Modeling
Ali Ghorbani; Mohammad Amin Torabi; Matineh Moghaddam
Abstract
This article examines the phenomenon of "meeting madness" among managers, recognized as a significant challenge in workplace and organizational environments. The primary aim of this research is to identify the causes and contributing factors to the emergence of this phenomenon and to propose solutions ...
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This article examines the phenomenon of "meeting madness" among managers, recognized as a significant challenge in workplace and organizational environments. The primary aim of this research is to identify the causes and contributing factors to the emergence of this phenomenon and to propose solutions for managers to counteract it. For this study, an advanced meta-synthesis method using artificial intelligence algorithms and natural language processing has been employed. Specifically, scripts alongside the development of advanced AI algorithms such as recurrent neural networks and genetic algorithms were utilized to search for and extract data. These algorithms, particularly the machine learning models, were capable of analyzing key concepts and emerging trends in the realm of meeting madness with high precision. Utilizing these technologies has led to the creation of a centralized database that organizes data for subsequent analyses, reduces human error, and enables quicker and more accurate data analysis. Various causes of this phenomenon include issues in meeting planning and organization, defects in organizational culture and communications, psychological and emotional issues of managers and employees, among other reasons. Following this identification, the consequences of meeting madness have been detailed, and ultimately, a set of practical and applicable solutions such as improving managerial skills, reforming culture and organizational structure, enhancing effective communications, and introducing innovative methods like leadership symbiosis, meeting diplomacy, decision-making quantization in meetings, and organizational pluralism have been presented.
