20.500.12556/ReVIS-14022 Stakeholder Interview Transcripts on Science–Industry Collaboration and GenAI-Enabled Ecosystem Orchestration, 2026 The research dataset Stakeholder Interview Transcripts on Science–Industry Collaboration and GenAI-Enabled Ecosystem Orchestration contains anonymised qualitative data collected within the research project Usability and Effectiveness of a Generative Artificial Intelligence (GenAI)-Enabled Tool for Science–Industry Collaboration (L7-70279). The study aimed to investigate barriers and facilitators of collaboration among scientists, industry representatives and policymakers and to identify the functional requirements for the development of a GenAI-enabled digital platform supporting collaboration, project development and knowledge exchange. The data were collected through semi-structured in-depth interviews conducted between April and June 2026. A total of 24 stakeholders from the Slovenian research and innovation ecosystem participated in the study, including researchers, industry representatives and policymakers. The unit of observation is the individual interview participant, and the data are stored in the form of textual interview transcripts. The interviews covered several thematic areas, including experiences with science–industry collaboration, needs and barriers related to partnership formation, access to information and competencies, the role of trust in collaborative processes, and expectations regarding the use of digital platforms and generative artificial intelligence to support collaboration, project proposal development and knowledge transfer. The dataset includes anonymised interview transcripts, a coding framework for qualitative analysis, thematic codes and methodological documentation describing the research design, data collection procedures and analytical approach. Data were analysed using reflexive thematic analysis. To ensure compliance with data protection requirements, all direct identifiers (e.g., names of individuals, organisations and contact details) were removed from the transcripts. Potential indirect identifiers were also reviewed and, where necessary, anonymised. The dataset is therefore prepared for long-term preservation and secondary use in accordance with applicable data protection regulations, research ethics principles and open science practices. The dataset is intended to support scientific publications, project reporting and further research on innovation ecosystems, science–industry collaboration, digital platforms, innovation intermediaries and the application of generative artificial intelligence to collaboration support and knowledge management. true false false Slovenski jezik Ni določen Raziskovalni podatki 2026-06-11 09:15:53 2026-06-11 11:30:03 2026-06-12 03:09:22 0000-00-00 00:00:00 0 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 ReadMe.txt ReadMe.txt 1 B51AA8661CFFBEC51E632B42BF21192B ff9dcc3f1ab6db83062f9bb9679b1f3c05be8b5cd44d231bf75c07c543008c20 bbb9af8f-6565-11f1-9215-001a4af901a5 https://revis.openscience.si/Dokument.php?lang=slv&id=16997 ReadMe.docx ReadMe.docx 1 D2B960EED83FB5495078C738BF0BF034 bfc46439c45038dc1a1a20da131c1d10b5e43446e6e3218c8990ffb7d83cab47 cbbf1af3-6565-11f1-9215-001a4af901a5 https://revis.openscience.si/Dokument.php?lang=slv&id=16998 RAZ_Erjavec_Karmen_0.docx RAZ_Erjavec_Karmen_0.docx 1 6029237879EE27FB1EFF1C539574DD40 0902e751f717f819dc49b0b033203ac0ea7d06999f36f4e8b548ac486cfc4b8d 9ccbc7c8-6581-11f1-9215-001a4af901a5 https://revis.openscience.si/Dokument.php?lang=slv&id=17000 Univerza v Novem mestu - Fakulteta za ekonomijo in informatiko 0 0 0