Aplicabilidade da Robotic Process Automation para a detecção de sinais fracos na internet
DOI:
https://doi.org/10.51359/2317-0115.2022.256791Palavras-chave:
robotic process autoamtion, escaneamento do ambiente, sinais fracos, Foresight, tecnologia de automaçãoResumo
Diante a sistematização necessária à atividade de escaneamento do ambiente e as características da tecnologia Robotic Process Automation (RPA), esse estudo teve por objetivo avaliar a aplicabilidade da RPA nas etapas da atividade de escaneamento do ambiente para detecção de sinais fracos através de mineração de texto na internet. Para isso, foi realizada uma Revisão Sistemática da Literatura sobre a temática dos sinais fracos. Das 8 etapas identificadas, em 6 delas foi percebida compatibilidade, onde a RPA pode ser utilizada para conferir maior qualidade e eficiência. O estudo contribui com a literatura científica ao consolidar as etapas da atividade de escaneamento do ambiente, o que igualmente contribui com a prática profissional, a qual se beneficia dos ganhos de eficiência e qualidade da utilização de RPA na atividade de escaneamento.Referências
BEREZNOY, A. Corporate Foresight in Multinational Business Strategies. Foresight and STI Governance, v. 11, n. 1, p. 9-22, 2017. http://dx.doi.org/10.17323/2500-2597.2017.1.9.22.
BISSON, C.; DINER, Ö. Y. Strategic Early Warning System for the French milk market: A graph theoretical approach to foresee volatility. Futures, v. 87, p. 10-23, 2017. http://dx.doi.org/10.1016/j.futures.2017.01.004
CABRAL, P. H. D. Horizonte Contábil diante da Tecnologia Robotic Process Automation. 2022. Dissertação (Mestrado em Controladoria e Contabilidade) – Faculdade de Ciências Econômicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, 2022.
COOPER, L. A. et al. Robotic Process Automation in Public Accounting. Accounting Horizons, v. 33, n. 4, p. 15-35, 2019. https://doi.org/10.2308/acch-52466
DEY, S.; DAS, A. Robotic process automation: Assessment of the technology for transformation of business processes. International Journal of Business Process Integration and Management, v. 9, n. 3, p. 220-230, 2019. http://dx.doi.org/10.1504/IJBPIM.2019.100927
DUDIN, M. N. et al. Managing the development of high-tech enterprises based on foresighting. Academy of Strategic Management Journal, v. 16, n. 2, p. 1-12, 2017.
EL AKROUCHI, M.; BENBRAHIM, H.; KASSOU, I. Review on adopting concept extraction in weak signals detection in competitive intelligence. In: International Conference on Arab Women in Computing, 7, 2021. Anais […], Sharjah, United Arab Emirates, 2021. https://doi.org/10.1145/3485557.3485560
ENRÍQUEZ, J. G. et al. Robotic Process Automation: A Scientific and Industrial Systematic Mapping Study. IEEE Access, v. 8, p. 39113-39129, 2020. https://doi.org/10.1109/ACCESS.2020.2974934
FERNANDEZ, D.; AMAN, A. Impacts of Robotic Process Automation on Global Accounting Services. Asian Journal of Accounting and Governance, v. 9, p. 123-131, 2018. http://dx.doi.org/10.17576/AJAG-2018-09-11
GARCIA-NUNES, P. I.; SILVA, A. E. A. Using a conceptual system for weak signals classification to detect threats and opportunities from web. Futures, v. 107, p. 1-16, 2019. https://doi.org/10.1016/j.futures.2018.11.004
GOTTHARDT, M. et al. Current State and Challenges in the Implementation of Smart Robotic Process Automation in Accounting and Auditing. ACRN Journal of Finance and Risk Perspectives, v. 9, p. 90-102, 2020. https://doi.org/10.35944/jofrp.2020.9.1.007
GRAEFE, A.; LUCKNER, S.; WEINHARDT, C. Prediction markets for foresight. Futures, v. 42, p. 394-404, 2019. https://doi.org/10.1016/j.futures.2009.11.024
HOFMANN, P.; SAMP, C.; URBACH, N. Robotic process automation. Electronic Markets, v. 30, p. 99-106, 2020. https://doi.org/10.1007/s12525-019-00365-8
HUANG, F.; VASARHELYI, M. A. Applying robotic process automation (RPA) in auditing: A framework. International Journal of Accounting Information Systems, v. 35, p. 1-11, 2019. https://doi.org/10.1016/j.accinf.2019.100433
ILMOLA, L.; KUUSI, O. Filters of weak signals hinder foresight: Monitoring weak signals efficiently in corporate decision-making. Futures, v. 38, p. 908-924, 2006. https://doi.org/10.1016/j.futures.2005.12.019
