Network Analysis of DICE Community

Abstract

This study explores how entrepreneurship education (EE) fosters effective networking for venture creation among pre-career students. Prior research has focused primarily on professional entrepreneurs and MBA students, leaving a gap in understanding how students with limited initial networks can build essential entrepreneurial connections. Grounded in the "network success hypothesis," which posits that access to key resources impacts venture creation more than network size or diversity, this study tracks the networking patterns and venture outcomes of students from a Japanese university's pre-career EE program. Using network analysis and multinomial logistic regression on survey data from 135 alumni, we examined the roles of network structure and strategic networking in students' venture progress. Network analysis results indicate that broad acquaintance networks did not correlate with venture advancement; targeted connections to influential individuals significantly contributed to venture creation. Regression analysis further highlights continuous engagement with individuals who serve as connectors to key resources and opportunities proved critical for advancing students' business. These results underscore the value of incorporating well-connected mentors in EE, suggesting a design in EE towards strategic mentorship and resource-accessible networks for students. In addition, we contribute to EE evaluation by providing insights into the longitudinal development of pre-career students' entrepreneurial networks.

Questionnaire

• Basic Information
  • Grade
  • Recommendation
  • Semester (divided into semesters with classes and semesters without classes)
  • Experience as a Bridging Tutor (BT)
  • Laboratory
  • Presence of people starting a business in the laboratory
  • Experience as a working adult
• Graduate School (for those applicable)
  • Graduate School
  • Major
  • Major in Master's and Laboratory (for those in the doctoral program whose current major differs from the major in the master's program)
• Undergraduate
  • Department of the first period (for universities other than the University of Tokyo where there is no distribution of advancement guidance, write the name of the university in other)
  • Department of the second period
  • Department
  • Course / Sub-discipline
• Additional Information
  • Presence of a person who has started a business within two degrees of separation?
  • Specialty field
  • Field of interest
  • Current research
  • Research achievements (conferences, journals, grants, etc.)
  • Experience in acquiring patents
  • What you were working on in high school / technical college in the fields of deep tech, information technology, and business, whether or not you have been awarded
  • What you were working on during your university days and details (science contests that develop, competitive programming, information technology-related courses other than lectures, research experience before being assigned to the main laboratory, internship experience, business contest experience, multiple selections from others)
  • Affiliated community
• Business
  • Business history
  • Business attributes (basic research-type DeepTech, development-type DeepTech, AI / software, selection from non-technical fields)
  • Business area (space, robotics, IT hardware, environment / energy, materials, drug discovery, agriculture, medicine, agriculture, AI. Software, multiple selections from others)
  • When did you work on the business (before the lecture, after the lecture)
  • Did the lecture help with business creation?
  • What helped and how
  • If you did not take the lecture and did not join DICE, do you think you could have proceeded with the business?
  • If you only took the lecture and did not join DICE, would you be doing your current business (/ activities aimed at business creation)?
  • How did you connect with the business members?
  • Amount of funds raised
  • Subsidies
  • Equity finance
  • Debt
  • Annual sales
  • Do you have someone like a mentor (role model or someone you often consult with) when working on the business (multiple answers allowed)
• Lecture
  • Did you make a final presentation in the lecture?
  • How did you team up?
  • People who took care of you in the lecture activities (multiple answers allowed)
  • People you are still taking care of
• Future Career
  • When do you want to be involved in a DeepTech startup by August 2024?
• About DICE (Alumni)
  • Priority of DICE in the community you belong to
  • What helped in DICE activities / business creation (multiple choice)
  • How to use DICE
  • Changes before and after joining DICE
• Networking
  • Number of people around you who have started a business
  • People you communicate with on a regular basis (guideline of once a week or more. Select from alumni members)
  • People who know more than acquaintances (guideline of knowing what they are doing. Select from alumni members)
  • People you have asked for an introduction (select from alumni members)
  • People who have asked you for an introduction (select from alumni members)