Four Patterns of Data-Driven Design Activities in New Product Development
dc.contributor.author | Lee, BY | |
dc.contributor.author | Ahmed-Kristensen, S | |
dc.date.accessioned | 2024-03-15T10:19:25Z | |
dc.date.issued | 2023-06-19 | |
dc.date.updated | 2024-03-14T17:12:05Z | |
dc.description.abstract | In the midst of Industry 4.0 where digitalisation is stimulated through the Internet of Things (IoT), Big Data, and machine learning technologies, an increasing volume of valuable data has been acquired from sensors and interconnected devices. This data-driven paradigm can enable organisations to create new or improved products and services, build long-term customer relationships in a value co-creation manner, adapt to continuous business reconfiguration or address societal challenges such as sustainability. Scientific research addressing Data-driven design has increased steadily in the last few years. However, despite this, there is still a need for a comprehensive understanding of data-driven design processes. Thus, through a systematic literature review, we review the data-driven design activities observed in the new product and service development and types of data utilised in New Product Development (NPD) process. This paper contributes to design research and through reviewing the current landscape of Data-driven design identifies ten data-driven design activities and four-dimensional aspects in NPD process | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.identifier.citation | Vol. 3: ICED23, pp. 1925 - 1934 | en_GB |
dc.identifier.doi | https://doi.org/10.1017/pds.2023.193 | |
dc.identifier.grantnumber | EP/T022566/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/135560 | |
dc.language.iso | en | en_GB |
dc.publisher | Cambridge University Press | en_GB |
dc.rights | © The Author(s), 2023. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work. | en_GB |
dc.subject | Big data | en_GB |
dc.subject | New product development | en_GB |
dc.subject | Design practice | en_GB |
dc.subject | Data-driven design | en_GB |
dc.title | Four Patterns of Data-Driven Design Activities in New Product Development | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2024-03-15T10:19:25Z | |
exeter.location | Bordeaux | |
exeter.place-of-publication | Cambridge University Press | |
dc.description | This is the final version. Available on open access from Cambridge University Press via the DOI in this record | en_GB |
dc.description | Paper presented at the International Conference on Engineering Design, ICED23, Bordeaux, France, 24 - 28 July 2023 | en_GB |
dc.identifier.eissn | 2732-527X | |
dc.identifier.journal | Proceedings of the Design Society | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2023-06-19 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2024-03-14T17:12:08Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2024-03-15T10:19:31Z | |
refterms.panel | C | en_GB |
pubs.name-of-conference | International Conference of Engineering Design |
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Except where otherwise noted, this item's licence is described as © The Author(s), 2023. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.