scholarly journals A Case Study on Spotify: Exploring Perceptions of the Music Streaming Service

2013 ◽  
Vol 13 (1) ◽  
pp. 207-230 ◽  
Author(s):  
Kate Swanson
Keyword(s):  
Streaming Service ◽  
Music Streaming

Market Capture of Music Streaming Services in India

2020 ◽  
pp. 65-67
Keyword(s):  
Country Music ◽  
Internet Services ◽  
Indian Market ◽  
Internet Users ◽  
Streaming Services ◽  
Market Capture ◽  
Streaming Service ◽  
Music Streaming ◽  
Day By Day

India is a very vast market for internet services as it has over 480 million active internet users in the country. Music streaming services in India is emerging day by day. The competition in the market is so high that even two giants Jio Music and Saavn join their hand in 2018 to provide a combine service all across the globe. In, 2019 a global giant Spotify entered into music streaming market in India and affected the each music service in India. Gaana owned by Times Internet have over 150 million active monthly users in the country while JioSaavn reported 100 million active monthly users as per a website. This research is going to study the market capture of various music streaming services in India. Currently, as per the research, Spotify is the most popular streaming service. As per the literature available on various platforms other streaming services were holding the major proportion of the Indian market but after the launch of Spotify, it became most loved streaming service. The research is being done to find out the existing music streaming services are affected by the entrance of Spotify or not

scholarly journals Locating Power in Platformization: Music Streaming Playlists and Curatorial Power

2020 ◽  
Vol 6 (2) ◽  
pp. 205630512093329
Author(s):  
Robert Prey
Keyword(s):  
Structural Dynamics ◽  
Power Dynamics ◽  
Music Market ◽  
Music Streaming ◽  
Platform Economy

Where does the “power” of platformization reside? As is widely recognized, platforms are matchmakers which interface between different markets or “sides.” This article analyzes platform power dynamics through three of the most important markets that Spotify—the leading audio streaming platform—is embedded within: the music market; the advertising market; and the finance market. It does so through the lens of the playlist. Playlists can be seen as a central example of how platforms like Spotify employ curation or “curatorial power” to mediate markets in the attempt to advance their own interests. At the same time, playlists are an outcome of the conflicting pressures and tensions between these markets. As such, they provide a lens through which to view broader structural dynamics within the platform economy. As this case study of Spotify demonstrates, platform “power” is an always unstable and shifting outcome of the ongoing attempt to coordinate between various markets and actors.

scholarly journals Factors Influencing Consumer Intention to Subscribe to the Premium Music Streaming Services in China

2021 ◽  
Vol 29 (6) ◽  
pp. 0-0
Keyword(s):  
Mixed Method ◽  
Online Survey ◽  
Qualitative Data ◽  
Behavioral Control ◽  
Perceived Behavioral Control ◽  
Descriptive Norm ◽  
Injunctive Norm ◽  
Streaming Services ◽  
Streaming Service ◽  
Music Streaming

This study investigates the causes impacting the consumers' intention of the premium music streaming services' subscription in China. An integrated model called the Theory of Streaming Service Acceptance (TSSA) is proposed to explain and predict premium music streaming service subscription behaviors. The TSSA consists of four constructs: attitude, descriptive norm, injunctive norm and perceived behavioral control. The research data was collected in the form of an online survey in China with 120 respondents. Then, interviews were conducted to collect qualitative data from 20 participants. An explanatory sequential mixed method was implemented and the PLS-SEM technique was used to analyze the survey data. The results showed that all constructs in modified research mode, including attitude, injunctive norm and perceived behavioral control except descriptive norm, are indicative predictors for a person’s intention toward premium music streaming services’ subscription. Significant practical inspirations from the perspective of music streaming services providers are also summarized.

scholarly journals Music Platforms and the Optimization of Culture

2020 ◽  
Vol 6 (3) ◽  
pp. 205630512094069
Author(s):  
Jeremy Wade Morris
Keyword(s):  
Digital Culture ◽  
Cultural Goods ◽  
Software Developers ◽  
Recording Technology ◽  
Streaming Service ◽  
Music Streaming ◽  
Data Optimization

Drawing on Mark Katz’s notion of phonographic effects—where musicians, during the advent of early recording technology, altered their style of play to be better captured by microphones—this article explores some of the “platform effects” that arise in the shift to platformization and how cultural goods and user practices are re-formatted in the process. In particular, I examine the case of the music streaming service Spotify to think through the variety of means, sonic, and otherwise, that artists, labels, and other platform stakeholders use to “optimize” music to respond to the pressures platformization creates. I develop a typology of strategies—sonic optimization, data optimization, and infrastructural optimization—to consider the creative and logistical challenges optimization poses for platforms, artists, and users alike. From creating playlist friendly songs to musical spam to artificial play counts, I use the blurry lines these cases create to explore the tensions between the competing needs of platform providers, content producers, and users. I argue that music, as data, adds pressure on musicians and producers to think and act like software developers and coders, treating their music not just as songs that need to reach listeners, but as an intermingling of sonic content and coded metadata that needs to be prepared and readied for discovery. This optimization of culture, and the pressures it creates, affects not just musicians, but content producers of all kinds (e.g., video, podcasts, apps, books, etc.) who are forced to negotiate their relationships digital culture and the platforms through which it circulates.

Doing it yourself: Coventry University Library’s streaming project

2009 ◽  
Vol 34 (3) ◽  
pp. 21-25 ◽  
Author(s):  
Jane Gibbs
Keyword(s):  
Higher Education ◽  
Short Discussion ◽  
New Era ◽  
Future Developments ◽  
Levels Of Use ◽  
Streaming Service ◽  
The Uk ◽  
Uk Higher Education ◽  
The Impact

This case study provides an overview of the logistical aspects of introducing a DIY streaming service, from original idea to implementation, at Coventry University. The study includes reflection on practical problems such as the structuring of file names and complying with the terms and conditions of the ERA licence. It concludes with a short discussion of the impact of the new ERA+ licence on levels of use, together with possible future developments in streaming in the UK Higher Education sector.

scholarly journals User Intention towards a Music Streaming Service: A Thailand Case Study

2018 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Debajyoti Pal ◽  
Tuul Triyason
Keyword(s):  
Technology Acceptance ◽  
Behavioral Intention ◽  
Model Building ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Perceived Satisfaction ◽  
Perceived Enjoyment ◽  
Streaming Service ◽  
Acceptance Model ◽  
Music Streaming

This paper presents a novel acceptance model for an online music streaming scenario of Thailand. The music streaming industry has been gaining in popularity in the recent times.  This research has been conducted in order to measure the user attitude towards the use of this relatively new service using a modified version of the popular Technology Acceptance Model. We try to identify the most popular music-streaming service of Thailand and also the factors that affect the use of such a service. Data has been collected in the form of an online questionnaire survey from more than 300 participants for the purpose of model building and validation. A subsequent regression analysis carried out on the proposed model explains more than 60 percent of the variance of the dependent variable i.e. Behavioral Intention in our case to the predictor variables Perceived Usefulness, Perceived Ease of Use, Perceived Enjoyment and Perceived Satisfaction Level. The results show that Perceived Enjoyment and Perceived satisfaction are the two strongest predictors for Behavioral Intention which is quite different from that of the utilitarian type of information systems.Keywords: Music streaming, TAM, hedonic information systems, regression

Economic Analysis on Music Streaming Service

2020 ◽  
Vol 23 (1) ◽  
pp. 77-97
Author(s):  
Sang-Yong Oh ◽  
Byung In Lim
Keyword(s):  
Economic Analysis ◽  
Streaming Service ◽  
Music Streaming
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