The Job Security of Employees of Financially Distressed Companies

2021 ◽  
Vol 33 (2) ◽  
pp. 200-237
Author(s):  
Mieka E Loubser ◽  
Christoph Garbers
Keyword(s):  
Financial Distress ◽  
Job Security ◽  
Legislative Regulation ◽  
Permanent Loss ◽  
Financially Distressed ◽  
A Company

This contribution considers the legislative regulation of the job security (which boils down to preservation of employment) of employees in case of financial distress of a company. It juxtaposes the legislative regulation of four interrelated processes a company may engage in where it finds itself in financial distress, namely a voluntary internal restructuring (especially retrenchment), the transfer of the business or part of the business, business rescue and winding up. The legislative endeavour to preserve the job security of employees in all these processes is described and analysed. The discussion shows that room exists for companies to circumvent this protection and, to the extent that the protection does apply, that it remains difficult for employees to ultimately challenge the substance of decisions negatively affecting their job security. The main protection for employees in all these processes is procedural in nature and to be found in their rights to be informed of and consulted prior to decisions negatively affecting them. In this regard, business rescue is the most employee-friendly process. Participation in this process by employees, however, requires a fine balance as it may be self-defeating and lead to winding up and the permanent loss of jobs.

Financial Distress, Earnings Benchmark and Earnings Management Practices

2021 ◽  
pp. 097226292110109
Author(s):  
Karan Gandhi
Keyword(s):  
Panel Data ◽  
Earnings Management ◽  
Financial Distress ◽  
Management Practices ◽  
Real Earnings Management ◽  
Public Companies ◽  
Large Panel ◽  
Distressed Firms ◽  
Contradictory Evidence ◽  
Financially Distressed

Prior research exhibits contradictory evidence on earnings management practices, both accrual and real, undertaken by the firms in state of financial distress. This study uniquely examines the issue in the presence of earnings-increasing earnings management motivation- meeting earnings benchmark of avoiding losses. For examining the issue, this study analyzes large panel data of Indian public companies for the period 2000–2016. The findings indicate prevalence of earnings-decreasing real earnings management practices, that is, decrease in overproduction and increase in spending on discretionary expenses, in financially distressed firms despite there being motivation to increase earnings to avoid losses. No evidence of accrual earnings management practices has been observed in such firms.

scholarly journals An Empirical Test Of The View Of Inventory As A Liability IN Explaining Financial Distress

2011 ◽  
Vol 14 (2) ◽  
pp. 83 ◽  
Author(s):  
Benjamin P. Foster ◽  
M. Cathy Sullivan ◽  
Terry J. Ward
Keyword(s):  
Logistic Regression ◽  
Financial Distress ◽  
Regression Models ◽  
Empirical Test ◽  
Explanatory Power ◽  
Manufacturing Firms ◽  
Logistic Regression Models ◽  
Financially Distressed ◽  
Accounting Ratios ◽  
Extreme View

<span>This study reports a first attempt in a financial distress context to test the extreme JIT and TOC view that inventory is a liability. We compared inventory levels and the change in inventory for healthy and financially distressed manufacturing firms. We also compared the explanatory power of logistic regression models including traditional accounting ratios to that of models including accounting ratios created by viewing inventory as a liability. We found some support for the extreme view of some JIT and TOC proponents that traditional inventory should be considered a liability.</span>

Indirect financial distress costs in non-financial firms: evidence from an emerging market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Farooq ◽  
Shahzadah Fahed Qureshi ◽  
Zahra Masood Bhutta
Keyword(s):  
Financial Distress ◽  
Intangible Assets ◽  
Emerging Market ◽  
Investment Policy ◽  
Tobin’S Q ◽  
Optimal Model ◽  
Tobin's Q ◽  
Content Type ◽  
Tangible Assets ◽  
Financially Distressed

