arbiter
JournalsPricingAccount

TECHNOLOGY TRANSFER THROUGH ACADEMIC SPIN-OFFS: A SOFT SYSTEMS METHODOLOGY APPROACH

Vilma dos Santos Ramos & Rafael Verão Françozo

Pesquisa Operacional2025https://doi.org/10.1590/0101-7438.2025.045.00294679article
AJG 1
Weight
0.37

What the paper says

Academic spin-offs (ASOs) are an important channel for technology transfer in universities and are created with the participation of researchers or inventors. However, their development and market success require actions and resources from various stakeholders, making the process challenging. This study proposes a structured model for technology transfer through ASOs in public universities, using a case study at the Federal University of Mato Grosso do Sul (UFMS). The research follows the guidelines of the Soft Systems Methodology (SSM) to structure the problem and define a set of essential activities for the creation and consolidation of spin-offs. The main results include a list of key actions for implementing the process and a detailed model for creating ASOs at UFMS, aiming to strengthen innovation and academic entrepreneurship.

1 citation

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1590/0101-7438.2025.045.00294679

Or copy a formatted citation

@article{vilma2025,
  title        = {{TECHNOLOGY TRANSFER THROUGH ACADEMIC SPIN-OFFS: A SOFT SYSTEMS METHODOLOGY APPROACH}},
  author       = {Vilma dos Santos Ramos & Rafael Verão Françozo},
  journal      = {Pesquisa Operacional},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1590/0101-7438.2025.045.00294679},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

TECHNOLOGY TRANSFER THROUGH ACADEMIC SPIN-OFFS: A SOFT SYSTEMS METHODOLOGY APPROACH

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.