Supplementary Materials for "Data Want to Be Free: An Innovation Resistance Theory Model for identifying Barriers to Government Data Sharing" study

The below files are Supplementary Materials for “Data Want to Be Free: An Innovation Resistance Theory Model for identifying Barriers to Government Data Sharing” study. Despite global movements toward data-driven innovation and sustainability across sectors, public agencies continue to face resistance when it comes to data sharing as open government data (OGD). As we transition into the fourth wave of open data—a phase that emphasizes inclusive data reuse beyond traditional publication norms—understanding this resistance becomes increasingly critical. While existing research has explored factors impacting the public organizations’ intention to share data, 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 and empirically validating an Innovation Resistance Theory (IRT) model tailored to OGD -IRT4DS (IRT For Data Sharing)- that allows identifying predictors of resistance among public agencies. These barriers span functional (usage, value, risk) and psychological (tradition, image) dimensions. The model is refined through interviews with 25 representatives across 21 public agencies in six countries with varied open data maturity levels. The findings contribute to the literature by adapting IRT to the context of OGD amid the evolving open data paradigm, 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 -uncovered dominant resistance factors- support policymakers in designing inclusive data ecosystems that account for institutional resistance and address challenges in OGD adoption. The below files are (1) research contexts for IRT applications as implies form the literature review that informed the developement of the Innovation Resistance Theory (IRT) model tailored to OGD -IRT4DS (IRT For Data Sharing), (2) the interview instrument developed by transforming the developed model and its individual barriers (i.e., items) into an interview protocol.以下文件均为《数据欲求自由：一款用于识别政府数据共享障碍的创新阻力理论模型》研究的补充材料。 尽管全球各领域均在推进数据驱动创新与可持续发展的进程，但公共机构在以开放政府数据（Open Government Data, OGD）形式开展数据共享时，仍持续面临阻力。随着我们迈入开放数据的第四波浪潮——这一阶段强调在传统出版规范之外实现包容性的数据再利用——对这类阻力的理解愈发关键。尽管现有研究已探讨了影响公共机构数据共享意愿的各类因素，但鲜有研究通过理论模型，探究公共机构阻碍政府数据公开的阻力因素。本研究通过构建并实证验证一款适配开放政府数据场景的创新阻力理论（Innovation Resistance Theory, IRT）模型（IRT4DS，即数据共享用创新阻力理论），以识别公共机构的阻力预测因子，填补了这一研究空白。这类阻力涵盖功能维度（使用、价值、风险）与心理维度（传统观念、形象声誉）。研究通过对六个不同开放数据成熟度等级国家的21家公共机构的25名代表进行访谈，对该模型进行了优化完善。本研究的发现将创新阻力理论适配于不断演进的开放数据范式下的开放政府数据场景，而该场景下该理论的应用此前极为有限，这为相关学术文献做出了贡献。因此，本研究回应了学界日益增长的需求，即开发新颖的理论框架以探究开放政府数据的采纳障碍。研究揭示的核心阻力因素所带来的实践启示，可助力政策制定者设计兼具包容性的数据生态系统，兼顾制度层面的阻力，并解决开放政府数据采纳过程中的各类挑战。 以下文件包括：（1）适配开放政府数据场景的创新阻力理论（IRT4DS，即数据共享用创新阻力理论）模型开发所依托的文献综述中衍生的创新阻力理论应用研究场景；（2）通过将已构建的模型及其各阻力条目转化为访谈提纲而形成的访谈工具。