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Dynamic predictions of financial distress of the firms have received less attention in finance literature rather than static prediction, specifically in Malaysia. This study, therefore, investigates dynamic symptoms of the financial distress event a few years before it happened to the firms by using neural network method. Cox Proportional Hazard regression models are used to estimate the survival probabilities of Malaysian PN17 and GN3 listed firms. Forecast accuracy is evaluated using receiver operating characteristics curve. From the findings, it shown that the independent directors’ ownership has negative association with the financial distress likelihood. In addition, this study modeled a mix of corporate financial distress predictors for Malaysian firms. The combination of financial and non-financial ratios which pressure-sensitive institutional ownership, independent director ownership, and Earnings Before Interest and Taxes to Total Asset shown a negative relationship with financial distress likelihood specifically one year before the firms being listed in PN 17 and GN 3 status. However, Retained Earnings to Total Asset, Interest Coverage, and Market Value of Debt have positive relationship with firm financial distress likelihood. These research findings also contribute to the policy implications to the Securities Commission and specifically to Bursa Malaysia. Furthermore, one of the initial goals in introducing the PN17 and GN3 status is to alleviate the information asymmetry between distressed firms, the regulators, and investors. Therefore, the regulator would be able to monitor effectively distressed firms, and investors can protect from imprudent investment.

The incidence of important bankruptcy cases has led to a growing interest in corporate bankruptcy prediction models since the 1960s. Several past reviews of this literature are now either out‐of‐date or too narrowly focused. They do not provide a complete comparison of the many different approaches towards bankruptcy prediction and have also failed to provide a solution to the problem of model choice in empirical application. Seeks to address this issue.

Through an extensive literature review, this study provides a comprehensive analysis of the methodologies and empirical findings from these models in their applications across ten different countries.

The predictive accuracies of different models seem to be generally comparable, although artificially intelligent expert system models perform marginally better than statistical and theoretical models. Individually, the use of multiple discriminant analysis (MDA) and logit models dominates the research. Given that financial ratios have been dominant in most research to date, it may be worthwhile increasing the variety of explanatory variables to include corporate governance structures and management practices while developing the research model. Similarly, evidence from past research suggests that small sample size, in such studies, should not impede future research but it may lead researchers away from methodologies where large samples are critically necessary.

It is hoped that this study will be the most comprehensive to‐date review of the literature in the field. The study also provides a unique ranking system, the first ever of its kind, to solve the problem of model choice in empirical application of bankruptcy prediction models.

Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types of employment have risen significantly, there has been significant growth in adopting AI technology in enterprises. Despite the anticipated benefits of AI adoption, many businesses are still struggling to make progress. This research article focuses on the influence of elements affecting the acceptance procedure of AI in organisations.

Design/Methodology/Approach: To achieve this objective, propose a hierarchical paradigm for the same by developing an Interpretive Structural Modelling (ISM). This paper reveals the barriers obstructing AI adoption in organisations and reflects the contextual association and interaction amongst those barriers by emerging a categorised model using the ISM approach. In the next step, cross-impact matrix multiplication is applied for classification analysis to find dependent, independent and linkages.

Findings: As India is now focusing on the implementation of AI adoption, therefore, it is essential to identify these barriers to AI to conceptualise it systematically. These findings can play a significant role in identifying essential points that affect AI adoption in organisations. Results show that low regulations are the most critical factor and functional as the root cause and further lack of IT infrastructure is the barrier. These two factors require the most attention by the government of India to improve AI adoption.

Implications: This study may be utilised by organisations, academic institutions, Universities, and research scholars to fill the academic gap and faster implementation of AI.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

The aim of the paper is to investigate several aspects of bankruptcy prediction within both theoretical and empirical frameworks. In particular, it has focused on the comparison of different techniques used to forecast failure through a balanced sample of companies within a geographical area (the Campania region) located in the south of Italy.

Business failure has been one of the most investigated topics within corporate finance and the empirical approach to bankruptcy prediction has recently gained further attention from financial institutions. The aim of corporate failure prediction is to have a methodological approach which discriminates firms with a high probability of future failure from those which are considered to be healthy. Starting from the seminal paper of Altman (1968), many other significant contributions have been subsequently made to this field (Ravi Kumar and Ravi, 2007). This paper's approach is to compare different statistical techniques based on the analysis of financial data for the prediction and diagnosis of the risk of bankruptcy.

The paper investigates the determinants of bankruptcy in a specific geographical area (Campania region). Empirical evidence on a data‐set of the annual reports of a balanced sample of companies for a given time period has been analyzed. These findings aim to make a contribution to current literature as well as to contribute to the elaboration of efficient prevention and recovery strategies.

Researchers have tended to restrict the scope of their analysis due to the problems related to the collection and storage of financial data. This study focuses on financial information relating to the area of interest in order to provide a comparative analysis of different forecasting techniques.

The purpose of the study is to develop and validate scale to measure the “product knowledge of salesforce in Islamic financial institutions”.

A total of 371 responses were collected from the salesforce of Islamic financial institutions in the United Arab Emirates. Study adopted both exploratory and confirmatory approach with fundamental principles of Islamic finance. Content validity test and factor analysis are employed to refine measurement items and define as well as validate the scale, respectively.

Total three dimensions were extracted, i.e. “System”, “Features” and “Contracts” through “exploratory factor analysis” (EFA), and evidence of validation of measurement scale/construct was reported through “confirmatory factor analysis” (CFA).

The span of the study is limited to a single country. Future studies are suggested to employ the newly developed scale/construct in the research frameworks and obtain the overall model fit.

