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Value co-creation for open innovation: An evidence-based study of the data driven paradigm of social media using machine learning
Published (Version of record)CC BY-NC-ND V4.0, Open
Journal article
Value co-creation for open innovation: An evidence-based study of the data driven paradigm of social media using machine learning
International Journal of Information Management Data Insights, Vol.1(2), 100022
11/2021
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Abstract
Social media encapsulates one of the most prominent human information behaviours that has rapidly evolved to create a new data-driven paradigm that uses data-intensive digital environments to communicate, collaborate, express opinions and support decisions. This has established social media as a unique information asset for value co-creation as it empowers individuals to actively express opinions and sentiment on all facets of interactions with an external entity. Despite recent research on the theoretical underpinnings of social media in open service innovation, practical demonstrations of actionable insights are limited, mainly due to the voluminous and unstructured nature of social media data. We address this limitation by presenting an evidence-based study that uses machine learning algorithms to generate actionable insights of strategic value from this data-driven paradigm. These outcomes provide fresh perspectives and new thinking that advances social media as an emergent information asset for end-to-end open innovation and incremental value co-creation.
Details
- Title
- Value co-creation for open innovation: An evidence-based study of the data driven paradigm of social media using machine learning
- Creators
- Achini Adikari - Centre for Data Analytics and Cognition, La Trobe University, AustraliaDonna Burnett - Centre for Data Analytics and Cognition, La Trobe University, AustraliaDarshana Sedera - Swinburne University of TechnologyDaswin de Silva - Centre for Data Analytics and Cognition, La Trobe University, AustraliaDamminda Alahakoon - Centre for Data Analytics and Cognition, La Trobe University, Australia
- Publication Details
- International Journal of Information Management Data Insights, Vol.1(2), 100022
- Publisher
- Elsevier Ltd
- Identifiers
- 991012992898202368
- Copyright
- This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
- Academic Unit
- Management; Faculty of Business, Law and Arts
- Language
- English
- Resource Type
- Journal article