EntSciLab | From Data to Actionable Knowledge
Welcome to the Computational Enterprise Science Lab Website!
Rahul C. Basole, Professor, Director, Georgia Institute of Technology, Stanford University, Tennenbaum Institute, College of Computing, School of Interactive Computing, PhD, Visualization, Analytics, Ecosystem
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From Data to Actionable Knowledge.

Research Areas

We apply and advance knowledge in interactive computing, systems engineering, and management science to solve complex enterprise issues.

Data Visualization

We design, improve & implement novel visual representations + interactions

Anticipatory Analytics

We innovate, develop & apply novel analytical tools + methods.

Strategy & Decision Support

We study, create & evaluate emerging strategy + decision support systems.

Enterprise Transformation

We study & develop computational solutions for enterprise transformation.

Projects

Research Highlight

Visualizing Startup Ecosystems

Much research on entrepreneurial ecosystems has focused on venture creation, strategy, and growth. However, little is known about variation in strategic positioning — how firms present technologies and products to key stakeholders including customers, employees, and investors — within and across global entrepreneurial ecosystems. While strategic positioning is important for established companies, it is particularly critical for entrepreneurial ventures, which face a difficult trade-off in balancing legitimacy through similarity versus innovativeness through differentiation. Using a computational approach based on data mining, text analytics, and network visualization, we provide insights into the structure of strategic positioning of nearly 60,000 companies in 35 global entrepreneurial ecosystems. Our study makes several important contributions. First, by examining strategic positioning statements of geographically defined ventures, we contribute and advance our understanding of the geography of innovation and structure of entrepreneurial ecosystems. Our results indicate that there are wide differences in entrepreneurial ecosystem size, structure, diversity, and positioning. Second, methodologically we use novel computational approaches and introduce visualization as a powerful means to understand entrepreneurial ecosystems. Third, our results show that ventures from widely different industries actually often use similar position statements, thus highlighting that ecosystems are indeed not just defined by industries but also strategic positioning.

The Similarity Network of Entrepreneurial Ventures in Silicon Valley
The Similarity Network of Entrepreneurial Ventures in Silicon Valley
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Publications

4051

FIFA Games Played

6

Alumni

431782

Cumulative Skymiles

Supporters & Partners

Our research is enabled by generous support of different partners and supporters.