IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i15p6185-d392957.html
   My bibliography  Save this article

Behind the Review Curtain: Decomposition of Online Consumer Ratings in Peer-to-Peer Markets

Author

Listed:
  • Daniel Kaimann

    (Department of Management, Faculty of Business Administration and Economics, Paderborn University, Warburger Street 100, 33098 Paderborn, Germany)

Abstract

Peer-to-peer markets are especially suitable for the analysis of online ratings as they represent two-sided markets that match buyers to sellers and thus lead to reduced scope for opportunistic behavior. We decompose the online ratings by focusing on the customer’s decision-making process in a leading peer-to-peer ridesharing platform. Using data from the leading peer-to-peer ridesharing platform BlaBlaCar, we analyze 17,584 users registered between 2004 and 2014 and their online ratings focusing on the decomposition of the explicit determinants reflecting the variance of online ratings. We find clear evidence to suggest that a driver’s attitude towards music, pets, smoking, and conversation has a significantly positive influence on his received online ratings. However, we also show that the interaction of female drivers and their attitude towards pets has a significantly negative effect on average ratings.

Suggested Citation

  • Daniel Kaimann, 2020. "Behind the Review Curtain: Decomposition of Online Consumer Ratings in Peer-to-Peer Markets," Sustainability, MDPI, vol. 12(15), pages 1-17, July.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:15:p:6185-:d:392957
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/15/6185/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/15/6185/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ralf Dewenter & Ulrich Heimeshoff, 2015. "Do expert reviews really drive demand? Evidence from a German car magazine," Applied Economics Letters, Taylor & Francis Journals, vol. 22(14), pages 1150-1153, September.
    2. Jean‐Charles Rochet & Jean Tirole, 2006. "Two‐sided markets: a progress report," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 645-667, September.
    3. Chandrasekaran, Deepa & Arts, Joep W.C. & Tellis, Gerard J. & Frambach, Ruud T., 2013. "Pricing in the international takeoff of new products," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 249-264.
    4. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    5. Jolivet, Grégory & Jullien, Bruno & Postel-Vinay, Fabien, 2016. "Reputation and prices on the e-market: Evidence from a major French platform," International Journal of Industrial Organization, Elsevier, vol. 45(C), pages 59-75.
    6. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    7. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    8. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    9. Park, Sangwon & Nicolau, Juan L., 2017. "Effects of general and particular online hotel ratings," Annals of Tourism Research, Elsevier, vol. 62(C), pages 114-116.
    10. Kulkarni, Gauri & Ratchford, Brian T. & Kannan, P.K., 2012. "The Impact of Online and Offline Information Sources on Automobile Choice Behavior," Journal of Interactive Marketing, Elsevier, vol. 26(3), pages 167-175.
    11. Luís Cabral & Ali Hortaçsu, 2010. "The Dynamics Of Seller Reputation: Evidence From Ebay," Journal of Industrial Economics, Wiley Blackwell, vol. 58(1), pages 54-78, March.
    12. Tutz, Gerhard, 1991. "Sequential models in categorical regression," Computational Statistics & Data Analysis, Elsevier, vol. 11(3), pages 275-295, May.
    13. Basuroy, Suman & Chatterjee, Subimal, 2008. "Fast and frequent: Investigating box office revenues of motion picture sequels," Journal of Business Research, Elsevier, vol. 61(7), pages 798-803, July.
    14. Nicoleta Dospinescu & Octavian Dospinescu & Maria Tatarusanu, 2020. "Analysis of the Influence Factors on the Reputation of Food-Delivery Companies: Evidence from Romania," Sustainability, MDPI, vol. 12(10), pages 1-13, May.
    15. Shapley, L. S. & Shubik, Martin, 1954. "A Method for Evaluating the Distribution of Power in a Committee System," American Political Science Review, Cambridge University Press, vol. 48(3), pages 787-792, September.
    16. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    17. Boyer, Marcel & Dionne, Georges, 1989. "An Empirical Analysis of Moral Hazard and Experience Rating," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 128-134, February.
    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. Dawei Li & Yuchen Song & Dongjie Liu & Qi Cao & Junlan Chen, 2023. "How carpool drivers choose their passengers in Nanjing, China: effects of facial attractiveness and credit," Transportation, Springer, vol. 50(3), pages 929-958, June.

