Abstract
Online music service is one of the most popular kinds of online services. To analyze the quality of end user experience, we investigate the quality of experience (QoE) index of these services. Based on the SERVPERF model, we collect data from college students and obtain weights of key factors. A hierarchical QoE index system is proposed in this paper. Using this QoE index system, we comparing several popular online music services, and give some improvement suggestion to these services.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Rahimi, R.A., Park, K.-H.: A comparative study of internet architecture and applications of online music streaming services: the impact on the global music industry growth. In: 2020 8th International Conference on Information and Communication Technology (ICoICT), pp. 1–6 (2020)
Chang, J., Liu, S., Huang, H., Qi, D., Zhao, Z.: Study on online music business model innovation based on value chain theory. In: 2016 International Conference on Logistics, Informatics and Service Sciences, pp. 1–6 (2016)
Xu, C., Zhu, Y., Feng, D.D.: Content protection and usage control for digital music. In: Proceedings First International Conference on WEB Delivering of Music. WEDELMUSIC 2001, pp. 43–50 (2001)
Chen, M., Lin, K.C., Kung, C., Chou, C., Tu, C.: On the design of the semantic P2P system for music recommendation. In: International Symposium on Parallel and Distributed Processing with Applications, pp. 442–448 (2010)
Rui, S., Jiaji, Z.: Research on influencing factors of user satisfaction of interactive online music platform. Econ. Res. Rev. 32, 157–159 (2018). (in Chinese)
Yuling, F., Shengli, D., Lina, Y.: Research on comprehensive evaluation method of user experience in information interaction. J. Inf. Resour. Manag. 1, 38–43 (2015)
Kong, F., Liu, H.: Analysis of and improvement on ranking method for fuzzy AHP. In: 2006 6th World Congress on Intelligent Control and Automation, pp. 2498–2502 (2006)
Razali, S.N., Shahbodin, F.: Questionnaire on perception of online collaborative learning: measuring validity and reliability using rasch model. In: 2016 4th International Conference on User Science and Engineering (i-USEr), pp. 199–203 (2016)
Suradi, N.R.M., Kahar, S., Jamaludin, N.A.A.: Validation of a web-based integrated student assessment application questionnaire in public institution: a rasch analysis approach. In: 2020 6th International Conference on Interactive Digital Media (ICIDM), pp. 1–5 (2020)
Youssef, Y.B., Afif, M., Tabbane, S.: Novel AHP-based QoE factors’ selection approach. In: 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), pp. 1–6 (2016)
Kai, Z.: Competitiveness analysis of O2O online group buying platform based on Likert scale and AHP. J. Kunming Cadre Acad. Natl. 2016(10), 64 (2016). (in Chinese)
Tang Yuanyi, H., Qingfeng, L.Y.: A new scale method of analytic hierarchy process. J. Ezhou Univ. 2005(6), 40–41 (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Chen, R., Chen, L., He, J., Li, W., Yang, Y., Cui, P. (2022). Research on QoE Evaluation Index of Online Music Service. In: Jiang, D., Song, H. (eds) Simulation Tools and Techniques. SIMUtools 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-030-97124-3_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-97124-3_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-97123-6
Online ISBN: 978-3-030-97124-3
eBook Packages: Computer ScienceComputer Science (R0)