The scope of developed and validated measurement scale is broad and can be applied in any kind of Islamic financial institutions in which the study requires capturing product knowledge of salesforce with special reference to peculiar characteristics of Islamic financial institutions.

While there is ample literature addressing the issues of competence and need for capacity building among Islamic banking practitioners in general, little has been explored with special reference to the salesforce, their degree of knowledge about the product they offer to the customers and a scale to measure their knowledge that envelopes the specific features of Islamic finance. These gaps serve as justification for undertaking this study.

The purpose of this paper is to explore the types of Shariah capabilities of Islamic banks, which provide bases for the types of Shariah value propositions, offered by the relationship managers in their front-line service experiences with the customers.

A resource-based view of Shariah capabilities and a service-dominant logic view of value propositions are adopted. Fifteen relationship managers from multiple Islamic banks in Pakistan are interviewed to find a typology of Shariah capabilities and a resultant typology of value propositions for Islamic banks.

The findings suggest that Islamic banks claim to possess five types of Shariah capabilities, namely, Shariah governance capability (SGC), Shariah compliance capability (SCC), Shariah monitoring capability (SMC), Shariah structuring (product) capability (SSC) and Shariah learning capability (SLC). These capabilities lead to four types of values propositions, namely, Shariah identity value (SIV), Riba-free value (RFV), Shariah disclosure value (SDV) and Tangibility value (TV) of the real assets in transactions.

The study has relied on the front-line experiences of relationship managers who are connected to the Islamic banks’ capabilities inside the banks and the value propositions that they offer to show relationships with customers in front-line service experiences. Other stakeholders may have different perspectives on both capabilities and value propositions.

This paper contributes to Islamic finance theory by theoretically and empirically showing two typologies for the Islamic banks' capabilities and value propositions, respectively.

This research paper aims to determine the factors needed to propose a platform where waqf (Islamic endowment) organizations can collaborate with government public hospitals to develop corporate waqf hospitals. Consequently, the elements of governance and sustainability are included in the management of corporate waqf hospitals thereby leading to the corporatization of public hospitals.

This study adopts the qualitative research methodology and undertakes content analysis of data collected from journal articles, magazines and official websites. Data analysis involves open coding with NVivo 12.

General findings from the literature review have shown that architectural and engineering fundamentals were essential factors in the success of past waqf hospitals of the era between 8th and 14th centuries. In that era, the decentralized waqf-based hospitals employed the mutawalli (the trustee/manager of the waqf assets) to govern the administration of the hospitals. Present corporate waqf hospitals can exploit the elements identified from past waqf-based hospitals and additionally adopt the private-public partnership model in the form of a muḍārabah (profit-sharing contract) agreement to design a sustainable waqf governance model for Malaysian public healthcare services.

The proposed platform is designed for a corporate waqf model developed in collaboration between Malaysian waqf institutions and public healthcare services. It abides by both the Malaysian fatwa (Islamic rulings) on waqf and the laws of the Malaysian Government.

There is potential for developing the Malaysian corporate waqf-governance healthcare model which will enable the hospital to provide better quality healthcare to more patients through upgrading the quality of equipment used in hospitals and/or better facilities at equal or lower costs. Consequently, this will not only improve waqf management and distribution but also result in reduction of government expenditure.

This research promotes the concept of a corporate waqf hospital which will provide innumerable beneficial healthcare services in terms of improved healthcare quality at affordable costs to the general public and at no cost to the poor and the underprivileged.

Although waqf has played an important role as a vehicle for Islamic financing in the society for centuries, a model of collaboration or partnership of waqf with public healthcare services has yet to be explored and developed. With proper corporate governance and well-managed sustainability in a corporate waqf model, this newly developed partnership between waqf institutions and public healthcare providers can be a first step in many more interesting collaborative arrangements that can be established between waqf institutions and public services in the future.

At the age of 92, Mahathir Mohamad served his country as the Prime Minister for the second time. But unlike his first stint as the head of the government, which lasted 22 years, this time, his tenure was less than two years. His resignation, which was linked to some internal issues within the Pakatan Harapan (PH) allied parties, came at a time when many countries in the world were in the early stages of the coronavirus outbreak. Mahathir was aware of the power struggle that was adversely affecting the government's response to combat the virus transmission and reduce the rising number of COVID-19 infection cases. With his long experience in governance and as a former medical officer, Mahathir offered some advice and recommendations to the existing government on ways to address the public health crisis. Since the coronavirus outbreak, the domestic political and economic developments also drew his direct criticism and critical commentaries.

The rising awareness of the significance of protecting the environment and reducing the carbon footprints of buildings has led to the development of sustainable or green office buildings that are believed to be more energy-efficient and environmentally friendly. Despite this, not many have studied the extent of impacts between green classification and rental depreciation in Malaysia, besides the other traditional causes. Therefore, the primary purpose of this study is to identify the relationship of building characteristics and location factors, namely, green building classifications (BCLs), location and site (LOT), building engineering and services (BES) and building appearance and design (BAD) that contribute to rental depreciation in the Golden Triangle Area of Kuala Lumpur.

A survey using a questionnaire was used in the data collection targeting the selected Kuala Lumpur commercial purpose built office building property managers. To establish the significance and relevance of the model, this study employed the PLS algorithm and bootstrapping procedures.

This research suggests that there were significant impacts of LOT, BAD, and BES towards rental depreciation. On the contrary, sustainable classifications were found insignificant towards rental depreciation.

The novelty of this study is that it proposes the sustainable classifications as one of the components in analysing the commercial property depreciation.