GENÇ İNSANLARIN PERSPEKTİFİNDEN ONLİNE ALIŞVERİŞ SİTELERİ SEÇİMİNDEKİ KRİTER AĞIRLIKLARININ BELİRLENMESİ

Online alışveriş son iki asırdır çok hızlı büyümekte olup Covid-19 salgını yüzünden insanlar online alışverişi tercih etmektedir. Bu özellikle genç insanlar arasında çok popülerdir ve gençler alışveriş merkezlerine gitmek yerine online alışveriş yapma eğilimi içindedir çünkü alışveriş merkezlerinde yürümeyi sıkıcı bulmaktadırlar. Buna ilave olarak, alışveriş siteleri bir çok avantaj ve promosyon içermekte ve genç insanlar bu avantajlardan yararlanmak istemektedirler. Bu nedenle, online alışveriş siteleri için gençlerin kararlarını etkileyen kriterleri ve bunların ağırlıklarını bilmeleri pazarlama stratejilerine karar vermeleri açısından önem arz etmektedir. Bu çalışmada, literatür taranarak ve genç insanlarla görüşmeler yapılarak online alışveriş sitesi seçim kriterleri tanımlanmıştır. Toplamda 7 ana ve 23 alt kriter belirlenmiştir. İkinci adımda, bir anket hazırlanarak Ankara’da bulunan öğrencilere uygulanmıştır. Son aşamada, AHP metodu anketi değerlendirmek ve kriter ağırlıklarını bulmak için kullanılmıştır. 7 ana kriterin önem dereceleri şöyle bulunmuştur: Web sitesi kalitesi (%5,47), Ödeme Yöntemleri (%8,67), Ürün Çeşitliliği (%16,15), Ürün gönderimi ve Garanti (%31,4), Aile ve Arkadaş Etkisi (%8,26), Geçmiş Deneyim (%26,56), ve Reklamlar (%3,49). Ayrıca 23 alt kriterin ağırlıkları da bulunmuştur. Ana kriter ve alt kriter ağırlıkları öğrencilerin cinsiyet ve gelir seviyelerine göre analiz edilmiş ve karşılaştırılmıştır.

DETERMINING CRITERIA WEIGHTS AT ONLINE SHOPPING WEBSITE SELECTION FROM THE PERSPECTIVE OF YOUNG PEOPLE

Online shopping have been growing very rapidly especially for last two decades and due to Covid-19 virus people prefer shopping online. It is very popular especially among young people and they tend to shop online rather than going to the shopping malls since they find it boring to walk along shopping malls. In addition, websites have many advantages and promotions and young people would like to benefit from those advantages. Therefore, it is very important for the online shopping websites to know the criteria and their weights, which affect the decisions of young people in order to manage their marketing options. In this study, first, the criteria that affect the selection of online shopping websites are determined by searching the literature and interviewing with young people from different universities. A total of 7 main criteria and their 23 sub-criteria are defined. In the second step, a questionnaire is prepared and applied to the university students in Ankara. At the last step, AHP (analytic hierarchy process) methodology is used to evaluate the questionnaire and find the weights of the criteria. Seven main criteria are sorted with respect to their importance percentages as follows: Website Quality (5.47%), Payment Methods (8.67%) Product Variety (16.15%), Delivery and guarantee (31.4%), Family Friend Affect (8.26%), Past Experiences (26.56%) and Advertisements (3.49%). Weights of 23 sub-criteria are also found. Main criteria and sub-criteria weights are analyzed and compared according to gender and income level of the students.

