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1 – 10 of over 7000Yuting Rong, Shan Liu, Shuo Yan, Wei Wayne Huang and Yanxia Chen
Lenders in online peer-to-peer (P2P) lending platforms are always non-experts and face severe information asymmetry. This paper aims to achieve the goals of gaining high returns…
Abstract
Purpose
Lenders in online peer-to-peer (P2P) lending platforms are always non-experts and face severe information asymmetry. This paper aims to achieve the goals of gaining high returns with risk limitations or lowering risks with expected returns for P2P lenders.
Design/methodology/approach
This paper used data from a leading online P2P lending platform in America. First, the authors constructed a logistic regression-based credit scoring model and a linear regression-based profit scoring model to predict the default probabilities and profitability of loans. Second, based on the predictions of loan risk and loan return, the authors constructed linear programming model to form the optimal loan portfolio for lenders.
Findings
The research results show that compared to a logistic regression-based credit scoring method, the proposed new framework could make more returns for lenders with risks unchanged. Furthermore, compared to a linear regression-based profit scoring method, the proposed new framework could lower risks for lenders without lowering returns. In addition, comparisons with advanced machine learning techniques further validate its superiority.
Originality/value
Unlike previous studies that focus solely on predicting the default probability or profitability of loans, this study considers loan allocation in online P2P lending as an optimization research problem using a new framework based upon modern portfolio theory (MPT). This study may contribute theoretically to the extension of MPT in the specific context of online P2P lending and benefit lenders and platforms to develop more efficient investment tools.
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Apriani Dorkas Rambu Atahau and Tom Cronje
The purpose of this paper is to determine the impact of loan concentration on the returns of Indonesian banks and examines whether bank ownership types affect the relationship…
Abstract
Purpose
The purpose of this paper is to determine the impact of loan concentration on the returns of Indonesian banks and examines whether bank ownership types affect the relationship between concentration and returns.
Design/methodology/approach
This research uses heuristic measures of concentration: The Hirschman–Herfindahl index and Deviation from Aggregated Averages are applied to Indonesian banks across all sectors. The data covers the pre and post global financial crises periods from 2003-2011 for 109 commercial banks in Indonesia. Panel feasible generalised least squares analysis was applied.
Findings
The findings show that loan concentration increases bank returns. The positive effect of concentration on returns tends to be more significant for domestic-owned banks. In addition, the interaction effect shows that the positive effect of concentration on returns is less for foreign-owned banks.
Research limitations/implications
The Indonesian central bank changes to the reporting format of sectoral loan allocation by banks since 2012 in terms of the Indonesian Banking Statistics Details of Enhancement matrix requires separate data analysis for 2012 onwards. The findings of this paper could be enhanced by more detailed data like interest rate expenses and bank level sectoral non-performing loans data.
Practical implications
The findings suggest that a focus strategy provides better returns. Moreover, bank ownership types is an important factor to consider when setting a bank lending policy.
Originality/value
This paper is among the few studies where different measures of loan concentration in combination with measures of return are applied in Indonesia as an emerging Asian country. The research also provides evidence of the impact of concentration on the interest earnings of the loan portfolios of banks in addition to return on assets and return on equity that are generally applied as measures of return in previous research.
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Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18;…
Abstract
Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.
Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management…
Abstract
Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.
Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18;…
Abstract
Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.
Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18;…
Abstract
Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.
The purpose of this article is to determine the optimal use of collateral in order to maximize the borrower's wealth by reducing the interest rate payments. This analysis is to…
Abstract
Purpose
The purpose of this article is to determine the optimal use of collateral in order to maximize the borrower's wealth by reducing the interest rate payments. This analysis is to shed light on the fundamental question whether good or bad borrowers pledge more collateral.
Design/methodology/approach
The analysis bases on a simple firm value model similar to Merton's but with the additional feature that the borrower can bring in collateral. This article not only presents the case with perfect information between borrowers and lenders but also regards the consequences arising from asymmetric information.
