{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,21]],"date-time":"2025-12-21T15:15:37Z","timestamp":1766330137043,"version":"3.37.3"},"reference-count":80,"publisher":"American Accounting Association","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,6,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n               <jats:p>This paper considers the use of neural networks\u2014namely self-organizing maps (SOMs)\u2014to analyze and cluster firms' financial performance. Applying SOMs to financial statement data is a consolidated practice; however, in this paper SOMs are used to overcome several limitations encountered in previous works on financial reporting indicators such as the small number of companies in the sample, the limited number of ratios, the homogeneity of the economic sector, and the lack of explanation and further analysis of the SOM outputs. This study uses a large financial dataset related to more than 3,000 companies belonging to every economic sector; it demonstrates that SOMs can effectively process a large dataset of heterogeneous data. Moreover, the SOM results are supported by detailed explanations of the research methodology applied, and further traditional financial analysis addresses the black box nature of the SOMs and can help professionals in the understanding and use of SOMs.<\/jats:p>","DOI":"10.2308\/isys-18-002","type":"journal-article","created":{"date-parts":[[2020,1,29]],"date-time":"2020-01-29T16:50:48Z","timestamp":1580316648000},"page":"149-166","source":"Crossref","is-referenced-by-count":10,"title":["Neural Networks in Accounting: Clustering Firm Performance Using Financial Reporting Data"],"prefix":"10.2308","volume":"34","author":[{"given":"Renata Paola","family":"Dameri","sequence":"first","affiliation":[{"name":"University of Genoa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0001-116X","authenticated-orcid":true,"given":"Roberto","family":"Garelli","sequence":"additional","affiliation":[{"name":"University of Genoa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marina","family":"Resta","sequence":"additional","affiliation":[{"name":"University of Genoa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1112","published-online":{"date-parts":[[2020,1,29]]},"reference":[{"key":"2024082915335961300_i1558-7959-34-2-149-AlfaroCid1","doi-asserted-by":"crossref","unstructured":"Alfaro-Cid,\n              E.,\n            \n            \n              Mora\n              A. M.,\n            \n            \n              Merelo\n              J. J.,\n            \n            \n              Esparcia-Alc\u00e1zar\n              A. I.,\n             and\n\t\t\t\t\t\tSharmanK.\n          2009.\n\t\t\t\t\tFinding relevant variables in a financial distress prediction problem using genetic programming and self-organizing maps.\n\t\t\t\t\tInNatural Computing in Computational Finance,\n\t\t\t\t\t31\u201349.\n\t\t\t\t\tBerlin, Germany:\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-3-540-95974-8_3"},{"key":"2024082915335961300_i1558-7959-34-2-149-Alpar1","doi-asserted-by":"crossref","unstructured":"Alpar,\n              P.,\n             and\n\t\t\t\t\t\tWinkelstr\u00e4terS.\n          2014.\n\t\t\t\t\tAssessment of data quality in accounting data with association rules.\n\t\t\t\t\tExpert Systems with Applications41\n\t\t\t\t\t(5):\n\t\t\t\t\t2259\u20132268.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2013.09.024","DOI":"10.1016\/j.eswa.2013.09.024"},{"key":"2024082915335961300_i1558-7959-34-2-149-Altman1","doi-asserted-by":"crossref","unstructured":"Altman,\n              E. I.,\n            \n            \n              Marco\n              G.,\n             and\n\t\t\t\t\t\tVarettoF.\n          1994.\n\t\t\t\t\tCorporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience).\n\t\t\t\t\tJournal of Banking & Finance18\n\t\t\t\t\t(3):\n\t\t\t\t\t505\u2013529.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/0378-4266(94)90007-8","DOI":"10.1016\/0378-4266(94)90007-8"},{"key":"2024082915335961300_i1558-7959-34-2-149-Amani1","doi-asserted-by":"crossref","unstructured":"Amani,\n              F. A.,\n             and\n\t\t\t\t\t\tFadlallaA. M.\n          2017.\n\t\t\t\t\tData mining applications in accounting: A review of the literature and organizing framework.\n\t\t\t\t\tInternational Journal of Accounting Information Systems24:\n\t\t\t\t\t32\u201358.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.accinf.2016.12.004","DOI":"10.1016\/j.accinf.2016.12.004"},{"key":"2024082915335961300_i1558-7959-34-2-149-Amin1","doi-asserted-by":"crossref","unstructured":"Amin,\n              A.,\n             and\n\t\t\t\t\t\tWilkinsonF.\n          1999.\n\t\t\t\t\tLearning, proximity and industrial performance: An introduction.\n\t\t\t\t\tCambridge Journal of Economics23\n\t\t\t\t\t(2):\n\t\t\t\t\t121\u2013125.\n\t\t\t\t\thttps:\/\/doi.org\/10.1093\/cje\/23.2.121","DOI":"10.1093\/cje\/23.2.121"},{"key":"2024082915335961300_i1558-7959-34-2-149-Back1","doi-asserted-by":"crossref","unstructured":"Back,\n              B.,\n            \n            \n              Sere\n              K.,\n             and\n\t\t\t\t\t\tVanharantaH.