Non-numerical and social anchoring in consumer-generated ratings

Yigit Oezcelik and Michel Tolksdorf

No 202319, Working Papers from University of Liverpool, Department of Economics

Abstract: Inaccurate online ratings can be harmful to both consumers and firms. We perform an experiment to assess the effect of the anchoring bias on consumer ratings. Our rating task is a framed variation of the slider task. We diverge from the literature by implementing non-numerical (visual) anchors. We compare three anchoring conditions, with either high, low, or socially derived anchors present, against two control conditions – one without anchors and an unframed slider task. High and socially derived anchors lead to significant overrating compared to both control conditions. We find no difference between low anchors and the control condition without anchors, whereas both exhibit overrating compared with the unframed slider task. Participants place higher trust in socially derived anchors compared with high and low anchors. When there is a social context, the trust participants exhibit towards the socially derived anchors explains the anchoring bias.

Keywords: Anchoring; online ratings; laboratory experiment (search for similar items in EconPapers)
JEL-codes: C91 D80 D91 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2023-12
New Economics Papers: this item is included in nep-cbe, nep-exp and nep-mkt
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Persistent link: https://EconPapers.repec.org/RePEc:liv:livedp:202319

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