{"id":{"repo_id":"middlesex","oai_identifier":"oai:repository.mdx.ac.uk:233y95"},"canonical_url":"https://search.dev.ndltd.org/etd/middlesex/oai:repository.mdx.ac.uk:233y95","repository":{"repo_id":"middlesex","name":"Middlesex University","base_url":"https://repository.mdx.ac.uk/oai2"},"display":{"title":"The effects of reputation on collaboration","abstract":"This study explored how direct and indirect reputations impacted collaboration in an online dictator game. Previous research shows that human participants in dictator games are more generous towards players with a positive reputation. In our study (n = 260), the participant played a multi-round trivia game with three \"agents\" (presented as real players, but they were not): one \"key agent\" and two regular agents. The agents' predetermined behaviours allowed us to isolate their influence on the participant's decision-making process. In certain rounds, an agent was guaranteed to win and received 100 tokens. They then “decided” whether to share the tokens with the participant, imitating an online player's decision. In other rounds, the participant was guaranteed to win and received 100 tokens. They then decided whether to share the tokens with the other player (an agent). After each round, the results of the other matchup and the tokens shared by the victor were displayed in a results section. This allowed the participant to see how the key agent interacted with the regular agents. We measured participant collaboration using the key agent's behaviour in four conditions: generous, selfish, exclusive (generous to the participant, selfish to regular agents), and excluded (selfish to the participant, generous to regular agents). The dependent variable was the mean number of tokens sent to the key agent in the final round. The statistical analysis focused on the difference in the mean number of tokens sent to the key agent across the four conditions. We found that reputation significantly influenced collaboration; participants gave more tokens to the key agent in the generous condition than in the selfish condition. Also, “reputation discounting” occurred between the selfish-exclusive and generous-excluded conditions, but not between the selfish-excluded and generous-exclusive conditions. The results indicate that the participants primarily based their collaborative behaviour on direct reputation, with indirect reputation being less influential on decision-making.","abstract_html":"This study explored how direct and indirect reputations impacted collaboration in an online dictator game. Previous research shows that human participants in dictator games are more generous towards players with a positive reputation. In our study (n = 260), the participant played a multi-round trivia game with three "agents" (presented as real players, but they were not): one "key agent" and two regular agents. The agents' predetermined behaviours allowed us to isolate their influence on the participant's decision-making process. In certain rounds, an agent was guaranteed to win and received 100 tokens. They then “decided” whether to share the tokens with the participant, imitating an online player's decision. In other rounds, the participant was guaranteed to win and received 100 tokens. They then decided whether to share the tokens with the other player (an agent). After each round, the results of the other matchup and the tokens shared by the victor were displayed in a results section. This allowed the participant to see how the key agent interacted with the regular agents. We measured participant collaboration using the key agent's behaviour in four conditions: generous, selfish, exclusive (generous to the participant, selfish to regular agents), and excluded (selfish to the participant, generous to regular agents). The dependent variable was the mean number of tokens sent to the key agent in the final round. The statistical analysis focused on the difference in the mean number of tokens sent to the key agent across the four conditions. We found that reputation significantly influenced collaboration; participants gave more tokens to the key agent in the generous condition than in the selfish condition. Also, “reputation discounting” occurred between the selfish-exclusive and generous-excluded conditions, but not between the selfish-excluded and generous-exclusive conditions. The results indicate that the participants primarily based their collaborative behaviour on direct reputation, with indirect reputation being less influential on decision-making.","abstract_has_math":false,"creators":["Taiwo, K."],"institution":"Middlesex University","degree_name":null,"degree_level":"Masters thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023","date_published":"2023","updated_at":"2026-07-24T03:03:26Z","subjects":["reputation","reputation discounting","dictator game","collaboration"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:repository.mdx.ac.uk:233y95"],"render_values":[{"text":"oai:repository.mdx.ac.uk:233y95","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Taiwo, K."