The Impact of Advancing Technology on Marketing and Academic Research
Academic research in marketing often and rightfully tends to either build on well-established past research topics or follow well-established practices in industry. However, as technology advances, it might be possible to foresee some more enduring trends and focus research on future issues rather than on past issues. One approach would be to study emerging technologies with rapidly declining costs. Each of these emerging technologies spawns myriad applications that have the potential to dramatically impact existing markets. Interesting research topics include the study of the impact of these applications on different market participants (e.g., final consumers, the seller, the seller of complementary services, intermediaries, information providers, competitors, other industries). Research topics also include the optimal structure for products and services, given these new applications, as well as which intermediary should offer particular services. Research topics also include the interactive ability to rapidly customize marketing strategy by identifying individuals at particular points in time and under particular demand conditions. Five of these technologies include enhanced search services, biometrics and smart cards, enhanced computational speed, M-commerce, and GPS tracking.
Volume (Year): 23 (2004)
Issue (Month): 4 ()
|Contact details of provider:|| Postal: 7240 Parkway Drive, Suite 300, Hanover, MD 21076 USA|
Web page: http://www.informs.org/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Toubia, Olivier & Simester, Duncan & Hauser, John & Dahan, Ely, 2003.
"Fast Polyhedral Adaptive Conjoint Estimation,"
4171-01, Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Thomas J. Steenburgh & Andrew Ainslie & Peder Hans Engebretson, 2003. "Massively Categorical Variables: Revealing the Information in Zip Codes," Marketing Science, INFORMS, vol. 22(1), pages 40-57, August.
- Jinhong Xie & Steven M. Shugan, 2001. "Electronic Tickets, Smart Cards, and Online Prepayments: When and How to Advance Sell," Marketing Science, INFORMS, vol. 20(3), pages 219-243, June.
- Jianan Wu & Arvind Rangaswamy, 2003. "A Fuzzy Set Model of Search and Consideration with an Application to an Online Market," Marketing Science, INFORMS, vol. 22(3), pages 411-434, March.
- Amiya Basu & Tridib Mazumdar & S. P. Raj, 2003. "Indirect Network Externality Effects on Product Attributes," Marketing Science, INFORMS, vol. 22(2), pages 209-221, April.
- Eric T. Bradlow & David C. Schmittlein, 2000. "The Little Engines That Could: Modeling the Performance of World Wide Web Search Engines," Marketing Science, INFORMS, vol. 19(1), pages 43-62, June.
- Steven M. Shugan, 2003. "Editorial: Defining Interesting Research Problems," Marketing Science, INFORMS, vol. 22(1), pages 1-15.
- Anthony Dukes & Esther Gal–Or, 2003. "Negotiations and Exclusivity Contracts for Advertising," Marketing Science, INFORMS, vol. 22(2), pages 222-245, November.
- Peter J. Danaher & Isaac W. Wilson & Robert A. Davis, 2003. "A Comparison of Online and Offline Consumer Brand Loyalty," Marketing Science, INFORMS, vol. 22(4), pages 461-476, February.
- Gerard J. Tellis & Stefan Stremersch & Eden Yin, 2003. "The International Takeoff of New Products: The Role of Economics, Culture, and Country Innovativeness," Marketing Science, INFORMS, vol. 22(2), pages 188-208, October.
- Patrali Chatterjee & Donna L. Hoffman & Thomas P. Novak, 2003. "Modeling the Clickstream: Implications for Web-Based Advertising Efforts," Marketing Science, INFORMS, vol. 22(4), pages 520-541, May.
- Gavan J. Fitzsimons & Donald R. Lehmann, 2004. "Reactance to Recommendations: When Unsolicited Advice Yields Contrary Responses," Marketing Science, INFORMS, vol. 23(1), pages 82-94, September.
- Thomas P. Novak & Donna L. Hoffman & Yiu-Fai Yung, 2000. "Measuring the Customer Experience in Online Environments: A Structural Modeling Approach," Marketing Science, INFORMS, vol. 19(1), pages 22-42, May.
When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:23:y:2004:i:4:p:469-475. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc)
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.