Trust Evaluation of a System for an Activity

International audienceWhen users need to perform a digital activity, they evaluate available systems according to their functionality, ease of use, QoS, and/or economical as- pects. Recently, trust has become another key factor for such evaluation. Two main issues arise in the trust management research community. First, how to de- fine the trust in an entity, knowing that this can be a person, a digital or a physical resource. Second, how to evaluate such value of trust in a system as a whole for a particular activity. Defining and evaluating trust in systems is an open problem because there is no consensus on the used approach. In this work we propose an approach applicable to any kind of system. The distinctive feature of our pro- posal is that, besides taking into account the trust in the different entities the user depends on to perform an activity, it takes into consideration the architecture of the system to determine its trust level. Our goal is to enable users to have a per- sonal comparison between different systems for the same application needs and to choose the one satisfying their expectations. This paper introduces our approach, which is based on probability theory, and presents ongoing results

The Role of Kansei Engineering in Influencing Overall Satisfaction and Behavioral Intention in Service Encounters

Customers today concern themselves more on fulfilling their emotional needs rather than rationales and functionalities. In dealing with customer emotions in products/services, Kansei Engineering (KE) is applied. A comprehensive case study in luxury hotels was conducted. Eighty one Indonesian, 75 Singaporean, and 74 Japanese tourists participated in this survey. It aims to investigate the relationships among constructs during service encounter process. The finding shows that emotions (affective process) play a significant role as a complement to cognitive process in influencing customer satisfaction. Among 3 populations, Japanese was found to be more Kansei-oriented customer. Keywords: Kansei Engineering, emotional needs, customer satisfactio

Secure Cloud-Edge Deployments, with Trust

Assessing the security level of IoT applications to be deployed to heterogeneous Cloud-Edge infrastructures operated by different providers is a non-trivial task. In this article, we present a methodology that permits to express security requirements for IoT applications, as well as infrastructure security capabilities, in a simple and declarative manner, and to automatically obtain an explainable assessment of the security level of the possible application deployments. The methodology also considers the impact of trust relations among different stakeholders using or managing Cloud-Edge infrastructures. A lifelike example is used to showcase the prototyped implementation of the methodology

The role of customer experience in building brand loyalty within the service context

Customer experience theory, research, and practice represent an evolving area of study within the marketing discipline. Despite its importance, the customer experience concept remains vague and lacks a thorough theoretical foundation. This study addresses this gap in the literature and examines the antecedents and consequences of customer experience from customer perspectives. The study provides a conceptual framework building from a qualitative study and the existing literature. This article includes a formal test of the framework using a large-scale survey of British customers to examine their experience with resort-hotel brands. The results show price perception, core services, and word-of-mouth have a direct impact on how customers interpret their experiences with resort-hotel brands; perceived service quality plays a mediatory role in the relationship between servicescape, core service, and customer experience. Measuring validation strength of customer experience upon brand loyalty by best fit in combination with cross-sample predictive validity models is a valuable contribution of this study

Approximate Models and Robust Decisions

Decisions based partly or solely on predictions from probabilistic models may be sensitive to model misspecification. Statisticians are taught from an early stage that "all models are wrong", but little formal guidance exists on how to assess the impact of model approximation on decision making, or how to proceed when optimal actions appear sensitive to model fidelity. This article presents an overview of recent developments across different disciplines to address this. We review diagnostic techniques, including graphical approaches and summary statistics, to help highlight decisions made through minimised expected loss that are sensitive to model misspecification. We then consider formal methods for decision making under model misspecification by quantifying stability of optimal actions to perturbations to the model within a neighbourhood of model space. This neighbourhood is defined in either one of two ways. Firstly, in a strong sense via an information (Kullback-Leibler) divergence around the approximating model. Or using a nonparametric model extension, again centred at the approximating model, in order to `average out' over possible misspecifications. This is presented in the context of recent work in the robust control, macroeconomics and financial mathematics literature. We adopt a Bayesian approach throughout although the methods are agnostic to this position

Veracity Roadmap: Is Big Data Objective, Truthful and Credible?

This paper argues that big data can possess different characteristics, which affect its quality. Depending on its origin, data processing technologies, and methodologies used for data collection and scientific discoveries, big data can have biases, ambiguities, and inaccuracies which need to be identified and accounted for to reduce inference errors and improve the accuracy of generated insights. Big data veracity is now being recognized as a necessary property for its utilization, complementing the three previously established quality dimensions (volume, variety, and velocity), But there has been little discussion of the concept of veracity thus far. This paper provides a roadmap for theoretical and empirical definitions of veracity along with its practical implications. We explore veracity across three main dimensions: 1) objectivity/subjectivity, 2) truthfulness/deception, 3) credibility/implausibility – and propose to operationalize each of these dimensions with either existing computational tools or potential ones, relevant particularly to textual data analytics. We combine the measures of veracity dimensions into one composite index – the big data veracity index. This newly developed veracity index provides a useful way of assessing systematic variations in big data quality across datasets with textual information. The paper contributes to the big data research by categorizing the range of existing tools to measure the suggested dimensions, and to Library and Information Science (LIS) by proposing to account for heterogeneity of diverse big data, and to identify information quality dimensions important for each big data type

Impact of disease, cognitive and behavioural factors on caregiver outcome in amyotrophic lateral sclerosis

Up to 50% of patients with amyotrophic lateral sclerosis (ALS) show mild to moderate cognitive-behavioural change alongside their progressive functional impairment. This study examines the relative impact of patients' disease symptoms, behavioural change and current executive function and social cognition abilities on psychosocial outcomes in spouse caregivers of people with ALS. Thirty-five spouse caregivers rated their own levels of depression and anxiety, subjective burden and marital satisfaction. Caregivers also rated their partner's everyday behaviour. The patients were assessed for disease severity and cognitive function, with composite scores derived for executive function and social cognition. Regression analyses revealed that caregiver burden was predicted by the severity of patients' limb involvement and behavioural problems. Depression was predicted by patients' limb involvement, while behavioural problems and patient age predicted caregiver anxiety. Current marital satisfaction was predicted by patient behavioural problems beyond the level of pre-illness marital satisfaction. In conclusion, the study highlights the potential impact of ALS patients' functional impairment and behavioural change on ALS caregivers' psychosocial functioning. Clinical communication with ALS families should emphasise both physical and psychological challenges presented by the disease