Ranking of Web Sites Performance of Commercial Banks in Turkey by SWARA and ARAS Method

Year 2021, , 1514 - 1537, 10.07.2021

Muhammed Maruf , Kadir Özdemir

https://doi.org/10.26466/opus.888184

Cited By: 5

Abstract

Nowadays, with the technological advancements, lots of significant transformations have started in many areas and many of the economic and commercial activities have been transferred to the online environment. Thus, transition to digitalization has accelerated in many sectors. Banking sector is one of the fastest sector which adapt to digital transformation. With the acceleration of digital transformation in the banking sector, many banks have commenced to offer lots of services through internet banking applicates on their websites. Thus, the importance of banking websites has increased. In this context, the main object of this study to analysis and rank of 15 commercial banks’ websites according to website performance criteria. SWARA and ARAS methods were used to rank the websites. According to results of SWARA method page opening time and speed index were found to be the highest weighted criteria, while the average time spent on the websites, world ranking and Turkey ranking were found to be the lowest weighted criteria in the evaluation of the bank’s website performance. On the other hand, according to the benefit values which calculated as a result of the ARAS method, it was concluded that HSBC, Fiba Bank, and Şeker Bank had the best performing websites. Also, TEB, ING Bank, and Akbank had the worst performing websites.

Keywords

SWARA, ARAS, Website, Banking

Türkiye’deki Ticari Bankalara Ait Web Sitelerin Performanslarının SWARA ve ARAS Yöntemi İle Sıralanması

Abstract

Günümüzde teknolojik gelişmeler ile birlikte küresel olarak birçok alanda önemli dönüşümler başlamış olup ekonomik ve ticari faaliyetlerin birçoğu internet ortamına taşımıştır. Böylece birçok sektörde dijitalleşmeye geçişi hızlanmıştır. Özellikle bankacılık sektörü dijital dönüşüme en hızlı adapte olan sektörlerden biridir. Bankacılık sektöründeki dijital dönüşümün hızlanmasıyla birçok banka şubelerinde sunduğu hizmetleri web sitelerinde internet bankacılığı uygulamaları aracılığıyla da sunmaya başlamıştır. Böylece bankalara ait web sitelerin önemi artmıştır. Bu bağlamda bu çalışmada Türkiye’deki 15 ticari bankanın web sitelerinin performansını analiz ederek banka web sitlerini sıralamak amaçlanmıştır. Web sitelerinin performans kriterlerine göre sıralanmasında SWARA ve ARAS yöntemleri kullanılmıştır. SWARA yöntemi sonuçlarına göre banka web sitesi performansının değerlendirilmesinde sayfa açılma süresi ve hız endeksi kriterleri en yükse ağırlığa sahip kriterler olarak bulunmuşken, web sitesinde geçirilen ortalama süre, dünya sıralaması ve Türkiye sıralaması kriterleri ise en düşük ağırlığı sahip kriterler olarak bulunmuştur. ARAS yöntemi sonucunda hesaplanan fayda değerlerine göre ise sırasıyla HSBC, Fiba Bank ve Şeker Bank’ın en iyi performans gösteren web sitelerine sahip olduğu sonucuna ulaşılmıştır. Türkiye Ekonomi Bankası, ING Bank ve Akbank ise en kötü performans gösteren web sitelerine sahip olup yapılan sıralamada son üç sırada yer almıştır.

Keywords

SWARA, ARAS, Web sitesi, Bankacılık.