Purpose This study aims to analyse 508 financially distressed firm-year observations for the period 2010–2018 of Pakistan Stock Exchange (PSX) listed firms to examine the magnitude of indirect financial distress costs (IFDC) and to investigate which firm-specific variable is relatively important in explaining these indirect costs. This will not only enrich empirical literature but also helpful in cross-country comparison. Design/methodology/approach Optimal model selection along with panel data analysis technique is used to select the most optimal model to observe the findings. Financial distress is measure through Altman’s Z-score and firm-specific variables cover leverage, level of intangible assets, investment policy, tangible assets, firm’s size, level of liquid assets and Tobin’s Q of sample firms. Findings The findings of this study show that the average size of IFDC for the sample observations is 6.70%. In addition to this, finding further suggest that leverage, the level of intangible assets and changes in investment policy have positive while the size of the firm and Tobin’s Q have a significant negative impact on IFDC. Further, this paper argues that the level of tangible assets and liquid assets are statistically unimportant in observing the IFDC for PSX financially distressed firm-year observations. Practical implications The findings of this study provide more insight to corporate managers and investors about the association between firm-specific financial characteristics and IFDC concerning Pakistani firms. Furthermore, this study contributes to the existing literature by adding new evidence from developing countries such as Pakistan which are helpful for regulatory bodies and policymakers in the formulation of long-term strategies to manage the financial distress costs. Originality/value The study extends the body of existing literature on IFDC regarding Pakistan. The results suggest that policymakers may pay special attention to the quality of a firm’s capital structure strategies while predicting corporate financial distress costs.

Chapter 13

1996 ◽  
pp. 174-182
Keyword(s):  
Job Security ◽  
Wage Cuts ◽  
Career Uncertainty ◽  
A Company ◽  
Salary Negotiations

This chapter explores Salter’s period of career uncertainty towards the end of his life and provides a reflection on the job security and discontent of both a miner and a mariner. Salter provides a summary of the speed of which a Company can rise and fall and documents his own experience of wage cuts and salary negotiations. Salter ends Chapter 14 with his unemployment, in 1870.

Corporate governance during financial distress – an empirical analysis

2016 ◽  
Vol 58 (5) ◽  
pp. 486-506 ◽  
Author(s):  
Marjan Marandi Parkinson
Keyword(s):  
Corporate Governance ◽  
Empirical Research ◽  
Financial Distress ◽  
Legal Theory ◽  
Case Study Research ◽  
Theory And Practice ◽  
Positive Contribution ◽  
Content Type ◽  
Financially Distressed

Purpose The traditional form of legal research with its predominant emphasis on doctrinal and theoretical analysis is now increasingly augmented by empirical research that seeks to document actions and decisions and draw broader conclusions. This relatively new research tradition is arguably making a positive contribution to legal theory and practice, particularly in the USA [for a general discussion see SJ Lubben, “Do Empricial Bankruptcy Studies Matter?” (2012) 20 ABI L Rev 715]. The paper aims to report on the use of empirical research to examine corporate governance in the context of financially distressed UK public companies. Design/methodology/approach The paper uses statutory corporate filings and mandatory stock exchange reports to document the process of informal debt resolution prior to the company’s entry into administration or Company Voluntary Arrangement. The findings are presented in an innovative way as a series of case studies focusing on process, participants and outcomes of informal debt resolution. Findings The paper concludes that it is possible to use case study research as a means to explore corporate governance in the context of financially distressed companies. Although such an approach is challenging in various ways, there are some advantages that complement more traditional research approaches. The findings show how directors’ attention shifts away from shareholders’ interests to those of creditors at times of financial distress and challenges conventional models of governance that stress shareholder value. Originality/value The distinctive features of the research are the development of a case-study based approach that draws on publicly available data sources, a process based analysis and a synthesis of corporate governance and law.

scholarly journals MODEL ALTMAN SCORE DAN GROVER SCORE : MENDETEKSI FINANCIAL DISTRESS PADA PERUSAHAAN RITEL DI INDONESIA

