The Sound of Blockchain – The Next Generation of Music Streaming platforms
Msc Thesis
Innovation in a digital world
Msc Business Administration - Digital Business Faculty of Economics & Business
Student name: Bing Voorham
Student number 11808365
Supervisor: Beauregard Berton
Abstract
The music industry has witnessed much change over the last decade. Where music listeners previously bought Vinyl and CD’s, streaming platforms have now become the norm when it comes to accessing and listening to music. The highly centralized nature of these platforms have burdened artists with minimal and complicated payout rates, poor copyright management and very limited insight into their fanbase. Blockchain technology has been a proposed solution to fix these recurring issues which has led to the emergence of multiple blockchain-powered music streaming platforms. To many, however, it remains unclear what to expect from these blockchain streaming platforms and how they compare to traditional streaming platforms such as Spotify or Apple Music. This study aims to break down the variables that define and characterize blockchain music streaming platforms and to identify how they differ to traditional streaming platforms. The research uses an inductive approach that is based upon multiple interviews with blockchain streaming company officials and the available archival data including whitepapers and blog articles. The findings suggest there are six main variables that see a shift in functionality as they are replaced by a blockchain alternative of the streaming platform. This article therefore acts as an introduction to both artists and listeners on what to expect when switching to a blockchain streaming platform.
Keywords: Music industry, Blockchain, Cryptocurrency, Smart Contract, Digital Music,
Music Streaming.
Statement of originality.
This document is written by Bing Voorham who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the
supervision of completion of the work, not for the contents.
Table of content
Definitions ………..………5
1. Introduction ………...………7
2. Literature review ……….11
2.1 Two-sides music platforms ………12
2.1.1 Network externalities ………13
2.1.2 Artist compensation ………14
2.1.3 Transparency ……….15
2.1.4 Centralization ………...17
2.2 Blockchain technology ………..17
2.2.1 Immutability. ……….18
2.2.2 Consensus mechanisms. ………...19
2.2.3 Decentralized network. ……….19
2.2.4 Distributed ledger. ………20
3. Methodology ………....21
3.1 Research strategy & Sample selection ……….21
3.2 Data collection. ………..23
3.3 Data Analysis ……….24
4. Results ……….26
4.1 Within-Case Analysis ………....27
4.2 Cross-Case Analysis ………..32
5. Discussion ……….39
5.1 Governance ………...40
5.2 Revenue Sources. ………..42
5.3 Currency ………44
5.4 Contracting ………46
5.5 Type of users ……….48
5.6 Relationships ……….49
6. Conclusion ………..52
References …………..………..
56Appendices ………..64
Definitions
Bitcoin
A cryptocurrency of which every single transaction is recorded on a blockchain, operating independently of a central bank.
Black box
The earned royalties that have not reached the artists due to unclear copyright management
Block Data structure used in blockchains to group
transactions.
Consensus protocol When using the blockchain, every user agrees to a specific set of procedures. This ensures convergence towards a single, immutable version of the ledger.
Ethereum Open and permissionless blockchain; most common
blockchain where smart contracts operate on.
Hash A unique fingerprint of each block that represents
each block through a set of characters and numbers.
Miners The nodes that group transactions into new blocks
and suggest them to the existing network.
Nodes Computers that save a local version of the distributed
ledger.
Proof-of-work Consensus mechanism in which one party proves to others that a certain amount of a specific computational effort has been expended
Proof-of-Stake Consensus mechanisms for blockchains that work by selecting validators in proportion to their quantity of holdings in the associated cryptocurrency
Public and permissionless blockchain A blockchain that anyone can read and on which anyone can propose new transactions.
P2P network There is no central authority that controls the blockchain; instead it uses a network with the nodes serving as different peers.
Semi-private blockchain A blockchain in which a single company manages the blockchain, and access to enter the blockchain is granted to any qualified user.
Smart contract Pieces of code stored on the blockchain, that are automatically performed once deployed, enhancing the trust and security of the blockchain network.
Token effect A lower incentive to join the blockchain when more
users use it, contrary to a network effect in other
digital platforms.
1. Introduction
The purpose of this article is to generate an understanding of how the variables defining traditional music streaming platforms like Spotify or Apple Music change when switching to a streaming platform that is built on blockchain technology. This thesis will proceed with a general overview of how the rising popularity of music streaming platforms have affected the music industry including an analysis of the arising problems it has brought with it. A brief introduction will be given to blockchain technology and how it has had a disruptive effect on many industries and its potential to solve many of the problems within the music streaming industry today. This will lead to the development of the research question which will be answered throughout the remaining sections of this paper.
Digital music streaming has had a large impact in shaping the music industry as we know it
today. The debut of Napster in 1999 initiated a trend in (free) digital downloading of music and
file sharing, this no longer required people to visit their local retail store and to pay $10-15 for an
album (Lamont, 2013). Over the last decade this music ‘piracy’ has transformed into the
subsequent adoption of legal downloading and streaming services. This has, however, still
caused a sharp decline in the income of artists as the industry shifted from physical to digital
distribution (Sisario & Russell, 2016). The rise in adoption of streaming services has reorganized
the value chain as music consumption has shifted from ‘ownership’ to ‘access’, which has also
been the principal cause of the proceeding almost two decade consistent decline in overall
recorded-music revenue after Napster’s launch (IFPI, 2016). Since 2015 we have seen a slow
gradual yearly increase in the value of the industry, mainly due to the rise in popularity of
streaming platforms like Spotify and Apple Music. Today these streaming platforms have
captured a significant portion (56.1%) of the $20.2 billion recorded-music industry market share
(IFPI, 2020) as they have again disrupted the industry’s traditional revenue model. The ability of artists to capitalize on their music, however, remains only a fraction of what it was before the digital era, still leading record labels and artists to lose revenue (Sisario & Russell, 2016), and is still ‘miniscule’ compared to the massive capitalization of music on platforms such as YouTube.
