Abstract
This paper aims to apply a deep learning algorithm to estimate the prediction of various external financial input variables on adopting eco-innovation practices such as renewable energy operations of 5456 SMEs. A Long Short-Term Memory Units (LSTM) is applied to the data set to evaluate 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 important theoretical implications for management scholars are given.
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