SYSTEMATIC EVALUATION OF A CONVERSATIONAL VOICE USER INTERFACE FOR DECISION-MAKING

Abstract

When making routine and critical purchase decisions, consumers often have a need to process a surplus of information to make the right choice. Today’s technology must be able to assist them in this process. Although conversational voice user interfaces have the potential to help consumers in their decision-making, extensive testing is required to ensure that they are up to par with the expectations and the needs of users and contexts. Therefore, we focus on evaluating the ability of a multi-strategy conversational mobile decision-aid (MODA) (Alikhademi et al., in press) in correctly classifying the decision-making strategies used by consumers and recognizing attributes, brands, and criteria voiced in an air filter purchase context. Our system evaluation results revealed that MODA performed with high levels of accuracy with classifying the user’s decision-making strategy (over 80%) and recognizing decision parameters (over 75%). The main contribution of MODA is that it can support users in many domains and disciplines by recognizing voiced decision parameters.