Adoption of emerging technologies in a regulated environment: a study in audit companies
A study in audit companies
DOI:
https://doi.org/10.17524/repec.v19.e3687Palavras-chave:
Adoção de tecnologias emergentes. Estrutura TOE. Auditoria.Resumo
Objective:
Analyze the moderating role of the environmental context in the relationship between technological and organizational contexts and audit firms’ adoption of emerging technologies in a regulated environment.
Method
This descriptive study was conducted using a quantitative survey. The population consisted of audit firms registered with the Securities and Exchange Commission. A sample of 114 valid responses was obtained. Structural Equation Modeling (PLS-SEM) and moderation analysis using the product indicator method were performed.
Results
The findings confirm the theoretical foundation of this study, the Technology, Organization, and Environment (TOE) framework, demonstrating that a company’s technological, organizational, and environmental contexts influence audit firms’ decisions regarding the adoption of emerging technologies. Concerning the moderating role of the environmental context, the results suggest that coercive and mimetic pressures do not play a moderating role. In contrast, normative pressure positively moderates the relationship between the technological and organizational contexts and the adoption of new technologies.
Contribution
The predictive power of the TOE framework in audit firms’ adoption of emerging technologies was empirically validated. Additionally, in the theoretical field, the study advances the discussion on the factors influencing the adoption of new technologies by audit firms within the Brazilian regulatory environment.
Tradução
Este artigo é uma tradução em English do artigo:
Adoção de tecnologias emergentes em ambiente regulado
Referências
AICPA. Reimagining Auditing in Wire Word. AICPA, 2014. Disponível em: https://us.aicpa.org/content/dam/aicpa/interestareas/frc/assuranceadvisoryservices/downloadabledocuments/whitepaper_blue_sky_scenario-pinkbook.pdf. Acesso em: 10 abr. 2022.
Al-Htaybat, K. & Von Alberti-Alhtaybat, L. (2017). Big Data and corporate reporting: impacts and paradoxes. Accounting, Auditing & Accountability Journal, 30(4), 850-873.
https://doi.org/10.1108/AAAJ-07-2015-2139.
Ali, M. & Park, K. (2016). The mediating role of an innovative culture in the relationship between absorptive capacity and technical and non-technical innovation. Journal of Business Research, 69(5), 1669-1675.
https://doi.org/10.1016/j.jbusres.2015.10.036.
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), 439–49.
https://doi.org/10.2308/acch-51067.
Amorim, E. N. C.; Vicente. E. F. R.; Will, A. R. & Silva, F. A. (2012). O mercado de auditoria no Brasil: um retrato considerando a percepção das firmas de auditoria. Revista Catarinense da Ciência Contábil – CRCSC, 11(32).
http://dx.doi.org/10.16930/2237-7662/rccc.v11n32p73-87.
Appelbaum, D. & Nehmer, R. A. (2017). Using drones in internal and external audits: An exploratory framework. Journal of Emerging Technologies in Accounting, 1, 99-113.
http://10.2308/jeta-51704.
Austin, A.; Carpenter, T; Christ, M & Nielson, C. (2019). The data analytics transformation: Evidence from auditors, CFOs, and standard-setters. SSRN.
http://10.2139/ssrn.3214140.
Baker, J. (2011). The technology-Organization-Environment Framework. In: Y.K. Dwivedi et al. (Eds.). Information Systems Theory: Explaining and Predicting Our Digital Society, Integrated Series in Information Systems, 1(28).
Barr-Pulliam, D.; Brown-Liburd, H. L. & Munoko, I. (2022). The Effects of Person-Specific, Task, and Environmental Factors on Digital Transformation and Innovation in Auditing: A Review of the Literature. Journal of International Financial Management & Accounting, 33 (2), 337-374.
https://doi.org/10.1111/jifm.12148
Barr-Pulliam, D.; Brown-Liburd, H. L. & Sanderson, K. A. (2021). The effects of the internal control opinion and use of audit data analytics on perceptions of audit quality, assurance, and auditor negligence. Auditing: A Journal of Practice and Theory, 41 (1): 25–48.
https://doi.org/10.2308/AJPT-19-064.
