With an increasing number of technologies supporting transactions over distance and replacing traditional forms of interaction, designing for trust has become a core concern for researchers in both HCI and CMC. While much research focuses on increasing trust in mediated interactions, this paper takes a systemic view to identify the factors that support trustworthy behavior. In a second step, we analyze how the presence of these factors can be signaled to allow the formation of well-placed trust. For our analysis we draw on relevant research from sociology, economics, and psychology, as well as empirical findings in HCI and CMC research. The key factors that warrant trust in another actor are contextual properties (temporal, social, and institutional embeddedness) and the trusted actor's intrinsic properties (ability and motivation). In first interactions, trust is mainly warranted by contextual properties, as they provide external incentives and threat of punishment. As interactions are repeated over time and trust grows, intrinsic properties become more important. To increase the level of well-placed trust, researchers and designers need to identify signals for the presence of such trust-warranting properties that are reliable and easy to interpret. At the same time, they must be cheap to emit for actors whose actions are governed by them but costly to mimic for untrustworthy actors. Our analysis provides a frame of reference for the design of studies on trust in technology-mediated exchanges, as well as a guide for identifying trust requirements in design processes. We demonstrate application of the model in three scenarios: ecommerce, voice-enabled online gaming, and ambient technologies.

In a typical probability learning task participants are presented with a repeated choice between two response alternatives, one of which has a higher payoff probability than the other. Rational choice theory requires that participants should eventually allocate all their responses to the high-payoff alternative, but previous research has found that people fail to maximize their payoffs. Instead, it is commonly observed that people match their response probabilities to the payoff probabilities. We report three experiments on this choice anomaly using a simple probability learning task in which participants were provided with (i) large financial incentives, (ii) meaningful and regular feedback, and (iii) extensive training. In each experiment large proportions of participants adopted the optimal response strategy and all three of the factors mentioned above contributed to this. The results are supportive of rational choice theory. Copyright # 2002 John Wiley & Sons, Ltd.key words probability matching; maximization; choice; rationality; feedback; payoffs; learning; reinforcement A striking violation of rational choice theory is commonly observed in simple repeated binary choice tasks in which a payoff is available with higher probability given one response than another. In such tasks people often tend to 'match' probabilities: That is, they allocate their responses to the two options in proportion to their relative payoff probabilities. Thus suppose that a monetary payoff of fixed size is given with probability p ¼ 0.7 for choosing left and with probability 1 À p ¼ 0.3 for choosing right. Probability matching refers to behavior in which left is chosen on about 70% of trials and right on 30%. Such responding violates rational choice theory because the optimal strategy in such tasks, after an initial period of experimentation and assuming that the payoff probabilities are stationary, is always to select the option associated with the higher probability of payoff. On any trial, the expected payoff for choosing left is higher than the expected payoff for choosing right.

We describe an experiment to assess the influence of body movements on presence in a virtual environment. In the experiment 20 participants were to walk through a virtual field of trees and count the trees with diseased leaves. A 2 x 2 between subjects design was used to assess the influence of two factors on presence: tree height variation and task complexity. The field with greater variation in tree height required participants to bend down and look up more than in the lower variation tree height field. In the higher complexity task participants were told to remember the distribution of diseased trees in the field as well as to count them. The results showed a significant positive association between reported presence and the amount of body movement in particular, head yaw--and the extent to which participants bent down and stood up. There was also a strong interaction effect between task complexity and gender: Women in the more-complex task reported a much lower sense of presence than in the simpler task. For applications in which presence is an important requirement, the research in this paper suggests that presence will be increased when interaction techniques are employed that permit the user to engage in whole-body movement.

The aim of this paper is to establish a methodological foundation for Human-Computer Interaction (HCI) researchers aiming to assess trust between people interacting via computer-mediated communication (CMC) technology. The most popular experimental paradigm currently employed by HCI researchers are social dilemma games based on the Prisoner's Dilemma (PD), a technique originating from economics. HCI researchers employing this experimental paradigm currently interpret the rate of cooperation-measured in the form of collective pay-off-as the level of trust the technology allows its users to develop. We argue that this interpretation is problematic, since the game's synchronous nature models only very specific trust situations. Furthermore, experiments that are based on PD games cannot model the complexity of how trust is formed in the real world, since they neglect factors such as ability and benevolence. In conclusion, we recommend (a) means of improving social dilemma experiments by using asynchronous Trust Games, (b) collecting a broader range (in particular qualitative) data, and (c) increasing use of longitudinal studies.

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