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Journals / Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2026 / Cilt: 28 Sayı: Özel Sayı Özel Sayı

Benchmarking enterprise digital transformation and AI readiness across EU-27 and selected European countries using recent MCDM methods

AB-27 ve seçili Avrupa ülkelerinde işletmelerin dijital dönüşüm ve yapay zekâ hazırlığının güncel ÇKKV yöntemleri kullanılarak karşılaştırmalı değerlendirilmesi

Nilsen Kundakcı(PAMUKKALE ÜNİVERSİTESİ)0000-0002-7283-320X
Ali Katrancı(PAMUKKALE ÜNİVERSİTESİ)0000-0002-7586-1169
Kevser Arman Tunçer(PAMUKKALE ÜNİVERSİTESİ)0000-0002-4400-5976
Pages
116–134
Publication Date
2026-10-21
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings reveal that use of AI has the highest discriminatory effect among the criteria, and AI use is an important dimension of digital readiness.

📌 3 Key Takeaways

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Objective & Hypothesis:This study evaluates digital transformation and artificial intelligence (AI) readiness among the European Union-27 (EU-27) and selected European countries using an integrated multi-criteria decision-making approach.
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Key Findings & Data:In this evaluation process, seven criteria are considered as enterprises using AI technologies, purchasing cloud computing services, performing data analytics, using ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), and BI (Business Intelligence) software, using social media, having a fixed internet connection with a speed above 1 Gb/s, and having a website or functionalities.
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Conclusion & Impact:The findings reveal that use of AI has the highest discriminatory effect among the criteria, and AI use is an important dimension of digital readiness.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Dijital Dönüşüm · Çok Kriterli Karar Verme (ÇKKV) · MEREC

Abstract

This study evaluates digital transformation and artificial intelligence (AI) readiness among the European Union-27 (EU-27) and selected European countries using an integrated multi-criteria decision-making approach. In this evaluation process, seven criteria are considered as enterprises using AI technologies, purchasing cloud computing services, performing data analytics, using ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), and BI (Business Intelligence) software, using social media, having a fixed internet connection with a speed above 1 Gb/s, and having a website or functionalities. These seven criteria were selected because they collectively represent the key dimensions of enterprise-level digital maturity. The MEREC (Method Based on the Removal Effects of Criteria) method is proposed to determine objective criteria weights and SPOTIS (Stable Preference Ordering towards Ideal Solution) method is used to rank the countries. The findings reveal that use of AI has the highest discriminatory effect among the criteria, and AI use is an important dimension of digital readiness. According to the ranking results obtained with the SPOTIS method, Denmark, Finland, the Netherlands, Belgium and Sweden are the leading countries in digital transformation performance. The proposed integrated multi-criteria decision-making (MCDM) approach provides a transparent and repeatable framework for benchmarking digital transformation and AI readiness levels by identifying areas requiring policy intervention.

Özet

Bu çalışma, AB-27 (Avrupa Birliği-27) ve seçili Avrupa ülkelerinde işletmelerin dijital dönüşüm ve yapay zekâ hazırlık düzeylerini bütünleşik ÇKKV (Çok Kriterli Karar Verme) yaklaşımıyla değerlendirmektedir. Bu kapsamda, “yapay zekâ teknolojilerini kullanma, bulut bilişim hizmeti satın alma, veri analitiği yapma, ERP (Kurumsal Kaynak Planlama), CRM (Müşteri İlişkileri Yönetimi) veya BI (iş zekâsı) yazılımı kullanma, sosyal medya kullanımı, 1 Gb/s üzeri sabit internet bağlantısına sahip olma ve web sitesi ya da web fonksiyonlarına sahip olma” olmak üzere yedi kriter dikkate alınmıştır. Analizde, yedi kriter işletme düzeyindeki dijital olgunluğun temel boyutlarını birlikte temsil etmeleri nedeniyle seçilmiştir. Kriter ağırlıkları, kriterlerin kaldırılma etkilerine dayalı objektif bir ağırlıklandırma yöntemi olan MEREC (Kriterlerin Kaldırılma Etkilerine Dayalı Yöntem) ile belirlenmiş; ülkelerin sıralanmasında ise SPOTIS (İdeal Çözüme Doğru Kararlı Tercih Sıralaması) yöntemi kullanılmıştır. Bulgular, yapay zekâ teknolojilerinin kullanımının en yüksek ayırt edici etkiye sahip kriter olduğunu göstermektedir. SPOTIS sonuçlarına göre Danimarka, Finlandiya, Hollanda, Belçika ve İsveç dijital dönüşüm performansı açısından öne çıkan ülkeler arasındadır. Önerilen MEREC-SPOTIS modeli, ülkeler arası dijital hazırlık düzeyinin karşılaştırılmasında şeffaf ve tekrarlanabilir bir değerlendirme çerçevesi sunmaktadır.

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Cite This Article

Kundakcı, N., Katrancı, A., Tunçer, K. A. (2026). Benchmarking enterprise digital transformation and AI readiness across EU-27 and selected European countries using recent MCDM methods. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt: 28 Sayı: Özel Sayı Özel Sayı, 116–134. https://doi.org/10.33707/akuiibfd.1968066

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