USING FUZZY TOPSIS AND REGRESSION BASED WEIGHTS TO RANK E-COMMERCE WEBSITES

Yıl 2019, Cilt: 27 Sayı: 2, 116 - 124, 15.08.2019

N. Fırat Özkan , Fulya Gökalp Yavuz

https://doi.org/10.31796/ogummf.563348

Cited By: 3

Öz

Web
sitesi kullanılabilirliği, çeşitli disiplinlerden katkılarla beslenen
araştırmaları içeren yaygın bir çalışma alanıdır. Bir web sitesinin
kullanılabilirliğini değerlendirmek için çeşitli yöntemler mevcuttur. Kontrol
listeleri, sezgisel değerlendirmeler, uzman değerlendirmeleri, anketler ve
kullanıcı testleri web sitelerinin değerlendirilmesinde en popüler yöntemler
olarak sunulmaktadır. Özellikle e-ticaret web sitelerinin kullanılabilirliği,
bu sitelere oluşan rağbet ve e-ticaret web sitelerinin sayısındaki artış
nedeniyle kritik bir öneme sahiptir. E-ticaret web sitelerinin çeşitliliği,
insanlığın günlük yaşamında çok kriterli karar verme (MCDM) sorununa tipik bir
örnek olarak gösterilebilir. Farklı kullanıcı gruplarının web sitelerinden
farklı beklentileri olduğundan, değerlendirme yöntemi uygun ölçüm kriterlerini
içerecek şekilde yapılandırılmalıdır. Değerlendirme yöntemi tanımlanırken ana
amaç ve web sitesinin hedef kullanıcıları dikkatle değerlendirilmelidir. Bu
çalışmada, en çok ziyaret edilen (Ocak 2018’de Alexa.com listesine göre), Türkiye'deki
e-ticaret web sitelerinin kullanılabilirlik açısından karşılaştırılmıştır. Lee
ve Kozar (2015) tarafından önerilen e-ticaret siteleri kullanılabilirlik ölçütleri
kriter olarak dikkate alınmıştır.. TOPSIS yöntemine iki farklı ağırlıklandırma
yaklaşımı entegre edilmiştir. Bu yaklaşımlardan biri bulanık uzman
değerlendirmesi ve diğeri ağırlıklı regresyon tahminidir. Bu çalışma ile kapsamlı
bir bakış açısı sağlamak ve e-ticaret web sitesi tasarımcıları ile
kullanıcıları arasında ortak kriterlerdeki farklı izlenimleri keşfetmek
amaçlanmıştır.

Anahtar Kelimeler

E-Ticaret, Web Siteleri, Çok Kriterli Karar Verme, Regresyon, Bulanık TOPSIS

USİNG FUZZY TOPSIS AND REGRESSİON BASED WEİGHTS TO RANK E-COMMERCE WEBSİTES

Öz

Website usability is a widespread
study area which incorporates researches from various disciplines. Several
methods are available to evaluate usability of a website. Checklists, heuristic
evaluations, expert evaluations, surveys and user tests are presented as the
most popular methods for the evaluation of websites. Especially e-commerce
websites’ usability has a critical importance due to the rising in competence
and the rising in the number of e-commerce websites.  The diversity of e-commerce websites evokes
typical example of multi criteria decision making (MCDM) issue in daily life of
humanity. Since different user groups have different expectations from the
websites, the evaluation method should be structured to include appropriate
measurement criteria. The main aim and the target users of the website should
be considered attentively while defining the evaluation method. In this study,
the most visited (Based on Alexa.com list in January, 2018) e-commerce websites
in Turkey are compared in terms of usability. Criteria are decided based on the
study which was published by Lee and Kozar (2015).  Two different weighting approaches are
integrated to TOPSIS method. One of these approaches is fuzzy expert evaluation
and the other one is weighted regression estimate. We aim to discover different
different impressions between e-commerce website designers and users on the
same criteria to provide a comprehensive viewpoint.

