Trust Decisions Research Articles

The Causal Effect of Market Priming on Trust: An Experimental Investigation Using Randomized Control

We report data from laboratory experiments where participants were primed using phrases related to markets and trade. Participants then participated in trust games with anonymous strangers. The decisions of primed participants are compared to those of a control group. We find evidence that priming for market participation affects positively the beliefs regarding the trustworthiness of anonymous strangers and increases trusting decisions.

Facial trust appraisal negatively biased in borderline personality disorder

Borderline personality disorder (BPD) is characterized by unstable interpersonal relationships and intense concerns regarding abandonment and rejection. Previous studies suggest that these and other symptoms of BPD may have their origin in a greater appraisal of untrustworthiness in others. However, it is not known whether this is a result of a heightened sensitivity to trust related stimuli, an improved ability to discriminate between such stimuli, or a response bias. Furthermore, impairment in facial fear appraisal may influence trust appraisal. Healthy controls and individuals diagnosed with BPD appraised human faces that were parametrically varied along either a trust or fear dimension. The BPD group exhibited a response bias to rate the untrustworthiness of facial stimuli higher compared to controls, but there were no significant differences in the discriminability or sensitivity of trustworthiness between groups. Furthermore, ambiguous trust decisions were associated with longer response times (RTs) in individuals with BPD relative to controls. Individuals with BPD have a facial appraisal bias specific to untrustworthiness that does not co-occur with impairments in the appraisal of fear.

Applying AHP Technique for Trust Evaluation in the Semantic Web

The increasing reliance on information gathered from the web and other internet technologies raises the issue of trust. Through the development of semantic Web,One major difficulty is that, by its very nature, the semantic web is a large, uncensored system to which anyone may contribute. This raises the question of how much credence to give each resource. We can't expect eachuser to know the trustworthiness of each resource, nor would we want to assign top-down or global credibility values due to the subjective nature of trust. Trust policiesand trust evaluation mechanisms are needed to filter untrustworthy resource. We tackle this problem by employing a trust model for evaluating trustworthiness ofeach resource. This proposed model uses semantic webmetadata, recommendation, and reputation as based factorfor evaluation algorithm. The weighting and Combination Methods are two main challenges for Proposed Trust evaluation algorithm. These factors have various type and semantic. Therefore we apply the AHP technique for trust evaluation that offers justification for trust decisions andcontrolled trust measurement.

Reasons to believe: Participants' explanations of trust in an outsourcing relationship

The nature of trust in an information systems outsourcing relationship is examined by considering the explanations for trust or distrust offered by individuals working at the boundary between the two organisations. Previous studies of trust in outsourcing situations have focused either on evidential bases of trust or the process of the development of trusting relationships. This study takes an institutional perspective and examines how trust may be shaped by the institutional norms of the trustors and the trustees. Interviews with ‘boundary spanners’ suggest that trusting decisions can be explained by reference to an implicit set of rules that govern ‘normal’ behaviour in outsourcing relationships. However, competing sets of rules and contested meanings of these rules arising from different interpretations of the institutional context were implicated in conflict and trust erosion. This case study contributes an alternative viewpoint to the body of research on trust in outsourcing relationships and adds to our understanding of how institutional contexts may influence trust in these business-to-business relationships. Further research on the nature and elicitation of rules and potential organisational interventions is suggested.

Trust Enforcing and Trust Building, Different Technologies and Visions

Concern about vulnerabilities of IT systems is growing together with attention to risks of intrusive cyber-control over personal activities and data. This article discusses some new technologies that are being integrated into computing devices for realizing so-called Trusted Computing and Digital Rights Management systems, which can remotely attest their current hardware/software state and can enforce external policies to access protected content. These technologies are then confronted with distributed Trust Management systems, which realize access control for local resources on the basis of delegation of access rights according to local trust decisions. Both technologies are discussed from various points of view: architecture, vision, ethics, politics and law.

Trust and Inventory Replenishment Decisions: An Experimental Investigation in Serial Supply Chains

Trust has been identified as a significant role-playing factor guarding supply chains against over-ordering and hoarding behavior, high inventory levels, high transaction costs, and poor customer satisfactions. Previous research addressed trust in supply chain mostly with the aid of surveys, interviews and field data analysis. Using an extended, computerized version of the Beer distribution Game, this paper examines the relationship between trust and inventory replenishment in customer-supplier relationship. To measure trust, a multi-round trust measurement mechanism is proposed, based on questionnaires to be filled at the beginning of each round by suppliers and customers. Correlation analysis is preformed to assess the relationship between trust and inventory replenishment decision. Results show that customer trust in supplier is negatively associated with overall mean order quantity and overall mean order time intervals for customers. Although, no significant correlation is found between supplier trust in customer and inventory replenishment decision indicators, results show a negative correlation between supplier trust in customer, overall mean standard deviation of order quantity, and overall mean standard deviation of order time intervals. Moreover, results indicate that both trust types evolve over time and that they play a significant role in the dynamics of customer-supplier relationship.

