In psychology decision-making is regarded as cognitive processes by which a preferred strategy is chosen from among several alternatives based on different criteria.

This paper describes main features of Multichoice, a new version of software for multi-criteria decision analysis with ANP/AHP. Multichoice has been developed by authors at the Central Institute of Economics and Mathematics of the Russian Academy of Science in Moscow in 2016, and is the first software for ANP in Russia (available in Russian and English). The paper outlines the main steps of ANP technology: model constructing, relative and absolute evaluating, synthesizing, visualizing and importing the results, and sensitivity analysis. The authors also discuss further development of implementation of ANP-algorithms.

The idea of synthesizing analytical and heuristic approaches is proposed in order to join different approaches to the Venture Capitalists (VCs) decision making. The research applies Analytic Network Process (ANP) methodology to the comparative evaluation of four e-commerce startups. The proposed ANP model represents the decision problem as a structure of Benefits-Opportunities and Risks networks with dependences and feedbacks between decision criteria and alternatives. Based on VCs judgments that are checked for consistency, the ANP approach helps choose the best startup for funding or to estimate the target startup versus other startups. The ratings that are obtained may be used as weights for determining a startups valuation.  In the model, heuristics is used without reducing the complexity of the task and thus helps avoid the systematic error. Moreover, the idea of applying ANP to the VCs decision making serves to make the decision process transparent and understandable. To implement the ANP model, Multichoice software has been developed.

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

This paper aims to draw attention to the interdisciplinary research of the AHP/ANP methodology by emphasizing how it can be studied from a cognitive perspective. We provide an overview of the main cognitive approaches in decision-making, and consider different heuristics that lie at the basis of pairwise comparisons. We emphasize that the AHP/ANP must be considered at the junction of mathematics and psychology, and for further development of the methodology, we should examine the AHP/ANP from the cognitive point of view. We review the recent experimental studies of the AHP/ANP that test human behavior in real decision problems. We also discuss the future applicability of the AHP/ANP methodology in the Experience Age - the age of not only digital information and knowledge, but also behavior. This article is just a small step on the way to discovering the cognitive aspects and future extensions of decision making with the AHP/ANP.