The music industry therefore remains complex, both in terms of the flow of money as well as the industry’s interaction with digital platforms. Even today, the industry remains highly network based as independent artists are unable to upload their own music to platforms such as Spotify, thereby requiring artists to go through an approved distributor if they wish to be on the platform (Twigg-Flesner, 2018). Where over the last 100 years newly emerging technologies have transformed the foundations of many industries, the music industry has remained somewhat unchanged compared to 100 years ago (Haynes & Marshall, 2018). For that reason, it is time for the music industry to catch up on the technological possibilities that are available in the digital era we live in today.
It has become clear that blockchain technology has the disruptive power and ability to change the
structure of different industries. A clear example where the technology has proven to be
successful is in the finance and banking industry. This does not come as a surprise as the
blockchain was initially invented to act as a decentralized ledger that allows the exchange of
value through cryptocurrencies like bitcoin, without the need for financial intermediaries
(Treleaven, Brown & Yang, 2017). A disproportionately large amount of this blockchain research
has therefore been focused solely on the finance and banking industry, especially concerning
financial transactions and distributed ledger systems (Pilkington, 2016). This is, however, only
the tip of the iceberg for the underlying potential of blockchain technology and its possible
applications throughout other industries remain somewhat overlooked, especially in most
creative industries, the music & entertainment industry being a perfect example (Rennie, Potts &
Pochesneva, 2019). Blockchain technology has to potential to be the new generation of disruption in the music streaming industry that could increase the value captured by the artists, shift the market power from the streaming platforms and record labels to the creators, disintermediate the current value chain and add more transparency to the monetization of music (O’Dair, et al. 2019). This could offer artists the opportunity to finally be properly rewarded for their creative endowments after two decades of decreasing returns (Rogers, 2016). According to Mougar, blockchain technology is of similar importance as the World Wide Web and can arguably give us back the internet in a form that it was supposed to be, namely more open and decentralized, more equitable whilst also being more accessible (2016). Creatives in the music industry are often the first ones to put in the work and the last ones to reap their profits. They have minimal knowledge of how royalty payments are calculated and have little aggregate data of where and how people are listening to their music (Heap, 2017).
That there is potential for blockchain technology to solve many recurring issues within the music streaming industry is evident. However, what remains uncertain is how streaming would look like after implementing such technology. Music streaming being the current most popular way of accessing music, may encounter significant changes in usability for both artists and listeners, yet what the exact impact of the technology would be is also often unclear (Knezevic, 2018).
Although substantial literature exists considering the applications of blockchain in the music
industry, it has never been applied specifically to streaming platforms and broken down into
separate variables and distinctly looked at from a practical perspective. Existing research has
been focused on analyzing the disruptive force that blockchain technology may have on the
music industry (Arcos, 2018; Kim, 2019; Sitonio & Nucciarelli, 2018), and the consequent
impact of this digital innovation (De León & Gupta, 2017). Extensive focus has been placed on how blockchain technology could enhance the distribution of music industry revenue, and in particular its implications for the artists and their ability to capitalize on their music (Kim, 2019).
No literature has broken down the variables that define and characterize music streaming platforms and how these variables may be subject to change when transitioning to a blockchain powered music streaming platform. Nor has previous research addressed how the user experience, for both listeners as artists will change as they navigate themselves through these decentralized music streaming platforms. Due to blockchain streaming services being relatively new and previously not yet having built a working model, researching these companies has previously been rather complicated. However due to a rising interest in blockchain technology and its possible effects on tangled industries such as the music streaming industry, it has led to the emergence of a number of companies which have successfully launched and now aim to become the next industry standard and capture a share of the market share currently occupied by traditional streaming services like Spotify or Apple Music (Builtin, 2020).
This has opened a window for more of a ‘hands-on’ approach that will clearly identify the
differences between the current streaming platforms as we know them, and their blockchain
alternative in order to provide a clear and simple framework to identify the main differences in a
simplified manner. This research paper will build on the analysis of Trabucci et al (2019) that
investigated how blockchain reshapes two-sided platforms, one of the few papers that looked
into existing blockchain companies to determine how they compare with traditional two-sided
platforms. This article will elaborate on this paper by specifically diving into how blockchain
music streaming platforms compare to traditional music streaming platforms and identifying the
differences between the variables that define the two types of platforms. This paper aims to address this gap in the literature by answering the following research question:
How does Blockchain Technology Affect and Change the Main Variables that are Used to Define and Characterize Two-sided Music Streaming Platforms?
Since two-sided music streaming platforms have played a significant role in disrupting the music industry as we know it today (Negus, 2019), the question thus becomes if a new era in music streaming is upon us and how this new technology is again going to ‘disrupt’ the disruptor of the music streaming industry. To tackle this question we will move on to see where we stand with current academic literature available, focusing particularly on what we know about blockchain technology and two-sided platforms. Afterwards we will cover the ‘Methods’ section where the research methods will be presented which are based on multiple primary and secondary data sources. In section ‘Results’ the main findings will be presented which will be followed by a
“Discussion'' section where these results will be discussed. Finally the paper will finish with a conclusion where the implication of this work will be presented along with opportunities for further research.
