IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v64y2011i11p1183-1189.html
   My bibliography  Save this article

Investigating the roles of online buzz for new product diffusion and its cross-country dynamics

Author

Listed:
  • Chung, Jaihak

Abstract

This research investigates the roles of online buzz activities in influencing the speed and scope of new product diffusion and also the interactive dynamics of online buzz activities within and across countries. This study applies a diffusion model with two latent adopters and a log linear model to monthly sales and online messages collected from major online communication sites in five different countries. The empirical study evaluates two different roles of online buzz: (1) accelerating the new product diffusion process by influencing imitation tendency; and (2) expanding potential market size. In addition, the empirical study shows the interactive dynamics of online buzz activities within and across countries, and provides some information on what encourages online buzz activities, and how they interact with each other within a country and across countries.

Suggested Citation

  • Chung, Jaihak, 2011. "Investigating the roles of online buzz for new product diffusion and its cross-country dynamics," Journal of Business Research, Elsevier, vol. 64(11), pages 1183-1189.
    • Handle: RePEc:eee:jbrese:v:64:y:2011:i:11:p:1183-1189
    DOI: 10.1016/j.jbusres.2011.06.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296311002074
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2011.06.020?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. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. Christophe Van den Bulte & Yogesh V. Joshi, 2007. "New Product Diffusion with Influentials and Imitators," Marketing Science, INFORMS, vol. 26(3), pages 400-421, 05-06.
    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. Shi, Xiaohui & Li, Feng & Bigdeli, Ali Ziaee, 2016. "An examination of NPD models in the context of business models," Journal of Business Research, Elsevier, vol. 69(7), pages 2541-2550.
    2. Jang, Seongsoo & Chung, Jaihak & Rao, Vithala R., 2021. "The importance of functional and emotional content in online consumer reviews for product sales: Evidence from the mobile gaming market," Journal of Business Research, Elsevier, vol. 130(C), pages 583-593.
    3. Aleksandar Bradic, 2012. "The Role of Social Feedback in Financing of Technology Ventures," Papers 1301.2196, arXiv.org.
    4. Gobinda Roy & Biplab Datta & Rituparna Basu, 2017. "Effect of eWOM Valence on Online Retail Sales," Global Business Review, International Management Institute, vol. 18(1), pages 198-209, February.
    5. Duan, Hongbo & Zhang, Gupeng & Wang, Shouyang & Fan, Ying, 2018. "Peer interaction and learning: Cross-country diffusion of solar photovoltaic technology," Journal of Business Research, Elsevier, vol. 89(C), pages 57-66.
    6. Bo-Seong Yun & Sang-Gun Lee & Yaichi Aoshima, 2019. "An analysis of the trilemma phenomenon for Apple iPhone and Samsung Galaxy," Service Business, Springer;Pan-Pacific Business Association, vol. 13(4), pages 779-812, December.

    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. Grant Miller & A. Mushfiq Mobarak, 2015. "Learning About New Technologies Through Social Networks: Experimental Evidence on Nontraditional Stoves in Bangladesh," Marketing Science, INFORMS, vol. 34(4), pages 480-499, July.
    2. Jing Wang & Anocha Aribarg & Yves F. Atchadé, 2013. "Modeling Choice Interdependence in a Social Network," Marketing Science, INFORMS, vol. 32(6), pages 977-997, November.
    3. Olivier Toubia & Jacob Goldenberg & Rosanna Garcia, 2014. "Improving Penetration Forecasts Using Social Interactions Data," Management Science, INFORMS, vol. 60(12), pages 3049-3066, December.
    4. Sebastian Schneider & Frank Huber, 2022. "You paid what!? Understanding price-related word-of-mouth and price perception among opinion leaders and innovators," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 64-80, February.
    5. Florian Probst & Laura Grosswiele & Regina Pfleger, 2013. "Who will lead and who will follow: Identifying Influential Users in Online Social Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(3), pages 179-193, June.
    6. Peter Zubcsek & Miklos Sarvary, 2011. "Advertising to a social network," Quantitative Marketing and Economics (QME), Springer, vol. 9(1), pages 71-107, March.
    7. Inyoung Chae & Andrew T. Stephen & Yakov Bart & Dai Yao, 2017. "Spillover Effects in Seeded Word-of-Mouth Marketing Campaigns," Marketing Science, INFORMS, vol. 36(1), pages 89-104, January.
    8. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    9. Vakratsas, Demetrios & Kolsarici, Ceren, 2008. "A dual-market diffusion model for a new prescription pharmaceutical," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 282-293.
    10. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    11. Sang-Gun Lee & Eui-bang Lee & Chang-Gyu Yang, 2014. "Strategies for ICT product diffusion: the case of the Korean mobile communications market," Service Business, Springer;Pan-Pacific Business Association, vol. 8(1), pages 65-81, March.
    12. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    13. Chaab, Jafar & Salhab, Rabih & Zaccour, Georges, 2022. "Dynamic pricing and advertising in the presence of strategic consumers and social contagion: A mean-field game approach," Omega, Elsevier, vol. 109(C).
    14. L. Lucchio & G. Modanese, 2024. "Diffusion on assortative networks: from mean-field to agent-based, via Newman rewiring," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(10), pages 1-15, October.
    15. Antonio Ladrón-de-Guevara & William Putsis, 2015. "Multi-Market, Multi-Product New Product Diffusion: Decomposing Local, Foreign, and Indirect (Cross-Product) Effects," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 57-70, March.
    16. Tolotti, Marco & Yepez, Jorge, 2020. "Hotelling-Bertrand duopoly competition under firm-specific network effects," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 105-128.
    17. Franses, Philip Hans, 2021. "Modeling box office revenues of motion pictures✰," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    18. Beck, Jonathan, 2008. "Diderot´s rule," Discussion Papers, Research Unit: Competition and Innovation SP II 2008-13, WZB Berlin Social Science Center.
    19. Yair Orbach & Gila Fruchter, 2014. "Predicting product life cycle patterns," Marketing Letters, Springer, vol. 25(1), pages 37-52, March.
    20. Xueming Luo, 2009. "Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flows and Stock Prices," Marketing Science, INFORMS, vol. 28(1), pages 148-165, 01-02.

    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:jbrese:v:64:y:2011:i:11:p:1183-1189. 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.elsevier.com/locate/jbusres .

    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.