Although shadow banking widely exists in the financial systems of various countries, their definitions vary significantly due to specific economic and financial characteristics. This paper classifies Chinese shadow banking into six categories: securities, trust, private lending, banking, fund, and insurance. The AR-GARCH-DCC model is used to measure systemic risk spillover through from an industrial and institutional perspective. The network topology index is employed to analyze risk contagion and further explore influencing factors. Firstly, based on the results of the AR-GARCH-DCC, the estimated dynamic volatility (σ) indicates that shadow banking risk spillover is time-varying, especially in trust and securities. Second, according to the static risk spillover analysis, various institutions play different roles and can transform between risk spillovers and overflowers. Thirdly, eigenvector centrality, leverage, assets, CPI, and macroeconomic prosperity significantly impact shadow banking systemic risk spillover.

This paper investigates a novel induced ordered weighted averaging (IOWA) distance operator and its application in Pythagorean fuzzy (PF) multiattribute group decision making (MAGDM). First, a new induced aggregated distance operator named the weighted IOWA distance (WIOWAD) operator is developed, which differs from the existing methods in that it considers the dual roles of the order-inducing variables at the same time. In other words, in addition to inducing the order of the arguments, the order-inducing variables of the WIOWAD operator also plays an important role in moderating the associated weight vector. Some useful properties and different families of the WIOWAD are also discussed. Then, an extension of the WIOWAD within the PF situation is presented, thus obtaining the PFWIOWAD operator. Furthermore, a MAGDM method based on the PFWIOWAD is introduced. Finally, the practicality and effectiveness of proposed approach are illustrated in a research and development project selection problem.