Influence of Entrepreneurial Characteristics on the Performance of MSMEs in Gautam Buddha Nagar
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2026.17.1.13Keywords:
Entrepreneurial Characteristics, MSME Performance, Gautam Buddha Nagar, Risk-Taking, Innovation, Quantitative AnalysisDimensions Badge
Issue
Section
License
Copyright (c) 2026 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Background: Micro, Small, and Medium Enterprises (MSMEs) are seen as the principal source of economic progress in the world regardless of the economic level of the country. The traits and behaviors of entrepreneurs are the ones that have the most impact on the performance of MSMEs in an environment that is growing more competitive and uncertain. Nevertheless, there is still a lack of empirical evidence that investigates this relationship in specific regional contexts.Abstract
Objective: The research was conducted to investigate the influence of entrepreneurial traits on the performance of MSMEs in Gautam Buddha Nagar, an area of Uttar Pradesh that is quickly turning into an industrial hub.
Methodology: The quantitative approach was used in the study. A structured questionnaire was used to obtain primary data from 400 MSME owners, founders, and managers. A 5-point Likert scale going from Strongly Agree to Strongly Disagree was used to determine both entrepreneurial traits and MSME performance. The relationship between entrepreneurial traits and MSME performance indicators was evaluated through correlation and regression analyses.
Results: The research results showed a robust and significant positive connection between the traits of entrepreneurs and the performance of MSMEs. The improvement in customer satisfaction, the rise in employee productivity, the increase in profits, and the better sales growth were all linked to the stronger entrepreneurial orientation.
Implications: The research offers beneficial insights to policy makers, industry players, incubators, and would-be entrepreneurs. The conclusions can assist in the creation of specific training programs, financial support, and government measures that form the basis of entrepreneurial skills and improve MSME’s performance, finally leading to the advancement of the local economy’s endurance and innovation through the community.
How to Cite
Downloads
Similar Articles
- Subna MP, Kamalraj N, Human Activity Recognition through Skeleton-Based Motion Analysis Using YOLOv8 and Graph Convolutional Networks , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- Nida Syeda, Kishore Selva Babu, Exploring the role of digital humanities in the centralization of knowledge production: Clusters, networks, or echo chambers , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- V. Manibabu, M. Gomathy, Data Quality Management and Risk Assessment of Dairy Farming with Feed Behaviour Analysis Using Big Data Analytics with YOLOv5 Algorithm , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- R. Gomathi, Balaji V, Sanjay R. Pawar, Ayesha Siddiqua, M. Dhanalakshmi, Ravi Rastogi, Ensuring ethical integrity and bias reduction in machine learning models , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Ravi Kumar P, C. Gowri Shankar, Optimizing power converters for enhanced electric vehicle propulsion: A novel research methodology , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Selva Kumar D, Revisiting the challenges of disinvestment practices and central public sector enterprises (CPSEs): Indian empirical evidence , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Vijai Pillarsetti, K. Madhava Rao, The craft of portfolio construction in estate planning: A comprehensive review on equity and mutual fund strategies, and its risks , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Arvind K Shukla, Balaji V, Dharani R, M Ananthi, R Padmavathy, Romala V. Srinivas, Precision agriculture predictive modeling and sensor analysis for enhanced crop monitoring , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- S Selvakumari, M Durairaj, Performance Analysis of Deep Learning Optimizers for Arrhythmia Classification using PTB-XL ECG Dataset: Emphasis on Adam Optimizer , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- Kumari Sandhiya, Ashwani Pandey, Ruchi Sharma, Kaneez Fatima, Rukhsar Parveen, Naveen Gaurav, Assessment of Phytochemical and Antimicrobial Activity of Withania somnifera (Ashwagandha) , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.

