Analyzing suitable revenue model of digital music platforms in China based on the assumption of paid-music

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Zhang, Yu
dc.date.accessioned 2014-10-09T08:07:58Z
dc.date.available 2014-10-09T08:07:58Z
dc.date.issued 2014
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/14181
dc.description.abstract Objectives of the study: As changes in the distribution channels of music, the online platforms become the most popular and most important channel around audiences all over the world. But in the meanwhile, pirated music on the Internet is a great threat for the licensed digital music services. Especially in China, due to the audience's lower willingness-to-pay and the rampant pirated music, music platforms are looking forward to some practical solutions. This research aims at exploring feasible revenue models with applicable features for Chinese digital music platforms. Academic background and methodology: At first, literature reviews contributed to build the research framework of this study, which included business model, revenue models used in digital music platforms, web 2.0, and the value-adding strategy. The empirical research was divided into two parts - business model evaluation of leading international music platforms and the China market study. The business model evaluation of selected case companies was based on the modified business model. And the case companies were selected following the four different types of revenue models. The second part of China market study was comprised of a SWOT analysis of local digital music industry and the consuming behavior of Chinese audience. Furthermore, the business model evaluation was regarded as benchmarking to highlight specific features that the foreign music platforms are using. The China market study was the ground of analyzing and reflecting beneficial characters for the local digital music platforms. Findings and conclusions: The essential finding of this research is that the artist-to-consumer model is the most suitable model for Chinese digital music platforms. Moreover, a three-sided platform should be developed to leverage the power of audience, advertiser, and celebrities and stars. Application of big data is helpful for music platforms not only at attracting more advertisers and music listeners, but also at encouraging the conversion rate. The value-adding services could combine online features and offline activities through fully leveraging celebrity effects. en
dc.format.extent 98
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Analyzing suitable revenue model of digital music platforms in China based on the assumption of paid-music en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Kauppakorkeakoulu fi
dc.contributor.school School of Business en
dc.contributor.department Tieto- ja palvelutalouden laitos fi
dc.contributor.department Department of Information and Service Economy en
dc.subject.keyword Digital Music Platforms
dc.subject.keyword Business Model
dc.subject.keyword E-Business Ontology
dc.subject.keyword Revenue Models
dc.subject.keyword China Digital Music Market
dc.subject.keyword Value-Adding Service
dc.identifier.urn URN:NBN:fi:aalto-201410102795
dc.type.dcmitype text en
dc.programme.major Information Systems Science en
dc.programme.major Tietojärjestelmätiede fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Pro gradu tutkielma fi
dc.subject.helecon tietojärjestelmät
dc.subject.helecon information systems
dc.subject.helecon musiikki
dc.subject.helecon music
dc.subject.helecon palvelut
dc.subject.helecon service
dc.subject.helecon digitaalitekniikka
dc.subject.helecon digital technology
dc.subject.helecon internet
dc.subject.helecon internet
dc.subject.helecon liiketalous
dc.subject.helecon business economics
dc.subject.helecon mallit
dc.subject.helecon models
dc.subject.helecon kulttuurijohtaminen
dc.subject.helecon arts management
dc.subject.helecon Kiina
dc.subject.helecon China
dc.ethesisid 13746
dc.date.dateaccepted 2014-09-11
dc.location P1 I


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