EFFICIENCY MEASUREMENT OF ARTIFICIAL INTELLIGENCE: A RESEARCH ON COMPANIES IN TÜRKİYE

Yıl 2025, Sayı: 32, 1 - 9, 16.02.2025

Yusuf Ersoy , Ali Tehci , Fuad Selamzade

https://doi.org/10.58348/denetisim.1520416

Öz

The use of technology is increasing due to Industry 4.0. Both countries and organizations have had to invest in the field of artificial intelligence (AI) to compete with their rivals in global competitive conditions and to adapt to the ever-changing world. An organization or a country needs to evaluate its performance to ensure its sustainability constantly. The Data Envelopment Analysis (DEA) method is widely used in performance evaluation. This study aimed to evaluate Türkiye AI performance for the nine years between 2014 and 2022. In the research, years were included in the analysis as the decision-making unit. Two input and two output variables were used in the analyses. The study was carried out by using the input-oriented CCR DEA model and its super-efficiency model. According to the results of the analysis, efficient/inefficient decision-making units were determined. Several potential improvement suggestions have been put forward for inefficient decision-making units.

Anahtar Kelimeler

Industry 4.0, Performance, Efficiency, DEA, Artificial Intelligence

YAPAY ZEKÂ ETKİNLİK ÖLÇÜMÜ: TÜRKİYE’DE ŞİRKETLER ÜZERİNE BİR ARAŞTIRMA

Öz

Endüstri 4.0’a bağlı olarak teknoloji kullanımı her geçen gün artmaktadır. Gerek ülkeler gerekse organizasyonlar küresel rekabet koşullarında rakipleriyle mücadele edebilmek ve sürekli değişen dünyaya uyum sağlayabilmek için yapay zekâ alanına yatırımlar yapmak zorunda kalmıştır. Bir organizasyonun veya ülkenin sürdürülebilirliğini sağlayabilmesi için performansını değerlendirmesi oldukça önemlidir. Veri Zarflama Analizi (VZA) yöntemi performans değerlendirmesinde yaygın bir şekilde kullanılmaktadır. Bu çalışmada Türkiye’nin 2014-2022 yılları arasındaki dokuz yıl için yapay zekâ performansının değerlendirmesi amaçlanmıştır. Araştırmada, karar verme birimi olarak yıllar analize dâhil edilmiştir. Analizlerde iki girdi ve iki çıktı değişkeni kullanılmıştır. Çalışma girdi odaklı CCR VZA ve süper etkinlik modeli kullanılarak gerçekleştirilmiştir. Analiz sonuçlarına göre etkin olan/olmayan karar verme birimleri belirlenmiştir. Etkin olmayan karar verme birimleri için potansiyel iyileştirme önerileri sunulmuştur.

Anahtar Kelimeler

Endüstri 4.0, Performans, Etkinlik, VZA, Yapay Zeka

Kaynakça

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