KADIN GİRİŞİMCİLERİN ONLİNE SATIN ALMA NİYETİNDE YAPAY ZEKA İLE ÜRÜN KİŞİSELLEŞTİRMEYE BAKIŞ

Öz

E-ticaret ekosisteminde yapay zekâ (YZ) tabanlı kişiselleştirme uygulamaları, tüketicilerin karar verme süreçlerinde giderek daha belirleyici bir rol oynamaktadır. Ürün önerileri, dinamik fiyatlandırma stratejileri, kişiselleştirilmiş reklamcılık ve sanal asistanlar bu dönüşümün temel bileşenleri arasında yer almaktadır. Kadın girişimciler ise hem işletmeci hem de bireysel tüketici kimlikleriyle bu teknolojilerle doğrudan etkileşim hâlindedir. Bu çalışmanın amacı, kadın girişimcilerin YZ tabanlı ürün kişiselleştirmeye yönelik algılarını keşfetmek ve bu algıların çevrim içi satın alma niyetine yönelik anlamlarını derinlemesine incelemektir. Araştırma, nitel bir desende yürütülmüştür. Çalışmada, Hakkâri’de faaliyet gösteren 30 kadın girişimci ile yarı yapılandırılmış görüşmeler yapılmış ve NVivo 11 aracılığıyla içerik analizi yöntemiyle analiz edilmiştir. Analiz sonucunda iki ana tema ve altı tema belirlenmiştir: (1) yapay zeka ile kişiselleştirme ve (2) online satın alma niyeti. Bulgular, kadın girişimcilerin YZ tabanlı kişiselleştirmeyi hem fırsat hem de risk olarak değerlendirdiklerini göstermektedir. Katılımcıların önemli bir bölümü kişiselleştirmenin zaman tasarrufu ve kolaylık sağladığını belirtirken, bir kısmı ise veri gizliliği, dolandırıcılık ve mahremiyet kaygıları nedeniyle temkinli bir tutum sergilemiştir.

Anahtar Kelimeler

• Kadın girişimcilik
• Yapay zeka tabanlı kişiselleştirme
• Online satın alma niyeti

EXPLORİNG WOMEN ENTREPRENEURS’ PERSPECTİVES ON AI-POWERED PRODUCT PERSONALİZATİON İN ONLİNE PURCHASE INTENTİONS

Öz

In the e-commerce ecosystem, AI-based personalization applications play an increasingly decisive role in consumers’ decision-making processes. Product recommendations, dynamic pricing strategies, personalized advertising, and virtual assistants are among the key components of this digital transformation. Women entrepreneurs, in particular, interact directly with these technologies both as business owners and as individual consumers. The aim of this study is to explore women entrepreneurs’ perceptions of AI-based product personalization and to examine in depth the implications of these perceptions for online purchase intentions. The study employed a qualitative research design. Semi-structured interviews were conducted with 30 women entrepreneurs operating in Hakkâri, Türkiye, and the data were analyzed using content analysis in NVivo 11 software. The analysis revealed two main themes and six subthemes: (1) AI-based personalization and (2) online purchase intentions. The findings indicate that women entrepreneurs perceive AI-based personalization as both an opportunity and a risk. While many participants emphasized the time-saving and convenience aspects of personalization, others expressed concerns regarding data privacy, fraud, and confidentiality.

Anahtar Kelimeler

• Women entrepreneurship
• Al-based personalization
• Online purchase intention

Kaynakça

1. Alkaddour, M. (2022). Pazarlamada yapay zeka kullanımı. İşletme ve Girişimcilik Araştırmaları Dergisi, Aralık(1), 48–66.
2. An, G. K., & Ngo, T. T. A. (2025). AI-powered personalized advertising and purchase intention in Vietnam’s digital landscape: The role of trust, relevance, and usefulness. Journal of Open Innovation: Technology, Market, and Complexity, 11(3), 100580. https://doi.org/10.1016/j.joitmc.2025.100580
3. Atalay, Y. & Varol, Ç. (2016). İleri teknoloji sektöründe kadın girişimciliği: Ankara’daki sektörel ve mekânsal farklılaşmalar. Planning, 26(3), 181-192. https://doi.org/10.14744/planlama.2016.51423 Awad, N. F. & Krishnan, M. S. (2006). The personalization privacy paradox: An empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS Quarterly, 30(1), 13–28. https://doi.org/10.2307/25148715
4. Beyari, H. (2024). The effect of AI on pink marketing: The case of women’s purchasing behavior using mobile applications. Frontiers in Artificial Intelligence, 7, 1502580. https://doi.org/10.3389/frai.2024.1502580
5. Bhagat, R., Chauhan, V. & Bhagat, P. (2023). Investigating the impact of artificial intelligence on consumer’s purchase intention in e-retailing. Foresight, 25(2), 249–263. https://doi.org/10.1108/FS-10-2021-0218
6. Bilal, M., Zhang, Y., Cai, S., Akram, U. & Halibas, A. (2024). Artificial intelligence is the magic wand making customer-centric a reality! An investigation into the relationship between consumer purchase intention and consumer engagement through affective attachment. Journal of Retailing and Consumer Services, 77, 103674. https://doi.org/10.1016/j.jretconser.2023.103674
7. Brush, C. G., Carter, N. M., Gatewood, E. J., Greene, P. G. & Hart, M. M. (2006). Chapter 1: Introduction: The Diana Project International. In C. G. Brush, N. M. Carter, E. J. Gatewood, P. G. Greene & M. M. Hart (Der.) Growth‑oriented women entrepreneurs and their businesses: A global research perspective (pp. 1‑17).
8. Cheltenham, UK: Edward Elgar Publishing. https://doi.org/10.4337/9781845429942.00006 Büyüköztürk, Ş., Çakmak Kılıç, E., Akgün, Ö. E., Karadeniz, Ş. & Demirel, F. (2014). Bilimsel araştırma yöntemleri. Ankara: Pegem Akademi.

