NETWORK MAPPING OF AI-DRIVEN INNOVATION STUDIES: A CONCEPTUAL BIBLIOMETRIC COUPLING REVIEW

Abstract

Purpose: The aim of this study is investigate the subareas, the research trends and the conceptual structure artificial intelligence studies in innovation researches. The paper will first introduce a coherent framework based on the prevalent state of knowledge in the area and will then help in a stepwise development of future research. Methodology: This study has citation and bibliometric coupling analysis. The dataset was collected by scanning papers containing the phrases "innovation" and "artificial intelligence" in their titles, abstracts or keywords together with their accompanying ratings of 3, 4, 4* in the Association of Business Schools Journal List (ABS Journal List) in the Web of Science database. The research has 908 papers were published until September 2025. Findings: The study shows the field is divided into four clusters. These clusters include dynamic capabilities theory and digital transformation, value creation processes, product-service transformation and business model development and the dynamics of AI adoption and organizational transformation. Practical Implications: total number of articles in this article research area increased dramatically after 2020. They were divided into more subtopics. In order to populate the interdisciplinary knowledge stream involved, it is a must to collect data in different ways from the databases by the use of variety of key phrases. Also applying varied analytical methods is going to assist in determining the current status of the field from diverse insights. Originality: This work represents a pioneering effort among the few bibliometric studies that particularly focus on the AI innovation literature in the realm of high impact business journals. The resulting cluster structure is indeed a valuable tool for researchers as it gives quantitative indicators to gaps and emerging themes in the field.

Keywords

• Innovation
• Artificial Intelligence
• Bibliometric Analysis
• Bibliometric Coupling Analysis
• Business Studies.

YAPAY ZEKÂ ODAKLI İNOVASYON ÇALIŞMALARININ AĞ HARİTALANDIRMASI: KAVRAMSAL BİBLİYOMETRİK EŞLEME İNCELEMESİ

Abstract

Amaç: Bu çalışmanın temel amacı, inovasyon literatüründe yapay zekâ (YZ) temasını ele alan akademik çalışmaların kavramsal yapısını, araştırma eğilimlerini ve entelektüel iş birliklerini ortaya koymaktır. Böylece söz konusu alandaki bilgi birikiminin mevcut durumuna ilişkin bütüncül bir çerçeve sunularak gelecekteki araştırmalara yön gösterilmesi hedeflenmektedir. Yöntem: Çalışmada Bibliyometrik analiz yöntemlerinden atıf analizi ve bibliyometrik eşleme yöntemleri beraber kullanılmıştır. Veri seti, Web of Science veritabanında İşletme Okulları Derneği (ABS) dergi listesinde 4*, 4 ve 3 puanına sahip dergilerde yayımlanmış başlık, özet veya anahtar kelimelerinde hem “innovation” hem de “artificial intelligence” kavramlarını içeren makalelerin taranmasıyla elde edilmiştir. Araştırma 2025 Kasım ayına kadar olan tüm dönemi kapsamış ve toplam 908 özgün makale analiz edilmiştir. Bulgular: Yapılan analizde alanın dört ana kümede toplandığını göstermektedir. Bu kümeler dinamik yetkinlikler ve dijital dönüşüm, değer yaratma süreçleri, ürün-hizmet dönüşümü ve iş modeli gelişimi ve son olarak yapay zekâ benimseme dinamikleri ve kurumsal dönüşümdür. Sonuç ve Öneriler: Alandaki çalışmalar 2020 yılı sonrasında hızla artarak ve farklı alt başlıklara ayrılmıştır. Gün geçtikçe disiplinler arası önem kazanan bu alandaki oluşan akademik bilgi dağarcığını arttırmak için farklı veri tabanlarında, farklı anahtar cümleler veri toplanması gerekmektedir. Ayrıca farklı analiz yöntemleri alandaki bilgi birikimini farklı açılardan değerlendirmeye katkı sağlayacaktır. Özgünlük/Değer: Bu çalışma, inovasyon alanındaki YZ odaklı literatürü yüksek etki faktörlü işletme dergileri çerçevesinde sistematik biçimde haritalayan ilk bibliyometrik incelemelerden biridir. Elde edilen kümelenme yapısı, araştırmacılara alandaki teorik boşlukları ve yükselen temaları nicel göstergelerle sunarak özgün katkı sağlamaktadır.

Keywords

• İnovasyon
• Yapay Zeka
• Bibliyometrik Analiz
• Bibliyometrik Eşleme Analizi

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