A service selection model for digital music service platforms using a hybrid MCDM approach

Chia Li Lin, Ying Hsiu Shih, Gwo Hshiung Tzeng, Hsiao Cheng Yu

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)


Digital music services have provided more and more digital contents and service styles. The number of people paying to download music is on the rise. Digital music files, mainly in MP3 format, have become widespread on the internet. Downloading digital products for free may harm creators and music publishers, because it is very easy to obtain free-music through peer-to-peer sharing technologies over the internet. At the same time, portable entertainment devices and mobile phones are now able to carry music files, enabling people to access music much more easily. On the other hand, with the coming of the 5G in the telecom infrastructure, the rise in downloading music using mobile devices becomes possible. People can access online-music platform services through cable/ADSL with their digital devices (e.g., Personal computer, Notebook and Smart phone) or through the telecom services accompanying their mobile devices. Therefore, a critical issue for record publishers, or digital music service providers, is how to provide services to create value and fulfill customer needs. By determining customer music service needs and intentions, this study identifies the selection criteria necessary for customers to evaluate and select digital music service platforms. A novel MCDM (Multiple Criteria Decision Making) technique is developed that integrates the Decision making Trial and Evaluation Laboratory (DEMATEL), Principal Component Analysis (PCA), Analytical Network Procedure (ANP), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). This technique ranks and improves the digital music service platforms to obtain the best win-win service selection. This paper will propose the key driving aspects of the digital music service platforms and rank them by using the model proposed. The conclusions are composed of suggestions for service providers to improve their existing functions and plan further utilities for the digital music service platforms.

Original languageEnglish
Pages (from-to)385-403
Number of pages19
JournalApplied Soft Computing Journal
Publication statusPublished - 2016 Nov 1

All Science Journal Classification (ASJC) codes

  • Software


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