IDEAS home Printed from https://ideas.repec.org/a/aif/journl/v3y2019i1p17-28.html
   My bibliography  Save this article

AI foundations of the international business planning and the AI consciousness model

Author

Listed:
  • Laskai András

Abstract

With the continuous development of data mining instruments we acquire increasingly accurate and deep knowledge regarding the processes and network correlations related to business planning that can be considered one of the cornerstones of the world of business. During data mining activity patterns can be derived that provide assistance in the analysis of basic correlations. The most widely accepted analysis methods are hybrid data mining models and instruments, and within those neural networks that model the functioning of the human brain, which provide an avenue for the discovery and understanding of deeper correlations. By the application of data mining a consciousness model can be formulated, which evaluates and analyzes company movements, operations and decision making mechanisms. Data mining is one of the most important current paradigms of advanced business analyses and decision making instruments. It is a multidisciplinary approach that applies various techniques in the areas of statistics, machine learning and databases. One of the special branches of data mining inspects the correlations of financial balance sheets and reports as well as their derived indicators. In the case of this method, data mining provides the identification of data patterns in an innovative and ultimately interpretable manner. Data mining makes it possible for organizations to identify the statistical correlations between performance indicators more easily. In connection with this, by using hybrid data mining instruments the conscious operation of a specific company unit can be defined. By mapping conscious operations research may get closer to the mapping of the Unified Field.

Suggested Citation

  • Laskai András, 2019. "AI foundations of the international business planning and the AI consciousness model," International Journal of Science and Business, IJSAB International, vol. 3(1), pages 17-28.
  • Handle: RePEc:aif:journl:v:3:y:2019:i:1:p:17-28
    as

    Download full text from publisher

    File URL: https://ijsab.com/wp-content/uploads/303.pdf
    Download Restriction: no

