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E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı

Year 2026, Issue: e-ticaret lojistiği, 85 - 101, 06.03.2026
https://izlik.org/JA68PF84AE

Abstract

E-ticaret ekosistemi; pazar yerleri, çevrim içi perakendeciler, ödeme sistemleri, lojistik şirketleri, platform sağlayıcılar, üreticiler ve markalardan oluşmaktadır. Artan dijitalleşme yatırımları ve tüketici harcamaları ile küresel e-ticaret pazarı giderek büyümektedir. E-ticaret kapsamında teknolojilerin değerlendirilmesi, işletmelerin rekabet gücünü koruyabilmesi, müşteri deneyimini iyileştirebilmesi ve operasyonel verimliliğini artırabilmesi açısından son derece kritik bir süreçtir. Kullanıcıların e-ticaretten başlıca beklentileri uygun fiyat, zaman tasarrufu, ürün çeşitliliği gibi etkenlerdir. Bu sayede kullanıcılar mağazaya gitmeden satın almak istedikleri ürünle ilgili fiyat karşılaştırmasını kısa bir sürede çeşitli ürünler için yapabilir. Bu bağlamda, müşteri ihtiyaçlarının analizi rekabetçi e-ticaret ortamında büyük bir önem kazanmaktadır. E-ticaret kapsamında teknoloji değerlendirilmesi, yalnızca teknik bir gereklilik değil, aynı zamanda stratejik bir yönetim sürecidir. Bu çalışmanın amacı, dijital dünyada gelişen ve değişen e-ticaret uygulamaları için teknolojik gereksinimleri önceliklendirmek ve bu kapsamda bir teknolojik bakış açısı sunmaktadır. Bu kapsamda bu çalışmada yazın taraması ve uzman değerlendirmeleriyle belirlenen e-ticaret kullanıcı ihtiyaçları ve teknolojik gereksinimleri Kalite Fonksiyonu Yayılımı yönteminin temel aracı olan Kalite Evi yaklaşımından yararlanılarak modellenmekte, analiz edilmekte ve elde edilen bulgular yorumlanmaktadır. Müşteri ihtiyaçlarının ağırlıklarını belirlemek için Analitik Hiyerarşi Süreci (AHS) tekniği uygulanmaktadır. E-ticaret teknolojilerinin değerlendirilmesi için bir uygulama gerçekleştirilerek sonuçlar çalışmanın son kısmında paylaşılmaktadır. Çalışmadan elde edilen bulgulara göre uygun fiyat, mobil uyumluluk ve kullanıcı dostu arayüz en önemli müşteri beklentileri olarak karşımıza çıkarken yapay zeka teknolojisi ile büyük veri analitiği en kritik teknolojik gereksinimler olarak bulunmuştur.

