MÜŞTERİ MEMNUNİYETİ TAHMİNİNDE YAPAY SİNİR AĞLARI, LOJİSTİK REGRESYON VE AYIRMA ANALİZİNİN PERFORMANSLARININ KARŞILAŞTIRILMASI

Yrd.doç.dr.nezih Tayyar

Müşteri Memnuniyeti Tahmininde Yapay Sinir Ağları, Lojistik Regresyon ve Ayırma Analizinin Performanslarının Karşılaştırılması

Yıl 2010, Cilt: 15 Sayı: 1, 339 - 355, 01.03.2010

Yrd.doç.dr.nezih Tayyar

Öz

Anahtar Kelimeler

Kaynakça

1. Ainscough, T.L. & Aronson, J.E. (1999), “An empirical investigation and comparison of neural networks and regression for scanner data analysis”, Journal of Retailing and Consumer Services, 6(4), 205 – 217.
2. Akpınar, H. (1993), “Yapay Sinir Ağları ve Kredi Taleplerinin Değerlendirilmesinde Bir Uygulama Önerisi”, İstanbul Üniversitesi İşletme Fakültesi Sayısal Yöntemler Ana Bilim Dalı, İstanbul, 1993.
3. Anton, J. (1996), Customer Relationship Management. Making Hard Decisions with Soft Numbers, Upper Saddle River, NJ: Prentice Hall.
4. Audrain, A.F. (2002), “The attribute–satisfaction link over time: a study on panel data”, proceedings of the 31st EMAC Conference, 28–31 May 2002, University of Minho and European Marketing Academy (EMAC), Braga, Portugal.
5. Auh, S. & Johnson, M.D. (1997), “The complex relationship between customer satisfaction and loyalty for automobiles”, In: M.D. Johnson, A. Hermann, F. Huber & A. Gustafsson (eds), Customer Retention in the Automotive Industry: Quality, Satisfaction, and Loyalty. Wiesbaden, Germany: Gabler, pp. 117 – 139.
6. Bowen, J.T. & Chen, S.L. (2001), “The Relationship Between Customer Loyalty and Customer Satisfaction”, International Journal of Contemporary Hospitality Management, 13(5), 213 – 217.
7. Chiang, W.K., Zhang, D. & Zhou, L. (2006), “Predicting and explaining patronage behavior toward web and traditional stores using neural networks: A comparative analysis with logistic regression”, Decision Support Systems, 41, 514 – 531.
8. Churchill, G.A. & Surprenant, C. (1982), “An Investigation Into The Determinants of Customer Satisfaction”, Journal of Marketing Research, 19(11), 491 – 504.
9. Cronin, J.J. Jr. & Taylor, S.A. (1992), “Measuring service quality: a reexamination and extension”, Journal of Marketing, 56(3), 55 - 68.
10. Çolak, C., Çolak M.C. ve Atıcı, M.A. (2005), “Ateroskleroz’un tahmini için bir yapay sinir ağı”, Ankara Üniversitesi Tıp Fakültesi Mecmuası, 58, 159 - 162.
11. Çörek, E.T. (2003), “Müşteri memnuniyetinde İstatistiksel Yöntemler ve Bir Uygulama”, Yayımlanmamış Yüksek Lisans Tezi, Marmara Üniversitesi Sosyal Bilimler Enstitüsü Ekonometri Anabilim Dalı: İstanbul.
12. Dasgupta, C.G., Dispensa, G.S. & Ghose, S. (1994), “Comparing the predictive performance of a neural network model with some traditional market response models”, International Journal of Forecasting, 10, 235 – 244.
13. Duman, T. (2003), “Richard L. Oliver’ın Tüketici Memnuniyeti (Consumer Satisfaction) ve Tüketici Değer Algısı (Consumer Value) Kavramları Hakkındaki Görüşleri: Teorik Bir Karşılaştırma”, Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 5(2), 45 - 56.
14. Dutta, S., Shekhar, S., & Wong, W.Y. (1994), “Decision support in nonconservative domains: Generalization with neural Networks”, Decision Support Systems, 11, 527 – 544.
15. Fadlalla, A. & Lin, C.H. (2001), “An analysis of the applications of neural Networks in finance”, Interfaces, 31(4), 112 – 122.
16. Fausett, L. (1994), Fundamentals of neural Networks, Upper Saddle River, NJ: Prentice-Hall.