Bradley, S. W.; Shepherd, D. A. & Wiklund, J. (2011). The importance of slack for new organizations facing ‘tough’ environments. Journal of Management Studies, 48(5), 1071–1097.
https://doi.org/10.1111/j.1467-6486.2009.00906.x
Brown-Liburd, H. & Vasarhelyi, M. (2015). Big Data and Audit Evidence. Journal of Emerging Technologies in Accounting, 12(1), 1–16.
https://10.2308/jeta-10468.
Carpenter, V. L. & Feroz, E. H. (2001). Institutional theory and accounting rule choice: An analysis of four US state governments’ decisions to adopt generally accepted accounting principles. Acc. Organ. Soc., 26(7), 565–596.
https://doi.org/10.1016/S0361-3682(00)00038-6.
Chan, F. T. & Chong, A. Y. L. (2013). Determinants of mobile supply chain management system diffusion: a structural equation analysis of manufacturing firms. International Journal of Production Research, 51(4), 1196-1213.
https://doi.org/10.1080/00207543.2012.693961.
Chong, L. W. & He, Z. (2019). Blockchain disruption and smart contracts. Review of Financial Studies, 32(5), 54–97.
https://doi.org/10.1093/rfs/hhz007.
Cohen, W. & Levinthal, D. (1990). Absorptive capacity, a new perspective on learning and innovation, Admin. Sci. Quart, 35(1), 128–152.
https://doi.org/10.2307/2393553.
Cooper, L. A.; Holderness, D. K.; Sorensen, T. L. & Wood, D. A. (2019). Robotic Process Automation in Public Accounting. Accounting Horizons, 33(4), 15-35.
http://dx.doi.org/10.2139/ssrn.3193222.
Dagiliene, 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.
Dedoulis, E. (2016). Institutional formations and the Anglo-Americanization of local auditing practices: The case of Greece. Accounting Forum, 40(1), 29–44.
https://doi.org/10.1016/j.accfor.2015.11.003.
Dimaggio, P. J. & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review,48(2), 147–160.
https://doi.org/10.2307/2095101.
Eilifsen, A.; Kinserdal, F; Messier Jr & Mckee, T. E. (2020). An exploratory study into the use of audit data analytics on audit engagements. Accounting Horizons.34(4).
http://10.2308/HORIZONS-19-121.
Flatten, T. C.; Engelen, A.; Zahra, S. A. & Brettel, M. (2011). A measure of absorptive capacity: Scale development and validation. European Management Journal, 29(2), 98-116.
https://doi.org/10.1016/j.emj.2010.11.002.
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing, 18(1), 39-59.
https://doi.org/10.2307/3151312
Freitas, C. A. S. & Guimarães, T. A. (2007). Isomorphism, Institutionalization and Legitimacy: Operational Auditing at the Court of Auditors. RAC, 153 - 175.
https://doi.org/10.1590/S1415-65552007000500008.
Grover, V. & Kohli, R. (2012). Cocreating IT value: New capabilities and metrics for multifirm environments. Mis Quarterly, 36(1).
https://doi.org/10.2307/41410415.
Hair, J. F. J.; Ringle, C. M. & Sarstedt, M. (2014). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning: Prentice-Hall.
http://dx.doi.org/10.1016/j.lrp.2013.01.001.
Handoko, B. L. (2021). How audit firm size moderate effect of TOE context toward auditor adoption of machine learning. Journal of Theoretical and Applied Information Technology, 99(24), 5972-5980.
Handoko, B. L. & Thomas, G. N. (2021). How audit firm size moderate effect of TOE context toward auditor adoption of technology. Turkish Journal of Computer and Mathematics Education. 12(6), 1518-1526.
Henry, B. & Hicks, M. (2015). A Survey of Perspectives on the Future of the Accounting Profession. The CPA Journal; 85(8), 6-9.
Hinings, B.; Gegenhuber, T. &Greenwood, R. (2018). Digital innovation and transformation: An institutional perspective. Information and Organization, 28(1), 52–61.
https://doi.org/10.1016/j.infoandorg.2018.02.004.
Huang, F. & Vasarhelyi, M. A. (2019). Applying robotic process automation (HUU) in auditing: A framework. International Journal of Accounting Information Systems, 35, 1-11.
https://doi.org/10.1016/j.accinf.2019.100433.
Inghirami, I. E. (2018). Accounting Information Systems in the Time of Blockchain. Pávia: ITAIS Conference.
