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GELENEKSEL PAZARLAMANIN ÖTESİNDE TÜKETİCİ DAVRANIŞLARI: YAPAY ZEKÂ VE NÖROPAZARLAMAYA YÖNELİK SİSTEMATİK BİR LİTERATÜR İNCELEMESİ

BEYOND TRADITIONAL MARKETING: A SYSTEMATIC LITERATURE REVIEW OF AI AND NEUROMARKETING IN CONSUMER BEHAVIOR

Ezgi Delen(İZMİR BAKIRÇAY ÜNİVERSİTESİ)0000-0003-1434-7913
Abdulkadir Hızıroğlu(İZMİR BAKIRÇAY ÜNİVERSİTESİ)0000-0003-4582-3732
Sayfa
102–125
Yayın Tarihi
2026-06-29
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Bulgular, 2018 sonrası yayınlarda belirgin bir artış olduğunu ve 2024 yılında %32,56 ile zirveye ulaşıldığını göstermektedir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Bu çalışma, tüketici davranışları araştırmalarında yapay zekâ ile nöropazarlamanın entegrasyonunu incelemektedir.
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Temel Bulgular & Veri:Bu amaç doğrultusunda, 2015–2024 yılları arasında yayımlanmış, Scopus veri tabanından belirlenen anahtar kelimelerle erişilen 43 hakemli makale, PRISMA (Sistematik Derlemeler ve Meta-Analizler için Tercih Edilen Raporlama Maddeleri) ilkeleri doğrultusunda yürütülen sistematik literatür taraması yöntemiyle analiz edilmiştir.
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Sonuç & Katkı:Bulgular, 2018 sonrası yayınlarda belirgin bir artış olduğunu ve 2024 yılında %32,56 ile zirveye ulaşıldığını göstermektedir.
🔬Tür:Literatür & Derleme Çalışması
📍Kapsam:2015–2024 Verileri
⚙️Değişkenler:Nöropazarlama · Yapay Zeka · Tüketici Davranışı

Özet

Bu çalışma, tüketici davranışları araştırmalarında yapay zekâ ile nöropazarlamanın entegrasyonunu incelemektedir. YZ temelli analiz teknikleri ile nöropazarlama yöntemlerinin bir araya getirilmesi yoluyla pazarlama doğruluğunun artırılması ve tüketici karar süreçlerinin daha derinlemesine anlaşılması amaçlanmıştır. Bu amaç doğrultusunda, 2015–2024 yılları arasında yayımlanmış, Scopus veri tabanından belirlenen anahtar kelimelerle erişilen 43 hakemli makale, PRISMA (Sistematik Derlemeler ve Meta-Analizler için Tercih Edilen Raporlama Maddeleri) ilkeleri doğrultusunda yürütülen sistematik literatür taraması yöntemiyle analiz edilmiştir. Çalışmada dört ana boyuta odaklanan bir içerik analizi gerçekleştirilmiştir: tematik alanlar, teorik temeller, araştırma desenleri ve yöntemsel yaklaşımlar. Bulgular, 2018 sonrası yayınlarda belirgin bir artış olduğunu ve 2024 yılında %32,56 ile zirveye ulaşıldığını göstermektedir. İncelenen çalışmalar üç ana tema altında toplanmıştır: nöropazarlama tekniklerinin tüketici davranışlarına etkisi (%44,2), yapay zeka uygulamalarının pazarlama ve müşteri etkileşimindeki rolü (%27,9) ve yapay zeka temelli araştırmalarda etik kaygılar (%27,9). Psikolojik ve bilişsel teorilerin sıklıkla tercih edildiği, veri kaynaklarında ise çoğunlukla birincil verilerin kullanıldığı görülmüştür. EEG, makine öğrenmesi ve duygu analizi gibi ileri tekniklerin artan kullanımı, yöntemsel bir dönüşüme işaret etmektedir. Bu çalışma, yapay zekanın nöropazarlamaya katkısını haritalayarak alandaki boşluğu doldurmakta ve gelecekteki araştırmalar için yapısal bir çerçeve sunmaktadır.

Abstract

This study explores the integration of artificial intelligence (AI) and neuromarketing in consumer behavior research. By combining AI-driven analytics with neuromarketing techniques, it aims to improve marketing precision and deepen understanding of consumer decision-making. A systematic literature review was conducted, in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, analyzing 43 peer-reviewed articles published between 2015 and 2024, following a defined elimination process. Articles were retrieved from Scopus using predefined keywords. The content analysis focused on four dimensions: thematic areas and research topics, theoretical foundations, research design, and methodological patterns. The findings reveal a marked increase in publications after 2018, with a notable peak in 2024 at 32.56%. Three dominant themes were identified: neuromarketing techniques in consumer behavior (44.2%), AI applications in marketing and engagement (27.9%), and ethical concerns in AI-driven research (27.9%). While psychological and cognitive theories are frequently used, most studies rely on primary data. The growing use of EEG, machine learning, and sentiment analysis signals a methodological shift. This review addresses a gap in the literature by mapping the contribution of AI to neuromarketing. It provides a structured agenda for future research, illustrating how AI can enhance traditional methods and generate new insights into consumer behavior.

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Bu Makaleye Atıf Yap

Delen, E., Hızıroğlu, A. (2026). GELENEKSEL PAZARLAMANIN ÖTESİNDE TÜKETİCİ DAVRANIŞLARI: YAPAY ZEKÂ VE NÖROPAZARLAMAYA YÖNELİK SİSTEMATİK BİR LİTERATÜR İNCELEMESİ. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, Cilt: 27 Sayı: 1, 102–125. https://doi.org/10.24889/ifede.1809547

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