References

  • Akoa, Y., (1990), “Quality function deployment”, integrating customer requirements into product design. Productivity Press, Cambridge.
  • Bening, S. A., Dachyar, M., Pratama, N. R., Park, J., & Chang, Y. (2023). E-Commerce technologies adoption strategy selection in Indonesian SMEs using the decision-makers, technological, organizational and environmental (DTOE) framework. Sustainability, 15(12), 9361.
  • Bocean, C. G., Popescu, L., Simion, D., Sperdea, N. M., Puiu, C., Marinescu, R. C., & Maria, E. (2025). The Role of AI technologies in e-commerce development: A European comparative study. Journal of Theoretical and Applied Electronic Commerce Research, 20(3), 225.
  • Bonetti, F., Warnaby, G., & Quinn, L. (2018). Augmented reality and virtual reality in physical and online retailing: A review, synthesis and research agenda. Augmented reality and virtual reality, 119-132.
  • Bukhari, E. A., Daim, T., Alzahrani, S., Gillpatrick, T., & Santiago, L. (2025). Multi perspective technology readiness assessment for E-commerce: Case of the omni-channel adoption in the food retail sector during COVID-19. Technology in Society, 81, 102792.
  • Büyüközkan, G. (2009). Determining the mobile commerce user requirements using an analytic approach. Computer Standards & Interfaces, 31(1), 144-152.
  • Cao, J. (2025). Evaluation of cross-border e-commerce economic and trade data management device based on blockchain technology. Journal of Internet Technology, 26(1), 137-145.
  • Chan, L. K., & Wu, M. L. (2002). Quality function deployment: a comprehensive review of its concepts and methods. Quality engineering, 15(1), 23-35.
  • Dahlberg, T., Guo, J., & Ondrus, J. (2015). A critical review of mobile payment research. Electronic commerce research and applications, 14(5), 265-284.
  • Demirdöğmez, M., Gültekin, N., & Taş, H. Y. (2018). Türkiye’de e-ticaret sektörünün yıllara göre gelişimi. OPUS International Journal of Society Researches, 8(15), 2216-2236.
  • Euromonitor International (2025). Retail E-Commerce By Marketplace E-Commerce, Market Size Historical 2018-2023 (https://www.euromonitor.com/insights/retail-and-ecommerce)
  • Gulfraz, M. B., Sufyan, M., Mustak, M., Salminen, J., & Srivastava, D. K. (2022). Understanding the impact of online customers’ shopping experience on online impulsive buying: A study on two leading E-commerce platforms. Journal of Retailing and Consumer Services, 68, 103000.
  • Hanaysha, J. R., Ramadan, H. I., & Alhyasat, K. M. (2025). Exploring the impact of customer reviews, website quality, perceived service quality, and product assortment on online purchase intention: Mediating role of trust. Telematics and Informatics Reports, 100236.
  • Indrayanto, A., Restianto, Y. E., Iskandar, D., & Kurniawan, R. E. (2024). Evaluation of e-commerce organic coconut sugar: Technology acceptance model (TAM) and end-user computing satisfaction (EUCS) Model. Quality-Access to Success, 25(199).
  • Javornik, A. (2016). Augmented reality: Research agenda for studying the impact of its media characteristics on consumer behaviour. Journal of Retailing and Consumer Services, 30, 252-261.
  • Karakış, İ., Gültekin, O., Karabıyık, B., Sağmanlı, D. (2024). E-Ticaret Lojistiğinde Sorunlar ve Politika Önerileri. TÜSİAD.
  • Kennedyd, S. I., Marjerison, R. K., Yu, Y., Zi, Q., Tang, X., & Yang, Z. (2022). E-Commerce engagement: a prerequisite for economic sustainability—an empirical examination of influencing factors. Sustainability, 14(8), 4554.
  • Khanna, A. (2024). Exploring Customer Experience using Artificial Intelligence in Retail Businesses: A Technology Acceptance Model Approach. International Journal of Business Analytics & Intelligence (IJBAI), 12(2).
  • Li, J., & Chen, H. (2024). Analysis of the impact of live E-commerce on consumer happiness based on big data technology from the perspective of perception control. Electronic Commerce Research, 1-21.
  • Liu, H., & Bai, O. (2022). Evaluation method of innovative education model of e‐commerce video live broadcast based on big data analysis technology. Advances in Mathematical Physics, 2022(1), 6806823.
  • Pires, P. B., Prisco, M., Delgado, C., & Santos, J. D. (2024). A conceptual approach to understanding the customer experience in e-commerce: An empirical study. Journal of Theoretical and Applied Electronic Commerce Research, 19(3), 1943-1983.
  • Qiu, Y. (2018). Impact of E-commerce evaluation authenticity on consumer purchase decision based on electroencephalogram test technology. NeuroQuantology, 16(5), 481-487.
  • Rekabet Kurumu. (2022). E-Pazaryeri Platformları Sektör İncelemesi Nihai Raporu,. (https://www.rekabet.gov.tr/Dosya/geneldosya/e-pazaryeri-si-raporu-pdf)
  • Saaty, T. L. (1980). Analytic hierarchy process. John Wiley & Sons, Ltd.
  • Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International journal of services sciences, 1(1), 83-98.
  • Statista, (2024). E-Commerce in Turkey (https://www.statista.com/statistics/1290279/e-commerce-market-size-in-turkey/).
  • Taşel, F. (2020). Mobil Ticaret için Önemli Lojistik Kriterlerin Analitik Hiyerarşi Süreci ile Belirlenmesi. Lojistik Dergisi, 52, 97-106.
  • Wang, C., Ahmad, S. F., Ayassrah, A. Y. B. A., Awwad, E. M., Irshad, M., Ali, Y. A., ... & Han, H. (2023b). An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce. Heliyon, 9(8).
  • Wang, H., Li, Y., Lin, W., & Wei, W. (2023a). How does digital technology promote carbon emission reduction? Empirical evidence based on e-commerce pilot city policy in China. Journal of Environmental Management, 325, 116524.
  • Yadav, H., Soni, U., Gupta, S., & Kumar, G. (2022). Evaluation of barriers in the adoption of E-commerce technology in SMEs: A fuzzy DEMATEL approach. Journal of Electronic Commerce in Organizations (JECO), 20(1), 1-18.
  • Yim, M. Y. C., Chu, S. C., & Sauer, P. L. (2017). Is augmented reality technology an effective tool for e-commerce? An interactivity and vividness perspective. Journal of interactive marketing, 39(1), 89-103.
  • Zarrin, S., Daim, T., Gillpatrick, T., Bolatan, G., & Sharma, M. (2025). Evaluating customer orientation in e-commerce: an organization focused technology assessment. Technology Analysis & Strategic Management, 37(11), 1663-1678.
  • Zhu, K. (2004). The complementarity of information technology infrastructure and e-commerce capability: A resource-based assessment of their business value. Journal of management information systems, 21(1), 167-202.

