Evaluation of Financial Performance of Companies in Marmara Region Through A Systematic Multi-Criteria Decision-Making Approach

Stok Kodu:
9786256319806
Boyut:
16x24
Sayfa Sayısı:
117
Baskı:
1
Basım Tarihi:
2024-09
Kapak Türü:
Ciltsiz
Kağıt Türü:
2. Hamur
%35 indirimli
158,00TL
102,70TL
Taksitli fiyat: 12 x 10,92TL
Havale/EFT ile: 100,65TL
Temin süresi 6 gündür.
9786256319806
952399
Evaluation of Financial Performance of Companies in Marmara Region Through A Systematic Multi-Criteria Decision-Making Approach
Evaluation of Financial Performance of Companies in Marmara Region Through A Systematic Multi-Criteria Decision-Making Approach
102.70

Financial performance analysis is critical to users such as managers, business employees, the government, lenders, investors, and others. It is crucial for making forecasts for the future, evaluating a business’s position within the industry, and determining its standing relative to competitors. Therefore, this study analyzed thirty-seven companies listed on the ISO 500 2022 list in the Marmara Region and traded on BIST using seventeen evaluation criteria. Firstly, the financial data of the firms were collected. Due to the presence of negative values in the collected data, the Z-Score Standardization Method was used. Subsequently, the weights of the criteria were determined using the ENTROPY Method. Three different Fuzzy TOPSIS variations were utilized to evaluate the company alternatives. These variations were Triangular Fuzzy TOPSIS, Trapezoidal Fuzzy TOPSIS, and Intuitionistic Fuzzy TOPSIS Methods. The evaluation results obtained from each TOPSIS variation were integrated using the Borda Count Method to derive a single ranking. Among the evaluation criteria, the Inventory Turnover Ratio (C1) was the most important, with a weight of 0.36, followed by the Book Value Per Share Ratio (C15), with a weight of 0.12, and the Current Ratio (C1), with a weight of 0.09. Conversely, the Operating Cash Flow Ratio (C4), Return on Equity Ratio (C14), and Price-Earnings Ratio (C17) were the least critical criteria, each with a weight of 0.00. As a result, the best company alternatives were AYGAZ, FROTO, TOASO, BOBET, and BANVT, while the worst company alternatives were DGNMO, DEVA, VESTL, TATGD, and HEKTS. These findings provided valuable insights for stakeholders, enabling them to make more informed investment and strategic planning decisions.

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Axess Kartlar
Taksit Sayısı Taksit tutarı Genel Toplam
Tek Çekim 102,70    102,70   
3 37,41    112,23   
6 19,75    118,51   
9 13,87    124,79   
12 10,92    131,06   
QNB Finansbank Kartları
Taksit Sayısı Taksit tutarı Genel Toplam
Tek Çekim 102,70    102,70   
3 37,41    112,23   
6 19,75    118,51   
9 13,87    124,79   
12 10,92    131,06   
Bonus Kartlar
Taksit Sayısı Taksit tutarı Genel Toplam
Tek Çekim 102,70    102,70   
3 37,41    112,23   
6 19,75    118,51   
9 13,87    124,79   
12 10,92    131,06   
Paraf Kartlar
Taksit Sayısı Taksit tutarı Genel Toplam
Tek Çekim 102,70    102,70   
3 37,41    112,23   
6 19,75    118,51   
9 13,87    124,79   
12 10,92    131,06   
Maximum Kartlar
Taksit Sayısı Taksit tutarı Genel Toplam
Tek Çekim 102,70    102,70   
3 37,41    112,23   
6 19,75    118,51   
9 13,87    124,79   
12 10,92    131,06   
World Kartlar
Taksit Sayısı Taksit tutarı Genel Toplam
Tek Çekim 102,70    102,70   
3 37,41    112,23   
6 19,75    118,51   
9 13,87    124,79   
12 10,92    131,06   
Diğer Kartlar
Taksit Sayısı Taksit tutarı Genel Toplam
Tek Çekim 102,70    102,70   
3 -    -   
6 -    -   
9 -    -   
12 -    -   

Financial performance analysis is critical to users such as managers, business employees, the government, lenders, investors, and others. It is crucial for making forecasts for the future, evaluating a business’s position within the industry, and determining its standing relative to competitors. Therefore, this study analyzed thirty-seven companies listed on the ISO 500 2022 list in the Marmara Region and traded on BIST using seventeen evaluation criteria. Firstly, the financial data of the firms were collected. Due to the presence of negative values in the collected data, the Z-Score Standardization Method was used. Subsequently, the weights of the criteria were determined using the ENTROPY Method. Three different Fuzzy TOPSIS variations were utilized to evaluate the company alternatives. These variations were Triangular Fuzzy TOPSIS, Trapezoidal Fuzzy TOPSIS, and Intuitionistic Fuzzy TOPSIS Methods. The evaluation results obtained from each TOPSIS variation were integrated using the Borda Count Method to derive a single ranking. Among the evaluation criteria, the Inventory Turnover Ratio (C1) was the most important, with a weight of 0.36, followed by the Book Value Per Share Ratio (C15), with a weight of 0.12, and the Current Ratio (C1), with a weight of 0.09. Conversely, the Operating Cash Flow Ratio (C4), Return on Equity Ratio (C14), and Price-Earnings Ratio (C17) were the least critical criteria, each with a weight of 0.00. As a result, the best company alternatives were AYGAZ, FROTO, TOASO, BOBET, and BANVT, while the worst company alternatives were DGNMO, DEVA, VESTL, TATGD, and HEKTS. These findings provided valuable insights for stakeholders, enabling them to make more informed investment and strategic planning decisions.

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