scholarly journals Impact Of Financial Information Fraudulence To Financial Distress In Malaysia.

Author(s):  
Dalila Binti Abu Bakar, Et. al.

We investigate if Malaysian listed companies engaged in financial information fraud during financial distressed after two years of US subprime mortgage crisis.We also investigate the impact of financial information fraudulence in bankruptcy prediction and misclassification errors. This study used consumer product companies listed on the main board and the timeframe is from 2011 till 2015. The Altman Z score indicates that 37 out of 133 Malaysian consumer product companies are financially distressed. Meanwhile, the M score shows that 28 out of 224observations are engaged in financial information fraudulence. However, these results are relatively low because the samples are taken from the main board and fraudulence in their financial statements might be done in lower magnitude in order to avoid sanctions by the Security Exchange Commission. Logistic regression was used to measure the predicting accuracy. The result of the overall accuracy percentage slightly improved by 0.9 after eliminating fraudulent companies. The confusion matrix result i.e. before and after the removal of financial information fraudulent companies, the misclassification errors especially type one has improved. This finding satisfied objective three, whereby one of the reasons for the deterioration in financial distress prediction is due to the upward bias of financial information fraudulence.Governments, monitoring bodies, and all those involved in an insolvency process would benefit from this study.

Author(s):  
Olga Lvova

The paper provides the solution to the problem of an integrated classification of existing bankruptcy prediction based on the content analysis of 270 relevant foreign and Russian publications issued within a period of 1910-2020. The author identifies two main groups of models– normative and positive, with the latter categorized into expert, mixed and objective including traditional statistical models and artificial intelligent techniques; and considers the specific features of certain predicting models, their advantages and disadvantages. He then reveals the economic content of such models and the set of ratios applied for identifying company’s financial distress with the following conclusions: approaches to the variables selection are rarely justified, indicators are usually borrowed from previous models or generated automatically by the database configuration; the accounting approach to bankruptcy forecasting based on financial ratios prevails and has serious limitations for Russian companies; the most significant market, value and qualitative variables indicating a decline in the business financial stability are highlighted. Significant limitations of the general use of bankruptcy prediction models for making decisions aimed at insolvency prevention are identified: the inability to anticipate the impact of informal factors that are irregular, unable to extrapolate, and affect companies in different ways; the need to take into account the economic conditions of the national economy, financial reporting standards, and the level of availability of diverse data; the impossibility of creating a universal indicative basis to identify decline of sustainability of any business due to the high volatility of operating conditions in Russia. Bayesian methods and nowcasting, as well as the development of forecasting models for certain industries, are promising areas for the development of modern approaches to bankruptcy prediction, but the fundamental activity for preventing insolvency is not forecasting by models, but the implementation of continuous monitoring of the overall business performance in relation to influencing market, operational, investment, financial, managerial and organizational factors, taking into account significant qualitative variables.


Author(s):  
Olga Lvova

The paper provides the solution to the problem of an integrated classification of existing bankruptcy prediction based on the content analysis of 270 relevant foreign and Russian publications issued within a period of 1910-2020. The author identifies two main groups of models– normative and positive, with the latter categorized into expert, mixed and objective including traditional statistical models and artificial intelligent techniques; and considers the specific features of certain predicting models, their advantages and disadvantages. He then reveals the economic content of such models and the set of ratios applied for identifying company’s financial distress with the following conclusions: approaches to the variables selection are rarely justified, indicators are usually borrowed from previous models or generated automatically by the database configuration; the accounting approach to bankruptcy forecasting based on financial ratios prevails and has serious limitations for Russian companies; the most significant market, value and qualitative variables indicating a decline in the business financial stability are highlighted. Significant limitations of the general use of bankruptcy prediction models for making decisions aimed at insolvency prevention are identified: the inability to anticipate the impact of informal factors that are irregular, unable to extrapolate, and affect companies in different ways; the need to take into account the economic conditions of the national economy, financial reporting standards, and the level of availability of diverse data; the impossibility of creating a universal indicative basis to identify decline of sustainability of any business due to the high volatility of operating conditions in Russia. Bayesian methods and nowcasting, as well as the development of forecasting models for certain industries, are promising areas for the development of modern approaches to bankruptcy prediction, but the fundamental activity for preventing insolvency is not forecasting by models, but the implementation of continuous monitoring of the overall business performance in relation to influencing market, operational, investment, financial, managerial and organizational factors, taking into account significant qualitative variables.


