IDEAS home Printed from https://ideas.repec.org/a/spr/elmark/v32y2022i3d10.1007_s12525-022-00549-9.html
   My bibliography  Save this article

Explaining consumer suspicion: insights of a vignette study on online product reviews

Author

Listed:
  • Tim Kollmer

    (Universität Innsbruck)

  • Andreas Eckhardt

    (Universität Innsbruck)

  • Victoria Reibenspiess

    (Carson College of Business)

Abstract

As part of the online product and service selection and purchase process, many consumers consult and rely on online product reviews. In order to persuade potential customers to buy their products, many organizations and businesses post deceptive product reviews of their own products on their own or third-party websites to their advantage. This creates consumer suspicion about the authenticity and veracity of online product reviews. To better understand how consumers’ experiences of having been deceived by deceptive online product reviews in the past and the density of deception characteristics in an online product review influence their level of suspicion about the review and, ultimately, their intention to buy the product, we conduct a 3 × 3 vignette study. Our results indicate that deceptive characteristics in online product reviews and prior encounters with deception in online marketplaces increase consumer suspicion. Furthermore, we show that preference for a specific product decreases consumer suspicion about reviews of that product. Lastly, we demonstrate that consumer suspicion towards a product decreases purchase intention.

Suggested Citation

  • Tim Kollmer & Andreas Eckhardt & Victoria Reibenspiess, 2022. "Explaining consumer suspicion: insights of a vignette study on online product reviews," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1221-1238, September.
    • Handle: RePEc:spr:elmark:v:32:y:2022:i:3:d:10.1007_s12525-022-00549-9
    DOI: 10.1007/s12525-022-00549-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12525-022-00549-9
    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/s12525-022-00549-9?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. Young Kwark & Jianqing Chen & Srinivasan Raghunathan, 2014. "Online Product Reviews: Implications for Retailers and Competing Manufacturers," Information Systems Research, INFORMS, vol. 25(1), pages 93-110, March.
    2. Christie M. Fuller & David P. Biros & Judee Burgoon & Jay Nunamaker, 2013. "An Examination and Validation of Linguistic Constructs for Studying High-Stakes Deception," Group Decision and Negotiation, Springer, vol. 22(1), pages 117-134, January.
    3. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    4. Reo Song & Ho Kim & Gene Moo Lee & Sungha Jang, 2019. "Does Deceptive Marketing Pay? The Evolution of Consumer Sentiment Surrounding a Pseudo-Product-Harm Crisis," Journal of Business Ethics, Springer, vol. 158(3), pages 743-761, September.
    5. Liu, Angela Xia & Xie, Ying & Zhang, Jurui, 2019. "It's Not Just What You Say, But How You Say It: The Effect of Language Style Matching on Perceived Quality of Consumer Reviews," Journal of Interactive Marketing, Elsevier, vol. 46(C), pages 70-86.
    6. Friestad, Marian & Wright, Peter, 1994. "The Persuasion Knowledge Model: How People Cope with Persuasion Attempts," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 1-31, June.
    7. Plotkina, Daria & Munzel, Andreas & Pallud, Jessie, 2020. "Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews," Journal of Business Research, Elsevier, vol. 109(C), pages 511-523.
    8. Zhuang, Mengzhou & Cui, Geng & Peng, Ling, 2018. "Manufactured opinions: The effect of manipulating online product reviews," Journal of Business Research, Elsevier, vol. 87(C), pages 24-35.
    9. Oza, Shweta S. & Srivastava, Joydeep & Koukova, Nevena T., 2010. "How suspicion mitigates the effect of influence tactics," Organizational Behavior and Human Decision Processes, Elsevier, vol. 112(1), pages 1-10, May.
    10. Kavita Krishnan & Yun Wan, 2021. "The Detection of Fake Reviews in Bestselling Books: Exploration and Findings," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 19(4), pages 64-79, October.
    11. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2014. "Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue," Management Science, INFORMS, vol. 60(7), pages 1632-1654, July.
    12. Daria Plotkina & Andreas Munzel & Jessie Pallud, 2020. "Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews," Post-Print hal-02423585, HAL.
    13. Vamsi Vallurupalli & Indranil Bose, 2020. "Exploring thematic composition of online reviews: A topic modeling approach," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 791-804, December.
    14. Robert Zinko & Paul Stolk & Zhan Furner & Brad Almond, 2020. "A picture is worth a thousand words: how images influence information quality and information load in online reviews," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 775-789, December.
    15. Ansari, Sana & Gupta, Sumeet, 2021. "Customer perception of the deceptiveness of online product reviews: A speech act theory perspective," International Journal of Information Management, Elsevier, vol. 57(C).
    16. Joachim Büschken & Greg M. Allenby, 2016. "Sentence-Based Text Analysis for Customer Reviews," Marketing Science, INFORMS, vol. 35(6), pages 953-975, November.
    17. Lina Zhou & Yu-wei Sung & Dongsong Zhang, 2013. "Deception Performance in Online Group Negotiation and Decision Making: The Effects of Deception Experience and Deception Skill," Group Decision and Negotiation, Springer, vol. 22(1), pages 153-172, January.
