---
OA_type: closed access
_id: '19968'
abstract:
- lang: eng
  text: In the dynamic arena of innovation, the relations between academia and industry
    are a keystone for breakthroughs and practical applications. Yet, the groundwork
    of these pivotal University-Industry (U-I) partnerships remains covered in complexity.
    This paper delves into these intricate relations, unraveling the factors that
    help successful collaborations. Grounded in the Resource-Based Theory, our study
    transcends traditional analytical boundaries, leveraging a neural network model
    to understand a comprehensive dataset from the UK’s Higher Education Statistics
    Agency, SCIMAGO Rankings, and Clarivate Publications. This novel approach helps
    to make clear the interplay of academic load, administrative support, scientific
    output, and university rank in sculpting U-I collaboration dynamics. Our findings
    suggest that reduced academic load and robust administrative support significantly
    bolster U-I collaborations. However, the influence of scientific output and university
    ranking is more nuanced, challenging the common belief. High scientific output,
    while indicative of expertise, doesn't always align with industry goals. Similarly,
    while higher-ranked universities could attract more collaborations, the benefits
    are not universal. This paper not only contributes to a deeper understanding of
    U-I collaborations, but also provides actionable insights for university administrators,
    policymakers, and industry leaders. In a world where innovation is key, understanding
    these collaborative dynamics is crucial for fostering partnerships that push the
    boundaries of research and practical application.
article_processing_charge: No
author:
- first_name: Carlos
  full_name: Plata, Carlos
  last_name: Plata
- first_name: Alejandro
  full_name: Casallas Garcia, Alejandro
  id: 92081129-2d75-11ef-a48d-b04dd7a2385a
  last_name: Casallas Garcia
  orcid: 0000-0002-1988-5035
citation:
  ama: 'Plata C, Casallas Garcia A. Machine learning analysis of the factors influencing
    university-industry collaborations. In: <i>85th Annual Meeting of the Academy
    of Management</i>. Vol 2025. Academy of Management; 2025. doi:<a href="https://doi.org/10.5465/AMPROC.2025.54bp">10.5465/AMPROC.2025.54bp</a>'
  apa: 'Plata, C., &#38; Casallas Garcia, A. (2025). Machine learning analysis of
    the factors influencing university-industry collaborations. In <i>85th Annual
    Meeting of the Academy of Management</i> (Vol. 2025). Copenhagen, Denmark: Academy
    of Management. <a href="https://doi.org/10.5465/AMPROC.2025.54bp">https://doi.org/10.5465/AMPROC.2025.54bp</a>'
  chicago: Plata, Carlos, and Alejandro Casallas Garcia. “Machine Learning Analysis
    of the Factors Influencing University-Industry Collaborations.” In <i>85th Annual
    Meeting of the Academy of Management</i>, Vol. 2025. Academy of Management, 2025.
    <a href="https://doi.org/10.5465/AMPROC.2025.54bp">https://doi.org/10.5465/AMPROC.2025.54bp</a>.
  ieee: C. Plata and A. Casallas Garcia, “Machine learning analysis of the factors
    influencing university-industry collaborations,” in <i>85th Annual Meeting of
    the Academy of Management</i>, Copenhagen, Denmark, 2025, vol. 2025, no. 1.
  ista: 'Plata C, Casallas Garcia A. 2025. Machine learning analysis of the factors
    influencing university-industry collaborations. 85th Annual Meeting of the Academy
    of Management. AOM: Annual Meeting of the Academy of Management vol. 2025.'
  mla: Plata, Carlos, and Alejandro Casallas Garcia. “Machine Learning Analysis of
    the Factors Influencing University-Industry Collaborations.” <i>85th Annual Meeting
    of the Academy of Management</i>, vol. 2025, no. 1, Academy of Management, 2025,
    doi:<a href="https://doi.org/10.5465/AMPROC.2025.54bp">10.5465/AMPROC.2025.54bp</a>.
  short: C. Plata, A. Casallas Garcia, in:, 85th Annual Meeting of the Academy of
    Management, Academy of Management, 2025.
conference:
  end_date: 2025-07-29
  location: Copenhagen, Denmark
  name: 'AOM: Annual Meeting of the Academy of Management'
  start_date: 2025-07-25
date_created: 2025-07-06T22:01:23Z
date_published: 2025-06-17T00:00:00Z
date_updated: 2025-09-09T08:39:03Z
day: '17'
department:
- _id: CaMu
doi: 10.5465/AMPROC.2025.54bp
intvolume: '      2025'
issue: '1'
language:
- iso: eng
month: '06'
oa_version: None
publication: 85th Annual Meeting of the Academy of Management
publication_identifier:
  eissn:
  - 2151-6561
  issn:
  - 0065-0668
publication_status: published
publisher: Academy of Management
quality_controlled: '1'
scopus_import: '1'
status: public
title: Machine learning analysis of the factors influencing university-industry collaborations
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2025
year: '2025'
...