Predictive Bankruptcy of European e-Commerce: Credit Underwriters Inexperience and Self-assessment

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F17%3A10365696" target="_blank" >RIV/00216208:11230/17:10365696 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-49559-0_9" target="_blank" >http://dx.doi.org/10.1007/978-3-319-49559-0_9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-49559-0_9" target="_blank" >10.1007/978-3-319-49559-0_9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Predictive Bankruptcy of European e-Commerce: Credit Underwriters Inexperience and Self-assessment

Popis výsledku v původním jazyce

In the current competitive and uncertain e-commerce environment, businesses have the need to predict in advance their likelihood of falling into bankruptcy. The central focus of this paper is to statistically model through different approaches the bankruptcy probability of e-commerce companies in Europe. The authors examine the econometric techniques, two-step cluster, logistic regression, discriminant analysis, data mining tree, and ROC curves, to classify these companies into &quot;bankrupt&quot; and &quot;not bankrupt&quot;. This paper finds also evidences about the current credit underwriting inexperience among several financial institutions. The classification approaches included in this paper may be applied in real working practice whether by credit underwriters or by business decision-makers. The research was developed using financial and accounting information available in the Bureau van Dijk database. This paper suggests further analytical developments in the field of predictive bankruptcies and recommends improvements on the credit evaluation scorecards such as the inclusion of advanced online metrics to increase the accuracy of the creditworthiness evaluation of an e-commerce company.

Název v anglickém jazyce

Predictive Bankruptcy of European e-Commerce: Credit Underwriters Inexperience and Self-assessment

Popis výsledku anglicky

In the current competitive and uncertain e-commerce environment, businesses have the need to predict in advance their likelihood of falling into bankruptcy. The central focus of this paper is to statistically model through different approaches the bankruptcy probability of e-commerce companies in Europe. The authors examine the econometric techniques, two-step cluster, logistic regression, discriminant analysis, data mining tree, and ROC curves, to classify these companies into &quot;bankrupt&quot; and &quot;not bankrupt&quot;. This paper finds also evidences about the current credit underwriting inexperience among several financial institutions. The classification approaches included in this paper may be applied in real working practice whether by credit underwriters or by business decision-makers. The research was developed using financial and accounting information available in the Bureau van Dijk database. This paper suggests further analytical developments in the field of predictive bankruptcies and recommends improvements on the credit evaluation scorecards such as the inclusion of advanced online metrics to increase the accuracy of the creditworthiness evaluation of an e-commerce company.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50201 - Economic Theory

Projekt

—

Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

New Trends in Finance and Accounting

ISBN

978-3-319-49559-0

ISSN

2198-7246

e-ISSN

neuvedeno

Počet stran výsledku

12

Strana od-do

93-104

Název nakladatele

Springer International Publishing AG

Místo vydání

Cham

Místo konání akce

Prague

Datum konání akce

27. 5. 2016

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

000416113500009