This project aims to use data science with historical version of startup websites to identify when do they pivot to new strategies.

Firm strategies—what they choose to to do or not to do, and why—represent the main way in which firms shape the economy. In a time of widely encompassing platforms, corporate-led crypto currencies, activist CEOs, and socially-oriented corporations, characterizing how firms differ in their strategies, and in the choices they take, appears as important as ever. There is a need for tools to measure firm strategy.

As a student scholar, your role in this position would be to work in the nascent Measuring Strategy Lab, using natural language processing methods to devise new ways to understand and measure firm strategy. Specifically, using a large sample of startup websites downloaded through the Wayback Machine, develop systematic ways to understand when a startup is changing their strategy and why, and how does this predict their performance. This work builds also on the Startup Cartography Project, and is part of the ongoing efforts of bringing data science into strategy research.

This is an UNPAID research project.

Faculty Advisor

  • Professor: Jorge guzman
  • Center/Lab:
  • data science and startup strategy

Project Timeline

  • Earliest starting date: 9/6/21
  • End date: 5/1/22
  • Number of hours per week of research expected during Fall 2021: ~15
  • Number of hours per week of research expected during Summer 2022: ~20

Candidate requirements

  • Skill sets: data science, NLP, regression analysis.
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes
  • Additional comments: none