17. Fish, K.E., Barnes, J.H. & Aiken, M.W. (1995), “Artificial neural networks: a new methodology for industrial market segmentation”, Industrial Marketing Management, 24(5), 431 – 439.
18. Fornell, C. (1992), “A national customer satisfaction barometer: the Swedish experience”, Journal of Marketing, 56(1), 6 - 21.
19. Gan, C., Limsombunchai, V., Clemes, M. & Weng, A. (2005), “Consumer choice prediction: Artificial neural networks versus logistic models”, Journal of Social Sciences, 1(4), 211 – 219.
20. Gorr, W.L. (1994), “Research prospective on neural network forecasting”, International Journal of Forecasting, 10, 1 – 4.
21. Grønholdt, L. & Martensen, A. (2005), “Analyzing customer satisfaction data: a comparison of regression and artificial neural Networks”, International Journal of Market Research, 47(2), 121 – 130.
22. Hallowell, R. (1996), “The Relationships of Customer Satisfaction, Customer Loyalty and Profitability: An Empirical Study”, International Journal of Service Industry Management, 7(4), 27 - 42.
23. Hassoum, M.H. (1995), Fundamentals of artificial neural networks, Cambridge, MA: The MIT Press.
24. Hill, T. & Remus, W. (1994), “Neural network approach for intelligent support of managerial decision making”, Decision Support Systems, 11, 449 – 459.
25. Hruschka, H. (1993), “Determining market response functions by neural network modelling: A comparison to econometric techniques”, European Journal of Operational Research, 66, 27 – 35.
26. Hu, M.Y., Shanker, M. & Hung, M.S. (1999), “Estimation of posterior probabilities of consumer situational choices with neural network classifiers”, International Journal of Research in Marketing, 16(4), 307 – 317.
27. Jones, T.O. & Sasser, W.E. Jr (1995), “Why satisfied customers defect”, Harvard Business Review, 73(6), 88 – 99.
28. Johnson, M.D. & Gustafsson, A. (2000), Improving Customer Satisfaction, Loyalty, and Profit, University of Michigan Business School Management Series, San Francisco, CA: Jossey-Bass.
29. Lee, W.I., Shih, B.Y. & Chung, Y.S. (2008), “The exploration of consumers’ behavior in choosing hospital by the application of neural Networks”, Expert Systems with Applications, 34, 806 – 816.
30. Liao, N.N.H.& Chiang, A.C.Y. (2005), “Management Model To Create Customer Satisfaction: An Empirical Research On Suppliers’ Perspectives”, The Journal of American Academy of Business, 6(2), 159 – 165.
31. Löthgren, M. & Tambour, M. (1996), “Productivity and Customer Satisfaction –A DEA Network Model”, Stockholm School Of Economics, Working Paper Series in Economics and Finance, No. 140, December.
32. Nelson, M.M. & Illingworth, W.T. (1994), Practical guide to neural nets, USA: Addison Wesley Publishing Company.
33. Nguyen, N. & Cripps, A. (2001), “Predicting housing value: a comparison of multiple regression analysis and artificial neural Networks”, Journal of Real Estate Research, 22(3), 313 – 336.
34. Oliver, R.L. (1997), Satisfaction: A behavioral perspective on the consumer, Boston: McGraw-Hill.
35. Özdamar, K. (2004), Paket Programlar ile İstatistiksel Veri Analizi, 5. Baskı, Kaan Kitabevi, Eskişehir.
36. Öztemel, E. (2006), Yapay Sinir Ağları, 2. Baskı, Papatya Yayıncılık, İstanbul.
37. Piercy, N.F. & Morgan, N.A. (1995), “Customer satisfaction measurement: A processual analysis”, Journal of Marketing Management, 11(8), 817 – 834.
38. Paliwal M. & Kumar U.A. (2009), “Neural networks and statistical techniques: A review of applications”, Expert Systems with Applications, 36, 2 – 17.
