Stars that shine less bright at night

Bayerl, Andreas ; Stahl, Florian

URN: urn:nbn:de:bsz:180-madoc-623191
Document Type: Conference presentation
Year of publication: 2021
Conference title: EMAC Doctoral Colloquium 2021
Location of the conference venue: Online
Date of the conference: 23.-25.05.2021
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Publication language: English
Institution: Business School > ABWL, Quantitatives Marketing (Stahl 2013-)
Subject: 650 Management
Abstract: Online reviews are ubiquitous these days. Hotels, restaurants, products, services, medical doctors or employers can be rated online. Such online reviews have been shown to significantly influence people’s decision-making processes and are often used as a source of information, for example, when making a dinner reservation, booking a vacation or choosing an employer (for meta-analyses, see Floyd et al. 2014; You et al. 2015; Purnawirawan et al. 2015; Babić Rosario 2016). There are, however, concerns that the User Generated Content (UGC) conveyed in online reviews may be dishonest, forged, or biased. For example, Mayzlin et al. (2014) raise concerns about review fraud and Schoenmueller et al. (2020) point towards a self-selection bias. In this paper, we investigate factors that influence reviewers subconsciously when writing an online review. More specifically, we focus on time (i.e., time-of-the-day and day-of-the-week) as well as weather conditions as potential subconscious influences when reviewing. It may be that satisfied and dissatisfied reviewers differ in their activity and willingness to write a review under certain conditions. For example, dissatisfied reviewers, i.e., reviewers providing a negative (low) rating, may be more inclined during certain days and times to vent their anger or warn other people. Alternatively, reviewers may not select themselves to certain conditions, but are rather exogenously influenced by these conditions. For example, weather conditions could subconsciously affect people in how they write their reviews. Sunny (rainy) days could affect the mood (Schwarz & Clore 1983; Cunningham 1979; Howarth & Hoffman 1984) and thereby subconsciously improve (worsen) an online review.

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ORCID: Bayerl, Andreas ; Stahl, Florian ORCID: 0000-0002-2846-3424

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