IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v17y2006i4p425-439.html
   My bibliography  Save this article

Research Note: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites

Author

Listed:
  • Nanda Kumar

    (Baruch College, City University of New York, 55 Lexington Avenue, Box B11-220, New York, New York 10010)

  • Izak Benbasat

    (Sauder School of Business, University of British Columbia, Vancouver, Canada V6T 1Z2)

Abstract

Recommendations and consumer reviews are universally acknowledged as significant features of a business-to-consumer website. However, because of the well-documented obstacles to measuring the causal impact of these artifacts, there is still a lack of empirical evidence demonstrating their influence on two important outcome variables in the shopping context: perceived usefulness and social presence. To test the existence of a causal link between information technology (IT)-enabled support for the provision of recommendations and consumer reviews on the usefulness and social presence of the website, this study employs a novel approach to generate the experimental conditions by filtering the content of Amazon.com in real time. The results show that the provision of recommendations and consumer reviews increases both the usefulness and social presence of the website.

Suggested Citation

  • Nanda Kumar & Izak Benbasat, 2006. "Research Note: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites," Information Systems Research, INFORMS, vol. 17(4), pages 425-439, December.
    • Handle: RePEc:inm:orisre:v:17:y:2006:i:4:p:425-439
    DOI: 10.1287/isre.1060.0107
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.1060.0107
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.1060.0107?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
    ---><---

    References listed on IDEAS

    as
    1. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    2. Gronroos, Christian, 1990. "Relationship approach to marketing in service contexts: The marketing and organizational behavior interface," Journal of Business Research, Elsevier, vol. 20(1), pages 3-11, January.
    3. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
    Full references (including those not matched with items on IDEAS)

    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. Ana Alina Tudoran, 2022. "A machine learning approach to identifying decision-making styles for managing customer relationships," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 351-374, March.
    2. Aby Abraham & Sanjay Patro, 2014. "‘Country-of-Origin’ Effect and Consumer Decision-making," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 39(3), pages 309-318, August.
    3. Barney Tan & Cheng Yi & Hock C. Chan, 2015. "Research Note—Deliberation Without Attention: The Latent Benefits of Distracting Website Features for Online Purchase Decisions," Information Systems Research, INFORMS, vol. 26(2), pages 437-455, June.
    4. Abastante, Francesca & Corrente, Salvatore & Greco, Salvatore & Ishizaka, Alessio & Lami, Isabella M., 2018. "Choice architecture for architecture choices: Evaluating social housing initiatives putting together a parsimonious AHP methodology and the Choquet integral," Land Use Policy, Elsevier, vol. 78(C), pages 748-762.
    5. Gottschalk, Sabrina A. & Mafael, Alexander, 2017. "Cutting Through the Online Review Jungle — Investigating Selective eWOM Processing," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 89-104.
    6. Yi, Sangyoon & Kim, Dongyeon & Ju, Jaehyeon, 2022. "Recommendation technologies and consumption diversity: An experimental study on product recommendations, consumer search, and sales diversity," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    7. Murray, Kyle B. & Häubl, Gerald, 2009. "Personalization without Interrogation: Towards more Effective Interactions between Consumers and Feature-Based Recommendation Agents," Journal of Interactive Marketing, Elsevier, vol. 23(2), pages 138-146.
    8. Dongwon Lee & Anandasivam Gopal & Sung-Hyuk Park, 2020. "Different but Equal? A Field Experiment on the Impact of Recommendation Systems on Mobile and Personal Computer Channels in Retail," Information Systems Research, INFORMS, vol. 31(3), pages 892-912, September.
    9. Überschaer, Anja & Baum, Matthias, 2020. "Top employer awards: A double-edged sword?," European Management Journal, Elsevier, vol. 38(1), pages 146-156.
    10. Chang, Woondeog & Park, Jungkun, 2024. "A comparative study on the effect of ChatGPT recommendation and AI recommender systems on the formation of a consideration set," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    11. Tianshi Li & Wenli Li & Yuqing Zhao & Jingpei Ma, 2023. "Rationality manipulation during consumer decision-making process: an analysis of Alibaba’s online shopping carnival," Electronic Commerce Research, Springer, vol. 23(1), pages 331-364, March.
    12. Cheng Yi & Zhenhui (Jack) Jiang & Izak Benbasat, 2017. "Designing for Diagnosticity and Serendipity: An Investigation of Social Product-Search Mechanisms," Information Systems Research, INFORMS, vol. 28(2), pages 413-429, June.
    13. Torgler, Benno & Schneider, Friedrich & Schaltegger, Christoph A., 2007. "With or Against the People? The Impact of a Bottom-Up Approach on Tax Morale and the Shadow Economy," Berkeley Olin Program in Law & Economics, Working Paper Series qt6331x6vz, Berkeley Olin Program in Law & Economics.
    14. März, Armin & Lachner, Michael & Heumann, Christian G. & Schumann, Jan H. & von Wangenheim, Florian, 2021. "How You Remind Me! The Influence of Mobile Push Notifications on Success Rates in Last-Minute Bidding," Journal of Interactive Marketing, Elsevier, vol. 54(C), pages 11-24.
    15. Christina Leuker & Thorsten Pachur & Ralph Hertwig & Timothy J. Pleskac, 2019. "Do people exploit risk–reward structures to simplify information processing in risky choice?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 76-94, August.
    16. Ranganathan, Kavitha & Lejarraga, Tomás, 2021. "Elicitation of risk preferences through satisficing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    17. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.
    18. Shi, Yi & Deng, Yawen & Wang, Guoan & Xu, Jiuping, 2020. "Stackelberg equilibrium-based eco-economic approach for sustainable development of kitchen waste disposal with subsidy policy: A case study from China," Energy, Elsevier, vol. 196(C).
    19. Lawrence Bunnell & Kweku-Muata Osei-Bryson & Victoria Y. Yoon, 0. "RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers," Information Systems Frontiers, Springer, vol. 0, pages 1-42.
    20. da Silveira, Jaylson Jair & Lima, Gilberto Tadeu, 2021. "Wage inequality as a source of endogenous macroeconomic fluctuations," Structural Change and Economic Dynamics, Elsevier, vol. 56(C), pages 35-52.

    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:inm:orisre:v:17:y:2006:i:4:p:425-439. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.