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  1. The Role of Ranking Algorithms in Crowdfunding
    Autor*in: Vana, Prasad; Lambrecht, Anja
    Erschienen: [2022]
    Verlag:  SSRN, [S.l.]

    Online platforms, marketplaces and retailers typically use ranking algorithms to determine the order in which hundreds or thousands of choices are presented to consumers. While ranking algorithms may aid consumer choice, there are concerns they may... mehr

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    Verlag (kostenfrei)
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    Standort:
    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
    Fernleihe:
    keine Fernleihe

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Fernleihe:
    keine Fernleihe

     

    Online platforms, marketplaces and retailers typically use ranking algorithms to determine the order in which hundreds or thousands of choices are presented to consumers. While ranking algorithms may aid consumer choice, there are concerns they may also lead to socially undesirable outcomes. In this research, we ask two questions. First, we examine the impact of ranking algorithms on consumer choice and the degree to which researchers may obtain biased estimates of preferences if abstracting from the algorithmic code or the rank order of search results. Second, we ask whether ranking algorithms can further socially desirable outcomes. We use data and the ranking algorithm obtained from the US educational crowdfunding website DonorsChoose and develop a structural model of donors’ contributions using a multiple discrete continuous choice framework. We demonstrate that not accounting for the ranking algorithm leads to a systematic bias in estimated consumer preferences. In two sets of counterfactuals, we then test how well DonorsChoose’s algorithm serves its objectives to both benefit disadvantaged groups and achieve a high rate of project completion. First, we show that removing the parameters from the algorithm that prioritize projects from high and highest poverty schools reduces contributions to such schools by 12.98 percentage points. Second, we find that the inclusion of parameters designed to increase the number of projects that succeed on the platform do not substantially affect overall contributions to projects from schools with high and highest poverty. To the ongoing debate about algorithmic bias, we add empirical evidence that algorithms can positively affect disadvantaged groups without compromising a platform’s overall goals

     
    Export in Literaturverwaltung   RIS-Format
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    Schriftenreihe: Tuck School of Business Working Paper ; No. 4132785
    Schlagworte: crowdfunding; algorithms; multiple discrete continuous models; structural models
    Umfang: 1 Online-Ressource (49 p)
    Bemerkung(en):

    Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 31, 2022 erstellt
  2. Online reviews
    star ratings, position effects and purchase likelihood
    Autor*in: Vana, Prasad; Lambrecht, Anja
    Erschienen: 8 May 2018
    Verlag:  [Tuck School of Business at Dartmouth], [Hanover, NH]

    Online product reviews constitute a powerful source of information for consumers. Past research has studied the effect of aggregate measures of reviews (such as, average product rating and number of reviews) on consumer behaviour. In this study, we... mehr

    Zugang:
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)

    Standort:
    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
    Fernleihe:
    keine Fernleihe

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    Keine Speicherung
    Fernleihe:
    keine Fernleihe

     

    Online product reviews constitute a powerful source of information for consumers. Past research has studied the effect of aggregate measures of reviews (such as, average product rating and number of reviews) on consumer behaviour. In this study, we investigate how individual reviews displayed on a product webpage affect consumers' purchase likelihood. Identifying this effect is challenging because retailers are free to select which reviews to display on the product page and in what order, making the display of reviews in particular positions potentially endogenous. We address this challenge by utilizing an empirical context where the retailer displays reviews by recency and exploit the variation in review positions generated as newer reviews are added on top of older ones. We find that individual reviews have a strong effect on consumer purchase decisions. These effects are particularly pronounced when individual reviews contrast with the aggregate information that is instantly available on the product page or help consumers resolve uncertainty about the product

     
    Export in Literaturverwaltung   RIS-Format
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    Hinweise zum Inhalt
    Volltext (kostenfrei)
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    Schriftenreihe: [Tuck School of Business working paper ; no. 3108086]
    Umfang: 1 Online-Ressource (circa 47 Seiten), Illustrationen