Search results

This paper aims to provide a complete analysis framework and prediction method for the construction of the patent securitization (PS) basic asset pool.

This paper proposes an integrated classification method based on genetic algorithm and random forest algorithm. First, comprehensively consider the patent value evaluation model and SME credit evaluation model, determine 17 indicators to measure the patent value and SME credit; Secondly, establish the classification label of high-quality basic assets; Then, genetic algorithm and random forest model are used to predict and screen high-quality basic assets; Finally, the performance of the model is evaluated.

The machine learning model proposed in this study is mainly used to solve the screening problem of high-quality patents that constitute the underlying asset pool of PS. The empirical research shows that the integrated classification method based on genetic algorithm and random forest has good performance and prediction accuracy, and is superior to the single method that constitutes it.

The main contributions of the article are twofold: firstly, the machine learning model proposed in this article determines the standards for high-quality basic assets; Secondly, this article addresses the screening issue of basic assets in PS.

The case describes the structure of Infrastructure Investment Trusts (InvITs) created and launched in Indian markets in 2017. Besides introducing InvITs and their potential role in relaxing the financing constraint created by the lack of an active corporate debt market in India, the case can help in analysing why the market is discounting the IndiGrid unit price relative to its issue price. It also offers an opportunity to value IndiGrid's Patran acquisition.

This study examines the cognitive factors of adopting blockchain technology in various supply chain scenarios and its role in reframing the distinctive values of supply chain financing. Based on expectancy theory, this study explores the different profiles underlying the components of expectancy, valence and instrumentality.

This is a multiple-case study of four Fintech companies using blockchain technology to promote the performance of supply chain operations and financing.

The results show that blockchain-enabled supply chain finance (BSCF) can be classified into four scenarios based on the scope and purpose of blockchain technology applications. The success of BSCF depends on the profiles of BSCF expectancy (the recognized purpose and scope of BSCF), instrumentality (identified blockchain attributes and other technology combinations) and valence (the perceived distinctive value of BSCF). Blockchain attributes help solve information asymmetry problems and enhance financing performance in two ways: one is supporting transparency, traceability and verification of transmissions and the other entails facilitating a transformation to new business models.

This research applies a new perspective based on expectancy theory to study how cognitive factors affect Fintech companies' blockchain solutions under a given supply chain operation or financing activity. It explains the behavioral antecedents for applying blockchain technology, the situations appropriate for the different roles of blockchain technology and the profiles for realizing the value of blockchain technology.

This paper aims to document the impact of shadow banking on non-performing loans (NPLs) of publicly listed banks in an international setting.

This paper uses the data from 27 countries and various estimation strategies to test the arguments presented in this paper. The sample covers the period between 2002 and 2020.

The empirical results suggest that banks headquartered in countries with high shadow banking activity have fewer NPLs than otherwise similar banks headquartered in countries with low shadow banking activity. The findings remain qualitatively the same in different sub-samples and after replacing the main variables with their alternate proxies. The paper also shows that this relationship is sensitive to bank-specific characteristics. Moreover, the paper also indicates that the stringency of banking regulations weakens the relationship between shadow banking and NPLs.

The study’s data limitations prevent a detailed year-by-year analysis of NPLs and shadow banking, restricting insights into their evolving dynamics. In addition, the focus on country-level shadow banking data limits the exploration of how multinational banks’ activities in various jurisdictions impact individual banks’ NPLs.

The paper not only documents the effect of shadow banking on NPLs but also shows that the relationship between shadow banking and NPLs weakens as banking regulations become more stringent.

This study investigates the role of market concentration and efficiency in banking system stability during the COVID-19 pandemic. We empirically test the hypothesis that market concentration and efficiency are significant determinants of bank performance and stability during the time of crises, using a sample of 575 banks in 20 countries in the Middle East and North Africa (MENA).

The main sources of bank data are the BankScope and BankFocus (Bureau van Dijk) databases, World Bank development indicators, and official websites of banks in MENA countries. This study combined descriptive and analytical approaches. We utilize a panel dataset and adopt panel data econometric techniques such as fixed/random effects and the Generalized Method of Moments (GMM) estimator.

The results reveal that market concentration negatively affects bank profitability, whereas improved efficiency further enhances bank performance and contributes to the banking sector’s overall stability. Furthermore, our analysis indicates that during the COVID-19 pandemic, bank stability strongly depended on the level of market concentration, but not on bank efficiency. However, more efficient banks are more profitable and stable if the banking institutions are Islamic. Similarly, Islamic banks with the same level of efficiency demonstrated better overall financial performance during the pandemic than their conventional peers did.

