“…However, all these nine reviews were in fact positive.14 Specifically, the scenario featured the information that the email with the voucher code had not arrived by email 3 days after the auction had ended causing some anxiety over whether voucher would arrive soon enough for its intended use. The scenario also stated that after one had reached out to the seller, the voucher was received within 1 day.15 This resulted in n = 95/104/99 observations for the treatments with the higher/same/lower price.16 It is also consistent with the findings byBartling et al (2017) and the notion that reviewing customers antagonism is not driven by distributional preferences with respect to a specific seller who benefited from the higher price in the auction.17 The same sequential sales strategy, though not motivated by profit-seeking concerns, can also be employed to prevent (ticket-)scalping(Bhave & Budish, 2017;Courty, 2003;Leslie & Sorensen, 2014;Roth, 2007).18 eBay has tried to prevent such feedback by making it clear that before buyers give a "neutral or negative feedback, they should contact the seller and try to resolve problems" and that such feedback should be "fair and objective" (eBay.de's feedback rules, retrieved and translated from http://pages.ebay.de/help/feedback/howitworks.html at 09.02.2009).19 More details on the used software packages in the Python script, which is part of the paper's data package.20 Maximal p values from using either all observations or only each buyer's first review (independent observations).…”