Infometry in the Web of Science and Scopus bases: Corporate Governance, Information and Information Technology; Pricing of Actions and Market Risks

Authors

DOI:

https://doi.org/10.33448/rsd-v10i5.15433

Keywords:

Corporate governance; Information; Information technology; Stock pricing; Market risks.

Abstract

The study aimed to raise the theoretical framework through an infometry to identify the state of the art on "Corporate Governance", "Information", "Information technology", "Stock Pricing" and "Market risks", in Portuguese / English, based on keywords / terms, researched in the Web of Science and Scopus databases in the period from 2015 to 2020. For this portfolio, a bibliometric analysis and a systematic review of the literature was carried out in order to build the referent knowledge. to matters. As the articles in the Scopus database were also present in the Web of Science database and because there were a smaller number of articles found in the Scopus database, it was decided to keep only the articles of the Web of Science database, a total of 307 articles, in continuity of research. English; as the base chosen is a very complete, multidisciplinary base and access to the use of the VOSViewer and NVivo software used in this study is acceptable. The articles analyzed were all from 2020 because they are as current as possible. It is inferred that in this study most authors study in isolation, without connections. Document analysis was performed in the bibliographic coupling of 30 articles. Thus, the novelty and gap in the research stands out. It is stated that the words searched for in the study when all together with the Boolean operators are not found in the respective articles. Although in all the articles studied, the term “Information” is only explained. The importance of this term for the authors is well known, in a broad context it is understood that “information” is an essential element for human survival.

References

Afonso, M. H. F. et al. (2012). Como construir conhecimento sobre o tema de pesquisa? Aplicação do processo Proknow-C na busca de literatura sobre avaliação do desenvolvimento sustentável. Revista de Gestão Social e Ambiental, 5(2), 47-62.

Alexopoulou, A., Batsou, A., & Drigas, A. (2021). The contribution of Information and Communication Technologies to the improvement of the adaptive skills and the social inclusion of students with intellectual disability. Research, Society and Development, 10(4), e47010413046, 2021 (CC BY 4.0) | ISSN 2525-3409 | . http://dx.doi.org/10.33448/rsd-v10i4.13046

Antonelli, R. A., et al. (2016). Adhesion and migration to the differentiated levels of corporate governance: an investigation of the event window. Contabilidade, Gestão e Governança, Brasília, 19(1), 23-48, jan./abr.

Araújo, C. A. A. (2006). Bibliometria: evolução histórica e questões atuais. Em Questão, 12(1), 11-32.

Arrivabene, A., Sassi, R. J., Andrelo, P. F. A., & Oliveira, M. L. A. de M. (2021). Análise do Impacto da Adequação nos Processos Operacionais de Tecnologia da Informação Às Exigências da Lei Sarbanes-Oxley em Empresa do Ramo Financeiro. Research, Society and Development, 10(1), e7710111374. (CC BY 4.0) | ISSN 2525-3409 | http://dx.doi.org/10.33448/rsd-v10i1.11374.

Assunção, R. R., Luca, M. M., & Vasconcelos. (2017). A Complexity and corporate governance: an analysis of companies listed on the, BM&FBOVESPA. Revista Contabilidade e Finanças, São Paulo, 28(74), 213-228, maio/ago.

Belinski, R., et al. (2020). Organizational learning and Industry 4.0: findings from a systematic literature review and research agenda. Benchmarking: An International Journal, 27(8), 2435-2457.

Ben-Dayaa, M., & Hassinib; Bahrouna, Z. (2017). Internet of things and supply chain management: a literature review. International Journal of Production Research, 59(15/16), 4719-4742,

Braga, G. M. (1973). Relações Bibliométricas Entre a Frente de Pesquisa (Research Front) e Revisões da Literatura: Estudo Aplicado a Ciência da Informação. Ciência da Informação, Rio de Janeiro, 2(1), 9-26.

