A computational method to track the evolution of business models in the Digital Economy
dc.contributor.author | Wood, Z | |
dc.contributor.author | Walker, David | |
dc.contributor.author | Parry, G | |
dc.date.accessioned | 2023-05-17T10:10:51Z | |
dc.date.available | 2023-05-17T10:10:51Z | |
dc.date.issued | 2022-01-01 | |
dc.identifier.isbn | 9780998133157 | |
dc.identifier.issn | 1530-1605 | |
dc.identifier.uri | https://pearl.plymouth.ac.uk/handle/10026.1/20895 | |
dc.description.abstract |
Companies within the Digital Economy are evolving their business models as they take advantage of the opportunities afforded by emerging digital technologies. There is a need to develop methods that will allow researchers and policy makers to understand the existence of, and relationships between, the different business models within the Digital Economy and track their evolution. Such methods could also help quantify the size and growth of the Digital Economy. This paper presents a computational method, which utilizes machine learning and web scraping, to identify new business models, and a taxonomy of organisations, through the analysis of a firm's webpage. The work seeks to provide an autonomous tool that provides regular output tracking trends in the number of firms in a market, their business model and changes in activity from product to service over time. This information would provide valuable and actionable insight for researchers, firms and markets. | |
dc.format.extent | 1300-1309 | |
dc.title | A computational method to track the evolution of business models in the Digital Economy | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.volume | 2022-January | |
plymouth.conference-name | 55th Hawaii International Conference on System Sciences | |
plymouth.publication-status | Published | |
plymouth.journal | Proceedings of the Annual Hawaii International Conference on System Sciences | |
plymouth.organisational-group | |Plymouth | |
plymouth.organisational-group | |Plymouth|Faculty of Science and Engineering | |
plymouth.organisational-group | |Plymouth|Faculty of Science and Engineering|School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | |Plymouth|REF 2021 Researchers by UoA | |
plymouth.organisational-group | |Plymouth|Users by role | |
plymouth.organisational-group | |Plymouth|Users by role|Academics | |
plymouth.organisational-group | |Plymouth|REF 2021 Researchers by UoA|UoA11 Computer Science and Informatics | |
dcterms.dateAccepted | 2021-09-23 | |
dc.date.updated | 2023-05-17T10:10:51Z | |
dc.rights.embargodate | 2023-5-18 |