• Journal of Arbitration Studies
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• v.34 no.2
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• pp.3-26
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• 2024

The insolvency proceedings, which are collective debt processing procedures that equitably distribute properties of the debtor who is declared insolvency to multiple creditors, and the arbitral proceedings that resolve disputes over individual legal relationships between the parties differ in nature. However, there are no express provisions that directly regulate the legal relationships when the party to an arbitration agreement is declared insolvency. The presence of an arbitration agreement between the parties does not necessarily initiate the arbitral proceedings, the arbitral proceedings are initiated by the parties' application under the arbitration agreement. It is also necessary to examine the effect of the insolvency of the party to the arbitration agreement on the arbitral proceedings step by step. This paper reviews the cases in which the parties to the arbitration agreement have been declared insolvency before the commencement of the arbitral proceedings and have been declared insolvency during the arbitral proceedings. This paper examines how the effect of the arbitration agreement affects the insolvency proceedings when the debtor is declared insolvency after concluding the arbitration agreement and how the declaration of insolvency affects the arbitral proceedings when the debtor, who is a party to the arbitration agreement, is declared insolvency during the arbitration proceedings.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.432-438
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• 2011

The purpose of the present thesis is to develop bankruptcy prediction models capable of being applied to the Korean construction industry and to deduce an optimal model through comparative evaluation of final developed models. A study population was selected as general contractors in the Korean construction industry. In order to ease the sample securing and reliability of data, it was limited to general contractors receiving external audit from the government. The study samples are divided into a bankrupt company group and a non-bankrupt company group. The bankruptcy, insolvency, declaration of insolvency, workout and corporate reorganization were used as selection criteria of a bankrupt company. A company that is not included in the selection criteria of the bankrupt company group was selected as a non-bankrupt company. Accordingly, the study sample is composed of a total of 112 samples and is composed of 48 bankrupt companies and 64 non-bankrupt companies. A financial ratio was used as early predictors for development of an estimation model. A total of 90 financial ratios were used and were divided into growth, profitability, productivity and added value. The MDA (Multivariate Discriminant Analysis) model and BLRA (Binary Logistic Regression Analysis) model were used for development of bankruptcy prediction models. The MDA model is an analysis method often used in the past bankruptcy prediction literature, and the BLRA is an analysis method capable of avoiding equal variance assumption. The stepwise (MDA) and forward stepwise method (BLRA) were used for selection of predictor variables in case of model construction. Twenty two variables were finally used in MDA and BLRA models according to timing of bankruptcy. The ROC-Curve Analysis and Classification Analysis were used for analysis of prediction performance of estimation models. The correct classification rate of an individual bankruptcy prediction model is as follows: 1) one year ago before the event of bankruptcy (MDA: 83.04%, BLRA: 93.75%); 2) two years ago before the event of bankruptcy (MDA: 77.68%, BLRA: 78.57%); 3) 3 years ago before the event of bankruptcy (MDA: 84.82%, BLRA: 91.96%). The AUC (Area Under Curve) of an individual bankruptcy prediction model is as follows. : 1) one year ago before the event of bankruptcy (MDA: 0.933, BLRA: 0.978); 2) two years ago before the event of bankruptcy (MDA: 0.852, BLRA: 0.875); 3) 3 years ago before the event of bankruptcy (MDA: 0.938, BLRA: 0.975). As a result of the present research, accuracy of the BLRA model is higher than the MDA model and its prediction performance is improved.