Bruna Júnior, E. D., Ensslin, L., & Ensslin, S. R. (2012). Seleção e análise de um portfólio de artigos sobre avaliação de desempenho na cadeia de suprimentos. Gestão da Produção, Operações e Sistemas, GEPROS, 7(1), 113-125, jan./mar.

Carley, K. (1993). Coding choices for textual analysis: A comparison of content analysis and map analysis. Sociological Methodology, v. 23, p. 75-126.

Chen, L.-C., et al. (2018). Encoder-decoder with atrous separable convolution for semantic image segmentation. In: The European Conference On Computer Vision (ECCV). Proceedings [...], p. 801-818.

Chen, Yu., Yang, C., Zhang, Y., & Li, Y. (2020). Deep conditional adaptation networks and label correlation transfer for unsupervised domain adaptation. Pattern Recognition, 98, 107-172.

Coordenação De Aperfeiçoamento De Pessoal De Nível Superior (Capes). (2020). http://www.periodicos.capes.gov.br/.

Dias, M. M. K., & Belluzzo, R. C. B. (2003). Gestão da informação em ciência e tecnologia sob a ótica do cliente: EDUSC.

Ding, H., Pan, Z., Cen, Q., Li, Y., & Chen, S. (2020). Multi-scale fully convolutional network for gland segmentation using three-class classification. Neurocomputing, 380, 150-161.

Egghe, L., & Rousseau, R. (2002). Co-citation, bibliographic coupling and a characterization of lattice citation networks. Scientometrics, 55(3), 349-361.

Eck, N. J. V., & Waltman, L. (2007). Vos: a new method for visualizing similarities between objects. In: Annual Conference of The German Classification Society, 30. Proceedings […]. p. 299-306.

Eck, N. J. V. (2011). Methodological Advances in Bibliometric Mapping of Science. Rotterdam: Erasmos University.

Enssiln, S. R., et al. (2014). Costs’ Behavior: Selection of a Literature Review Material and Bibliometric Analysis. Revista de Contabilidade do Mestrado em Ciências Contábeis da UERJ, Rio de Janeiro, 19(3), 2-25, set/dez.

Ensslin, L., Ensslin, S. R., & Pinto, H. M. (2013). Processo de Investigação e Análise Bibliométrica: Avaliação da qualidade dos serviços bancários. Revista de Administração Contemporânea, p. 325- 349.

Estevão, J. S. B., & Strauhs, F. do R. (2020). Letramento informacional para reuso de dados nas ciências sociais: requisitos e competências. Informação & Informação, Londrina, 252, 1-25, abr./jun.

Estevão, J. S. B. (2020). Introdução ao NVivo: potencialidades para pesquisas qualitativas, quantitativas e mistas. Material Didático: UFPR.

Etges, A. P. B. S & Souza, J. S. (2015). Estudo de campo sobre gestão de riscos corporativos em empresas participantes de um parque científico e tecnológico. International Journal of Software Engineering and Knowledge Engineering, Florianópolis, 4(8), 23-42.

Fang, Y., et al. (2020). A survey of community search over big graphs. The VLDB Journal, 29, 353-392.

Fellet, B. G. (2016). Avaliação de Modelos de Precificação de Ativos no Mercado Acionário Brasileiro. Dissertação (Mestrado em Ciências Contábeis) – Programa Multiinstitucional e Inter-Regional de Pós-Graduação em Ciências Contábeis, Universidade de Brasília, Brasília.

Feng, X., & Behar-Horenstein, L. (2019). Maximizing NVivo Utilities to Analyze Open-Ended Responses. Qualitative Report, 243, 563-571.

Fernandes, G., & Brandão, L. E. T. (2016). Managing uncertainty in product innovation using marketing strategies. Revista de Gestão da Tecnologia e Sistemas de Informação, 13(2), 219-240, maio/ago.

Fu, J., et al. (2020). Contextual deconvolution network for semantic segmentation. Pattern Recognition, 101, p. 107152.

Galvão, T. F., & Pereira, M. G. (2014). Systematic reviews of the literature: steps for preparation. Epidemiologia e Serviços de Saúde, Brasília, 23(1), 183-184, jan./mar.

