2006, p. 13.
Wang, H. and Wang, C. (2003). Taxonomy of security considerations and software quality. Communications of the ACM, v. 46, n. 6, p. 75–78.
Wang, T., Wen, C. Y. and Seng, J. L. (2014). The association between the mandatory adoption of XBRL and the performance of listed state-owned enterprises and non-state-owned enterprises in China. Information and Management, v. 51, n. 3, p. 336–346.
An Evaluation of the Current State and Future of XBRL and Interactive Data for Investors and Analysts (2012). Whitepaper, Columbia University, Center for Excellence in Accounting & Security Analysis,
Blankespoor, E. A. (2012). The Impact of Investor Information Processing Costs on Firm Disclosure Choice: Evidence from the XBRL Mandate.
Boslaugh, S. and Watters, P. (2008). Statistics In a Nutshell: A Desktop Quick Reference. 1th. ed. United States: O’Reilly. v. 1
Carroll, C., Falessi, D., Forney, V., et al. (2015). A Mapping Study of Software Causal Factors for Improving Maintenance. In International Symposium on Empirical Software Engineering and Measurement.
Cleophas, T. J. and Zwinderman, A. H. (2016). SPSS for Starters and 2nd Levelers.
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, v. 78, n. 1, p. 98–104.
Couper, M. P., Tourangeau, R. and Steiger, D. M. (2001). Social presence in web surveys. Proceedings of the SIGCHI …, n. 3, p. 412–417.
Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. 4th. ed. Nebraska: Pearson Education. v. 3
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, v. 16, n. 3, p. 297–334.
Davidson, A., Robinson, A. and Malthus, S. (2006). Knowledge and use of XBRL by Chartered Accountants in New Zealand.
Debreceny, R., Farewell, S., Piechocki, M., Felden, C. and Gräning, A. (2010). Does it add up? Early evidence on the data quality of XBRL filings to the SEC. Journal of Accounting and Public Policy, v. 29, n. 3, p. 296–306.
Debreceny, R., Felden, C. and Ochocki, B. (2009). XBRL Taxonomy Extensions. XBRL for Interactive …,
Debreceny, R., Felden, C., Ochocki, B., Piechocki, M. and Piechocki, M. (2009). XBRL for Interactive Data.
Debreceny, R., Felden, C. and Piechocki, M. (2007). New dimensions of business reporting and XBRL. Wiesbaden: DUV.
Debreceny, R. S. and Gray, G. L. (2010). Data mining journal entries for fraud detection: An exploratory study. International Journal of Accounting Information Systems, v. 11, n. 3, p. 157–181.
Denzin, N. K. and Lincoln, Y. S. (2006). Introduction The Discipline and Practice of Qualitative Research. Handbook of Qualitative Research, p. 1–20.
Dyba, T. (2000). An Instrument for Measuring the Key Factors of Success in Software Process Improvement. Empirical Software Engineering, v. 5, p. 357–390.
Escobar-Rodríguez, T. and Gago-Rodríguez, S. (2012). “We were the first to support a major is innovation”. Research into the motivations of spanish pioneers in XBRL. Revista de Contabilidad, v. 15, n. 1, p. 91–108.
Feng, L., Chang, E. and Dillon, T. (2002). A semantic network-based design methodology for XML documents. ACM Transactions on Information Systems, v. 20, n. 4, p. 390–421.
Field, A. (2013). Discovering Statistics using IBM SPSS Statistics. Discovering Statistics using IBM SPSS Statistics, p. 297–321.
Field, A. (2009). Discovering Statistics Using SPSS. THIRD EDIT ed. London: SAGE Publications Ltd.
Fisher, R. J. (1993). Social Desirability Bias and the Validity of Indirect Questioning. Journal of Consumer Research,
Gomaa, M. I., Markelevich, A. and Shaw, L. (jun 2011). Introducing XBRL through a financial statement analysis project. Journal of Accounting Education, v. 29, n. 2–3, p. 153–173.
Gräning, A., Felden, C. and Piechocki, M. (2011). Status Quo and Potential of XBRL for Business and Information Systems Engineering. Business & Information Systems Engineering
Günther, H. (2003). Como Elaborar um Questionário. Planejamento de Pesquisa nas Ciências Sociais, n. 1999, p. 1–35.
Hair, J. F., Black, W. C., Babin, B. J. and Anderson, R. E. (2010). Multivariate Data Analysis. Vectors
Heitmann, S. and Ohling, A. (2005). Audit of the Future - An Analysis of the Impact of XBRL on Audit and Assurance.
Hoffman, C. and Watson, L. (2009). XBRL for Dummies.
Hwang, J. S., Leem, C. S. and Moon, H. J. (2008). A study on relationships among accounting transparency, accounting information transparency, and XBRL. Proceedings - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008, v. 1, n. 0, p. 502–509.
Janvrin, D. and Mascha, M. F. (2010). The Process Of Creating XBRL Instance Documents: A Research Framework. The Review of Business Information Systems, v. 14, n. 2, p. 11–34.