\n          1998.\n\t\t\t\t\tManaging complexity in large data bases using self-organizing maps.\n\t\t\t\t\tAccounting, Management and Information Technologies8\n\t\t\t\t\t(4):\n\t\t\t\t\t191\u2013210.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/S0959-8022(98)00009-5","DOI":"10.1016\/S0959-8022(98)00009-5"},{"key":"2024082915335961300_i1558-7959-34-2-149-Back2","doi-asserted-by":"crossref","unstructured":"Back,\n              B.,\n            \n            \n              Toivonen\n              J.,\n            \n            \n              Vanharanta\n              H.,\n             and\n\t\t\t\t\t\tVisaA.\n          2001.\n\t\t\t\t\tComparing numerical data and text information from annual reports using self-organizing maps.\n\t\t\t\t\tInternational Journal of Accounting Information Systems2\n\t\t\t\t\t(4):\n\t\t\t\t\t249\u2013269.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/S1467-0895(01)00018-5","DOI":"10.1016\/S1467-0895(01)00018-5"},{"key":"2024082915335961300_i1558-7959-34-2-149-Biscontri1","doi-asserted-by":"crossref","unstructured":"Biscontri,\n              R.,\n             and\n\t\t\t\t\t\tParkK.\n          2000.\n\t\t\t\t\tAn empirical evidence of the financial performance of lean production adoption: A self-organizing neural networks approach.\n\t\t\t\t\tAvailable at: https:\/\/ieeexplore.ieee.org\/document\/861477","DOI":"10.1109\/IJCNN.2000.861477"},{"key":"2024082915335961300_i1558-7959-34-2-149-Bishop1","doi-asserted-by":"crossref","unstructured":"Bishop\n              C.\n            \n          \n          ,\n          \n            \n              Svens\u00e9n\n              M.,\n             and\n\t\t\t\t\t\tWilliamsC.\n          1996.\n\t\t\t\t\tGTM: A principled alternative to the self-organizing map.\n\t\t\t\t\tAvailable at: https:\/\/link.springer.com\/chapter\/10.1007\/3-540-61510-5_31","DOI":"10.1007\/3-540-61510-5_31"},{"key":"2024082915335961300_i1558-7959-34-2-149-Brown1","doi-asserted-by":"crossref","unstructured":"Brown,\n              C. E.\n            \n          \n          1991.\n\t\t\t\t\tExpert systems in public accounting: Current practice and future directions.\n\t\t\t\t\tExpert Systems with Applications3\n\t\t\t\t\t(1):\n\t\t\t\t\t3\u201318.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/0957-4174(91)90084-R","DOI":"10.1016\/0957-4174(91)90084-R"},{"key":"2024082915335961300_i1558-7959-34-2-149-Budayan1","doi-asserted-by":"crossref","unstructured":"Budayan,\n              C.,\n            \n            \n              Dikmen\n              I.,\n             and\n\t\t\t\t\t\tBirgonulM. T.\n          2009.\n\t\t\t\t\tComparing the performance of traditional cluster analysis, self-organizing maps and fuzzy C-means method for strategic grouping.\n\t\t\t\t\tExpert Systems with Applications36\n\t\t\t\t\t(9):\n\t\t\t\t\t11772\u201311781.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2009.04.022","DOI":"10.1016\/j.eswa.2009.04.022"},{"key":"2024082915335961300_i1558-7959-34-2-149-Burrell1","doi-asserted-by":"crossref","unstructured":"Burrell,\n              J.\n            \n          \n          2016.\n\t\t\t\t\tHow the machine \u201cthinks\u201d: Understanding opacity in machine learning algorithms.\n\t\t\t\t\tBig Data & Society3\n\t\t\t\t\t(1):\n\t\t\t\t\t1\u201312.\n\t\t\t\t\thttps:\/\/doi.org\/10.1177\/2053951715622512","DOI":"10.1177\/2053951715622512"},{"key":"2024082915335961300_i1558-7959-34-2-149-CharteredGlobalManagementAccountantCGMA1","unstructured":"Chartered Global Management Accountant (CGMA).\n\t\t\t\t\t2013.\n\t\t\t\t\tFrom insight to impact: Unlocking opportunities in Big Data.\n\t\t\t\t\tAvailable at: https:\/\/www.cgma.org\/resources\/reports\/downloadabledocuments\/from-insight-to-impact-unlocking-the-opportunities-in-big-data.pdf"},{"key":"2024082915335961300_i1558-7959-34-2-149-Chatfield1","doi-asserted-by":"crossref","unstructured":"Chatfield,\n              C.\n            \n          \n          1985.\n\t\t\t\t\tThe initial examination of data.\n\t\t\t\t\tJournal of the Royal Statistical Society. Series A (General)148\n\t\t\t\t\t(3):\n\t\t\t\t\t214\u2013253.\n\t\t\t\t\thttps:\/\/doi.org\/10.2307\/2981969","DOI":"10.2307\/2981969"},{"key":"2024082915335961300_i1558-7959-34-2-149-Chen1","doi-asserted-by":"crossref","unstructured":"Chen,\n              K. H.,\n             and\n\t\t\t\t\t\tShimerdaT. A.\n          1981.\n\t\t\t\t\tAn empirical analysis of useful financial ratios.\n\t\t\t\t\tFinancial Management10\n\t\t\t\t\t(1):\n\t\t\t\t\t51\u201360.\n\t\t\t\t\thttps:\/\/doi.org\/10.2307\/3665113","DOI":"10.2307\/3665113"},{"key":"2024082915335961300_i1558-7959-34-2-149-ChungFernWu1","doi-asserted-by":"crossref","unstructured":"Chung-Fern Wu,\n              R.\n            \n          \n          1994.\n\t\t\t\t\tIntegrating neurocomputing and auditing expertise.\n\t\t\t\t\tManagerial Auditing Journal9\n\t\t\t\t\t(3):\n\t\t\t\t\t20\u201326.\n\t\t\t\t\thttps:\/\/doi.org\/10.1108\/02686909410054745","DOI":"10.1108\/02686909410054745"},{"key":"2024082915335961300_i1558-7959-34-2-149-Cil1","doi-asserted-by":"crossref","unstructured":"Cil,\n              I.