Anahtar Kelimeler

Multicriteria, E-Commerce, Websites, Regression, Fuzzy TOPSIS

Kaynakça

• Belanche, D., Casaló, L. V., & Guinalíu, M. (2012). Website usability, consumer satisfaction and the intention to use a website: The moderating effect of perceived risk. Journal of Retailing and Consumer Services,19(1), 124-132. doi: https://doi.org/10.1016/j.jretconser.2011.11.001
• Boran, F. E., Genç, S., Kurt, M., & Akay, D. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363-11368. doi: https://doi.org/10.1016/j.eswa.2009.03.039
• C.L. Hwang, K. Yoon, Multple Attribute Decision Making－Methods and Applications: A State-of-the-Art Survey (1981), Springer-Verlag, New York, 1981.
• Carmona, C. J., Ramírez-Gallego, S., Torres, F., Bernal, E., del Jesus, M. J., & García, S. (2012). Web usage mining to improve the design of an e-commerce website: OrOliveSur. com. Expert Systems with Applications, 39(12), 11243-11249. doi: https://doi.org/10.1016/j.eswa.2012.03.046
• Chen CT (2000). Extension of the TOPSIS for group decision making under fuzzy Environment. Fuzzy Sets and Systems,114(1):1–9. doi: https://doi.org/10.1016/S0165-0114(97)00377-1
• Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International journal of production economics, 102(2), 289-301. doi: https://doi.org/10.1016/j.ijpe.2005.03.009
• Davidavičienė, V., & Tolvaišas, J. (2011). Measuring quality of e-commerce web sites: Case of lithuania. Economics and Management, 16, 723-729.
• De Jong, M., & Lentz, L. (2006). Scenario evaluation of municipal Web sites: Development and use of an expert-focused evaluation tool. Government Information Quarterly, 23(2), 191-206. doi: https://doi.org/10.1016/j.giq.2005.11.007
• Gelman, A. and Hill, J. (2009). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press, NY, USA.
• Goh, K. N., Chen, Y. Y., Lai, F. W., Daud, S. C., Sivaji, A., & Soo, S. T. (2013). A Comparison of Usability Testing Methods for an E-Commerce Website: A Case Study on a Malaysia Online Gift Shop. In Information Technology: New Generations (ITNG), 2013 Tenth International Conference on (pp. 143-150). IEEE.
• Guo, M., & Zhang, Y. B. (2010). A stock selection model based on analytic hierarchy process, factor analysis and TOPSIS. In Computer and communication technologies in agriculture engineering (CCTAE), 2010 international conference on (Vol. 2, pp. 466-469). IEEE.
• Huang, J. (2008). Combining entropy weight and TOPSIS method for information system selection. In Cybernetics and Intelligent Systems, 2008 IEEE Conference on (pp. 1281-1284). IEEE.
• L.A. Zadeh (1965). Fuzzy Sets. Information and Control 8 (3) 338- 356.
• Lee, S., & Koubek, R. J. (2010). The effects of usability and web design attributes on user preference for e-commerce web sites. Computers in Industry, 61(4), 329-341. doi: https://doi.org/10.1016/j.compind.2009.12.004
• Lee, Y., & Kozar, K. A. (2012). Understanding of website usability: Specifying and measuring constructs and their relationships. Decision Support Systems, 52(2), 450-463. doi: https://doi.org/10.1016/j.dss.2011.10.004
• M. Zeleny (1982). Multiple Criteria Decision Making. McGraw-Hill, New York.
• Nivala, A. M., Brewster, S., & Sarjakoski, T. L. (2008). Usability evaluation of web mapping sites. The Cartographic Journal, 45(2), 129-138. doi: https://doi.org/10.1179/174327708X305120
• Pal, M. N., & Choudhury, K. (2009). Exploring the dimensionality of service quality: an application of topsis in the Indian banking industry. Asia-Pacific Journal of Operational Research, 26(01), 115-133. doi: https://doi.org/10.1142/S0217595909002110
• Sivaji, A., Downe, A. G., Mazlan, M. F., Soo, S. T., & Abdullah, A. (2011). Importance of incorporating fundamental usability with social & trust elements for e-commerce website. In Business, Engineering and Industrial Applications (ICBEIA), 2011 International Conference on (pp. 221-226). IEEE.
• Sun, C. C., & Lin, G. T. (2009). Using fuzzy TOPSIS method for evaluating the competitive advantages of shopping websites. Expert Systems with Applications, 36(9), 11764-11771. doi: https://doi.org/10.1016/j.eswa.2009.04.017
• Tracy, J. P., & Albers, M. J. (2006). Measuring cognitive load to test the usability of web sites. In Annual Conference-society for technical communication (53), p. 256.Youngblood, N. E., & Mackiewicz, J. (2012). A usability analysis of municipal government website home pages in Alabama. Government Information Quarterly, 29(4), 582-588.
• Yu, X., Guo, S., Guo, J., & Huang, X. (2011). Rank B2C e-commerce websites in e-alliance based on AHP and fuzzy TOPSIS. Expert Systems with Applications, 38(4), 3550-3557. doi: https://doi.org/10.1016/j.eswa.2010.08.143
• Yue, Z. (2011). An extended TOPSIS for determining weights of decision makers with interval numbers. Knowledge-Based Systems, 24(1), 146-153. doi: https://doi.org/10.1016/j.giq.2011.12.010
• Alptekin, N., Hall, E. E., & Sevim, N. (2015). Evaluation of Websites Quality Using Fuzzy TOPSIS Method. International Journal of Academic Research in Business and Social Sciences, 5(8), 221-242. doi: https://doi.org/10.6007/ijarbss/v5-i8/1778
• Nagpal, R., Mehrotra, D., Bhatia, P. K., & Sharma, A. (2015). Rank university websites using fuzzy AHP and fuzzy TOPSIS approach on usability. International journal of information engineering and electronic business, 7(1), 29. . doi: https://doi.org/10.5815/ijieeb.2015.01.04
• Şengül, Ü, Eren, M., Shiraz, S. E., Gezder, V., & Şengül, A. B. (2015). Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renewable Energy, 75, 617-625. doi: https://doi.org/10.1016/j.renene.2014.10.04.
• Top Sites in Turkey The sites in the top sites lists are ordered by their 1 month Alexa traffic rank. Retrieved January 30, 2018, from https://www.alexa.com/topsites/countries/TR
• Turkey B2C E-Commerce Market 2017. Retrieved January 15, 2018, from https://www.ystats.com/market-reports/turkey-b2c-e-commerce-market-2017-2/
• Turkey B2C E-Commerce Market 2016, yStats.com. Retrieved January 15, 2018, from https://www.ystats.com/market-reports/turkey-b2c-e-commerce-market-2016/