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Establishing and implementing data collaborations for public good: A critical factor analysis to scale up the practice

Establishing and implementing data collaborations for public good: A critical factor analysis to... Data analytics for public good has become a hot topic thanks to the inviting opportunities to utilize ‘new’ sources of data, such as social media insights, call detail records, satellite imagery etc. These data are sometimes shared by the private sector as part of corporate social responsibility, especially in situations of urgency, such as in case of a natural disaster. Such partnerships can be termed as ‘data collaboratives’. While experimentation grows, little is known about how such collaborations are formed and implemented. In this paper, we investigate the factors which are influential and contribute to a successful data collaborative using the Critical Success Factor (CSF) approach. As a result, we propose (1) a framework of CSFs which provides a holistic view of elements coming into play when a data collaborative is formed and (2) a list of Top 15 factors which highlights the elements which typically have a greater influence over the success of the partnership. We validated our findings in two case studies and discussed three broad factors which were found to be critical for the formation of data collaboratives: value proposition, trust, and public pressure. Our results can be used to help organizations prioritize and distribute resources accordingly when engaging in a data collaborative. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Information Polity IOS Press

Establishing and implementing data collaborations for public good: A critical factor analysis to scale up the practice

Susha, Iryna
Information Polity , Volume 25 (1): 22 – Mar 23, 2020
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22 pages

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Publisher
IOS Press
Copyright
Copyright © 2020 © 2020 – IOS Press and the authors. All rights reserved
ISSN
1570-1255
eISSN
1875-8754
DOI
10.3233/IP-180117
Publisher site
See Article on Publisher Site

Abstract

Data analytics for public good has become a hot topic thanks to the inviting opportunities to utilize ‘new’ sources of data, such as social media insights, call detail records, satellite imagery etc. These data are sometimes shared by the private sector as part of corporate social responsibility, especially in situations of urgency, such as in case of a natural disaster. Such partnerships can be termed as ‘data collaboratives’. While experimentation grows, little is known about how such collaborations are formed and implemented. In this paper, we investigate the factors which are influential and contribute to a successful data collaborative using the Critical Success Factor (CSF) approach. As a result, we propose (1) a framework of CSFs which provides a holistic view of elements coming into play when a data collaborative is formed and (2) a list of Top 15 factors which highlights the elements which typically have a greater influence over the success of the partnership. We validated our findings in two case studies and discussed three broad factors which were found to be critical for the formation of data collaboratives: value proposition, trust, and public pressure. Our results can be used to help organizations prioritize and distribute resources accordingly when engaging in a data collaborative.

Journal

Information Polity – IOS Press

Published: Mar 23, 2020

References

  • Investigating the Critical Success Factors for Implementing Electronic Document Management Systems in Governments: Evidence From Jordan
    Alshibly
  • Collaborative governance in theory and practice
    Ansell
  • Cross-sector social partnership success: A process perspective on the role of relational factors
    Barroso-Mendez
  • (Re)forming strategic cross-sector partnerships: Relational processes of social innovation
    Ber
  • Electronic information sharing in local government authorities: Factors influencing the decision-making process
    Bigdeli