TY - JOUR AU - Pisoni, Galena AU - Molnár, Bálint TI - AI-Based Solution for Sustainability Tracing for Companies JF - INTERNATIONAL JOURNAL OF KNOWLEDGE MANAGEMENT J2 - IJKM VL - 20 PY - 2024 IS - 1 SP - 1 EP - 17 PG - 17 SN - 1548-0666 DO - 10.4018/IJKM.340723 UR - https://m2.mtmt.hu/api/publication/34760161 ID - 34760161 AB - Many companies look for novel ways to trace their operational sustainability. The application of AI to analyze and make sense of the big data the company holds represents one promising approach for this aim. The authors study how one can set and design an AI-based solution for improving the sustainability of complex business processes and decision-making in companies of different types. First, they provide a general analysis of current frameworks for measuring adherence to sustainability goals for companies, then they present a conceptual framework and architecture design for an AI-enabled sustainability service for companies. The implications of our research suggest that AI can provide distinct functions: (a) automation: taking big data from different departments and analyzing them with the aim of tracing the sustainability of the company; (b) support: to help decision-making and create relevant insights for stakeholders that are coherent with defined sustainability decision criteria. To the authors' knowledge, no previous research has provided analysis and design of such AI solution for companies. LA - English DB - MTMT ER - TY - CONF AU - Galena, Pisoni AU - Erika, Mináriková AU - Miroslav, Hudec AU - Hanna, Kristin Skaftadottir AU - Molnár, Bálint AU - Miljan, Vučetić AU - Denisa, Sedláková TI - REDUCING COMPLEXITY BY USING LINGUISTIC SUMMARIES FOR BUSINESS INTELLIGENCE REPORTING T2 - 17th IADIS INTERNATIONAL CONFERENCE INFORMATION SYSTEMS 2024 PB - IADIS Press C1 - Oporto SN - 9789898704566 PY - 2024 SP - 174 EP - 178 PG - 5 SN - 9789898704566 UR - https://m2.mtmt.hu/api/publication/34741958 ID - 34741958 LA - English DB - MTMT ER - TY - CONF AU - Galena, Pisoni AU - Molnár, Bálint AU - Szabolcs, Korba AU - Maria, Moloney TI - SUSTAINABILITY TRACING FOR COMPANIES: GOVERNANCE, REGULATION, ECONOMICAL AND ETHICAL CONSIDERATIONS T2 - 17th IADIS INTERNATIONAL CONFERENCE INFORMATION SYSTEMS 2024 PB - IADIS Press C1 - Oporto SN - 9789898704566 PY - 2024 SP - 136 EP - 140 PG - 5 UR - https://m2.mtmt.hu/api/publication/34741953 ID - 34741953 LA - English DB - MTMT ER - TY - BOOK AU - Galena, Pisoni AU - Molnár, Bálint AU - Szabolcs, Korba AU - Maria, Moloney TI - SUSTAINABILITY TRACING FOR COMPANIES: GOVERNANCE, REGULATION, ECONOMICAL AND ETHICAL CONSIDERATIONS PB - IADIS Press C1 - Porto PY - 2024 SP - 5 SN - 9789898704566 UR - https://m2.mtmt.hu/api/publication/34741944 ID - 34741944 LA - English DB - MTMT ER - TY - JOUR AU - Molnár, Bálint TI - Review: Quick start guide to large language models: strategies and best practices for using ChatGPT and other LLMs JF - COMPUTING REVIEWS - ASSOCIATION FOR COMPUTING MACHINERY J2 - COMP REV - ACM VL - 2024 PY - 2024 IS - January SN - 1530-6585 UR - https://m2.mtmt.hu/api/publication/34536179 ID - 34536179 LA - English DB - MTMT ER - TY - CHAP AU - Molnár, Bálint TI - An Analysis of the Concept of Cognitive Enterprise Architecture Foundation of Cognitive Enterprise Archtecture T2 - 14th IEEE International Conference on Cognitive Infocommunications PB - IEEE CY - Piscataway (NJ) SN - 9798350325652 PY - 2023 SP - 107 EP - 112 PG - 6 DO - 10.1109/CogInfoCom59411.2023.10397536 UR - https://m2.mtmt.hu/api/publication/34548975 ID - 34548975 LA - English DB - MTMT ER - TY - CHAP AU - Pisoni, Galena AU - Molnár, Bálint ED - Tsiatsos, Thrasyvoulos ED - Langmann, Reinhard ED - Auer, Michael E. TI - Data Management and Enterprise Architectures for Responsible AI Services T2 - Open Science in Engineering PB - Springer Nature Switzerland