Logistics 4.0: Analysis of the Impact of Countries' Digitalization and Innovation Levels on Logistics Performance with Machine Learning

Bünyamin Çelebi; Burcu Yengil Bülbül; Maide Betül Aksoy; Mehmet Fatih Sert

Makale detayları

Logistics 4.0: Analysis of the Impact of Countries' Digitalization and Innovation Levels on Logistics Performance with Machine Learning

Yazarlar:

Bünyamin Çelebi | Burcu Yengil Bülbül | Maide Betül Aksoy | Mehmet Fatih Sert

Yayıncı:

Ataturk University

Ana Başlıklar:

Yapay Zeka (Diğer) | Lojistik

Dergi:

Trends in Business and Economics Vol.39 Issue 4, pp.571-583

Belge Tipi:

Makale

Yayın Tarihi:

10/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360145

pISSN:

2822-2652

Anahtar kelimeler:

Özet:

 The widespread adoption of globalization and e-commerce has increased the strategic importance of logistics processes, leading to the emergence of the concept of Logistics 4.0 through the integration of Industry 4.0 technologies into the logistics sector. This situation necessitates the strengthening of logistics infrastructures by firms and countries to achieve competitive advantage. In this context, fully determining the impact of digitalization and innovation on logistics performance is of critical importance for policy-making and serves as the starting point of this study. In this study, a machine learning method, the random forest technique, is employed to assess the impact of countries digitalization and innovation levels on logistics performance and to rank the variables influencing the Logistics Performance Index LPI based on their significance. According to the studys findings, research and development RD expenditures, the number of patents, the level of global innovation, high-tech exports, internet usage rate, and e-government development servicesconsidered as indicators of digitalization and innovationexplain a significant portion of the variation in LPI. Among these factors, RD has been identified as the most critical variable. RD activities directly influence a countrys logistics performance by fostering innovation and technological progress. In this regard, investments in RD significantly contribute to strengthening logistics infrastructure, improving processes, and enhancing the efficiency of technologies.

 The widespread adoption of globalization and e-commerce has increased the strategic importance of logistics processes, leading to the emergence of the concept of Logistics 4.0 through the integration of Industry 4.0 technologies into the logistics sector. This situation necessitates the strengthening of logistics infrastructures by firms and countries to achieve competitive advantage. In this context, fully determining the impact of digitalization and innovation on logistics performance is of critical importance for policy-making and serves as the starting point of this study. In this study, a machine learning method, the random forest technique, is employed to assess the impact of countries digitalization and innovation levels on logistics performance and to rank the variables influencing the Logistics Performance Index LPI based on their significance. According to the studys findings, research and development RD expenditures, the number of patents, the level of global innovation, high-tech exports, internet usage rate, and e-government development servicesconsidered as indicators of digitalization and innovationexplain a significant portion of the variation in LPI. Among these factors, RD has been identified as the most critical variable. RD activities directly influence a countrys logistics performance by fostering innovation and technological progress. In this regard, investments in RD significantly contribute to strengthening logistics infrastructure, improving processes, and enhancing the efficiency of technologies.

 The widespread adoption of globalization and e-commerce has increased the strategic importance of logistics processes, leading to the emergence of the concept of Logistics 4.0 through the integration of Industry 4.0 technologies into the logistics sector. This situation necessitates the strengthening of logistics infrastructures by firms and countries to achieve competitive advantage. In this context, fully determining the impact of digitalization and innovation on logistics performance is of critical importance for policy-making and serves as the starting point of this study. In this study, a machine learning method, the random forest technique, is employed to assess the impact of countries digitalization and innovation levels on logistics performance and to rank the variables influencing the Logistics Performance Index LPI based on their significance. According to the studys findings, research and development RD expenditures, the number of patents, the level of global innovation, high-tech exports, internet usage rate, and e-government development servicesconsidered as indicators of digitalization and innovationexplain a significant portion of the variation in LPI. Among these factors, RD has been identified as the most critical variable. RD activities directly influence a countrys logistics performance by fostering innovation and technological progress. In this regard, investments in RD significantly contribute to strengthening logistics infrastructure, improving processes, and enhancing the efficiency of technologies.

