MARKOV ZİNCİRLERİ MODELLEMESİ İLE GENÇLERİN SPOR AYAKKABI MARKA TERCİHLERİNİN BELİRLENMESİ

Yıl 2020, , 131 - 141, 30.04.2020

Özge Ercan

https://doi.org/10.33723/rs.692827

Cited By: 2

Öz

Stokastik süreçlerin bir çeşidi olan Markov zincirleri önceden tahmin edilemeyen süreçlerde uygulanır. Markov zincirleri matematiksel bir modeldir. Ancak sosyal bilimlerde de pek çok alanda kullanılabilmektedir. Bu çalışmada, genç tüketicilerin spor ayakkabı marka tercihleri belirlenmeye çalışılmıştır. Markov zincirleri analizi için Ankara ilinde yaşayan 14-19 yaş arası genç tüketiciler araştırmaya dahil edilmiştir. Katılımcıların, %47’si (N=102) erkek ve %53’ü (N= 115) kadın olmak üzere toplam 217 katılımcı olarak belirlenmiştir. Araştırma sonucunda, Spor ayakkabısı için marka bağlılığı “0,4483” ile en yüksek Nike markasındadır. Aynı markayı tercih olasılıkları Adidas için %36,11, Reebok için %18,18 Skechers için %33,33, Puma için %14,29, New Balance için %11,11 olarak hesaplanmıştır. Uzun dönemde gençlerin spor ayakkabısı tercihlerinin; %33,02’sinin Nike, %30,47’sinin diğer markalar, %23,32’sinin Adidas, %4,42’sinin Puma, %3,72’sinin New Balance, %1,87’sinin Converse, %1,49’unun Skechers, %0,9’unun Reebok ve %0,8’inin Asics marka spor ayakkabısı olması beklenmektedir.

Anahtar Kelimeler

Marka Bağlılığı, Marka Tercihi, Markov Zincirleri, Stokastik Süreçler

Determination of Sports Shoes Preferences of Young People with Markov Chains Modeling

Öz

Markov chains, a kind of stochastic processes, are applied in unpredictable processes. As a mathematical model, it can be used in many fields in social sciences. The purpose of this study is to determine the sports shoe brand preferences of young consumers via this model. For the analysis of Markov chains, young consumers between the ages of 14-19 living in Ankara have been included in the study. A total of 217 participants include 47% (N = 102) men and 53% (N = 115) women. As a result of the research, brand loyalty for sports shoes is the highest Nike brand with “0.4483”. The probabilities of choosing the same brand have been calculated as 36.11% for Adidas, 18.18% for Reebok, 33.33% for Skechers, 14.29% for Puma and 11.11% for New Balance. In the long term, the young people expectations of the preference for the sports shoes have been calculated via Markov chains model as 33,02% Nike, 30,47% other brands, 23,32% Adidas, 4,42% Puma, 3,72% New Balance, 1,87% Converse, 1.49% Skechers, 0.9% Reebok and 0.8% Asics sports shoes”. 

Anahtar Kelimeler

Brand Loyalty, Brand Preference, Markov Chains, Stochastic Processes

Kaynakça

• Akcay, O., Sable, P., & Dalgin, M. H. (2012). The importance of color in product choice among young Hispanic, Caucasian, and African-American groups in the USA. International Journal of Business and Social Science, 3(6).
• Bramel, S. (2005). Key Trends in Sportswear Design. In Textiles in Sport (pp. 25-43). Woodhead Publishing.
• Cox, D. R., & Miller, H. D. (1996). Stochastic processes. Chapman and Hall, London.
• Dawes, J. (2009). Brand Loyalty in The UK Sportswear Market. International Journal of Market Research, 51(4).
• Durmaz, Y., & Yildiz, B. (2016). The Impacts Of Social Environment And Individual Factors Of Young Adult Consumers On Brand Loyalty.
• Govan, J.B., & Woodman, H.B. (2008). Sneakers and Street Culture: A Postcolonial Analysis of Marginalized Cultural Consumption. Consumption, Markets and Culture, 11(2), 93-112.
• Hillier, S.Frederick, Gerald J. Lieberman (2001), Introduction to Operations Research, 7th. Edition. McGraw-Hill, New York.
• Ko, E., Taylor, C. R., Sung, H., Lee, J., Wagner, U., Navarro, D. M. C., & Wang, F. (2012). Global marketing segmentation usefulness in the Sportswear Industry. Journal of Business Research, 65(11), 1565-1575.
• Lebrun, A. M., Souchet, L., & Bouchet, P. (2013). Social Representations and Brand Positioning in The Sporting Goods Market. European Sport Management Quarterly, 13(3), 358-379.
• Lopez, A. ve Rodriguez, R. (2018), "Çocuklar ve markaları: genç tüketicilerin markalarla ilişkisi", Journal of Consumer Marketing , 35 (2), 130-142.
• Sericola,B., (2013). Markov Chains- Theory, Algorithms and Applications, John Wiley &Sons Inc.
• Su, J., & Tong, X. (2015). Brand Personality and Brand Equity: Evidence From The Sportswear Industry. Journal of Product & Brand Management, 24(2), 124-133.
• Puterman, M. L. (2014). Markov Decision Processes.: Discrete Stochastic Dynamic Programming. John Wiley & Sons Inc.
• Pfeifer, P. E., & Carraway, R. L. (2000). Modeling customer relationships as Markov chains. Journal of interactive marketing, 14(2), 43-55.
• Rhee, J. and Johnson, K. (2012), "Investigating relationships between adolescents' liking for an apparel brand and brand self congruency", Young Consumers, Vol. 13 No. 1, pp. 74-85.
• Ross, Sheldon M. (2000), Introduction to Probability Models, Seventh Edition, Academic Press, United States of America.
• Rubini, A. (2010). Role of Brand in Consumer Behavior: Case How Sneakers Have Turned into Status Symbols.
• Taha, H. A. (2000). Yöneylem Araştırması, (Çeviri: ŞA Baray ve Ş. Esnaf) Literatür Yayıncılık.
• Timor, Mehpare (2001), Yöneylem Araştırması ve İşletmecilik Uygulamaları, İstanbul Üniversitesi Basımevi Müdürlüğü, İşletme Fakültesi Yayın No:280, İstanbul.
• Tong, X., & Hawley, J. M. (2009). Measuring Customer-Based Brand Equity: Empirical Evidence From The Sportswear Market in China. Journal of Product & Brand Management, 18(4), 262-271.
• Winston, W. L., & Goldberg, J. B. (2004). Operations Research: Applications and Algorithms. Belmonte Calif Calif: Thomson/Brooks/Cole.