\n            \n          \n          2012.\n\t\t\t\t\tConsumption universes based supermarket layout through association rule mining and multidimensional scaling.\n\t\t\t\t\tExpert Systems with Applications39\n\t\t\t\t\t(10):\n\t\t\t\t\t8611\u20138625.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2012.01.192","DOI":"10.1016\/j.eswa.2012.01.192"},{"key":"2024082915335961300_i1558-7959-34-2-149-Cottrell1","doi-asserted-by":"crossref","unstructured":"Cottrell,\n              M.,\n            \n            \n              de Bodt\n              E.,\n             and\n\t\t\t\t\t\tVerleysenM.\n          2001.\n\t\t\t\t\tA statistical tool to assess the reliability of self-organizing maps.\n\t\t\t\t\tInAdvances in Self-Organising Maps,\n\t\t\t\t\t7\u201314.\n\t\t\t\t\tLondon, U.K.:\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-1-4471-0715-6_2"},{"key":"2024082915335961300_i1558-7959-34-2-149-Curry1","doi-asserted-by":"crossref","unstructured":"Curry,\n              B.,\n            \n            \n              Davies\n              F.,\n            \n            \n              Phillips\n              P.,\n            \n            \n              Evans\n              M.,\n             and\n\t\t\t\t\t\tMoutinhoL.\n          2001.\n\t\t\t\t\tThe Kohonen self-organizing map: An application to the study of strategic groups in the U.K. hotel industry.\n\t\t\t\t\tExpert Systems: International Journal of Knowledge Engineering and Neural Networks18\n\t\t\t\t\t(1):\n\t\t\t\t\t19\u201331.\n\t\t\t\t\thttps:\/\/doi.org\/10.1111\/1468-0394.00152","DOI":"10.1111\/1468-0394.00152"},{"key":"2024082915335961300_i1558-7959-34-2-149-Dameri1","doi-asserted-by":"crossref","unstructured":"Dameri,\n              R. P.,\n            \n            \n              Garelli\n              R.,\n             and\n\t\t\t\t\t\tRestaM.\n          2016.\n\t\t\t\t\tUnsupervised neural networks for the analysis of business performance at infra-city level.\n\t\t\t\t\tInOrganizational Innovation and Change,\n\t\t\t\t\t203\u2013215.\n\t\t\t\t\tCham, Switzerland:\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-3-319-22921-8_16"},{"key":"2024082915335961300_i1558-7959-34-2-149-Deng1","doi-asserted-by":"crossref","unstructured":"Deng,\n              Q.,\n             and\n\t\t\t\t\t\tMeiG.\n          2009.\n\t\t\t\t\tCombining self-organizing map and K-means clustering for detecting fraudulent financial statements.\n\t\t\t\t\tAvailable at: https:\/\/ieeexplore.ieee.org\/abstract\/document\/5255148","DOI":"10.1109\/GRC.2009.5255148"},{"key":"2024082915335961300_i1558-7959-34-2-149-diTollo1","doi-asserted-by":"crossref","unstructured":"di Tollo,\n              G.,\n            \n            \n              Tanev\n              S.,\n            \n            \n              Davide\n              D. M.,\n             and\n\t\t\t\t\t\tMaZ.\n          2012.\n\t\t\t\t\tNeural networks to model the innovativeness perception of co-creative firms.\n\t\t\t\t\tExpert Systems with Applications39\n\t\t\t\t\t(16):\n\t\t\t\t\t12719\u201312726.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2012.05.022","DOI":"10.1016\/j.eswa.2012.05.022"},{"key":"2024082915335961300_i1558-7959-34-2-149-Eklund1","doi-asserted-by":"crossref","unstructured":"Eklund,\n              T.,\n            \n            \n              Back\n              B.,\n            \n            \n              Vanharanta\n              H.,\n             and\n\t\t\t\t\t\tVisaA.\n          2003.\n\t\t\t\t\tUsing the self-organizing map as a visualization tool in financial benchmarking.\n\t\t\t\t\tInformation Visualization2\n\t\t\t\t\t(3):\n\t\t\t\t\t171\u2013181.\n\t\t\t\t\thttps:\/\/doi.org\/10.1057\/palgrave.ivs.9500048","DOI":"10.1057\/palgrave.ivs.9500048"},{"key":"2024082915335961300_i1558-7959-34-2-149-Eklund2","doi-asserted-by":"crossref","unstructured":"Eklund,\n              T.,\n            \n            \n              Back\n              B.,\n            \n            \n              Vanharanta\n              H.,\n             and\n\t\t\t\t\t\tVisaA.\n          2008.\n\t\t\t\t\tA face validation of a SOM-based financial benchmarking model.\n\t\t\t\t\tJournal of Emerging Technologies in Accounting5\n\t\t\t\t\t(1):\n\t\t\t\t\t109\u2013127.\n\t\t\t\t\thttps:\/\/doi.org\/10.2308\/jeta.2008.5.1.109","DOI":"10.2308\/jeta.2008.5.1.109"},{"key":"2024082915335961300_i1558-7959-34-2-149-Fanning1","doi-asserted-by":"crossref","unstructured":"Fanning,\n              K.,\n             and\n\t\t\t\t\t\tCoggerK. O.\n          1998.\n\t\t\t\t\tNeural network detection of management fraud using published financial data.\n\t\t\t\t\tInternational Journal of Intelligent Systems in Accounting Finance & Management7\n\t\t\t\t\t(1):\n\t\t\t\t\t21\u201341.\n\t\t\t\t\thttps:\/\/doi.org\/10.1002\/(SICI)1099-1174(199803)7:1&lt;21:AID-ISAF138&gt;3.0.CO;2-K","DOI":"10.1002\/(SICI)1099-1174(199803)7:1<21::AID-ISAF138>3.0.CO;2-K"},{"key":"2024082915335961300_i1558-7959-34-2-149-Feng1","doi-asserted-by":"crossref","unstructured":"Feng,\n              C.,\n             and\n\t\t\t\t\t\tWangR.