2. Literature review
The following section will be split into two parts, the first part will define and introduce
two-sided music streaming platforms and the different problems stumbled upon. This will give a
reasoned understanding of the issues the current streaming industry is facing and how these
issues have arisen. This section will be followed by an elaborate description of blockchain
technology including different features that characterize the technology. This will build a
foundational understanding of the streaming industry problems and how blockchain technology has the potential to disrupt the industry.
2.1 Two-sides music platforms
The infrastructure of current internet applications are increasingly moving towards platformization. Platforms have frequently been defined throughout previous research.
According to Lusch and Nambisan (2015) a service platform can be defined as a modular
structure that combines either tangible and intangible resources or components and coordinates
the interaction of resources and actors. A classic example would be Ebay, one of the first
commercial digital marketplace that connects buyers and sellers of a wide range of products and
services to each other, or Linux in enterprise software, that connects complementors and users
(Rochet & Tirole, 2003; Hagiu, 2014). Similarly, video game systems are digital platforms that
serve producers and consumers of video games (Zhu & Iansiti, 2012). In other cases, such as
dating websites, social networks, content-sharing platforms such as YouTube and even music
streaming platforms, it may be difficult to categorize platform users into consumers and
producers, as producers can simultaneously be consumers, and vice versa, at any time (Dellaert,
2019). Platforms can thus be conceptualized as interfaces that act as a mediary for transactions
between two or more sides that can be embodied in products, services or technologies (Figure
2.1). Fundamentally, two-sided platforms have two key features which are that they enable
interactions between two distinct sides, and that both sides are each affiliated with the platform
(Hagiu & Wright, 2015).
Figure 2.1 The main elements of two-sided platforms (Trabucci et al, 2020)
2.1.1 Network externalities
For newly created platforms, network externalities lead to the common “chicken-and-egg”
problem (Caillaud & Jullien, 2003; Evans & Schmalensee, 2010) where they believe the difficulty lies in the initial attracting of users to a platform, where the value really excels once a robust user base exists. For instance a music streaming platform like Spotify must have gathered a large “artist base” to provide enough music in order to be able to attract and satisfy its listeners.
Network externalities tend to create a winner-takes-all outcome, where that platform with the
largest user base drives its rivals out of the market (Ingham, 2018). It comes to no surprise that
the majority of the music streaming market share is controlled by a handful of platforms, as can
be seen in Table 2.1. These platforms must create a value proposition for content producers and
consumers in order to attract both user-groups to their platform (Bender, Gal-on & Geylani,
2021). If they can overcome this initial hurdle, platform firms remain under pressure to capture
and lock in more users than its rival platforms, as network size will be a main source of
competitive advantage (Shankar & Bayus, 2003; Shapiro & Varian, 1999; Sun & Tse, 2009).
This positive feedback loop can translate an early lead in network size into a lasting competitive advantage, and therefore competition between rival platform firms tends to be characterized by significant first-mover advantages (Parente et al, 2018). According to the extant literature, the key to leveraging indirect network effects is price structure design (Hagiu, 2006). Simply put, aggressive pricing strategies that aim for subsidizing one market side usually result in getting them on board of the platform, while the other market side can be charged for above marginal cost prices due to indirect network effects, even under platform competition (Kaiser & Wright, 2006). Looking at the current dominant music streaming platforms, they have greatly subsidized the listeners side of the platform at the cost of the artist side, whilst also taking a large cut for themselves.
2.1.2 Artist compensation
Artists publishing their content on some of the major music streaming platforms such as Google
Music, Spotify and Apple Music receive only marginal compensation for their work because the
intermediaries take a large cut in earnings, up to 40 percent (see Table 2.3). The big music
platforms shown in Table 2.2 are also tightly intertwined with dominant labels. For instance,
Aguiar and Waldfogel (2018) mention that “major record labels have substantial ownership
stakes in Spotify”. Adding to this, Meier and Manzerolle (2019) also point out that big streaming
platforms have shown to make lucrative deals with major labels, paying them tens of millions of
dollars up in advance. Due to this individual artists stand powerless to these agreements of big
companies, forcing them to accept that only a small portion of their earned revenue lands in their
hands. It is unclear exactly how much of the cut platforms like Spotify and Apple music take,
however according to aCooke (2018) this can be expected to be between 25% and 40% of all
money inflow, simply for providing the platform for artists to reach their listeners. This makes it very difficult for independent musicians to earn a stable income without being under contract with major music labels. After an investigation it has shown that 152,094 Spotify subscriber streams generate only around $100 for artists (Bershidsky, 2017), allowing only the top 1% of artists to earn a living from their music as mentioned current streaming platforms “lacked the infrastructure needed to make sure songs are licensed and pay the artists respectively”. This has caused a large amount of artist revenue to have landed in a ‘black box’ outside of the reach of the artist. (Bargfrede, 2015). The music industry itself is a $21 billion dollar industry (IFPI, 2021) therefore there is evidently a value gap to be filled between the value that some digital platforms extract from the revenues earned, and the revenues returned to the music community.
