Author

Date of Award

2026

Document Type

MA Project - Restricted Access (SIA Only)

Project Type

MA Project - Business Plan

Degree Name

Master of Arts (MA)

Department

Art Business

First Advisor

Judith Prowda

Second Advisor

Morgan Falconer

Abstract

This business plan develops and evaluates Resonant, a non-therapeutic, software-centric decision-support platform designed for institutional deployment within galleries, fairs, and curated art environments. The venture addresses a documented structural challenge in the contemporary art market: persistent decision uncertainty at the point of purchase, particularly in mid-to-lower price segments where transaction volume is high but value concentration and buyer confidence remain uneven. Drawing on industry market data and an exploratory survey (n = 78), the study identifies a recurrent gap between positive engagement with artworks and final decision completion. A majority of respondents reported neutral or low confidence when considering purchase, and 69% reported abandoning a desired artwork due to uncertainty. At the same time, most respondents indicated that better understanding their personal engagement with artworks would support more confident decisions. Resonant applies multimodal physiological sensing and signal-processing principles informed by neuroaesthetic research to generate structured, non-interpretive engagement metrics during live artwork encounters. The system does not diagnose, predict behavior, or label emotions. Instead, it provides comparative feedback to support reflection and self-directed decision-making while preserving curatorial authority and buyer autonomy. Financial modeling under conservative institutional adoption assumptions indicates potential operating break-even in Year 2, with recurring license revenue as the primary income stream. The analysis concludes that decision-support infrastructure can be commercially viable within art-market norms when positioned as non-prescriptive, institutionally controlled, and privacy-bounded.

Available for download on Wednesday, July 05, 2028

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