Gao, P., et al. Siamese Attentional Keypoint Network for High Performance. Visual Tracking, arXiv:1904.10128v2. (2019).

Halpern, E. S. (1983). Auditing naturalistic inquiries: The development and application of a model Thesis (Degree Ph. D.) – Indiana University, Bloomington.

Han, X., et al. (2020). An Attention-Based Model Using Character Composition of Entities in Chinese Relation Extraction. Information, v.11, p. 79.

Howison, J., et al. (2015). Understanding the scientific software ecosystem and its impact: Current and future measures. Research Evaluation, 24(4), 454-470.

Karlsson, C. (2008). Researching operations management: Routledge.

Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation,14(1), 10-25.

Krzyzanowski, R., & Ferreira, M. C. (1998). Avaliação de periódicos científicos e técnicos brasileiros. Ciência da Informação, 27(2), 165-175, maio/ago.

Lei, K., et al. (2020). Time-driven feature-aware jointly deep reinforcement learning for financial signal representation and algorithmic trading. Expert Systems With Applications, 140, 112-872.

Lecun, Y., et al. (1998). Gradient-based learning applied to document recognition. IEEE, 86(11), 2278-2324.

Li, J., et al. (2020). Deep graph regularized non-negative matrix factorization for multi-view clustering. Neurocomputing, 390, 108-116.

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Thousand Oaks: Sage.

Liu, Y., et al. (2020). Deep Salient Object Detection With Contextual Information Guidance. IEEE, v. 29.

Li, Y., et al. (2020). Simultaneously learning affinity matrix and data representations for machine fault diagnosis. Neural Networks, 122, 395-406.

LI, H., et al. (2020). Translation-Based Sequential Recommendation for Complex Users on Sparse Data. IEEE, 32(8).

Liu, Y., et al. (2020). A multidimensional chaotic image encryption algorithm based on the region of interest. Multimedia Tools and Applications, 79, 17669-17705.

Liu, Y., et al. 2020. Identifying Key Opinion Leaders in Social Media via Modality-Consistent Harmonized Discriminant Embedding. IEEE, 50(2).

Liao, W., et al. (2020). Improved sequence generation model for multi-label classification via CNN and initialized fully connection. Neurocomputing, 382, 188-195.

Liu, Y., et al. (2020). Label-activating framework for zero-shot learning. Neural Networks, 121, 1-9.

Long, M., et al. (2015). Learning Transferable Features with Deep Adaptation Networks. In: International Conference On Machine Learning, 32., 2015. Proceedings [...]. p. 97-105.

Lopes, I. F., Beuren, I. M., &Vicente, E. F. R. (2021). Association Between Risks Management Disclosure and Corporate Governance and Performance in Companies with ADRs. Revista Evidenciação Contábil & Finanças, ISSN 2318-1001, João Pessoa, 9(1), 5-21, jan./abril.

Lucas, E. R. O., Garcia-Zorita, J. C., & Sanz-Casado, E. (2013). Evolução histórica de investigação em informetria: ponto de vista espanhol. Liinc em revista, 9(1), 255-270.

Macaulay, P. J. R., et al. (2018). Perceptions and responses towards cyberbullying: A systematic review of teachers in the education system. Aggression and Violent Behavior, 43, 1-12.

Macias-Chapula, C. A. (1998). O papel da informetria e da cienciometria e sua perspectiva nacional e internacional. Ciência da informação, 27(2), 134-140.

Mamaghani, F. (2010). The Social and Economic Impact of Information and Communication Technology on Developing Countries: An Analysis. International Journal of Management, 27(3), 255-276, dez.

Mendes-Da-Silva, W., et al. (2013). Rede de Pesquisadores de Finanças no Brasil: um Mundo Pequeno Feito por Poucos. RAC, Rio de Janeiro, 17(6), 739-763, nov./dez.

