Purpose – The purpose of this paper is to study the effects of multidimensional friendship networks on economic outcomes in the domain of online people-to-people (P2P) lending markets. Design/methodology/approach – The empirical analysis is based on the data set of transactions and friendship networks from PPDai.com market, the most prominent P2P lending market in China. A friendship hierarchy is proposed in this paper to conceptualize friendship network types. Furthermore, methodologies of t-test, logistic regression and ordinary least squares regression are implemented to measure the impact of multidimensional friendship network variables on the probability of successful funding, as well as the interest rates on funded loans. Findings – The study demonstrates significant effects of structural, relational and cognitive friendship networks using PPDai.com data. The results indicate that structural friendship network measured in terms of the number of friendship ties is a significant factor of funding performance. Additionally, borrowers, who are involved in higher-quality friendship networks, are more likely to be funded and pay lower interest rates on funded loans. Also, the deeper the level of the relationship is in the friendship hierarchy, the more significant will be the effect of friendship on the final economic results. Furthermore, quality is more important than quantity in determining funding performance. Originality/value – This paper is the first to study the effects of multidimensional friendship networks on economic outcome variables in the domain of online P2P lending, thus broadening the theory of multidimensional social capital, which can deepen our understanding about how social networks work and have significant implications practically and theoretically.

In online P2P lending market, borrowers need to make strategic decisions, which will determine they will get the loans or not. In this study, we firstly investigate what and how the decisions made by borrowers influence the auction results. The empirical results display that borrower' decisions, e.g., loan amount, interest rate will determine whether she could successfully fund loan or not, especially loan amount requested by borrowers. Then, it is focus on analyzing the difference of two borrower's critical decisions (loan amount and interest rate) among successful, unsuccessful capable and incapable listings, and find out that borrowers of three types of listings make heterogeneous decisions. Finally, we provide some suggestions to online P2P lending market about borrowers' decisions aid services based on the results, which could be a contribution with the practical implementation of borrower decision support system.

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