Name and surname:
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Mgr. Eva Ticina
|
Document type:
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Research/art/teacher profile of a person
|
The name of the university:
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Comenius University Bratislava
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The seat of the university:
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Šafárikovo námestie 6, 818 06 Bratislava
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III.a - Occupation-position | III.b - Institution | III.c - Duration |
---|---|---|
Web designer | AsicFox. Ukraine. Kyiv | 1 year |
Web developer | AsicFox. Ukraine. Kyiv | 1 year |
Data Analytic | AdvantISS. Ukraine. Sumy | 6 month |
Doctoral student | DEPARTMENT OF INFORMATION MANAGEMENT AND BUSINESS SYSTEMS (Comenius University) | 3 month |
IV.a - Activity description, course name, other | IV.b - Name of the institution | IV.c - Year |
---|---|---|
Busines with China. The course includes knowledge about website development from a marketing and sales perspective, setting up contextual and display advertising in search networks, setting up targeted advertising on social media, working with analytical tools, monitoring the advertising budget, and its optimization. | Sonimax | 3 month |
Digital Marketing. Basics of e-marketing | Google Digital Garage | 3 month |
Web Design Junior. Advanced courses of UI/UX design | Projector | 4 month |
English IELTS | British Council | 2 month |
Bc. in Data Science | UI University of Applied Sciences. Germany | 2 |
V.1.a - Name of the profile course | V.1.b - Study programme | V.1.c - Degree | V.1.d - Field of study |
---|---|---|---|
Business Analytics and Decision Making | Erazmus | Magister | Management |
Management of Information Systems | Erasmus | Mgr | Management |
Management of Information Systems | English | Mgr | Management |
V.2.a - Name of the study programme | V.2.b - Degree | V.2.c - Field of study |
---|---|---|
Management of Information Systems | Mgr | Management |
A Proposal for AI-Driven Method for Strategic Business Decision-Making
This article proposes a method of using AI to improve the business decision-making process, implemented within the Dara framework using the CausalNex model and integrating the interpretation of model results via ChatGPT-4. The study involved developing an experimental application for two specific business scenarios and comparing its effectiveness with standard ChatGPT-4. Results show that the app excels in detecting complex cause-and-effect relationships, surpassing the capabilities of ChatGPT-4. The utility of the approach in accurately visualizing patterns and responding to critical queries based on the interpretation of newly obtained data is demonstrated. The results suggest that the application can significantly contribute to strategic business decision-making, offering precise recommendations. Thus, the approach has potential to become an integral tool in shaping future strategic decision-making.