IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v23y2021i3d10.1007_s10796-020-09980-9.html
   My bibliography  Save this article

Personalize, Summarize or Let them Read? A Study on Online Word of Mouth Strategies and Consumer Decision Process

Author

Listed:
  • Mahesh Balan U

    (Indian Institute of Technology Madras)

  • Saji K. Mathew

    (Indian Institute of Technology Madras)

Abstract

This study integrates theories of task complexity and cognitive stopping rule to understand how complexity of information environment impacts uncertainty, effectiveness and efficiency of consumers’ decision process. Using the reviews provided by an online retailer, we develop an e-commerce environment with three levels of complexity: high with raw textual reviews, medium with attribute-level review summaries and low with web personalization strategy based on attribute preferences extracted from online reviews. In a controlled lab experiment, users took buying decisions under different levels of complexity. Our analyses of clickstream data showed that users’ effectiveness and efficiency were the highest in review based personalized environment. However, between groups who received summarized and textual reviews, the latter demonstrated apparently higher effectiveness and efficiency in decision making, which went against our anticipation. Further investigation showed that users simplified decision process when exposed to raw reviews. These results further inform reviews-based personalization strategy in e-commerce.

Suggested Citation

  • Mahesh Balan U & Saji K. Mathew, 2021. "Personalize, Summarize or Let them Read? A Study on Online Word of Mouth Strategies and Consumer Decision Process," Information Systems Frontiers, Springer, vol. 23(3), pages 627-647, June.
    • Handle: RePEc:spr:infosf:v:23:y:2021:i:3:d:10.1007_s10796-020-09980-9
    DOI: 10.1007/s10796-020-09980-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-020-09980-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-020-09980-9?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. Stigler, George J., 2011. "Economics of Information," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 35-49.
    2. Kar Yan Tam & Shuk Ying Ho, 2005. "Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective," Information Systems Research, INFORMS, vol. 16(3), pages 271-291, September.
    3. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    4. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    5. Shuk Ying Ho & David Bodoff & Kar Yan Tam, 2011. "Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior," Information Systems Research, INFORMS, vol. 22(3), pages 660-679, September.
    6. 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.
    7. 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.
    8. Vinodh Krishnaraju & Saji K Mathew & Vijayan Sugumaran, 2016. "Web personalization for user acceptance of technology: An empirical investigation of E-government services," Information Systems Frontiers, Springer, vol. 18(3), pages 579-595, June.
    9. Smith, Gerald F. & Benson, P. George & Curley, Shawn P., 1991. "Belief, knowledge, and uncertainty: A cognitive perspective on subjective probability," Organizational Behavior and Human Decision Processes, Elsevier, vol. 48(2), pages 291-321, April.
    10. Browne, Glenn J. & Pitts, Mitzi G., 2004. "Stopping rule use during information search in design problems," Organizational Behavior and Human Decision Processes, Elsevier, vol. 95(2), pages 208-224, November.
    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. Meihua Zuo & Spyros Angelopoulos & Zhouyang Liang & Carol X. J. Ou, 2023. "Blazing the Trail: Considering Browsing Path Dependence in Online Service Response Strategy," Information Systems Frontiers, Springer, vol. 25(4), pages 1605-1619, August.

    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. Onesun Steve Yoo & Rakesh Sarin, 2018. "Consumer Choice and Market Outcomes Under Ambiguity in Product Quality," Marketing Science, INFORMS, vol. 37(3), pages 445-468, May.
    2. Nagler Matthew G., 2007. "Understanding the Internet's Relevance to Media Ownership Policy: A Model of Too Many Choices," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 7(1), pages 1-28, June.
    3. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.
    4. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    5. Samek, Anya & Hur, Inkyoung & Kim, Sung-Hee & Yi, Ji Soo, 2016. "An experimental study of the decision process with interactive technology," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 20-32.
    6. Erlend Dancke Sandorf & Danny Campbell, 2019. "Accommodating satisficing behaviour in stated choice experiments," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 46(1), pages 133-162.
    7. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    8. Schunk, Daniel, 2009. "Behavioral heterogeneity in dynamic search situations: Theory and experimental evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 33(9), pages 1719-1738, September.
    9. Nasim Mousavi & Panagiotis Adamopoulos & Jesse Bockstedt, 2023. "The Decoy Effect and Recommendation Systems," Information Systems Research, INFORMS, vol. 34(4), pages 1533-1553, December.
    10. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.
    11. Yabing Jiang & Hong Guo, 2012. "Design of Consumer Review Systems and Product Pricing," Working Papers 12-10, NET Institute.
    12. Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
    13. Andreas Klein, 2011. "Die Entwicklung eines agentenbasierten Basismodells zur Bestimmung der deckungsbeitragsmaximierenden Anzahl von Außendienstmitarbeitern," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 21(2), pages 189-210, January.
    14. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    15. Guha Majumder, Madhumita & Dutta Gupta, Sangita & Paul, Justin, 2022. "Perceived usefulness of online customer reviews: A review mining approach using machine learning & exploratory data analysis," Journal of Business Research, Elsevier, vol. 150(C), pages 147-164.
    16. Clement A. Tisdell, 2017. "Bounded Rationality, Satisficing and the Evolution of Economic Thought," Economic Theory, Applications and Issues Working Papers 264873, University of Queensland, School of Economics.
    17. Pantelis P. Analytis & Amit Kothiyal & Konstantinos Katsikopoulos, 2014. "Multi-attribute utility models as cognitive search engines," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(5), pages 403-419, September.
    18. Boccali, Filippo & Mariani, Marcello M. & Visani, Franco & Mora-Cruz, Alexandra, 2022. "Innovative value-based price assessment in data-rich environments: Leveraging online review analytics through Data Envelopment Analysis to empower managers and entrepreneurs," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    19. Scott Shane, 2001. "Organizational Incentives and Organizational Mortality," Organization Science, INFORMS, vol. 12(2), pages 136-160, April.
    20. repec:cup:judgdm:v:16:y:2021:i:6:p:1324-1369 is not listed on IDEAS
    21. P. Février & L. Wilner, 2012. "Do Consumers Correctly Expect Price Reductions? Testing Dynamic Behavior," Documents de Travail de l'Insee - INSEE Working Papers g2012-03, Institut National de la Statistique et des Etudes Economiques.

    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:spr:infosf:v:23:y:2021:i:3:d:10.1007_s10796-020-09980-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.