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Applying LLMs and GenAI in Innovation Economics – Potentials and Pitfalls

Call for Submissions

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SSH

Applying LLMs and GenAI in Innovation Economics – Potentials and Pitfalls

Large Language Models (LLMs) and Generative AI are revolutionizing how we understand innovation economics and measure the economic impacts of technological change. In innovation studies and innovation economics, these tools facilitate novel approaches to causal identification, enable scalable analysis of previously intractable economic questions, and open new frontiers in understanding how AI technologies reshape market dynamics, productivity patterns, and policy outcomes including within specific sectors such as healthcare, energy, science, education, and public policy.

Call for Submissions

Deadline 15th of August

  • 09.07.2025 Kl. 10:00 - 15.08.2025 Kl. 23:59

  • English

  • On location

Submit here

Call for Submissions

Deadline 15th of August

09.07.2025 Kl. 10:00 - 15.08.2025 Kl. 23:59

English

On location

Submit here

SSH

Applying LLMs and GenAI in Innovation Economics – Potentials and Pitfalls

Large Language Models (LLMs) and Generative AI are revolutionizing how we understand innovation economics and measure the economic impacts of technological change. In innovation studies and innovation economics, these tools facilitate novel approaches to causal identification, enable scalable analysis of previously intractable economic questions, and open new frontiers in understanding how AI technologies reshape market dynamics, productivity patterns, and policy outcomes including within specific sectors such as healthcare, energy, science, education, and public policy.

Call for Submissions

Deadline 15th of August

  • 09.07.2025 Kl. 10:00 - 15.08.2025 Kl. 23:59

  • English

  • On location

Submit here

Call for Submissions

Deadline 15th of August

09.07.2025 Kl. 10:00 - 15.08.2025 Kl. 23:59

English

On location

Submit here

Innovation economics has yet to fully harness the potential of emerging AI-driven LLM methods for addressing core economic questions about innovation performance, R&D patterns, and technological diffusion. With efforts to integrate these techniques, there is a growing need for researchers to exchange best practices and discuss both the potential and methodological limitations inherent to these novel approaches.

Workshop Announcement
We are pleased to announce an upcoming two-day workshop on the 8th and 9th of December 2025 hosted by AAU Business School (DK) in collaboration with representatives from the University of Strasbourg (FR), Copenhagen Business School (CBS), University of Bremen (DE), and UNU-MERIT (NL) that jointly contribute to the PhD and Research network "Economics of Innovation, AI & Data Science applications". The 6th workshop of the network will provide a platform for sharing and discussing research that integrates LLMs and Generative AI within innovation economics, emphasizing methodological rigor and policy relevance in the analysis of AI's economic impacts. 

IMPORTANT

info
We seek submissions that use LLMs and GenAI in research methods of innovation economics, for example, combining AI techniques with econometric analysis, causal identification strategies, or policy evaluation frameworks. Applications can also refer to text analysis of innovation documents, AI-enhanced difference-in-differences analysis, innovation measurement and metrics, natural experiments and counterfactuals using LLM-processed data, automated survey analysis, historical innovation analysis, or utilising novel unstructured data sources to construct datasets. Submissions should demonstrate how these tools advance our understanding of innovation economics exemplifying application potential and discussing inherent limitations.
Submission
Extended abstract: Maximum 2,000 words
Reference list: Maximum 500 words
One figure or table illustrating key findings (optional)
Submit at: https://masshine-workshop-2025.rjuro.com/#
Important Dates
Abstract Submission Deadline: 15. August 2025
Acceptance Notification: 5. September 2025
Camera Ready Paper: 14. November 2025

CALL FOR SUBMISSIONS

Submissions topics:
Innovation Performance and Productivity Analysis

  •  LLM-enhanced measurement of firm-level innovation outcomes
  • AI-processed patent data for productivity analysis
  • Automated processing of R&D survey data for econometric studies

Market Structure and Industrial Analysis:

  • AI-augmented analysis of competitive dynamics and market concentration
  • LLM-based classification of innovation strategies for industrial organization research
  • Automated extraction of market intelligence from unstructured business data

Economic Policy Analysis and Evaluation

  •  AI-enhanced policy impact assessment and natural experiments
  • LLM-processed government documents for policy analysis
  • Automated evaluation of R&D and innovation policy effectiveness

Geographic and Regional Innovation Economics

  • Mapping the geography of skills and occupations using AI-processed job posting data
  • LLM-enhanced analysis of regional innovation systems and knowledge spillovers
  • Geographic diffusion analysis of AI and emerging technologies

Labor Economics and Human Capital

  • AI-augmented analysis of occupational transitions and skills evolution
  • LLM-processed job descriptions for labor market analysis
  • Economic impact assessment of AI on employment and wages

Sectoral Innovation Dynamics

  • Economic analysis of AI diffusion patterns across healthcare, energy, education sectors
  • LLM-enhanced study of sector-specific innovation processes
  • Productivity and performance implications of sectoral AI adoption

Methodological approaches

  •  Combination of GenAI/LLM approaches with econometrics and causal inference
  • Zero-shot classification for economic categorization and measurement
  • Chain-of-thought approaches for complex economic relationship analysis
  • Scaling qualitative insights to large datasets for economic analysis

Submissions should highlight both the economic potential and the methodological limitations that emerge when using LLMs and GenAI techniques in innovation economics research. This should address data quality and economic representativeness, temporal knowledge boundaries for economic trend analysis, causal identification challenges, economic validation and interpretation, reliability and consistency for policy applications, ethical considerations in economic research, as well as reproducibility of economic findings.

The event is free of charge, supported by AAU/MASSHINE. Participants are expected to cover their transport and accommodation.

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