Authors:
S. Briskline Kiruba, Rejwan Bin Sulaiman, A. Prabha, Mykhailo Paslavskyi, C. Christina Angelin
Addresses:
Department of Computer Science, Jaya College of Arts and Science, Chennai, Tamil Nadu, India. Department of Computer Science and Technology, Northumbria University, Newcastle, London, United Kingdom. Department of Electrical and Electronics Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. Department of Computer Science, Ukrainian National Forestry University, Lviv, Lviv Oblast, Ukraine. Department of Mathematics, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India.
Abstract:
This study presents a qualitative analysis of job satisfaction among Management Consultants' employees, conducted as an internal audit for the company. The primary purpose of the research is to determine the extent of employee satisfaction and specifically how the company's management of the work environment influences employees in general. It is conducted on the premise of initial data gathering. Information was gathered using a pre-prepared questionnaire survey, duly distributed among the employees. Their feedback was examined using percentage analysis and chat analysis methods, making it easy to interpret the degree of satisfaction. Work environment, leadership, rewards, chances of growth, and work-life balance are the most influential drivers, which are determined primarily by this research. Job satisfaction is maximised if it leads to greater productivity, lower turnover, and better organisational performance. The study has also provided extensive learning opportunities, which have further enhanced my knowledge of organisational behaviour and business processes in Management Consultants. Besides honing my knowledge in the dynamics of employee satisfaction, the study also gives me a general background on human resource management and how it is the key to organisational success.
Keywords: Management Consultants; Percentage Analysis; Self-Contentment; Chat Analysis; Analysis of Data; Primary Data; Pre-Designed Questionnaire; Organisational Behaviour; Human Resource Management; Organisational Commitment.
Received: 12/08/2024, Revised: 06/10/2024, Accepted: 20/11/2024, Published: 05/03/2025
DOI: 10.64091/ATITP.2025.000109
AVE Trends in Intelligent Technoprise Letters, 2025 Vol. 2 No. 1 , Pages: 40-50