How to Trust

This paper concerns decision-making processes that rely on trust. In particular, it analyzes how different aspects of trust (e.g., trust, trustworthiness, trustworthy evidence) influence trust decisions, and acting on them eventually. It proposes a trust decision model that structures the analysis of contextualized trust problems. Rather than seeking a general definition of trust, this paper advocates the necessity to have a structured way to analyze and characterize situational trust problems systematically.

@Trust: A trust model based on feedback-arbitration in structured P2P network

Aiming at shortcomings in feedback information aggregation and trust decision in existing trust models, a novel trust model, named @Trust, is proposed for structured P2P networks. @Trust calculates the node’s credibility of service, feedback and arbitration based on the evaluations of the specific service which were arbitrated according to the rule of majority in human society, to enhance the model against the malicious peers. @Trust also involves the applying of the credibility of specific services and the punishment mechanism to improve the trust decision and to resist the repeated attacks of the malicious peers. The simulation results show that @Trust has advantages in distinguishing out the false feedback and resisting the malicious peers, and thus improves the availability of P2P networks.

Lightweight trusted routing for wireless sensor networks

Communication in ad hoc network, such as Wireless Sensor Networks (WSN), needs the use of decentralised routing algorithms requiring that several sensors behave in an expected way. This introduces a vulnerability as the global issue of decentralized tasks depends on local behaviors and is compromised in case of failures or malicious intrusions. We propose here an adaptation of a routing protocol for WSN, the MWAC model, that introduces trust decisions to detect and avoid sensors that exhibit an incorrect behavior. The proposed trusted routing algorithms takes into account the low energy, communication and memory capacity of sensors to provide a realistic improvement of the routing robustness.

Managers’ experience of training the associate practitioner role

This paper documents findings from a service evaluation of clinical managers' (n = 5) perceptions of the assistant practitioner (AP) training programme in one National Health Service (NHS) Trust in South East England, UK. The AP has been identified in England as a means for supporting registered nurses and enhancing patient care. The development of the AP role requires managers to consider how the role will be embedded and how they work with education providers. This service evaluation interviewed five clinical managers who have supported APs in relation to their function for the specialist clinical role. The AP role should be defined by competence, boundaries and the skill mix needed for specific clinical team function. Careful recruitment is vital and mentors need clear outcomes for the AP role. Managers need to be involved in all levels of the programme, from liaison with the Higher Education Institute and Trust decisions on role job descriptions and employment. Recruitment is vital, individuals have to be flexible and responsive to change and should be used in relation to their clinical competence. A competency framework for all health-care workers was the managers' desire for job descriptions and assessment of practice so that every member of the health-care team was 'fit for purpose'. Nurse managers need to work with workforce leads when considering introduction of new roles so appropriate skill mix is achieved and the AP role is embedded.

Effects of Strategic Exiting from Sponsorship after Negative Event Publicity

ABSTRACTResearch on the effects of event sponsorship has focused mainly on the consequences for brand equity of the association between a sponsor and a sponsored event. However, the effects of management's decision to exit from a sponsorship have received little empirical consideration. The studies reported here were carried out to fill this gap by systematically examining (a) the impact of a sponsor's corporate reputation on consumer responses to the strategic exit from a controversial sponsorship, and (b) the role that perceived trust in the decision plays in determining the outcomes. The results of two studies emphasize that strategic exiting from a controversial sponsorship (i.e., possible doping scandals at the event) can have positive consequences for the sponsor's image when the decision is trusted, but detrimental consequences when the exiting is attributed to overly self‐serving reasons. Trust in sponsorship withdrawal is elicited when the sponsor is perceived as having a good character with respect to meeting societal obligations, or when communication efforts are made salient that create trust in the withdrawal decision by a firm with a bad character.

