---
res:
  bibo_abstract:
  - Aggregation metrics in reputation systems are important for overcoming information
    overload. When using these metrics, technical aggregation functions such as the
    arithmetic mean are implemented to measure the valence of product ratings. However,
    it is unclear whether the implemented aggregation functions match the inherent
    aggregation patterns of customers. In our experiment, we elicit customers' aggregation
    heuristics and contrast these with reference functions. Our findings indicate
    that, overall, the arithmetic mean performs best in comparison with other aggregation
    functions. However, our analysis on an individual level reveals heterogeneous
    aggregation patterns. Major clusters exhibit a binary bias (i.e., an over-weighting
    of moderate ratings and under-weighting of extreme ratings) in combination with
    the arithmetic mean. Minor clusters focus on 1-star ratings or negative (i.e.,
    1-star and 2-star) ratings. Thereby, inherent aggregation patterns are neither
    affected by variation of provided information nor by individual characteristics
    such as experience, risk attitudes, or demographics.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Dirk
      foaf_name: van Straaten, Dirk
      foaf_surname: van Straaten
      foaf_workInfoHomepage: http://www.librecat.org/personId=10311
  - foaf_Person:
      foaf_givenName: Vitalik
      foaf_name: Melnikov, Vitalik
      foaf_surname: Melnikov
      foaf_workInfoHomepage: http://www.librecat.org/personId=58747
  - foaf_Person:
      foaf_givenName: Eyke
      foaf_name: Hüllermeier, Eyke
      foaf_surname: Hüllermeier
      foaf_workInfoHomepage: http://www.librecat.org/personId=48129
  - foaf_Person:
      foaf_givenName: Behnud
      foaf_name: Mir Djawadi, Behnud
      foaf_surname: Mir Djawadi
      foaf_workInfoHomepage: http://www.librecat.org/personId=26032
    orcid: 0000-0002-6271-5912
  - foaf_Person:
      foaf_givenName: René
      foaf_name: Fahr, René
      foaf_surname: Fahr
      foaf_workInfoHomepage: http://www.librecat.org/personId=111
  bibo_volume: 72
  dct_date: 2021^xs_gYear
  dct_language: eng
  dct_title: 'Accounting for Heuristics in Reputation Systems: An Interdisciplinary
    Approach on Aggregation Processes@'
...