___

  • Chen L, Nan G, Li M. (2018), “Wholesale Pricing or Agency Pricing on Online Retail Platforms: The Effects of Customer Loyalty”, International Journal of Electronic Commerce, 22(4), 576-608.
  • Cheng CMK, Lee M. (2005), “The asymmetric effect of web site attribute performance”. E-Service Journal, 3(3), 65-86.
  • Celsi M, Gilly M. (2001) “Shopping Online for Freedom, Control, and Fun,” California Management Review, 43(2), 34-55.
  • Ducoffe RH. (1996), “Advertising value and advertising on the web”. Journal of Advertising Research, 36(5), 21-35.
  • Gao Y. (2005), “Web systems design and online consumer behavior”. London: Idea Group Inc. (IGI), 6298-6304.
  • Garcı´a SIP. (2012), “When satisfied consumers do not return”, Psychology and marketing, 29(1), 15-24.
  • Hyejeong K, Linda SN. (2009), “The Impact of Website Quality on Information Quality”. Journal of Interactive Marketing, 23(3), 221–233.
  • Hsieh JY, Liao PW. (2011) “Antecedents and Moderators of Online Shopping”. Social Behavior and Personality, 39(9), 1271-1280.
  • Ilias O, Pappas G, Pateli MN. (2014), “Moderating effects of online shopping experience on customer satisfaction and repurchase intentions”. International Journal of Retail & Distribution Management, 42(3), 187-204.
  • Islam MS. (2015) “An Analysis of Factors Affecting on Online Shopping Behavior of Consumers”, European Journal of Business and Management, 7(1), 6-17.
  • Keeney R. (1999) “The value of Internet commerce to the customer”. Management Science, 45(4), 533–542.
  • Koufaris, M. (2002), “Applying the technology acceptance model and flow theory to online consumer”. Information Systems Research, 13(2), 205-223.
  • Koyuncu C. (2004), “The impacts of quickness, price, and payment risk”. Journal of Socio-Economics, 33(1), 241-251.
  • Lima YJ, Osman A, Salahuddin SN. (2016), “Factors Influencing Online Shopping Behavior: The Mediating Role of Purchase Intention”. Procedia Economics and Finance, 35(1), 401 – 410.
  • Liu XH. (2008) “An empirical study of online shopping customer satisfaction in China: a holistic perspective.” International Journal of Retail & Distribution Management, 36(11), 919-940.
  • López MFJ, Luna P. (2005), “Online shopping, the standard learning hierarchy, and consumers’ internet expertise An American-Spanish comparison”. Internet Research 15(3), 312-334.
  • Mislove A. (2007), “Measurement and Analysis of Online Social Networks. IMC’07 “. Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement. San Diego, California, USA. October 24-26.
  • Oliveira RC. (2007) “Evidences from link between quality and loyalty in e-service”. Sistemas & Gestão, 2(1), 1-15.
  • Pires G, Stanton J, Eckfor A. (2004), “Influences on the perceived risk of purchasing”. Journal of Consumer Behavior, 4(2), 118-131.
  • Saaty, TL. (1977) “A scaling method for priorities in hierarchical structures”. Journal of Mathematical Psychology, 15(1), 234–281.
  • Sheikh JF. (2009), “Cultural Representation for Multi-culture Interaction Design”. Internationalization, Design and Global Development: Third International Conference IDGD, San Diego, CA, USA, July 19-24.
  • Sheikh JA, Abbas A, Mehmood Z. (2015), “Design Consideration of Online Shopping Website to Reach to Reach Women in Pakistan”. Procedia Manufacturing, (3), 6298-6304.
  • Smith D. (2003), “Strategic online Customer Decision making: Leveraging the transformational power of internet”. Online Information Review, 27(6) 418-432.
  • Sun CC, Lin G T. (2009) “Using fuzzy TOPSIS method for evaluating the competitive advantages”. Expert Systems with Applications, 36(9), 11764-11771.
  • Tong X. (2010) “A cross-national investigation of an extended technology acceptance model in”. International Journal of Retail & Distribution Management, 38(10), 742-759.
  • Wells JD, Parboteeah V, Valacich JS. (2011), “Online Impulse Buying: Understanding the Interplay between Consumer Impulsiveness and Website Quality”. Journal of the Association for Information Systems, 12(1), 32-56.
  • Whittler TE. (2002), “Model’s race: A peripheral cue in advertising messages”. Journal of Consumer Psychology, 12(4), 291-301.
  • Zhou LD. (2007), “Online Shopping Acceptance Model – a critical survey of.” Journal of Electronic Commerce Research, 8(1), 41-62.
  • Zhau Z, Bao Y. (2002), “User’s attitudes toward web advertising: Effects of”. Advances in Consumer Research, 29(1), 71-78.
Uluslararası Yönetim İktisat ve İşletme Dergisi-Cover
  • ISSN: 2147-9208
  • Başlangıç: 2005
  • Yayıncı: Zonguldak Bülent Ecevit Üniversitesi