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The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

This study investigates determinant factors (influence of the third party (ITP), credit policy (CP) and follow-up process (FP)) of micro, small and medium enterprises' (MSMEs) accounting processes (APs) and strategic debtors' management.

The study employed a sequential mixed-method approach, combining quantitative and qualitative methods for comprehensive data analysis. Phase I involved purposively selecting and interviewing 10 MSME owners or accountants to gain insights into debtors' management. In Phase II, a quantitative approach was used for collecting survey data from 72 MSME owners or accountants. Structural equation modeling-partial least squares (SEM-PLS) are the statistical tools that validated the study's proposed hypotheses.

The findings indicate that determinant factors (ITP, CP and FP) positively affect MSMEs' AP, significantly influencing strategic debtors' management. As a result, sole proprietors can use this study's findings to create value through systematic management of their debtors, guaranteeing sustainable firm growth and profitability.

The sample has restricted to MSMEs in Oman, where the findings may not be generalized to other companies. Overall, the findings suggest that it requires considering the proposed determinant factor of MSMEs' AP to manage their debtors or accounts receivable (AR) to be more profitable.

MSMEs play an essential role in the growth of any country's economy. However, the dearth of comprehensive research on influential factors of MSMEs' debtors’ management studies justifies the significance of the current study.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.

Know your customer (KYC), accounting standards, issuance, clearing, and trade settlement became the major barrier to implement accounting, accountability and assurance process in supply chain finance (SCF). Blockchain technology features have the potential to solve accounting problems. This research focuses on exploring how blockchain technology provides solutions to overcome the barriers of accounting process in SCF. The benefits, opportunities, costs and risks related to blockchain adoption are also explored.

Multi-case study and qualitative methods are used with a framework based on blockchain role to overcome the accounting process barriers. Ten blockchain projects in SCF and 29 interviews of participants as a unit of analysis are considered.

The findings indicate that blockchain technology offers solutions to solve accounting, accountability and assurance problems in SCF. Validity, verification, smart contracts, automation and enduring data on trade transactions potentially solve those barriers. However, it is also necessary to consider costs such as implementation, technology, education and integration costs. Then there are possible risks such as regulatory compliance, operational, code development and scalability risk. This finding reflects the current status of blockchain technology roles in SCF.

This study unveils blockchain's SCF accounting potential, emphasizing multi-case method limitations and future research prospects. Diverse contexts challenge findings' applicability, warranting cross-industry studies for deeper insights. Addressing selection bias and integrating quantitative measures can enhance understanding of blockchain's accounting impact.

Accounting professionals can get an idea of the future direction and impact of blockchain technology on accounting, accountability and assurance processes.

This study provides initial findings on the potential, costs and risks of blockchain that is beneficial for parties involved in SCF, especially for banks and insurance underwriters. In addition, the findings also provide direction for the contribution of blockchain technology to accounting theory in the future.

The purpose of the study is to examine the use of alternative information in bank lending to small and medium enterprises (SMEs). Understanding alternative information and its use in bank lending to SMEs is important because it has become a growing part of the future of SME finance. The results and findings of my study not only enrich the finance literature but, more importantly, also address the use of Fintech in the risk management of SME lending, a new and complex problem that is specific to both the information technology and finance field.

To answer the research question, the author used a case study approach that relies upon qualitative data and analysis. By iterating between the existing literature, theoretical pieces and empirical findings, the author explain and interpret in detail how the use of alternative information impacts loan outcomes and develop insights to guide future research.

The case is outlined in two time periods including the prepartnership period and the postpartnership period. It highlights the establishment of a partnership between LoanBank and FintechInc (pseudonym), aimed at SME-focused Fintech lending. The findings underscore how the partnership has enabled a mutually beneficial situation where LoanBank and FintechInc leverage each other’s strengths to provide efficient and effective lending services. The adoption of alternative information in the risk management Fintech (RMF) platform of FintechInc has transformed LoanBank’s lending processes, showcasing how technological innovations can enhance SME lending practices.

The study’s originality mainly lies in the three detailed insights regarding alternative information’s impact on SME lending: information, platform properties and financial inclusion. The information part demonstrates that RMF platforms expand the information used for lending decisions, shifting from traditional hard and soft data to incorporating various alternative information sources. The platform properties part suggests that location, openness and technology also play a pivotal role in shaping lending outcomes. Finally, the financial inclusion part proposes that the use of alternative information has the potential to improve financial inclusion and offer better credit terms to previously underserved borrowers.

The purpose of this study is to extend previous literature and examine risk management efficiency among Takaful (TI) and conventional insurance (CI) firms in the Kingdom of Saudi Arabia (KSA) and the United Arab Emirates (UAE). This study also aims to determine whether Takaful firms are more efficient in managing risks, compared to CI firms.

This study examines risk management efficiency among Takaful and CI firms in the KSA and the UAE for a sample of 20 insurance firms comprising 10 TI firms and 10 CI firms for the period 2018–2020. The authors use Data Envelopment Analysis to estimate efficiency scores among insurance companies to compare risk management efficiency between CI and TI companies and apply two-way analysis of variance to statistically analyze the data.

The results of this study show that TI firms have a higher efficiency score than CI firms, but not significantly and that insurance firms in KSA have higher efficiency scores than insurance firms in UAE. The results also reveal that TI firms did not significantly outperform CI firms in managing risks; however, there is a significant difference in efficiency scores among insurance firms in KSA and UAE.

