Journal article 749 views 269 downloads
The Underlying Complexities Impacting Accelerator Decision Making—A Combined Methodological Analysis
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Mike Williams,
Gareth Davies
IEEE Transactions on Engineering Management, Volume: 70, Issue: 1, Pages: 1 - 16
Swansea University Authors:
Kelvin Donne, Laurie Hughes , Mike Williams, Gareth Davies
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DOI (Published version): 10.1109/tem.2020.3041558
Abstract
Business accelerators play a key role in the initial critical stages of assessment of commercial viability, offering mentorship provision of funding and protection of intellectual property for product development and refinement. However, little is known about the decision making criteria and detaile...
| Published in: | IEEE Transactions on Engineering Management |
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| ISSN: | 0018-9391 1558-0040 |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2021
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa55800 |
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| Abstract: |
Business accelerators play a key role in the initial critical stages of assessment of commercial viability, offering mentorship provision of funding and protection of intellectual property for product development and refinement. However, little is known about the decision making criteria and detailed analysis of the underlying criteria and interdependencies between the key factors used by accelerator organisations to fund start-ups. This study focusses on the decision making criteria utilised by a leading £21M accelerator programme, largely funded by the European Regional Development Fund for initial stage funding and intellectual property protection for product and innovation commercialisation. We incorporate a multi-methodological interpretive based approach based on Day’s ‘Real-Win-Worth’ framework to develop the interrelationships and ranking between the factors. The results highlight the significance and weighting attached to the factors associated with the technical competency of the proposer and evidence of demand existing for the product. We propose a new framework that models the key factor interrelationships offering additional insight to accelerator based decision making. |
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| College: |
Faculty of Humanities and Social Sciences |
| Issue: |
1 |
| Start Page: |
1 |
| End Page: |
16 |