Capsule Networks and Innovation Performance in Resource-Based Firms

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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Publication Details

Journal
International Journal of Cognitive Informatics and Natural Intelligence
Published
2025-03-08
DOI
https://doi.org/10.4018/ijcini.370965
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Capsule Networks and Innovation Performance in Resource-Based Firms

Fangjing Ma, Shuwei Sun
International Journal of Cognitive Informatics and Natural Intelligence
Innovation and Knowledge Management
article

Capsule Networks and Innovation Performance in Resource-Based Firms

Fangjing Ma, Shuwei Sun
article en

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.

International Journal of Cognitive Informatics and Natural IntelligenceVol. 19(1)
Liaoning University of Technology (CN), China Institute of Finance and Capital Markets (CN), Woosong University (KR)
Openalex Percentile: Top 94%
Innovation and Knowledge Management
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