39. Patterson, P.G. & Spreng, R.A. (1997), “Modelling the relationship between perceived value, satisfaction and repurchase intentions in a business-to-business, services context: an empirical examination”, International Journal of Service Industry Management, 8(5), 414 - 434.
40. Reichheld, F. (1996), The Loyalty Effect: The Hidden Force Behind Growth, Profits, and Lasting Value, Boston: Harvard Business School Press.
41. Rumelhart, D.E. & McClelland, J.L. (1986), Parallel distributed processing (vol. 1), Cambridge, MA: The MIT Press.
42. Söderlund, M. (1998), “Customer Satisfaction and Its Consequences on Customer Behaviour Revisited”, International Journal of Service Industry Management, 9(2), 169 - 188.
43. Spangler, W.E., May, J.H. & Vargas, L.G. (1999), “Choosing datamining methods for multiple classification: representational and performance measurement implications for decision support”, Journal of Management Information Systems, 16(1), 37 – 62.
44. Tayyar, N. ve Bektaş, Ç. (2008), “SSK Hastaneleri’nin Sağlık Bakanlığına Devrinin Hizmet Kalitesine Etkileri”, Finans Politik & Ekonomik Yorumlar, 45(524), 73 - 87.
45. Thieme, R.J., Song, M. & Calantone, R.J. (2000), “Artificial neural network decision support systems for new product development project selection”, Journal of Marketing Research, 37(4), 499 – 507.
46. Tolon, M. (2007), “Tüketici tatmininin yapay sinir ağları yöntemiyle ölçülmesi ve Ankara`daki perakendeci mağazaların müşterileri üzerinde bir uygulama”, Yayımlanmamış Doktora Tezi, Gazi Üniversitesi Sosyal Bilimler Enstitüsü İşletme Anabilim Dalı: Ankara
47. Uysal, M. & Roubi, S.E. (1999), “Artificial neural networks versus multiple regression in tourism demand analysis”, Journal of Travel Research, 38, November, 111 – 118.
48. Vavra, T.G. (1997), Improving Your Measurement of Customer Satisfaction: A Guide to Creating, Conducting, Analyzing and Reporting Customer Satisfaction Measurement Program, Milwaukee, Wis.: ASQ Quality Press.
49. Ville, B. (1996), “Predictive models in market research”, Marketing Research, 8(2), 43 – 45.
50. West, P.M., Brockett, P.L. & Golden, L. L. (1997), “A comparative analysis of neural networks and statistical methods for predicting consumer choice”, Marketing Science, 16(4), 370 – 391.
51. Wiele, T.V.D.,Boselie, P. & Hesselink, M. (2001), “Empirical evidence for the relation between customer satisfaction and business performance”, Erasmus Research Institute of Management, ERIM Report Series Reference No: ERS-2001-32-ORG, May.
52. Willson, E. & Wragg, T. (2001), “We cannot diagnose the patient’s illness … but experience tells us what treatment Works” International Journal of Market Research, 43(2), 189 – 215.
53. Wray, B., Palmer, A. & Bejou, D. (1994), “Using neural network analysis to evaluate buyer–seller relationships”, European Journal of Marketing, 28(10), 32 – 48.
54. Yao X. (1999), “Evolving Artificial Neural Networks”, Proceedings of the IEEE, 87, 1423 - 1444.
55. Yeung, M.C.H., Ging, L.C. & Ennew, C.T. (2002), “Customer satisfaction and profitability: A reappraisal of the nature of the relationship”, Journal of Targeting, Measurement and Analysis for Marketing, 11(1), 24 – 33.
56. Zahavi, J. & Levin, N. (1997), “Applying neural computing to target marketing”, Journal of Direct Marketing, 11(1), 5 – 24.
57. Zhang, G., Hu, M., Patuwo, B.E. & Indro, D.C. (1999), “Artificial neural networks in bankruptcy prediction: general framework and crossvalidation analysis”, European Journal of Operational Research, 116(1), 16 – 32.

