1,282,477 research outputs found

    The Influence of Trust in Traditional Contracting: Investigating the "Lived Experience" of Stakeholders

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    The traditional procurement approach is ever-present within the construction industry. With fundamental design principles founded on definitive risk allocation, this transactional based approach fails to acknowledge or foster the cooperative relationships considered to be vital to the success of any project. Contractual design encourages stakeholders to defend their own individual interest to the likely detriment of project objectives. These failings are not disputed, however, given that trust is a fundamental requirement for human interaction the influence of trust is potentially important in terms of stakeholder relationships and ultimate project success. Trust is therefore examined within this context. A conceptual framework of trust is presented and subsequently used to code and analyse detailed, semi-structured interviews with multiple stakeholders from different projects. Using a phenomenological investigation of trust via the lived experiences of multiple practitioners, issues pertaining to the formation and maintenance of trust within traditionally procured construction projects are examined. Trust was found to be integral to the lived experiences of practitioners, with both good and bad relationships evident within the constructs of traditional procurement mechanisms. In this regard, individual personalities were considered significant, along with appropriate risk identification and management. Communication, particularly of an informal nature, was also highlighted. A greater emphasis on project team selection during the initial stages of a project would therefore be beneficial, as would careful consideration of the allocation of risk. Contract design would also be enhanced through prescriptive protocols for developing and maintaining trust, along with mandated mechanisms for informal communication, particularly when responding to negative events. A greater understanding regarding the consequences of lost trust and the intricacies of trust repair would also be of value. 

    A Classification Model for Sensing Human Trust in Machines Using EEG and GSR

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    Today, intelligent machines \emph{interact and collaborate} with humans in a way that demands a greater level of trust between human and machine. A first step towards building intelligent machines that are capable of building and maintaining trust with humans is the design of a sensor that will enable machines to estimate human trust level in real-time. In this paper, two approaches for developing classifier-based empirical trust sensor models are presented that specifically use electroencephalography (EEG) and galvanic skin response (GSR) measurements. Human subject data collected from 45 participants is used for feature extraction, feature selection, classifier training, and model validation. The first approach considers a general set of psychophysiological features across all participants as the input variables and trains a classifier-based model for each participant, resulting in a trust sensor model based on the general feature set (i.e., a "general trust sensor model"). The second approach considers a customized feature set for each individual and trains a classifier-based model using that feature set, resulting in improved mean accuracy but at the expense of an increase in training time. This work represents the first use of real-time psychophysiological measurements for the development of a human trust sensor. Implications of the work, in the context of trust management algorithm design for intelligent machines, are also discussed.Comment: 20 page

    Factors affecting patients' trust and confidence in GPs: evidence from the English national GP patient survey.

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    OBJECTIVES: Patients' trust in general practitioners (GPs) is fundamental to effective clinical encounters. Associations between patients' trust and their perceptions of communication within the consultation have been identified, but the influence of patients' demographic characteristics on these associations is unknown. We aimed to investigate the relative contribution of the patient's age, gender and ethnicity in any association between patients' ratings of interpersonal aspects of the consultation and their confidence and trust in the doctor. DESIGN: Secondary analysis of English national GP patient survey data (2009). SETTING: Primary Care, England, UK. PARTICIPANTS: Data from year 3 of the GP patient survey: 5 660 217 questionnaires sent to patients aged 18 and over, registered with a GP in England for at least 6 months; overall response rate was 42% after adjustment for sampling design. OUTCOME MEASURES: We used binary logistic regression analysis to investigate patients' reported confidence and trust in the GP, analysing ratings of 7 interpersonal aspects of the consultation, controlling for patients' sociodemographic characteristics. Further modelling examined moderating effects of age, gender and ethnicity on the relative importance of these 7 predictors. RESULTS: Among 1.5 million respondents (adjusted response rate 42%), the sense of 'being taken seriously' had the strongest association with confidence and trust. The relative importance of the 7 interpersonal aspects of care was similar for men and women. Non-white patients accorded higher priority to being given enough time than did white patients. Involvement in decisions regarding their care was more strongly associated with reports of confidence and trust for older patients than for younger patients. CONCLUSIONS: Associations between patients' ratings of interpersonal aspects of care and their confidence and trust in their GP are influenced by patients' demographic characteristics. Taking account of these findings could inform patient-centred service design and delivery and potentially enhance patients' confidence and trust in their doctor

    Data centric trust evaluation and prediction framework for IOT

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    © 2017 ITU. Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas

    The Costly Business of Trust

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    The paper provides a framework to analyses trust-based projects which can be used as a diagnostic tool to design more effective policy intervention, particularly addressing the problem of meeting users needs for which many microfinance scheme have come under criticism. the theory is developed on the basis of both secondary literature and direct empirical evidence from two micro-finance projects in Mexico. we illustrate how a system of trust is built, and derive general propositions regarding the specificity of trust, the role of trust brokers, and the policy of subsidising trust-building projects, that can be applied both to microfinance and other trust-based development projects. we aim, to provide a tool capable of identifying crucial actors in trust systems and the nature of the linkages between them, so that trust can be effectively operationalised and incorporated into policy design in order to improve projects' effectiveness and suitability to local conditions.

    The mechanics of trust: a framework for research and design

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    With an increasing number of technologies supporting transactions over distance and replacing traditional forms of interaction, designing for trust in mediated interactions has become a key concern for researchers in human computer interaction (HCI). While much of this research focuses on increasing users’ trust, we present a framework that shifts the perspective towards factors that support trustworthy behavior. In a second step, we analyze how the presence of these factors can be signalled. We argue that it is essential to take a systemic perspective for enabling well-placed trust and trustworthy behavior in the long term. For our analysis we draw on relevant research from sociology, economics, and psychology, as well as HCI. We identify contextual properties (motivation based on temporal, social, and institutional embeddedness) and the actor's intrinsic properties (ability, and motivation based on internalized norms and benevolence) that form the basis of trustworthy behavior. Our analysis provides a frame of reference for the design of studies on trust in technology-mediated interactions, as well as a guide for identifying trust requirements in design processes. We demonstrate the application of the framework in three scenarios: call centre interactions, B2C e-commerce, and voice-enabled on-line gaming

    Trust and Economic Growth: Conflicting Results between Cross-Sectional and Panel Analysis

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    This paper examines the relationship between trust and economic growth. With the help of panel data I conclude that economic growth is negatively related to an increase in trust. My result is contrary to works taking a cross section design in which trust is positively related to growth. The relationship is tested in the context of EU countries, OECD countries, transition countries and developing countries. Interpersonal trust and systemic trust is differentiated.Social Capital; Trust; Economic Growth; Panel Analyis
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