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The purpose of this study is to empirically assess the relationship between the dimensions of creditworthiness and access to finance of small and medium-sized enterprises (SMEs) in Malaysia, with creditworthiness as the mediating variable. The lack of empirical research on the relationship between creditworthiness and access to finance forms the motivation of this study.

Questionnaires covering various characteristics of the firms, their access to finance and creditworthiness were distributed to a total of 456 SMEs in the Kuala Lumpur and Selangor region for this purpose. A total of 158 responses were returned, of which 145 were usable responses and the relationships are tested using SEM-PLS.

This study finds that an SME and its owner’s character have significant influences on access to finance. An SME’s condition and its ability to provide high quality collateral are found to be highly significant in influencing its access to finance. Capacity is significant but its significance is low, while capital is insignificant. Creditworthiness has a significant positive influence on access to finance.

This study contributes to the important yet under-researched issue of access to finance for SMEs. It highlights the issue of character of applicant as an important dimension of creditworthiness that can significantly influence access to finance for SMEs.

This study seeks to explore developments in corporate creditworthiness before and after ownership events.

The paper uses the Blockholders database of Dlugosz, Fahlenbrach, Gompers, and Metrick, and three credit quantities, and deploys a standard event study methodology to examine the relation to corporate creditworthiness.

The paper discovers that ownership‐construction is generally associated with prior‐ and post‐improvement in creditworthiness, while a block‐destruction is typically surrounded by deterioration in corporate creditworthiness. The paper also finds proper evidence for a relation between the construction or destruction of managerial block and future developments in corporate creditworthiness. The paper further realizes that outside shareholders exhibit higher impact than inside block‐holders on later variations in credit risk.

The paper is unable to conduct further robustness checks with structural credit methodologies due to the reduced number of valid observations.

Market participants can utilize the conclusions to better predict future trends in corporate creditworthiness.

This study investigates the influence of inter-firm linkages between small and medium enterprises (SMEs) and large firms on the relationship between an SME's creditworthiness and its access to finance.

Survey questionnaire was distributed to 456 SMEs in the manufacturing sector in the Selangor and Federal Territory of Kuala Lumpur regions and a total of 145 useable responses were gathered. Investigation into the possible differences in the effect of creditworthiness – and its dimensions – on access to finance for SMEs with and without linkages are examined using Partial Least Squares-Multi Group Analysis (PLS-MGA).

It is found that the relationship between creditworthiness and access to finance is significant for both SMEs with and without links to large firms. However, no significant difference is found in the effect of creditworthiness on access to finance for both types of SME. Further analysis on the five different dimensions of creditworthiness shows statistically significant differences between SMEs with links and those without for the dimensions of collateral and condition. This implies that alliances formed between SMEs and large firms do not have much of an influence on the overall creditworthiness but do influence the collateral and condition of the SME.

This study contributes to the understanding of the effects of interfirm linkages on SME creditworthiness and access to finance. To the authors' knowledge no such study has been conducted on links between SMEs and large firms, especially in a developing country such as Malaysia.

The purpose of this study is to determine the impact of environment, social and governance (ESG) disclosure on credit ratings of companies in India.

Firms under study are listed on the Bombay Stock Exchange (BSE) 500 and represent almost 93 per cent of the total market capitalization on BSE. This study considers a sample of 122 firms from a population of 500 to examine the relationship between ESG scores and Credit Rating. The scope of this study is confined to those firms listed on the S&P BSE 500 which have made ESG disclosures and were rated by various credit rating agencies like Crisil, ICRA and CARE. Data were sourced from Bloomberg. Ratings were given in ascending order. In the first model, credit rating was used as predicted variable; ESG score as predictor variable and market capitalization, net debt to equity, and total debt to asset as control considering the ordered nature of dependent variable in the study, ordered logistic regression was applied. It was repeated taking individual scores on environment rating, social rating and governance rating as predictors. The authors further segregated the 122 selected firms into large, medium and low capital firms and assessed separate logistic regression models taking credit rating as the predicted variable and overall ESG score as the predictor.

It was found that overall ESG performance and performance of individual components (environment, social and financial variables such as market capitalization, and debt to equity ratio) had significant positive indicators of creditworthiness as measured through credit rating. Governance score had a positive and insignificant relation with credit rating. Market capitalization was observed to have significant direct relationship with credit worthiness. On the other hand, number of independent directors in companies showed significant inverse relationship with creditworthiness. ESG significantly impacted credit rating in the desired direction only for small- and middle-level firms; for large firms which already had higher credit rating, ESG showed no effect. It was also found that credit rating itself determined significantly the extent of overall ESG reporting and disclosure of its components.

This is unique study that covers the aspects of ESG reports and its impact on credit rating.

