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Journals / Doğuş Üniversitesi Dergisi / 2026 / Cilt: 6 Sayı: 1

EARLY WARNING SYSTEMS, THE CASE OF TURKEY

ERKEN UYARI SİSTEMLERİ, TÜRKİYE UYGULAMASI

Sinan Aktan(Doğuş University)
Pages
1–15
Publication Date
2005-01-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Our aim is to study if these essential differences between methods affect the empirical selection of independent variables to the models and lead significant differences in failure prediction accuracy; moreover, develop a prediction model that would be benefited by management itself, shareholders, government, vendors, creditors, investors and other stakeholders in their projections and strategies.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:We are focusing on two alternative techniques that can be used empirically to select predictors for failure prediction purposes.
📊
Key Findings & Data:The selected techniques have all different assumptions about the relationships between the independent variables.
💡
Conclusion & Impact:Our aim is to study if these essential differences between methods affect the empirical selection of independent variables to the models and lead significant differences in failure prediction accuracy; moreover, develop a prediction model that would be benefited by management itself, shareholders, government, vendors, creditors, investors and other stakeholders in their projections and strategies.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Ayırma Analizi · Logit Analiz · İşletme Başarısızlıkları

Abstract

We are focusing on two alternative techniques that can be used empirically to select predictors for failure prediction purposes. The selected techniques have all different assumptions about the relationships between the independent variables. Linear discriminant analysis is based on linear combination of independent variables; logit analysis uses logistic cumulative probability distribution function. Our aim is to study if these essential differences between methods affect the empirical selection of independent variables to the models and lead significant differences in failure prediction accuracy; moreover, develop a prediction model that would be benefited by management itself, shareholders, government, vendors, creditors, investors and other stakeholders in their projections and strategies.

Özet

İşletme başarısızlıklarını tahmin üzerine yapacağımız ampirik çalışmamızda iki alternatif teknik üzerinde duracağız. Seçmiş olduğumuz teknikler bağımsız değişkenler arasındaki ilişki üzerinde farklı varsayımlara sahiptir. Doğrusal ayırma analizi, bağımsız değişkenlerin doğrusal kombinasyonlarına bağlı bir modelken; logit analizi ise bağımsız değişkenlerin lojistik kümülatif olasılık dağılımlarına bağlı bir modeldir. Amacımız, metotlar arasındaki farklılıkların, bağımsız değişkenlerin ampirik seçimleri üzerindeki etkÜerini ve başarısızlık tahmini üzerindeki doğruluk paylarını incelemektir. Bunun yanında; işletme yönetiminin, hissedarların, devletin, tedarikçilerin, yatırımcıların ve diğer hak sahiplerinin kolaylıkla faydalanabilecekleri bir ayırma fonksiyonu geliştirmektir.

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Cite This Article

Aktan, S. (2005). EARLY WARNING SYSTEMS, THE CASE OF TURKEY. Doğuş Üniversitesi Dergisi, Cilt: 6 Sayı: 1, 1–15. https://ajindex.com/articles/1172509

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