Strategizing and Ratings

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Strategizing and Ratings

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Title: Strategizing and Ratings
A multiple-case study on the challenges of online review platforms
Author: Német, Vidor; Jeberg, Sidsel
Abstract: Research on online review platforms is particularly scarce, despite their growing importance in customer decision-making. This dissertation contributes to a better understanding of, how managers strategize in response to the challenges of online review platforms. The findings are based on a multiple-case study of five Danish companies from the managers’ perspective, using primarily interviews as research method; while the research context is mainly the review platform ‘Trustpilot’. The conclusion of the study unites an understanding of how managers make sense of the review platform, how they construct narratives about it and how they react to it, thereby offering a model for the process of their strategizing. The findings show that managers first make sense of how the apparatus of Trustpilot works, what its role is for the customers, what its role is in the industry and what the future tendencies are for review platforms. Based on this, they identify opportunities and challenges. We found that the challenges are all connected to the gap between representation and reality, deriving from the composition of reviewers, algorithmic actions, the subscription offered by the platform, fake reviews and blackmailing with negative reviews. Making sense of the possible roles of Trustpilot in the organization and constructing narratives leads to actions of strategizing. We found that the established theories cannot entirely explain the patterns of reactivity in our case companies. We conclude that this is because research so far, has largely been concentrated on formulaic valuation systems; however, a key difference between formulaic and algorithmic systems directed us towards introducing a new concept. This key difference is that while the rating of a formulaic system is indivisible from the managers’ perspective the rating of an algorithmic system can be decomposed to its constituents; making it possible for managers to show different reactivity to different groups of constituents. We defined a theoretically new pattern of reactivity, a concept we call ‘diverting’; by which we mean having different practices for positive reviews compared to negative reviews in order to decrease the amount of the latter. The dissertation also contributes with practical implications for managers on how to act strategically in connection with Trustpilot.
URI: http://hdl.handle.net/10417/6314
Date: 2019-02-25
Pages: 283 s.
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