E-Thesis 173 views
Open innovation ecosystems: A multi-method assessment of knowledge transfer success / EMILY BACON
Swansea University Author: EMILY BACON
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DOI (Published version): 10.23889/SUthesis.59511
This research conducts an empirical investigation into the conditions for knowledge transfer success across open innovation ecosystems. The ecosystem approach has received significant theoretical attention in recent decades, with such a popularity echoed in its practical applications across a variet...
|Supervisor:||Williams, Michael ; Davies, Gareth|
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This research conducts an empirical investigation into the conditions for knowledge transfer success across open innovation ecosystems. The ecosystem approach has received significant theoretical attention in recent decades, with such a popularity echoed in its practical applications across a variety of organisations. Despite effective information exchange significantly supporting the ecosystem infrastructure, existing literature has established very limited insights into the variances between transfer practices of diverse ecosystem partner types, thus failing to increase knowledge of how knowledge transfer can be achieved successfully within these contexts. In remedying this absence, this study adopts a two-phase, multi-method approach to establish how knowledge transfer conditions are maintained and prioritised between ecosystem partners, in order to accelerate the development of this approach to innovations, both theoretically and practically. Through developing a novel conceptual framework, this study detects seven knowledge transfer conditions, categorising them into three groupings that reflect the nature of the relationship; the knowledge exchanged; and the characteristics of the recipient organisation. Their relevance for innovation ecosystems is ascertained through conducting a qualitative, two-phase investigation into partner perceptions of the identified conditions. Based upon qualitative questionnaires with key stakeholders from an ecosystem orchestrator, results from Interpretive Structural Modelling (ISM) reveal that the conditions retain equal importance, necessitating further analyses to illuminate their relationships with knowledge transfer success. To engender more nuanced understandings, fuzzy-set Qualitative Comparative Analysis (fsQCA) is utilised to analyse semi-structured interviews with 30 ecosystem partners, segregated into threefold analyses representing the common organisational typologies within an ecosystem: multinationals, small-and-medium sized enterprises (SMEs) and universities. Results reveal distinct, mutually exclusive solutions for success, grounded upon combinations of conditions that manifest within causal configurations. These findings affect how information exchange should be construed and accomplished by practitioners engaging in ecosystem approaches.
Due to Embargo and/or Third Party Copyright restrictions, this thesis is not available via this service.ORCiD identifier: https://orcid.org/0000-0001-9933-3902
Faculty of Humanities and Social Sciences