Author(s):  
Supitriyani Supitriyani ◽  
Yansen Siahaan ◽  
Astuti Astuti ◽  
Juan Anastasia Putri ◽  
Elly Susanti

The increasing spread of the Covid-19 virus at this time has forced several company sectors to experience setbacks in their operations. This epidemic has had a major impact, especially on the Transportation Sub-Sector Companies because they have to make some adjustments to government regulations such as implementing health protocols and physical restrictions on travel to break the chain of virus spread. The regulation has an impact on the company's revenue decline and the potency to suffer losses that can result in bankruptcy. This study aims to determine the bankruptcy prediction of the Transportation Sub-Sector Companies listed on the IDX before and after the covid-19 pandemic and to find out the most accurate method. The sampling technique used was non-probability sampling with the purposive sampling technique. The method used is descriptive with a quantitative approach. The results of the hypothesis test show that there are differences in predictions between the Altman and Springate models in predicting bankruptcy before and after the covid-19 pandemic. The Altman model is the most accurate prediction with an accuracy rate of 85.75%, while the Springate model has an accuracy rate of 73%. The study focused on companies listed on the IDX and used two bankruptcy measurement models, so researchers are next expected to use the entire company and other existing bankruptcy prediction, models. In addition, some factors beyond the control of researchers, such as economic conditions that cannot be measured. The renewal of previous research is to use two methods of prediction of bankruptcy, different objects, and research time (before and after the covid-19 pandemic).


2018 ◽  
Vol 15 (1) ◽  
pp. 55-72
Author(s):  
Herlin Hamimi ◽  
Abdul Ghafar Ismail ◽  
Muhammad Hasbi Zaenal

Zakat is one of the five pillars of Islam which has a function of faith, social and economic functions. Muslims who can pay zakat are required to give at least 2.5 per cent of their wealth. The problem of poverty prevalent in disadvantaged regions because of the difficulty of access to information and communication led to a gap that is so high in wealth and resources. The instrument of zakat provides a paradigm in the achievement of equitable wealth distribution and healthy circulation. Zakat potentially offers a better life and improves the quality of human being. There is a human quality improvement not only in economic terms but also in spiritual terms such as improving religiousity. This study aims to examine the role of zakat to alleviate humanitarian issues in disadvantaged regions such as Sijunjung, one of zakat beneficiaries and impoverished areas in Indonesia. The researcher attempted a Cibest method to capture the impact of zakat beneficiaries before and after becoming a member of Zakat Community Development (ZCD) Program in material and spiritual value. The overall analysis shows that zakat has a positive impact on disadvantaged regions development and enhance the quality of life of the community. There is an improvement in the average of mustahik household incomes after becoming a member of ZCD Program. Cibest model demonstrates that material, spiritual, and absolute poverty index decreased by 10, 5, and 6 per cent. Meanwhile, the welfare index is increased by 21 per cent. These findings have significant implications for developing the quality of life in disadvantaged regions in Sijunjung. Therefore, zakat is one of the instruments to change the status of disadvantaged areas to be equivalent to other areas.


2017 ◽  
Vol 11 (3) ◽  
pp. 255
Author(s):  
Jeky El Boru

Abstract: This research aims to analyze the impact of Janti Flyover Construction toward the growth of layout at Janti Urban Area, including structured space, open space, and linkage. Method used for data collecting are observation, air photograph monitoring, and interview, whereas the analysis method is qualitative description, which is the superimposed method of two layers, that are the layout condition before and after flyover construction. The result shows that the impact of Janti Flyover construction can be seen on building mass (solid), the increasing number of open spaces, including the road network, parking place, and park, whereas the relation between spaces, visually and structurally, can be seen on the growth of buildings which have new shapes and styles, therefore the performance of the overall building does not have a proportional shape. Considering Janti Street at the collective relation, its role is getting stronger as the main frame road network.Keywords: Flyover construction, layout changing, Janti AreaAbstrak: Penelitian ini bertujuan untuk menganalisis pengaruh pembangunan Jalan Layang Janti terhadap perkembangan tata ruang Kawasan Janti, meliputi ruang terbangun, ruang terbuka, serta hubungan antar ruang (“linkage”). Metode pengumpulan data dilakukan melalui observasi, pengamatan foto udara, dan wawancara; sedangkan metode analisis melalui deskripsi secara kualitatif yang berupa “superimposed method” dari dua lapisan kondisi lahan, yakni kondisi tata ruang sebelum dan sesudah pembangunan jalan layang. Hasil penelitian menunjukkan bahwa pengaruh pembangunan Jalan Layang Janti terdapat pada massa bangunan (“solid”), pertambahan ruang terbuka yang berupa jaringan jalan, parkir, dan taman; sedangkan pada hubungan antar ruang ̶ secara visual dan struktural ̶ yakni tumbuhnya bangunan dengan bentuk dan gaya baru, sehingga bentuk tampilan bangunan secara keseluruhan tidak proporsional. Pada hubungan kolektif, Jalan Janti semakin kuat perannya sebagai kerangka utama jaringan jalan.Kata kunci : Pembangunan jalan layang, tata ruang, Kawasan Janti


1970 ◽  
Vol 5 (1) ◽  
pp. 77
Author(s):  
Mahadzir Ismail ◽  
Saliza Sulaiman ◽  
Hasni Abdul Rahim ◽  
Nordiana Nordin

The Financial Master Plan (2001- 2010) aims to enhance the capacity of banking industry so that higher effic iency and productivity can be reaped in the future. This study seeks to determine the impact of merger on the efficiency and productivity ofcommercial banks in Malaysia for the period 1995 until 2005. The study uses a non-parametric approach, nam ely DEA (data envelopment analysis?) to estimate the efficiency scores and to construct the Malmquist productivity index. To enable this estimation, three bank inputs and outputs are used. Amongst the findings are those banks exhibit higher efficiency score after the merger and thefo reign banks are more efficient than the local banks. Productivity of the banks is calculated in both periods, before and after the merger: The results show that, it is the local banks that have improved the most after the merger. The main source of productivity is technical change or innovation. The findings support the existing policy of having larger domestic banks in term of size.


2018 ◽  
Vol 7 (1) ◽  
pp. 8-17
Author(s):  
Mahsa Assadi

This study reports a pre-experimental research on the impact of metacognitive instruction on EFL learners’ metacognitive awareness and their listening performance. To obtain the goal of the study, a group of 30 Iranian intermediate EFL learners, including 14 males and 16 females, were selected randomly. Their ages range from 20 to 24. The participants took part in 16 weeks’ intervention program based on metacognitive pedagogical sequence consisted of five stages. The metacognitive awareness listening questionnaire (MALQ), and a listening test were also used to find changes in metacognitive awareness and listening performance before and after the treatment. The results of comparing pre and posttests scores revealed that metacognitive instruction raised the learners’ metacognitive awareness and helped them improve their listening comprehension ability.


2020 ◽  
pp. 1-6
Author(s):  
Paul Park ◽  
Victor Chang ◽  
Hsueh-Han Yeh ◽  
Jason M. Schwalb ◽  
David R. Nerenz ◽  
...  

OBJECTIVEIn 2017, Michigan passed new legislation designed to reduce opioid abuse. This study evaluated the impact of these new restrictive laws on preoperative narcotic use, short-term outcomes, and readmission rates after spinal surgery.METHODSPatient data from 1 year before and 1 year after initiation of the new opioid laws (beginning July 1, 2018) were queried from the Michigan Spine Surgery Improvement Collaborative database. Before and after implementation of the major elements of the new laws, 12,325 and 11,988 patients, respectively, were treated.RESULTSPatients before and after passage of the opioid laws had generally similar demographic and surgical characteristics. Notably, after passage of the opioid laws, the number of patients taking daily narcotics preoperatively decreased from 3783 (48.7%) to 2698 (39.7%; p < 0.0001). Three months postoperatively, there were no differences in minimum clinically important difference (56.0% vs 58.0%, p = 0.1068), numeric rating scale (NRS) score of back pain (3.5 vs 3.4, p = 0.1156), NRS score of leg pain (2.7 vs 2.7, p = 0.3595), satisfaction (84.4% vs 84.7%, p = 0.6852), or 90-day readmission rate (5.8% vs 6.2%, p = 0.3202) between groups. Although there was no difference in readmission rates, pain as a reason for readmission was marginally more common (0.86% vs 1.22%, p = 0.0323).CONCLUSIONSThere was a meaningful decrease in preoperative narcotic use, but notably there was no apparent negative impact on postoperative recovery, patient satisfaction, or short-term outcomes after spinal surgery despite more restrictive opioid prescribing. Although the readmission rate did not significantly increase, pain as a reason for readmission was marginally more frequently observed.


Background: Integrated disease management with self-management for Chronic Obstructive Pulmonary Disease (COPD) is effective to improve clinical outcomes. eHealth can improve patients’ involvement to be able to accept and maintain a healthier lifestyle. Eventhough there is mixed evidence of the impact of eHealth on quality of life (QoL) in different settings. Aim: The primary aim of the e-Vita-COPD-study was to investigate the effect of use of eHealth patient platforms on disease specific QoL of COPD patients. Methods: We evaluated the impact of an eHealth platform on disease specific QoL measured with the clinical COPD questionnaire (CCQ), including subscales of symptoms, functional state and mental state. Interrupted time series (ITS) design was used to collect CCQ data at multiple time points. Multilevel linear regression modelling was used to compare trends in CCQ before and after the eHealth intervention. Results: Of 742 invited COPD patients, 244 signed informed consent. For the analyses, we only included patients who actually used the eHealth platform (n = 123). The decrease of CCQ-symptoms was 0,20% before the intervention and 0,27% after the intervention; this difference was statistically significant (P=0.027). The decrease of CCQ-mental was 0,97% before the intervention and after the intervention there was an increase of 0,017%; this difference was statistically significant (P=0,01). No significant difference was found in the slopes of CCQ (P=0,12) and CCQ-function (P=0,11) before and after the intervention. Conclusion: The e-Vita eHealth platform had a potential beneficial impact on the CCQ-symptoms of COPD patients, but not on functional state. The CCQ-mental state remained stable after the intervention, but this was a deterioration compared to the improving situation before the start of the eHealth platform. In conclusion, this study shows that after the introduction of the COPD platform, patients experienced fewer symptoms, but their mental state deteriorated slightly at the same time. Therefore, health care providers should be aware that, although symptoms improve, there might be a slight increase in anxiety and depression after introducing an eHealth intervention to support self-management.


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