Entrepreneurship & Organization Management

This paper explores the synergy between Language Model (LLM) suggestions and traditional budgeting models for achieving optimal financial planning at both individual and group levels. As technology continues to play a pivotal role in personal finance, leveraging advanced language models can provide insightful recommendations to enhance budgeting strategies. The integration of LLM suggestions with individual and group budgeting models is examined to identify synergies, address challenges, and propose a comprehensive approach to financial planning. The study considers key aspects such as personalization, behavioral economics and collaborative budgeting for effective implementation.

This conceptual paper integrates social entrepreneurship concepts, identifies gaps, and proposes a model. The literature suggests women social entrepreneurs embody interplay collaborative and authentic leadership attributes focusing on unravelling the intricate dynamics between authentic and collaborative leadership, emphasizing the pivotal role of self-awareness, and highlighting potential enriched practices combining both styles. Central research questions revolve around what motivates women social entrepreneurs and the leadership styles they exhibit. The proposed concept model is a guiding framework for comprehending the intricate dynamics of leadership attributes in women social entrepreneurs and their impact on organizational productivity implicating the initiation of an empirical study.

This paper investigates the intricate relationship between financial factors and the dynamics of economic cycles in a few European countries. The analysis focuses on key financial indicators, including interest rates, inflation rates, exchange rates, and credit availability, to understand their impact on economic cycles. By examining data from selected European countries over a specific time period, this study aims to provide insights into the interplay between financial variables and economic fluctuations. The findings have important implications for policymakers, investors, and businesses seeking to navigate the complexities of economic cycles in the European context.

Artificial Intelligence (AI) has emerged as a transformative force across various industries, revolutionizing innovation and knowledge management practices. This paper explores the multifaceted applications of AI in fostering innovation and sustainable knowledge management, with a particular focus on data analytics in the energy sector. The integration of AI technologies, including machine learning, natural language processing, and predictive analytics, has significantly enhanced the efficiency, accuracy, and sustainability of knowledge-driven processes. By leveraging AI, organizations can optimize decision-making, streamline operations, and contribute to a more sustainable future. This paper delves into key AI applications, challenges, and opportunities in innovation, knowledge management, and data analytics within the energy sector.