Research on policy diffusion mechanism of Government Procurement of Public Services based on an MFCM

Purpose The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation. Design/methodology/approach In view of the four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of the MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers, respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on the MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy. Findings Research results show that, compared with monolayer Fuzzy Cognitive Map, the MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned. Originality/value This paper constructs the MFCM model, which is a new approach based on several monolayer FCMs, to study the policy diffusion mechanism.