Kenny, D. A. & Judd, C. M. (1984). Estimating the nonlinear and interactive effects of latent variables. Psychological Bulletin, 96 (1), 201–210.
https://doi.org/10.1037/0033-2909.96.1.201.
Kroon, N.; Alves, M. C. & Martins, I. (2021). The Impacts of Emerging Technologies on Accountants’ Role and Skills: Connecting to Open Innovation—A Systematic Literature Review. Journal of Open Innovation: Technology, Market, and Complexity, 7(3), 2021.
https://doi.org/10.3390/joitmc7030163.
Li, Q. & Vasarhelyi, M. (2018). Developing a Cognitive Assistant for the Audit Plan Brainstorming Session. The International Journal of Digital Accounting Research, 18, 119–140.
https://doi.org/10.4192/1577-8517-v18_5.
Liang, H.; Saraf, N.; Hu, Q. & Xue, Y. (2007). Assimilation of Enterprise Systems: The Effect of Institutional Pressures and the Mediating Role of Top Management. Mis Quarterly, 31(1), 59-87.
https://doi.org/10.2307/25148781.
Low, C.; Chen, Y. & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial management & data systems, 111 (7), 1006-1023.
https://doi.org/10.1108/02635571111161262.
Majchrzak, A.; Markus, M. L. & Wareham, J. (2016). Designing for digital transformation: Lessons for information systems research from the study of ICT and societal challenges. MIS Quarterly, 40(2), 267-277.
Mckinley, W. & Mone, M. (2003). Organization theory. Oxford University Press – USA.
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.
Montes, G. A. & Goertzel, B. (2019). Distributed, decentralized, and democratized artificial intelligence. Technological Forecasting and Social Change,141, 354-358.
https://doi.org/10.1016/j.techfore.2018.11.010.
Oliveira, R. C. R. (2017). Adoção de tecnologias da informação em micro, pequenas e médias empresas: um estudo a partir da adaptação do modelo technology, organization and environment (TOE) sob influência de fatores institucionais. Pesquisa de Doutorado - Programa de Pós-Graduação em Administração, Universidade Federal da Bahia, Bahia.
Oliveira, T. & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. The Electronic Journal Information Systems Evaluation, 14 (1), 110-121.
Oliveira, T.; Martins, R.; Sarker, S.; Thomas, M. & Popovič, A. (2019). Understanding SaaS adoption: The moderating impact of the environment context. International Journal of Information Management, 49, 1-12.
https://doi.org/10.1016/j.ijinfomgt.2019.02.009.
Pimentel, E. & Boulianne, E. (2020). Blockchain in Accounting Research and Practice: Current Trends and Future Opportunities. Accounting Perspectives, 19(4), 325–361.
https://doi.org/10.1108/AAAJ-10-2020-4991.
Pivar, J. (2020). Conceptual Model of Big Data Technologies Adoption in Smart Cities of the European Union. IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, 572-585.
Rozario, A. M. & Vasarhelyi, M. A. (2018). Auditing with smart contracts. International Journal of Digital Accounting Research, 18(1), 1–27.
https://doi.org/10.4192/1577-8517-v18_1.
Rozario, A. M. & Vasarhelyi, M. A. (2019). Enhancing Substantive Analytical Procedures with Third-Party Generated Information from Social Media. Rutgers Business School.
Rozario A. M. & Vasarhelyi, M. A. (2018). How robotic process automation is transforming accounting and auditing. The CPA Journal, 88, 46–49.
https://doi.org/10.20869/AUDITF/2020/160/024.
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.
Sancho-Zamora, R.; Hernández-Perlines, F.; Peña-García, I. & Gutiérrez-Broncano, S. (2022). The Impact of Absorptive Capacity on Innovation: The Mediating Role of Organizational Learning. International Journal of Environment Research and Public Health, 19(2), 842.
https://doi.org/10.3390/ijerph19020842.
Santos, F.; Pereira, R. & Vasconcelos, J. B. (2020). Toward robotic process automation implementation: an end-to-end perspective. Business Process Management Journal, 26(2), 405-420.
https://doi.org/10.1108/BPMJ-12-2018-0380
Scott, W. (2003). Organisation: Rational, Natural, and Open System. 5. ed. Upper Saddle River, NJ: Prentice Hall.