Race and reputation: perceived racial group trustworthiness influences the neural correlates of trust decisions

Decisions to trust people with whom we have no personal history can be based on their social reputation-a product of what we can observe about them (their appearance, social group membership, etc.)-and our own beliefs. The striatum and amygdala have been identified as regions of the brain involved in trust decisions and trustworthiness estimation, respectively. However, it is unknown whether social reputation based on group membership modulates the involvement of these regions during trust decisions. To investigate this, we examined blood-oxygenation-level-dependent (BOLD) activity while participants completed a series of single-shot trust game interactions with real partners of varying races. At the time of choice, baseline BOLD responses in the striatum correlated with individuals' trust bias-that is, the overall disparity in decisions to trust Black versus White partners. BOLD signal in the striatum was higher when deciding to trust partners from the race group that the individual participant considered less trustworthy overall. In contrast, activation of the amygdala showed greater BOLD responses to Black versus White partners that scaled with the amount invested. These results suggest that the amygdala may represent emotionally relevant social group information as a subset of the general detection function it serves, whereas the striatum is involved in representing race-based reputations that shape trust decisions.

Behind HumanBoost: Analysis of Users’ Trust Decision Patterns for Identifying Fraudulent Websites

This paper analyzes users’ trust decision patterns for detecting phishing sites. Our previous work proposed HumanBoost [1] which improves the accuracy of detecting phishing sites by using users’ Past Trust Decisions (PTDs). Web users are generally required to make trust decisions whenever their personal information is requested by a website. Human-Boostassumed that a database of Web user’s PTD would be transformed into a binary vector, representing phishing or not-phishing, and the binary vector can be used for detecting phishing sites, similar to the existing heuristics. Here, this paper explores the types of the users whose PTDs are useful by running a subject experiment, where 309 participants- browsed 40 websites, judged whether the site appeared to be a phishing site, and described the criterion while assessing the credibility of the site. Based on the result of the experiment, this paper classifies the participants into eight groups by clustering approach and evaluates the detection accuracy for each group. It then clarifies the types of the users who can make suitable trust decisions for HumanBoost.

Effects of Direct Social Experience on Trust Decisions and Neural Reward Circuitry

The human striatum is integral for reward-processing and supports learning by linking experienced outcomes with prior expectations. Recent endeavors implicate the striatum in processing outcomes of social interactions, such as social approval/rejection, as well as in learning reputations of others. Interestingly, social impressions often influence our behavior with others during interactions. Information about an interaction partner’s moral character acquired from biographical information hinders updating of expectations after interactions via top down modulation of reward circuitry. An outstanding question is whether initial impressions formed through experience similarly modulate the ability to update social impressions at the behavioral and neural level. We investigated the role of experienced social information on trust behavior and reward-related BOLD activity. Participants played a computerized ball-tossing game with three fictional partners manipulated to be perceived as good, bad, or neutral. Participants then played an iterated trust game as investors with these same partners while undergoing fMRI. Unbeknownst to participants, partner behavior in the trust game was random and unrelated to their ball-tossing behavior. Participants’ trust decisions were influenced by their prior experience in the ball-tossing game, investing less often with the bad partner compared to the good and neutral. Reinforcement learning models revealed that participants were more sensitive to updating their beliefs about good and bad partners when experiencing outcomes consistent with initial experience. Increased striatal and anterior cingulate BOLD activity for positive versus negative trust game outcomes emerged, which further correlated with model-derived prediction error learning signals. These results suggest that initial impressions formed from direct social experience can be continually shaped by consistent information through reward learning mechanisms.

The role of networks in science communication and engagement with non‐expert publics

AbstractIn this ongoing study, I examine associations among scientists by analyzing scholarly publication data and Internet hyperlink relationships using a social network analysis framework. Unlike other studies of collaboration, this study does not start with an extant network of scientists who share a research focus, but rather groups who are networked for purposes of public and political engagement. I have chosen as my nodes two presumed “networks” of scientists: the group of 16 scientists who authored a January 27th', 2012 op‐ed in The Wall Street Journal which suggested concerns about climate change were being exaggerated, and the group of 38 scientists who authored a response piece (supporting climate change science) on February 1st.I have chosen climate science because of its scientific complexity that is of necessity interdisciplinary, and its scrutiny by non‐expert publics. Building on the theoretical foundations of social epistemology, I examine how notions of the role of shared practices in engendering trust and knowledge‐sharing among expert groups can be applied when the lines between expert and non‐expert are contested in high‐visibility public arenas. In exploring some of those questions, this study aims to discover if a social network methodology combining co‐authorship data and hyperlink data can reveal patterns of association and engagement with traditional (e.g., scholarly publications) vs. non‐traditional (e.g., web sites or blog articles) methods of communication and legitimation.This study is intended as part of a larger research trajectory examining the role of social associations in influencing credibility and information trust decisions in areas where expert and non‐experts must meet and negotiate shared meanings. These findings could suggest future directions for collaborative data sharing practices as well as support theoretical work in understanding how trust and credibility are granted in networked information environments.