\n          2000.\n\t\t\t\t\tPerformance evaluation for airlines including the consideration of financial ratios.\n\t\t\t\t\tJournal of Air Transport Management6\n\t\t\t\t\t(3):\n\t\t\t\t\t133\u2013142.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/S0969-6997(00)00003-X","DOI":"10.1016\/S0969-6997(00)00003-X"},{"key":"2024082915335961300_i1558-7959-34-2-149-Folta1","doi-asserted-by":"crossref","unstructured":"Folta,\n              T. B.,\n            \n            \n              Cooper\n              A. C.,\n             and\n\t\t\t\t\t\tBaikY. S.\n          2006.\n\t\t\t\t\tGeographic cluster size and firm performance.\n\t\t\t\t\tJournal of Business Venturing21\n\t\t\t\t\t(2):\n\t\t\t\t\t217\u2013242.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.jbusvent.2005.04.005","DOI":"10.1016\/j.jbusvent.2005.04.005"},{"key":"2024082915335961300_i1558-7959-34-2-149-Foltin1","unstructured":"Foltin,\n              C.,\n             and\n\t\t\t\t\t\tGarceauL.\n          1996.\n\t\t\t\t\tBeyond expert systems: Neural networks in accounting.\n\t\t\t\t\tNational Public Accountant41\n\t\t\t\t\t(6):\n\t\t\t\t\t26\u201332."},{"key":"2024082915335961300_i1558-7959-34-2-149-Franklin1","doi-asserted-by":"crossref","unstructured":"Franklin,\n              J.\n            \n          \n          2005.\n\t\t\t\t\tThe elements of statistical learning: Data mining, inference and prediction.\n\t\t\t\t\tThe Mathematical Intelligencer27\n\t\t\t\t\t(2):\n\t\t\t\t\t83\u201385.\n\t\t\t\t\thttps:\/\/doi.org\/10.1007\/BF02985802","DOI":"10.1007\/BF02985802"},{"key":"2024082915335961300_i1558-7959-34-2-149-Gombola1","unstructured":"Gombola,\n              J.,\n             and\n\t\t\t\t\t\tKetzJ. E. .\n\t\t\t\t\t\n          Jan.\n          1983.\n\t\t\t\t\tA note on cash flow and classification patterns of financial ratios.\n\t\t\t\t\tThe Accounting Review58\n\t\t\t\t\t(1):\n\t\t\t\t\t105\u2013114."},{"key":"2024082915335961300_i1558-7959-34-2-149-Haga1","doi-asserted-by":"crossref","unstructured":"Haga,\n              J.,\n            \n            \n              Siekkinen\n              J.,\n             and\n\t\t\t\t\t\tSundvikD.\n          2015.\n\t\t\t\t\tInitial stage clustering when estimating accounting quality measures with self-organizing maps.\n\t\t\t\t\tExpert Systems with Applications42\n\t\t\t\t\t(21):\n\t\t\t\t\t8327\u20138336.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2015.06.049","DOI":"10.1016\/j.eswa.2015.06.049"},{"key":"2024082915335961300_i1558-7959-34-2-149-Hansen1","doi-asserted-by":"crossref","unstructured":"Hansen,\n              J. V.,\n             and\n\t\t\t\t\t\tMessier,W. F.Jr.\n\t\t\t\t\t\n          1991.\n\t\t\t\t\tArtificial neural networks: Foundations and application to a decision problem.\n\t\t\t\t\tExpert Systems with Applications3\n\t\t\t\t\t(1):\n\t\t\t\t\t135\u2013141.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/0957-4174(91)90094-U","DOI":"10.1016\/0957-4174(91)90094-U"},{"key":"2024082915335961300_i1558-7959-34-2-149-Huang1","doi-asserted-by":"crossref","unstructured":"Huang,\n              S. Y.,\n            \n            \n              Tsaih\n              R. H.,\n             and\n\t\t\t\t\t\tLinW. Y.\n          2012.\n\t\t\t\t\tUnsupervised neural networks approach for understanding fraudulent financial reporting.\n\t\t\t\t\tIndustrial Management & Data Systems112\n\t\t\t\t\t(2):\n\t\t\t\t\t224\u2013244.\n\t\t\t\t\thttps:\/\/doi.org\/10.1108\/02635571211204272","DOI":"10.1108\/02635571211204272"},{"key":"2024082915335961300_i1558-7959-34-2-149-Kangas1","doi-asserted-by":"crossref","unstructured":"Kangas,\n              Y.,\n            \n            \n              Kohonen\n              T.,\n             and\n\t\t\t\t\t\tLaaksonenJ. T.\n          1990.\n\t\t\t\t\tVariants on self organizing maps.\n\t\t\t\t\tIEEE Transactions on Neural Networks1\n\t\t\t\t\t(1):\n\t\t\t\t\t93\u201399.\n\t\t\t\t\thttps:\/\/doi.org\/10.1109\/72.80208","DOI":"10.1109\/72.80208"},{"key":"2024082915335961300_i1558-7959-34-2-149-Karlsson1","unstructured":"Karlsson,\n              J.,\n            \n            \n              Back\n              B.,\n            \n            \n              Vanharanta\n              H.,\n             and\n\t\t\t\t\t\tVisaA.\n          2001.\n\t\t\t\t\tFinancial benchmarking of telecommunications companies.\n\t\t\t\t\tTurku:\n\t\t\t\t\tTurku Centre for Computer Science."},{"key":"2024082915335961300_i1558-7959-34-2-149-Kim1","doi-asserted-by":"crossref","unstructured":"Kim,\n              H. J.,\n            \n            \n              Mannino\n              M.,\n             and\n\t\t\t\t\t\tNieschwietzR. J.\n          2009.\n\t\t\t\t\tInformation technology acceptance in the internal audit profession: Impact of technology features and complexity.\n\t\t\t\t\tInternational Journal of Accounting Information Systems10\n\t\t\t\t\t(4):\n\t\t\t\t\t214\u2013228.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.accinf.2009.09.001","DOI":"10.1016\/j.accinf.2009.09.001"},{"key":"2024082915335961300_i1558-7959-34-2-149-Kirkos1","doi-asserted-by":"crossref","unstructured":"Kirkos,\n              E.,\n            \n            \n              Spathis\n              C.,\n             and\n\t\t\t\t\t\tManolopoulosY.