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The purpose of this paper is to test the effect of informal finance and trade credit on the performance of private firms.

Based on a survey to private firms in 19 cities, the paper empirically tests the promoting effects of informal finance and trade credit on the performance of private firms in China.

It was found that informal finance and trade credit have positive effects on private firms' performance measured by ROA. The net income reinvestment rate of private firms is positively related to whether or not the firm adopts informal financing or trade credit financing. A private firm having limited access to formal finance is more inclined to rely on self‐funds and is more limited by financing choices. Informal financing and trade credit can relieve the tension of cash flow chain but cannot solve the financing constraints. The empirical results also show that bank credit is still not the main financing choice for private firms and has not yet played a promoting role in private firms' performance and growth. Informal finance is more important to promote performance in manufacturing industry, while trade credit is more effective in wholesale and trading industry. The results show the coexistence viability of informal financing channels and formal financial institutions in China.

The policy implication is the Chinese Government should take careful steps to regulate informal financing sources.

After some theoretical literature, such as Lin and Sun, this paper explores for the first time the effect of informal financing channels on the performance of private firms.

The purpose of this paper is to expand the investor sentiment’s effect on investment efficiency to the layer of “credit financing,” studying whether investor sentiment can affect credit financing level and the inner mechanism of the effect.

The authors obtain firm-level data from the Shanghai and Shenzhen stock markets and using panel estimation techniques examine whether investor sentiment can affect credit financing level and the inner mechanism of the effect.

This paper finds that credit financing plays the role of partial media in the process of investor sentiment affecting investment efficiency. Based on the funds increasing effect, with the high-investor sentiment and increasing credit financing, corporations alleviate the financing constraints, but also provide a convenient for the abuse of corporate funds. So, investor sentiment positively associates with enterprises’ overinvestment, while investor sentiment negatively associates with enterprises’ underinvestment. Relying on the particular system background and property right environment in China, this paper finds that investor sentiment has an effect on the overinvestment of state-owned enterprises and the underinvestment of private enterprises through credit financing channel, while it does not function in the overinvestment of private enterprises. The reason of the difference is that under the soft budget constraint in the country, the credit preference of state-owned enterprises and the creditor’s rights management of banks are partially absent.

By fusing the special financial environment and institutional background, this thesis further includes in the analysis frame the difference in governance effect by credit financing between state-owned and privately owned listed companies, and further analyzes the difference in impact on investment efficiency in enterprises of different natures after investor sentiment has affected enterprise credit financing.

This paper has verified the constraint assumption and deepened the research work on bank credit supply and answered practical questions such as whether the banks in the country exercise supervision function over the listed companies and on which kind of listed companies the supervision function plays a more effective role.

As an unofficial substitution mechanism, bank-enterprise relationship can elevate the investment efficiency by private owned enterprises. Based on the timely research results on credit financing, reference is provided for private listed companies to utilize investor sentiment to improve its investment efficiency.

This paper has proved the specific path which creates the dual effects on resources allocation by investor sentiment, that is, the intermediary transmission in credit financing, clarifying the mechanism of action by which investor sentiment affects the efficiency of enterprise investment and making incremental contribution to the research of how investor sentiment affects the efficiency of enterprise investment.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

The purpose of the study is to investigate the financing channels and carbon emission abatement preferences of supply chain members, and further examine the optimal contract design of the retailer.

This paper develops a low-carbon supply chain composed of one retailer and one manufacturer, in which the retailer provides trade credit to the manufacturer. Considering the cap-and-trade regulation, the manufacturer with uncertain yield makes decision on whether to invest in emission abatement. There are bank loan and trade credit to finance production for the manufacturer and green credit to finance emission abatement investment. Meanwhile, the retailer may provide the manufacturer with three kinds of contracts to improve emission abatement efficiency, namely, revenue sharing, cost sharing or both sharing.

The results show that the retailer prefers to offer financing service at lower interest rate, but trade (and green) credit financing is always optimal for manufacturer and supply chain. The investment in emission abatement is value-added to all players. The sharing contracts offered by the retailer at lower sharing ratios can realize Pareto improvement of the system regardless of the financing scheme. However, comparing with the revenue or cost sharing contract, the existence of optimal sharing ratios makes the both sharing contract more favorable to the retailer.

The findings provide guidance for the emission-dependent manufacturer in financing and emission abatement decisions, as well as recommendations for the retailer to offer loan service and sharing contract.

This paper integrates green credit into bank loan or trade credit to analyze the financing decision of the manufacturer with uncertain yield and further considers the influence of three kinds of sharing contracts introduced by the retailer on improving operational performance.

The review examines the existing literature on blockchain-based small and medium enterprise (SME) finance and highlights its trend, themes, opportunities and challenges. Based on these factors, the authors create a framework for the existing literature on blockchain-based SME financing and lay down future research paths.