Bank creditworthiness refers to the evaluation of a bank’s ability to meet its financial obligations. It is an assessment of the bank’s financial health, stability and capacity to manage risks. This paper aims to investigate the credit rating patterns that are crucial for assessing creditworthiness of the Islamic banks, thereby evaluating the stability of their industry.

Three distinct machine learning algorithms are exploited and evaluated for the desired objective. This research initially uses the decision tree machine learning algorithm as a base learner conducting an in-depth comparison with the ensemble decision tree and Random Forest. Subsequently, the Apriori algorithm is deployed to uncover the most significant attributes impacting a bank’s credit rating. To appraise the previously elucidated models, a ten-fold cross-validation method is applied. This method involves segmenting the data sets into ten folds, with nine used for training and one for testing alternatively ten times changeable. This approach aims to mitigate any potential biases that could arise during the learning and training phases. Following this process, the accuracy is assessed and depicted in a confusion matrix as outlined in the methodology section.

The findings of this investigation reveal that the Random Forest machine learning algorithm superperforms others, achieving an impressive 90.5% accuracy in predicting credit ratings. Notably, our research sheds light on the significance of the loan-to-deposit ratio as a primary attribute affecting credit rating predictions. Moreover, this study uncovers additional pivotal banking features that intensely impact the measurements under study. This paper’s findings provide evidence that the loan-to-deposit ratio looks to be the purest bank attribute that affects credit rating prediction. In addition, deposit-to-assets ratio and profit sharing investment account ratio criteria are found to be effective in credit rating prediction and the ownership structure criterion came to be viewed as one of the essential bank attributes in credit rating prediction.

These findings contribute significant evidence to the understanding of attributes that strongly influence credit rating predictions within the banking sector. This study uniquely contributes by uncovering patterns that have not been previously documented in the literature, broadening our understanding in this field.

This manuscript reports evidence on how debt-taking decisions of top management in a multi-country setting do affect credit rating scores assigned by credit rating agencies (CRAs) as global monitors of creditworthiness of borrowers. This aspect has been long ignored by researchers in the literature. The purpose of this paper is twofold. A test model is specified first using theories to connect debt-taking behavior to credit rating scores. Once that model helps to identify a number of statistically significant factors, the next step helps to identify threshold values at which the variables driving debt-taking behavior would worsen the credit rating scores as turning points of the thresholds.

The study identifies factors driving creditworthiness scores due to debt-taking behavior of countries and develops a correct research design to identify a model that explains (1) credit rating scores and the factors driving the scores and runs (2) panel-type regressions to test model fit. Having found factors driving debt-taking behavior by observed units, the next step identifies threshold values of factors at which point further debt-taking is likely to worsen credit rating risk of the observed units. This is a robustness test of the methodology used. The observed units are 20 countries with data series across 14 years.

First, new findings suggest there are about six major factors associated with debt-taking behavior and credit rating changes. Second, the model developed in this study is able to account for substantial variability while the identified factors are statistically significant within the normal p-values for acceptance of hypotheses. Finally, the threshold values of factors identified are likely to be useful for managerial decisions to judge the levels at which further debt-taking would worsen the credit rating scores of the observed units.

The observed units are from 20 countries over 14 years of annual data available on credit rating scores (privately obtained from Standard and Poor [S&P]). The sample represents major economies but did not include emerging countries. In that regard, it will be worthwhile to explore the debt-taking behavior of emerging economies in a future study using the methodology verified in this study.

The findings help add few useful guidelines for top management decisions. (1) There are actually factors that are associated with debt-taking behavior, so the authors now know these factors as guides for managerial actions. (2) The authors are free to state that the credit rating changes occur on objective changes in the factors found as significantly related to the debt-taking behavior. (3) The threshold values of key factors are known, so top management could use these threshold values of named factors to monitor if a debt-taking decision is going to push the credit rating to a worse score.

There are society-wide implications. Knowing that the world's debt level is high at US$2.2 for each gross domestic product (GDP) dollar across almost 200 countries, any knowledge on what factors help drive creditworthiness scores, thus credit riskiness, is revealed in this paper. Knowing those factors and also knowing the turning points of the factors – the threshold values – likely to worsen creditworthiness scores is a powerful tool for controlling excessive debt-taking by an observation unit included in this study (The dataset in this research can also be used to see inter-temporal movement on debt-taking in a future study).

In the authors' view, there are many studies on debt-taking behavior. But none has connected debt-taking on how (1) named factors are observable to management that affect credit rating changes and (2) if a factor affects creditworthiness, at which point of the factor value, the creditworthiness will flip to worsen the score. These aspects are seldom found in the literature. Hence, the paper is original with practical value at the global level.

The creditworthiness of corporates is most visible in credit ratings. This paper aims to present an alternative credit rating measure independently of credit rating agencies. The credit rating score (CRS) is based on the credit default swap (CDS) market trading.

