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Capsule Networks and Innovation Performance in Resource-Based Firms
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Author(s): Fangjing Ma (Economics and Management College, Liaoning University of Technology, China & SolBridge International School of Business, Woosong University, South Korea)and Shizhe Sun (China Securities Co., Ltd., China)
Copyright: 2025
Volume: 19
Issue: 1
Pages: 22
Source title:
International Journal of Cognitive Informatics and Natural Intelligence (IJCINI)
Editor(s)-in-Chief: Kangshun Li (South China Agricultural University, China)
DOI: 10.4018/IJCINI.370965
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Abstract
Resource-based enterprises face increasing pressure to address resource challenges amid global issues. This paper explores how digital transformation can enhance their sustainability, economic efficiency, and innovation performance. The authors propose a model combining a capsule network (CapsNet) with adaptive stochastic gradient descent optimization (ASGDO) to analyze the impact of digital transformation. The study involves data collection, preprocessing, and the development of an optimized CapsNet enhanced by ASGDO for performance prediction. The results, compared with existing methods, show that the proposed model achieves 95.5% accuracy, demonstrating its potential to significantly improve the performance of resource-based enterprises.
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