Exploring the Usefulness of Agent-Based Product Social Impact Modeling Through a Systematic Literature Review

Abstract

A key part of an engineer’s purpose is to create products and services that benefit society, or, in other words, create products with a positive social impact. While engineers have many predictive models to aid in making design decisions about the performance or safety of a product, very few models exist for estimating or planning for the wide range of social impacts an engineered product can have. To model social impact, a model must contain representations of the product and society. Agent-based modeling is a tool that can model society and incorporate social impact factors. In this paper, we investigate factors that have historically limited the usefulness of product adoption agent-based models, and predictive social impact models through a systematic literature review. Common themes of limiting factors are identified and steps are presented to improve the usefulness of agent-based product adoption models and predictive social impact models. The goal of a predictive social impact model is to help an engineer/designer make better decisions. Predictive social impact models can help identify areas in the design space for improving the social impact of products. When coupled with existing design methods, agent-based predictive social impact models can help increase the probability that a product achieves positive social impact.