Cognitive Model Of Trust Research Articles

Trust Miscalibration Is Sometimes Necessary: An Empirical Study and a Computational Model

The literature on trust seems to have reached a consensus that appropriately calibrated trust in humans or machines is highly desirable; miscalibrated (i.e., over- or under-) trust has been thought to only have negative consequences (i.e., over-reliance or under-utilization). While not invalidating the general idea of trust calibration, a published computational cognitive model of trust in strategic interaction predicts that some local and temporary violations of the trust calibration principle are critical for sustained success in strategic situations characterized by interdependence and uncertainty (e.g., trust game, prisoner’s dilemma, and Hawk-dove). This paper presents empirical and computational modeling work aimed at testing the predictions of under- and over-trust in an extension of the trust game, the multi-arm trust game, that captures some important characteristics of real-world interpersonal and human-machine interactions, such as the ability to choose when and with whom to interact among multiple agents. As predicted by our previous model, we found that, under conditions of increased trust necessity, participants actively reconstructed their trust-investment portfolios by discounting their trust in their previously trusted counterparts and attempting to develop trust with the counterparts that they previously distrusted. We argue that studying these exceptions of the principle of trust calibration might be critical for understanding long-term trust calibration in dynamic environments.

A Cognitive Model of Trust for Biological and Artificial Humanoid Robots

This paper presents a model of trust for biological and artificial humanoid robots and agents as antecedent condition of interaction. We discuss the cognitive engines of social perception that accounts for the units on which agents operate and the rules they follow when they bestow trust and assess trustworthiness. We propose that this structural information is the domain of the model. The model represents it in terms of modular cognitive structures connected by a parallel architecture. Finally we give a preliminary formalization of the model in the mathematical framework of the I/O automata for future computational and human-humanoid application.

Trust in interprofessional collaboration: Perspectives of pharmacists and physicians.

Trust is integral to effective interprofessional collaboration. There has been scant literature characterizing how trust between practitioners is formed, maintained or lost. The objective of this study was to characterize the cognitive model of trust that exists between pharmacists and family physicians working in collaborative primary care settings. Pharmacists and family physicians who work collaboratively in primary care were participants in this study. Family health teams were excluded from this study because of the distinct nature of these settings. Through a snowball convenience sampling method, a total of 11 pharmacists and 8 family physicians were recruited. A semistructured interview guide was used to guide discussion around trust, relationships and collaboration. Constant-comparative coding was used to identify themes emerging from these data. Pharmacists and family physicians demonstrate different cognitive models of trust in primary care collaboration. For pharmacists, trust appears to be conferred on physicians based on title, degree, status and positional authority. For family physicians, trust appears to be earned based on competency and performance. These differences may lead to interprofessional tension when expectations of reciprocal trust are not met. Further work in characterizing how trust is developed in interprofessional relationships is needed to support effective team formation and functioning.

Cognitive Trust Model for B2B E-Market

In recent years, B2B E-Market has received widespread amount of research attention in the field of electronic commerce. As majority of companies are investing huge amount of money to build the infrastructure for e-collaboration. Selecting suitable trading partners in an e-market still remains a huge challenge, as the selection of supplier depends not only on cost but on other factors such as reputation, satisfaction and trust. Trust is regarded as one of the most important factors for success and to ensure customers repeat trading. One of the major challenges faced by both research and industry is to measure trustworthiness of a supplier in an e-market place. This paper proposes a cognition based model to measure trustworthiness of a supplier. The proposed model with its implementation using multi-agent systems is described in detail. Finally empirical evaluation is carried out to validate the system and future direction for research in this area.

Cloud-DLS: Dynamic trusted scheduling for Cloud computing

Clouds are rapidly becoming an important platform for scientific applications. In the Cloud environment with uncountable numeric nodes, resource is inevitably unreliable, which has a great effect on task execution and scheduling. In this paper, inspired by Bayesian cognitive model and referring to the trust relationship models of sociology, we first propose a novel Bayesian method based cognitive trust model, and then we proposed a trust dynamic level scheduling algorithm named Cloud-DLS by integrating the existing DLS algorithm. Moreover, a benchmark is structured to span a range of Cloud computing characteristics for evaluation of the proposed method. Theoretical analysis and simulations prove that the Cloud-DLS algorithm can efficiently meet the requirement of Cloud computing workloads in trust, sacrificing fewer time costs, and assuring the execution of tasks in a security way.

A Cognitive Model Of Trust In E-Commerce: Evidence From A Field Study In China

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt; mso-bidi-font-style: italic;"><span style="font-family: Times New Roman;">Trust formation in the virtual environment is a complex process and is influenced by a plethora of factors.<span style="mso-spacerun: yes;">  </span>This paper proposes a cognitive model of trust in e-commerce based on consumer research and the trust literature. It argues that perceived informativeness, perceived entertainment, and perceived irritation of online shopping, coupled with trust propensity, contribute to a customer’s general trust in e-commerce and intention to use e-commerce.<span style="mso-spacerun: yes;">  </span>This model is tested in a field study in China via a survey instrument. Path analysis of data collected shows that all proposed relationships in the model are supported in the hypothesized directions. Results demonstrate that online marketers and Web system designers alike should pay keen attention to elements that may influence an Internet shopper’s cognitive perceptions in order to nurture consumers’ trust in e-commerce and realize the full potentials of doing business online.</span></span></p>

Bayesian cognitive trust model based self-clustering algorithm for MANETs

With the introduction of mobile Ad hoc networks (MANETs), nodes are able to participate in a dynamic network which lacks an underlying infrastructure. Before two nodes agree to interact, they must trust that each will satisfy the security and privacy requirements of the other. In this paper, using the cognition inspired method from the brain informatics (BI), we present a novel approach to improving the search efficiency and scalability of MANETs by clustering nodes based on cognitive trust mechanism. The trust relationship is formed by evaluating the level of trust using Bayesian statistic analysis, and clusters can be formed and maintained autonomously by nodes with only partial knowledge. Simulation experiments show that each node can form and join proper clusters, which improve the interaction performance of the entire network. The essence of the underlying reason is analyzed through the theory of complex networks, revealing great scalability of this method.

Trust and reciprocity: misunderstandings

We contest a reductive view of trust, quite diffused in economics, and in studies influenced by the Game-Theory framework: the idea that trust has necessarily to do with contexts requiring “reciprocation”; or that trust is trust in the other’s reciprocation. A multi-layer cognitive model of trust will be proposed. Trust is not conceived only as an attitude towards the other, implying different kinds of beliefs (evaluations, expectations, beliefs on the other”s motives, etc.), but also as a willingness to rely on others that makes us dependent and vulnerable to them, as well as a concrete act of reliance based on this. Not necessarily we trust people because they will be willing to reciprocate; and we do not necessarily reciprocate for reciprocating. Trust (even “genuine” trust) is based on a variety of motivations ascribed to others and makes prevail the adoption of our needs and goals: from “altruism” to “self-interest”, from reciprocation to norms or to affective reasons.