1. GİRİŞİMCİLİĞİN İLLERE GÖRE DAĞILIMI: BULANIK K ORTALAMALAR VE SOM KÜMELEME YÖNTEMLERİ.
- Author
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IŞIK, Kasım Can and POLATGİL, Mesut
- Subjects
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ARTIFICIAL neural networks , *NET worth , *INFORMATION storage & retrieval systems ,DEVELOPING countries - Abstract
Due to constantly changing market conditions and developing technology; The importance of entrepreneurial activity is increasing, especially in developing countries such as Turkey. Likewise, the clustering of entrepreneurial activities according to the places with the same features is becoming more and more important. Because the number of these clusters is less than the provinces, development regions and geographical regions. But because of the common features they have, these clusters; It is an important data source both in promoting / supporting entrepreneurship activities and in identifying / resolving problems that arise in entrepreneurship activities. There are no studies in the literature that cluster all cities according to their entrepreneurial characteristics, with this study, it is aimed to close this gap in the literature. Turkey Ministry of Industry and Technology / Entrepreneur Information System (GBS) located in the “Number of enterprises by cities, net sales and assets” were used as data in the study. Fuzzy k means and SOM ANN (Artificial Neural Networks) methods, one of the clustering methods, have been applied to the published data of 2017 in the GBS database. and Turkey’s entrepreneurship is mapped. According to the fuzzy k means method, 19 cities were collected in 3 different clusters and 62 cities were collected in a single cluster. According to SOM clustering method, 8 cities were collected in 4 different clusters and 73 cities were collected in a single cluster. Finally, remarkable findings have been explained and the similarities / differences between the results of the 2 methods have been interpreted. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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