Predicción del fracaso empresarial: Una contribución a la síntesis de una teoría mediante el análisis comparativo de distintas técnicas de predicción

Monelos, Pablo de Llano; Sánchez, Carlos Piñeiro; López, Manuel Rodríguez

doi:10.4067/s0718-52862016000200001

Cited by 12 publications

(2 citation statements)

References 42 publications

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“…He concluded that an artificial neural network was the most recommended technique for the Korean hotel sector due to its high accuracy and small relative error costs. de Llano Monelos et al. (2016) compared the effectiveness of eight popular prediction methods, pointing out that different methodologies used in each study did not show significant influence on the results, and they suggested focusing on improving the quality of informational context of variables rather than designing sophisticated analysis techniques.…”

Section: Literature Review Of Bibliometric Study and Bankruptcy Predimentioning

confidence: 99%

A bibliometric study on intelligent techniques of bankruptcy prediction for corporate firms

Shi

2019

Heliyon

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Bibliometric analysis is an effective method to carry out quantitative study of academic output to address the research trends on a given area of investigation through analysing existing documents. This paper aims to explore the application of intelligent techniques in bankruptcy predictions so as to assess its progress and describe the research trend through bibliometric analysis over the last five decades. The results indicate that, although there is a significant increase in publication number since the 2008 financial crisis, the collaboration among authors is weak, especially at the international dimension. Also, the findings provide a comprehensive view of interdisciplinary research on bankruptcy modelling in finance, business management and computer science fields.The authors sought to contribute to the theoretical development of bankruptcy prediction modeling by bringing new knowledge and key insights. Artificial intelligent techniques are now serving as important alternatives to statistical methods and demonstrate very promising results. This paper has both theoretical and practical implications. First, it provides insights for scholars into the theoretical evolution and intellectual structure for conducting future research in this field. Second, it sheds light on identifying under-explored machine learning techniques applied in bankruptcy prediction which can be crucial in management and decision-making for corporate firm managers and policy makers.

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Section: Literature Review Of Bibliometric Study and Bankruptcy Predimentioning

confidence: 99%

A bibliometric study on intelligent techniques of bankruptcy prediction for corporate firms

Shi

2019

Heliyon

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“…In 1966, the first research paper on business failure was published in the Journal of Accounting Research [22]. Since then, a great deal of research has focused on predicting corporate insolvency scenarios; therefore, it is necessary to evaluate the development of this research and identify the main actors (e.g., countries, institutions, authors) and suggest directions for future research [23][24][25][26][27]. A review of articles related to the subject is of great help to those who wish to approach this line of research, since the literature often appears confusing and chaotic for those who start in this field [28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Explanatory Factors of Business Failure: Literature Review and Global Trends

2021

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This study aims to provide a bibliometric analysis of business failure research, recognise the main existing research topics and establish future research challenges. The results, based on a sample of 588 articles, show that the number of published papers and citations has grown steadily, especially in the last 14 years. The most productive and relevant journals, countries, institutions and authors are presented using bibliometric performance indicators. In addition, through the graphical mapping of strategic diagrams, this study identifies the most significant research trends and proposes several directions for future research. The results of this research may be helpful for beginner researchers and experts in business failure, as they contribute to bringing clarity to this line of investigation. These results reveal all the aspects involved in business failure research, analysing its temporal and methodological characterisation, and the most prolific authors who have participated in its study (see, i.e., H. Li), leading journals (see, i.e., Expert Systems with Applications) or academic institutions that have headed the scientific analysis of this business phenomenon. Likewise, it has been possible to identify three main areas in which the research on business failure has been focused: business, management and accounting; economics, econometrics and finance; and social sciences. In addition, a complete, synthesised and organised summary of the various definitions, perspectives and research trends are presented.

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Ensemble Classification Methods With Applicationsin R

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Predicción del fracaso empresarial: Una contribución a la síntesis de una teoría mediante el análisis comparativo de distintas técnicas de predicción

Cited by 12 publications

References 42 publications

A bibliometric study on intelligent techniques of bankruptcy prediction for corporate firms

A bibliometric study on intelligent techniques of bankruptcy prediction for corporate firms

Explanatory Factors of Business Failure: Literature Review and Global Trends

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