The impacts of XBRL adoption on software quality factors: a descriptive analysis
DOI:
https://doi.org/10.5753/isys.2020.533Keywords:
XBRL, Software Quality Factors, Software Engineering, Impacts of XBRLAbstract
XBRL (eXtensible Business Reporting Language) is a technology currently adopted by various government institutions and companies around the world. Many papers related to its use and benefits for the financial and accounting areas are found in the literature. However, little is known of its benefits for Software Engineering. XBRL can impact on financial software development processes as well as software quality factors. Therefore, there is a need to identify the impacts that arise from the adoption of XBRL in financial software development processes and software quality factors. This paper aims to identify the impacts of adopting XBRL on software quality factors. Identifying these impacts may help software developers to understand the advantages of using XBRL and to increase the adoption of XBRL in other companies which may contribute to improving the quality of the software developed and to better implementation of software quality frameworks within these institutions. In addition, this work will contribute to the identification of the adoption factors of the XBRL language.
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References
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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.
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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.
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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.
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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
How to Cite
da Silva, P. C., & de Cerqueira, M. G. (2020). The impacts of XBRL adoption on software quality factors: a descriptive analysis. ISys - Brazilian Journal of Information Systems, 13(1), 33–59. https://doi.org/10.5753/isys.2020.533
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