Natural Language Processing and Large-Scale Semantic Data Mining for Business Performance and Strategic Decision-Making

Dear Colleagues,

The rapid expansion of digital information has generated unprecedented opportunities to understand how firms create, communicate and sustain competitive advantage through data-driven insights. Advances in Natural Language Processing (NLP), artificial intelligence (AI) and semantic data mining enable researchers and practitioners to extract meaningful patterns from unstructured data, including corporate disclosures, patents, news and social media. These approaches are reshaping how we evaluate determinants of organizational performance, innovation capacity and sustainability strategies. 

This Special Issue aims to showcase cutting-edge research in Big Data analytics, natural language processing (NLP), artificial intelligence (AI) and semantic network analysis, with a focus on leveraging large-scale text data to enhance firm performance, strategic decision-making and market intelligence. We welcome both theoretical and empirical contributions exploring how semantic and linguistic data analysis can provide new perspectives on:

• corporate strategy and performance evaluation;
• innovation and technological trajectories;
• ESG and sustainability reporting;
• financial and risk forecasting;
• organizational learning and knowledge management.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• Advanced NLP and semantic mining techniques applied to business and management research;

• Large-scale text analytics for evaluating firm performance and competitive dynamics;
• Semantic network construction and network-based approaches to corporate data;
• Brand or reputation analysis through news, patents or social media;
• AI-based decision support systems using linguistic and semantic information;
• Integration of structured (e.g., accounting, market) and unstructured (e.g., textual) data;
• Explainable AI and interpretable NLP models for corporate applications;
• Applications of semantic similarity, topic modelling or large language models (LLMs) in business contexts.

We look forward to receiving your contributions. 

Dr. Ludovica Segneri
Dr. Andrea Fronzetti Colladon
Prof. Dr. Francesca Grippa
Dr. Aleksandra Przegalińska
Guest Editors

Manuscript Submission Information

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