Siew, E.G., Rosli, K. & Yeow, P.H.P. (2019). Organizational and environmental influences in the adoption of computer-assisted audit tools and tec. International Journal of Accounting Information Systems, 36, 100445.
https://doi.org/10.1016/j.accinf.2019.100445.
Sun, T. (2019). Applying Deep Learning to Audit Procedures: An Illustrative Framework. Accounting Horizons.
Sun, T. & Sales, L. J. (2018). Predicting Public Procurement Irregularity: An Application of Neural Networks. Journal of Emerging Technologies in Accounting, 15(1), 141–154.
https://doi.org/10.2308/jeta-52086.
Tornatzky, L. G. & Fleischer, M. (1990). The Processes of Technological Innovation. Lexington – MA: Lexington Books.
Tsou, H.-T. & Hsu, S. H.-Y. (2015). Performance effects of technology–organization–environment openness, service co-production, and digital-resource readiness: The case of the IT industry. International Journal of Information Management, 35(1), 1-14.
https://doi.org/10.1016/j.ijinfomgt.2014.09.001.
Venkatesh, V. & Bala, H. (2012). Adoption and impacts of interorganizational business process standards: Role of partnering synergy. Information Systems Research, 1-27.
https://doi.org/10.1287/isre.1110.0404.
Villadsen, A. R.; Hansen, J. R. & Mols, N. P. (2010). When do public managers imitate each other? Mimetic decision making in contracting decisions of Danish municipalities. Public Organization Review, 10(4), 357–376.
https://doi.org/10.1007/s11115-010-0111-x
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.
White, B. S.; King, C. G. & Hollada, J. (2020). Blockchain security risk assessment and the auditor. Journal of Corporate Accounting & Finance, 31(2), 47–53.
https://doi.org/10.1002/jcaf.22433.
Widuri, R.; Handoko, B. L. &Prabowo, I. C. (2019). Adoption of Information Technology in Public Accounting Firm. In: Proceedings of the 4th International Conference on Big Data and Computing, 198-202.
Widuri, R.; O’connell, B. & Yapa, P. W. W. (2019). Adopting generalized audit software: an Indonesian perspective. Managerial Auditing Journal, 31(8/9), 821-847.
https://doi.org/10.1108/MAJ-10-2015-1247
Witte, A. L. (2020). Technology Based Audit Tools: Implications for Audit Quality. 2020. Pesquisa (Doutorado em Contabilidade) – Setor de Contabilidade, Bentley University.
Zahra, S. A. & George, G. (2002). Absorptive Capacity: A Review, Reconceptualization and Extension. The Academy of Management Review, 27(2), 185-203.
https://doi.org/10.2307/4134351.
Zhu, K. & Kraemer, K. L. (2005). Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry. Information systems Research, 16 (1), 61–84.
https://doi.org/10.1287/isre.1050.0045.
Al-Htaybat, K. & Von Alberti-Alhtaybat, L. (2017). Big Data and corporate reporting: impacts and paradoxes. Accounting, Auditing & Accountability Journal, 30(4), 850-873.
https://doi.org/10.1108/AAAJ-07-2015-2139.
Ali, M. & Park, K. (2016). The mediating role of an innovative culture in the relationship between absorptive capacity and technical and non-technical innovation. Journal of Business Research, 69(5), 1669-1675.
https://doi.org/10.1016/j.jbusres.2015.10.036.
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), 439–49.
https://doi.org/10.2308/acch-51067.
Amorim, E. N. C.; Vicente. E. F. R.; Will, A. R. & Silva, F. A. (2012). O mercado de auditoria no Brasil: um retrato considerando a percepção das firmas de auditoria. Revista Catarinense da Ciência Contábil – CRCSC, 11(32).
http://dx.doi.org/10.16930/2237-7662/rccc.v11n32p73-87.
Appelbaum, D. & Nehmer, R. A. (2017). Using drones in internal and external audits: An exploratory framework. Journal of Emerging Technologies in Accounting, 1, 99-113.
http://10.2308/jeta-51704.
Austin, A.; Carpenter, T; Christ, M & Nielson, C. (2019). The data analytics transformation: Evidence from auditors, CFOs, and standard-setters. SSRN.
http://10.2139/ssrn.3214140.