    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. Dominik Gutt, 2018. "In the Eye of the Beholder? Empirically Decomposing Different Economic Implications of the Online Rating Variance," Working Papers Dissertations 40, Paderborn University, Faculty of Business Administration and Economics.
    2. Mingfeng Lin & Yong Liu & Siva Viswanathan, 2018. "Effectiveness of Reputation in Contracting for Customized Production: Evidence from Online Labor Markets," Management Science, INFORMS, vol. 64(1), pages 345-359, January.
    3. Jürgen Neumann & Dominik Gutt & Dennis Kundisch, 2018. "The Traveling Reviewer Problem – Exploring the Relationship between Offline Locations and Online Rating Behavior," Working Papers Dissertations 44, Paderborn University, Faculty of Business Administration and Economics.
    4. 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.
    5. Marchand, André & Hennig-Thurau, Thorsten & Wiertz, Caroline, 2017. "Not all digital word of mouth is created equal: Understanding the respective impact of consumer reviews and microblogs on new product success," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 336-354.
    6. Floyd, Kristopher & Freling, Ryan & Alhoqail, Saad & Cho, Hyun Young & Freling, Traci, 2014. "How Online Product Reviews Affect Retail Sales: A Meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 217-232.
    7. Juan Feng & Xin Li & Xiaoquan (Michael) Zhang, 2019. "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence," Information Systems Research, INFORMS, vol. 30(4), pages 1107-1123, December.
    8. King, Robert Allen & Racherla, Pradeep & Bush, Victoria D., 2014. "What We Know and Don't Know About Online Word-of-Mouth: A Review and Synthesis of the Literature," Journal of Interactive Marketing, Elsevier, vol. 28(3), pages 167-183.
    9. Daniel Kaimann & Joe Cox, 2014. "The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry," Working Papers Dissertations 13, Paderborn University, Faculty of Business Administration and Economics.
    10. Daniel Kaimann & Joe Cox, 2014. "The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry," Working Papers CIE 84, Paderborn University, CIE Center for International Economics.
    11. Tao Lu & May Yuan & Chong (Alex) Wang & Xiaoquan (Michael) Zhang, 2022. "Histogram Distortion Bias in Consumer Choices," Management Science, INFORMS, vol. 68(12), pages 8963-8978, December.
    12. Steffen Zimmermann & Philipp Herrmann & Dennis Kundisch & Barrie R. Nault, 2018. "Decomposing the Variance of Consumer Ratings and the Impact on Price and Demand," Information Systems Research, INFORMS, vol. 29(4), pages 984-1002, December.
    13. Zhen Li & Aoi Shimizu, 2018. "Impact of Online Customer Reviews on Sales Outcomes: An Empirical Study Based on Prospect Theory," The Review of Socionetwork Strategies, Springer, vol. 12(2), pages 135-151, December.
    14. Yabing Jiang & Hong Guo, 2012. "Design of Consumer Review Systems and Product Pricing," Working Papers 12-10, NET Institute.
    15. Pauwels, Koen & Aksehirli, Zeynep & Lackman, Andrew, 2016. "Like the ad or the brand? Marketing stimulates different electronic word-of-mouth content to drive online and offline performance," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 639-655.
    16. Zhuolan Bao & Wenwen Li & Pengzhen Yin & Michael Chau, 2021. "Examining the impact of review tag function on product evaluation and information perception of popular products," Information Systems and e-Business Management, Springer, vol. 19(2), pages 517-539, June.
    17. Hyunwoo Hwangbo & Jonghyuk Kim, 2019. "A Text Mining Approach for Sustainable Performance in the Film Industry," Sustainability, MDPI, vol. 11(11), pages 1-16, June.
    18. Paulo B. Goes & Mingfeng Lin & Ching-man Au Yeung, 2014. "“Popularity Effect” in User-Generated Content: Evidence from Online Product Reviews," Information Systems Research, INFORMS, vol. 25(2), pages 222-238, June.
    19. Yang Liu & Juan Feng & Xiuwu Liao, 2017. "When Online Reviews Meet Sales Volume Information: Is More or Accurate Information Always Better?," Information Systems Research, INFORMS, vol. 28(4), pages 723-743, December.
    20. Farajallah, Mehdi & Hammond, Robert G. & Pénard, Thierry, 2019. "What drives pricing behavior in Peer-to-Peer markets? Evidence from the carsharing platform BlaBlaCar," Information Economics and Policy, Elsevier, vol. 48(C), pages 15-31.

    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:gam:jsusta:v:12:y:2020:i:15:p:6185-:d:392957. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.