    File URL: https://ijsab.com/volume-3-issue-1/1661
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Callen, Jeffrey L. & Kwan, Clarence C. Y. & Yip, Patrick C. Y. & Yuan, Yufei, 1996. "Neural network forecasting of quarterly accounting earnings," International Journal of Forecasting, Elsevier, vol. 12(4), pages 475-482, December.
    2. Amani, Farzaneh A. & Fadlalla, Adam M., 2017. "Data mining applications in accounting: A review of the literature and organizing framework," International Journal of Accounting Information Systems, Elsevier, vol. 24(C), pages 32-58.
    3. Ittner, Christopher D. & Larcker, David F., 2001. "Assessing empirical research in managerial accounting: a value-based management perspective," Journal of Accounting and Economics, Elsevier, vol. 32(1-3), pages 349-410, December.
    4. Sumit Chakraborty & Sushil K. Sharma, 2007. "Prediction of corporate financial health by Artificial Neural Network," International Journal of Electronic Finance, Inderscience Enterprises Ltd, vol. 1(4), pages 442-459.
    5. Gray, Glen L. & Debreceny, Roger S., 2014. "A taxonomy to guide research on the application of data mining to fraud detection in financial statement audits," International Journal of Accounting Information Systems, Elsevier, vol. 15(4), pages 357-380.
    6. Hian Koh & Sen Tan, 1999. "A neural network approach to the prediction of going concern status," Accounting and Business Research, Taylor & Francis Journals, vol. 29(3), pages 211-216.
    7. Salterio, Steven, 1996. "The effects of precedents and client position on auditors' financial accounting policy judgment," Accounting, Organizations and Society, Elsevier, vol. 21(5), pages 467-486, July.
    8. Dan-Bee Song & Ho-Young Lee & Eun-Jung Cho, 2013. "The association between earnings management and asset misappropriation," Managerial Auditing Journal, Emerald Group Publishing, vol. 28(6), pages 542-567, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Amani, Farzaneh A. & Fadlalla, Adam M., 2017. "Data mining applications in accounting: A review of the literature and organizing framework," International Journal of Accounting Information Systems, Elsevier, vol. 24(C), pages 32-58.
    2. Mushang Lee & Yu-Lan Huang, 2020. "Corporate Social Responsibility and Corporate Performance: A Hybrid Text Mining Algorithm," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
    3. Robert G. Biscontri, 2012. "A Radial Basis Function Approach To Earnings Forecast," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(1), pages 1-18, January.
    4. Zhang, Chao & Zhu, Weidong & Dai, Jun & Wu, Yong & Chen, Xulong, 2023. "Ethical impact of artificial intelligence in managerial accounting," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
    5. Fábio Albuquerque & Paula Gomes Dos Santos, 2023. "Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools," FinTech, MDPI, vol. 2(2), pages 1-27, April.
    6. Andrea Cardoni & Evgeniia Kiseleva & Francesco De Luca, 2020. "Continuous auditing and data mining for strategic risk control and anticorruption: Creating “fair” value in the digital age," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 3072-3085, December.
    7. Saxton, Gregory D. & Guo, Chao, 2020. "Social media capital: Conceptualizing the nature, acquisition, and expenditure of social media-based organizational resources," International Journal of Accounting Information Systems, Elsevier, vol. 36(C).
    8. Abernethy, Margaret A. & Vagnoni, Emidia, 2004. "Power, organization design and managerial behaviour," Accounting, Organizations and Society, Elsevier, vol. 29(3-4), pages 207-225.
    9. Jana Fibírová, 2008. "The Competitive Advantage of Management Accounting [Konkurenční výhoda manažerského účetnictví]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2008(2), pages 78-90.
    10. Zbysław Dobrowolski & Grzegorz Drozdowski & Mirela Panait & Arkadiusz Babczuk, 2022. "Can the Economic Value Added Be Used as the Universal Financial Metric?," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    11. Sterling Huang & Gilles Hilary, 2018. "Zombie Board: Board Tenure and Firm Performance," Journal of Accounting Research, Wiley Blackwell, vol. 56(4), pages 1285-1329, September.
    12. Olson, Dennis & Mossman, Charles, 2003. "Neural network forecasts of Canadian stock returns using accounting ratios," International Journal of Forecasting, Elsevier, vol. 19(3), pages 453-465.
    13. Rafael Becerra-Vicario & David Alaminos & Eva Aranda & Manuel A. Fernández-Gámez, 2020. "Deep Recurrent Convolutional Neural Network for Bankruptcy Prediction: A Case of the Restaurant Industry," Sustainability, MDPI, vol. 12(12), pages 1-15, June.
    14. Joan Luft & Michael Shields, 2002. "Zimmerman's contentious conjectures: describing the present and prescribing the future of empirical management accounting research," European Accounting Review, Taylor & Francis Journals, vol. 11(4), pages 795-803.
    15. Federica De Santis, 2016. "Auditing Standard Change and Auditors' Everyday Practice: A Field Study," International Business Research, Canadian Center of Science and Education, vol. 9(12), pages 41-54, December.
    16. Chen, Clara Xiaoling & Lill, Jeremy B. & Lucianetti, Lorenzo, 2023. "Performance measurement system diversity and product innovation: Evidence from longitudinal survey data," Accounting, Organizations and Society, Elsevier, vol. 111(C).
    17. Diana COZMIUC & Ioan PETRISOR, 2015. "The Paradox Of Investment: Constraining Strategy," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 9(1), pages 81-96, November.
    18. Ülle Pärl, 2006. "Choice of measures for performance measurement models on the example of successful Estonian companies," University of Tartu - Faculty of Economics and Business Administration, in: Entrepreneurship in Estonia: policies, practices, education and research, volume 28, chapter 12, pages 228-247, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    19. Leslie A. Robinson & Phillip C. Stocken, 2013. "Location of Decision Rights Within Multinational Firms," Journal of Accounting Research, Wiley Blackwell, vol. 51(5), pages 1261-1297, December.
    20. Ganna Demydyuk, 2011. "Optimal Financial Key Performance Indicators: Evidence From The Airline Industry," Accounting & Taxation, The Institute for Business and Finance Research, vol. 3(2), pages 39-51.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aif:journl:v:3:y:2019:i:1:p:17-28. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Farjana Rahman (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.