2.1.3 Transparency
An additional problem that artists encounter when receiving their paychecks is the lack of transparency on where exactly these earnings came from. This is because much of the streaming revenue is collected behind closed doors without insight given to the artists concerning their listener demographics, this further limits artists to reach out and connect directly with their fans.
Contract details and royalty payments are often vague on purpose as this is part of the business
model of music stakeholders. Spotify is currently sitting on around $4 billion of unpaid royalties
simply because they do ‘not know’ who to pay (Dahrooge, 2021). These issues were brought to
court Spotify was subject to a $1.6 billion fine in 2018 for not paying the appropriate royalties
and not knowing who the music that was streamed on their platform belonged to
(Beaumont-Thoman & Rushe, 2018), thus demonstrating the unsustainability of how they
operate.
Streaming service Market share
Spotify 32%
Apple Music 18%
Amazon Music 14%
Tancent Music 11%
Youtube Music 6%
Total 82%
Table 2.1: Global music streaming market share, measured by subscriber share (Midiaresearch, 2020)
Major music label Market share Universal Music 31%
Sony Music 21%
Warner Music 18%
Total 70%
Table 2.2: Global market share of top 3 music labels, measured by volume of recorded music (MidiaResearch, 2020)
Music release Label cut Platform cut Artist/band cut Streams per month to earn min. wage (solo musician)
TIDAL Unsigned 0% 40% 60% 117,760
Signed 55% 50% 20% 353,280
Spotify Unsigned 0% 40% 60% 287,574
Signed 55% 25% 20% 862,722
Apple Music Unsigned 0% 40% 60% 200,272
Signed 55% 25% 20% 600,816
Google Play Unsigned 0% 40% 60% 217,752
Signed 55% 25% 20% 653,256
Table 2.3 : Overview of revenue cuts (estimated) on streaming platforms, with a note on the streams/plays per month that an artist should have in order to make a minimum wage. The challenge of this thesis is to liberate artists from depending on intermediaries that take a large revenue cut. Sources: DigitalMusicNews (2018).
2.1.4 Centralization
In the context of music, subscriptions and purchases are majorly happening on a few central platforms, such as Spotify or Apple Music. In essence, platforms are taking control of “the surface on which the market exchange takes place” (Schwarz, 2016). According to Srnicek (2017), the power of platform companies is rising because platforms, in general, tend towards a monopoly. The latest movement in platform accumulation is the monopolization of data. Large scale data about user interactions with the platform forms a ‘monopoly of knowledge’ (Innis, 2007), yet the amount of information that is presented to the artists remains very limited. Along the same lines, the music streaming oligarchs can use their commercial muscle to demand low pays to artists. Spotify founder and CEO Daniel Ek declared to its investors that the increase in interactions with its in-house curated playlists “puts Spotify in control of the demand curve”
(Spotify, 2019). Music streaming is heavily dependent on the accessibility of these streaming platforms, and the large amounts of data they possess puts them in a favorable advantage over any other new market entrants. They therefore act as an important middleman by providing a platform that allows artists and listeners to find each other, and therefore giving them the ability to change heavily for it. Yet whether the amount of value they provide is in proportion to the amount of the revenue they receive will be determined once alternatives to their service are found, and if they are able to maintain their dominant position within the industry.
2.2 Blockchain technology
Blockchain is the core technology used to create the cryptocurrency, Bitcoin, through the
maintenance of immutable distributed ledgers in thousands of nodes proposed by Satoshi
Nakamoto in 2008 (Nakamoto, 2008). During the initial stages of its appearance, blockchain
technology was not able to draw a lot of attention. However, as Bitcoin consistently continued to grow in popularity over the years, society has gradually begun to see blockchain technology’s enormous potential. The underlying blockchain technology can not only be used to power the bitcoin cryptocurrency but can be used by a wide array of applications, much of which society has not yet fully been aware of (Collins, 2016). Blockchain technology is increasingly becoming more of a hot topic for more and more countries, institutions, enterprises, and researchers. It has been considered as part of the fourth industrial revolution since the invention of steam engine, electricity, and information technology (Chung & Kim, 2016; Schwab, 2017). The technology does not require any central control system, and it stores the transaction history in blocks of data that are cryptographically locked together. As it is replicated on every node in the blockchain network, it becomes an immutable and transparent historical record of all transactions (Bargfrede
& Penay, 2015).
Blockchain technology comprises many different features that share a number of common characteristics. These include:
2.2.1 Immutability.
A central property for the participants' trust in the blockchain is the immutability of the data
records (Swan, 2015; Crosby et al, 2016). This means that data cannot be manipulated or
modified after being accepted by the blockchain network. The trust border is therefore shifted to
the individual user level realized by the technical principles of data blocks where the information
is stored in. Each block contains a ‘hash’ which can be considered a digital fingerprint which
contains the desired information along with the hash of the preceding block, making it near
impossible to manipulate the information without being noticed, as the reference value would no longer fit the reference data blocks (Hofmann et al, 2017).
2.2.2 Consensus mechanisms.
A consensus mechanism is a protocol which is in place to ensure that all the participants in the blockchain network are complying with the agreed rules (Baliga, 2017). It ensures that the transactions emerge from a legitimate source by having every participant consent to the state of the distributed ledger. The public blockchain is a decentralized technology, and no centralized authority is in place to regulate the required act (Sayeed & Marco-Gisbert, 2019). For that reason, the network requires authorizations from the network ‘nodes’ for the authentication and verification of any activities that occur in the blockchain network. The process is based on the consensus of the network participants making the blockchain a trustless, secure, and reliable technology for digital transactions (Zheng et al, 2018). Multiple consensus mechanisms have been introduced to endorse the requirements of secure digital transactions. However, proof of work (PoW) and proof of stake (PoS) are the consensus protocols used by the main cryptocurrencies (Sayeed & Marco-Gisbert, 2019).