Baker, J. (2011). The technology-Organization-Environment Framework. In: Y.K. Dwivedi et al. (Eds.). Information Systems Theory: Explaining and Predicting Our Digital Society, Integrated Series in Information Systems, 1(28).
Barr-Pulliam, D.; Brown-Liburd, H. L. & Munoko, I. (2022). The Effects of Person-Specific, Task, and Environmental Factors on Digital Transformation and Innovation in Auditing: A Review of the Literature. Journal of International Financial Management & Accounting, 33 (2), 337-374.
https://doi.org/10.1111/jifm.12148
Barr-Pulliam, D.; Brown-Liburd, H. L. & Sanderson, K. A. (2021). The effects of the internal control opinion and use of audit data analytics on perceptions of audit quality, assurance, and auditor negligence. Auditing: A Journal of Practice and Theory, 41 (1): 25–48.
https://doi.org/10.2308/AJPT-19-064.
Bradley, S. W.; Shepherd, D. A. & Wiklund, J. (2011). The importance of slack for new organizations facing ‘tough’ environments. Journal of Management Studies, 48(5), 1071–1097.
https://doi.org/10.1111/j.1467-6486.2009.00906.x
Brown-Liburd, H. & Vasarhelyi, M. (2015). Big Data and Audit Evidence. Journal of Emerging Technologies in Accounting, 12(1), 1–16.
https://10.2308/jeta-10468.
Carpenter, V. L. & Feroz, E. H. (2001). Institutional theory and accounting rule choice: An analysis of four US state governments’ decisions to adopt generally accepted accounting principles. Acc. Organ. Soc., 26(7), 565–596.
https://doi.org/10.1016/S0361-3682(00)00038-6.
Chan, F. T. & Chong, A. Y. L. (2013). Determinants of mobile supply chain management system diffusion: a structural equation analysis of manufacturing firms. International Journal of Production Research, 51(4), 1196-1213.
https://doi.org/10.1080/00207543.2012.693961.
Chong, L. W. & He, Z. (2019). Blockchain disruption and smart contracts. Review of Financial Studies, 32(5), 54–97.
https://doi.org/10.1093/rfs/hhz007.
Cohen, W. & Levinthal, D. (1990). Absorptive capacity, a new perspective on learning and innovation, Admin. Sci. Quart, 35(1), 128–152.
https://doi.org/10.2307/2393553.
Cooper, L. A.; Holderness, D. K.; Sorensen, T. L. & Wood, D. A. (2019). Robotic Process Automation in Public Accounting. Accounting Horizons, 33(4), 15-35.
http://dx.doi.org/10.2139/ssrn.3193222.
Dagiliene, 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.
Dedoulis, E. (2016). Institutional formations and the Anglo-Americanization of local auditing practices: The case of Greece. Accounting Forum, 40(1), 29–44.
https://doi.org/10.1016/j.accfor.2015.11.003.
Dimaggio, P. J. & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review,48(2), 147–160.
https://doi.org/10.2307/2095101.
Eilifsen, A.; Kinserdal, F; Messier Jr & Mckee, T. E. (2020). An exploratory study into the use of audit data analytics on audit engagements. Accounting Horizons.34(4).
http://10.2308/HORIZONS-19-121.
Flatten, T. C.; Engelen, A.; Zahra, S. A. & Brettel, M. (2011). A measure of absorptive capacity: Scale development and validation. European Management Journal, 29(2), 98-116.
https://doi.org/10.1016/j.emj.2010.11.002.
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing, 18(1), 39-59.
https://doi.org/10.2307/3151312
Freitas, C. A. S. & Guimarães, T. A. (2007). Isomorphism, Institutionalization and Legitimacy: Operational Auditing at the Court of Auditors. RAC, 153 - 175.
https://doi.org/10.1590/S1415-65552007000500008.
Grover, V. & Kohli, R. (2012). Cocreating IT value: New capabilities and metrics for multifirm environments. Mis Quarterly, 36(1).
https://doi.org/10.2307/41410415.
Hair, J. F. J.; Ringle, C. M. & Sarstedt, M. (2014). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning: Prentice-Hall.
http://dx.doi.org/10.1016/j.lrp.2013.01.001.
