IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v89y2014icp3-11.html
   My bibliography  Save this article

The effect of new media on consumer media usage: An empirical study in South Korea

Author

Listed:
  • Woo, JongRoul
  • Choi, Jae Young
  • Shin, Jungwoo
  • Lee, Jongsu

Abstract

The advent and proliferation of the Internet (a form of new media) have heavily influenced consumers' media usage behavior and a number of other social, political, cultural, and economic outcomes. The recent introduction of smart mobile media, including smartphones and tablets, is expected to similarly affect these issues. This study empirically analyzes how the advent of the Internet and smart mobile media affects Korean consumers' media usage behavior, seeking to provide a means to anticipate the ripple effect to societal outcomes related to the evolution of new media in Korea. We modeled consumers' media usage behavior and conducted preference and simulation analyses using data gleaned from a survey of consumers' media behavior and a Multiple Discrete-Continuous Extreme Values (MDCEV) model. The results of the analyses illustrate how consumer preferences regarding old and new media differ in terms of socio-demographic variables. Moreover, the analyses revealed that whereas the advent of the Internet has negatively influenced consumers' use of old media, the arrival of smart mobile media has had a synergistic effect on television use. As a result, the advent of mobile media increased the use of television, but decreased use of other forms of old media.

Suggested Citation

  • Woo, JongRoul & Choi, Jae Young & Shin, Jungwoo & Lee, Jongsu, 2014. "The effect of new media on consumer media usage: An empirical study in South Korea," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 3-11.
    • Handle: RePEc:eee:tefoso:v:89:y:2014:i:c:p:3-11
    DOI: 10.1016/j.techfore.2014.09.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162514002583
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2014.09.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen Lin & Sriram Venkataraman & Sandy D. Jap, 2013. "Media Multiplexing Behavior: Implications for Targeting and Media Planning," Marketing Science, INFORMS, vol. 32(2), pages 310-324, March.
    2. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    3. 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.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    5. Bhat, Chandra R. & Sen, Sudeshna, 2006. "Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 35-53, January.
    6. Rajshree Agarwal & A. Edward Day, 1998. "The Impact of the Internet on Economic Education," The Journal of Economic Education, Taylor & Francis Journals, vol. 29(2), pages 99-110, June.
    7. Ahn, Jiwoon & Jeong, Gicheol & Kim, Yeonbae, 2008. "A forecast of household ownership and use of alternative fuel vehicles: A multiple discrete-continuous choice approach," Energy Economics, Elsevier, vol. 30(5), pages 2091-2104, September.
    8. Naik, Prasad A. & Peters, Kay, 2009. "A Hierarchical Marketing Communications Model of Online and Offline Media Synergies," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 288-299.
    9. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
    10. Chen, Peng-Ting & Hsieh, Hsin-Pei, 2012. "Personalized mobile advertising: Its key attributes, trends, and social impact," Technological Forecasting and Social Change, Elsevier, vol. 79(3), pages 543-557.
    11. Robert E. Litan & Alice M. Rivlin, 2001. "Projecting the Economic Impact of the Internet," American Economic Review, American Economic Association, vol. 91(2), pages 313-317, May.
    12. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M. & Yildirim, Gökhan, 2015. "Historical impact of technological change on the US mass media advertising expenditure," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 306-316.
    2. Shin, Jungwoo & Hwang, Won-Sik & Choi, Hyundo, 2019. "Can hydrogen fuel vehicles be a sustainable alternative on vehicle market?: Comparison of electric and hydrogen fuel cell vehicles," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 239-248.
    3. Acharya, Bikram & Marhold, Klaus, 2019. "Determinants of household energy use and fuel switching behavior in Nepal," Energy, Elsevier, vol. 169(C), pages 1132-1138.
    4. Kim, Ju-Hee & Yoo, Seung-Hoon, 2020. "Public perspective on the environmental impacts of sea sand mining: Evidence from a choice experiment in South Korea," Resources Policy, Elsevier, vol. 69(C).
    5. Guoqiang Wu & Jinhyun Hong & Piyushimita Thakuriah, 2022. "Investigating the temporal changes in the relationships between time spent on the internet and non-mandatory activity-travel time use," Transportation, Springer, vol. 49(1), pages 213-235, February.
    6. 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.