An Integrated House of Quality Approach for E-Commerce Technology Assessment

Year 2026, Issue: e-ticaret lojistiği, 85 - 101, 06.03.2026
https://izlik.org/JA68PF84AE

Abstract

The e-commerce ecosystem consists of marketplaces, online retailers, payment systems, logistics companies, platform providers, manufacturers, and brands. The global e-commerce market is growing rapidly, driven by increased digitalization investments and consumer spending. Evaluating technologies in the e-commerce context is crucial for businesses to maintain competitiveness, improve the customer experience, and increase operational efficiency. Users' primary expectations from e-commerce include affordability, time savings, and product variety. This allows users to quickly compare prices across products without going to a store. In this context, analyzing customer needs is crucial in the competitive e-commerce environment. Evaluating technology within the e-commerce context is not only a technical requirement but also a strategic management process. The purpose of this study is to prioritize technological requirements for evolving and changing e-commerce applications in the digital world and to provide a technological perspective within this context. In this context, this study models and analyzes e-commerce user needs and technological requirements, identified through a literature review and expert opinions, using the House of Quality approach (the main tool of the Quality Function Deployment method), and interprets the results. The Analytical Hierarchy Process (AHP) technique is applied to determine the weights of customer needs. An application is implemented to evaluate e-commerce technologies, and the results are shared in the final section of the study. According to the study's findings, while affordable prices, mobile compatibility, and a user-friendly interface are the most important customer expectations, artificial intelligence and big data analytics are the most critical technological requirements.

