Search results
1 – 4 of 4Evangelia Avgeri and Maria Psillaki
The research documented in this paper aims to examine multiple factors related to borrowers' default in peer-to-peer (P2P) lending in the USA. This study is motivated by the…
Abstract
Purpose
The research documented in this paper aims to examine multiple factors related to borrowers' default in peer-to-peer (P2P) lending in the USA. This study is motivated by the hypothesis that both P2P loan characteristics and macroeconomic variables have influence on loan performance. The authors define a set of loan characteristics, borrower characteristics and macroeconomic variables that are significant in determining the probability of default and should be taken into consideration when assessing credit risk.
Design/methodology/approach
The research question in this study is to find the significant explanatory variables that are essential in determining the probability of default for LendingClub loans. The empirical study is based on a total number of 1,863,491 loan records issued through LendingClub from 2007 to 2020Q3 and a logistic regression model is developed to predict loan defaults.
Findings
The results, in line with prior research, show that a number of borrower and contractual loan characteristics predict loan defaults. The innovation of this study is the introduction of specific macroeconomic indicators. The study indicates that macroeconomic variables assessed alongside loan data can significantly improve the forecasting performance of default model. The general finding demonstrates that higher percentage change in House Price Index, Consumer Sentiment Index and S&P500 Index is associated with a lower probability of delinquency. The empirical results also exhibit significant positive effect of unemployment rate and GDP growth rate on P2P loan default rates.
Practical implications
The results have important implications for investors for whom it is of great importance to know the determinants of borrowers' creditworthiness and loan performance when estimating the investment in a certain P2P loan. In addition, the forecasting performance of the model could be applied by authorities in order to deal with the credit risk in P2P lending and to prevent the effects of increasing defaults on the economy.
Originality/value
This paper fulfills an identified need to shed light on the association between specific macroeconomic indicators and the default risk from P2P lending within an economy, while the majority of the existing literature investigate loan and borrower information to evaluate credit risk of P2P loans and predict the likelihood of default.
Details
Keywords
Abstract
Details
Keywords
The purpose of this study is to identify the determinants of success in peer-to-peer (P2P) lending campaigns, especially amid global financial disruptions like the COVID-19…
Abstract
Purpose
The purpose of this study is to identify the determinants of success in peer-to-peer (P2P) lending campaigns, especially amid global financial disruptions like the COVID-19 pandemic. Addressing a notable gap in current research, we explore how factors such as firm uncertainty, loan characteristics (interest rates and maturity) and venture quality (human, social and intellectual capital) influence P2P lending effectiveness. Using multiple regression analysis on data from 523 projects on the October platform, our study aims to enhance the understanding and operational efficiency of P2P platforms, contributing to a more resilient financial ecosystem.
Design/methodology/approach
This study employs a quantitative research design using multiple regression analysis to examine the impact of specific variables on the success of P2P lending campaigns. Data were collected from 523 concluded P2P lending projects on the October platform, spanning from 2015 to 2021. Variables of interest include the level of uncertainty of the firm, loan characteristics such as interest rate and maturity and the quality of the venture assessed through human, social and intellectual capital. This method allows for a robust analysis of the factors contributing to the success of P2P lending within a dynamic financial context.
Findings
The findings of this study reveal that the success of P2P lending campaigns is significantly influenced by the level of uncertainty of the firm, the interest rate of the loan and the quality of the venture. Specifically, higher uncertainty in firms correlates negatively with campaign success, while competitive interest rates positively impact funding outcomes. Furthermore, ventures that demonstrate robust human capital, particularly those with management teams that possess diverse skills and high qualifications, tend to attract more funding. These results underscore the critical role of strategic financial and human resource planning in enhancing the effectiveness of P2P lending platforms.
Originality/value
This study contributes uniquely to the literature by integrating multiple variables – firm uncertainty, loan characteristics and venture quality – into a comprehensive analysis of success factors in P2P lending. It addresses the scarcity of research examining the combined effects of these factors, particularly in the context of global financial disruptions like the COVID-19 pandemic. By focusing on a specific European platform during a dynamic period, this research provides new insights into how P2P lending can adapt to and thrive amid financial crises. The findings offer valuable guidance for both practitioners and policymakers aiming to optimize P2P lending practices in uncertain economic landscapes.
Details
Keywords
Antonios Tiganis and Polymeros Chrysochou
Local food impacts tourist satisfaction and drives the choice of a tourist destination. However, it is not clear which attributes of local food products drive tourists’…
Abstract
Purpose
Local food impacts tourist satisfaction and drives the choice of a tourist destination. However, it is not clear which attributes of local food products drive tourists’ preferences. More specifically, little is known about potential segments in the tourist market. Acknowledging consumers’ divergent inclinations, we explore tourist preferences toward local food attributes through a market segmentation approach.
Design/methodology/approach
This study uses the Best-Worst Scaling method to examine the preferences of 311 tourists for attributes of local food products that are known to affect their choices. We employ a Latent Class Analysis to identify market segments with distinct preferences.
Findings
Results indicate that tourists prioritize taste, quality, authenticity, healthiness, connection to local culture and tradition and environmental friendliness over price, appearance, enhancement of local economy, availability and packaging. We further identify three segments: Sensory Seekers, Cultural Experiencers, and Price Conscious. The largest segment, Sensory Seekers, is driven by taste and quality attributes, while Cultural Experiencers prioritize connection to local culture and authenticity. The Price Conscious segment places a greater emphasis on price than the other segments. Cultural Experiencers demonstrate the highest willingness to pay for local food products.
Practical implications
The positioning of local products should target Cultural Experiencers. Agri-firms and state agencies promoting a tourist destination internationally can also use the connection to local culture and authenticity in their marketing campaigns.
Originality/value
Our research contributes to food marketing literature by showing which local food attributes drive tourist preferences. Moreover, we uncover unobservable heterogeneous preferences among tourists.
Details