9. Chellappa, R.K. & Sin, R.G. Personalization versus privacy: An empirical examination of the online consumer’s dilemma. Inf Technol Manage 6, 181–202 (2005). https://doi.org/10.1007/s10799-005-5879-y
10. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
11. Gefen, D., Karahanna, E. & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519
12. Global Entrepreneurship Monitor (GEM). (2021). Women’s entrepreneurship report 2020/21: Thriving through crisis. Global Entrepreneurship Research Association. https://www.gemconsortium.org
13. Global Entrepreneurship Monitor. (2024). Women’s entrepreneurship report 2023/24: Reshaping economies and communities. https://www.gemconsortium.org/report/202324-womens-entrepreneurship-report-reshaping-economies-and-communities-2
14. Hassan, N., Abdelraouf, M. & El-Shihy, D. (2025). The moderating role of personalized recommendations in the trust–satisfaction–loyalty relationship: An empirical study of AI driven e-commerce. Future Business Journal, 11(1), 66. https://doi.org/10.1186/s43093-025- 00476-z Jain, N., Dubey, R. S., Yadav, L. N., Poongodi, G., Kumar, N. & Thavara, S. S. (2025). Artificial intelligence in personalization and its impact on consumer trust: A cross-cultural study of digital purchases. Advances in Consumer Research, 2(4), 1–9. https://acr journal.com/article/artificial-intelligence-in-personalization-and-its-impact-on-consumer trust-a-cross-cultural-study-of-digital-purchases-1533/
15. Konuk, F. A. (2015). The effects of price consciousness and sale proneness on purchase intention towards expiration date-based priced perishable foods. British Food Journal, 117(2), 793–804. https://doi.org/10.1108/BFJ-10-2013-0305
16. Lee, J. M. & Rha, J. Y. (2016). Personalization–privacy paradox and consumer conflict with the use of location-based mobile commerce. Computers in Human Behavior, 63, 453–462. https://doi.org/10.1016/j.chb.2016.05.056
17. Liang, Y., Lee, S.-H. & Workman, J. E. (2020). Implementation of artificial intelligence in fashion: Are consumers ready? Clothing and Textiles Research Journal, 38(1), 3–18. https://doi.org/10.1177/0887302X19873437
18. Moodley, K. & Sookhdeo, L. (2025). The role of artificial intelligence personalisation in e-commerce: Customer purchase decisions in the retail sector. South African Journal of Information Management, 27(1), a1926. https://doi.org/10.4102/sajim.v27i1.1926
19. Nadiger, A. & Venkatesh, S. (2025). Leveraging artificial intelligence for women entrepreneurs in Karnataka: Opportunities and challenges. Jain Journal of Emerging Management (JJEM), Special Issue 4, 52–60. https://doi.org/10.37314/JJEM.SP0452
20. Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). Sage Publications.
21. Putri, V. C. C. & Sonni, A. F. (2025). AI-driven personal branding for female entrepreneurs: The Indonesian hijabi startup ecosystem. Journal of Open Innovation, 11(3), 131. https://doi.org/10.3390/journalmedia6030131
22. Rafieian, O. & Yoganarasimhan, H. (2023). AI and personalization. Artificial intelligence in marketing, 77-102.
23. Schumpeter, J. A. (1934). The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle (R. Opie, Çev.). Cambridge, MA: Harvard University.
24. Shakila, K. & Golden, A. R. S. (2025). Artificial intelligence (AI) personalization on the online shopping experience of professional women: A study on the Down South in India retail industry. International Journal of Accounting and Economics Studies, 12(3), 1–9. https://doi.org/10.14419/abdgyt59
25. Tan, J. (2008). Breaking the “bamboo curtain” and the “glass ceiling”: The experience of women entrepreneurs in high-tech industries in an emerging market. Journal of Business Ethics, 80(3), 547–564. https://doi.org/10.1007/s10551-007-9454-9
26. Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926 Vermeir, I. & Verbeke, W. (2006). Sustainable food consumption: Exploring the consumer “attitude – behavioral intention” gap. Journal of Agricultural and Environmental Ethics, 19(2), 169–194. https://doi.org/10.1007/s10806-005-5485-3
27. Yadav, R. & Pathak, G. S. (2016). Young consumers' intention towards buying green products in a developing nation: Extending the theory of planned behavior. Journal of Cleaner Production, 135, 732–739. https://doi.org/10.1016/j.jclepro.2016.06.120
28. Yaşbay Kobal, H. (2021). Çalışanlarda cam tavan algısı: Hakkâri Üniversitesi örneği. Doğu Anadolu Sosyal Bilimlerde Eğilimler Dergisi, 5(2), 26‑38. https://doi.org/10.31457/dased.977988
29. Yıldırım, A. & Şimşek, H. (2013). Sosyal bilimlerde nitel araştırma yöntemleri. Ankara: Seçkin.
30. Yin, J. & Qiu, X. (2021). AI technology and online purchase intention: Structural equation model based on perceived value. Sustainability, 13(10), 5671. https://doi.org/10.3390/su13105671
31. Yin, J., Qiu, X. & Wang, Y. (2025). The impact of AI-personalized recommendations on clicking intentions: Evidence from Chinese e-commerce. Journal of Theoretical and Applied Electronic Commerce Research, 20(1), 21. https://doi.org/10.3390/jtaer20010021