References

  • Akoa, Y., (1990), “Quality function deployment”, integrating customer requirements into product design. Productivity Press, Cambridge.
  • Bening, S. A., Dachyar, M., Pratama, N. R., Park, J., & Chang, Y. (2023). E-Commerce technologies adoption strategy selection in Indonesian SMEs using the decision-makers, technological, organizational and environmental (DTOE) framework. Sustainability, 15(12), 9361.
  • Bocean, C. G., Popescu, L., Simion, D., Sperdea, N. M., Puiu, C., Marinescu, R. C., & Maria, E. (2025). The Role of AI technologies in e-commerce development: A European comparative study. Journal of Theoretical and Applied Electronic Commerce Research, 20(3), 225.
  • Bonetti, F., Warnaby, G., & Quinn, L. (2018). Augmented reality and virtual reality in physical and online retailing: A review, synthesis and research agenda. Augmented reality and virtual reality, 119-132.
  • Bukhari, E. A., Daim, T., Alzahrani, S., Gillpatrick, T., & Santiago, L. (2025). Multi perspective technology readiness assessment for E-commerce: Case of the omni-channel adoption in the food retail sector during COVID-19. Technology in Society, 81, 102792.
  • Büyüközkan, G. (2009). Determining the mobile commerce user requirements using an analytic approach. Computer Standards & Interfaces, 31(1), 144-152.
  • Cao, J. (2025). Evaluation of cross-border e-commerce economic and trade data management device based on blockchain technology. Journal of Internet Technology, 26(1), 137-145.
  • Chan, L. K., & Wu, M. L. (2002). Quality function deployment: a comprehensive review of its concepts and methods. Quality engineering, 15(1), 23-35.
  • Dahlberg, T., Guo, J., & Ondrus, J. (2015). A critical review of mobile payment research. Electronic commerce research and applications, 14(5), 265-284.
  • Demirdöğmez, M., Gültekin, N., & Taş, H. Y. (2018). Türkiye’de e-ticaret sektörünün yıllara göre gelişimi. OPUS International Journal of Society Researches, 8(15), 2216-2236.
  • Euromonitor International (2025). Retail E-Commerce By Marketplace E-Commerce, Market Size Historical 2018-2023 (https://www.euromonitor.com/insights/retail-and-ecommerce)
  • Gulfraz, M. B., Sufyan, M., Mustak, M., Salminen, J., & Srivastava, D. K. (2022). Understanding the impact of online customers’ shopping experience on online impulsive buying: A study on two leading E-commerce platforms. Journal of Retailing and Consumer Services, 68, 103000.
  • Hanaysha, J. R., Ramadan, H. I., & Alhyasat, K. M. (2025). Exploring the impact of customer reviews, website quality, perceived service quality, and product assortment on online purchase intention: Mediating role of trust. Telematics and Informatics Reports, 100236.
  • Indrayanto, A., Restianto, Y. E., Iskandar, D., & Kurniawan, R. E. (2024). Evaluation of e-commerce organic coconut sugar: Technology acceptance model (TAM) and end-user computing satisfaction (EUCS) Model. Quality-Access to Success, 25(199).
  • Javornik, A. (2016). Augmented reality: Research agenda for studying the impact of its media characteristics on consumer behaviour. Journal of Retailing and Consumer Services, 30, 252-261.
  • Karakış, İ., Gültekin, O., Karabıyık, B., Sağmanlı, D. (2024). E-Ticaret Lojistiğinde Sorunlar ve Politika Önerileri. TÜSİAD.
  • Kennedyd, S. I., Marjerison, R. K., Yu, Y., Zi, Q., Tang, X., & Yang, Z. (2022). E-Commerce engagement: a prerequisite for economic sustainability—an empirical examination of influencing factors. Sustainability, 14(8), 4554.
  • Khanna, A. (2024). Exploring Customer Experience using Artificial Intelligence in Retail Businesses: A Technology Acceptance Model Approach. International Journal of Business Analytics & Intelligence (IJBAI), 12(2).
  • Li, J., & Chen, H. (2024). Analysis of the impact of live E-commerce on consumer happiness based on big data technology from the perspective of perception control. Electronic Commerce Research, 1-21.
  • Liu, H., & Bai, O. (2022). Evaluation method of innovative education model of e‐commerce video live broadcast based on big data analysis technology. Advances in Mathematical Physics, 2022(1), 6806823.
  • Pires, P. B., Prisco, M., Delgado, C., & Santos, J. D. (2024). A conceptual approach to understanding the customer experience in e-commerce: An empirical study. Journal of Theoretical and Applied Electronic Commerce Research, 19(3), 1943-1983.
  • Qiu, Y. (2018). Impact of E-commerce evaluation authenticity on consumer purchase decision based on electroencephalogram test technology. NeuroQuantology, 16(5), 481-487.
  • Rekabet Kurumu. (2022). E-Pazaryeri Platformları Sektör İncelemesi Nihai Raporu,. (https://www.rekabet.gov.tr/Dosya/geneldosya/e-pazaryeri-si-raporu-pdf)
  • Saaty, T. L. (1980). Analytic hierarchy process. John Wiley & Sons, Ltd.
  • Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International journal of services sciences, 1(1), 83-98.
  • Statista, (2024). E-Commerce in Turkey (https://www.statista.com/statistics/1290279/e-commerce-market-size-in-turkey/).
  • Taşel, F. (2020). Mobil Ticaret için Önemli Lojistik Kriterlerin Analitik Hiyerarşi Süreci ile Belirlenmesi. Lojistik Dergisi, 52, 97-106.
  • Wang, C., Ahmad, S. F., Ayassrah, A. Y. B. A., Awwad, E. M., Irshad, M., Ali, Y. A., ... & Han, H. (2023b). An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce. Heliyon, 9(8).
  • Wang, H., Li, Y., Lin, W., & Wei, W. (2023a). How does digital technology promote carbon emission reduction? Empirical evidence based on e-commerce pilot city policy in China. Journal of Environmental Management, 325, 116524.
  • Yadav, H., Soni, U., Gupta, S., & Kumar, G. (2022). Evaluation of barriers in the adoption of E-commerce technology in SMEs: A fuzzy DEMATEL approach. Journal of Electronic Commerce in Organizations (JECO), 20(1), 1-18.
  • Yim, M. Y. C., Chu, S. C., & Sauer, P. L. (2017). Is augmented reality technology an effective tool for e-commerce? An interactivity and vividness perspective. Journal of interactive marketing, 39(1), 89-103.
  • Zarrin, S., Daim, T., Gillpatrick, T., Bolatan, G., & Sharma, M. (2025). Evaluating customer orientation in e-commerce: an organization focused technology assessment. Technology Analysis & Strategic Management, 37(11), 1663-1678.
  • Zhu, K. (2004). The complementarity of information technology infrastructure and e-commerce capability: A resource-based assessment of their business value. Journal of management information systems, 21(1), 167-202.
There are 33 citations in total.