\n          2007.\n\t\t\t\t\tData mining techniques for the detection of fraudulent financial statements.\n\t\t\t\t\tExpert Systems with Applications32\n\t\t\t\t\t(4):\n\t\t\t\t\t995\u20131003.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2006.02.016","DOI":"10.1016\/j.eswa.2006.02.016"},{"key":"2024082915335961300_i1558-7959-34-2-149-Kiviluoto1","unstructured":"Kiviluoto,\n              K.\n            \n          \n          1998.\n\t\t\t\t\tTwo-level self-organizing maps for analysis of financial statements.\n\t\t\t\t\tAvailable at: https:\/\/ieeexplore.ieee.org\/document\/682260"},{"key":"2024082915335961300_i1558-7959-34-2-149-Kiviluoto2","doi-asserted-by":"crossref","unstructured":"Kiviluoto,\n              K.,\n             and\n\t\t\t\t\t\tBergiusP.\n          1998.\n\t\t\t\t\tMaps for analysing failures of small and medium-size enterprises.\n\t\t\t\t\tInVisual Explorations in Finance: with Self-Organizing Maps,\n\t\t\t\t\tedited byDeboekG. and\n\t\t\t\t\t\tKohonenT. .\n\t\t\t\t\tBerlin, Germany:\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-1-4471-3913-3_4"},{"key":"2024082915335961300_i1558-7959-34-2-149-Kloptchenko1","doi-asserted-by":"crossref","unstructured":"Kloptchenko,\n              A.,\n            \n            \n              Eklund\n              T.,\n            \n            \n              Karlsson\n              J.,\n            \n            \n              Back\n              B.,\n            \n            \n              Vanharanta\n              H.,\n             and\n\t\t\t\t\t\tVisaA.\n          2004.\n\t\t\t\t\tCombining data and text mining techniques for analysing financial reports.\n\t\t\t\t\tIntelligent Systems in Accounting, Finance & Management12\n\t\t\t\t\t(1):\n\t\t\t\t\t29\u201341.\n\t\t\t\t\thttps:\/\/doi.org\/10.1002\/isaf.239","DOI":"10.1002\/isaf.239"},{"key":"2024082915335961300_i1558-7959-34-2-149-Kohonen1","doi-asserted-by":"crossref","unstructured":"Kohonen,\n              T.\n            \n          \n          1982.\n\t\t\t\t\tSelf-organized formation of topologically correct feature maps.\n\t\t\t\t\tBiological Cybernetics43\n\t\t\t\t\t(1):\n\t\t\t\t\t59\u201369.\n\t\t\t\t\thttps:\/\/doi.org\/10.1007\/BF00337288","DOI":"10.1007\/BF00337288"},{"key":"2024082915335961300_i1558-7959-34-2-149-Kohonen2","doi-asserted-by":"crossref","unstructured":"Kohonen,\n              T.\n            \n          \n          1995.\n\t\t\t\t\tLearning vector quantization.\n\t\t\t\t\tInSelf-Organizing Maps,\n\t\t\t\t\t175\u2013189.\n\t\t\t\t\tBerlin, Germany:\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-3-642-97610-0_6"},{"key":"2024082915335961300_i1558-7959-34-2-149-Kohonen3","doi-asserted-by":"crossref","unstructured":"Kohonen,\n              T.\n            \n          \n          1997.\n\t\t\t\t\tSelf-Organizing Maps.\n\t\t\t\t\t2nd edition.\n\t\t\t\t\tBerlin, Germany:\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-3-642-97966-8"},{"key":"2024082915335961300_i1558-7959-34-2-149-Koskivaara1","doi-asserted-by":"crossref","unstructured":"Koskivaara,\n              E.\n            \n          \n          2004.\n\t\t\t\t\tArtificial neural networks in analytical review procedures.\n\t\t\t\t\tManagerial Auditing Journal19\n\t\t\t\t\t(2):\n\t\t\t\t\t191\u2013223.\n\t\t\t\t\thttps:\/\/doi.org\/10.1108\/02686900410517821","DOI":"10.1108\/02686900410517821"},{"key":"2024082915335961300_i1558-7959-34-2-149-Koyuncugil1","doi-asserted-by":"crossref","unstructured":"Koyuncugil,\n              A. S.,\n             and\n\t\t\t\t\t\tOzgulbasN.\n          2012.\n\t\t\t\t\tFinancial early warning system model and data mining application for risk detection.\n\t\t\t\t\tExpert Systems with Applications39\n\t\t\t\t\t(6):\n\t\t\t\t\t6238\u20136253.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2011.12.021","DOI":"10.1016\/j.eswa.2011.12.021"},{"key":"2024082915335961300_i1558-7959-34-2-149-Lan1","unstructured":"Lan,\n              J.\n            \n          \n          2012.\n\t\t\t\t\t16 financial ratios for analysing a company's strengths and weaknesses.\n\t\t\t\t\tAAII Journal\n\t\t\t\t\t(September)."},{"key":"2024082915335961300_i1558-7959-34-2-149-Langen1","doi-asserted-by":"crossref","unstructured":"Langen,\n              P. D.\n            \n          \n          2002.\n\t\t\t\t\tClustering and performance: The case of maritime clustering in The Netherlands.\n\t\t\t\t\tMaritime Policy & Management29\n\t\t\t\t\t(3):\n\t\t\t\t\t209\u2013221.\n\t\t\t\t\thttps:\/\/doi.org\/10.1080\/03088830210132605","DOI":"10.1080\/03088830210132605"},{"key":"2024082915335961300_i1558-7959-34-2-149-Lee1","doi-asserted-by":"crossref","unstructured":"Lee,\n              K.,\n            \n            \n              Booth\n              D.,\n             and\n\t\t\t\t\t\tAlamP.\n          2005.\n\t\t\t\t\tA comparison of supervised and unsupervised neural networks in predicting bankruptcy of Korean firms.\n\t\t\t\t\tExpert Systems with Applications29\n\t\t\t\t\t(1):\n\t\t\t\t\t1\u201316.