A team of researchers with members from several institutions in Spain and Italy has found via experiments with volunteers that a large percentage of people faced with social conflict are motivated by competition. In their paper published in the journal Science Advances, the team describes their experiments, challenges they addressed, and their conclusions.
Scientists who study social behavior have long wondered why people cooperate with one another when engaging in social behavior, given the widespread belief that people are motivated primarily by self-interest. Prior research investigating such behavior has tended to involve engaging volunteers to participate in certain games. Because they typically involve just one type of game at a time, these studies do not allow for observation of behavior during other types of conflicts.
To get around that problem, the researchers asked 541 volunteers to randomly pair up and play four different social games involving conflict—some of games also involved having to choose between keeping quiet or betraying a partner. The researchers then manipulated the games by offering differing amounts of rewards for outcomes.
After the completion of the games, the researchers entered the data into a computer and ran previously developed behavioral algorithms that placed each of the volunteers into one of five categories: Undefined, Trustful, Pessimistic, Optimistic or Envious. The study revealed that roughly a third of the volunteers were categorized as Envious—the most for any category. Volunteers in this group tended not to cooperate with their partners even when it resulted in a reduced reward—the researchers concluded that they tended to value competition more highly than rationality. The next largest groups were people categorized as Optimists or Pessimists—they tended to over- or underestimate what might be driving the behavior of their partners.
The researchers suggest their results offer new insight into the ways that people behave and the decisions they make when tension is added to interactions, which might be useful in a broad range of fields.