PL EN


Preferences help
enabled [disable] Abstract
Number of results
2019 | 125 | 114-126
Article title

Expert systems as a tool supporting the assessment of the financial condition of business units

Authors
Content
Title variants
Languages of publication
EN
Abstracts
EN
The ubiquitousness of information systems means that more and more areas of the company's activity are moving into the virtual sphere. IT systems take over most of the complicated tasks performed by people, which has a positive impact on time and costs incurred for the implementation of these tasks. One of the areas in which IT systems are used is the area of financial management, and thus the management of the financial condition of the unit. This article aims to test the suitability of expert systems as tools that can support the analysis and assessment of the financial condition of business units. The theoretical part discusses the essence of IT systems, theoretical foundations of expert systems and their advantages and disadvantages. The research part shows the use of an expert system to conduct the analysis of the financial condition of selected enterprises based on data from the financial statements of these units from 2015. The expert system provided information on the financial condition of selected companies. These results were compared with the results of the analysis carried out in the traditional way. This confirmed the author's assumption that it is possible to replace the financial analysis carried out with traditional methods by using a properly prepared expert system.
Year
Volume
125
Pages
114-126
Physical description
Contributors
  • Faculty of Management, Czestochowa University of Technology, 19B Armii Krajowej Str., 42-200 Czestochowa, Poland
References
  • [1] Wade M., Hulland J. The resource-based view and information systems research: review, extension, and suggestions for future research. MIS Quarterly (2004), 28(1), 107-142
  • [2] Legris P., Ingham J., Collerette P. Why do people use information technology? A critical review of the technology acceptance model. Information & Management (2003), 40(3), 191-204
  • [3] DeLone W. H., McLean E. R. (1992). Information systems success: The quest for the dependent variable. Information systems research (1992), 3(1), 60-95.
  • [4] Trkman P. The critical success factors of business process management. International journal of information management (2010), 30(2), 125-134
  • [5] Haag S., Cummings M., Dawkins J. (2013). Management information systems for the Information Age. Irwin McGraw-Hill (2013).
  • [6] Talvinen J. M. Information systems in marketing: Identifying opportunities for new applications. European Journal of Marketing (1995), 29(1), 8-26
  • [7] Arnott D., Pervan G. A critical analysis of decision support systems research. Journal of information technology (2005), 20(2), 67-87
  • [8] Shim J. P., Warkentin M., Courtney J. F., Power D. J., Sharda R., Carlsson C. Past, present, and future of decision support technology. Decision support systems (2002), 33(2), 111-126
  • [9] Gennari J. H., Musen M. A., Fergerson R. W., Grosso W. E., Crubézy M., Eriksson H., Tu S. W. The evolution of Protégé: an environment for knowledge-based systems development. International Journal of Human-Computer Studies (2003), 58(1), 89-123
  • [10] Huang H. C. Designing a knowledge-based system for strategic planning: A balanced scorecard perspective. Expert Systems with Applications (2009), 36(1), 209-218
  • [11] Sowa J. F. Principles of semantic networks: Explorations in the representation of knowledge. Morgan Kaufmann (2014).
  • [12] Bhatt G. D. Knowledge management in organizations: examining the interaction between technologies, techniques, and people. Journal of knowledge management (2001), 5(1), 68-75
  • [13] Studer R., Benjamins V. R., Fensel D. Knowledge engineering: principles and methods. Data & knowledge engineering (1998), 25(1-2), 161-197
  • [14] Liao S. H. Expert system methodologies and applications - a decade review from 1995 to 2004. Expert systems with applications (2005), 28(1), 93-103
  • [15] Nemati H. R., Steiger D. M., Iyer L. S., Herschel, R. T. Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decision Support Systems (2002), 33(2), 143-161
  • [16] Belleau F., Nolin M. A., Tourigny N., Rigault, P., Morissette J. Bio2RDF: towards a mashup to build bioinformatics knowledge systems. Journal of biomedical informatics (2008), 41(5), 706-716
  • [17] Castillo E., Gutierrez J., Hadi A. Expert Systems and Probabilistic Network Models. New York: Springer Science & Business Media (2012).
  • [18] O’Brien J. Introduction to information systems. New York: McGraw-Hill/Irwin (2005)
  • [19] Liao S. H. Knowledge management technologies and applications - literature review from 1995 to 2002. Expert systems with applications (2003), 25(2), 155-164
  • [20] Sahin S., Tolun M. R., Hassanpour R. Hybrid expert systems: A survey of current approaches and applications. Expert systems with applications (2012), 39(4), 4609-4617
Document Type
article
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.psjd-0dda7f15-19b3-4c48-88e2-f28a5fed3451
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.