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Journals / Trakya Üniversitesi Sosyal Bilimler Dergisi / 2020 / Cilt: 22 Sayı: 2

ANALYSIS OF SECTORAL DISTRIBUTION OF BANK CARD, CREDIT CARD AND INTERNET CARD PAYMENTS WITH ORTOGONAL (VERTICAL) AND DIAGONAL (CORNER) MATRIX

BANKA KARTI, KREDİ KARTI VE İNTERNETTEN KART İLE YAPILAN ÖDEMELERİN SEKTÖREL DAĞILIMININ ORTOGONAL (DİKEY) VE DİAGONAL (KÖŞEGEN) MATRİSLER İLE ANALİZİ

Sonat Bayram(Trakya Üniversitesi Uygulamalı Bilimler Fakültesi)0000-0001-9885-8707
Gökhan Sönmezler(Trakya Üniversitesi Uygulamalı Bilimler Fakültesi)0000-0002-4301-6008
Orçun Gündüz(Trakya Üniversitesi Uygulamalı Bilimler Fakültesi)0000-0002-8754-2915
Pages
1063–1084
Publication Date
2020-12-18
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AI Summary & Key Takeaways

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

In the light of results such as eigenvalues, values, forward difference in eigenvalues, and the total variance ratio explained, it was determined that some of the sectors paid by card differ significantly from other sectors and clustered by carrying positive or negative loads (variances).

📌 3 Key Takeaways

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Objective & Hypothesis:In order to reveal the sectoral composition between the years (2003-2020) with the inflation-free (real) values of the Payments made by Debit Card, Credit Card and Internet Card, and to increase the efficiency of payment systems by identifying similar and differentiated sectors, Binary Loads (Orthogonal (Vertical) and Diagonal (Diagonal) matrices are created.
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Key Findings & Data:The eigenvalues, eigenvectors (charges) and ordinary correlation results obtained from the matrices are combined in the plane of the binary load graph and the shapes of the columns are equalized to the eigenvalues using Mahalanobis distances, and without observation scaling so that the cosines of the angles between the vectors are equal to the correlations between the variables, the results are interpreted only in a constant proportionality.
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Conclusion & Impact:In the light of results such as eigenvalues, values, forward difference in eigenvalues, and the total variance ratio explained, it was determined that some of the sectors paid by card differ significantly from other sectors and clustered by carrying positive or negative loads (variances).
🔬Design:Araştırma Makalesi
📍Scope:2003-2020 Verileri
⚙️Variables:Banka Kartı · Kredi Kartı · İnternetten Kart ile Ödeme

Abstract

In order to reveal the sectoral composition between the years (2003-2020) with the inflation-free (real) values of the Payments made by Debit Card, Credit Card and Internet Card, and to increase the efficiency of payment systems by identifying similar and differentiated sectors, Binary Loads (Orthogonal (Vertical) and Diagonal (Diagonal) matrices are created. The eigenvalues, eigenvectors (charges) and ordinary correlation results obtained from the matrices are combined in the plane of the binary load graph and the shapes of the columns are equalized to the eigenvalues using Mahalanobis distances, and without observation scaling so that the cosines of the angles between the vectors are equal to the correlations between the variables, the results are interpreted only in a constant proportionality. In the light of results such as eigenvalues, values, forward difference in eigenvalues, and the total variance ratio explained, it was determined that some of the sectors paid by card differ significantly from other sectors and clustered by carrying positive or negative loads (variances).

Özet

Banka Kartı, Kredi Kartı ve İnternetten Kart ile Yapılan Ödemelerin enflasyondan arındırılmış (reel) değerleri ile (2003-2020) yılları arasındaki sektörel bileşimini ortaya koymak, benzeşen ve ayrışan sektörleri tespit ederek ödeme sistemlerinin etkinliğinin arttırılmasını sağlamak maksadıyla, korelasyon matrisleri ile İkili Yükler (Ortogonal (Dikey) ve Diagonal (Köşegen)) matrisler oluşturulmuştur. Matrislerden elde edilen özdeğerler, özvektörler (yükler) ve sıradan korelasyon sonuçları ikili yük grafik düzleminde birleştirilerek ve Mahalanobis mesafeleri kullanılarak sütunların şekilleri özdeğerlere eşitlenmekte ve vektörler arasındaki açıların kosinüsleri değişkenler arasındaki korelasyonlara eşit olacak şekilde gözlem ölçeklendirmesi olmadan, sonuçlar yalnızca sabit bir orantılılık içerisinde yorumlanmaktadır. Özdeğerler, değerler, özdeğerlerdeki ileriye doğru fark, açıklanan toplam varyans oranı gibi sonuçlar ışığında, kart ile ödeme yapılan sektörlerden bazılarının diğer sektörlerden ciddi ölçüde ayrıştığı ve pozitif veya negatif yükler (varyanslar) taşıyarak kümelendiği tespit edilmiştir.

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Cite This Article

Bayram, S., Sönmezler, G., Gündüz, O. (2020). ANALYSIS OF SECTORAL DISTRIBUTION OF BANK CARD, CREDIT CARD AND INTERNET CARD PAYMENTS WITH ORTOGONAL (VERTICAL) AND DIAGONAL (CORNER) MATRIX. Trakya Üniversitesi Sosyal Bilimler Dergisi, Cilt: 22 Sayı: 2, 1063–1084. https://doi.org/10.26468/trakyasobed.802253

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