Genetic - fuzzy - grey algorithms: A hybrid model for establishing companies' failure reasons

Scarlat, Emil; Delcea, Camelia; Maracine, Virginia

doi:10.1109/icsmc.2010.5641762

Cited by 9 publications

(7 citation statements)

References 22 publications

(20 reference statements)

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“…Grey systems theory has been widely applied to a great range of domains from the economic and social field such as: decision making (Luo and Song, 2012;Zhu et al, 2012), credit risk assessment (Jin et al, 2012), risk management (Bradea, Delcea and Paun, 2014;Bradea, Delcea, Scarlat, et al, 2014;Maracine et al, 2013), stock market forecasting (Rathnayaka et al, 2015;Scarlat et al, 2010), bankruptcy forecasting (Mărăcine and Delcea, 2009;Zhang and Chen, 2014), innovation competency evaluation (Zhu et al, 2012), evaluating complex products' quality (Xu et al, 2014), etc.…”

Section: Grey Relational Analysismentioning

confidence: 99%

Grey social media engagement analysis

Delcea

2016

Grey Systems: Theory and Application

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.

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Section: Grey Relational Analysismentioning

confidence: 99%

Grey social media engagement analysis

Delcea

2016

Grey Systems: Theory and Application

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“…Having the risk categories and their main key risk indicators a grey incidence analysis has been conducted in accordance with the theoretical mechanisms provided by the grey systems theory (Mărăcine and Delcea, 2009;Scarlat et al, 2010). As a result, the degrees of grey incidence captured in Figure 6 have been reached.…”

Section: Case Studymentioning

confidence: 99%

Fostering risk management in healthcare units using grey systems theory

Delcea

Bradea

2016

Grey Systems: Theory and Application

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Purpose – The identification of the main risk triggers is essential for the hospital’s survival and performance with direct effects on its patients’ health and well-being. For this reason, in this paper some of the most important risk categories have been determined. While in a previous research a qualitative analysis has been done for determining which are the most important risks felt by the patient that are believed to affect their health through the usage of a questionnaire and through conducting a confirmatory factor analysis, the purpose of this paper is to analyze the quantitative side of these risks’ presence in a hospital. Design/methodology/approach – On this purpose, four main categories of risks have been considered (the same as in the qualitative research) and they have been analyzed from the hospital’s point of view – through the usage of the hospital financial and internal documents. Therefore, a series of indicators have been determined for each risk category. After that, a representative indicator has been selected and the grey incidence analysis has been conducted. Findings – By comparing the results gathered form this study with the qualitative analysis conducted among the patients (Delcea et al., 2016) it can be said that there can be seen a difference among the way a hospital and a patient perceive the risks within a medical activity. While for the hospital, the most affecting risk is the technological and hospital conditions risk, for the patients the most affecting risk seems to be the human resources and clinical risk. The mismanagement risk and inability to treat patients is the second in intensity for both the hospital and patients, with a smaller value in the patients’ case. Practical implications – From here, the research can be extended for capturing the risks that are considered to be important for the medical stuff, which will permit us to have a global image over the healthcare risks. After that, a comparative analysis among the hospitals with different financial performance can be conducted in order to see how these risks are affecting their performance and to determine which can be the decisions that can fostering the reduction of these risks. Originality/value – The present paper offers a quantitative analysis from the hospital’s point of view using the advantages offered by the grey systems theory. Combining this analysis with a qualitative one conducted on the patients, the managers of the hospital can a have a more adequate view over the risks that they are facing with. In this context, grey systems theory offers the needed methods for dealing with such situations.

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“…The list can be extended by using some of the financial and accounting indicators presented in the following (Scarlat et al, 2010):…”

Section: Gs 32mentioning

confidence: 99%

Companies' quality characteristics vs their performance

Delcea¹,

Scarlat²,

Cotfas³

2013

Grey Systems: Theory & Appl

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Purpose -This paper attempts to identify the strength of the relation between the quality characteristics of companies that are activating in an economy and their performance. Design/methodology/approach -In the quality characteristics sphere were included almost all the elements related to company's behaviour on a market, in an uncertain environment and in the relations developed with stockholders. And what theory can better shape this relation than grey systems theory, a theory of uncertainty and of continual changes? At first, all of these qualitative characteristics that are reflecting company's activity have been divided into six categories for a better reality reflection. A performance indicator was also depicted by taking into consideration each company's managerial objectives. Findings -By applying grey relational analysis (GRA) in a case of eight Romanian firms, the results were convincing: not only that these characteristics determine firm's evolution, but, by knowing them and acting properly on them, firm's extreme situations (such as insolvency or bankruptcy) can be avoided. Practical implications -The method exposed in the paper can be used for any company for evaluating the linkage between its main characteristics and the way its performance can evolve. Originality/value -The paper succeeds in identifying the linkage between the characteristics of a company at a certain point and its performance by using one of the newest developed theories: grey systems theory.

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Genetic - fuzzy - grey algorithms: A hybrid model for establishing companies' failure reasons

Cited by 9 publications

References 22 publications

Grey social media engagement analysis

Grey social media engagement analysis

Fostering risk management in healthcare units using grey systems theory

Companies' quality characteristics vs their performance

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