Correlation of Relatedness and Complexity with Patent Applications: A Regional Analysis from Türkiye

Yıl 2023, Cilt: 57 Sayı: 1, 73 - 84, 31.01.2023

Sedef Akgüngör , Mert Abay

https://doi.org/10.51551/verimlilik.1060389

Cited By: 1

Öz

Purpose: The aim of this paper is to test the hypothesis that regional innovativeness is positively correlated with the two main building variables of smart specialization: relatedness density (a region’s potential to develop new technologies compatible with existing capabilities) and knowledge complexity (a region’s potential to develop unique and hard-to-imitate technologies).

Methodology: Analysis are made over a panel regression model, using data from OECD-REGPAT database for the years 1978–2017 covering Türkiye’s NUTS-3 regions. The dependent variable is innovativeness, and the independent variables are the average relatedness density and knowledge complexity indices for each region. Per capita income, number of universities, number of technoparks, Turkish Patent Institute, Türkiye-EU Customs Union agreement, and lagged value of the dependent variable are the control variables.

Findings: The results confirm that innovativeness and a region’s potential to develop new technologies that are compatible with existing technological portfolios (relatedness density) are correlated, while the variable that measures a region’s potential to develop unique technologies (knowledge complexity) is not statistically significant.

Originality: The originality of this work is that we demonstrate relatedness to be one of the building blocks of smart specialization as correlated with regional innovativeness; complexity, the other building block, is not correlated. 

Anahtar Kelimeler

Relatedness, Complexity, Smart Specialization, Regional Innovativeness

İlişkililik ve Karmaşıklık ile Patent Başvuruları Arasındaki Korelasyon: Türkiye için Bölgesel Bir Analiz

Öz

Amaç: Çalışmanın amacı, bölgesel yenilikçiliğin akıllı uzmanlaşmanın iki temel boyutu ile arasında pozitif bir korelasyon olduğu hipotezini test etmektir. Akıllı uzmanlaşmanın iki temel boyutu, ilişkililik yoğunluğu (bölgenin mevcut yeteneklerine uygun yeni teknolojileri kendine çekebilme potansiyeli) ve bilgi karmaşıklığıdır (bölgenin benzersiz ve taklit edilmesi güç teknolojileri yaratma potansiyeli).

Yöntem: Analizler panel regresyon modeli kullanılarak yapılmıştır. Çalışmanın verilerini Türkiye'nin İBB-3 düzey bölgeleri için 1978–2017 yılları kapsamında OECD-REGPAT veri tabanı oluşturmaktadır. Bağımlı değişken yenilikçilik ve bağımsız değişkenler bölgenin ilişkililik yoğunluğu ve bilgi karmaşıklığı indeksleridir. Kontrol değişkenleri olarak kişi başına gelir, üniversite sayısı, iki kukla değişken (Türk Patent Enstitüsü ile Türkiye-AB Gümrük Birliği anlaşması) ve bağımlı değişkenin gecikmeli değeri kullanılmıştır.

Bulgular: Sonuçlar, bölgesel yenilikçilik ile bölgenin mevcut teknoloji portföyü ile uyumlu yeni teknolojileri çekme potansiyeli arasında anlamlı bir ilişki olduğunu ortaya koymakta, ancak bölgenin benzersiz olma potansiyeli ile istatistiksel olarak bir bağlantı olmadığını doğrulamaktadır.

Özgünlük: Makalenin özgünlüğü, akıllı uzmanlaşmanın iki temel bileşeninden biri olan ilişkililik boyutunun bölgesel yenilikler ile bağlantılı olduğunu, diğer bileşeni olan karmaşıklık boyutunun ise yenilikler üzerinde bir etkisinin olmadığını göstermesidir. 

Anahtar Kelimeler

İlişkililik, Karmaşıklık, Akıllı Uzmanlaşma, Türkiye, Bölgesel Yenilikçilik

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