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2005.01.004","DOI":"10.1016\/j.eswa.2005.01.004"},{"key":"2024082915335961300_i1558-7959-34-2-149-Li1","doi-asserted-by":"crossref","unstructured":"Li,\n              S. G.,\n             and\n\t\t\t\t\t\tKuoX.\n          2008.\n\t\t\t\t\tThe inventory management system for automobile spare parts in a central warehouse.\n\t\t\t\t\tExpert Systems with Applications34\n\t\t\t\t\t(2):\n\t\t\t\t\t1144\u20131153.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.eswa.2006.12.003","DOI":"10.1016\/j.eswa.2006.12.003"},{"key":"2024082915335961300_i1558-7959-34-2-149-Liao1","doi-asserted-by":"crossref","unstructured":"Liao,\n              S. H.,\n             and\n\t\t\t\t\t\tChenY. J.\n          2014.\n\t\t\t\t\tA rough set-based association rule approach implemented on exploring beverages product spectrum.\n\t\t\t\t\tApplied Intelligence40\n\t\t\t\t\t(3):\n\t\t\t\t\t464\u2013478.\n\t\t\t\t\thttps:\/\/doi.org\/10.1007\/s10489-013-0465-1","DOI":"10.1007\/s10489-013-0465-1"},{"key":"2024082915335961300_i1558-7959-34-2-149-Lionzo1","unstructured":"Lionzo,\n              A.\n            \n          \n          2010.\n\t\t\t\t\tL'analisi di fenomeni complessi negli studi di strategia aziendale. L'algoritmo SOM applicato allo studio dei percorsi di crescita e di svilupo delle imprese.\n\t\t\t\t\tInEconomia Aziendale & Management. Scritti in onore di Vittorio Coda.\n\t\t\t\t\tMilano, Italy:\n\t\t\t\t\tEGEA."},{"key":"2024082915335961300_i1558-7959-34-2-149-Liou1","doi-asserted-by":"crossref","unstructured":"Liou,\n              F. M.\n            \n          \n          2008.\n\t\t\t\t\tFraudulent financial reporting detection and business failure prediction models: A comparison.\n\t\t\t\t\tManagerial Auditing Journal23\n\t\t\t\t\t(7):\n\t\t\t\t\t650\u2013662.\n\t\t\t\t\thttps:\/\/doi.org\/10.1108\/02686900810890625","DOI":"10.1108\/02686900810890625"},{"key":"2024082915335961300_i1558-7959-34-2-149-Little1","unstructured":"Little,\n              E.,\n            \n            \n              Hickey\n              R.,\n             and\n\t\t\t\t\t\tBrabazonA.\n          2006.\n\t\t\t\t\tIdentifying merger and takeover targets using a self-organising map.\n\t\t\t\t\tAvailable at: http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.83.7605&rep=rep1&type=pdf"},{"key":"2024082915335961300_i1558-7959-34-2-149-Marghescu1","unstructured":"Marghescu,\n              D.\n            \n          \n          2007.\n\t\t\t\t\tMultidimensional data visualization techniques for financial performance data: A review.\n\t\t\t\t\tAvailable at: https:\/\/www.researchgate.net\/profile\/Dorina_Rajanen_marghescu\/publication\/31597178_Multidimensional_Data_Visualization_Techniques_for_Financial_Performance_Data_A_Review\/links\/53ee4bac0cf23733e80bcf99.pdf"},{"key":"2024082915335961300_i1558-7959-34-2-149-Brio1","doi-asserted-by":"crossref","unstructured":"Martin-del-Br\u00edo,\n              B.,\n             and\n\t\t\t\t\t\tSerrano-CincaC.\n          1993.\n\t\t\t\t\tSelf-organizing neural networks for the analysis and representation of data: Some financial cases.\n\t\t\t\t\tNeural Computing & Applications1\n\t\t\t\t\t(3):\n\t\t\t\t\t193\u2013206.\n\t\t\t\t\thttps:\/\/doi.org\/10.1007\/BF01414948","DOI":"10.1007\/BF01414948"},{"key":"2024082915335961300_i1558-7959-34-2-149-McNelis1","unstructured":"McNelis,\n              P. D.\n            \n          \n          2005.\n\t\t\t\t\tNeural Networks in Finance: Gaining Predictive Edge in the Market.\n\t\t\t\t\tCambridge, MA:\n\t\t\t\t\tAcademic Press."},{"key":"2024082915335961300_i1558-7959-34-2-149-Ott1","unstructured":"Ott,\n              B. H\n            \n          \n          2012.\n\t\t\t\t\tA convergence criterion for self-organizing maps.\n\t\t\t\t\tThesis paper, University of Rhode Island."},{"key":"2024082915335961300_i1558-7959-34-2-149-Peat1","doi-asserted-by":"crossref","unstructured":"Peat,\n              M.,\n             and\n\t\t\t\t\t\tJonesS.\n          2014.\n\t\t\t\t\tDetecting changing financial relationships: A self organising map approach.\n\t\t\t\t\tInEnterprise Applications and Services in the Finance Industry,\n\t\t\t\t\t1\u201312.\n\t\t\t\t\tNew York, NY:\n\t\t\t\t\tSpringer International Publishing.","DOI":"10.1007\/978-3-319-28151-3_1"},{"key":"2024082915335961300_i1558-7959-34-2-149-Resta1","doi-asserted-by":"crossref","unstructured":"Resta,\n              M.\n            \n          \n          2016.\n\t\t\t\t\tHubs and communities of financial assets with enhanced self-organizing maps.\n\t\t\t\t\tInComputational Intelligence Paradigms in Economic and Financial Decision Making,\n\t\t\t\t\t93\u2013114.\n\t\t\t\t\tNew York, NY:\n\t\t\t\t\tSpringer International Publishing.","DOI":"10.1007\/978-3-319-21440-5_6"},{"key":"2024082915335961300_i1558-7959-34-2-149-Rousseeuw1","doi-asserted-by":"crossref","unstructured":"Rousseeuw,\n              P. J.\n            \n          \n          1987.\n\t\t\t\t\tSilhouettes: A graphical aid to the interpretation and validation of cluster analysis.