Handoko, B. L. (2021). How audit firm size moderate effect of TOE context toward auditor adoption of machine learning. Journal of Theoretical and Applied Information Technology, 99(24), 5972-5980.
Handoko, B. L. & Thomas, G. N. (2021). How audit firm size moderate effect of TOE context toward auditor adoption of technology. Turkish Journal of Computer and Mathematics Education. 12(6), 1518-1526.
Henry, B. & Hicks, M. (2015). A Survey of Perspectives on the Future of the Accounting Profession. The CPA Journal; 85(8), 6-9.
Hinings, B.; Gegenhuber, T. &Greenwood, R. (2018). Digital innovation and transformation: An institutional perspective. Information and Organization, 28(1), 52–61.
https://doi.org/10.1016/j.infoandorg.2018.02.004.
Huang, F. & Vasarhelyi, M. A. (2019). Applying robotic process automation (HUU) in auditing: A framework. International Journal of Accounting Information Systems, 35, 1-11.
https://doi.org/10.1016/j.accinf.2019.100433.
Inghirami, I. E. (2018). Accounting Information Systems in the Time of Blockchain. Pávia: ITAIS Conference.
Kenny, D. A. & Judd, C. M. (1984). Estimating the nonlinear and interactive effects of latent variables. Psychological Bulletin, 96 (1), 201–210.
https://doi.org/10.1037/0033-2909.96.1.201.
Kroon, N.; Alves, M. C. & Martins, I. (2021). The Impacts of Emerging Technologies on Accountants’ Role and Skills: Connecting to Open Innovation—A Systematic Literature Review. Journal of Open Innovation: Technology, Market, and Complexity, 7(3), 2021.
https://doi.org/10.3390/joitmc7030163.
Li, Q. & Vasarhelyi, M. (2018). Developing a Cognitive Assistant for the Audit Plan Brainstorming Session. The International Journal of Digital Accounting Research, 18, 119–140.
https://doi.org/10.4192/1577-8517-v18_5.
Liang, H.; Saraf, N.; Hu, Q. & Xue, Y. (2007). Assimilation of Enterprise Systems: The Effect of Institutional Pressures and the Mediating Role of Top Management. Mis Quarterly, 31(1), 59-87.
https://doi.org/10.2307/25148781.
Low, C.; Chen, Y. & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial management & data systems, 111 (7), 1006-1023.
https://doi.org/10.1108/02635571111161262.
Majchrzak, A.; Markus, M. L. & Wareham, J. (2016). Designing for digital transformation: Lessons for information systems research from the study of ICT and societal challenges. MIS Quarterly, 40(2), 267-277.
Mckinley, W. & Mone, M. (2003). Organization theory. Oxford University Press – USA.
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.
Montes, G. A. & Goertzel, B. (2019). Distributed, decentralized, and democratized artificial intelligence. Technological Forecasting and Social Change,141, 354-358.
https://doi.org/10.1016/j.techfore.2018.11.010.
Oliveira, R. C. R. (2017). Adoção de tecnologias da informação em micro, pequenas e médias empresas: um estudo a partir da adaptação do modelo technology, organization and environment (TOE) sob influência de fatores institucionais. Pesquisa de Doutorado - Programa de Pós-Graduação em Administração, Universidade Federal da Bahia, Bahia.
Oliveira, T. & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. The Electronic Journal Information Systems Evaluation, 14 (1), 110-121.
Oliveira, T.; Martins, R.; Sarker, S.; Thomas, M. & Popovič, A. (2019). Understanding SaaS adoption: The moderating impact of the environment context. International Journal of Information Management, 49, 1-12.
https://doi.org/10.1016/j.ijinfomgt.2019.02.009.
Pimentel, E. & Boulianne, E. (2020). Blockchain in Accounting Research and Practice: Current Trends and Future Opportunities. Accounting Perspectives, 19(4), 325–361.
https://doi.org/10.1108/AAAJ-10-2020-4991.
Pivar, J. (2020). Conceptual Model of Big Data Technologies Adoption in Smart Cities of the European Union. IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, 572-585.
Rozario, A. M. & Vasarhelyi, M. A. (2018). Auditing with smart contracts. International Journal of Digital Accounting Research, 18(1), 1–27.
https://doi.org/10.4192/1577-8517-v18_1.