2.2.3 Decentralized network.
Intermediaries often play essential roles in reducing transaction costs and expanding transaction
possibilities. In order to ease transaction making, intermediaries often help transacting parties
find each other, establish trust, and settle transactions (Roth, 2015). Each transaction must be
validated through the central trusted agency, inevitably resulting in the cost and the performance
bottlenecks at the central servers (Zheng et al, 2018). In contrast, in decentralized networks, third
parties are no longer needed as the consensus algorithms are used to maintain data consistency in
distributed networks. Trust is therefore a main consequence of decentralisation as it removes the need to assess the trustworthiness of the intermediary or other participants in the network (Nofer et al, 2017). Blockchain changed the network architecture removing the need for participants to trust each other or a third party to cooperate in the form of sharing resources throughout the peer-to-peer network (Mingxiao et al, 2017). Through the elimination of certain third-party intermediaries, blockchain can simultaneously lower costs and save time (Chen, & Bellavitis, 2020). Where traditional and new modes of governance rely on the identity and roles of specific actors, blockchain technology thus requires a re-appreciation of the powers exerted by different actors.
Figure 2.2: Traditional (centralized) Figure 2.3: Decentralized network internet service infrastructure of phones, as in blockchain
2.2.4 Distributed ledger.
A distributed ledger is a fully transparent database of recorder digital events that exists across
several locations and which is accessed by multiple participants (Crosby et al, 2016). The ledger
is stored across multiple servers forming a peer-to-peer network through which the servers
communicate to ensure the most accurate and up-to-date records of transactions are maintained (Franks, 2020). It employs a distributed system for the verification of records where the “asset”
may not only be money or transactional information, but also information regarding ownership, contracts, goods, and any other information (Wang et al, 2019). This could therefore also include copyrights and ownership verification. Unlike other peer-to-peer networks it does not duplicate the value that is transferred, but instead, it registers that a value has been transferred from one actor to another. Blocks are verified by thousands of network participants around the globe to keep the network active. The network is made up of several nodes each of which contains an individual local copy of the distributed ledger. The nodes are autonomous in nature and communicate with each other independently to arrive at a consensus over the contents of the distributed ledger (Mayuranathan, Murugan & Dhanakoti, 2020).
3. Methodology
This section consists of three subsections that will provide a complete overview of the research strategy & sample selection used in this research and in finding the interviewees. It will then cover how this data was collected and in what format, followed by an analytical description of how the data was analyzed in order to accurately retrieve answers from the data collected.
3.1 Research strategy & Sample selection
This research will adopt a qualitative research approach for data collection. Since existing
theories specifically looking at blockchain music streaming platforms remain rather scarce, an
exploratory strategy will be used in order to provide new in-depth insight and assess topics under
a new light. The approach used can therefore be considered inductive. The ‘richness’ of
qualitative info is necessary to capture the full dimensions of data collected so that the most
accurate framework can be produced. The units of analysis of our research will be the variables
that characterize the blockchain music streaming platform or the traditional streaming platform,
so that the two types of music streaming platforms can be compared in order to clearly identify
the similarities and differences. The respondents that were selected for the interviews were
chosen based on the criteria that they have the expertise to be able to answer technical questions
regarding the fundamental technology that their streaming platform uses, preferably someone
higher up in the chain of command like CEO’s and co-founders, or otherwise with technological
knowledge of blockchain technology. This was accomplished very well as eight of the total ten
interviews that were conducted included at least one co-founder or CEO, increasing the
reliability to the information collected. The interviewees were reached out to through a
combination LinkedIn in-mail messages, Twitter and in one case a personal website. These were
considerably the most efficient yet also the most professional and non-invading methods of
communication. A purposive sampling method was embraced in which interviewees were
pre-selected based on their role within the company, in some cases additional interviewees within
the same company were reached through snowball sampling by which their relationship to other
colleagues were used to establish the interview. Multiple blockchain powered music platform
companies were reached out to with the aim of being able to conduct at least two semi-structured
interviews per blockchain powered music streaming platforms. In order for an interviewee to be
selected and data to be collected, the interviewees were required to possess good
English-speaking skills with a large vocabulary to make sure they were able to accurately
describe what they intended to. This decreased the potential bias when processing the text at a
later stage.
