Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/78925
Title: INVESTIGATING OPEN INNOVATION IN PUBLIC SECTOR: EMPIRICAL STUDIES OF OPEN DATA INITIATIVES
Authors: YANG ZHENBIN
Keywords: E-Government, Open Innovation, Public Sector, Open Data, Innovation Uncertainty, Resource Dependence
Issue Date: 1-Apr-2014
Source: YANG ZHENBIN (2014-04-01). INVESTIGATING OPEN INNOVATION IN PUBLIC SECTOR: EMPIRICAL STUDIES OF OPEN DATA INITIATIVES. ScholarBank@NUS Repository.
Abstract: This thesis seeks to increase understanding of the open data phenomenon in two essays. Essay 1 develops a model that explains how public agencies? dependence on various external stakeholders? resources can influence their open data sharing behaviour. Key findings from a survey of public sector organizations indicate that IT and human resources are two types of resources that public agencies are dependent on their external stakeholders, while there was no significant dependence for financial resource. We further found that public agencies? dependence on external stakeholders positively relates to their open data sharing behaviour. Results also suggest that the sensitivity of agency function and public agency conformity needs negatively and positively influence open data sharing behaviour respectively. Essay 2 examines the reasons hindering the demand-side of open data initiatives from the theoretical perspective of risk-taking by identifying the different sources of uncertainty that potential innovators can consider/perceive when deciding whether or not to innovate with open data. Key findings from a survey of potential open data innovators indicate that while financial, IT, demand, and data uncertainty had positive effects on perceived risk of innovating, competitive uncertainty had no effect. Our results also show that risk taking propensity negatively affects perceived risk of innovating, which in turn negatively impacts the intention to innovate with open data. Individual innovativeness had no direct effect but was found to moderate the impact of perceived risk on innovation intention. Overall, the findings of this thesis contribute to theory building in open data innovation and yields important implications for management of public agencies.
URI: http://scholarbank.nus.edu.sg/handle/10635/78925
Appears in Collections:Ph.D Theses (Open)

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