Details

Primary Language Turkish
Subjects E-Trade
Journal Section Research Article
Authors

Gülçin Büyüközkan 0000-0002-2112-3574

Esin Mukul 0000-0003-4835-8821

Merve Güler 0000-0003-1664-1139

Submission Date November 2, 2025
Acceptance Date March 6, 2026
Publication Date March 6, 2026
IZ https://izlik.org/JA68PF84AE
Published in Issue Year 2026 Issue: e-ticaret lojistiği

Cite

APA Büyüközkan, G., Mukul, E., & Güler, M. (2026). E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, e-ticaret lojistiği, 85-101. https://izlik.org/JA68PF84AE
AMA 1.Büyüközkan G, Mukul E, Güler M. E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2026;(e-ticaret lojistiği):85-101. https://izlik.org/JA68PF84AE
Chicago Büyüközkan, Gülçin, Esin Mukul, and Merve Güler. 2026. “E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. e-ticaret lojistiği: 85-101. https://izlik.org/JA68PF84AE.
EndNote Büyüközkan G, Mukul E, Güler M (March 1, 2026) E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi e-ticaret lojistiği 85–101.
IEEE [1]G. Büyüközkan, E. Mukul, and M. Güler, “E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. e-ticaret lojistiği, pp. 85–101, Mar. 2026, [Online]. Available: https://izlik.org/JA68PF84AE
ISNAD Büyüközkan, Gülçin - Mukul, Esin - Güler, Merve. “E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. e-ticaret lojistiği (March 1, 2026): 85-101. https://izlik.org/JA68PF84AE.
JAMA 1.Büyüközkan G, Mukul E, Güler M. E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2026;:85–101.
MLA Büyüközkan, Gülçin, et al. “E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. e-ticaret lojistiği, Mar. 2026, pp. 85-101, https://izlik.org/JA68PF84AE.
Vancouver 1.Gülçin Büyüközkan, Esin Mukul, Merve Güler. E-Ticaret Teknolojilerinin Değerlendirilmesi İçin Entegre Kalite Evi Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi [Internet]. 2026 Mar. 1;(e-ticaret lojistiği):85-101. Available from: https://izlik.org/JA68PF84AE