3.2 Data collection.
The aim of this cross-sectional study is to collect a large quantity of data to provide a peripheral
vision into the variables that characterize the specific company that is being looked into. For that
reason, a combination of primary and secondary information sources were used for data
collection. The results were obtained by using a multi-method approach. Grounded theory
methodology, especially un/semi-structured interviews with the company representatives for the
collection of descriptive to be analyzed. This resulted in a data collection procedure that
consisted of nine one-on-one interviews and one one-on-three interview, covering a total of
twelve interviewees and four post-interview verification emails as primary data. This data was
backed up with archival research that can be found publicly to fill up any gaps that may be left
unaddressed. This included three whitepapers and seven blog posts from company websites that
acted as secondary data. The collecting and comparing data of different sources also allowed the
verification of the data and ensured triangulation. The units of observation were therefore both
the transcripts of the conversation with the interviewees, and the documents that were used to
add value to these already existing interview transcripts. Interviewees came from five different
companies as can be seen in table 3.1. Of these five companies only four were used for within
and cross-case company analysis as one interviewee did not work for a blockchain streaming
platform himself, but instead had his own blockchain company in the paper-waste industry
(Daniel Dewar, Paperchain). Yet due to his expertise in blockchain streaming platforms and close
relationships with other interviewees his responses were also included in data analysis where
relevant. Un/semi-structured interviews were used to make sure a wide range of themes were
discussed within the blockchain streaming industry, giving the interview the freedom to cover
any themes that were not previously thought of by the interviewer. The interviews did, however,
have some sort of pre-established list of themes and variables to discuss concerning fundamentals and technological aspects that the companies operate upon. The interviews had a somewhat large difference in duration that ranged between 15 and 45 minutes, depending on the availability of the interviewee and their ease in communicating. To ensure the validity and reliability of the results, respondent validation was used that involved testing the data collected from archival sources with the transcript data for verification and sense-making.
3.3 Data Analysis
Data analysis took a very similar approach as was done by the Trabucchi et al paper. This was done to facilitate the results of the findings at a later stage in this research paper. Data analysis involved three stages: a within-case analysis, a cross-case analysis, and a theory-building stage.
Open coding was adopted in the first two stages, as the different themes within the blockchain
streaming platforms were identified on the basis of transcripts, notes and the already identified
themes from the Trabucchi et al paper. The analysis of data for the within-case analysis was
rather straightforward, the data was analyzed to provide an introduction of the blockchain
powered streaming platform, including how the platform was run, how their revenue model was
configured and how they are addressing the problems within the current music streaming
industry. Meanwhile, labels and codes were identified that appeared across the different data
sources to identify the different variables that re-emerged from the data. The final variables were
then subjectively selected to form the most all-round, representable and mutually exclusive
variables that characterize the music streaming industry. All the data was then analyzed again
with the NVivo Program, this time being coded into the selected variables for cross-case
analysis. Each theme consisted of a traditional streaming platform variant code and a blockchain
streaming platform variant code, so that when a specific variable was discussed with relation to
blockchain streaming platforms the data could be coded to that exact variable and vice versa.
Considering that in total six variables were selected, the data was thus coded into one of twelve categories. After all the data across all the four companies were coded into their appropriate theme, the word frequency counter was used to identify the most frequent words that were mentioned and to understand how each case was characterized. Adopting this word-by-word approach, the most frequent words were considered keywords for the respective category. The third phase was the development of the coding tree to perform data reduction; words without a minimum length of three characters were excluded from the word frequency counter, so were words that did not provide any academic value. Such words included e.g. ‘able’, ‘among’ or
‘better’. Also were the high-frequency words put into context to avoid contradicting findings to occur, e.g. if the word ‘transparent’ was preceded by the word ‘not’ that word would be excluded from the analysis. Stemmed words were also displayed, if different words had the same stem word their frequencies were added together e.g. the words ‘transparency’ and ‘transparent’
would have been added up cumulatively. After the data was coded and the word frequency
counter had run, keywords were identified that allowed comparisons to be made between
traditional and blockchain streaming platforms which was used to build propositions and answers
to the research question. The purpose of the cross-case analysis was to identify the differences
among the two types of platforms. The cross-case analysis was performed independently by a
single student researcher. Finally the theory building stage was completed to perform
interpretation and abstraction, this involved iterating data and theory with the purpose of
designing the new framework for characterizing and comparing the design of traditional music
streaming platforms with platforms that are built upon blockchain technology.
Table 3.1 - Sample of analysis
Case Direct data Secondary data
Audius 1 interview with co-founder
1 interview with second co-founder * 1 interview with current CEO
1 interview with crypto strategist
1 white paper 3 blog articles
Ujo 1 interviews with co-founder
1 second interview with co-founder * 1 interview with Project lead
2 emails for clarification
1 whitepaper 2 blog articles
Musicoin 1 interview with founder
1 interview with System Engineer
1 white paper
Bitsong 1 interview with co-founder 1 interview with CEO 2 emails for clarification
1 white paper 2 blog articles
Paperchain 1 interview with founder *
Note. Interviews marked with star (*) took place in conjunction
4. Results
The following section is composed of a within-case analysis that provides an analysis of the
different blockchain streaming platforms that were included in the research. This will provide an
analysis of each individual company, how they operate and the problems they are addressing
within the music streaming industry. This is followed by a cross-case analysis where the
collective results will be presented. The word frequency counts will be presented and put into
context with exemplary quotations from the interviews.
