Choicharoon, A orcid.org/0000-0003-1539-7576, Hodgett, R orcid.org/0000-0002-4351-7240, Summers, B orcid.org/0000-0002-9294-0088 et al. (1 more author) (2024) Hit or miss: A decision support system framework for signing new musical talent. European Journal of Operational Research, 312 (1). pp. 324-337. ISSN 0377-2217
Abstract
In the music industry, the process of signing new musical talent is one of the most complex decision-making problems. The decision, which is generally made by an artist and repertoire (A&R) team, involves consideration of various quantitative and qualitative criteria, and usually results in a low success rate. We conducted a series of mental model interviews with the aim of developing a decision support framework for A&R teams. This framework was validated by creating a decision support system that utilises multi-criteria decision analysis to support decision-making. Our framework and subsequent implementation of the decision support system involving decision rule and weighted sum methods show an improvement in the ability to analyse and decide on greater amounts of talent. This paper serves as a building block for developing systems to aid in this complex decision-making problem.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Decision support systems; OR in entertainment; Decision analysis; Problem structuring |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Management Division Decision Research (LUBS) |
Funding Information: | Funder Grant number Innovate UK - KTP fkaTechnology Strategy Board (KTP) 510933 |
Depositing User: | Symplectic Publications |
Date Deposited: | 20 Jun 2023 10:15 |
Last Modified: | 18 Oct 2024 14:43 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.ejor.2023.06.014 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:200450 |