The authors also contribute to the literature by providing important insights into how the operational business environment of the country can influence the risk management efficiency of CI and TI companies.

This study promotes understanding the insurance industry, its efficiency and risk management, thus offering key implications for decision-makers, regulators and managers associated with the insurance industry in UAE, KSA and other emerging insurance markets. Regulators could provide enabling policies that foster and promote the business environment, as there is a need to improve risk management efficiency in the insurance industry. Also, the results of this study show that the operating status of the UAE insurance industry in terms of efficiency and risk management is lower than that of KSA. Hence, it would be useful for UAE managers and regulators in taking steps to improve the overall insurance industry market.

The results of this study make significant contributions by providing new insights to the existing literature on the risk management efficiency in the insurance industry, as it adopts a different methodological approach that examines risk management efficiency among TI and CI companies.

This study aims to synthesize records and information management (RIM) with the professional literature of industrial/organizational (I/O) psychology to explain undesirable recordkeeping behaviors that may manifest in employees who interact with business records.

The author’s views are based on a literature review of both records management and organizational psychology trends and draw on case studies that identify undesirable recordkeeping behavior.

There is considerable overlap between the problems encountered by RIM professionals and the answers offered by I/O psychology. I/O psychology offers us the tools to better understand recordkeeping behaviors.

The author proposes using I/O psychology concepts to better situate RIM programs within the larger organizational context.

In 2018, the International Financial Reporting Standard 9-Financial Instruments became mandatory, effectively changing the underlying accounting principles of financial instruments. This paper systematically reviews the academic literature on the implementation effects of IFRS 9, providing a coherent picture of the state of the empirical literature on IFRS 9.

The study thrives on a systematic review approach by analyzing existing academic studies along the following three broad categories: adoption and implementation, impact on financial reporting, and risk management and provisioning. The study concludes by providing research prospects to fill the identified gaps.

We document data-related issues, forecasting uncertainties and the interaction of IFRS 9 with other regulatory standards as implementation challenges encountered. Also, we observe cross-country heterogeneity in reporting quality. Furthermore, contrary to pre-implementation expectations, we find improvement in risk management. This suggests that despite the complexities of the new regulatory standard on financial instruments, it appears to be more successful in achieving the intended objective of enhancing better market discipline and transparency rather than being a regulatory overreach.

As the literature on IFRS 9 is burgeoning, we provide state-of-the-art guidance and direction for researchers with a keen interest in the economic significance and implications of IFRS 9 adoption. The study identifies gaps in the literature that require further research, specifically, IFRS 9 adoption and firm’s hedging activities, IFRS 9 implications on non-financial firms. Lastly, existing studies are mostly focused on Europe and underscore the need for more research in under-researched jurisdictions, particularly in Asia and Africa. Also, to standard setters, policymakers and practitioners, we provide some insight to aid the formulation and application of standards.

The purpose of this paper is to engage in a systematic examination of previous scholarship on the relationship between Sharia governance (SG), which is represented by the Sharia Supervisory Board (SSB), and the Internal Sharia Review (ISR), to determine whether the ISR can minimize financing risk in Islamic banking.

The literature search consisted of two steps: a randomized and systematic literature review. The methodology adopted in this article is a systematic literature review.

To reduce the risk of financing in Islamic banking, SG must be implemented optimally by making rules regarding the role of the SSB in supervising customer financing. In addition, it is a necessary to establish an entity that assists the SSB in the implementation of SG, namely, the ISR section, but there is still very little research on the role of the SSB and ISR in minimizing financing risk.

Establishing an ISR to assist the SSB in carrying out its duties has direct practical implications for Islamic banking: minimizing financing risks and compliance with Islamic Sharia principles. In addition, new rules regarding the role of SSBs and the ISR in reducing credit risk include monitoring customers to ensure that they fulfill their financing commitments on time. This new form of regulation and review can be used as a reference by the Otoritas Jasa Keuangan or Finance Service Authority to create new policies or regulations regarding SG, especially in Indonesia.

Subsequent research may introduce other more relevant variables, such as empirically testing the competence, independence or integrity of SSB and the ISR team as it attempts to minimize the risk of financing in Islamic banks. In addition, further research is expected to examine whether the SSB or the ISR team has a positive or negative influence on the risk of financing Islamic banks with secondary data.

This study investigates the implementation challenges and economic consequences of the International Financial Reporting Standards 9 (IFRS 9) Financial Instruments.

Descriptive evidence on equity asset reclassifications and estimated impairment using the new expected credit loss (ECL) model are presented. Multivariate analyses on the disposal of available-for-sale (AFS) and fund investment post-announcement and the value relevance of impairments to financial assets post-implementation are performed.

Over 60% of sample firms report inconsistent equity asset reclassifications and do not change estimated impairment using the new expected credit loss model. Firms also switch from AFS to equity fund investments post-announcement. Lastly, impairments to financial assets increase in value relevance to investors’ post-implementation, but only in financial institutions and firms with Big 4 auditors.

This study's findings suggest that IFRS 9 presents implementation challenges and changes equity investment strategies. They also indicate cross-sectional differences in firms' ability to effectively apply the new standards. This study is valuable for policymakers, business leaders, investors and academics.