AKUNTABILITAS ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 133-154
Author(s):  
Patmawati Patmawati ◽  
Muhammad Hidayat ◽  
Muhammad Farhan
Keyword(s):  
Structural Equation Model ◽  
Financial Distress ◽  
Structural Equation ◽  
Positive Impact ◽  
Poor Performance ◽  
Equation Model ◽  
Analysis Method ◽  
Public Companies ◽  
Score Model ◽  
A Company

This study aims to detect financial distress of listed retail companies at Indonesian Exchange using Altman Score and Grover Score Model. The samples are go public companies in Indonesia, which consist of 20 retail companies. Structural Equation Model (SEM) was employed as the analysis method using PLS software. The result shows that Altman Score Model has positive impact toward financial distress. High score on Altman Score indicates poor performance of a company. Further, Grover Score model has positive impact toward financial distress on retail companies which are go public circa 2015-2018. Higher score of grover score indicates a company has been suffering financial distress. Lastly, we inference that Altman Score Model is more accurate in detecting financial distress compared to Grover Score Model     

scholarly journals Financial Distress Prediction Using RGEC Model on Foreign Exchange Banks and Non-Foreign Exchange Banks

2019 ◽  
Vol 2 (1) ◽  
pp. 48-55
Author(s):  
Laely Aghe Africa
Keyword(s):  
Logistic Regression ◽  
Foreign Exchange ◽  
Financial Distress ◽  
Risk Profile ◽  
Capital Adequacy ◽  
Financial Distress Prediction ◽  
Good Corporate Governance ◽  
Capital Adequacy Ratio ◽  
Distress Prediction ◽  
A Company

The bankruptcy of a company can be marked called Financial Distress, and the company is expected to anticipate the situation. This research aimed to analyze whether the RGEC model can be used to predict Financial Distress on Foreign Exchange Banks and Non-Foreign Exchange Banks. The RGEC model uses several ratios including Risk Profile represented by NPL (Non-Performing Loan) LDR (Loan to Deposit Ratio), GCG is represented by the Composite Value of GCG (Good Corporate Governance), Earnings is represented by ROA (Return On Asset), and Capital is represented by CAR (Capital Adequacy Ratio). It is a quantitative study, with a sample of 185 data of Foreign Exchange Bank and Non-Foreign Exchange ranging from 2013 to 2017, and fulfills this criterion for research from IDX. Logistic regression was used in analyzing data and using SPSS version of IBM 23. The results of the study indicate that NPL, GCG, ROA, and CAR are best used to predict financial distress in Foreign Exchange Bank and Non-Foreign Exchange Bank. The results can be applied to banking companies in determining what policies need to be taken when the company experiences Financial Distress.

scholarly journals Analisis Perbandingan Financial Distress Pada Perusahaan Sub Sektor Rokok Periode 2015-2019

2021 ◽  
Vol 3 (3) ◽  
pp. 157-163
Author(s):  
Anang Makruf ◽  
Deni Ramdani
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Market Value ◽  
Sampling Technique ◽  
Z Score ◽  
Book Value ◽  
Purposive Sampling ◽  
Quantitative Models ◽  
A Company ◽  
Analyze Data

