Inspired by Yager, in this paper, we present the concept of likelihood for intuitionistic fuzzy sets (IFSs), and propose an approach for flexible computation of likelihood functions of IFSs for multicriteria decision‐making (MCDM). We employ ordered weighted average (OWA) aggregation method to soften the strong likelihood constraint condition. The OWA measure can be considered as the attitudinal character, which determines OWA weights, including optimistic or pessimistic likelihood values. Then the reliability‐based soft likelihood function is developed by considering the reliability of intuitionistic fuzzy information. Some examples are conducted by using the proposed (reliability‐based) soft likelihood functions in intuitionistic fuzzy environment for MCDM problem, and the results are analyzed in detail.

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Many companies are introducing voice-based service artificial intelligence (AI) into their call centers. Little is known about the relationship between customers' emotions to voice-based service AI and customers' negative reactions. This study investigates the link between customers' emotions toward voice-based service AI and customers' negative reactions. Our results reveal that customers' emotion toward voice-based service AI could significantly affect their complaint behavior, and customers' complaint differ among different emotions types. Customers' negative and positive emotions toward voice-based AI services have asignificantly positive and negative effect, respectively, on customer complaint behavior than neutral emotion. We also find that the exchange round of human-AI interaction moderates the effect of the customer emotion on customer complaint. This study investigates the impact of customers' emotions toward voice-based service AI on customers' complaint behavior to make up the existing research insufficiency in a certain degree.