Search results

This study aims to develop a novel approach for predicting default risk in bancassurance, which plays a crucial role in the relationship between interest rates in banks and premium rates in insurance companies. The proposed method aims to improve default risk predictions and assist with client segmentation in the banking system.

This research introduces the group method of data handling (GMDH) technique and a diversified classifier ensemble based on GMDH (dce-GMDH) for predicting default risk. The data set comprises information from 30,000 credit card clients of a large bank in Taiwan, with the output variable being a dummy variable distinguishing between default risk (0) and non-default risk (1), whereas the input variables comprise 23 distinct features characterizing each customer.

The results of this study show promising outcomes, highlighting the usefulness of the proposed technique for bancassurance and client segmentation. Remarkably, the dce-GMDH model consistently outperforms the conventional GMDH model, demonstrating its superiority in predicting default risk based on various error criteria.

This study presents a unique approach to predicting default risk in bancassurance by using the GMDH and dce-GMDH neural network models. The proposed method offers a valuable contribution to the field by showcasing improved accuracy and enhanced applicability within the banking sector, offering valuable insights and potential avenues for further exploration.

This study aims to investigate window dressing as practiced by commercial banks in Kuwait, using monthly aggregate balance sheet data covering the period January 1993 to December 2017.

This study applies the structural time series model to decompose an observed time series into unobserved components based on monthly data covering January 1993 to December 2017 on the consolidated balance sheet of commercial banks in Kuwait.

The empirical results indicate that Kuwaiti commercial banks indulge in upward window dressing to boost size and liquidity. This kind of behaviour is indicated by a statistically significant rise in assets under the control of banks in December, followed by a statistically significant decline in January. The operation is funded by borrowing, leading to a December rise and a January fall in foreign and other liabilities, which are also under the control of commercial banks.

This study uses a novel methodology to detect window dressing based on the seasonal behaviour of balance sheet items. This study suggests a unified framework for the motives, targets, types and consequences of window dressing and how they are related.

This paper aims to investigate the perceptions of financial accountants and both internal and external auditors regarding the impact of corporate governance (CG) and information technology (IT) on the detection and prevention of fraud within organizations.

Primary data were collected from 250 financial accountants, internal auditors and external auditors through questionnaires. The non-probability snowball sampling technique was used for data collection, with the sample t-test, one-way ANOVA and paired sample t-test applied for analysis.

The results indicate that robust CG practices and IT techniques significantly aid in detecting and reducing fraudulent activities by minimizing opportunities, rationalizations, pressures and capabilities of potential employees to commit fraud. Internal controls also play a significant role in reducing instances of fraud. Notably, ethical officers and ethical training were not perceived as significantly effective in preventing and detecting fraud, leading to a perception that fraudulent practices are prevalent and increasing the risk of future fraudulent activities.

This study recommends the adoption of strong CG practices to identify potential fraud within an organization. Moreover, IT techniques should be tailored to specific needs for effective utilization. Furthermore, the government should increase awareness regarding data provision by departments, organizations and other related personnel. Future research could use secondary data from various regions to expand the literature in this field.

This research uniquely combines three significant factors: CG, IT and forensic accounting in fraud detection and prevention. It contributes to the enhancement of literature about fraud and its preventive and detective measures. The results of this study set the seed for future research, government policymaking and enhanced organizational practices.

This study evaluates the implementation of ISO 9001 using total quality management on the engineering, procurement and construction phases in the Jordanian construction sector.

A quantitative design has been employed with a total of 132 project team members selected from 5 construction organizations working in Jordan. A close-ended questionnaire was used to gather data which was later evaluated using descriptive and inferential statistics.

The results show a significant role in project performance, customer satisfaction, project quality, cost-effectiveness, time effectiveness, shared cooperation and motivation of employees. It emphasizes the role of engineering in achieving the ISO 9001 standard. Quality standards in the construction project were also endorsed by 46.2% of participants, while 33.3% responded neutrally. The time effectiveness aspects of ISO 9001 endorsed by 38.5% participants 33.3% participants disagreed. Majority of the managers (61.5%) agreed that poor planning is a major barrier in the engineering phase (p-value, 0.011), followed by the incomplete design (56.4%) as the prime impeding factors linked to the decline of the quality in the construction sector.

With the integration of the ISO 9001 quality standard, project managers can improve the project quality and make it cost-effective. The successful adaptation of the ISO 9001 certification allows the company to not only market its product/service but also internally audit itself for the possible deficits in its work capacity.

