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Blockchain is regarded as a mainstream technology by corporate leaders, who believe it will drive a new generation of business models. The trends of digital innovation have accelerated corporate blockchain technology adoptions, but when it comes to its applications, numerous barriers still exist that must be carefully addressed. In contrast to past decades, data gathering with the help of information technology has switched from being an expensive to an inexpensive process. It brings users sufficient messages, but also incurs the information overload problem. To combat this, a fusion framework integrated FRST-PSO and fuzzy DEMATEL is introduced herein. It assists users in identifying essential information and depicting the opaque relationships among criteria. The findings indicate that improvement priority, which runs in the order of regulatory environment, blockchain development talent, system integration, and function and reliability based on the magnitude of the impact, serves as a reference for the blockchain technology adoption to facilitate/solidify a firm's competitive edges.

This study applies Data Envelopment Analysis (DEA) to estimate banks' efficiency. In stage 1, we construct a risk appetite index (RAI) by measuring the rank correlation between the order of current excess returns and the order of past riskiness across assets and use the risk appetite index to estimate how much risk banks can bear. In stage 2, we apply the Slacks- Based Measurement (SBM) super-efficiency model to calculate the bank's efficiency. The result shows that many of Taiwan's banks have a low appetite for risk and that the efficiency estimation will be improved when risk appetite is considered in the model.