4.1 Within-Case Analysis
Audius . Founded in 2018, Audius is the most evolved decentralized music streaming platform to date. They describe themself as “decentralised audio hosting and streaming protocol that is essentially a protocol for listeners and artists to connect without a middleman and stream music and pay artists directly” (Roneil Rumburg, co-founder). They aim to “give everyone the freedom to distribute, monetize and stream any audio content” (Cooper Turley, Crypto Strategist), and all brought together on open-source software. The Audius protocol brings artists, node operators and fans together in an incentive-aligned way, allowing these actors to collectively provide high-quality audio streaming experience without the need of centralized infrastructure. These features are guided by the fundamental beliefs that “users should be compensated in proportion to how much value they create for the network” (Audius Whitepaper). They allow artists to directly engage and transact with their fans where the prices and earnings for the participants should be consistent, predictable and transparent. Today Audius has over 200,000 tracks on their platform and serves around 750,000 listeners each month which means they have 3-folded their growth in the last 18 months. Many famous artists like deadmau5 and RAC have also moved their content to the Audius platform demonstrating the interest in not only small artists but also artists with an already large streaming base. All the information concerning transactions is publicly accessible as intermediaries are removed when possible; and when necessary, they should be algorithmic, transparent and verifiably accurate. They stand for platform access to be
“completely democratized where everyone can contribute to Audius if they follow the protocol
rules” (Audius Whitepaper). The protocol is composed of 5 components that work in
conjunction; these include the use of the Audius token ($AUDIO) which acts as the main
currency within the Audius ecosystem. This token is considered “the main incentive structure
among participants, with three primary prongs of functionality: access, security and governance”
(Audius Whitepaper). These tokens can be staked as by node operators to run the Audius protocol, and by artists to unlock exclusive features and services. Other components include the
‘content node’ which is a user-operated network of nodes to host content and permission access to content on behalf of artists. The ‘content ledger’ acts as the single source of truth for all data accessible within the Audius protocol. Then there is the ‘discovery node’ which provides an easily queryable interface for retrieving metadata. An overview of this governance system can be seen in Figure 4.1.
Figure 4.1: Audius content lifecycle
Ujo Music. Ujo was the first decentralized music streaming platform as it was founded in 2015.
Similarly to Audius, Ujo aims to “bridge the gap between musicians and listeners by creating a
transparent and effective system through the use of blockchain technology for music lovers and
creators globally”, (Jesse Grushack, founder). It is run on the Ethereum blockchain and has
therefore adopted the Ethereum currency to purchase streaming licenses and pay out the artists.
There are different licenses available to purchase, namely a streaming license, here you pay the equivalent of $0.01 in Ethereum for simply listening to the song. There is a download license which allows you to own the song and listen to it as many times as you wish for $0.60. Finally there is a so-called ‘stems’ license which allows you to commercially use the song or parts of the song in your own music, useful when for example wanting to make remixes of an existing song.
Ujo wants to give artists direct insight into who is playing their song and where. Jack Spallone (Project Lead) mentioned an idealized situation where “when a DJ in Germany plays a song, the artist gets a notification on a device that says thank you for playing my music”. Besides offering listeners to pay for the streaming Ujo also allows artists to sell non-fungible tokens (NFT’s) to their fans which are special collectibles that come with special features such as early-access to music or personal concerts. This gives artists multiple streams of income besides simply from streaming. Ujo focuses on automatic payment which is split between all the contributors of the song where “ the amount paid would be instantly split among all the collaborators of the song and deposited in all their accounts and this all occurred in 15 seconds, instead of the usual at best 1-2 months that it takes to get paid”, as mentioned by Jesse.
Bitsong. BitSong is a project dedicated to musicians and listeners and will “generate profit both for the artist and the users who listen to their songs while creating a money saving opportunity for advertisers” (BitSong Whitepaper). On the BitSong platform you will be able to produce songs in which an advertiser can attach advertisements and users can access from any device.
BitSong is another blockchain powered ecosystem fully designed to empower the music industry.
It’s a decentralized ecosystem of services providing the global community of artists, fans and
music providers with a trustless music marketplace that becomes the industry’s point of
reference. It uses blockchain technology to create an immutable ledger that facilitates the process of recording transactions and business assets in a business network with full transparency “the transparency will be solved by blockchain technology, every transaction will be visible to the community” (Lulian Anghelin, co-founder). They provide multiple artist revenue streams including real-time royalty payment and the ability to create and sell NFT’s that will be based on smart contracts between the artist and fans “The blockchain smart contract would provide the artist the user the possibility to get paid in real time” (Angelo Recca, CEO). The Bitsong ecosystem runs on validators that run on a proof-of-stake (POS) algorithm to stake their tokens and achieve distributed consensus. If a node successfully mines the next block in the blockchain the node is rewarded in $BTSG, which is the currency that the Bitsong ecosystem has adopted, there is a hard cap of 90 million $BTSG available for supply. They will distribute 75% of the
$BTSG mined to artists and listeners for viewing and listening to the advertisements. For each advertisement listened, the artist and the listener will receive the profits invested by the advertiser. The user will be paid for the "User Attention". 15% of the $BTSG tokens are kept by the validators and 10% will be retained by Bitsong for platform maintenance. The distribution of these tokens mined will be automatic by the use of smart contracts where “the blockchain smart contract would provide the artist and the user the possibility to get paid in real time” (Lulian Anghelin, co-founder).
Musicoin. Musicoin describes itself as a “decentralized platform revolutionizing creation,
distribution and consumption of music” (Musicoin whitepaper). Musicoin is a decentralized
platform that leverages the power of blockchain technology in empowering musicians to take full
ownership of their content and finances. Our platform is built on a transparent peer-to-peer
network powered by programmable smart contracts to enable fair remuneration for all musical
content and services. They aim to turn Musicoin into an online ecosystem built on trust and transparency that benefits all stakeholders “Our long-term vision is to develop an open ecosystem where outside providers can build music related goods and services on top of the Musicoin platform” (Isaac Mao, founder). Their vision is to establish their brand as a global music platform that provides fair remuneration, distribution, and exposure for independent musicians.