Miguel Peixe, A. M., Rosa Filho, C. da., Passos, G. de A., Formiga, M. V., & Severo Peixe, B. (2016). Custos de Transação Aplicados no Setor Público e Privado: uma análise bibliométrica das edições do Congresso Brasileiro de Custos e USP International Conference in Accounting. In: Congresso Brasileiro De Custos, 23., 2016. Anais [...]. Porto de Galinhas. https://anaiscbc.emnuvens.com.br/anais/article/ view/4077/4078.

Moreira, P. S. C., Guimarães, A. J. R., & Tsunoda, D. F. (2020). Qual ferramenta bibliométrica escolher? Um estudo comparativo entre softwares. P2P & Inovação, Rio de Janeiro, 6(2), 140-158.

Mugnaini, R., Jannuzzi, P. M., & Quoniam, L. (2004). Indicadores bibliométricos da produção científica brasileira: uma análise a partir da base Pascal. Ciência da informação, 33(2), 123-131, maio/ago.

NIE, X., et al. (2020). Method to Predict Bursty Hot Events on Twitter Based on User Relationship Network. IEEE, v. 8.

Oliveira, A. C., Dórea, J. G., & Domene, S. M. A. (1992). Bibliometria na avaliação da produção científica da área de nutrição registrada no CIBRAN: período de 1984-1989. Ciência da Informação, Brasília, 21(3), 239-242, set./dez.

Onwuegbuzie, A. J., & Leech, N. L. (1985). Validity and qualitative research: An oxymoron? Quality & Quantity, 41(2), 233-249.

Paula, L. G., et al. (2015). Ict Strategic Planning at Public Higher Educational Organizations: Building an Approach Through Action Research at Unirio. JISTEM, 12(2), 351-370, maio/ago.

Price, D. J. S. (1965). Networks of scientific papers. Science, 149(3683), 56-64, jul.

Sampaio, R. F., & Mancini, M. C. (2007). Estudos de revisão sistemática: um guia para síntese criteriosa da evidência científica. Revista Brasileira de Fisioterapia, 11(1), 83-89.

Sartori, S. et al. (2014). Literature review of environmental sustainability related to information technology. TransInformação, Campinas, 26(1), 77-89, jan./abr.

Sbicca, A., & Pelaez, V. (2006). Sistemas de Inovação. In: Pelaez, V., Szmrecsányi, T. Economia da Inovação Tecnológica: Hucitec, p. 415-448.

Seção de Acesso às Bases de Dados (SEABD). (2020). http://www.seabd. bco.ufscar.br/bases-de-dados/bases-capes/scopus-base-multidiciplinar-elsevier-portal-capes.

Sêmola, M. (2014). Gestão da segurança da informação: uma visão executiva. (2ª ed.): Elsevier.

Silva, W. V., Kaczam, F., & Silva, D. J. C. (2020). Revisão Sistemática de Literatura. Material Didático: Universidade Federal de Santa Maria.

Sousa, C. B., et al. (2014). Market Value and Voluntary Disclosure: An empirical study in companies listed on BM&Fbovespa. Revista Ambiente Contábil, Natal, 6(2), 94-11.

Souza, M. M. de., Martinez, A. L., Murcia, F. DAL-RI., & Bastos, S. A. P. (2019). The Determinants of Compliance with The Disclousure Norms of Provisions and Contingent Assets and Liabilities in B3. Sociedade, Contabilidade e Gestão, Rio de Janeiro, 14(2), mai/ago. https://doi.org/10.21446/scg_ufrj.v0i0.20234.

Souza, I. G. M. C., Silva, A. T., & Serafim, A. de O. (2020). Disclosure of Voluntary Information in Social Media: Is it Serious? Study of Determining Factors in Facebook. RGO - Revista Gestão Organizacional, Chapecó, 13(1), 42-64, jan./abr.

Sun, F. (2020). Gait-based identification for elderly users in wearable healthcare systems. Information Fusion, 53, 134-14.

Tague-Sutcliffe, J. (1992). An introduction to informetrics. Information processing & management, Oxford, 28(1), 1-3.