A Twitter-Based Weighted Reputation system

Trust between buyers and sellers plays an essential role in online shopping. Therefore, reputation systems are, typically, integrated with online shopping systems to form trust decisions between sellers and buyers. Online Social Networks (OSNs), such as Twitter, LinkedIn, MySpace and Facebook connect people from all over the world in a virtual community. OSNs can provide information about the relationships between people. This information can be used to improve the reliability of reputation systems. With twitter having over than 200 million users and due to its microblogging nature, we choose twitter as a basis for a reputation system.

Context-sensitive trust computing in distributed environments

With deep and broad applications in distributed computing, how to promote cooperation between entities becomes more and more important. Trust has been proven to be essential to enforce cooperative behaviors in distributed environments. To build trust relationship depends on some factors, such as context, behaviors, and experiences, and it is more challenging to accurately measure them. In this paper, we present a context-sensitive trust computing model to address this problem. Firstly, a trust space with fit-degree is defined based on the contextual information and a context-sensitive fit-law is proposed to judge the abilities of entities. Then, a trust computing model is proposed and followed by an expatiated dynamics trust analysis. Next, considering a new entity without trustworthiness can almost not do anything, we further present an algorithm of initial trustworthiness based on the new entity’s abilities. The entity’s trustworthiness is divided into the initial trustworthiness, the direct trustworthiness, and the recommended trustworthiness. Based on the trustworthiness obtained by the trust fusion algorithm, a mechanism of making trust decision is presented to promote cooperation. The simulation results show that our model can enhance the cooperation among entities. The malicious behaviors can be controlled because of the trustworthiness threshold of services. As such, the honest peers can be incentive, the network stability can be promoted, and the extent of network security can be improved. The proposed dynamic trust computing model is proven to be reasonable, practical, comparable, and workable in distributed services environments.

The Politics of Interpersonal Trust and Reciprocity: An Experimental Approach

Trust and reciprocity are theoretically essential to strong democracies and efficient markets. Working from the theoretical frameworks of social identity and cognitive heuristics, this study draws on dual-process models of decision making to expect (1) the trustor to infer trustworthiness from partisan stereotypes and thus to discriminate trust in favor of co-partisans and against rival partisans, but (2) the trustee to base reciprocity decisions on real information about the trustor’s deservingness rather than a partisan stereotype. So whereas partisanship is likely to trigger trust biases, the trust decision itself provides enough information to override partisan biases in reciprocity. The analysis derives from a modified trust game experiment. Overall, the results suggest partisanship biases trust decisions among partisans, and the degree of partisan trust bias is consistent with expectations from both social identity theory and cognitive heuristics. When it comes to reciprocity, however, information about the other subject’s level of trust nullifies partisan bias.

To believe or not to believe: trust choice modulates brain responses in outcome evaluation

Making a trust decision in interpersonal relationship involves forming positive expectation toward the decision outcome. Previous studies have suggested that trust and distrust are qualitatively distinct and have differential neurocognitive substrates. In this study, we investigated how trust choice would modulate brain responses to decision outcome in a modified coin-toss game. Participants received statements from partners concerning the results of coin-toss and decided whether to believe the truthfulness of the statements. In two experiments, event-related potentials (ERPs) to the real results revealed after the trust choice demonstrated differential patterns following trust and distrust choices. Both the feedback-related negativity (FRN) and the P300 showed effects of outcome valence following trust choices, but the FRN effect was reduced following distrust choices. Thus, trust choice creates different contexts in which aspects of decision outcome can be encoded simultaneously by the FRN. The FRN may reflect the subjective evaluation of decision outcome in a specific context rather than a general expectancy towards the outcome.

Trust and self-control: The moderating role of the default

AbstractAccording to recent dual-process theories, interpersonal trust is influenced by both impulsive and deliberative processes. The present research explores the determinants of deliberative trust, investigating how trust decisions are affected by the availability of cognitive resources. We test the interaction of two relevant factors: self-control (the ability to exert mental control over one’s behavior) and the default response (a preselected option that requires minimal or no effort). Past research has shown that self-control has extensive effects on social behavior and decision making. Here, we report that the effect of self-control on trust depends on the default. Across two studies, we find no direct link between self-control and trust. Instead, self-control affects trust indirectly by influencing the level of effort in decision making. Poor self-control (due to experimental depletion or trait-based differences) predicts adherence to the default—the response that requires the least effort.