Kautz, K. and Larsen, E. A. (1996). Quality assurance and software process improvement in Norway. In 4th International Conference on the Software Process.
Kimber, A., Angwin, M., Miles-Khan, S. and Backeberg, M. (2015). Emerging Technology Trends. p. 1–7.
Kitchenham, B. and Charters, S. (2007). Guidelines for performing Systematic Literature reviews in Software Engineering Version 2.3. Engineering, v. 45, n. 4ve, p. 1051.
Kitchenham, B. and Pfleeger, S. L. (2002). Principles of survey research part 4: questionnaire evaluation. ACM SIGSOFT Software Engineering Notes, v. 27, n. 3, p. 20.
Kloos, M., Hulstijn, J., Seck, M. and Janssen, M. (2014). XBRL-driven business process improvement: A simulation study in the accounting domain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
Liu, C., Luo, X., Sia, C. L., O’Farrell, G. and Teo, H. H. (2014). The impact of XBRL adoption in PR China. Decision Support Systems, v. 59, n. 1, p. 242–249.
Liu, C., Wang, T. and Yao, L. J. (2014). XBRL’s impact on analyst forecast behavior: An empirical study. Journal of Accounting and Public Policy, v. 33, n. 1, p. 69–82.
Marconi, M. and Lakatos, E. (2003). Fundamentos de metodologia científica.
McCall, J. a., Richards, P. K. and Walters, G. F. (1977). Factors in Software Quality. at’l Tech. Information Servicel, v. 1, 2 and 3, n. ADA049055, p. 689–1699.
Mendon, M. (2013). Gismália Marcelino Mendonça Manual de Normalização para Apresentação de Trabalhos Acadêmicos.
Mesquita, M., Salvador, U., Silva, C., et al. (2013). Similarity Evaluation Between Concepts Represented by XBRL. p. 1889–1910.
Petrillo, F., Dal, C., Freitas, S. and Pimenta, M. (2011). Interactive Analysis of Likert Scale Data using a Multichart Visualization Tool. IHC - Simpósio Brasileiro sobre Fatores Humanos em Sistemas Computacionais, p. 358–365.
Pinsker, R. and Li, S. (2008). Costs and benefits of XBRL adoption. Communications of the ACM, v. 51, n. 3, p. 47–50.
Recker, J. (2013). Scientific Research in Information Systems. 1th Editio ed. London: Springer.
Robertson, J. (2012). Likert-type scales, statistical methods, and effect sizes. Communications of the ACM, v. 55, n. 5, p. 6.
Shan, Y. and Troshani, I. (2014). Does XBRL benefit financial statement auditing? Journal of Computer Information Systems,
Silva, P. C. (2003). Explorando Linguagens de Marcação para Representaçaõ de Relatórios de Informações Financeiras. v. 1, p. 1–135.
Silva, P. C. and Cerqueira, M. (2016). COMING IMPACTS OF XBRL ADOPTION IN FINANCIAL SOFTWARE DEVELOPMENT PROCESSES AND SOFTWARE QUALITY FACTORS: A SYSTEMATIC MAPPING. [CONTECSI, Ed.]In CONTECSI USP - International Conference on Information Systems and Technology Management. . FEAUSP.
Srivastava, R. P. and Kogan, A. (2010). Assurance on XBRL instance document: A conceptual framework of assertions. International Journal of Accounting Information Systems, v. 11, n. 3, p. 261–273.
Stålhane, T., Borgersen, P. C. and Arnesen, K. (jul 1997). In search of the customer’s quality view. Journal of Systems and Software, v. 38, n. 1, p. 85–93.
Streiner, D. L. (2003). Being inconsistent about consistency: when coefficient alpha does and doesn’t matter. Journal of personality assessment, v. 80, n. 3, p. 217–22.
Troshani, I. and Lymer, A. (2011). Institutionalizing XBLR in the UK: An Organizing Vision Perspective. ECIS 2011 Proceedings, p. Paper 152.
Vieira, H. C., Castro, A. E. De and Shuch Junior, V. F. (2010). O uso de questionários via e-mail em pesquisas acadêmicas sob a ótica dos respondentes. In: XIII Seminários em Administração - SEMEAD, n. 2006, p. 13.
Wang, H. and Wang, C. (2003). Taxonomy of security considerations and software quality. Communications of the ACM, v. 46, n. 6, p. 75–78.
Wang, T., Wen, C. Y. and Seng, J. L. (2014). The association between the mandatory adoption of XBRL and the performance of listed state-owned enterprises and non-state-owned enterprises in China. Information and Management, v. 51, n. 3, p. 336–346.
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Published
2020-01-06
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da Silva, P. C., & de Cerqueira, M. G. (2020). Os Impactos Provenientes da Adoção de XBRL nos Fatores de Qualidade de Software: uma análise descritiva. ISys - Revista Brasileira De Sistemas De Informação, 13(1), 33–59. https://doi.org/10.5753/isys.2020.533
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