Relationships between accounting and intelligence: research paths

Authors

DOI:

https://doi.org/10.51341/1984-3925_2021v24n3a2

Keywords:

Accounting, Intelligence, Systematic Literature Review

Abstract

Objective: to identify the possible gaps and the development of knowledge in research on accounting and intelligence processes.

Method: qualitative and quantitative study. A systematic literature review was carried out, analyzing 89 articles published in scientific journals, collected in July 2020.

Originality/Relevance: accounting is increasingly taking part in decision-making processes and business management. Therefore, accounting science must appropriate strategic intelligence concepts since using information from outside the organization can assist in the more assertive measurement of accounting events and obtaining better information for decision making.

Results: four main categories of research were observed in the articles analyzed. The use of Business Intelligence systems, improvement of accounting provisions, monitoring the environment to identify aspects relevant to the organizations’ financial life, and the automation of accounting processes through artificial intelligence and other technologies.

Theoretical/Methodological contributions: this study offers a view on how accounting and intelligence branch out into different research categories. It was possible to identify research gaps and four categories in the development of knowledge on accounting and intelligence processes. Two of them refer to technology and process automation, one focused on managerial aspects of monitoring the environment, and one category is more technical focused on accounting calculation. The study’s methodological contribution lies in its form of systematization and illustration of the collection processes.

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Author Biographies

Fernanda da Silva Momo, Universidade Federal do Rio Grande do Sul

Doutora e Mestra em Administração com ênfase em Gestão de Sistemas de Informação pela Escola de Administração da Universidade Federal do Rio Grande do Sul (UFRGS). Contadora, formada pela Faculdade de Ciências Econômicas da UFRGS. Professora do Departamento de Ciências Contábeis e Atuariais (DCCA) e do Programa de Pós-Graduação em Contralodoria e Contabilidade (PPGCont/FCE) da UFRGS.

Claudia Melati, Universidade Federal do Rio Grande do Sul

Doutoranda e Mestra em Administração com ênfase em Gestão de Sistemas de Informação pela Escola de Administração da Universidade Federal do Rio Grande do Sul (UFRGS). Administradora.

Raquel Janissek-Muniz, Universidade Federal do Rio Grande do Sul

Graduação em Informática com ênfase em Análise de Sistemas pela UNIJUÍ-RS (1995), Mestrado em Administração pela Escola de Administração da UFRGS (2000), Master DEA MATIS na Université de Genebra/Suíça (2001), Master DEA en Systèmes dInformation pela Université Pierre Mendes France (2001), Doutorado em Sciences de Gestion pela Université Pierre Mendes France (2004) e Pós-Doutorado em Administração no GIANTI-PPGA/EA/UFRGS (2005-2006). Desde setembro/2006 é Professora na Escola de Administração e no Programa de Pós-Graduação (PPGA/EA/UFRGS).

Ariel Behr, Universidade Federal do Rio Grande do Sul

Doutor e Mestre em Administração na área de Sistemas de Informação e Apoio à Decisão pelo PPGA/EA/UFRGS. Professor do Departamento de Ciências Contábeis e Atuariais (DCCA), do Programa de Pós-Graduação em Administração da Escola de Administração (PPGA/EA) e Programa de Pós-Graduação em Contralodoria e Contabilidade (PPGCont/FCE) da UFRGS.

References

Acker, D., Horton, J., & Tonks, I. (2002). Accounting standards and analysts’ forecasts: the impact of FRS3 on analysts’ ability to forecast EPS. Journal of Accounting and Public Policy, 21(3), 193-217. https://doi.org/10.1016/S0278-4254(02)00049-2 DOI: https://doi.org/10.1016/S0278-4254(02)00049-2

Adegbile, A., Sarpong, D., & Meissner, D. (2017). Strategic Foresight for Innovation Management: A Review and Research Agenda. International Journal of Innovation and Technology Management, 14(4), 1-34. DOI: https://doi.org/10.1142/S0219877017500195

Aleksic, M., Vujnovic-Gligoric, B., & Uremovic, N. (2015). The Role And The Significance Of Forecast Accounting In Financial Preview. Casopis Za Ekonomiju I Trzisne Komunikacije, 5(2), 229-236.

