EconPapers    
Economics at your fingertips  
 

Predicting the success of seed-stage startups to enter the acceleration program and receive seed money

Navid Mohammadi and Maysam Shafiee

International Journal of Entrepreneurial Venturing, 2022, vol. 14, issue 2, 168-201

Abstract: The accelerators, like any other business, are looking for success and an acceptable return on investment. This research aims to reduce the risk of these decisions by providing a framework to evaluate startups in their pre-launch period and select startups to enter the acceleration and receiving seed money that are most likely to succeed. For this purpose, the Delphi fuzzy method is used to finalise the criteria, the affinity diagram, which is one of the design thinking tools, is used to model the framework and the best worst method (BWM) is to weight the framework criteria. Finally, the four startups present in the NextEra accelerator pre-launch period in Iran have been studied and evaluated. The most important criteria in this framework are including the technical feasibility of the idea, team skills, knowledge level, characteristics of a lead entrepreneur, the culture of cooperation, and commitment of the members in achieving the goals.

Keywords: new venture success; startup; seed accelerator; best worst method; BWM; affinity diagram; design thinking. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=122654 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijeven:v:14:y:2022:i:2:p:168-201

Access Statistics for this article

More articles in International Journal of Entrepreneurial Venturing from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijeven:v:14:y:2022:i:2:p:168-201