MÜŞTERİ MEMNUNİYETİ TAHMİNİNDE YAPAY SİNİR AĞLARI, LOJİSTİK REGRESYON VE AYIRMA ANALİZİNİN PERFORMANSLARININ KARŞILAŞTIRILMASI

Yıl 2010, Cilt: 15 Sayı: 1, 339 - 355, 01.03.2010

Yrd.doç.dr.nezih Tayyar

Öz

Bu çalışmada Müşteri Memnuniyetinin tahmini için Yapay Sinir Ağları, Lojistik Regresyon ve Ayırma Analizinin performansları karşılaştırılmıştır. Veriler Uşak’taki kamu hastanelerinde 2007 yılında yapılan hasta memnuniyetini ölçmeyi amaçlayan bir anket uygulanarak elde edilmiştir ve 364 hastayı kapsamaktadır. Sonuçlar Yapay Sinir Ağlarının diğer yöntemlere göre müşteri memnuniyetini daha iyi tahmin ettiğini göstermiştir

Anahtar Kelimeler

Müşteri Memnuniyeti, Yapay Sinir Ağları, Lojistik Regresyon, Ayırma Analizi

Kaynakça

1. Ainscough, T.L. & Aronson, J.E. (1999), “An empirical investigation and comparison of neural networks and regression for scanner data analysis”, Journal of Retailing and Consumer Services, 6(4), 205 – 217.
2. Akpınar, H. (1993), “Yapay Sinir Ağları ve Kredi Taleplerinin Değerlendirilmesinde Bir Uygulama Önerisi”, İstanbul Üniversitesi İşletme Fakültesi Sayısal Yöntemler Ana Bilim Dalı, İstanbul, 1993.
3. Anton, J. (1996), Customer Relationship Management. Making Hard Decisions with Soft Numbers, Upper Saddle River, NJ: Prentice Hall.
4. Audrain, A.F. (2002), “The attribute–satisfaction link over time: a study on panel data”, proceedings of the 31st EMAC Conference, 28–31 May 2002, University of Minho and European Marketing Academy (EMAC), Braga, Portugal.
5. Auh, S. & Johnson, M.D. (1997), “The complex relationship between customer satisfaction and loyalty for automobiles”, In: M.D. Johnson, A. Hermann, F. Huber & A. Gustafsson (eds), Customer Retention in the Automotive Industry: Quality, Satisfaction, and Loyalty. Wiesbaden, Germany: Gabler, pp. 117 – 139.
6. Bowen, J.T. & Chen, S.L. (2001), “The Relationship Between Customer Loyalty and Customer Satisfaction”, International Journal of Contemporary Hospitality Management, 13(5), 213 – 217.
7. Chiang, W.K., Zhang, D. & Zhou, L. (2006), “Predicting and explaining patronage behavior toward web and traditional stores using neural networks: A comparative analysis with logistic regression”, Decision Support Systems, 41, 514 – 531.
8. Churchill, G.A. & Surprenant, C. (1982), “An Investigation Into The Determinants of Customer Satisfaction”, Journal of Marketing Research, 19(11), 491 – 504.
9. Cronin, J.J. Jr. & Taylor, S.A. (1992), “Measuring service quality: a reexamination and extension”, Journal of Marketing, 56(3), 55 - 68.
10. Çolak, C., Çolak M.C. ve Atıcı, M.A. (2005), “Ateroskleroz’un tahmini için bir yapay sinir ağı”, Ankara Üniversitesi Tıp Fakültesi Mecmuası, 58, 159 - 162.
11. Çörek, E.T. (2003), “Müşteri memnuniyetinde İstatistiksel Yöntemler ve Bir Uygulama”, Yayımlanmamış Yüksek Lisans Tezi, Marmara Üniversitesi Sosyal Bilimler Enstitüsü Ekonometri Anabilim Dalı: İstanbul.
12. Dasgupta, C.G., Dispensa, G.S. & Ghose, S. (1994), “Comparing the predictive performance of a neural network model with some traditional market response models”, International Journal of Forecasting, 10, 235 – 244.
13. Duman, T. (2003), “Richard L. Oliver’ın Tüketici Memnuniyeti (Consumer Satisfaction) ve Tüketici Değer Algısı (Consumer Value) Kavramları Hakkındaki Görüşleri: Teorik Bir Karşılaştırma”, Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 5(2), 45 - 56.
14. Dutta, S., Shekhar, S., & Wong, W.Y. (1994), “Decision support in nonconservative domains: Generalization with neural Networks”, Decision Support Systems, 11, 527 – 544.
15. Fadlalla, A. & Lin, C.H. (2001), “An analysis of the applications of neural Networks in finance”, Interfaces, 31(4), 112 – 122.
16. Fausett, L. (1994), Fundamentals of neural Networks, Upper Saddle River, NJ: Prentice-Hall.
