Big data maturity models for the public sector: a review of state and organizational level models. Issue 4 (15th July 2020)
- Record Type:
- Journal Article
- Title:
- Big data maturity models for the public sector: a review of state and organizational level models. Issue 4 (15th July 2020)
- Main Title:
- Big data maturity models for the public sector: a review of state and organizational level models
- Authors:
- Okuyucu, Aras
Yavuz, Nilay - Abstract:
- Abstract : Purpose: Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the purpose of this study is to identify the big data maturity models developed specifically for the public sector and evaluate two major big data maturity models in that respect: one at the state level and the other at the organizational level. Design/methodology/approach: A literature search is conducted using Web of Science and Google Scholar to determine big data maturity models explicitly addressing big data adoption by governments, and then two major models are identified and compared: Klievink et al. 's Big Data maturity model and Kuraeva's Big Data maturity model. Findings: While Klievink et al. 's model is designed to evaluate Big Data maturity at the organizational level, Kuraeva's model is appropriate for assessments at the state level. The first model sheds light on the micro-level factors considering the specific data collection routines and requirements of the public organizations, whereas the second one provides a general framework in terms of the conditions necessary for government's big data maturity such as legislative framework and national policy dimensions (strategic plans and actions). Originality/value: This study contributes to the literature by identifying and evaluating the models specifically designed to assess big data maturity in the public sector. BasedAbstract : Purpose: Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the purpose of this study is to identify the big data maturity models developed specifically for the public sector and evaluate two major big data maturity models in that respect: one at the state level and the other at the organizational level. Design/methodology/approach: A literature search is conducted using Web of Science and Google Scholar to determine big data maturity models explicitly addressing big data adoption by governments, and then two major models are identified and compared: Klievink et al. 's Big Data maturity model and Kuraeva's Big Data maturity model. Findings: While Klievink et al. 's model is designed to evaluate Big Data maturity at the organizational level, Kuraeva's model is appropriate for assessments at the state level. The first model sheds light on the micro-level factors considering the specific data collection routines and requirements of the public organizations, whereas the second one provides a general framework in terms of the conditions necessary for government's big data maturity such as legislative framework and national policy dimensions (strategic plans and actions). Originality/value: This study contributes to the literature by identifying and evaluating the models specifically designed to assess big data maturity in the public sector. Based on the review, it provides insights about the development of integrated models to evaluate big data maturity in the public sector. … (more)
- Is Part Of:
- Transforming government. Volume 14:Issue 4(2020)
- Journal:
- Transforming government
- Issue:
- Volume 14:Issue 4(2020)
- Issue Display:
- Volume 14, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 14
- Issue:
- 4
- Issue Sort Value:
- 2020-0014-0004-0000
- Page Start:
- 681
- Page End:
- 699
- Publication Date:
- 2020-07-15
- Subjects:
- Public sector -- Public administration -- ICT -- Maturity model -- Big data -- Big data readiness -- Public organizations
Internet in public administration -- Periodicals
Electronic government information -- Periodicals
351.028546 - Journal URLs:
- http://www.emeraldinsight.com/journals.htm?issn=1750-6166 ↗
http://www.emeraldinsight.com/ ↗
http://www.emeraldinsight.com/info/journals/tg/tg.jsp ↗ - DOI:
- 10.1108/TG-09-2019-0085 ↗
- Languages:
- English
- ISSNs:
- 1750-6166
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9020.679500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22225.xml