Andrade, J. P., & Lopes Lucena, W. G. (2018). Analysis of performance of forecast models insolvency and the implementation of International Accounting Standards. Revista Ciencias Administrativas, 24(2). http://dx.doi.org/10.5020/2318-0722.2018.6563 DOI: https://doi.org/10.5020/2318-0722.2018.6563

Andriotti, F., & Freitas, H. (2008). A informação informal e a monitoração do ambiente: fontes e exploração/disseminação. Revista de Administração da Universidade Federal de Santa Maria, 1(3). https://doi.org/10.5902/19834659607 DOI: https://doi.org/10.5902/19834659607

Atkinson, A. A., Banker, R. D., Kaplan, R. S., & Young, M. (2000) Contabilidade gerencial. São Paulo: Atlas.

Ayres, D., Huang, X. S., & Myring, M. (2017). Fair value accounting and analyst forecast accuracy. Advances in accounting, 37, 58-70. https://doi.org/10.1016/j.adiac.2016.12.004 DOI: https://doi.org/10.1016/j.adiac.2016.12.004

Baldwin-Morgan, A. A. (1995). Integrating artificial intelligence into the accounting curriculum. Accounting Education, 4(3), 217-229. https://doi.org/10.1080/09639289500000026 DOI: https://doi.org/10.1080/09639289500000026

Barnea, A., & Lakonishok, J. (1980). An analysis of the usefulness of disaggregated accounting data for forecasts of corporate performance. Decision Sciences, 11(1), 17-26. https://doi.org/10.1111/j.1540-5915.1980.tb01122.x DOI: https://doi.org/10.1111/j.1540-5915.1980.tb01122.x

Bardin L. Ánálise de conteúdo. SP: Edições 70, 2011.

Barth, M. E. (2014). Measurement in Financial Reporting: The Need for Concepts. Accounting Horizons, 28 (2). https://dx.doi.org/10.2139/ssrn.2235759 DOI: https://doi.org/10.2308/acch-50689

Barth, M. E.; & Shipper, K. (2008). Financial Reporting Transparency. Journal of Accounting, Auditing & Finance, 23 (2). https://doi.org/10.1177%2F0148558X0802300203 DOI: https://doi.org/10.1177/0148558X0802300203

Behrens, M. L., & Steinbart, P. J. (1992). Integrating expert systems and artificial intelligence in accounting: A description of the academic program at Memphis State University. Expert Systems with Applications, 4(2), 219-223. https://doi.org/10.1016/0957-4174(92)90113-7 DOI: https://doi.org/10.1016/0957-4174(92)90113-7

Berti, A. (2001). Contabilidade geral. São Paulo: Ícone.

Bradshaw, M. T., Christensen, T. E., Gee, K. H., & Whipple, B. C. (2018). Analysts’ GAAP earnings forecasts and their implications for accounting research. Journal of Accounting and Economics. https://doi.org/10.1016/j.jacceco.2018.01.003 DOI: https://doi.org/10.1016/j.jacceco.2018.01.003

Calof, J.L. and Wright, S. (2008), “Competitive intelligence: A practitioner, academic and inter‐disciplinary perspective”. European Journal of Marketing, 42(7/8), 717-730. https://doi.org/10.1108/03090560810877114 DOI: https://doi.org/10.1108/03090560810877114

Castanias, R. P., & Griffin, P. A. (1986). The effects of foreign‐currency translation accounting on security analysts’ forecasts. Managerial and Decision Economics, 7(1), 3-10. DOI: https://doi.org/10.1002/mde.4090070103

Chase, M. D., & Shim, J. K. (1991). Artificial intelligence and big six accounting: A survey of the current uses of expert systems in the modern accounting environment. Computers & industrial engineering, 21(1-4), 205-209. https://doi.org/10.1016/0360-8352(91)90089-O DOI: https://doi.org/10.1016/0360-8352(91)90089-O

Chen, A. Y., Comiskey, E. E., & Mulford, C. W. (1990). Foreign currency translation and analyst forecast dispersion: Examining the effects of statement of financial accounting standards no. 52. Journal of Accounting and Public Policy, 9(4), 239-256. https://doi.org/10.1016/0278-4254(90)90001-G DOI: https://doi.org/10.1016/0278-4254(90)90001-G

Cheng, Q. (2005). The role of analysts’ forecasts in accounting-based valuation: A critical evaluation. Review of Accounting Studies, 10(1), 5-31. https://doi.org/10.1007/s11142-004-6338-4 DOI: https://doi.org/10.1007/s11142-004-6338-4

Cho, J. S. (2013). The relation between accounting quality and security analysts’ target price forecast performance. Актуальні проблеми економіки, (3), 503-510.

Choi, K. S., Lee, S. J., Park, S. Y., & Yoo, Y. K. (2015). Accounting Conservatism, Changes in Real Investment, And Analysts’ Earnings Forecasts. Journal of Applied Business Research, 31(2), 727. https://doi.org/10.19030/jabr.v31i2.9163 DOI: https://doi.org/10.19030/jabr.v31i2.9163

Choo, C. W. (2002). Information management for the intelligent organization: the art of scanning the environment. Information Today, Inc.

D’Augusta, C. (2018). Does Accounting Conservatism Make Good News Forecasts More Credible and Bad News Forecasts Less Alarming? Journal of Accounting, Auditing & Finance. https://doi.org/10.1177%2F0148558X18780550

Davenport, T. H. (2000). Ecologia da informação: por que só a tecnologia não basta para o sucesso na era da informação. Futura.

Dorsman, A. B., Langendijk, H. P., & Praag, B. V. (2003). The association between qualitative management earnings forecasts and discretionary accounting in the Netherlands. The European Journal of Finance, 9(1), 19-40. https://doi.org/10.1080/13518470110099696 DOI: https://doi.org/10.1080/13518470110099696

Dull, RB, & Earp, J.B. (2000). Intelligent visualizations: Using artificial intelligence to improve accounting decisions. New Review of Applied Expert Systems and Emerging Technologies, 6.

Garvin, S.K., & Garvin, T.P. (1996). Considerations in the development of an environmental scanning system for the accounting academic department in an institution of higher education. Annual Meeting of the Decision Sciences Institute.

Gilad, B. (1989). The role of organized competitive intelligence in corporate-Strategy. Columbia Journal of World Business, 24(4), 29-35.

Glaum, M., Baetge, J., Grothe, A., & Oberdörster, T. (2013). Introduction of International Accounting Standards, disclosure quality and accuracy of analysts’ earnings forecasts. European Accounting Review, 22(1), 79-116. https://doi.org/10.1080/09638180.2011.558301 DOI: https://doi.org/10.1080/09638180.2011.558301

Grytz, R., & Krohn-Grimberghe, A. (2018, January). Business Intelligence & Analytics Cost Accounting: A Survey on the Perceptions of Stakeholders. In Proceedings of the 51st Hawaii International Conference on System Sciences. DOI: https://doi.org/10.24251/HICSS.2018.095

Hope, O. K. (2003a). Accounting policy disclosures and analysts’ forecasts. Contemporary Accounting Research, 20(2), 295-321. https://doi.org/10.1506/LA87-D1NF-BF06-FW1B DOI: https://doi.org/10.1506/LA87-D1NF-BF06-FW1B

Hope, O. K. (2003b). Disclosure practices, enforcement of accounting standards, and analysts’ forecast accuracy: An international study. Journal of accounting research, 41(2), 235-272. https://doi.org/10.1111/1475-679X.00102 DOI: https://doi.org/10.1111/1475-679X.00102

Horngren, C. T., Sundem, G. L., & Stratton, W. O. (2006). Contabilidade gerencial. 12. ed. São Paulo, Prentice Hall

Ionescu, I. (2012). The Newest Key to Unlock the Erp Systems “Accounting Intelligence”. AMIS 2012, 1243.

Ionescu, Luminita. (2019). Big data, blockchain, and artificial intelligence in cloud-based accounting information systems. Analysis and Metaphysics, 18, 44-49. https://doi.org/10.22381/AM1820196 DOI: https://doi.org/10.22381/AM1820196

Janissek-Muniz, R., & Blanck, M. R. de M. (2014). Weak signals management, entrepreneurship and uncertainty: a relational theoretical essay under the perspective of intelligence. 11º CONTECSI. DOI: https://doi.org/10.5748/9788599693100-11CONTECSI/COMM-625

