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- Title
IS IT POSSIBLE TO APPLY A DEEP LEARNING ALGORITHM TO INNOVATION MANAGEMENT RESEARCH?
- Authors
ÖZTÜRK, Cemal; İNCEKARA, Mustafa; TOKAT, Sezai
- Abstract
This paper aims to apply a deep learning algorithm to estimate the prediction of various external financial input variables on the adoption of eco-innovation practices such as renewable energy operations by 5456 SMEs. A Long Short-Term Memory Units (LSTM) is utilized to the data set to assess the performance of different input variables on the adoption of renewable energy. Furthermore, we process the dataset with different machine learning algorithms and compare the results. The findings indicate that LSTM gives the highest performance for all metrics. As a result, some essential theoretical implications for management scholars are given.
- Subjects
MACHINE learning; DEEP learning; INNOVATION management; RENEWABLE energy sources; ARTIFICIAL intelligence
- Publication
Pamukkale University Journal of Social Sciences Institute / Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 2023, Vol 56, p217
- ISSN
1308-2922
- Publication type
Article
- DOI
10.30794/pausbed.1127776