Abstract – The aim of the study was to analyze financial distress in cigarette companies list in Indonesia Stock Exchange in 2015-2019 using 3 methods, Altman Z-Score, Zmijewski, and Springate. Purposive sampling is used in this study to determine the sampling technique. The sample used in this study released 4 cigarette companies. Descriptive asalysis with quantitative models was used to analyze data in this research. Altman Z-Score, Zmijewski, and Springate in 2015-2019 PT. HM Sampoerna Tbk, PT. Gudang Garam Tbk, and PT. Wismilak Inti Makmur Tbk is related to safe, but it is needed a company that is estimated to be grey in the Altman Z-Score calculation in 2018, PT. Wismilak Inti Makmur Tbk. The Z-score is at the limit because the companie has a ratio with a lower value in market value of equity  to book value of liabilities   Abstrak – Penelitian ini memiliki bertujuan untuk menganalisis perbandingan kesulitan keuangan dalam perusahaan sun sektor rokok di Indonesia Stock Exchange periode 2015-2019 menggunakan tiga metode. Metode yang digunakan yaitu Altman Z-Score, Zmijewski, dan Springate. Purposive sampling digunakan dalam penelitian ini untuk menentukan teknik pengambilan sampel. Sampel yang digunakan berjumlah 4 perusahaan rokok. Analisis deskriptif dengan pendekatan kuantitatif digunakan sebagai teknik analisis data. Dalam penelitian ini menjelaskan financial distress yang dihitung menggunakan metode Altman Z-Score, Zmijewski , dan Springate pada tahun 2015-2019 PT. HM Sampoerna Tbk, PT. Gudang Garam Tbk, dan PT. Wismilak Inti Makmur Tbk mengalami dalam kondisi keuangan yang sehat, namun terdapat perusahaan yang diestimasi rawan kebangkrutan pada perhitungan Altman Z-Score pada  tahun 2018 yaitu PT. Wismilak Inti Makmur Tbk. hal ini dapat terjadi  karena nilai Z-Score PT. Wismilak Inti MakmurTbk  berada pada Z < 1,81 salah satu penyebabnya ialah rendahnya rasio market value of equity terhadap liabilities.

scholarly journals Financial Distress Prediction Using Hybrid Machine Learning Techniques

2020 ◽  
pp. 1-12
Author(s):  
Suduan Chen ◽  
Zong-De Shen
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Financial Distress ◽  
Machine Learning Techniques ◽  
Financial Variables ◽  
Financial Distress Prediction ◽  
Learning Techniques ◽  
Distress Prediction ◽  
Hybrid Machine ◽  
Financially Distressed

The purpose of this study is to establish an effective financial distress prediction model by applying hybrid machine learning techniques. The sample set is 262 financially distressed companies and 786 non-financially distressed companies, listed on the Taiwan Stock Exchange between 2012 and 2018. This study deploys multiple machine learning techniques. The first step is to screen out important variables with stepwise regression (SR) and the least absolute shrinkage and selection operator (LASSO), followed by the construction of prediction models, as based on classification and regression trees (CART) and random forests (RF). Both financial variables and non-financial variables are incorporated. This study finds that the financial distress prediction model built with CART and variables screened by LASSO has the highest accuracy of 89.74%.

scholarly journals Analisis Penilaian Financial Distress Dengan Menggunakan Model Altman Z-Score Dan Model Springate Pada Perusahaan Manufaktur Yang Terdaftar Di Bursa Efek Indonesia Periode Tahun 2015-2019

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Febriana Anindyka ◽  
Makhmud Zulkifli
Keyword(s):  
Data Analysis ◽  
Financial Distress ◽  
Descriptive Statistics ◽  
Z Score ◽  
Financial Condition ◽  
Similarities And Differences ◽  
The Difference ◽  
Score Model ◽  
A Company ◽  
Data Analysis Methods

The aim of this research to analyze financial distress of Manufature Company by using Altman Z-Score and Springate Models. Moreover, this research aimed to know aims to determine the similarities and differences in the results of the analysis of financial distress assessment using the Altman Z-Score model and the Springate Model. This research used Descriptive statistics and data analysis methods used  in this research were Altman Z-Score and Springate Model. To the finding on the research, it showed that (1) ) After evaluating the Altman Z-Score and Springate models, there are fifty companies that fall into different conditions. (2) The similarities and differences in the results of the Atman Z-Score model and the Springate model are the results of the two models that can be seen from having almost the same variable components and the difference is that the results of the financial distress assessment using the Altman Z-score model and the Springate model show that both These models have different criteria in determining the financial condition of a company.

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