Hands On & Paper Development Workshop: Natural Language Processing for Innovation Management

Date: June 5, 2026
Location: Hengqin

Fee: 700 HKD

Prof. Filippo Chiarello and Vito Giordano from the University of Pisa will host a full-day workshop on Natural Language Processing (NLP) for Innovation Management. The workshop combines a structured training course on NLP methods with a dedicated paper development workshop linked to a forthcoming Special Issue of Technovation.

Purpose of the Workshop

The workshop is designed to equip participants with both foundational knowledge and practical skills in NLP, with a special focus on applications in innovation management. During the first part of the day, participants will be introduced to key NLP concepts, including text preprocessing and encoding methods, as well as advanced techniques and Large Language Models (LLMs).

In the second part of the day, the workshop shifts from methods to research design and publication. Participants will be guided through a paper development workshop focused on how NLP and LLM-based methods can be used to develop high-quality, rigorous, and relevant academic research for top-tier journals. Special attention will be devoted to a forthcoming Special Issue of Technovation entitled 'Text as Knowledge for Innovation Management: Ensuring Research Relevance and Rigor with NLP and LLMs'.

Paper Development Workshop and Special Issue Focus

The final two hours of the workshop are explicitly devoted to a paper development workshop led by Vito Giordano and Prof. Filippo Chiarello, Guest Editor of the Technovation Special Issue. During this session, the goals, scope, and positioning of the Special Issue will be presented and discussed.

Participants are invited to submit a short extended abstract (maximum one page) describing a potential paper idea related to the Special Issue. Abstracts should be emailed to filippo.chiarello@unipi.it ccd vito.giordano@unipi.it prior to the workshop. Selected ideas will be discussed interactively during the session, with direct feedback on theoretical framing, methodological choices, and positioning, to help participants correctly orient and strengthen their work.

Technovation Special Issue – Call for Papers

Text as Knowledge for Innovation Management: Ensuring Research Relevance and Rigor with NLP and LLMs

Call for Papers publication date: 28 October 2025

Submission deadline: 31 March 2027

This Special Issue explores how Natural Language Processing (NLP) and Large Language Models (LLMs) can analyse and generate knowledge across the innovation process. From idea generation to commercialisation, these tools are transforming how organisations discover insights, evaluate ideas, and develop new products. The Special Issue aims to advance both theory and practice in innovation management by examining how textual data can be leveraged as a source of knowledge.

Link to the call for papers: https://www.sciencedirect.com/special-issue/327243/text-as-knowledge-for-innovation-management-ensuring-research-relevance-and-rigor-with-nlp-and-llms

Prerequisites and Materials

There are no strict prerequisites to attend the workshop. However, for the practical sessions, a basic understanding of Python and/or R will be helpful. All participants will receive the slides and source code (R and Python) used during the workshop.

Agenda

About the Workshop Host

Prof. Filippo Chiarello

Filippo Chiarello is an Associate Professor of Innovation at the University of Pisa (UNIPI). His work lies at the intersection of innovation, design, and artificial intelligence, with Natural Language Processing (NLP) as a core methodological approach. He focuses on applying AI—particularly language-based models—to innovation management, engineering design, and data-driven decision-making, bridging research, education, and real-world applications. He is the director of the DETAILLs Lab.

Vito Giordano is a Researcher at the University of Pisa (UNIPI), affiliated with the School of Engineering. His research focuses on Natural Language Processing (NLP) and its application to innovation phenomena, technological forecasting, and data-driven management. He investigates how text mining and large language models (LLMs) can support innovation processes such as foresight, technological trend analysis, and decision-making in engineering and organizational contexts.