Tranfield, D., Denyer, D., & Smart, E. P. (2003). Toward a methodology for developing evidence informed management knowledge by means of systematic review. British Journal of Management, n. 14, p. 207-222.

Ullaha, K., Razaa, M. S., & Mirzab, F. M. (2019). Barriers to hydro-power resource utilization in Pakistan: A mixed approach. Energy Policy, 132, 723-735.

Vanti, N. A. P. (2002). Da bibliometria à webometria: uma exploração conceitual dos mecanismos utilizados para medir o registro da informação e a difusão do conhecimento. Ciência da Informação, 31(2), 152-162.

Vergara, S. C. (2006). Métodos de pesquisa em administração. (2ª ed.): Atlas.

Wang, R., et al. (2020). Heterogeneous information network-based music recommendation system in mobile networks. Computer Communications, 150, 429-437.

Weins, N. W. et al. (2018). Áreas Naturais Particulares em Ambientes Urbanos: uma Revisão Bibliográfica. Desenvolvimento em Questão, 17(46), 287-298.

Woida, L. M. (2020). Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação, Florianópolis, 25, 01-24. Universidade Federal de Santa Catarina. ISSN 1518-2924. https://doi.org/10.5007/1518-2924.2020.e70464

Wu, C. et al. (2019). Motion Guided Siamese Trackers for Visual Tracking. IEEE, v. 24.

Wu, G. et al. (2020). Energy efficient for UAV-enabled mobile edge computing networks: Intelligent task prediction and offloading. Computer Communications, 150, 556-562.

Wu, Z. et al. (2020). Knowledge recommendation for product development using integrated rough set‑information entropy correction. Journal of Intelligent Manufacturing, 31, 1559-1578.

Zhang, Y. (1998). Definitions and Sciences of information. Information Processing & Management, 24(4), 35-93.

Zhang, Y. et al. Large-scale multi-label classification using unknown streaming images. Pattern Recognition, 99, 107-100. (2020).

Zhang, Y. et al. (2020). PGNet: A Part-based Generative Network for 3D object reconstruction. Knowledge-Based Systems, 194, p. 105574.

Zhang M. L., & Zhou Z.-H. (2007). Ml-Knn: A lazy learning approach to multi-label learning. Pattern Recognition, 40(7), 2038–2048.

Zhang, Y. et al. (2020). Keywords extraction with deep neural network model. Neurocomputing, 383, 113-121.

Zhang, Z., et al. (2020). Joint Label Prediction Based Semi-Supervised Adaptive Concept Factorization for Robust Data Representation. IEEE,32(5).

Zhang, Z., Zhang, Y., & Ren, Y. (2020). Employing neighborhood reduction for alleviating sparsity and cold start problems in user‑based collaborative filtering. Information Retrieval Journal, 23, 449-472.

Zhao, X., et al. (2019). Deep Plug-and-Play Prior for Low-Rank Tensor Completion. Computer Vision and Pattern Recognition, Cornel University, v. 3.

Yu, L., et al. (2020). ADPE: Adaptive Dynamic Projected Embedding on Heterogeneous Information Networks. ADPE on HINs, 8, 38970-38984.

Yao, Q., et al. (2020). Multi-class Arrhythmia detection from 12-lead varied-length ECG using Attention-based Time-Incremental Convolutional Neural Network. Information Fusion, 53, 174-182.

Yan, X., et al. (2020). Multiscale cascading deep belief network for fault identification of rotating machinery under various working conditions. Knowledge-Based Systems, 193, 105-484.

Published

16/05/2021

How to Cite

PEIXE, A. M. M. .; PINTO, J. S. de P. . Infometry in the Web of Science and Scopus bases: Corporate Governance, Information and Information Technology; Pricing of Actions and Market Risks. Research, Society and Development, [S. l.], v. 10, n. 5, p. e56110515433, 2021. DOI: 10.33448/rsd-v10i5.15433. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/15433. Acesso em: 18 apr. 2024.

Issue

Section

Human and Social Sciences