Identyfikatory
Warianty tytułu
Zrozumienie lojalności konsumenta przy wykorzystaniu sieci neuronowych
Języki publikacji
Abstrakty
Instant coffee products are very popular for consumers, at both urban and rural levels. Consumer loyalties respond to various attributes of instant coffee products, grouped by internal and external factors. The study using Artificial Neural Network (ANN) model. The proposed method provides a direct mapping from configuration loyalty attributes to consumer behavior. The algorithm used in training set is Scaled Conjugate Gradient (SCG) with random data division and the performance is calculated using MSE. The result revealed that internal factors were effective predictors of a lower preference in consumer loyalties whereas external factors were more effective in predicting a higher preference in consumer loyalties. This research represents a first attempt to use neural networking to model the relationship between consumer-producer attributes and consumer loyalties.
Produkty kawy rozpuszczalnej są bardzo popularne wśród konsumentów, zarówno w obszarach miejskich, jak i wiejskich. Lojalność konsumentów reaguje na różne cechy wymienionych produktów kawowych, można je pogrupować według czynników wewnętrznych i zewnętrznych. Badanie przeprowadzono z wykorzystaniem modelu sztucznej sieci neuronowej (ANN). Proponowana metoda zapewnia bezpośrednie odwzorowanie atrybutów lojalnościowych i konfiguracji zachowań konsumenckich. Algorytmem używanym w badaniu jest Scaled Conjugate Gradient (SCG) z losowym podziałem danych, a wydajność obliczana jest za pomocą MSE. Rezultaty wskazują, że czynniki wewnętrzne były skutecznymi predyktorami niższej preferencji w lojalności konsumentów, podczas gdy czynniki zewnętrzne były bardziej skuteczne w przewidywaniu wyższych preferencji w lojalności konsumentów. Badania te stanowią pierwszą próbę wykorzystania sieci neuronowych do modelowania relacji między cechami producent-konsument a lojalnością konsumenta.
Czasopismo
Rocznik
Tom
Strony
51--61
Opis fizyczny
Bibliogr. 32 poz., rys., tab.
Twórcy
autor
- Department of Agribusiness, Universitas Padjadjaran
autor
- Department of Economics, Universitas Padjadjaran
Bibliografia
- 1. Bedia L.M., 2014, Predicting Consumer Behavior with Artificial Neural Networks. Oricedia, “Economics and Finance”, 15.
- 2. Bodie R.J., Whittome J.R., Brush G.J., 2009, Investigating the service brand : A Customer value perspective, “Journal of Business Research”, 62(3).
- 3. Chen H.Ch., 2008, Brand equity, marketing strategi, and consumer income : A hypermarket study, “Journal of Management and Marketing Research”, 1.
- 4. Chinomona R., Mahlangu D., Pooe D., 2013, Brand Service Quality, Satisfaction, Trust, and Preference as Predictors of Consumer Brand Loyalty in the Retailing Industry, “Mediterranean Journal of Social Science”, 4(14).
- 5. Deliana Y., Rum I.A., 2017, Application artificial neural network for green consumer behavior, Paper presented at International Seminar on Mathematics, Science and Computer Science Education (MSCEIS), October 14, 2017 - Bandung, Indonesia, Third Annual Conference.
- 6. Forgacs G., 2006, Brand assset and balancing act in the hotel industry, “Hospitality Industry Trends”, 5(8).
- 7. Greve G., 2014, The Moderating Effect of Customer Engagement on The Brand Image - Brand Loyalty Relationship, “Procedia - Social and Behavior Sciences”, 148.
- 8. Heskett J., 2002, Beyond customer loyalty, “Managing Service Quality”, 12(6).
- 9. Kemal Ç., Erkan O., Muhsin D.E., Ömer Ö., 2015, Factors influencing consumers’ light commercial vehicle purchase intention in a developing country, “Management & Marketing”, 10(2).
- 10. Khalifa D., Paurav S., 2017, Me, my brand and I : Consumer response to luxury brand rejection, “Journal of Business Research”, 81.
