What organizational conditions, in combination, drive technology enactment in government-led smart city projects?

Nowadays, an increasing amount of literature acknowledges that smart cities’ core aspect is not technology per se but how organizational characteristics and capabilities influence the technology enactment. However, the extant studies primarily focus on business-led smart city projects. Little attention is paid to the causal relations between organizational conditions and technology enactment in government-led projects. Therefore, there is a research gap concerning what conditions of governmental organizations, singly or jointly, drive technology enactment in smart city projects. To fill the gap, this article establishes three increasing levels of smartness and formulates four government conditions. Based on this conceptual framework, this article explores different configurations of organizational conditions that lead to varying levels of smartness. It uses the Qualitative Comparative Analysis (QCA) method to study 11 smart city projects in Hangzhou, China. The results generate three configurations of organizational conditions that lead to decisional intelligence, indicating that multiple pathways exist to achieve the highest level of smartness. These configurations often emphasize the significant role of human resource pressure in driving decisional intelligence. But no single condition is necessary because when human resource pressure is absent, strong financial capacity, good information-sharing, and facilitative leadership can work together as a substitution.