Kalantari, B., Mehrmanesh, H., & Saeedi, N. (2012). Ranking the Driving Affecting Factors on Management Accounting: Business Intelligence Approach. World Appl. Sci. J, 20(8), 1147-1151. https://doi.org/10.5829/idosi.wasj.2012.20.08.2482

Kim, J. B. (2016). Accounting flexibility and managers’ forecast behavior prior to seasoned equity offerings. Review of Accounting Studies, 21(4), 1361-1400. https://doi.org/10.1007/s11142-016-9372-0 DOI: https://doi.org/10.1007/s11142-016-9372-0

Kocsis, D. (2019). A conceptual foundation of design and implementation research in accounting information systems. International Journal of Accounting Information Systems, 34. https://doi.org/10.1016/j.accinf.2019.06.003 DOI: https://doi.org/10.1016/j.accinf.2019.06.003

Kumar Doshi, Harisai Anil; Balasingam, Suresh; Arumugam, Dhamayanthi. Artificial Intelligence as a paradoxical Digital Disruptor in the Accounting Profession: An Empirical Study amongst Accountants. International Journal of Psychosocial Rehabilitation, 24(2), 2020. https://doi.org/10.37200/IJPR/V24I2/PR200396 DOI: https://doi.org/10.37200/IJPR/V24I2/PR200396

Lee, Cheah Saw; Tajudeen, Farzana Parveen. Impact of Artificial Intelligence on Accounting: Evidence from Malaysian Organizations. Asian Journal of Business and Accounting, 13(1). https://doi.org/10.22452/ajba.vol13no1.8 DOI: https://doi.org/10.22452/ajba.vol13no1.8

Lesca, H. (2003). Veille stratégique : La méthode L.E.SCAnning®, Editions EMS. 180 p.

Lesca H., & Janissek-Muniz, R. (2015). Inteligência Estratégica Antecipativa e Coletiva: o Método L.E.SCAnning. Porto Alegre: Palotti, p. 188.

Li, M., Ning, X., Li, M., & Xu, Y. (2017). An approach to the evaluation of the quality of accounting information based on relative entropy in fuzzy linguistic environments. Entropy, 19 (4). https://doi.org/10.3390/e19040152 DOI: https://doi.org/10.3390/e19040152

Liu, C., & O’Farrell, G. (2013). The role of accounting values in the relation between XBRL and forecast accuracy. International Journal of Accounting and Information Management, 21(4), 297-313. https://doi.org/10.1108/IJAIM-03-2013-0023 DOI: https://doi.org/10.1108/IJAIM-03-2013-0023

Lotka, Alfred J. (1926). The frequency distribution of scientific productivity. Journal of the Washington Academy of Sciences, 16(12), 317-323.

Madan, D. B. (1985). Project Evaluation and Accounting Income Forecasts. Abacus, 21(2), 197-202. DOI: https://doi.org/10.1111/j.1467-6281.1985.tb00119.x

Marconi, M.A., & Lakatos, E.M. (2003). Fundamentos de metodologia científica. 5. ed. São Paulo: Atlas.

Marek-Klimczak, K., & Szafranski, G. (2013). Coincident and forecast relevance of accounting numbers. Accounting Research Journal, 26(3), 239-255. https://doi.org/10.1108/ARJ-09-2012-0076 DOI: https://doi.org/10.1108/ARJ-09-2012-0076

Meservy, R. D., Denna, E. L., & Hansen, J. V. (1992). Application of artificial intelligence to accounting, tax, and audit services: Research at Brigham Young University. Expert Systems with Applications, 4(2), 213-218. https://doi.org/10.1016/0957-4174(92)90112-6 DOI: https://doi.org/10.1016/0957-4174(92)90112-6

Moreira, R. de L., Encarnação, L. V., Bispo, O. N. de A., Colauto, R. D., & Angotti, M. (2013). A importância da informação contábil no processo de tomada de decisão nas micro e pequenas empresas. Revista Contemporânea de Contabilidade, 10(19), 119-140. https://doi.org/10.5007/2175-8069.2013v10n19p119 DOI: https://doi.org/10.5007/2175-8069.2013v10n19p119

Muñoz, D. L. C. (2009) Estudos empíricos de gestão de conhecimento orientados para sustentabilidade: uma revisão sistemática de literatura de 1998 a 2009. 2009. 220 f. Dissertação (Programa de Pós-Graduação de Engenharia e Gestão de Conhecimento) – Universidade Federal de Santa Catarina (UFSC).