KAIVO-OJA, J. Weak signals analysis, knowledge management theory and systemic socio-cultural transitions. Futures, v. 44, p. 206-217, 2012. https://doi.org/10.1016/j.futures.2011.10.003
KIM, J.; PARK, Y.; LEE, Y. A visual scanning of potential disruptive signals for technology roadmapping: investigating keyword cluster, intensity, and relationship in futuristic data. Technology Analysis & Strategic Management, v. 28, n. 10, p. 1225-1246, 2016. https://doi.org/10.1080/09537325.2016.1193593
KIM, S. et al. NEST: A quantitative model for detecting emerging trends using a global monitoring expert network and Bayesian network. Futures, v. 52, p. 59-73, 2013. http://dx.doi.org/10.1016/j.futures.2013.08.004
KLERX, J. An intelligent screening agent to scan the internet for weak signals of emerging policy issues (ISA). In: International Conference on Politics and Information Systems, Technologies and Applications, 8, 2010. Anais […], Orlando, United States of America, 2010. https://www.iiis.org/CDs2010/CD2010SCI/PISTA_2010/PapersPdf/PA891PL.pdf
KOKINA, J.; BLANCHETTE, S. Early evidence of digital labor in accounting: Innovation with Robotic Process Automation. International Journal of Accounting Information Systems, v. 35, p. 1-13, 2019. https://doi.org/10.1016/j.accinf.2019.100431
LÓPEZ-ROBLES, J. R. et al. 30 years of intelligence models in management and business: A bibliometric review. International Journal of Information Management, v. 48, p. 22-38, 2019. https://doi.org/10.1016/j.ijinfomgt.2019.01.013
MEHO, L. I.; YANG, K. Impact of Data Sources on Citation Counts and Rankings of LIS Faculty: Web of Science Versus Scopus and Google Scholar. Journal of the American Society for Information Science and Technology, v. 58, n. 13, p. 2105-2125, 2007. https://doi.org/10.1002/asi.20677
MÜHLROTH, C.; GROTTKE, M. A systematic literature review of mining weak signals and trends for corporate foresight. Journal of Business Economics, v. 88, p. 643-687, 2018. https://doi.org/10.1007/s11573-018-0898-4
OKOLI, C. A Guide to Conducting a Standalone Systematic Literature Review. Communications of the Association for Information Systems, v. 37, n. 43, p. 879-919, 2015. https://doi.org/10.17705/1CAIS.03743
PIZZANI, L. et al. A Arte aa Pesquisa Bibliográfica na Busca do Conhecimento. Revista Digital de Biblioteconomia e Ciência da Informação, v. 10, n. 1, p. 53-66, 2007. https://doi.org/10.20396/rdbci.v10i1.1896
ROHRBECK, R.; THOM, N.; ARNOLD, H. IT tools for foresight: The integrated insight and response system of Deutsche Telekom Innovation Laboratories. Technological Forecasting and Social Change, v. 97, p. 115-126, 2015. https://doi.org/10.1016/j.techfore.2013.09.015
ROWE, E.; WRIGHT, G.; DERBYSHIRE, J. Enhancing horizon scanning by utilizing pre-developed scenarios: Analysis of current practice and specification of a process improvement to aid the identification of important ‘weak signals’. Technological Forecasting and Social Change, v. 125, p. 224-235, 2017. https://doi.org/10.1016/j.techfore.2017.08.001
SANTOS, F.; PEREIRA, R.; VASCONCELOS, J. B. Toward robotic process automation implementation: an end-to-end perspective. Business Process Management Journal, v. 26, n. 2, p. 405-420, 2020. https://doi.org/10.1108/BPMJ-12-2018-0380
SCHWARZ, J. O. Pitfalls in implementing a strategic early warning system. Foresight, v. 7, n. 4, p. 22-30, 2005. https://doi.org/10.1108/14636680510611813
SNYDER, H. Literature review as a research methodology: An overview and guidelines. Journal of Business Research, v. 104, p. 333-339, 2019. https://doi.org/10.1016/j.jbusres.2019.07.039
VIGNOLI, M. et al. An Exploration of the Potential of Machine Learning Tools for Media Analysis to Support Sense-Making Processes in Foresight. Frontiers in Communication, v. 7, n. 750614, 2022. https://doi.org/10.3389/fcomm.2022.750614
Downloads
Publicado
Edição
Seção
Licença
Copyright (c) 2022 Revista dos Mestrados Profissionais
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Os trabalhos submetidos são de responsabilidade exclusiva de sua autoria, que preserva o seu direito autoral.
É permitida a citação dos trabalhos publicados sem prévia autorização desde que seja explícita a menção à fonte da RMP