References

• Akgül, Y. (2018). Banking websites in Turkey: An accessibility, usability and security evaluation. Journal of Business Research - Turk, 10(1), 782–796.
• Arslan, H. M. (2017). AHP-ARAS hibrit yöntemi ile lojistik işletmelerinin en uygun araç seçimi. Alphanumeric Journal, 5(2), 271–282.
• Ayyıldız, E. ve Demirci, E. (2018). Türkiye’de yer alan şehirlerin yaşam kalitelerinin SWARA entegreli TOPSIS yöntemi ile belirlenmesi. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 30, 67–87.
• Bakır, M. ve Atalık, Ö. (2018). Entropi ve ARAS yöntemleriyle havayolu işletmelerinde hizmet kalitesinin değerlendirilmesi. Journal of Business Research - Turk, 10(1), 617–638.
• Balki, M. K., Erdoğan, S., Aydın, S. ve Sayin, C. (2020). The optimization of engine operating parameters via SWARA and ARAS hybrid method in a small SI engine using alternative fuels. Journal of Cleaner Production, 258, 1-12.
• Beybur, M. ve Çetinkaya, M. (2020). Covid-19 pademisinin Türkiye’de dijital bankacılık ürün ve hizmetlerin kullanımı üzerindeki etkisi. International Journal of Western Black Sea Socialand Humanities Sciences, 4(2), 148–163.
• Bhatti, A., Akram, H., Basit, H. M., Khan, A. U., Naqvi, S. M. Raza, ve Bilal, M. (2020). E-commerce trends during COVID-19 Pandemic. International Journal of Future Generation Communication and Networking, 13(2), 1449–1452.
• Booth, D. and Jansen, B. J. (2010). A review of methodologies for analyzing websites. Web technologies: Concepts, methodologies, tools, and applications, In B.J. Jansen, A. Spink & I. Taksa (Eds.), Handbook of research on web log analysis. 145-166. Hershey, PA.: IGI.
• Carmona, C. J., Ramírez-Gallego, S., Torres, F., Bernal, E., Del Jesus, M. J. and García, S. (2012). Web usage mining to improve the design of an e-commerce website: Or OliveSur.com. Expert Systems with Applications, 39(12), 11243–11249.
• Chmielarz, W. and Zborowski, M. (2018a). Analysis of e-banking websites’ quality with the application of the TOPsIs method - apPractical study. Procedia Computer Science, 126, 1964–1976.
• Chmielarz, W. and Zborowski, M. (2018). On analysis of e-banking websites quality - Comet application. Procedia Computer Science, 126, 2137–2152.
• Çakır, E. (2018). Bütünleşik SWARA ve EDAS yöntemi̇ kullanarak fi̇tnes merkezleri̇nin değerlendi̇ri̇lmesi̇: Örnek bi̇r uygulama. Hitit Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 11(3), 1907–1923.
• Dahooie, H., J., Beheshti Jazan Abadi, E., Vanaki, A. S. and Firoozfar, H. R. (2018). Competency-based IT personnel selection using a hybrid SWARA and ARAS-G methodology. Human Factors and Ergonomics In Manufacturing, 28(1), 5–16.
• Dehsiri, H., J., S. and Aghaei, M. (2020). Identifying and prioritizing human resources risks through the combination of SWARA and gray ARAS. Journal of Human Resource Studies, 10(1), 53–78.
• Ecer, F. (2014). A hybrid banking websites quality evaluation model using AHP and COPRAS-G: A turkey case. Technological and Economic Development of Economy, 20(4), 758–782.
• Elisa, N. (2017). Usability, accessibility and web security assessment of e-government websites in Tanzania. International Journal of Computer Applications, 164(5), 42–48.
• Ercan, E. ve Kundakcı, N. (2017). Bir tekstil işletmesi için desen programı seçiminde ARAS ve OCRA yöntemlerinin karşılaştırılması. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 1, 83–105.
• GTmetrix (2020). How fast does your website load? Find out with GTmetrix. https://gtmetrix.com/. Erişim tarihi: 07.02.2021.
• Gümüş, U. T., Öziç, H. C. ve Sezer, D. (2019). BİST’ te inşaat ve bayındırlık sektöründe işlem gören işletmelerin SWARA ve ARAS yöntemleriyle finansal performanslarının değerlendirilmesi. OPUS Uluslararası Toplum Araştırmaları Dergisi, 10(17), 835–858.
• Ighravwe, D. E. and Oke, S. A. (2019). A multi-criteria decision-making framework for selecting a suitable maintenance strategy for public buildings using sustainability criteria. Journal of Building Engineering, 24(March), 100753.
• Karabasevic, D., Stanujkic, D. and Urosevic, S. (2015). The MCDM model for personnel selection based on SWARA and ARAS methods. Management - Journal for theory and practice of management, 20(77), 43–52.
• Karabasevic, D., Zavadskas, E. K., Turskis, Z. and Stanujkic, D. (2016). The framework for the selection of personnel based on the SWARA and ARAS methods under uncertainties. Informatica (Netherlands), 27(1), 49–65.
• Karabasevic, D., Stanujkic, D., Urosevic, S., Popovic, G. and Maksimovic, M. (2017). An approach to criteria weights determination by integrating the DELPHI and the adapted SWARA methods. Management: Journal of Sustainable Business and Management Solutions in Emerging Economies, 22(3), 15-25.
• Karabasevic, D., Maksimović, M., Stanujkić, D., Jocić, G. and Rajčević, D. (2018). Selection of software testing method by using ARAS method. Tehnika, 73(5), 724–729.
• Kersuliene, V., Zavadskas, E. K. and Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
• Keršulienė, Violeta, and Zenonas Turskis. 2011. Integrated fuzzy multiple criteria decision making model for architect selection. Technological and Economic Development of Economy 17(4), 645–66.