\n\t\t\t\t\tJournal of Computational and Applied Mathematics20\n\t\t\t\t\t(1):\n\t\t\t\t\t53\u201365.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/0377-0427(87)90125-7","DOI":"10.1016\/0377-0427(87)90125-7"},{"key":"2024082915335961300_i1558-7959-34-2-149-Sarlin1","doi-asserted-by":"crossref","unstructured":"Sarlin,\n              P.\n            \n          \n          2013.\n\t\t\t\t\tDecomposing the global financial crisis: A self-organizing time map.\n\t\t\t\t\tPattern Recognition Letters34\n\t\t\t\t\t(14):\n\t\t\t\t\t1701\u20131709.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.patrec.2013.03.017","DOI":"10.1016\/j.patrec.2013.03.017"},{"key":"2024082915335961300_i1558-7959-34-2-149-Schreck1","doi-asserted-by":"crossref","unstructured":"Schreck,\n              T.,\n            \n            \n              Teku\u0161ov\u00e1\n              T.,\n            \n            \n              Kohlhammer\n              J.,\n             and\n\t\t\t\t\t\tFellnerD.\n          2007.\n\t\t\t\t\tTrajectory-based visual analysis of large financial time series data.\n\t\t\t\t\tSIGKDD Explorations9\n\t\t\t\t\t(2):\n\t\t\t\t\t30\u201337.\n\t\t\t\t\thttps:\/\/doi.org\/10.1145\/1345448.1345454","DOI":"10.1145\/1345448.1345454"},{"key":"2024082915335961300_i1558-7959-34-2-149-Schwab1","unstructured":"Schwab,\n              K.,\n             and\n\t\t\t\t\t\tSala-i-MartinX.\n          2011.\n\t\t\t\t\tThe global competitiveness report 2011\u20132012.\n\t\t\t\t\tAvailable at: http:\/\/www3.weforum.org\/docs\/WEF_GCR_Report_2011-12.pdf"},{"key":"2024082915335961300_i1558-7959-34-2-149-SecuritiesandExchangeCommissionSEC1","unstructured":"Securities and Exchange Commission (SEC).\n\t\t\t\t\t2007.\n\t\t\t\t\tBeginners' guide to financial statement.\n\t\t\t\t\tAvailable at: https:\/\/www.sec.gov\/reportspubs\/investor-publications\/investorpubsbegfinstmtguidehtm.html"},{"key":"2024082915335961300_i1558-7959-34-2-149-SerranoCinca1","doi-asserted-by":"crossref","unstructured":"Serrano-Cinca,\n              C.\n            \n          \n          1998.\n\t\t\t\t\tLet financial data speak for themselves.\n\t\t\t\t\tInVisual Explorations in Finance with Self-Organizing Maps,\n\t\t\t\t\tedited byDeboekG., and\n\t\t\t\t\t\tKohonenT. .\n\t\t\t\t\tBerlin, Germany:\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-1-4471-3913-3_1"},{"key":"2024082915335961300_i1558-7959-34-2-149-Shih1","unstructured":"Shih,\n              J. Y.\n            \n          \n          2009.\n\t\t\t\t\tUsing self-organizing maps for analysis of corporate governance information.\n\t\t\t\t\tInProceedings of the 10th Asia Pacific Industrial Engineering & Management Systems Conference,\n\t\t\t\t\t1532\u20131542.\n\t\t\t\t\tImus, Philippines:\n\t\t\t\t\tAsia Pacific Industrial Engineering & Management Systems."},{"key":"2024082915335961300_i1558-7959-34-2-149-Spathis1","doi-asserted-by":"crossref","unstructured":"Spathis,\n              C.\n            \n          \n          2002.\n\t\t\t\t\tDetecting false financial statements using published data: Some evidence from Greece.\n\t\t\t\t\tManagerial Auditing Journal17\n\t\t\t\t\t(4):\n\t\t\t\t\t179\u2013191.\n\t\t\t\t\thttps:\/\/doi.org\/10.1108\/02686900210424321","DOI":"10.1108\/02686900210424321"},{"key":"2024082915335961300_i1558-7959-34-2-149-Stavrou1","doi-asserted-by":"crossref","unstructured":"Stavrou,\n              E. T.,\n            \n            \n              Charalambous\n              C.,\n             and\n\t\t\t\t\t\tSpiliotisS.\n          2007.\n\t\t\t\t\tHuman resource management and performance: A neural network analysis.\n\t\t\t\t\tEuropean Journal of Operational Research181\n\t\t\t\t\t(1):\n\t\t\t\t\t453\u2013467.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.ejor.2006.06.006","DOI":"10.1016\/j.ejor.2006.06.006"},{"key":"2024082915335961300_i1558-7959-34-2-149-Stice1","unstructured":"Stice,\n              J.\n            \n          \n          1991.\n\t\t\t\t\tUsing financial and market information to identify pre-engagement market factors associated with lawsuits against auditors.\n\t\t\t\t\tThe Accounting Review66\n\t\t\t\t\t(3):\n\t\t\t\t\t516\u2013533."},{"key":"2024082915335961300_i1558-7959-34-2-149-Sugden1","doi-asserted-by":"crossref","unstructured":"Sugden,\n              R.,\n            \n            \n              Wei\n              P.,\n             and\n\t\t\t\t\t\tWilsonJ. R.\n          2006.\n\t\t\t\t\tClusters, governance and the development of local economies: A framework for case studies.\n\t\t\t\t\tInClusters and Globalisation: The Development of Economies,\n\t\t\t\t\tedited byPitelisC.,SugdenR., and\n\t\t\t\t\t\tWilsonJ. R. ,\n\t\t\t\t\t61\u201381.\n\t\t\t\t\tCheltenham, U.K.:\n\t\t\t\t\tEdward Elgar.","DOI":"10.4337\/9781847200136.00011"},{"key":"2024082915335961300_i1558-7959-34-2-149-Tang1","doi-asserted-by":"crossref","unstructured":"Tang,\n              Y. C.\n            \n          \n          2009.\n\t\t\t\t\tAn approach to budget allocation for an aerospace company\u2014Fuzzy analytic hierarchy process and artificial neural network.\n\t\t\t\t\tNeurocomputing72\n\t\t\t\t\t(16\/18):\n\t\t\t\t\t3477\u20133489.