Impact of Digital Streaming on Independent Labels: A Case Study of Moonlight Records

Thesis Abstract

Digital streaming has transformed the financial and strategic landscape of independent music labels, yet the differential impacts on small-scale entities remain underexplored. This study investigates how digital streaming platforms influence Moonlight Records, an independent label operating within a saturated market characterized by limited direct-to-consumer channels and rising royalty complexities. The central aim is to elucidate how streaming dynamics affect Moonlight Records’ revenue mix, distribution strategies, artist development, and long-term sustainability. Specific objectives are to (1) assess changes in revenue contribution from streaming versus traditional income streams over a five-year period (2019–2023), (2) examine streaming-driven decision-making processes related to repertoire selection, release cadence, and marketing investments, (3) analyze the role of playlisting, algorithmic promotion, and platform partnerships in audience growth, (4) evaluate label-artist negotiation outcomes and contract terms in the streaming era, and (5) propose an integrative model linking streaming metrics to strategic choices for independent labels. The study adopts a mixed-methods design anchored in a pragmatist paradigm to triangulate quantitative financial and usage data with qualitative insights from stakeholder perspectives. The population comprises Moonlight Records’ catalog (n=120 releases) and related organizational documents, with a purposive sample of 15 key personnel (including the label’s founder, a financial manager, a Head of A&R, and two producers) and 6 artist collaborators. Quantitative data will be sourced from platform analytics (Spotify for Artists, Apple Music for Artists, and YouTube Studio), label accounting records, and streaming payout statements, complemented by publicly available market data. The qualitative strand will use semi-structured interviews and documentary analysis of strategy memos and release plans. Instrumentation includes a structured interview guide validated through expert review and a data extraction protocol for financial and usage metrics. Reliability will be ensured through pilot testing of instruments and inter-rater agreement for documentary coding. Analytical techniques comprise descriptive statistics to map revenue trajectories and streaming shares; time-series analysis to identify trends and seasonality in revenue streams; multiple regression to assess how streaming metrics (streams, saves, playlist placements, and listener demographics) predict revenue and promotional expenditure, and structural equation modeling to test an integrated framework linking streaming activity to strategic outcomes. Thematic analysis will be applied to interview transcripts to extract determinants of decision-making under streaming uncertainty, with themes mapped to the theoretical constructs of diffusion of innovations and resource-based view (RBV) theory. A conceptual model will be developed to illustrate relationships among platform exposure, audience reach, revenue diversification, and label resilience. Key expected findings include (i) streaming revenue remaining a growing but imperfect substitute for traditional income, (ii) playlisting and platform partnerships exerting statistically significant influence on catalog visibility and subsequent monetization, (iii) a measurable shift in repertoire strategy toward more release cadence and non-traditional formats (singles, EPs) to optimize algorithmic discovery, (iv) negotiation dynamics between Moonlight Records and artists evolving toward more flexible royalty arrangements and performance-based incentives, and (v) evidence that RBV-aligned capabilities (curation, data analytics, and digital marketing) mediate performance outcomes in streaming environments. The study anticipates identifying a critical threshold at which streaming-driven marketing investments yield diminishing returns, and the role of external factors such as platform policy changes and macroeconomic conditions. This research contributes to knowledge by offering an empirically grounded, theory-informed account of how independent labels navigate streaming ecosystems, extending the RBV and diffusion of innovations literature with a sector-specific model of digital monetization, and providing a practical framework for catalog management and financial planning under platform-driven paradigms. It also informs policy debates on fair compensation models for independent artists and labels within major streaming ecosystems. The study concludes with actionable recommendations for Moonlight Records, including refining the release calendar to optimize playlist opportunities, investing in data analytics capabilities for strategic decision-making, diversifying revenue streams through direct-to-fan initiatives, and negotiating more performance-based elements in artist contracts to align incentives with streaming performance.