This study analyzes the impact of the procedures followed by the Central Bank of Jordan during the COVID-19 pandemic on the financial performance of Jordanian banks listed on the Amman Stock Exchange over the period (2019Q1–2021Q3).

The panel fixed effect model was used to measure the impact of each of the required reserve ratios and the deferred loans on the profitability of Jordanian banks represented by the return on total assets.

The results revealed a negative relationship at the significance level of 10% between the required reserve ratio and the return on total assets. Also, there is a negative relationship at the significance level of 5% between the deferred loans and the return on total assets.

The paper recommends the Central Bank of Jordan following a precautionary policy to encounter systematic risks that cannot be eliminated by using diversification.

With the severe impact of the Coronavirus pandemic on the overall economic performance of the national economic sectors and the subsequent negative impact on the living standard of society’s members, this study shows the government’s role represented by the procedures of its monetary authority (Central Bank of Jordan) to mitigate the effects of this pandemic, as well as measuring the impact of these procedures on the financial performance of Jordanian banks listed on the Amman Stock Exchange.

The purpose of this paper is to investigate and understand academic English language-related challenges in listening and speaking faced by English as a foreign language (EFL) international Master students enrolled in various taught Master programs in a Malaysian university from the viewpoint/lens of 16 lecturers teaching the students.

This qualitative research relied upon 16 in-depth one-to-one interview sessions with 16 lecturers teaching the taught Master programs at a higher education (HE) institution in Malaysia for data collection. Data collected were coded and categorized according to themes via qualitative analysis software, NVivo.

It was found that academic English language-related challenges in listening and speaking from the viewpoint of the 16 lecturers are such as lack of discipline content knowledge to communicate, lack of confidence in communicating orally, difficulty in understanding lectures and other oral activities in the classroom, and coping with differences in learning culture.

This study suggests policies and programs to equip lecturers and university administrators to overcome the challenges faced by the students in their academic English language practices especially in listening and speaking to ensure meaningful academic adaptation in the current context.

The uniqueness of this study is that it is a retrospection of the lecturers teaching EFL and English as a second language (ESL) international Master students in taught Master programs in a Southeast Asian country. The focus of the retrospection is on academic English language-related challenges in listening and speaking faced by EFL international Master students who are currently pursuing their Master education at a HE institution in Malaysia.

This paper aims to examine the impact of announcements related to 77 interventions by 46 listed Indian pharmaceutical firms during COVID-19 on the abnormal returns of the firms. The study also finds the variables which explain cumulative abnormal returns (CARs).

This study uses standard event methodology to compute the abnormal returns of firms announcing pharmaceutical interventions in 2020 and 2021. Besides this, the multilayer perceptron technique is applied to identify the variables that influence the CARs of the sample firms.

The results show the presence of abnormal returns of 0.64% one day before the announcement, indicating information leakage. The multilayer perceptron approach identifies five variables that explain the CARs of the sample companies, which are licensing_age, licensing_size, size, commercialization_age and approval_age.

The study contributes to the efficient market literature by revealing how firm-specific nonfinancial disclosures affect stock prices, especially in times of crisis like pandemics. Prior research focused on determining the effect of COVID-19 variables on abnormal returns. This is the first research to use artificial neural networks to determine which firm-specific variables and pharmaceutical interventions can influence CARs.

There is a long-standing interest in performance improvement within the construction industry. Approaches based upon cost, time and quality (often called the Iron Triangle), have been the focus of attention despite criticism of the validity of the Iron Triangle as a performance measure due to its simplistic approach. Furthermore, little emphasis has been placed on synthesising performance to understand whether this concept has evolved from the traditional view. An analysis of prominent literature was reviewed by classifying performance indicators which establish criteria for measuring performance in the construction industry. The purpose of this paper is to review the literature (1998–2018) on performance at a project level to determine a final rank of key performance indicators (KPIs) which will establish how projects are currently being measured.

This paper uses a combined qualitative and quantitative approach – a comprehensive literature review on overall performance at a project level and the statistical Kendall’s W test to find concordance among the authors on performance in the construction industry to determine a final rank of KPIs.

The results demonstrate there is no congruent correlation on what performance is and the traditional iron triangle of “cost-time-quality” is still the preferred method of analysing performance, despite it being proven to be ineffective.

Performance in the construction industry is an ambiguous concept that can be interpreted differently by the construction industry’s stakeholders. Despite this lack of concordance, a starting point on the definition of performance can be obtained from the literature. The paper presents a final rank of KPIs.