TY - JOUR
T1 - Success factors in peer-to-business (P2B) crowdlending
T2 - A predictive approach
AU - Moreno-Moreno, Antonio M.
AU - Sanchis-Pedregosa, Carlos
AU - Berenguer, Emma
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Peer-to-Business (P2B) crowdlending is gaining importance among companies seeking funding. However, not all projects get the same take-up by the crowd. Thus, this study aims to determine the key factors that drive non-professional investors to choose a given loan in an online environment. To this purpose, we have analyzed 243 crowdlending campaigns on October.eu platform. We have obtained a series of variables from the analyzed loans using logistic regression. Results indicate that loan amount, loan term and overall credit rating are the key predictors of non-professional lender P2B crowdlending success. These findings may be useful for predicting whether the crowd will subscribe to a loan request or not. This information would help businesses to modify specific loan characteristics (if possible) to make their loans more attractive or could even lead companies to consider a different financial option. It could also help platforms select and adapt project parameters to secure their success.
AB - Peer-to-Business (P2B) crowdlending is gaining importance among companies seeking funding. However, not all projects get the same take-up by the crowd. Thus, this study aims to determine the key factors that drive non-professional investors to choose a given loan in an online environment. To this purpose, we have analyzed 243 crowdlending campaigns on October.eu platform. We have obtained a series of variables from the analyzed loans using logistic regression. Results indicate that loan amount, loan term and overall credit rating are the key predictors of non-professional lender P2B crowdlending success. These findings may be useful for predicting whether the crowd will subscribe to a loan request or not. This information would help businesses to modify specific loan characteristics (if possible) to make their loans more attractive or could even lead companies to consider a different financial option. It could also help platforms select and adapt project parameters to secure their success.
KW - Crowdfunding
KW - crowdlending
KW - institutional lenders
KW - logistic regression
KW - non-professional lenders
KW - peer-to-business (P2B)
KW - Crowdfunding
KW - crowdlending
KW - institutional lenders
KW - logistic regression
KW - non-professional lenders
KW - peer-to-business (P2B)
UR - http://www.scopus.com/inward/record.url?scp=85077753841&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2019.2946858
DO - 10.1109/ACCESS.2019.2946858
M3 - Article in a journal
SN - 2169-3536
VL - 7
SP - 148586
EP - 148593
JO - IEEE Access
JF - IEEE Access
M1 - 8864063
ER -