Neely, M. P., & Cook, J. S. (2011). Fifteen years of data and information quality literature: developing a research agenda for accounting. Journal of Information Systems, 25(1). https://doi.org/10.2308/jis.2011.25.1.79 DOI: https://doi.org/10.2308/jis.2011.25.1.79

Nespeca, A., & Chiucchi, M. S. (2018). The Impact of Business Intelligence Systems on Management Accounting Systems: The Consultant’s Perspective. In Network, Smart and Open (pp. 283-297). Springer, Cham. https://doi.org/10.1007/978-3-319-62636-9_19 DOI: https://doi.org/10.1007/978-3-319-62636-9_19

Newman, M. R., Gamble, G. O., Chin, W. W., & Murray, M. J. (2013). An Investigation of the Impact Publicly Available Accounting Data, Other Publicly Available Information and Management Guidance on Analysts’ Forecasts. In New Perspectives in Partial Least Squares and Related Methods (pp. 315-339). Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8283-3_22 DOI: https://doi.org/10.1007/978-1-4614-8283-3_22

O’leary, D. E. (1991). Artificial intelligence and expert systems in accounting databases: Survey and extensions. Expert Systems with Applications, 3(1), 143-152. https://doi.org/10.1016/0957-4174(91)90095-V DOI: https://doi.org/10.1016/0957-4174(91)90095-V

Olson, D., & Mossman, C. (2003). Neural network forecasts of Canadian stock returns using accounting ratios. International Journal of Forecasting, 19(3), 453-465. https://doi.org/10.1016/S0169-2070(02)00058-4 DOI: https://doi.org/10.1016/S0169-2070(02)00058-4

Pae, J., & Thornton, D. B. (2010). Association between accounting conservatism and analysts’ forecast inefficiency. Asia‐Pacific Journal of Financial Studies, 39(2), 171-197. https://doi.org/10.1111/j.2041-6156.2010.00008.x DOI: https://doi.org/10.1111/j.2041-6156.2010.00008.x

Patrascu, L., Ratiu, I. G., Paraschivescu, A. O., & Radu, F. (2010, January). Accounting forecast models and calculation. In Proceedings of the 4th WSEAS international conference on Computer engineering and applications (pp. 76-79). World Scientific and Engineering Academy and Society (WSEAS).

Pirttimäki, V. (2007). Comparative study and analysis of the intelligence activities of large Finnish companies. Journal of Competitive Intelligence and Management. http://urn.fi/URN:NBN:fi:tty-200810021126

Pope, P. F. (2003). Discussion of disclosure practices, enforcement of accounting standards, and analysts’ forecast accuracy: An international study. Journal of Accounting Research, 41(2), 273-283. http://www.jstor.org/stable/3542403 DOI: https://doi.org/10.1111/1475-679X.00103

Rezende, D. A. (2012) Planejamento de estratégias e informações municipais para cidade digital: guia para projetos em prefeituras e organizações públicas. São Paulo: Atlas.

Rikhardsson, P., & Yigitbasioglu, O. (2018). Business intelligence & analytics in management accounting research: Status and future focus. International Journal of Accounting Information Systems, 29, 37-58. https://doi.org/10.1016/j.accinf.2018.03.001 DOI: https://doi.org/10.1016/j.accinf.2018.03.001

Rios, F. L. C., & Janissek-Muniz, R. (2014). Uma proposta de relação de requisitos funcionais para um software de apoio ao processo de Inteligência. Revista Eletrônica de Administração, 20(2), 425-460. http://dx.doi.org/10.1590/1413-2311056201238165 DOI: https://doi.org/10.1590/1413-2311056201238165

Rogers, J. L., & Van Buskirk, A. (2013). Bundled forecasts in empirical accounting research. Journal of Accounting and Economics, 55(1), 43-65. https://doi.org/10.1016/j.jacceco.2012.06.001 DOI: https://doi.org/10.1016/j.jacceco.2012.06.001

Rousseau, B., & Rousseau, R. (2000). LOTKA: A program to fit a power law distribution to observed frequency data. Cybermetrics: International Journal of Scientometrics, Informetrics and Bibliometrics, (4), 4.