17. Fish, K.E., Barnes, J.H. & Aiken, M.W. (1995), “Artificial neural networks: a new methodology for industrial market segmentation”, Industrial Marketing Management, 24(5), 431 – 439.
18. Fornell, C. (1992), “A national customer satisfaction barometer: the Swedish experience”, Journal of Marketing, 56(1), 6 - 21.
19. Gan, C., Limsombunchai, V., Clemes, M. & Weng, A. (2005), “Consumer choice prediction: Artificial neural networks versus logistic models”, Journal of Social Sciences, 1(4), 211 – 219.
20. Gorr, W.L. (1994), “Research prospective on neural network forecasting”, International Journal of Forecasting, 10, 1 – 4.
21. Grønholdt, L. & Martensen, A. (2005), “Analyzing customer satisfaction data: a comparison of regression and artificial neural Networks”, International Journal of Market Research, 47(2), 121 – 130.
22. Hallowell, R. (1996), “The Relationships of Customer Satisfaction, Customer Loyalty and Profitability: An Empirical Study”, International Journal of Service Industry Management, 7(4), 27 - 42.
23. Hassoum, M.H. (1995), Fundamentals of artificial neural networks, Cambridge, MA: The MIT Press.
24. Hill, T. & Remus, W. (1994), “Neural network approach for intelligent support of managerial decision making”, Decision Support Systems, 11, 449 – 459.
25. Hruschka, H. (1993), “Determining market response functions by neural network modelling: A comparison to econometric techniques”, European Journal of Operational Research, 66, 27 – 35.
26. Hu, M.Y., Shanker, M. & Hung, M.S. (1999), “Estimation of posterior probabilities of consumer situational choices with neural network classifiers”, International Journal of Research in Marketing, 16(4), 307 – 317.
27. Jones, T.O. & Sasser, W.E. Jr (1995), “Why satisfied customers defect”, Harvard Business Review, 73(6), 88 – 99.
28. Johnson, M.D. & Gustafsson, A. (2000), Improving Customer Satisfaction, Loyalty, and Profit, University of Michigan Business School Management Series, San Francisco, CA: Jossey-Bass.
29. Lee, W.I., Shih, B.Y. & Chung, Y.S. (2008), “The exploration of consumers’ behavior in choosing hospital by the application of neural Networks”, Expert Systems with Applications, 34, 806 – 816.
30. Liao, N.N.H.& Chiang, A.C.Y. (2005), “Management Model To Create Customer Satisfaction: An Empirical Research On Suppliers’ Perspectives”, The Journal of American Academy of Business, 6(2), 159 – 165.
31. Löthgren, M. & Tambour, M. (1996), “Productivity and Customer Satisfaction –A DEA Network Model”, Stockholm School Of Economics, Working Paper Series in Economics and Finance, No. 140, December.
32. Nelson, M.M. & Illingworth, W.T. (1994), Practical guide to neural nets, USA: Addison Wesley Publishing Company.
33. Nguyen, N. & Cripps, A. (2001), “Predicting housing value: a comparison of multiple regression analysis and artificial neural Networks”, Journal of Real Estate Research, 22(3), 313 – 336.
34. Oliver, R.L. (1997), Satisfaction: A behavioral perspective on the consumer, Boston: McGraw-Hill.
35. Özdamar, K. (2004), Paket Programlar ile İstatistiksel Veri Analizi, 5. Baskı, Kaan Kitabevi, Eskişehir.
36. Öztemel, E. (2006), Yapay Sinir Ağları, 2. Baskı, Papatya Yayıncılık, İstanbul.
37. Piercy, N.F. & Morgan, N.A. (1995), “Customer satisfaction measurement: A processual analysis”, Journal of Marketing Management, 11(8), 817 – 834.
38. Paliwal M. & Kumar U.A. (2009), “Neural networks and statistical techniques: A review of applications”, Expert Systems with Applications, 36, 2 – 17.
39. Patterson, P.G. & Spreng, R.A. (1997), “Modelling the relationship between perceived value, satisfaction and repurchase intentions in a business-to-business, services context: an empirical examination”, International Journal of Service Industry Management, 8(5), 414 - 434.
