Academic Highlights

Outstanding Research Recognition Class of 2026

What Is The Prevalence Of Adoption Of Ai in Non-Profit Dance Organizations in New York City, And What Operational Consequences Result From These Technology Decisions? By Annabel Miller Green

Abstract

This study examines the prevalence of AI adoption in nonprofit dance organizations in New York City and the operational consequences that result from these technology decisions. As artificial intelligence reshapes organizational operations across industries, nonprofit performing arts Organizations face a distinctive structural challenge: chronic resource constraints rooted in Baumol's Cost Disease make technology investment persistently difficult regardless of organizational willingness.

Drawing on secondary data from IRS Form 990 filings across 13 prominent NYC nonprofit dance organizations and semi-structured interviews with senior staff at American Ballet Theatre and Alvin Ailey American Dance Theater, this research applies a mixed-method comparative case study design. Key analytical frameworks include the Technology Acceptance Model (Davis, 1989), Greenhalgh et al.'s (2004) absorptive capacity concept, Godefroid et al.'s (2024) three structural barriers to technology adoption, and Selten and Klievink's (2024) integration versus separation framework.

Findings reveal a clear revenue threshold at approximately $30 million, below which dedicated IT capacity and meaningful AI adoption become structurally inaccessible. At the organizational level, adoption is shaped more by IT model than by revenue size, with internal IT enabling deeper and more embedded tool use. Both organizations report administrative efficiency gains following an initial period of friction, staff resistance that was demystified through policy and education, and role redefinition rather than replacement. An original finding emerges around sector-specific pragmatism: both organizations raised unprompted concerns about the environmental impact of AI and described the current moment as an 'AI bubble,' a disposition largely absent from the existing literature.

This research contributes practical implications for arts administrators, funders, and sector su- port bodies navigating technology adoption under conditions of structural resource constraint.

Turning Views Into Participants In The Creator Economy: An Evaluation of How Creator Platform Visibility Translates Into Audience Growth and Participation In New York Dance Organizations By Mariana Delgado Ceniceros

Abstract

As audiences have begun turning to digital platforms and seeking creators to guide their behavior, we now live in a Creator Economy where creator platforms, especially Instagram and TikTok, have transformed into marketing channels where brand recognition can thrive. However, in the dance industry, there is a gap in understanding the conversion process from passive viewers to active patrons and community members, as well as a lack of understanding of which content-release approaches can sustainably drive audience growth.

This research evaluates how mid- to large-scale dance organizations in New York City may leverage, and are already leveraging, creator platforms to convert digital visibility into active engagement and digital patronage. Using a mixed-methods approach that analyzes social media metrics over a five-month period and qualitative interviews with marketing professionals across three organizations to identify effective creator platform marketing strategies and opportunities that sustain engagement, recognition, and audience growth in a rapidly evolving digital landscape. Ultimately, the study argues that for dance institutions to be financially and culturally sustainable through digital presence, they must prioritize authentic relationship building, storytelling, and a balance between promotional and behind-the-scenes content to cultivate a long-term following.

Adapting the K-pop Fandom Ecosystem to Broadway: Applicability and Potential Economic Impact By Leona Minseo Koo

Abstract

Broadway's commercial musical sector now confronts a paradoxical condition: the 2024–25 season produced the highest-grossing total in recorded history, yet only one in ten musicals now recovers its capitalization. South Korea's musical theatre market, which originated as an importer of Broadway licensed works, has charted a strikingly divergent trajectory, roughly doubling its ticket revenue between 2021 and 2024. This growth has been driven almost entirely by domestic audiences rather than by international tourism. This thesis identifies the mechanism underlying that divergence as the institutionalization of K-pop Fandom Ecosystem within Korean musical theatre production, and examines whether this corporate-designed architecture can be adapted to Broadway's commercial environment.

Grounded in Rogers' Diffusion of Innovations theory, the study advances two analytical instruments: a 7×5 K-pop-to-Broadway Innovation Adoption Assessment Matrix that evaluates seven disaggregated ecosystem elements against Rogers' five perceived attributes of innovations, and four scenario-based financial simulations that project the magnitude of incremental revenue plausibly generated by selective adoption across distinct monetization channels. The case material is drawn from multiple Broadway productions purposively selected as documented precedents for fandom-adjacent audience engagement.

The transferability analysis yields a tripartite classification: Merchandise and Collectibility, Experiential Offline Spaces, and Fan Labor register as immediately applicable; Relationship Monetization registers as conditionally applicable; and Platform Direct Communication, IP Expansion and Collaboration, and Gamification register as long-term challenges. The four simulations, parameterized conservatively, indicate that selective adoption produces meaningful revenue across four non-overlapping channels: incremental ticket revenue, experiential retail margin, marketing-side cost displacement, and digital recurring revenue. The repeat-attendance simulation alone projects a conservative lower bound equivalent to five to six weeks of operating runway for an average Broadway musical.

Taken together, these results indicate that the K-pop fandom ecosystem, while not transferable to Broadway in its entirety, offers a coherent set of mechanisms whose selective adaptation could materially address Broadway's structural revenue vulnerability. The study thereby moves the question of fandom-ecosystem adaptation from anecdotal precedent to evidence-based assessment, and constitutes the first quantified bridge between K-pop fandom scholarship and Broadway commercial-theatre research.