Digital Audio Workstation (DAW) As A Technology Communication Medium in the Convergence of Music Production Practices in the Digital Age
DOI:
https://doi.org/10.58344/jws.v5i3.1648Keywords:
Digital Audio Workstation, media convergence, technological determinism, digital music, collaborationAbstract
The rapid development of digital technology has significantly transformed the music industry, particularly in the processes of production, distribution, and consumption. One of the key innovations driving this transformation is the Digital Audio Workstation (DAW), which enables musicians to produce music independently within a flexible and digital ecosystem. This research analyzes the role of the Digital Audio Workstation (DAW) in the convergence of technology and music production practices in the digital era. DAW is not only a music production tool but also serves as a communication medium that shapes musicians’ creative patterns. Using McLuhan’s technological determinism theory and Jenkins’ media convergence theory, the study finds that DAW introduces flexibility in music production, allowing cross-border collaboration. The results indicate that DAW has democratized music production, enabling independent musicians to control both the creative process and music distribution, although challenges such as digital literacy and quality standards remain. DAW plays a crucial role in shaping musicians’ identities, facilitating communication with audiences, and accelerating the emergence of a more collaborative and global digital music culture. This research also shows how DAW transforms the way musicians interact with technology and the broader music industry.
References
Bian, M., Zhang, L., & Zhao, H. (2025). Exploring the impact of artificial intelligence on the creativity perception of music practitioners. Journal of Intelligence, 13(4), 47. https://doi.org/10.3390/jintelligence13040047
Borisova, M., Kang, J., & Torres, R. (2024). The impact of artificial intelligence on musicians. Issues in Information Systems, 25(3), 267–276.
Bonnici, A., Dannenberg, R. B., Kemper, S., & Camilleri, K. P. (2021). Editorial: Music and AI. Frontiers in Artificial Intelligence, 4, 651446. https://doi.org/10.3389/frai.2021.651446
Frenneaux, R. (2023). The rise of independent artists and the paradox of democratisation in the digital age: Challenges faced by music artists in the new music industry. DIY, Alternative Cultures & Society, 1(2), 125–137. https://doi.org/10.1177/27538702231174200
Jan, A., Khan, S. A., Naz, S., Khan, O., & Khan, A. Q. (2020). Marshal McLuhan's technological determinism theory in the arena of social media. Theoretical and Practical Research in Economic Fields, 11(2), 133–137. https://doi.org/10.14505/tpref.v11.2(22).07
Kjus, Y. (2021). Datafication, literacy, and democratization in the music industry. Popular Music and Society, 44(5), 573–591. https://doi.org/10.1080/03007766.2021.1989558
Manovich, L. (2013). Software takes command. Bloomsbury Academic.
Micha?ko, A., Le?niewski, M., & Saper, R. (2022). AI-assisted music composition: Creative implications for musicians. Computers in Human Behavior, 135, 107350. https://doi.org/10.1016/j.chb.2022.107350
Morris, J. W. (2020). Music platforms and the optimization of culture. Social Media + Society, 6(3), 1–10. https://doi.org/10.1177/2056305120940690
Prey, R. (2020). Locating power in platformization: Music streaming playlists and curatorial power. Social Media + Society, 6(2), 1–11. https://doi.org/10.1177/2056305120933291
Raffa, M., & Dhaenens, F. (2024). Make-do-with listening: Competence, distinction, and resignation on music streaming platforms. Social Media + Society, 10(1). https://doi.org/10.1177/20563051231224272
Rapfa, M. (2025). Self-brand or be branded out: The convergence of mainstream and independent music talent scouting under platform capitalism. Convergence: The International Journal of Research into New Media Technologies. https://doi.org/10.1177/17499755251328560
Tofalvy, T., & Koltai, J. (2023). "Splendid isolation": The reproduction of music industry inequalities in Spotify's recommendation system. New Media & Society, 25(6), 1419–1440. https://doi.org/10.1177/14614448211022161
Towse, R. (2020). Dealing with digital: The economic organisation of streamed music. Media, Culture & Society, 42(7–8), 1461–1478. https://doi.org/10.1177/0163443720919376
Wikstrom, P. (2020). The music industry: Music in the cloud (3rd ed.). Polity Press.
Yang, X., Liu, H., & Chen, W. (2024). From tools to creators: A review on the development and application of artificial intelligence music generation. Information, 16(8), 656. https://doi.org/10.3390/info16080656
Zhang, Q., & Li, M. (2023). Artificial intelligence in music: Recent trends and challenges. Neural Computing and Applications, 36(3), 1121–1148. https://doi.org/10.1007/s00521-024-10555-x
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Ario Prabowo, Citra Pratiwi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International. that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
