Anais
Resumo do trabalho
Tecnologia da Informação · Transformação Digital e Inovação em Negócios Digitais
Título
LET’S ROCK! DESIGNING A RECOMMENDATION SCALE FOR MUSIC PLATFORMS
Palavras-chave
Music Streaming
Technology Adoption
Rock Industry
Autores
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Ricardo Vieira Nogueira JúniorUNIVERSIDADE ESTADUAL DO CEARÁ (UECE)
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Paulo César de Sousa BatistaUNIVERSIDADE ESTADUAL DO CEARÁ (UECE)
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Elnivan Moreira de SouzaPROGRAMA DE POS GRADUAÇÃO EM ADMINISTRAÇÃO - PPGA UECE
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Marcio de Oliveira MotaUNIVERSIDADE ESTADUAL DO CEARÁ (UECE)
Resumo
Introdução
The creative economy has experienced exponential growth, driven by digital transformation and the rise of e-commerce. Within this context, music streaming platforms have emerged as a dominant format, particularly for genres such as rock, which hold cultural and creative significance. Despite their relevance, the recommendation systems of these platforms have not been thoroughly assessed from the perspective of musicians and bands.
Problema de Pesquisa e Objetivo
Although several studies discuss music recommendation systems (Prey, 2018), there is a lack of instruments to measure musicians' perceptions regarding recommendation effectiveness and satisfaction. This study aims to fill this gap by developing and validating the Music Streaming Recommendation Scale (MSRS), specifically for the rock music segment.
Fundamentação Teórica
The literature review contextualizes three waves of disruption in the music industry (Urbinati et al., 2019), the role of human and algorithmic curation (Moschetta & Vieira, 2018), and the Unified Theory of Acceptance and Use of Technology. Studies reveal the oligopolistic influence of major labels and the challenges associated with personalization in automated recommendations (Schedl et al., 2018).
Metodologia
The research involved a systematic literature review and survey methodology. A Likert-scale questionnaire was sent to 745 rock music agents identified from Brazilian cultural maps, yielding 133 valid responses. The MSRS construction followed rigorous psychometric validation, including content and face validity, exploratory factor analysis (EFA), Rasch modelling, and confirmatory factor analysis (CFA).
Análise dos Resultados
The MSRS initially included seven items. After statistical refinement, four items (MSRS1, MSRS2, MSRS4, MSRS6) were retained. The scale demonstrated unidimensionality, reliability (composite reliability = 0.913), and a good model fit (CFI = 0.997; RMSEA = 0.066). Rasch analysis confirmed item coherence and measurement stability, supporting the empirical robustness of the measure.
Conclusão
The MSRS is a reliable and valid tool for measuring musicians' perceptions of streaming platform recommendations. The study confirms the importance of understanding the subjective experiences of creators within algorithmic ecosystems and encourages further research across genres and geographies.
Contribuição / Impacto
This research offers the first validated psychometric tool for evaluating recommendation systems from the producers’ perspective in music streaming. It bridges a methodological gap in the literature and supports more transparent and equitable practices in the creative digital economy.
Referências Bibliográficas
Moschetta, P. H., & Vieira, J. (2018). Music in the streaming era. Sociologias, 20(49), 258–292.
Prey, R. (2018). Nothing personal: Algorithmic individuation. Media, Culture and Society, 40(7), 1086–1100.
Schedl, M., Zamani, H., Chen, C. W., Deldjoo, Y., & Elahi, M. (2018). Music recommender systems research. International Journal of Multimedia Information Retrieval, 7(2), 95–116.
Urbinati, A., Chiaroni, D., Chiesa, V., Franzò, S., & Frattini, F. (2019). How incumbents manage disruptive innovations. International Journal of Innovation and Technology Management, 16(1).
Prey, R. (2018). Nothing personal: Algorithmic individuation. Media, Culture and Society, 40(7), 1086–1100.
Schedl, M., Zamani, H., Chen, C. W., Deldjoo, Y., & Elahi, M. (2018). Music recommender systems research. International Journal of Multimedia Information Retrieval, 7(2), 95–116.
Urbinati, A., Chiaroni, D., Chiesa, V., Franzò, S., & Frattini, F. (2019). How incumbents manage disruptive innovations. International Journal of Innovation and Technology Management, 16(1).