    7. Rodrigo J. Tapia & Gerard Jong & Ana M. Larranaga & Helena B. Bettella Cybis, 2021. "Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina," Networks and Spatial Economics, Springer, vol. 21(3), pages 581-608, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kyuho Maeng & Sungmin Ko & Jungwoo Shin & Youngsang Cho, 2020. "How Much Electricity Sharing Will Electric Vehicle Owners Allow from Their Battery? Incorporating Vehicle-to-Grid Technology and Electricity Generation Mix," Energies, MDPI, vol. 13(16), pages 1-25, August.
    2. Shin, Jungwoo & Hwang, Won-Sik & Choi, Hyundo, 2019. "Can hydrogen fuel vehicles be a sustainable alternative on vehicle market?: Comparison of electric and hydrogen fuel cell vehicles," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 239-248.
    3. Jung-Kyu Jung & Jae Young Choi, 2022. "Choice and allocation characteristics of faculty time in Korea: effects of tenure, research performance, and external shock," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2847-2869, May.
    4. Jungwoo Shin & Taehoon Lim & Moo Yeon Kim & Jae Young Choi, 2018. "Can Next-Generation Vehicles Sustainably Survive in the Automobile Market? Evidence from Ex-Ante Market Simulation and Segmentation," Sustainability, MDPI, vol. 10(3), pages 1-16, February.
    5. Huh, Sung-Yoon & Lee, Hyejin & Shin, Jungwoo & Lee, Donghyun & Jang, Jinyoung, 2018. "Inter-fuel substitution path analysis of the korea cement industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 4091-4099.
    6. Rodrigo J. Tapia & Gerard Jong & Ana M. Larranaga & Helena B. Bettella Cybis, 2021. "Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina," Networks and Spatial Economics, Springer, vol. 21(3), pages 581-608, September.
    7. Park, Soyeong & Maeng, Kyuho & Shin, Jungwoo, 2023. "Efficient subsidy distribution for hydrogen fuel cell vehicles based on demand segmentation," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    8. Ahn, Jiwoon & Jeong, Gicheol & Kim, Yeonbae, 2008. "A forecast of household ownership and use of alternative fuel vehicles: A multiple discrete-continuous choice approach," Energy Economics, Elsevier, vol. 30(5), pages 2091-2104, September.
    9. Sikder, Sujan & Pinjari, Abdul Rawoof, 2013. "The benefits of allowing heteroscedastic stochastic distributions in multiple discrete-continuous choice models," Journal of choice modelling, Elsevier, vol. 9(C), pages 39-56.
    10. Byun, Hyunsuk & Shin, Jungwoo & Lee, Chul-Yong, 2018. "Using a discrete choice experiment to predict the penetration possibility of environmentally friendly vehicles," Energy, Elsevier, vol. 144(C), pages 312-321.
    11. Koo, Yoonmo & Kim, Chang Seob & Hong, Junhee & Choi, Ie-Jung & Lee, Jongsu, 2012. "Consumer preferences for automobile energy-efficiency grades," Energy Economics, Elsevier, vol. 34(2), pages 446-451.
    12. Chandra R. Bhat & Subodh K. Dubey & Mohammad Jobair Bin Alam & Waleed H. Khushefati, 2015. "A New Spatial Multiple Discrete-Continuous Modeling Approach To Land Use Change Analysis," Journal of Regional Science, Wiley Blackwell, vol. 55(5), pages 801-841, November.
    13. Bhat, Chandra R. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Aarti C., 2020. "A multiple discrete extreme value choice model with grouped consumption data and unobserved budgets," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 196-222.
    14. Jian, Sisi & Rashidi, Taha Hossein & Dixit, Vinayak, 2017. "An analysis of carsharing vehicle choice and utilization patterns using multiple discrete-continuous extreme value (MDCEV) models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 362-376.
    15. Yuri Park & Hyunnam Kim & Jongsu Lee, 2009. "Model for Studying Commodity Bundling with a Focus on Consumer Preference," TEMEP Discussion Papers 200935, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Nov 2009.
    16. Fang, Hao Audrey, 2008. "A discrete-continuous model of households' vehicle choice and usage, with an application to the effects of residential density," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 736-758, November.
    17. Tapia, Rodrigo J. & de Jong, Gerard & Larranaga, Ana M. & Bettella Cybis, Helena B., 2020. "Application of MDCEV to infrastructure planning in regional freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 255-271.
    18. Acharya, Bikram & Marhold, Klaus, 2019. "Determinants of household energy use and fuel switching behavior in Nepal," Energy, Elsevier, vol. 169(C), pages 1132-1138.
    19. Sabreena Anowar & Naveen Eluru & Luis F. Miranda-Moreno, 2014. "Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 441-473, July.
    20. Acharya, Bikram & Adhikari, Santosh, 2021. "Household energy consumption and adaptation behavior during crisis: Evidence from Indian economic blockade on Nepal," Energy Policy, Elsevier, vol. 148(PB).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:89:y:2014:i:c:p:3-11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.