The main limitation is related to the period of COVID-19 pandemic that was covered in this paper (2020–2021). Therefore, further investigation of the COVID-19 effects on bank profitability and risk will require an extended period of the pandemic crisis, including 2022.

This study provides information that will enable bank managers and policymakers in MENA countries to assess the growing impact of market concentration and efficiency on the banking sector stability. It also helps them in formulating suitable strategies to mitigate the adverse consequences of the COVID-19 pandemic. Our recommendations are useful guides for policymakers and regulators in countries where Islamic and conventional banking systems co-exist and compete, based on different business models and risk management practices.

The authors contribute to the banking stability literature by investigating the role of market concentration and efficiency as the main determinants of bank performance and stability during the COVID-19 pandemic. This study is the first to analyze banking sector stability in the MENA region, using both individual and risk-adjusted aggregated performance measures.

This case is a sequel to the “IndiGrid: Creating India's First Power Transmission InvIT (A)” case. It describes the deal that would replace the trust's original sponsor, Sterlite Power, with a new set of KKR-led financial investors. It provides an opportunity to discuss the consequences of this change on the new investment manager's outlook for management and future acquisitions. The new investment manager, freed from the limiting interest of the original sponsor, had to search for investment opportunities from the perspective of incoming financial investors, which included the new sponsor. It also provides an opportunity to evaluate the trade-offs in investing in operational utility-scale renewable energy assets by the IndiGrid, which had so far only acquired operational transmission assets in its portfolio.

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.

This paper aims to examine the extent to which these reforms address the limitations of Saudi Arabia’s previous investment framework. Long viewed as a hostile environment in which to do business, the Saudi Government has enacted a broad sweep of measures aimed at restoring investor confidence in central aspects of the country’s evolving private law framework.

This paper offers a timely assessment of the raft of foreign investment reforms, both legislative and regulatory, that have been introduced in Saudi Arabia over the last decade.

The paper will proceed by outlining the perceived failings of the old investment regime before going on to reforms.

It will consider the remaining obstacles to the flow of foreign investment in Saudi Arabia in the context of the dual forces that have historically defined the Kingdom’s ambivalent investment law regime.

This study aims to attempt to investigate the factors that influence non-Muslims’ withdrawal behavioural intention from Islamic banking in Malaysia.

The push–pull–mooring approach is used to examine the determinants of withdrawal intention by non-Muslims from Islamic banking in Malaysia. Variables used in this study include religiosity (RELG) under push, deposit guarantee (DG), rate of return (RR), Islamic banks’ specific factors (IBSF) under pull and mooring factors as social influence (SI) and voluntary switching (VS) as the determinants of withdrawal intention from Islamic banking. In this study, the SPSS Statistics Version 22 and smart partial least squares were used to measure the withdrawal level.

Three variables, namely, SI, RR and IBSF are found to significantly influence the withdrawal behaviour intention. Meanwhile, three other variables, namely, RELG, DG and VS are not significant.

This study provides valuable insights pertaining to non-Muslim consumer withdrawal behaviour from Islamic banks. Bank managers, marketers and regulators could use these findings in developing effective strategies to increase and retain customer withdrawal.

This study expands the understanding of key determinants of the non-Muslim withdrawal behaviour from Islamic banks in Malaysia. To the best of the authors’ knowledge, this research is among the pioneer empirical study to assess the issue.

This paper investigates the influence of political connections on sustainability disclosure in the context of China's Regulation 18.

The study employs a quasi-experimental approach, utilizing difference-in-difference (DiD) analysis, dynamic DiD and propensity score matching to analyze the effects of politically connected independent directors on sustainability disclosure following the implementation of Regulation 18.

Companies with politically connected independent directors show an improvement in sustainability disclosures after Regulation 18. This effect is stronger for firms facing high political pressure or lacking alternative political power. Additionally, the increase in value from sustainability disclosures compensates for the loss of politically connected independent directors, indicating a positive value impact of sustainability disclosures.

This study provides novel insights into the corporate disclosure policy in China by investigating the impact of politically connected directors on sustainability disclosure. Additionally, it sheds light on the limitations of political power and its substitution effects within companies.