The review follows a systematic approach. It includes 53 articles encompassing multiple dimensions of blockchain-based SME finance, including peer-to-peer lending platforms, supply chain finance (SCF), decentralized lending protocols and tokenization of assets. The review critically evaluates these approaches' theoretical underpinnings, empirical evidence and practical implementations.

The review demonstrates that blockchain-based SME finance holds significant promise in addressing the credit gap by leveraging blockchain technology's decentralized and transparent nature. Benefits identified include reduced information asymmetry, improved access to financing, enhanced credit assessment processes and increased financial inclusion. However, the literature acknowledges several challenges and limitations, such as regulatory uncertainties, scalability issues, operational complexities and potential security risks.

The article contributes to the growing knowledge of blockchain-based SME finance by synthesizing and evaluating the existing literature. It also provides a framework for the existing literature in the area and future research paths. The study offers insights for researchers, policymakers and practitioners seeking to understand the potential of blockchain technology in filling the SME credit gap and fostering economic development through improved access to finance for SMEs.

A potential farm policy concern is that if nontraditional (vendor/point-of-sale) financing represents increased risk, it may have an aggregate effect on sector-wide farm financial risk. This analysis examines the use of nontraditional lender credit among borrowers in the US Department of Agriculture (USDA)'s Farm Service Agency (FSA)'s direct farm loan programs.

Data source included the USDA FSA direct operating loan program for 2011–2020. A Cox proportional hazards model was used to estimate the occurrence of default over seven-year term direct operating loans.

Results indicated that point-of-sale financing has a significant and positive relationship with risk for FSA direct operating loan borrowers. The presence of intermediate point-of-sale financing (mostly from machinery and equipment vendors) is associated with an increased probability of default of 9%, and the presence of such loan balances in the amount of $50,000 or more had a higher probability of default of 21%. Short-term nontraditional financing (for example from fertilizer vendors) was found to be positively related to borrower risk of default as indicated by a 22–25% increase in the likelihood of loan default.

Through FSA Farm Business Plan data, the authors were able to distinguish specific vendors and their loan purpose, which advances the knowledge beyond what is currently available through survey data. Findings indicate a minor increase in borrower risk for those with intermediate-term nontraditional financing. However, borrowers with short-term nontraditional financing and having large balances or greater number of nontraditional loans had increases in risk of default by substantive amounts.

The purpose of this paper is to examine the status of small-business lending following the recession.

The authors survey the literature and analyze recent surveys of small-business lending.

The results reinforce the importance of owner equity as a primary source of small-business financing. In addition, the authors find that small firms have been seeking and obtaining less capital since the 2008 financial crisis.

The findings about the main sources of small-business financing will be informative when formulating financial regulation.

The available evidence suggests that new regulation of the financial services industry may be restricting access to products that small-business owners rely on and may adversely affect small banks.

The authors offer the most recent analysis of small-business financing, focusing on changes that may have been caused by the recession and major financial regulations.

This chapter shows how to identify the characteristics of borrowers that are part of a credit scoring model. The credit risk scoring model is an important tool for evaluating credit risk associated with customer characteristics that affect defaults. This research was conducted at a financial institution, a subsidiary of a commercial bank in Indonesia, to answer the challenge of determining the feasibility of providing financing quickly and accurately. This model uses a logistic regression method based on customer data with indicators of demographic characteristics, assets, occupations, and financing payments. This study identifies nine variables that meet the goodness of fit criteria, which consist of WOE, IV, and p-value. The nine variables can be used as predictors of default probability: type of work, work experience, net finance value, tenor, car brand, asset price, percentage of down payment (DP), interest, and income. The results of the study form a risk assessment model to identify variables that have a significant effect on the probability of default.

Existing literature demonstrates the important role of information transparency in enterprise development and market surveillance. However, little empirical research has examined the information transparency effect in supply chain management. This study aims to fill this gap by exploring the significant role of information transparency on supply chain financing and its mechanism, taking trade credit as the starting point.

From the data set comprising 3,880 Chinese firms with A-shares listed on the Shenzhen and Shanghai Stock Exchanges from 2011 to 2020, we obtain the basic picture of information transparency and trade credit. Panel fixed effects regression is used to test the hypotheses concerning the antecedents to trade credit.

The empirical results show that: first, information transparency can significantly support corporate access to trade credit and is found to facilitate financing by mitigating perceived risk. Second, among companies with higher levels of financing constraints, weaker market power and more concentration of suppliers, information transparency promotes trade credit more markedly. Third, the outbreak of COVID-19 causes a substantial increase in uncertainty and risk in external circumstances and then the effect of information transparency is weakened. Fourth, the contribution to trade credit is likely to be stronger for disclosures containing management transparency elements compared to single financial transparency.

To the best of our knowledge, this study is one of the first to explore the positive role of information transparency to supply chain financing, which to a certain extent makes up for the lack of information transparency research in the supply chain. It provides new ideas for enterprises to obtain trade credit financing and promote the improvement of supervision departments’ disclosure policies.