• Koc, N. ve Uysal, F. (2017). Reverse logistics and application of ARAS method. Pressacademia, Journal of Management, Marketing and Logistics 4(2), 178–185.
• Korucuk, S. (2019). ÇKKV yöntemleri ile imalat işletmelerinde TZY performans faktörlerinin önem derecelerinin belirlenmesi ve en ideal rekabet stratejisi seçimi: Ordu ili örneği. Dokuz Eylul Universitesi Iktisadi ve Idari Bilimler Dergisi, 33(2), 569–593.
• Mostafaeipour, A., Dehshiri, S. J. H., Dehshiri, S. S. H. and Jahangiri, M. (2020a). Prioritization of potential locations for harnessing wind energy to produce hydrogen in Afghanistan. International Journal of Hydrogen Energy, 45(58), 33169–33184.
• Mostafaeipour, A., Hosseini Dehshiri, S. J. and Hosseini Dehshiri, S. S. (2020b). Ranking locations for producing hydrogen using geothermal energy in Afghanistan. International Journal of Hydrogen Energy, 45(32), 15924–15940.
• Nagy, Z. (2013). Improved speed on intelligent web sites. Recent Advances in Computer Science, 1(14), 215-220.
• Nakhate, S. B. and Jain, N. (2020). The effect of coronavirus on e-commerce. Studies in Indian Place Names, 40(68), 516-518.
• Oyefolahan, O., I., A. Sule, A., A. Adepoju, S. and Babakano, F. (2019). Keeping with the global trends: An evaluation of accessibility and usability of Nigerian banks websites. International Journal of Information Engineering and Electronic Business, 11(2), 44–53.
• Özdemir, M. and Turna, G. B. (2020). Website performances of commercial banks in Turkey. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 64, 38–52.
• Pakkala, H., Presser, K. and Christensen, T. (2012). Using Google Analytics to measure visitor statistics: The case of food composition websites. International Journal of Information Management, 32(6), 504–512.
• Pantelimon, F., Georgescu, T. and Posedaru, B. Ş. (2020). The impact of mobile e-commerce on GDP: A comparative analysis between Romania and Germany and how Covid-19 influences the e- commerce activity worldwide. Informatica Economică, 24(2), 27–41.
• Pelitli, T., Karagöz, E., Özbek, D. ve Yaralıo, K. (2018). Karar verme yöntemleri ARAS ve TOPSIS ile besin tercihlerine yönelik web tabanlı uygulama. 5th International Management Information Systems Conference, October 24.
• Prasad, R. (2019). Selection of internal safety auditors in an Indian construction organization based on the SWARA and ARAS methods. Journal of Occupational Health and Epidemiology, 8(3), 134–140. Sarkar, A. ve Pal, A. (2018). Websites of Indian banks: A webometric study. Library Philosophy and Practice (e-journal). 1-18.
• Shariati, S., Yazdani-Chamzini, A., Salsani, A. and Tamosaitiene, J. (2014). Proposing a new model for waste dump site selection: Case study of ayerma phosphate mine. Inzinerine Ekonomika-Engineering Economics, 25(4), 410–419.
• Similarweb, (2020). Traffic overview. https://www.similarweb.com/. Erişim tarihi: 07.02.2021.
• Stanujkic, D., Djordjevic, B., and Karabasevic, D. (2015). Selection of candidates in the process of recruitment and selection of personnel based on the SWARA and ARAS methods. Quaestus Multidisciplinary Research Journal, 7, 53–64.
• Sulova, S. (2019). A system for E-commerce website evaluation. International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, 19(2.1), 25–32.
• Thompson, M. F., Tuzovic, S. and Braun, C. (2019). Trustmarks: Strategies for exploiting their full potential in e-commerce. Business Horizons, 62(2), 237–247.
• Tran, L. T. T. (2020). Managing the effectiveness of e-commerce platforms in a pandemic. Journal of Retailing and Consumer Services, 58, 102-287.
• Vockic, M., Stojic, G. and Stevic, B. (2018). Integrated rough SWARA-ARAS model for selection of electric forklift. The 2nd International Conference on Management, Engineering and Environment, 216–227.
• Waisberg, D. and Kaushik, A. (2009). Web Analytics 2.0: Empowering customer centricity. The original Search Engine Marketing Journal, 2(1), 5-11.
• Yıldırım, B. F. (2015). Çok kri̇terli̇ karar verme problemleri̇nde ARAS yöntemi̇. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 6(9), 285–296.
• Yurdoğlu, H. ve Kundakcı, N. (2017). SWARA ve WASPAS yöntemleri̇ ile sunucu seçi̇mi̇. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 20(38), 253–270.
• Zavadskas, E. K. and Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technological and Economic Development of Economy, 16(2), 159-172.
• Zhu, J., Chan, D. S., Prabhu, M. S., Natarajan, P., Hu, H. and Bonomi, F. (2013). Improving web sites performance using edge servers in fog computing architecture. Proceedings - 2013 IEEE 7th International Symposium on Service-Oriented System Engineering, SOSE 2013, 320–323.
• Zolfani, H., S., Esfahani, M. H., Bitarafan, M., Zavadskas, E. K. and Arefi, S. L. (2013). Developing a new hybrid mcdm method for selection of the optimal alternative of mechanical longitudinal ventilation of tunnel pollutants during automobile accidents. Transport, 28(1), 89–96.
• Zolfani H., S. and Saparauskas, J. (2013). New application of SWARA method in prioritizing sustainability assessment indicators of energy system. Engineering Economics, 24(5), 408–414.