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023"]},{"key":"dc:date.issued","label":"Date","values":["2023"]},{"key":"dc:publisher","label":"Institution","values":["Middlesex University Research Repository"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Psychology","Science and Technology"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Middlesex University"]},{"key":"dc:relation","label":"Dc Relation","values":["https://repository.mdx.ac.uk/item/233y95"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://repository.mdx.ac.uk/item/233y95"]},{"key":"dc:type","label":"Dc Type","values":["Thesis or dissertation"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["reputation","reputation discounting","dictator game","collaboration"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:repository.mdx.ac.uk:233y95"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://repository.mdx.ac.uk/download/99dc3ed0de753e1211ebcb5f17854a8d3b8e4e95fcc69d9073a56d8485c0f40c/6202070/KTaiwo%20thesis.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This study explored how direct and indirect reputations impacted collaboration in an online dictator game. Previous research shows that human participants in dictator games are more generous towards players with a positive reputation. In our study (n = 260), the participant played a multi-round trivia game with three \"agents\" (presented as real players, but they were not): one \"key agent\" and two regular agents. The agents' predetermined behaviours allowed us to isolate their influence on the participant's decision-making process. In certain rounds, an agent was guaranteed to win and received 100 tokens. They then “decided” whether to share the tokens with the participant, imitating an online player's decision. In other rounds, the participant was guaranteed to win and received 100 tokens. They then decided whether to share the tokens with the other player (an agent). After each round, the results of the other matchup and the tokens shared by the victor were displayed in a results section. This allowed the participant to see how the key agent interacted with the regular agents. We measured participant collaboration using the key agent's behaviour in four conditions: generous, selfish, exclusive (generous to the participant, selfish to regular agents), and excluded (selfish to the participant, generous to regular agents). The dependent variable was the mean number of tokens sent to the key agent in the final round. The statistical analysis focused on the difference in the mean number of tokens sent to the key agent across the four conditions. We found that reputation significantly influenced collaboration; participants gave more tokens to the key agent in the generous condition than in the selfish condition. Also, “reputation discounting” occurred between the selfish-exclusive and generous-excluded conditions, but not between the selfish-excluded and generous-exclusive conditions. The results indicate that the participants primarily based their collaborative behaviour on direct reputation, with indirect reputation being less influential on decision-making."]},{"key":"dc:description.abstract","label":"Abstract","values":["This study explored how direct and indirect reputations impacted collaboration in an online dictator game. Previous research shows that human participants in dictator games are more generous towards players with a positive reputation. In our study (n = 260), the participant played a multi-round trivia game with three \"agents\" (presented as real players, but they were not): one \"key agent\" and two regular agents. The agents' predetermined behaviours allowed us to isolate their influence on the participant's decision-making process. In certain rounds, an agent was guaranteed to win and received 100 tokens. They then “decided” whether to share the tokens with the participant, imitating an online player's decision. In other rounds, the participant was guaranteed to win and received 100 tokens. They then decided whether to share the tokens with the other player (an agent). After each round, the results of the other matchup and the tokens shared by the victor were displayed in a results section. This allowed the participant to see how the key agent interacted with the regular agents. We measured participant collaboration using the key agent's behaviour in four conditions: generous, selfish, exclusive (generous to the participant, selfish to regular agents), and excluded (selfish to the participant, generous to regular agents). The dependent variable was the mean number of tokens sent to the key agent in the final round. The statistical analysis focused on the difference in the mean number of tokens sent to the key agent across the four conditions. We found that reputation significantly influenced collaboration; participants gave more tokens to the key agent in the generous condition than in the selfish condition. Also, “reputation discounting” occurred between the selfish-exclusive and generous-excluded conditions, but not between the selfish-excluded and generous-exclusive conditions. The results indicate that the participants primarily based their collaborative behaviour on direct reputation, with indirect reputation being less influential on decision-making."]