40. Reichheld, F. (1996), The Loyalty Effect: The Hidden Force Behind Growth, Profits, and Lasting Value, Boston: Harvard Business School Press.
41. Rumelhart, D.E. & McClelland, J.L. (1986), Parallel distributed processing (vol. 1), Cambridge, MA: The MIT Press.
42. Söderlund, M. (1998), “Customer Satisfaction and Its Consequences on Customer Behaviour Revisited”, International Journal of Service Industry Management, 9(2), 169 - 188.
43. Spangler, W.E., May, J.H. & Vargas, L.G. (1999), “Choosing datamining methods for multiple classification: representational and performance measurement implications for decision support”, Journal of Management Information Systems, 16(1), 37 – 62.
44. Tayyar, N. ve Bektaş, Ç. (2008), “SSK Hastaneleri’nin Sağlık Bakanlığına Devrinin Hizmet Kalitesine Etkileri”, Finans Politik & Ekonomik Yorumlar, 45(524), 73 - 87.
45. Thieme, R.J., Song, M. & Calantone, R.J. (2000), “Artificial neural network decision support systems for new product development project selection”, Journal of Marketing Research, 37(4), 499 – 507.
46. Tolon, M. (2007), “Tüketici tatmininin yapay sinir ağları yöntemiyle ölçülmesi ve Ankara`daki perakendeci mağazaların müşterileri üzerinde bir uygulama”, Yayımlanmamış Doktora Tezi, Gazi Üniversitesi Sosyal Bilimler Enstitüsü İşletme Anabilim Dalı: Ankara
47. Uysal, M. & Roubi, S.E. (1999), “Artificial neural networks versus multiple regression in tourism demand analysis”, Journal of Travel Research, 38, November, 111 – 118.
48. Vavra, T.G. (1997), Improving Your Measurement of Customer Satisfaction: A Guide to Creating, Conducting, Analyzing and Reporting Customer Satisfaction Measurement Program, Milwaukee, Wis.: ASQ Quality Press.
49. Ville, B. (1996), “Predictive models in market research”, Marketing Research, 8(2), 43 – 45.
50. West, P.M., Brockett, P.L. & Golden, L. L. (1997), “A comparative analysis of neural networks and statistical methods for predicting consumer choice”, Marketing Science, 16(4), 370 – 391.
51. Wiele, T.V.D.,Boselie, P. & Hesselink, M. (2001), “Empirical evidence for the relation between customer satisfaction and business performance”, Erasmus Research Institute of Management, ERIM Report Series Reference No: ERS-2001-32-ORG, May.
52. Willson, E. & Wragg, T. (2001), “We cannot diagnose the patient’s illness … but experience tells us what treatment Works” International Journal of Market Research, 43(2), 189 – 215.
53. Wray, B., Palmer, A. & Bejou, D. (1994), “Using neural network analysis to evaluate buyer–seller relationships”, European Journal of Marketing, 28(10), 32 – 48.
54. Yao X. (1999), “Evolving Artificial Neural Networks”, Proceedings of the IEEE, 87, 1423 - 1444.
55. Yeung, M.C.H., Ging, L.C. & Ennew, C.T. (2002), “Customer satisfaction and profitability: A reappraisal of the nature of the relationship”, Journal of Targeting, Measurement and Analysis for Marketing, 11(1), 24 – 33.
56. Zahavi, J. & Levin, N. (1997), “Applying neural computing to target marketing”, Journal of Direct Marketing, 11(1), 5 – 24.
57. Zhang, G., Hu, M., Patuwo, B.E. & Indro, D.C. (1999), “Artificial neural networks in bankruptcy prediction: general framework and crossvalidation analysis”, European Journal of Operational Research, 116(1), 16 – 32.

Toplam 57 adet kaynakça vardır.

Ayrıntılar

Birincil Dil	Türkçe
Bölüm	Makaleler
Yazarlar	Yrd.doç.dr.nezih Tayyar Bu kişi benim
Yayımlanma Tarihi	1 Mart 2010
Yayımlandığı Sayı	Yıl 2010 Cilt: 15 Sayı: 1

Kaynak Göster

APA	Tayyar, .Y. (2010). MÜŞTERİ MEMNUNİYETİ TAHMİNİNDE YAPAY SİNİR AĞLARI, LOJİSTİK REGRESYON VE AYIRMA ANALİZİNİN PERFORMANSLARININ KARŞILAŞTIRILMASI. Süleyman Demirel Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 15(1), 339-355.

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