Stimulating academic patenting in a university ecosystem: an agent-based simulation approach

Sabrina Backs (), Markus Günther and Christian Stummer
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Sabrina Backs: Bielefeld University
Markus Günther: Bielefeld University

The Journal of Technology Transfer, 2019, vol. 44, issue 2, No 6, 434-461

Abstract: Abstract Technology transfer to society is—in addition to research and teaching—widely acknowledged as a third mission of modern universities. Academic entrepreneurship and academic patenting are two closely related means to do so and, more often than not, patenting activity and entrepreneurship are part of a linear sequence in the commercialization process. This paper is mainly concerned with the first step. To further academic patenting, university administrations have installed or expanded existing technology transfer offices (TTOs) as active stakeholders in the university ecosystem. These offices must find the right measures (e.g., monetary or non-monetary incentives or providing information at internal events) and offer them to the right group of scientists (e.g., departments) at the right point in time. This is challenging because scientists’ decision whether to publish or patent depends on several factors, including individual preferences, perceived normative social pressure from peers, level of information received through word-of-mouth communication or informational events, and previous first-hand experience. An agent-based simulation approach may serve as a decision aid for this purpose. Such an approach models stakeholders as ‘agents’ who interact with each other, and through these interactions, the system’s behavior evolves and can be observed. In this paper, we introduce an agent-based simulation for evaluating measures that can be employed by a TTO in order to stimulate academic patenting and, subsequently, the foundation of spin-off companies relying on such patents. The applicability of the approach is illustrated through an example.

Keywords: University ecosystem; Technology transfer; TTO measures; Decision aid; Complex social system; Agent-based simulation (search for similar items in EconPapers)
JEL-codes: C53 I23 O31 O34 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (13)

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DOI: 10.1007/s10961-018-9697-x

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