Findings
A bad borrower, who is characterized by higher bankruptcy costs, riskier projects, and a lower contribution to the project value, typically pledges more collateral than a good borrower. These relationships base on the existence of perfect information between borrowers and lenders. If asymmetric information in terms of the project's riskiness or the contribution of the borrower to the project is present, these relationships invert and good borrowers tend to pledge more collateral. As a result, the allocation of information between a borrower and a lender is crucial for the optimal choice of collateral.
Research limitations/implications
This research underlines the potential for firms to add firm value by pledging collateral because collateral reduces interest rates and therefore results in more attractive terms of the loan. On the other hand, further empirical research can be done to verify our theoretical finding that under perfect information bad borrowers pledge more collateral, while under asymmetric information primarily good borrowers use collateral.
Originality/value
This paper introduces a new motive for the use of collateral and explains – in contrast to many other theoretical models – why bad borrowers tend to pledge more collateral.
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Steven Buck, Yoko Kusunose and Jeffrey Alwang
The purpose of this work is to experimentally measure trust and study its relationship to group loan allocation within a community bank.
Abstract
Purpose
The purpose of this work is to experimentally measure trust and study its relationship to group loan allocation within a community bank.
Design/methodology/approach
An artefactual field experiment is run to capture a measure of trust that mimics aspects of trusting behavior in a community bank. The experimental design and empirical setting take into account risk and altruism, two known confounders of trust measures. Regression analysis is used to estimate the relationship between a novel measure of trust and the loan amount a borrower receives from their rural community bank.
Findings
The trust measure has a statistically significant, positive relationship with loan size. A one standard deviation increase in the trust measure corresponds to a 13.3 percent increase in the loan amount.
Social implications
Results of the study suggest that, for community banks, trust in a borrower plays a large role in screening applicants and therefore determining loan size. Several such banks have considered graduating to commercial credit. However, given the outsize role of trust in lending decisions, it is not clear if commercial lending models – which rely less on social capital – will work.
Originality/value
A new trust game is developed that captures relationship-specific measures of directed trust that community bank members have towards each borrower. The trust measure is also context-specific as play in the game is analogous to how community bank members trust some borrowers (more than others) with larger loans. The emphasis on relationship- and context-specific trust measures is key to interpreting results from artefactual field experiments.
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Peter Davis Sumo, Xiaofen Ji and Liling Cai
Studies on textile upcycling in Africa are rare, particularly in Liberia, where extensive upcycling designs are appreciated throughout the country. This study aims to contribute…
Abstract
Purpose
Studies on textile upcycling in Africa are rare, particularly in Liberia, where extensive upcycling designs are appreciated throughout the country. This study aims to contribute to the upcycling literature from the perspective of Liberia’s fashion upcyclers by assessing their coping strategies and understanding the challenges confronting fashion upcycling in Monrovia’s four largest markets.
Design/methodology/approach
A fuzzy analytical hierarchy process and data envelopment analysis (DEA) models were used to assess labor input, delivery and flexibility, technological and innovation capability, financial capability, pricing of finished products, customer service and quality outputs of upcycled fashions. The fuzzy inference system model assessed upcyclers’ loaning eligibility.
Findings
The results highlight that Liberia’s fashion upcycling is expanding with varying innovative designs. The quality of upcycled fashions was deemed most important in the proposed AHP model. However, many upcycling businesses lack sufficient capital to make long-term investments. With the necessary investment, the innovation of these upcyclers could be a new line of fashion brands with great potential. In addition, using a fair judgment in assessing the little loaning funds available is paramount to enhancing their growth.
Research limitations/implications
Only 34 decision-making units were assessed. Future research could expand this scope using other models with more practical loaning strategies.
Originality/value
This study presents a wealth of managerial and policy implications. The proposed hybrid model is adequate for developing managerial decisions for fashion upcyclers. The proposed framework can manage ambiguity, inaccuracy and the complexity of making decisions based on numerous criteria, making it applicable in unearthing robust strategies for enhancing the fashion upcycling sectors and other industries in developing countries. In addition, the proposed fuzzy Mamdani system could also be extended to other sectors, such as agriculture, for a more transparent allocation of resources.