Sabau, E.M., Sgardea, F.M., Budacia, L.C.G., & Paunescu, M. (2009). The Accounting Information - Tool for Competitive Intelligence Systems. Proceedings of the 4th International Conference on Business Excellence.

Schoemaker, P. J., & Day, G. S. (2009). How to make sense of weak signals. Leading Organizations: Perspectives for a New Era, 2, 37-47.

Smieliauskas, W., Bewley, K., Gronewold, U., & Menzefricke, U. (2016). Misleading Forecasts in Accounting Estimates: A Form of Ethical Blindness in Accounting Standards? Journal of Business Ethics, 1-21. https://doi.org/10.1007/s10551-016-3289-1 DOI: https://doi.org/10.1007/s10551-016-3289-1

Sohn, B. C. (2012). Analyst forecast, accounting conservatism and the related valuation implications. Accounting & Finance, 52, 311-341. https://doi.org/10.1111/j.1467-629X.2011.00428.x DOI: https://doi.org/10.1111/j.1467-629X.2011.00428.x

Sun, Y., & Xu, W. (2012). The role of accounting conservatism in management forecast bias. Journal of Contemporary Accounting & Economics, 8(2), 64-77. https://doi.org/10.1016/j.jcae.2012.05.002 DOI: https://doi.org/10.1016/j.jcae.2012.05.002

Sutton, S. G., Holt, M., & Arnold, V. (2016). “The reports of my death are greatly exaggerated” - Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60-73. https://doi.org/10.1016/j.accinf.2016.07.005 DOI: https://doi.org/10.1016/j.accinf.2016.07.005

Valente, N. T. Z., & Fujino, A. (2016). Atributos e dimensões de qualidade da informação nas Ciências Contábeis e na Ciência da Informação: um estudo comparativo. Perspectivas em Ciência da Informação, 21(2). https://doi.org/10.1590/1981-5344/2530 DOI: https://doi.org/10.1590/1981-5344/2530

Varum, C. A., & Melo, C. (2010). Directions in scenario planning literature–A review of the past decades. Futures, 42(4), 355-369. https://doi.org/10.1016/j.futures.2009.11.021 DOI: https://doi.org/10.1016/j.futures.2009.11.021

Vidigal, F. (2013). Competitive intelligence: functional practices, goals and infrastructure of companies in Brazil. Transinformação, 25(3), 237-243. DOI: https://doi.org/10.1590/S0103-37862013000300006

Xu, M., & Kaye, R. (2007). The nature of strategic intelligence, current practice and solutions. In Managing Strategic Intelligence: Techniques and Technologies (pp. 36-54). IGI Global. DOI: https://doi.org/10.4018/978-1-59904-243-5.ch003

Wahab, S., Teitel, K., & Morzuch, B. (2017). How Analysts and Whisperers Use Fundamental Accounting Signals to Make Quarterly EPS Forecasts. Journal of Accounting, Auditing & Finance, 32(3), 401-422. https://doi.org/10.1177%2F0148558X15613040 DOI: https://doi.org/10.1177/0148558X15613040

Ye, S. (2017). 29. Research on the Enterprise Accounting Statement Evaluation and Financial Management Optimization based on Computer Artificial Intelligence Method. Boletín Técnico, 55(20). DOI: https://doi.org/10.1108/JPBAFM-29-01-2017-B002

Zhai, J., & Wang, Y. (2016). Accounting information quality, governance efficiency and capital investment choice. China Journal of Accounting Research, 9(4). https://doi.org/10.1016/j.cjar.2016.08.001 DOI: https://doi.org/10.1016/j.cjar.2016.08.001

Zhang, Yingying et al. (2020). The Impact of Artificial Intelligence and Blockchain on the Accounting Profession. IEEE Access, 8,110461-110477. https://doi.org/10.1109/ACCESS.2020.3000505 DOI: https://doi.org/10.1109/ACCESS.2020.3000505

Published

2021-12-30

How to Cite

da Silva Momo, F., Melati, C., Janissek-Muniz, R., & Behr, A. (2021). Relationships between accounting and intelligence: research paths. Journal of Accounting, Management and Governance, 24(3), 274–292. https://doi.org/10.51341/1984-3925_2021v24n3a2

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Section

Scientific Article (Private and Third Sector Management & Accounting)