- 11. Khaniwale M., 2015, Consumer buying behaviour, “International Journal of innovation and scientific research”, 14(2).
- 12. Kotler P., Keller K.L., 2009, Marketing Management, Upper Saddle River, New Jersey, USA, Pearson Prentice Hall.
- 13. Kuusik A., 2007, “Affecting customer loyalty do different factors have various influences in different loyalty level?”, Tarto University, Estonia, Europe : Tartu University Press.
- 14. Lindstrom M., 2011, Buy.Ology, 1st Edition, Istambul : Optimist Press, 32.
- 15. McMullan R., Gilmore A., 2008, Customer loyalty : An empirical study, “European Journal of Marketing”, 42(9/10).
- 16. Mellen M., DeKimpe M.G., Steenkampt J.R., 1996, A review of brand loyalty measures in marketing, “Tijdschift voor Econoniie en Management”, XLI(4).
- 17. Mokrysz S., 2016, Consumer preferences and behaviour on the coffee market in Poland, “Forum Scientiae Oeconomia”, 4.
- 18. Nam J., Yuksel E., Whyatt G., 2011, Brand equity and consumer satisfaction, “Annual of Tourism Research”, 38(3).
- 19. Needham C., 2005, Brand leaders: Clinton, Blair and the limitations of the permanent campaign, “Political Studies”, 53(2).
- 20. O’Neil J.W., Xiao W., 2006, The role of brand affiliation in hotel market value, “Cornell Hotel and Restaurant Administration Quarterly”, 47.
- 21. Raghav A., 2013, Internal and external element affecting willingness of consumers to purchase products, “International Journal of Advancements in Research and Technology”, 2.
- 22. Ramya N., Ali M., 2016, Factors affecting consumer buying behavior, “International Journal of Applied Research”, 2(10).
- 23. Reinartz W., Kumar V., 2000, On the profitability of long-life customers in a non-contractual setting : an empirical phase and implications for marketing, “Journal of Marketing”, 64(4).
- 24. Sahin A., Zehir C., Kitapci H., 2011, The effect of Brand Experiences, Trust and Satisfaction on Building Brand Loyalty; An Emperical Research on Global Brands, “Procedia - Social and Behavior Sciences”, 24.
- 25. Schleenbecker R., Hamm U., 2015, Information needs for a purchase of fairtrade coffee, “Sustainability - Switzerland”, 7(5).
- 26. Silva da I.N., Hernane Spatti D., Andrade Flauzino R., Liboni L.H.B., dos Reis Alves S.F., 2017, Artificial Neural Network. A Practice Cource, XX(307).
- 27. Sosilo W.H., 2016, An Impact of Behavior Segmentation to Increase Consumer Loyalty: Empirical Study in Higher Education of Postgraduate Institutions at Jakarta, “Procedia - Social and Behavior Sciences”, 229.
- 28. Stencl M., Popelka O., Stastny J., 2011, Forecast of Consumer Behavior Based on Neural Network Model Comparison, “ACTA Universitatis Agriculturae et Cilviculturae Mendelianae Brunensis”, LX(2).
- 29. White J., Chernatony L.De., 2002, New labour : A study of the creation, development and demise of a political brand, “Journal of Political Marketing”, 1(2/3).
- 30. Yazdanifard R., Lim P.L., 2015, What internal and external factors influence impulsive buying behaviour in online shopping?, “Global Journal of Management and Business Research : E-Marketing”, 15(1).
- 31. Zang Yi., 2015, The impact of brand image on consumer behaviour : A Literature Review, “Journal of Business and Management”, 3.
- 32. Zheng B., Thompson K., Larn S.S., Yoon S.W., 2013, Consumers’ Behavior Prediction Using Artificial Neural Network, Proceeding of the 2013 Industrial and Systems Engineering Research Conference.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4ce5f74c-21ba-4e29-87e2-7ffc6724ccc8
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