Title of article :
Does Fundraising Have Meaningful Sequential Patterns? The Case of Fintech Startups
Author/Authors :
Khajehpour ، Houman Department of Information Technology Management - Faculty of Management - Kharazmi University , Sadatrasoul ، Mahdi Department of Information Technology Management - Faculty of Management - Kharazmi University , Yousefi Zenouz ، Reza Department of Information Technology Management - Faculty of Management - Kharazmi University
Abstract :
Nowadays, fundraising is one of the most important issues for both Fintech investors and startups. The pattern of fundraising in terms of “number and type of rounds and stages needed” are important. The diverse features and factors that could stem from Fintech business models which can influence success are of the key issues in shaping these patterns. This study applied the top 100 KPMG Fintech startups’ data to extract clusters and fundraising pattern using sequential pattern discovery for each cluster. This led to the extraction of seven distinct clusters using 3 different clustering algorithms from 3 to 7 different rounds of investment for each cluster. The proposed frequent patterns can assist both investors and Fintech startups to show the future fundraising pattern based on their new or current startup cluster type and the ongoing stages of development.
Keywords :
Fundraising , Fintech , Venture capital , Clustering , sequential pattern recognition
Journal title :
Iranian Journal of Management Studies (IJMS)
Journal title :
Iranian Journal of Management Studies (IJMS)