Key Factors of Government Knowledge Base Adoption in First-, Second- and Third-Tier Cities in China

The government knowledge base (GKB) has increasing significance nowadays as a means of achieving enhanced connectivity, productivity, availability, and efficiency. The facilitators and barriers to adopting a government knowledge base are unknown from the perspective of civil servants. This research seeks to identify and compare critical factors that impact government knowledge base adoption in first-, second- and third-tier cities in China. According to the literature review, factors from the UTAUT and TOE framework were integrated, and trust to knowledge base and intention to knowledge reuse were introduced to the research model. A questionnaire was designed based on the model and distributed to civil servants. The proposed model was validated, and the collected data was analyzed by PLS-SEM. The results show the factors (effort expectancy, social influence, competitive pressure, trust to knowledge base, intention to knowledge reuse) have a positive impact on the adoption of knowledge base in local governments in all cities while performance expectancy and compatibility have a positive impact on the adoption only in first- and second-tier cities. Facilitating conditions do not positively impact the adoption of a knowledge base in any city. The development of a new GKB adoption model has contributed to a new theoretical finding in the area of digital government. The outcomes will provide insights to local governments seeking to make investment decisions on knowledge base adoption.