Understanding the determinants of the intention to innovate with open government data among potential commercial innovators: a risk perspective

PurposeThis study aims to examine factors influencing potential commercial innovators' intention to innovate with open government data (OGD) via a risk perspective.Design/methodology/approachThe authors develop a theoretical model that explains how different forms of uncertainty (i.e. financial...

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Bibliographic Details
Published in:Internet research 2023-04, Vol.33 (2), p.445-472
Main Authors: Yang, Zhenbin, Ha, Sangwook, Kankanhalli, Atreyi, Um, Sungyong
Format: Article
Language:English
Subjects:
Citizen Participation
Computer Software
Government (Administrative Body)
Government agencies
Innovation
Innovations
Intention
Open data
Opportunities
Perceptions
Public Agencies
Public Sector
Researchers
Risk perception
Software
Uncertainty
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Summary:PurposeThis study aims to examine factors influencing potential commercial innovators' intention to innovate with open government data (OGD) via a risk perspective.Design/methodology/approachThe authors develop a theoretical model that explains how different forms of uncertainty (i.e. financial, technology, competitive, demand, and data) and their inter-relationships influence potential commercial innovators' intention to innovate with OGD. The model is tested using survey data collected from 144 potential commercial innovators from a developed Asian country.FindingsThe results suggest that all other forms of uncertainty, except competitive uncertainty, negatively influence potential commercial innovators' intention to innovate, mediated by their perceived risk of innovating with OGD. The results also show positive relationships between different forms of uncertainty, i.e. competitive and financial, demand and competitive, data and financial uncertainty.Originality/valueThis paper identifies major forms of innovation uncertainty, perceived risk, their inter-relationships, and impacts on the intention to innovate with OGD. It also finds support for a unique form of uncertainty for OGD innovation (i.e. data uncertainty).
ISSN:1066-2243
2054-5657
DOI:10.1108/INTR-07-2021-0463