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Network management in the era of convergence: Focusing on application-based quality assessment of Internet access service

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  • Lee, Daeho
  • Shin, Jungwoo
  • Lee, Sangwon

Abstract

As Internet applications become more sensitive to latency time, the needs for network management increase. To maximize consumer surplus and profit of Internet service provider at the same time, it is necessary to investigate the consumer׳s willingness to pay for a given quality of service (QoS) level. This study investigates consumer preferences for Internet access services that provide different levels of QoS for different applications. We collect stated preference data via conjoint analysis method and estimate consumer preference using mixed logit model. Based on the estimation results, we find that consumers react most sensitively to changes in the quality of the web browsing service among internet access services and have the highest marginal willingness to pay for improvements in the quality of this service. On the other hand, marginal willingness to pays are relatively low for voice over IP (VoIP) and IP television (IPTV), which are sensitive to latency time. However, if service users of VoIP/IPTV are separated from non-users or if it is assumed that there is no substitute for VoIP and IPTV, marginal willingness to pays of VoIP and IPTV increase. It implies that Internet service providers can profit by providing high QoS to VoIP and IPTV as the markets for VoIP and IPTV services mature and user numbers increase.

Suggested Citation

  • Lee, Daeho & Shin, Jungwoo & Lee, Sangwon, 2015. "Network management in the era of convergence: Focusing on application-based quality assessment of Internet access service," Telecommunications Policy, Elsevier, vol. 39(8), pages 705-716.
    • Handle: RePEc:eee:telpol:v:39:y:2015:i:8:p:705-716
    DOI: 10.1016/j.telpol.2015.07.005
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    1. Joel Huber and Kenneth Train., 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Economics Working Papers E00-289, University of California at Berkeley.
    2. Lee, Jongsu & Kim, Yeonbae & Lee, Jeong-Dong & Park, Yuri, 2006. "Estimating the extent of potential competition in the Korean mobile telecommunications market: Switching costs and number portability," International Journal of Industrial Organization, Elsevier, vol. 24(1), pages 107-124, January.
    3. Layton, David F., 2000. "Random Coefficient Models for Stated Preference Surveys," Journal of Environmental Economics and Management, Elsevier, vol. 40(1), pages 21-36, July.
    4. Lee, Daeho & Kim, Yong-Hwa, 2014. "Empirical evidence of network neutrality – The incentives for discrimination," Information Economics and Policy, Elsevier, vol. 29(C), pages 1-9.
    5. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    6. Nakamura, Akihiro, 2010. "Estimating switching costs involved in changing mobile phone carriers in Japan: Evaluation of lock-in factors related to Japan's SIM card locks," Telecommunications Policy, Elsevier, vol. 34(11), pages 736-746, December.
    7. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    8. Gary S. Becker & Dennis W. Carlton & Hal S. Sider, 2010. "Net Neutrality And Consumer Welfare," Journal of Competition Law and Economics, Oxford University Press, vol. 6(3), pages 497-519.
    9. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    10. Saraei, Soudabe & Amini, Amir M., 2012. "A study of service quality in rural ICT renters of Iran by SERVQUAL," Telecommunications Policy, Elsevier, vol. 36(7), pages 571-578.
    11. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    12. Louviere, Jordan J & Hensher, David A, 1983. "Using Discrete Choice Models with Experimental Design Data to Forecast Consumer Demand for a Unique Cultural Event," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(3), pages 348-361, December.
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    Cited by:

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    2. Shin, Jungwoo & Park, Yuri & Lee, Daeho, 2016. "Strategic management of over-the-top services: Focusing on Korean consumer adoption behavior," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 329-337.

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