Machine Learning Strategies Fueling Economic Progress for Start-ups

Authors

  • Riya Sharma Graphic era deemed to be university Dehradun, India
  • Ambica P. Mani Graphic Era deemed to be university Dehradun, India
  • Sharon Christa Department of computer science and engineering MIT Art Design and Technology University Pune
  • Suma V. Dayananda Sagar College of Engineering Bengaluru, India
  • Aditya Pai H. Jain (Deemed to be University) Bengaluru, India

Keywords:

competitive advantage, financial performance, machine learning, predictive analysis, regression model, Start-up, statistical analysis, sustainable development goals

Abstract

Environmental concerns worldwide have propelled businesses towards adopting eco-friendly practices. However, determining the success of these efforts remains a challenge. Start-ups are emerging as pivotal drivers of sustainable innovation. Leveraging machine learning models for predictive analysis allows businesses to explore this relatively uncharted territory using historical data. This study employs machine learning techniques to conduct predictive analysis, specifically investigating the influence of sustainable business practices on financial performance. Examining data from 152 diverse start-ups, our research provides compelling evidence that the implementation of sustainable business practices significantly enhances financial performance. These practices not only confer a competitive advantage but also empower start-ups to thrive in dynamic business landscapes. The study integrates a regression-based model to predict financial performance in real-time when start-ups adopt sustainable practices. The developed regression model facilitates a comprehensive overview of start-up performance and insights into potential areas for improvement. Furthermore, our research establishes a correlation between financial performance and the intermediary role of competitive advantage, elucidating the intricate relationship between these variables. Sustainable business practices thus offer start-ups a competitive edge, enabling not only survival but also flourishing in volatile business environments. This research contributes valuable insights for entrepreneurs, governments, and academics, advocating for the widespread adoption of sustainable business practices among start-ups. The regression model serves as a practical tool for start-ups to assess their performance and strategize for future enhancements. The implications extend beyond immediate financial gains, emphasizing the imperative of integrating sustainability into the fabric of start-up operations for long-term success and societal benefit.

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Published

11.01.2024

How to Cite

Sharma, R. ., Mani, A. P. ., Christa, S. ., V., S. ., & H., A. P. . (2024). Machine Learning Strategies Fueling Economic Progress for Start-ups. International Journal of Intelligent Systems and Applications in Engineering, 12(11s), 414–427. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4462

Issue

Vol. 12 No. 11s (2024)

Section

Research Article

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