Journal of Pioneering Artificial Intelligence Research

Abstract

Conventional economic analysis treats goods and services as bundles of functional attributes whose value is revealed by prices and choices. Yet real-world demand is pervasively shaped by feelings—joy, disgust, pride, nostalgia, envy, comfort, belonging.

This paper formalizes emotional value as a measurable component of consumer welfare, distinct from (but interacting with) functional utility and monetary cost. Building on affective science, neuro-economics, marketing, and information systems, I propose a composite Emotional Value Index (EVI) that integrates (i) self-re port psychometrics, (ii) linguistic and behavioral traces, (iii) psychophysiology (e.g., HRV, EDA, pupil and gaze), (iv) neural evidence, and (v) digital footprints (search, clickstreams, reviews). The paper details measurement, validation, and computation of EVI, including methods to infer affect from online data rather than questionnaires alone. I illustrate applications for platform firms (Google/YouTube, Amazon, Apple, Netflix), discuss how love (positive valence, high identity alignment) and hate (negative valence, high arousal/identity threat) sit at opposite poles of an effect space, and show how EVI can slot into cost–benefit analysis, hedonic pricing, discrete-choice models, and computable general equilibrium.

I conclude with a governance blueprint (privacy law, dark-pattern avoidance, differential privacy) for ethically harnessing emotion. The approach reframes “value” to include how goods make us feel, not just what they do.

Key empirical and theoretical anchors are cited at the end.