**7. Conclusions**

To effectively deal with and process intuitionistic fuzzy information, in this study we have proposed the intuitionistic fuzzy weighted induced ordered weighted averaging distance operator, which improves the existing aggregation operators by extending the role of the order-inducing variables. In the proposed operator, the order-inducing variables induce the order of arguments and moderate the associated weights simultaneously. Thus, it enables us to capture the variations in the final aggregation results caused by the order-inducing variables. A generation of intuitionistic fuzzy weighted induced ordered weighted averaging distance operator has been further developed, based on which, a novel model for intuitionistic fuzzy multiple attribute decision making problems was developed. This model presents a useful and adaptable way to integrate subjective opinions and complex attitudinal characters in real situations. The comparative analysis illustrates that this model is expected to lead to more realistic and accurate results in intuitionistic fuzzy situations. Thus, this paper offers a significant contribution in regards to the development of MADM frameworks for investment selection problems.

In future research efforts, we will consider extending the approach with probabilities or other kinds of distance measures. We may also consider other situations based on the presented procedures and tools, such as the Pythagorean fuzzy set [36,42] and Neutrosophic set [43,44].

**Author Contributions:** Z.L. drafted the initial manuscript and conceived the MADM framework. D.S. provided the relevant literature review and the illustrated example. S.Z. revised the manuscript and analyzed the data.

**Funding:** This paper is supported by National Social Science Fund of China (No.18BTJ027).

**Conflicts of Interest:** The authors declare no conflict of interest.