AG CY - Cham SN - 9783031424670 T3 - Lecture Notes in Networks and Systems, ISSN 2367-3370 ; 763. PY - 2023 SP - 879 EP - 884 PG - 6 DO - 10.1007/978-3-031-42467-0_83 UR - https://m2.mtmt.hu/api/publication/34472933 ID - 34472933 AB - Big data is becoming a reality. Complex and difficult-to-understand data may be found in a wide range of industries. Big data is a critical component of enterprise services and technology architectures. Data science techniques and methodologies can be applied in many aspects of the working of companies. In this paper, first, as a background, we provide an overview of knowledge management practices and data analysis strategies and techniques in the daily operations of companies working towards development of AI agents. Furthermore, we look at the need in particular companies to develop human centric AI solutions; then, we discuss the basics for cross-disciplinary research, in which we stress the need to rethink development processes of AI services and make them more responsible. Thereby, we define research questions to investigate the problem. As the research proposal discusses, companies and public institutions can create and develop new responsible, ethical, and transparent AI services. LA - English DB - MTMT ER - TY - JOUR AU - Pisoni, Galena AU - Molnár, Bálint AU - Tarcsi, Ádám TI - Knowledge Management and Data Analysis Techniques for Data-Driven Financial Companies JF - JOURNAL OF THE KNOWLEDGE ECONOMY J2 - J KNOWL ECON VL - 1 PY - 2023 IS - 1 SN - 1868-7865 DO - 10.1007/s13132-023-01607-z UR - https://m2.mtmt.hu/api/publication/34411978 ID - 34411978 AB - In today’s fast-paced financial industry, knowledge management and data-driven decision making have become essential for the success of financial technology (FinTech) companies. Big data (BD) is a prevalent phenomenon that can be found across many industries, including finance. Despite its complexity and difficulty to comprehend, big data is a critical component of financial services enterprises and technology architectures. We examine BD from various aspects, considering data science (DS) techniques and methodologies that can be applied during the operation of an enterprise. Our aim is to provide an overview of knowledge management (KM) practices and data analysis (DA) strategies and techniques in the daily operations of financial companies. We address the role of knowledge management, data analytics in a financial institution. The paper demonstrates financial institutions’ enablement for new services resulting from technological advancements. LA - English DB - MTMT ER - TY - GEN AU - Teng, Huei-Wen AU - Härdle, Wolfgang Karl AU - Osterrieder, Joerg AU - Baals, Lennart John AU - Papavassiliou, Vassilios G. AU - Bolesta, Karolina AU - Kabasinskas, Audrius AU - Filipovska, Olivija AU - Thomaidis, Nikolaos S. AU - Moukas, Alexios Ioannis AU - Goundar, Sam AU - Nasir, Jamal Abdul AU - Weinberg, Abraham Itzhak AU - Arakelian, Veni AU - anon, Ciprian-Octavian AU - Akar, Mutlu AU - kabaklarli, esra AU - Apostol, Elena-Simona AU - Iannario, Maria AU - Bedowska-Sojka, Barbara AU - Skaftadottir, Hanna Kristin AU - Schwendner, Peter AU - Yıldırım, Özgür AU - Shala, Albulena AU - Pisoni, Galena AU - Coita, Ioana Florina AU - Korba, Szabolcs AU - Hafner, Christian M. AU - Molnár, Bálint AU - Xhumari, Elda AU - Pele, Daniel Traian TI - Mitigating Digital Asset Risks PY - 2023 PG - 54 DO - 10.2139/ssrn.4594467 UR - https://m2.mtmt.hu/api/publication/34399662 ID - 34399662 LA - English DB - MTMT ER - TY - JOUR AU - Molnár, Bálint TI - Review: Algorithms for constructing computably enumerable sets JF - COMPUTING REVIEWS - ASSOCIATION FOR COMPUTING MACHINERY J2 - COMP REV - ACM VL - 2023 PY - 2023 IS - November SN - 1530-6585 UR - https://m2.mtmt.hu/api/publication/34368042 ID - 34368042 LA - English DB - MTMT ER -