    18. Theodoros Lappas & Gaurav Sabnis & Georgios Valkanas, 2016. "The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry," Information Systems Research, INFORMS, vol. 27(4), pages 940-961, December.
    19. Petrescu, Maria & O’Leary, Kathleen & Goldring, Deborah & Ben Mrad, Selima, 2018. "Incentivized reviews: Promising the moon for a few stars," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 288-295.
    20. Michael Luca & Georgios Zervas, 2016. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Management Science, INFORMS, vol. 62(12), pages 3412-3427, December.
    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. Rainer Alt, 2022. "Electronic Markets on platform culture," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1019-1031, 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. Harrison-Walker, L. Jean & Jiang, Ying, 2023. "Suspicion of online product reviews as fake: Cues and consequences," Journal of Business Research, Elsevier, vol. 160(C).
    2. Li, Yuanshuo & Zhang, Zili & Pedersen, Susanne & Liu, Xudong & Zhang, Ziqiong, 2023. "The influence of relative popularity on negative fake reviews: A case study on restaurant reviews," Journal of Business Research, Elsevier, vol. 162(C).
    3. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Kumar, Ajay & Lu Wang, Cheng & Gupta, Shivam, 2023. "Impacts of consumer cognitive process to ascertain online fake review: A cognitive dissonance theory approach," Journal of Business Research, Elsevier, vol. 154(C).
    4. Wen Zhang & Qiang Wang & Jian Li & Zhenzhong Ma & Gokul Bhandari & Rui Peng, 2023. "What makes deceptive online reviews? A linguistic analysis perspective," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    5. Marios Kokkodis & Theodoros Lappas, 2020. "Your Hometown Matters: Popularity-Difference Bias in Online Reputation Platforms," Information Systems Research, INFORMS, vol. 31(2), pages 412-430, June.
    6. Banerjee, Snehasish & Chua, Alton Y.K., 2023. "Understanding online fake review production strategies," Journal of Business Research, Elsevier, vol. 156(C).
    7. Wu, Ruhai & Qiu, Chun, 2023. "When Karma strikes back: A model of seller manipulation of consumer reviews in an online marketplace," Journal of Business Research, Elsevier, vol. 155(PB).
    8. Guo, Qiaozhen & Chen, Ying-Ju & Huang, Wei, 2022. "Dynamic pricing of new experience products with dual-channel social learning and online review manipulations," Omega, Elsevier, vol. 109(C).
    9. Koukova, Nevena T. & Wang, Rebecca Jen-Hui & Isaac, Mathew S., 2023. "“If you loved our product”: Do conditional review requests harm retailer loyalty?," Journal of Retailing, Elsevier, vol. 99(1), pages 85-101.
    10. 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.
    11. Zhuang, Mengzhou & Cui, Geng & Peng, Ling, 2018. "Manufactured opinions: The effect of manipulating online product reviews," Journal of Business Research, Elsevier, vol. 87(C), pages 24-35.
    12. Xuying Zhao & Hong Guo & Gangshu Cai & Subhajyoti Bandyopadhyay, 2021. "The Role of Expectation–Reality Discrepancy in Service Contracts," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4160-4175, November.
    13. Theodoros Lappas & Gaurav Sabnis & Georgios Valkanas, 2016. "The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry," Information Systems Research, INFORMS, vol. 27(4), pages 940-961, December.
    14. Cheng Zhao & Chong Alex Wang, 2023. "A cross-site comparison of online review manipulation using Benford’s law," Electronic Commerce Research, Springer, vol. 23(1), pages 365-406, March.
    15. Jürgen Neumann, 2021. "When Biased Ratings Benefit the Consumer - An Economic Analysis of Online Ratings in Markets with Variety-Seeking Consumers," Working Papers Dissertations 77, Paderborn University, Faculty of Business Administration and Economics.
    16. Young Kwark & Gene Moo Lee & Paul A. Pavlou & Liangfei Qiu, 2021. "On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data," Information Systems Research, INFORMS, vol. 32(3), pages 895-913, September.
    17. Zaman, Mustafeed & Vo-Thanh, Tan & Nguyen, Chi T.K. & Hasan, Rajibul & Akter, Shahriar & Mariani, Marcello & Hikkerova, Lubica, 2023. "Motives for posting fake reviews: Evidence from a cross-cultural comparison," Journal of Business Research, Elsevier, vol. 154(C).
    18. Uttara M. Ananthakrishnan & Beibei Li & Michael D. Smith, 2020. "A Tangled Web: Should Online Review Portals Display Fraudulent Reviews?," Information Systems Research, INFORMS, vol. 31(3), pages 950-971, September.
    19. Petrescu, Maria & Ajjan, Haya & Harrison, Dana L., 2023. "Man vs machine – Detecting deception in online reviews," Journal of Business Research, Elsevier, vol. 154(C).
    20. Costa Filho, Murilo & Nogueira Rafael, Diego & Salmonson Guimarães Barros, Lucia & Mesquita, Eduardo, 2023. "Mind the fake reviews! Protecting consumers from deception through persuasion knowledge acquisition," Journal of Business Research, Elsevier, vol. 156(C).

    More about this item

    Keywords

    Product reviews; Online purchasing behavior; Deception; Suspicion; Vignette study;
    All these keywords.

    JEL classification:

    • M1 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration

    Statistics

    Access and download statistics

    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:elmark:v:32:y:2022:i:3:d:10.1007_s12525-022-00549-9. 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.