Olaleye, S.A., Mogaji, E., Agbo, F.J., Ukpabi, D. and Gyamerah Adusei, A. (2023), "The composition of data economy: a bibliometric approach and TCCM framework of conceptual, intellectual and social structure", Information Discovery and Delivery, Vol. 51 No. 2, pp. 223-240. https://doi.org/10.1108/IDD-02-2022-0014
The composition of data economy : a bibliometric approach and TCCM framework of conceptual, intellectual and social structure
|Author:||Olaleye, Sunday Adewale1; Mogaji, Emmanuel2; Agbo, Friday Joseph3,4;|
1School of Business, JAMK University of Applied Sciences, Jyvaskyla, Finland
2Department of Marketing, Events and Tourism, University of Greenwich, Greenwich, UK
3School of Computing, University of Eastern Finland, Joensuu, Finland
4School of Computing and Data Science, Willamette University, Salem, Oregon, USA
5Jyväskylä School of Business and Economics, University of Jyväskylä, Jyvaskyla, Finland
6Department of Industrial Engineering and Management, Oulun Yliopisto, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 2.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2023081194899
|Publish Date:|| 2023-08-11
Purpose: The data economy mainly relies on the surveillance capitalism business model, enabling companies to monetize their data. The surveillance allows for transforming private human experiences into behavioral data that can be harnessed in the marketing sphere. This study aims to focus on investigating the domain of data economy with the methodological lens of quantitative bibliometric analysis of published literature.
Design/methodology/approach: The bibliometric analysis seeks to unravel trends and timelines for the emergence of the data economy, its conceptualization, scientific progression and thematic synergy that could predict the future of the field. A total of 591 data between 2008 and June 2021 were used in the analysis with the Biblioshiny app on the web interfaced and VOSviewer version 1.6.16 to analyze data from Web of Science and Scopus.
Findings: This study combined findable, accessible, interoperable and reusable (FAIR) data and data economy and contributed to the literature on big data, information discovery and delivery by shedding light on the conceptual, intellectual and social structure of data economy and demonstrating data relevance as a key strategic asset for companies and academia now and in the future.
Research limitations/implications: Findings from this study provide a steppingstone for researchers who may engage in further empirical and longitudinal studies by employing, for example, a quantitative and systematic review approach. In addition, future research could expand the scope of this study beyond FAIR data and data economy to examine aspects such as theories and show a plausible explanation of several phenomena in the emerging field.
Practical implications: The researchers can use the results of this study as a steppingstone for further empirical and longitudinal studies.
Originality/value: This study confirmed the relevance of data to society and revealed some gaps to be undertaken for the future.
Information discovery and delivery
|Pages:||223 - 240|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
113 Computer and information sciences
This work was supported by the Foundation for Economic Education (Liikesivistysrahasto) [grant numbers: 16–9388, 18–10407].
© 2022, Sunday Adewale Olaleye, Emmanuel Mogaji, Friday Joseph Agbo, Dandison Ukpabi and Akwasi Gyamerah. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode.