The 6th International Conference on Modern Management based on Big Data (MMBD 2025)

Abstract: Generative Artificial Intelligence (GenAI) is becoming a powerful tool in modern entrepreneurship, providing new opportunities for automation, personalization, and the creation of innovative products and services. Through emerging technologies such as language models, image and audio generation systems, entrepreneurs can significantly accelerate their workflows and reduce costs. However, the implementation of GenAI is associated with a number of significant challenges. The technological barriers include high requirements for computing resources, complexity in integration, and the need for specialized knowledge. The lack of trained personnel and resistance to technological changes are another obstacle in its sustainable implementation. From a business perspective, the unpredictability of the GenAI results and the lack of trust among users can slow down the growth. The emerging global legal regulations impose additional responsibilities on the entrepreneurs. The invited speech analyzes these multi-layered challenges and offers guidelines for the responsible and effective use of GenAI in the entrepreneurship.

Abstract: In this paper we perform extensive literature review in order to derive a definition of effective digitalization for small and medium-sized enterprises (SMEs) in terms of identified key performance indicators. We focus our research on the crucial role of customer satisfaction in the light of SMEs ability to respond to actual demands of customers as a result of their digitalization efforts. We further study through literature analysis the cognitive (rational) and the affective (emotional) component, being the building blocks of customer satisfaction. Among our major findings is that a notable emotional component is documented in the reviewed research works. While traditional customer satisfaction surveys are a conventional and widely applied tool, an increasing number of studies draw the researchers’ attention to social media platforms as a source of important information. Consequently, we propose an “emotional” lens methodology to reveal deeper insights on SMEs effective digitalization on the basis of social media data. The proposed framework employs AI tools in order to extract sentiment-driven knowledge to support the deeper understanding of digitalization dimensions that are barely studied. We illustrate the motivation behind the proposed approach through a case study for Bulgaria.

Abstract: As organizations navigate the era of data abundance and AI acceleration, the intersection of data mining, generative AI, and informetrics becomes a powerful engine for innovation and insight. This keynote explores how advanced data mining techniques extract deep patterns from vast datasets, how generative AI transforms those patterns into creative and actionable outputs, and how informetrics quantifies the structure, impact, and evolution of knowledge within digital and scholarly ecosystems.
The talk highlights real-world applications where these fields converge—such as in scientific discovery, digital transformation, and strategic decision-making—and discusses both opportunities and ethical challenges in leveraging such technologies for modern management.
Attendees will gain a strategic perspective on harnessing data not only for prediction and automation but also for understanding influence, impact, and innovation in a data-driven world.