Search Results - subject:"Deep learning"

Collecting and analyzing user-generated content for decision support in marketing management: An overview of methods and use cases

Baier, Daniel; Decker, Reinhold; Asenova, Yana - In: Schmalenbach Journal of Business Research (SBUR) 77 (2025) 3, pp. 419-455

. Traditional data analysis and machine learning based on feature extraction methods as well as discriminative and generative deep … learning methods are discussed. Selected use cases across various marketing management decision areas (such as customer …

Persistent link: https://www.econbiz.de/10015546705

Collecting and analyzing user-generated content for decision support in marketing management : an overview of methods and use cases

Baier, Daniel; Decker, Reinhold; Asenova, Yana - In: Schmalenbach journal of business research : SBUR 77 (2025) 3, pp. 419-455

Persistent link: https://www.econbiz.de/10015543129

Beyond sentiment analysis of online customer reviews: an approach to automated measurement of technology acceptance from online customer reviews

Karasenko, Andreas; Baier, Daniel - In: Journal of Business Economics 95 (2025) 7, pp. 917-955

Recent developments in machine learning (ML), especially transformer-based discriminative and generative deep learning …

Persistent link: https://www.econbiz.de/10015564121

Deep speech embeddings of earning calls predict future stock returns

Goeij, Peter de; Liu, Zihao; Postma, Eric - 2025

Persistent link: https://www.econbiz.de/10015417094

Large (and deep) factor models

Kelly, Bryan T.; Kuznetsov, Boris; Malamud, Semyon; Xu, … - 2024

Persistent link: https://www.econbiz.de/10014483267

Transformers and tradition : using generative AI and Deep Learning for financial markets prediction

Wade, Toby J. - 2024

Persistent link: https://www.econbiz.de/10015190353

Credit risk assessment with stacked machine learning

Columba, Francesco; Cugliari, Manuel; Di Virgilio, Stefano - 2026

Persistent link: https://www.econbiz.de/10015562268

Merger and acquisition prediction based on deep learning with attention mechanism

Wan, Liangyong; Zheng, Yongjia; Xu, Xiaoying; Wang, Rui - In: China journal of accounting research : CJAR 19 (2026) 1, pp. 1-20

mergers and acquisitions (M&A). The model extends existing deep learning frameworks by incorporating M&A-specific features … forecasting M&A outcomes, achieving a 29.2% improvement in predictive accuracy over conventional deep learning methods. This study …

Persistent link: https://www.econbiz.de/10015596393

Identifying weak signals in the labor market : a machine learning approach for strategic policymaking

Kanzola, Anna-Maria; Papaioannou, Konstantina; … - In: Journal of innovation & knowledge : JIK 11 (2026), pp. 1-9

This study introduces a novel machine learning-based methodology for detecting and forecasting the strength of weak signals in the labor market, using Greece as a case study and utilizing Eurostat time series data (2000-2023). Weak signals, conceptualized as subtle anomalies within otherwise...

Persistent link: https://www.econbiz.de/10015607728

An overview of short-term wind power forecasting : multi-scale decomposition and multi-model deep learning fusion

Mei, Yan; Che, Jinxing; Sun, Qian; Dong, Wei - In: Energy strategy reviews 63 (2026), pp. 1-18

methodologies have evolved from traditional statistical models to deep learning architectures. A dominant paradigm in the field has …

Persistent link: https://www.econbiz.de/10015605194