  Open Government Data (OGD) plays a pivotal role in fostering data-driven
innovation and sustainability across various sectors. Despite its potential,
many public organizations are reluctant to share their data openly. While
existing research has explored factors impacting the public organizations
intention to share OGD, there is a paucity of research applying theoretical
models to investigate the resistance by public organizations to making
government data publicly available. This study addresses the gap by developing
an Innovation Resistance Theory (IRT) model tailored to OGD that allows
identifying predictors of resistance among public agencies. We develop an
initial model based on literature and refine it through interviews with 21
public agencies across six countries. The final model describes 39 barriers
related to usage, value, risks, tradition, and image. The findings contribute
to the literature by adapting IRT to the context of OGD, an area where its
application has been notably limited. As such, this study addresses the growing
demand for novel theoretical frameworks to examine OGD adoption barriers.
Practical insights are provided to support policymakers in creating data
ecosystems that encourage data openness and address challenges in OGD adoption.