Rozario, A. M. & Vasarhelyi, M. A. (2019). Enhancing Substantive Analytical Procedures with Third-Party Generated Information from Social Media. Rutgers Business School.
Rozario A. M. & Vasarhelyi, M. A. (2018). How robotic process automation is transforming accounting and auditing. The CPA Journal, 88, 46–49.
https://doi.org/10.20869/AUDITF/2020/160/024.
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.
Sancho-Zamora, R.; Hernández-Perlines, F.; Peña-García, I. & Gutiérrez-Broncano, S. (2022). The Impact of Absorptive Capacity on Innovation: The Mediating Role of Organizational Learning. International Journal of Environment Research and Public Health, 19(2), 842.
https://doi.org/10.3390/ijerph19020842.
Santos, F.; Pereira, R. & Vasconcelos, J. B. (2020). Toward robotic process automation implementation: an end-to-end perspective. Business Process Management Journal, 26(2), 405-420.
https://doi.org/10.1108/BPMJ-12-2018-0380
Scott, W. (2003). Organisation: Rational, Natural, and Open System. 5. ed. Upper Saddle River, NJ: Prentice Hall.
Siew, E.G., Rosli, K. & Yeow, P.H.P. (2019). Organizational and environmental influences in the adoption of computer-assisted audit tools and tec. International Journal of Accounting Information Systems, 36, 100445.
https://doi.org/10.1016/j.accinf.2019.100445.
Sun, T. (2019). Applying Deep Learning to Audit Procedures: An Illustrative Framework. Accounting Horizons.
Sun, T. & Sales, L. J. (2018). Predicting Public Procurement Irregularity: An Application of Neural Networks. Journal of Emerging Technologies in Accounting, 15(1), 141–154.
https://doi.org/10.2308/jeta-52086.
Tornatzky, L. G. & Fleischer, M. (1990). The Processes of Technological Innovation. Lexington – MA: Lexington Books.
Tsou, H.-T. & Hsu, S. H.-Y. (2015). Performance effects of technology–organization–environment openness, service co-production, and digital-resource readiness: The case of the IT industry. International Journal of Information Management, 35(1), 1-14.
https://doi.org/10.1016/j.ijinfomgt.2014.09.001.
Venkatesh, V. & Bala, H. (2012). Adoption and impacts of interorganizational business process standards: Role of partnering synergy. Information Systems Research, 1-27.
https://doi.org/10.1287/isre.1110.0404.
Villadsen, A. R.; Hansen, J. R. & Mols, N. P. (2010). When do public managers imitate each other? Mimetic decision making in contracting decisions of Danish municipalities. Public Organization Review, 10(4), 357–376.
https://doi.org/10.1007/s11115-010-0111-x
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.
White, B. S.; King, C. G. & Hollada, J. (2020). Blockchain security risk assessment and the auditor. Journal of Corporate Accounting & Finance, 31(2), 47–53.
https://doi.org/10.1002/jcaf.22433.
Widuri, R.; Handoko, B. L. &Prabowo, I. C. (2019). Adoption of Information Technology in Public Accounting Firm. In: Proceedings of the 4th International Conference on Big Data and Computing, 198-202.
Widuri, R.; O’connell, B. & Yapa, P. W. W. (2019). Adopting generalized audit software: an Indonesian perspective. Managerial Auditing Journal, 31(8/9), 821-847.
https://doi.org/10.1108/MAJ-10-2015-1247
Witte, A. L. (2020). Technology Based Audit Tools: Implications for Audit Quality. 2020. Pesquisa (Doutorado em Contabilidade) – Setor de Contabilidade, Bentley University.
Zahra, S. A. & George, G. (2002). Absorptive Capacity: A Review, Reconceptualization and Extension. The Academy of Management Review, 27(2), 185-203.
https://doi.org/10.2307/4134351.
Zhu, K. & Kraemer, K. L. (2005). Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry. Information systems Research, 16 (1), 61–84.
https://doi.org/10.1287/isre.1050.0045.
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31-03-2025
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Lima de Araujo, P. G., Costa de Oliveira ARaujo, L., & Façanha Camara, S. (2025). Adoption of emerging technologies in a regulated environment: a study in audit companies: A study in audit companies. Revista De Educação E Pesquisa Em Contabilidade (REPeC), 19. https://doi.org/10.17524/repec.v19.e3687
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