They currently license more than 30 million tracks and host at least 1 million independent musicians on their platform. Their pay-per-play (PPP) smart contract aligns with a musician’s intuitive expectation of a payout, from each single stream of their content. PPP is a smart contract on the Musicoin blockchain that enforces and executes licensing terms to reward a certain fixed amount of $MUSIC per playback, which is the native currency of the platform.
Moreover the smart contract allows the earnings to be split automatically between the artists accordingly “A PPP contract of a license for a four-person band can for example enforce a split payout of 45% to the main musician, 20% to the songwriters and producers, 10% to the guitarist and 25% to the drummer” (Isaac Mao). The use of this contract allows us to avoid unnecessary costs in content acquisition by removing all middle-men involved and thereby distributing 100%
of earnings to the musicians in the form of $MUSIC which can be freely exchanged to any other currency. The $MUSIC tokens are mined using a Proof-of-work (POW) which requires the miners to solve a mathematical equation problem to receive the block reward. 79.6% of the
$MUSIC mined from the block reward will be kept by the miners, 15.9% will go towards PPP earning for artists and the remaining 4.5% will go towards platform development.
4.2 Cross-Case Analysis
In analyzing the interview data, six themes emerged throughout the data which allowed specific
differences to be compared between traditional music streaming platforms and blockchain music
streaming platforms, these will be discussed in this section. These themes were: Governance, Revenue Sources, Currency, Agreements, Type of Users and Relationships. The themes and associative keywords can be found below in tables 4.1 and 4.2.
Table 4.1 Top associative words recorded concerning traditional music streaming platforms
Variable Keywords Frequenc
y
Exemplary quotation
Governance Centralized Intermediarie s
Middlemen Bureaucratic Outdated Inefficient
57 53 39 34 26 22
‘Centralized user-generated music distribution platforms have succumbed to the influence of legacy institutions, struggling to find sustainable business models as existing institutions reap the rewards of their (and artists’) labor.
The network of intermediaries and middlemen that formed in the early days of recorded music still persists” (Audius Whitepaper)
Revenue Sources
Royalties Licensing Complex Contract
50 41 28 17
“Artists' only source of income is from royalties, these are the payments that an artist earns from streams.
Spotify royalties are specifically distributed from the net revenue collected from ads and Premium
subscription fees” (Jack Spallone, Ujo music)
Currency Cent
Dollar Penny
46 28 19
“Most artists on major platforms continue to earn less than half a penny per stream. On average, they would need more than 500,000 plays to earn a monthly minimum wage of $1,472 USD” (Isaac Mao, Musicoin)
Agreements License (deal) Complex fixed
37 28 22
“In license contracts between record labels and streaming companies, most of the revenue goes towards paying the intermediaries, and musicians are almost always left out of these discussions. This results in a royalty distribution scheme that heavily favors intermediaries, at the expense of the musicians, ultimately undervaluing the musician’s work and revenue” (Musicoin whitepaper)
Type of users Listener Artist Platform
59 38 28
“Spotify really only classifies users into two groups, the artists and the listeners” (Jesse Grushack, Ujo)
Relationship Spotify Apple music Middleman Soundcloud Deezer Intermediary
19 18 13 13 12 12
“What we see in the streaming industry today is that all communication is done through the streaming
platform, without the ability for artists to communicate directly to their listeners” (Lulian Anghelin, Bitsong)
Notes. Frequencies reflect the number of time a keyword was mentioned when discussing the variable
Table 4.2 Top associative words recorded concerning blockchain music streaming platforms
Variable Keywords Frequency Exemplary quotation
Governance Community
Decentralized Distributed Ecosystem Open
Transparency Trust
57 52 38 37 30 28 28
“We're a music streaming service that connects fans directly with artists and
exclusive new content. So the the way that we enable that is by being fully decentralised, Audius is operated by a community of artists, listeners and node operators that effectively have come together to build an open
community built on trust” (Roneil Rumburg, Audius)
Revenue Sources NFT Token PPP Tipping
Micropayments
48 36 35 28 22
“Besides Pay-per-play we also allow fans to buy a $5 collectible badge or NFT using Ether as a cryptocurrency” (Jesse Grushack, Ujo)
Currency Crypto
Ethereum
$AUDIO
$MUSIC Tokens Stablecoin
47 34 27 18 18 15
“So I think, you know, we want to build something that the entire globe can access and have the same level of access. And I think in terms of like getting artists paid globally, crypto is the best solution”. (Ranidu Lankage, Audius co-founder)
Agreements Smart (contracts) Automatic Direct
62 38 29
“And so with Audius, as I mentioned earlier, with smart contracts, we want to create direct automatic payment channels, that means that if I stream your song, you're gonna get that royalty payment in real time, and you're able to sort of customise that rate” (Ray Lee, Audius)
Type of users Artist Listener Miner
66 52 41
“So Audius is operated by a community of artists, listeners and validators that effectively have come together” (Roneil Rumburg,
Validator Token holder
38 30
Audius)
Relationship P2P
Fans Artist Direct Interact Connect
44 36 28 22 22 20
“Our platform is built on a transparent Peer-to-Peer network to directly connect artists with their fans to enable fair remuneration for all musical content and services” (River Yan, Musicoin)
Notes. Frequencies reflect the number of time a keyword was mentioned when discussing the variable
