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    ASIA unversity > 管理學院 > 經營管理學系  > 博碩士論文 >  Item 310904400/115686


    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/115686


    Title: 運用灰色關聯分析建立印尼伊斯蘭商業銀行財務危機預測模型
    Building a Financial Distress Prediction Model for Islamic Commercial Bank in Indonesia Using Grey Relationship Analysis
    Authors: Johari, Sobar M.
    Contributors: 經營管理學系
    Keywords: 金融危機、灰色關聯分析、灰色預測模型、伊斯蘭商業銀行
    Financial Distress、Grey Relation Analysis、Grey Prediction Model、Islamic Commercial Banks
    Date: 2023
    Issue Date: 2023-05-02 02:00:34 (UTC+0)
    Publisher: 亞洲大學
    Abstract: 財務困難是企業,尤其是銀行業的典型現象。 遇到財務困難的銀行財務業績大幅下降,需要快速修復以降低狀況惡化和資不抵債的風險。 本研究旨在通過使用灰色關聯分析來檢查導致財務困境的因素,從而開發印尼伊斯蘭銀行業財務困難的預測模型。 同時使用灰色預測模型創建模型(1,12)。 這項研究的結果表明,伊斯蘭商業銀行出現財務困難的原因各不相同,其中包括可能成為銀行財務問題主要根源的特定因素。 研究表明,真實的財務困境與使用 GRA 模型預測的財務困境沒有顯著差異 (1,12) 。 可以說 GRA 模型可以用作下一年銀行業危機預測的替代模型。 預計這項工作將生成現有模型的替代模型,用於預測財務問題。 對於實證檢驗,研究人員採用了在印度尼西亞金融服務當局註冊的伊斯蘭商業銀行的 2015-2019 年財務變量.
    Financial difficulty is a typical occurrence in businesses, especially in the banking sector. Banks experiencing financial difficulties typically experience a substantial drop in financial performance, necessitating quick repairs to reduce the risk of deteriorating conditions and insolvency. This study seeks to develop a prediction model of financial difficulty in Indonesian Islamic banking. This study employs Grey Relation Analysis to examine the elements that contribute to financial distress, while the Grey Prediction Model is used to create the model (1,12). The findings of this research reveal that the causes that allow financial hardship to arise in Islamic Commercial Banks are distinct. However, Islamic banking must also be cognizant of a number of specific elements that may be the primary source of financial issues in banks. The research demonstrates that real financial distress is not significantly different from the forecast of financial distress using the GRA Model (1,12). It may be stated that the GRA model can be utilized as an alternate model for banking crisis forecasting in the following year. This work is anticipated to generate an alternate model to existing models for predicting financial trouble. For empirical testing, the researcher employs the 2015-2019 financial variables of Islamic-Commercial Banks registered with the Indonesian financial services authorities (IFS).
    Appears in Collections:[經營管理學系 ] 博碩士論文

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