Music intelligence: Granular data and prediction of top ten hit songs-Reference-Cited by-同舟云学术

Music intelligence: Granular data and prediction of top ten hit songs

Published:2021-06 Issue: Volume:145 Page:113535
ISSN:0167-9236
Container-title:Decision Support Systems
language:en
Short-container-title:Decision Support Systems

Author:

Kim Seon Tae,Oh Joo Hee

Publisher

Elsevier BV

Subject

Information Systems and Management,Arts and Humanities (miscellaneous),Developmental and Educational Psychology,Information Systems,Management Information Systems

Reference23 articles.

1. Quality predictability and the welfare benefits from new products: evidence from the digitization of recorded music;Aguiar;J. Polit. Econ.,2018

2. Cultural attributes and their influence on consumption patterns in popular music;Askin,2014

3. What makes popular culture popular? Product features and optimal differentiation in music;Askin;Am. Sociol. Rev.,2017

4. The song remains the same? Technological change and positioning in the recorded music industry;Benner;Strategy Science,2016

5. Stochastic dynamics of music album lifecycle: an analysis of the new market landscape;Bhattacharjee;International journal of human-computer studies,2007

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