A Resource-Based Approach to Evaluating Technological Business Entities

Abstract

This research study provides a decision-support tool for technology sector investors. Grounded in the Resource-Based View (RBV), the research highlights how core resources, dynamic capabilities, and external synergies collectively influence firm performance. The research includes a rigorous review of nearly 200 peer-reviewed articles, identifying critical theoretical themes essential for developing the machine learning model, a process crucial for the development of the research model. Out of these, 80 articles have been selected for in-depth analysis. The findings outline steps for research model development, focusing on extracting leading themes to establish a robust theoretical foundation. The RBV framework emphasizes the importance of resources that are unique, valuable, non-replicable, and non-substitutable in driving competitive advantage. By integrating insights across venture capital, entrepreneurial ecosystems, disruptive business models, and technological capabilities, the research highlights the interplay between internal assets—such as financial capital, intellectual property, and R&D capabilities—and external factors like strategic alliances, mentorship, and institutional support. Dynamic capabilities, including managerial expertise and adaptability, are shown to be critical in leveraging these resources to navigate market uncertainties and foster innovation. The study concludes that the integration of these complementary elements not only enhances a firm's ability to innovate and disrupt markets but also ensures sustainable performance and long-term growth. This research offers a comprehensive framework for evaluating startup success and guiding strategic resource allocation.