A CRS is developed which is a linear function of logarithmized CDS spreads. This new CRS is the first one that is completely independent of the rating agency. The estimated ratings are compared with ratings provided by Fitch Ratings for 310 European and US non-financial corporates.

The empirical analysis shows that logarithmized CDS spreads and issuer credit ratings by agencies have a linear relationship. The new CRS provides market participants with an alternative risk assessment, which is solely based on market factors, and does not rely on credit rating analysts. The results indicate that our CRS is able to anticipate agency ratings in advance. Moreover, the analysis shows that the trading volume has only a limited influence in the anticipation of rating changes.

This study shows a new approach to measure the creditworthiness of firms by analyzing CDS spreads. This is highly relevant for regulation, firm monitoring and investors.

The purpose of this paper is to return to Stinchcombe’s original emphasis on emerging vs existing organizations by examining the cognitive legitimacy challenges aspiring entrepreneurs face vis-à-vis entrepreneurs with existing businesses.

The data collection included content analysis of profiles of an online crowdfunding, peer-to-peer lending market leading to a sample of 507 business loan requests, 123 of which were requests to support new business ideas rather than existing businesses. Negative binomial regression was used to test hypotheses regarding whether aspiring entrepreneurs seeking convenience-based support for their new business ideas would be less successful than their counterpart entrepreneurs seeking support for their existing businesses.

The findings show that aspiring entrepreneurs received less convenience-based support for their new business ideas from key resource providers than their peer entrepreneurs asking for support for existing businesses. The findings also suggest that this liability of newer than newness may be able to be mitigated by reputational signals such as the creditworthiness of the entrepreneur making the request.

This study focuses on the original insights Stinchcombe introduced when he described the social conditions that produce the liability of newness. Moreover, this study offers explicit theory as to the key mechanisms that cause the liability of newness by focusing on an aspiring entrepreneur’s ability to secure convenience-based support and potential ways an aspiring entrepreneur may offset that liability.

In the mid 1970s two psychologists, Kahneman and Tversky, isolated three major aspects of heuristics which induce biases in our decisions, which they termed as: (1) representativeness, (2) availability and (3) anchoring. An example of the bias within the representativeness heuristic is the underutilization of base rates. Decision makers tend systematically to overweigh current information and underweigh background information (prior probabilities) relative to what Bayes′ theorem implies. Bias in the availability heuristic is observed for instance in the area of government regulation. Proponents of increasing government regulation of business consider the benefits of eliminating the relatively small number of observed abuses but do not consider the large number of cases where the current system has worked. Decision makers exhibit a tendency to concentrate on extremes rather than means. This is because extremes are more readily available to retrieve from our mental set (mind) than means. On the anchoring heuristic, it is noticed that people allow their decisions to be distorted by the presence of points of reference that should be irrelevant. Discusses biases associated with one particular activity which is important to bank marketing officials, i.e. assessing creditworthiness, and substantiates such a bias using empirical findings.

The purpose of this paper is to investigate the role of trust management on the fundraising performance in reward-based crowdfunding.

A research model was constructed based on elaboration likelihood model (ELM) and literatures with five hypotheses developed. Data were collected from www.demohour.com - the first and one of the largest reward-based crowdfunding platforms in China. In total, 829 reward-based crowdfunding projects were analyzed to test hypotheses. To test the hypotheses, partial least squares was used to analyze data of entrepreneur/sponsor profiles, entrepreneur/sponsor behaviors, and crowdfunding projects.

Results indicated trust management significantly promoted fundraising performance via central (entrepreneur’s creditworthiness) and peripheral (entrepreneur-sponsor interactions) routes. The peripheral route (entrepreneur-sponsor interaction) showed significantly higher effects than the central route (entrepreneur’s creditworthiness). The finding aligns with authors’ assumptions derived from unique characteristics of reward-based crowdfunding – community and collaboration because personal, dynamic message interactions were more effective than static, historical success records on the trust establishment. In addition to the main effects, the results also showed entrepreneur’s prior success crowdfunding records positively moderated the effect of entrepreneur-sponsor interaction on fundraising performance.

This study is the first paper that reveals the value of trust management in reward-based fundraising, especially the effect of dynamic entrepreneur-sponsor message interactions. Entrepreneur-sponsor interactions not only promoted community benefits in crowdfunding, but also cultivated trust relationships between entrepreneurs and sponsors. Previous studies mainly focussed on the entrepreneur’s popularity level on third-party social media (such as Facebook) toward fundraising performance. This study examines the effect of direct entrepreneur-sponsor interactions on the crowdfunding platform. Additionally, this study found one moderating effect from the central route to the peripheral route. It is a rare case in studies based on ELM. Finally, this study demonstrates how to incorporate a theoretical framework guiding the analysis of structured and unstructured data for in-depth analysis, result interpretation, and corresponding intervention strategy development.