 Küreselleşme ve e-ticaretin yaygınlaşması, lojistik süreçlerin stratejik önemini artırmış ve Endüstri 4.0 teknolojilerinin lojistik sektörüne entegrasyonuyla Lojistik 4.0 kavramı ortaya çıkmıştır. Bu durum, firmaların ve ülkelerin rekabet üstünlüğü sağlamak adına lojistik altyapılarını güçlendirmelerini gerektirmektedir. Bu kapsamda dijitalleşme ve inovasyonun lojistik performans üzerindeki etkisinin tam anlamıyla belirlenmesi, izlenecek politikalar açısından kritik öneme sahiptir ve söz konusu durum çalışmanın çıkış noktasını oluşturmaktadır. Yapılan çalışmada bir makine öğrenmesi yöntemi olan rastgele orman tekniği kullanılarak ülkelerin dijitalleşme ve inovasyon seviyelerinin lojistik performans üzerindeki etkisinin belirlenmesi ve Lojistik Performans Endeksini LPI etkileyen değişkenlerin önem derecesine göre sıralanması amaçlanmıştır. Çalışmanın bulgularına göre, modelde dijitalleşme ve inovasyonun göstergesi olarak ele alınan araştırma-geliştirme harcamaları, patent sayısı, küresel inovasyon düzeyi, yüksek teknoloji ihracatı, internet kullanım oranı ve e-devlet geliştirme hizmetleri, LPIdeki değişimin büyük bir kısmını açıklamaktadır. Bununla birlikte Ar-Ge faktörü, en önemli değişken olarak tespit edilmiştir. Ar-Ge faaliyetleri, inovasyonu ve teknolojik ilerlemeyi teşvik ederek bir ülkenin lojistik performansını doğrudan etkileyebilir. Bu doğrultuda, Ar-Geye yapılan yatırımlar, lojistik altyapının güçlendirilmesine, süreçlerin iyileştirilmesine ve teknolojilerin daha verimli hale getirilmesine katkılar sağlamaktadır.

Makale detayları

Logistics 4.0: Analysis of the Impact of Countries' Digitalization and Innovation Levels on Logistics Performance with Machine Learning

Yazarlar:

Bünyamin Çelebi | Burcu Yengil Bülbül | Maide Betül Aksoy | Mehmet Fatih Sert

Yayıncı:

Ataturk University

Ana Başlıklar:

Yapay Zeka (Diğer) | Lojistik

Dergi:

Trends in Business and Economics Vol.39 Issue 4, pp.571-583

Belge Tipi:

Makale

Yayın Tarihi:

10/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360145

pISSN:

2822-2652

Digitalization

Innovation

Logistics 4.0

LPI

Machine LearningDijitalleşme

İnovasyon

Lojistik 4.0

LPI

Makine Öğrenmesi

Sayı

Makale detayları

Yazarlar: Bünyamin Çelebi | Burcu Yengil Bülbül | Maide Betül Aksoy | Mehmet Fatih Sert

Yayıncı: Ataturk University

Ana Başlıklar: Yapay Zeka (Diğer) | Lojistik

Dergi: Trends in Business and Economics Vol.39 Issue 4, pp.571-583

Belge Tipi: Makale

Yayın Tarihi: 10/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001360145

pISSN: 2822-2652

Sayı

Yazarlar:

Bünyamin Çelebi | Burcu Yengil Bülbül | Maide Betül Aksoy | Mehmet Fatih Sert

Yayıncı:

Ataturk University

Ana Başlıklar:

Yapay Zeka (Diğer) | Lojistik

Dergi:

Trends in Business and Economics Vol.39 Issue 4, pp.571-583

Belge Tipi:

Makale

Yayın Tarihi:

10/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360145

pISSN:

2822-2652