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.neucom.2009.03.020","DOI":"10.1016\/j.neucom.2009.03.020"},{"key":"2024082915335961300_i1558-7959-34-2-149-Thiprungsri1","doi-asserted-by":"crossref","unstructured":"Thiprungsri,\n              S.,\n             and\n\t\t\t\t\t\tVasarhelyiM. A.\n          2011.\n\t\t\t\t\tCluster analysis for anomaly detection in accounting data: An audit approach.\n\t\t\t\t\tThe International Journal of Digital Accounting Research11\n\t\t\t\t\t(17):\n\t\t\t\t\t69\u201384.\n\t\t\t\t\thttps:\/\/doi.org\/10.4192\/1577-8517-v11_4","DOI":"10.4192\/1577-8517-v11_4"},{"key":"2024082915335961300_i1558-7959-34-2-149-Trigueiros1","doi-asserted-by":"crossref","unstructured":"Trigueiros,\n              D.\n            \n          \n          1994.\n\t\t\t\t\tIncorporating complementary ratios in the analysis of financial statements.\n\t\t\t\t\tAccounting, Management and Information Technologies4\n\t\t\t\t\t(3):\n\t\t\t\t\t149\u2013162.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/0959-8022(94)90002-7","DOI":"10.1016\/0959-8022(94)90002-7"},{"key":"2024082915335961300_i1558-7959-34-2-149-Tsai1","doi-asserted-by":"crossref","unstructured":"Tsai,\n              C. F.\n            \n          \n          2014.\n\t\t\t\t\tCombining cluster analysis with classifier ensembles to predict financial distress.\n\t\t\t\t\tInformation Fusion16:\n\t\t\t\t\t46\u201358.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.inffus.2011.12.001","DOI":"10.1016\/j.inffus.2011.12.001"},{"key":"2024082915335961300_i1558-7959-34-2-149-Tzeng1","unstructured":"Tzeng,\n              F. Y.,\n             and\n\t\t\t\t\t\tMaK. L.\n          2005.\n\t\t\t\t\tOpening the black box: Data driven visualization of neural networks.\n\t\t\t\t\tAvailable at: https:\/\/ieeexplore.ieee.org\/document\/1532820"},{"key":"2024082915335961300_i1558-7959-34-2-149-VonderMalsburg1","doi-asserted-by":"crossref","unstructured":"Von der Malsburg,\n              C.\n            \n          \n          1973.\n\t\t\t\t\tSelf-organization of orientation sensitive cells in the striate cortex.\n\t\t\t\t\tKybernetik14\n\t\t\t\t\t(2):\n\t\t\t\t\t85\u2013100.\n\t\t\t\t\thttps:\/\/doi.org\/10.1007\/BF00288907","DOI":"10.1007\/BF00288907"},{"key":"2024082915335961300_i1558-7959-34-2-149-White1","unstructured":"White,\n              L.\n            \n          \n          2004.\n\t\t\t\t\tWhy look at German cost management? Available at: https:\/\/sfmagazine.com\/wp-content\/uploads\/sfarchive\/2004\/09\/PERSPECTIVES-Why-look-at-German-cost-management.pdf"},{"key":"2024082915335961300_i1558-7959-34-2-149-Wu1","doi-asserted-by":"crossref","unstructured":"Wu,\n              C.,\n             and\n\t\t\t\t\t\tWangX. M.\n          2000.\n\t\t\t\t\tA neural network approach for analysing small business lending decisions.\n\t\t\t\t\tReview of Quantitative Finance and Accounting15\n\t\t\t\t\t(3):\n\t\t\t\t\t259\u2013276.\n\t\t\t\t\thttps:\/\/doi.org\/10.1023\/A:1008324023422","DOI":"10.1023\/A:1008324023422"},{"key":"2024082915335961300_i1558-7959-34-2-149-Yin1","doi-asserted-by":"crossref","unstructured":"Yin,\n              H.,\n             and\n\t\t\t\t\t\tAllinsonN. M.\n          1995.\n\t\t\t\t\tOn the distribution and convergence of feature space in self-organizing maps.\n\t\t\t\t\tNeural Computation7\n\t\t\t\t\t(6):\n\t\t\t\t\t1178\u20131187.\n\t\t\t\t\thttps:\/\/doi.org\/10.1162\/neco.1995.7.6.1178","DOI":"10.1162\/neco.1995.7.6.1178"},{"key":"2024082915335961300_i1558-7959-34-2-149-Zhang1","doi-asserted-by":"crossref","unstructured":"Zhang,\n              G.,\n            \n            \n              Hu\n              M. Y.,\n            \n            \n              Patuwo\n              B. E.,\n             and\n\t\t\t\t\t\tIndroD. C.\n          1999.\n\t\t\t\t\tArtificial neural networks in bankruptcy prediction: General framework and cross-validation analysis.\n\t\t\t\t\tEuropean Journal of Operational Research116\n\t\t\t\t\t(1):\n\t\t\t\t\t16\u201332.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/S0377-2217(98)00051-4","DOI":"10.1016\/S0377-2217(98)00051-4"}],"container-title":["Journal of Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/publications.aaahq.org\/jis\/article-pdf\/34\/2\/149\/9754\/i1558-7959-34-2-149.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/publications.aaahq.org\/jis\/article-pdf\/34\/2\/149\/9754\/i1558-7959-34-2-149.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T17:16:33Z","timestamp":1724951793000},"score":1,"resource":{"primary":{"URL":"https:\/\/publications.aaahq.org\/jis\/article\/34\/2\/149\/1183\/Neural-Networks-in-Accounting-Clustering-Firm"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,29]]},"references-count":80,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2020,1,29]]},"published-print":{"date-parts":[[2020,6,1]]}},"URL":"https:\/\/doi.org\/10.2308\/isys-18-002","relation":{},"ISSN":["1558-7959","0888-7985"],"issn-type":[{"type":"electronic","value":"1558-7959"},{"type":"print","value":"0888-7985"}],"subject":[],"published":{"date-parts":[[2020,1,29]]}}}