Rational behavior in decision making. A comparison between humans, computers and fast and frugal strategies

Rational behavior in decision making. A comparison between humans, computers, and fast and frugal strategies Chris Snijders and Frits Tazelaar (Eindhoven University of Technology, The Netherlands) Real life decisions often have to be made in "noisy" circumstances: not all crucial information is available, some of the information that is available is redundant, and it is usually far from obvious how to sensibly combine the useful information that is there. Under such circum- stances, the average human is not likely to make correct decisions. There are several theories or ideas as to how one might make good decisions, even under circumstances that are noisy. One idea is that, typically, humans acquire experience over time. Through experience people learn, perhaps even without being aware of it, which bits of information are important and how to combine them. A second stream of thought suggests that in such noisy circum- stances, it is better to use computer models to make a decision (this idea has been popularized by Meehl). Computer models are insensitive to useless information and are able, given enough input from previous similar decisions, to accurately infer what the best decision under particular circum- stances is. A third stream of thought suggests that humans tend to use simple decision- strategies to deal with complex and noisy information, and moreover that these strategies are remarkably accurate (Gigerenzer's "fast and frugal strategies"). We set out to compare these three kinds of decision making: experts, computer models, and fast and frugal strategies, in a set of seven experiments based on real-world data regarding purchasing decisions in organizations

Do you trust? Whom do you trust? When do you trust?

We try to provide a broader view on the factors that infiuence the decision to trust and honor trust. Using the "Trust Game" as our experimental paradigm, we consider three classes offactors that may he related to trust issues. The first one considers individual differences with regard to the probability to trust others (and honor frust of others), or disposilion factors. Which kinds of people are more likely to trust? Second, we examine who is more likely to he trusted (anticipation factors), focusing on tile appearance of the person who is to he trusted. And third, we analyze the circumstances under which trust is more likely to evolve (silualion faclors)

Rebuilding trust in online shops on consumer review sites : sellers’ responses to user-generated complaints

How do online shops re-build trust on consumer-generated review sites after customers accuse them of misbehaving? Theories suggest that the effectiveness of responses depends on the type of accusation, yet online research indicates that apologies are superior to denials regardless of the type of accusation. We argue that customers are suspicious about online sellers, making denials implausible and ineffective in re-building trust. A good reputation may mitigate suspicion, making denials more believable and restoring trust. An experiment employed mock-ups of consumer review sites featuring different forms of consumers’ complaints and shops’ responses. Although reputable online shops were regarded as more trustworthy, results confirmed that denials tended not to be believed and did not re-build trust. Apologies generated superior effects