4 edition of DEA based analysis of corporate failure found in the catalog.
DEA based analysis of corporate failure
Paul C. Simak
by National Library of Canada = Bibliothèque nationale du Canada in Ottawa
Written in English
|Series||Canadian theses = Thèses canadiennes|
|The Physical Object|
Why Do You Need to Conduct Failure Analysis? Failure analysis is a complex, critical, and multi-disciplinary process. As an important tool for managing and operating establishments and companies, this document can be included in a hotel SWOT analysis or any failure reports and assessments of businesses from various industries and fields of corporate expertise. Downloadable (with restrictions)! Abstract The purpose of this study is to measure the financial efficiency of firms considering both input and procurement capital. We propose a new method called three-dimensional data envelopment analysis model and conducted an efficiency analysis of 33 companies in Korea manufacturing auto parts. The results of the study are summarized as follows.
DEA as a business failure prediction tool. Application to the case of galician SMEs Contaduría y Administración 59 (2), abril-junio 67 creditors, employees, etc. Direct costs associated with business failure in the ju-dicial environment represent an average 5% of the company’s book . China’s primary health care system is the key to guaranteeing and implementing the “full coverage, basic protection” social medical policy. This study uses the DEA model and the entropy-weight TOPSIS method to estimate the efficiency of China’s primary medical and health institutions in The results found that in , the overall mean score of the efficiency of primary medical.
Corporate Failure Definition: The term corporate failure entails discontinuation of company’s operations leading to inability to reap sufficient profit or revenue to pay the business happens due to poor management, incompetence, and bad marketing strategies. Finally we look at possible ways in which failure might be prevented. Corporate failure models. There are two types of corporate failure models: quantitative models, which are based largely on published financial information; and qualitative models, which are based on an internal assessment of the company concerned.
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Data Envelopment Analysis. The goal of this work was to validate the hypothesis that DEA can be used as a tool for predicting future corporate distress.
DEA models were used to predict the financiai viability of firms based on their historicai financial data. The DEA Cited by: Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success.
The proposed approach is applied to a random sample of firms, which is composed of 50 large US bankrupt firms randomly selected from Altman's bankruptcy Cited by: distress zones by proposing cut-off points based on 5 years DEA analysis.
The result shows that the proposed method has obvious advanta ges in predicting corporate financial stress. Keywords Corporate Failure, Non-Manufacturing Company, Services Industry, Predictions, Data Envelopment Analysis (DEA), Altman’s Z Score 1. Introduction. DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment I.M.
Premachandraa,n, Yao Chenb, John Watsonc a Department of Finance and Quantitative Analysis, University of Otago, School of Business, Dunedin, New Zealand b College of Management, University of Massachusetts at Lowell, Lowell, MAUSA c Department of Accounting and Finance, Monash.
Recently, data envelopment analysis (DEA), rather than Altman's Z score model and traditional parametric methods, has become a research interest in relation to predicting corporate failure. However, there is still no research showing how to fix appropriate cut‐off points to Author: Joseph C.
Paradi, Xiaopeng Yang, Kaoru Tone. Downloadable (with restrictions). Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success.
The proposed approach is applied to a random sample of firms, which is composed of 50 large US bankrupt firms randomly selected from Altman's bankruptcy database and. AB - Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success.
The proposed approach is applied to a random sample of firms, which is composed of 50 large US bankrupt firms randomly selected from Altman s.
The purpose of this work was to study the ability of the Slacks-Based Model of Data Envelopment Analysis in the prediction of corporate failure of non-manufacturing companies as compared to Altmans Z score model. DEA had been tested for corporat e failure before.
He said that efficiency scores in DEA analyses can be too slant, especially when using super-efficient DEA models. Therefore, if we use the DEA analysis as a tool to forecast business failure, we should use an adjusted discriminant analysis or an evaluating function, establishing values between and for the cut-off point.
Corporate failure is normally a reflection of deep-seated corporate shortcomings, according to a report by the Cass Business School in London and published by Airmic, the risk management association.
Paul Hopkin, Airmic’s technical director, discusses the implications. Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success.
Abstract. This paper proposes a hybrid approach that predicts the failure of firms based on the past business data, combining rough set approach and worst practice data envelopment analysis (DEA).
corporate failure, nor do corporate failures occur only as a result of fraud. However, in some of the biggest corporate failures across the globe, fraud was involved. No single model can successfully predict the risks of fraud or the fact that fraud is occurring or has occurred.
Much research has been done globally to measure fraud, many articles. Zhu, Data Envelopment Analysis: A handbook of Empirical Studies and Applications, Springer,ISBN About this Book This handbook compiles state-of-the-art empirical studies and applications using Data Envelopment Analysis (DEA).
It includes a collection of 18 chapters written by DEA. Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers.
It is used to empirically measure productive efficiency of decision making units (DMUs). Although DEA has a strong link to production theory in economics, the tool is also used for benchmarking in operations management, where a set of measures is selected.
Corporate Financial Distress: An Empirical Analysis of Distress Risk DISSERTATION of the University of Graduate School of Business Administration, Economics, Law and Social Sciences (HSG) to obtain the title of Doctor Oeconomiae submitted by Natalia Outecheva from Russia approved on the application of Prof.
Klaus Spremann and. This paper aims to assess the application of seven statistical and data mining techniques to second-stage data envelopment analysis (DEA) for bank performance.,Different statistical and data mining techniques are used to second-stage DEA for bank performance as a part of an attempt to produce a powerful model for bank performance with effective predictive ability.
DEA as a business failure prediction tool Application to the case of galician SMEs Fecha de recepción: Fecha de aceptación: Abstract In the research group we are working to provide further em-pirical evidence on the business failure forecast.
Complex fit. We develop a model using DEA to predict the likelihood of failure of US companies in the retail-apparel industry based on information available from annual reports—financial statements and their corresponding Notes, Management’s Discussion and Analysis, and Auditor’s Report.
Liquidity Efficiency in the Greek Listed Firms: A Financial Ratio Based on Data Envelopment Analysis: /ijcfa The scope of this paper is to investigate the liquidity efficiency of the Food and Beverage listed firms in the Athens Exchange, for the period.
[Page (continued)] A Data Envelopment Analysis Example. Data envelopment analysis (DEA) is a linear programming application that compares a number of service units of the same typesuch as banks, hospitals, restaurants, and schoolsbased on their inputs (resources) and outputs.
From the analysis it’s found that distress is mostly caused as a result of poor corporate governance. To stem distress and its debilitating effect, there is a need for the adoption of new audit framework which stresses on time limit of audit tenure with a client, forensic audit, retrospective audit procedure, and auditor’s skepticism.In this study, the Data Envelopment Analysis (DEA) method is used, which is one of the potential tools available.
Several researchers have used the DEA method to measure corporate performance.