Big data and personalized pricing
Technological advances introduce the possibility that, in the future, firms will be able to use big-data analysis to discover and offer consumers their individual reservation price (i.e., the highest price each consumer would be willing to pay, given their preferences and available income). This can...
| Главный автор: | |
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| Формат: | Электронный ресурс Статья |
| Язык: | Английский |
| Проверить наличие: | HBZ Gateway |
| Journals Online & Print: | Загрузка...
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| Fernleihe: | Fernleihe für die Fachinformationsdienste |
| Опубликовано: |
Cambridge Univ. Press
2020
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| В: |
Business ethics quarterly
Год: 2020, Том: 30, Выпуск: 1, Страницы: 97-117 |
| Другие ключевые слова: | B
market-failures approach
B consumer fairness B Mass data B personalized pricing B Aufsatz in Zeitschrift B relational equality B Price discrimination |
| Online-ссылка: |
Presumably Free Access Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
| Итог: | Technological advances introduce the possibility that, in the future, firms will be able to use big-data analysis to discover and offer consumers their individual reservation price (i.e., the highest price each consumer would be willing to pay, given their preferences and available income). This can generate some interesting benefits, such as a better state of affairs in terms of equality of both welfare and resources, as well as increased social welfare. However, these benefits are countered by considerations of relational equality. This article takes up the market-failures approach as its basis to demonstrate what is wrong with using big data to personalize prices. The article offers an improvement to the market-failures approach and argues that what is wrong with using big data to personalize prices is that it unfairly undermines consumers’ ability to benefit from the market, which is the very point of having a market. |
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| ISSN: | 2153-3326 |
| Второстепенные работы: | Enthalten in: Business ethics quarterly
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| Persistent identifiers: | DOI: 10.1017/beq.2019.19 |