The influence of perceived costs and perceived benefits on AI-driven interactive recommendation agent value

Abstract

This study investigates the effects of perceived costs and benefits on the value of an AI-driven recommendation agent (AIRA) by examining an AIRAs influence on the perceived costs and benefits of an information search done during a consumers’ decision-making process. AIRAs use AI-driven algorithms that accelerate and integrate information search, the evaluation of alternatives, and the full decision process by extracting users’ preferences and acting on their behalf. These specialized agents facilitate searches for information or alternatives and offer recommendations to help consumers make decisions. This study contributes to the building of a theoretical model of AI-driven recommendation agent values and provides new resources for AI-driven marketing academics and practitioners.