Learning to Trust

Trust is full of puzzle and paradox.Trust is both rational and emotional. Trust can go beyond calculative self-interest, but has its limits.People may want to trust, while they may also feel threatened by it.If trust is not in place prior to a relationship, on the basis of institutions, prior experience, or reputation, it has to be built up, in specific relations.For that one needs to learn, in the sense of building empathy, and perhaps a certain degree of identification.In an attempt at a better understanding of the puzzles and processes of trust, this chapter applies the perspective of 'embodied cognition', and insights from mental 'framing' and decision heuristics from social psychology.learning;trust;institutions

Learning to Trust

Trust is full of puzzle and paradox.Trust is both rational and emotional. Trust can go beyond calculative self-interest, but has its limits.People may want to trust, while they may also feel threatened by it.If trust is not in place prior to a relationship, on the basis of institutions, prior experience, or reputation, it has to be built up, in specific relations.For that one needs to learn, in the sense of building empathy, and perhaps a certain degree of identification.In an attempt at a better understanding of the puzzles and processes of trust, this chapter applies the perspective of 'embodied cognition', and insights from mental 'framing' and decision heuristics from social psychology.

Learning to trust strangers: an evolutionary perspective

What if living in a relatively trustworthy society was sufficient to blindly trust strangers? In this paper we interpret generalized trust as a learning process and analyse the trust game paradox in light of the replicator dynamics. Given that trust inevitably implies doubts about others, we assume incomplete information and study the dynamics of trust in buyer-supplier purchase transactions. Considering a world made of “good” and “bad” suppliers, we show that the trust game admits a unique evolutionarily stable strategy: buyers may trust strangers if, on the whole, it is not too risky to do so. Examining the situation where some players may play, either as trustor or as trustee, we show that this result is robust.

Trust and Experience in Online Auctions

This paper aims to shed light on the complexities and difficulties in predicting the effects of trust and the experience of online auction participants on bid levels in online auctions. To provide some insights into learning by bidders, a field study was conducted first to examine auction and bidder characteristics from eBay auctions of rare coins. We proposed that such learning is partly because of institutional-based trust. Data were then gathered from 453 participants in an online experiment and survey, and a structural equation model was used to analyze the results. This paper reveals that experience has a nonmonotonic effect on the levels of online auction bids. Contrary to previous research on traditional auctions, as online auction bidders gain more experience, their level of institutional-based trust increases and leads to higher bid levels. Data also show that both a bidder’s selling and bidding experiences increase bid levels, with the selling experience having a somewhat stronger effect. This paper offers an in-depth study that examines the effects of experience and learning and bid levels in online auctions. We postulate this learning is because of institutional-based trust. Although personal trust in sellers has received a significant amount of research attention, this paper addresses an important gap in the literature by focusing on institutional-based trust

Learning to trust, learning to be trustworthy

Interpersonal trust is a one-sided social dilemma. Building on the binary trust game, we ask how trust and trustworthiness can evolve in a population where partners are matched randomly and agents sometimes act as trustors and sometimes as trustees. Trustors have the option to costly check a trustee's last action and to condition their behavior on the signal they receive. We show that the resulting population game admits two components of Nash equilibria. Nevertheless, the long-run outcome of an evolutionary social learning process modeled by the best response dynamics is unique. Even if unconditional distrust initially abounds, the trustors' checking option leads trustees to build a reputation for trustworthiness by honoring trust. This invites free-riders among the trustors who save the costs of checking and trust blindly, until it does no longer pay for trustees to behave in a trustworthy manner. This results in cyclical convergence to a mixed equilibrium with behavioral heterogeneity where suspicious checking and blind trusting coexist while unconditional distrust vanishes. (author's abstract)Series: Department of Economics Working Paper Serie

Simultaneous Inference of User Representations and Trust

Inferring trust relations between social media users is critical for a number of applications wherein users seek credible information. The fact that available trust relations are scarce and skewed makes trust prediction a challenging task. To the best of our knowledge, this is the first work on exploring representation learning for trust prediction. We propose an approach that uses only a small amount of binary user-user trust relations to simultaneously learn user embeddings and a model to predict trust between user pairs. We empirically demonstrate that for trust prediction, our approach outperforms classifier-based approaches which use state-of-the-art representation learning methods like DeepWalk and LINE as features. We also conduct experiments which use embeddings pre-trained with DeepWalk and LINE each as an input to our model, resulting in further performance improvement. Experiments with a dataset of $\sim$356K user pairs show that the proposed method can obtain an high F-score of 92.65%.Comment: To appear in the proceedings of ASONAM'17. Please cite that versio

Social Structures for Learning

This article investigates what learning groups there are in organizations, other than the familiar 'communities of practice'. It first develops an interdisciplinary theoretical framework for identifying, categorizing and understanding learning groups. For this, it employs a constructivist, interactionist theory of knowledge and learning. It employs elements of transaction cost theory and of social theory of trust. Transaction cost economics neglects learning and trust, but elements of the theory are still useful. The framework is used in an empirical study in a consultancy company, to explore what learning groups there are, and to see if our theory can explain their functioning and their success or failure.learning groups;social theory of trust;theory of knowledge and learning;transaction cost theory

Learning and Governance in Inter-Firm Relations

This paper connects theory of learning with theory of governance, in the context of inter-firm relations. It recognizes fundamental criticism of transaction cost economics (TCE), but preserves elements from that theory. The theory of governance used incorporates learning and trust. The paper identifies two kinds of relational risk: hold-up and spillover. For the governance of relations, i.e. the control of relational risk, it develops a box of instruments which includes trust, next to instruments derived and adapted from TCE. These instruments are geared to problems that are specific to learning in interaction between firms. They also include additional roles for go-betweens.transaction cost economics;trust;inter-organizational learning