Cooperation among sensor nodes is always essential for achieving reliable data dissemination in Wireless Sensor Network (WSNs). The sensor nodes can cat as a host or a router in which they establish communication between. In this context, the reliability of intermediate sensor nodes that establishes the routing path between the source and destination need to be dynamically assessed for enforcing cooperation. Thus, potential dynamic multi-criteria decision-making model for enforcing cooperation is necessary as the presence of malicious and selfish nodes in WSNs. Which severely crumbles the network performance. In this paper, Hybrid Grey PIPRECIA and Grey OCRA Method (HGP-GOCRAM) -based Dynamic Multi-Criteria Decision-Making Model is proposed for thwarting malicious and selfish nodes for achieving maximized cooperation among the sensor nodes of the routing path. This HGP-GOCRAM specifically used Grey Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA-G) for determining the weights of the criteria considered for evaluating the cooperation degree of the sensor nodes. It further used Grey Operational Competitiveness Rating (OCRA-G) for identifying the rank of the sensor nodes to isolate the worst cooperating nodes dynamically from the rouging path. The simulation results of the proposed HGP-GOCRAM achieved under different malicious and selfish node confirmed an improved packet delivery rate of 22.31%, maximized throughput of 19.78%, with minimized energy consumptions of 20.98% and end-to-end delay of 22.64%, better than the competitive cooperation enforcement approaches used for investigation. The results also proved that the proposed HGP-GOCRAM is capable in achieving rapid and accurate detection and isolation of malicious and selfish nodes.