},{"key":"dc:title","label":"Title","values":["The effects of reputation on collaboration"]}]}],"canonical_facts":{"dc:creator":["Taiwo, K."],"dc:date":["2023"],"dc:date.issued":["2023"],"dc:description":["This study explored how direct and indirect reputations impacted collaboration in an online dictator game. Previous research shows that human participants in dictator games are more generous towards players with a positive reputation. In our study (n = 260), the participant played a multi-round trivia game with three \"agents\" (presented as real players, but they were not): one \"key agent\" and two regular agents. The agents' predetermined behaviours allowed us to isolate their influence on the participant's decision-making process. In certain rounds, an agent was guaranteed to win and received 100 tokens. They then “decided” whether to share the tokens with the participant, imitating an online player's decision. In other rounds, the participant was guaranteed to win and received 100 tokens. They then decided whether to share the tokens with the other player (an agent). After each round, the results of the other matchup and the tokens shared by the victor were displayed in a results section. This allowed the participant to see how the key agent interacted with the regular agents. We measured participant collaboration using the key agent's behaviour in four conditions: generous, selfish, exclusive (generous to the participant, selfish to regular agents), and excluded (selfish to the participant, generous to regular agents). The dependent variable was the mean number of tokens sent to the key agent in the final round. The statistical analysis focused on the difference in the mean number of tokens sent to the key agent across the four conditions. We found that reputation significantly influenced collaboration; participants gave more tokens to the key agent in the generous condition than in the selfish condition. Also, “reputation discounting” occurred between the selfish-exclusive and generous-excluded conditions, but not between the selfish-excluded and generous-exclusive conditions. The results indicate that the participants primarily based their collaborative behaviour on direct reputation, with indirect reputation being less influential on decision-making."],"dc:description.abstract":["This study explored how direct and indirect reputations impacted collaboration in an online dictator game. Previous research shows that human participants in dictator games are more generous towards players with a positive reputation. In our study (n = 260), the participant played a multi-round trivia game with three \"agents\" (presented as real players, but they were not): one \"key agent\" and two regular agents. The agents' predetermined behaviours allowed us to isolate their influence on the participant's decision-making process. In certain rounds, an agent was guaranteed to win and received 100 tokens. They then “decided” whether to share the tokens with the participant, imitating an online player's decision. In other rounds, the participant was guaranteed to win and received 100 tokens. They then decided whether to share the tokens with the other player (an agent). After each round, the results of the other matchup and the tokens shared by the victor were displayed in a results section. This allowed the participant to see how the key agent interacted with the regular agents. We measured participant collaboration using the key agent's behaviour in four conditions: generous, selfish, exclusive (generous to the participant, selfish to regular agents), and excluded (selfish to the participant, generous to regular agents). The dependent variable was the mean number of tokens sent to the key agent in the final round. The statistical analysis focused on the difference in the mean number of tokens sent to the key agent across the four conditions. We found that reputation significantly influenced collaboration; participants gave more tokens to the key agent in the generous condition than in the selfish condition. Also, “reputation discounting” occurred between the selfish-exclusive and generous-excluded conditions, but not between the selfish-excluded and generous-exclusive conditions. The results indicate that the participants primarily based their collaborative behaviour on direct reputation, with indirect reputation being less influential on decision-making."],"dc:identifier":["oai:repository.mdx.ac.uk:233y95"],"dc:identifier.uri":["https://repository.mdx.ac.uk/download/99dc3ed0de753e1211ebcb5f17854a8d3b8e4e95fcc69d9073a56d8485c0f40c/6202070/KTaiwo%20thesis.pdf"],"dc:publisher":["Middlesex University Research Repository"],"dc:publisher.department":["Psychology","Science and Technology"],"dc:publisher.institution":["Middlesex University"],"dc:relation":["https://repository.mdx.ac.uk/item/233y95"],"dc:relation.isreferencedby":["https://repository.mdx.ac.uk/item/233y95"],"dc:subject":["reputation","reputation discounting","dictator game","collaboration"],"dc:title":["The effects of reputation on collaboration"],"dc:type":["Thesis or dissertation"],"dc:type.qualificationlevel":["Masters thesis"]},"updated_at":"2026-07-24T03:03:26Z"}