The sharing economy holds promise for the way we consume, work, and interact. However, consuming in the sharing economy is not without risk, as institutional trust measures (e.g. contracts, regulations, guarantees) are often absent. Trust between sellers and buyers is therefore crucial to complete transactions successfully. From a buyer ́s perspective, a seller ́s profile is an important source of information for judging trustworthiness, because it contains multiple trust cues such as a reputation score, a profile picture, and a textual self-description. The effect of a seller’s self-description on perceived trustworthiness is still poorly understood. We examine how the linguistic features of a seller’s self-description predict perceived trustworthiness. To determine the perceived trustworthiness of 259 profiles, 189 real buyers on a Dutch sharing platform rated their trustworthiness. The results show that profiles were perceived as more trustworthy if they contained more words (which could be an indicator of uncertainty reduction), more words related to cooking (indicator of expertise), and more words related to positive emotions (indicator of enthusiasm). Also, a profile’s perceived trustworthiness score correlated positively with the seller’s actual sales performance. These findings indicate that a seller’s self-description is a relevant signal to buyers, eventhough it is cheap talk (i.e. easy to produce). The results can guide sellers on how to self-present themselves on sharing platforms and inform platform owners on how to design their platform so that it enhances trust between platform users.
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This article proposes a model for the design of a hybrid VET curriculum across the school-work boundary.
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Dit artikel beschrijft een onderzoek naar werkzame elementen in de samenwerking binnen innovatieve leeromgevingen, professionele werkplaatsen (PW) genoemd. In PW werken onderwijs en beroepspraktijk samen aan complexe vraagstukken waarbij de ontwikkeling van betrokkenen en de innovatie van de beroepspraktijk centraal staan. Op basis van literatuuronderzoek, verkennende interviews met 11 sleutelfiguren en een meervoudige casestudie waarin vanuit 4 cases 75 betrokkenen participeerden, is het model Lerend en Onderzoekend Samenwerken in PW ontwikkeld. Het model omvat zes elementen en laat zien dat het lerend en onderzoekend samenwerken centraal staat in een PW en zich ontwikkelt binnen een grensoverstijgende en ontwikkelingsgerichte cultuur. Betrokkenen in een PW leren gezamenlijk doordat ze samenwerken in de dienstverlening en hierbij waarde hechten aan het delen van verschillende perspectieven. Door facilitering van mensen en middelen en door de samenwerking vorm te geven vanuit een gezamenlijke visie, kunnen betrokkenen elkaar leren kennen en afstemmen op welke manier zij samen kunnen bijdragen aan de innovatie van de beroepspraktijk. Hiervoor zijn zowel het opbouwen van relaties als het expliciteren en verdelen van taken en verantwoordelijkheden essentieel. Het model, dat een systemisch perspectief kent, biedt uitgangspunten en handvatten om de samenwerking binnen een PW te evalueren en te versterken.
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Trustworthy data-driven prognostics in gas turbine engines are crucial for safety, cost-efficiency, and sustainability. Accurate predictions depend on data quality, model accuracy, uncertainty estimation, and practical implementation. This work discusses data quality attributes to build trust using anonymized real-world engine data, focusing on traceability, completeness, and representativeness. A significant challenge is handling missing data, which introduces bias and affects training and predictions. The study compares the accuracy of predictions using Exhaust Gas Temperature (EGT) margin, a key health indicator, by keeping missing values, using KNN-imputation, and employing a Generalized Additive Model (GAM). Preliminary results indicate that while KNN-imputation can be useful for identifying general trends, it may not be as effective for specific predictions compared to GAM, which considers the context of missing data. The choice of method depends on the study’s objective: broad trend forecasting or specific event prediction, each requiring different approaches to manage missing data.
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Artificial Intelligence (AI) offers organizations unprecedented opportunities. However, one of the risks of using AI is that its outcomes and inner workings are not intelligible. In industries where trust is critical, such as healthcare and finance, explainable AI (XAI) is a necessity. However, the implementation of XAI is not straightforward, as it requires addressing both technical and social aspects. Previous studies on XAI primarily focused on either technical or social aspects and lacked a practical perspective. This study aims to empirically examine the XAI related aspects faced by developers, users, and managers of AI systems during the development process of the AI system. To this end, a multiple case study was conducted in two Dutch financial services companies using four use cases. Our findings reveal a wide range of aspects that must be considered during XAI implementation, which we grouped and integrated into a conceptual model. This model helps practitioners to make informed decisions when developing XAI. We argue that the diversity of aspects to consider necessitates an XAI “by design” approach, especially in high-risk use cases in industries where the stakes are high such as finance, public services, and healthcare. As such, the conceptual model offers a taxonomy for method engineering of XAI related methods, techniques, and tools.
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The model of the Best Practice Unit (BPU) is a specific form of practice based research. It is a variation of the Community of Practice (CoP) as developed by Wenger, McDermott and Snyder (2002) with the specific aim to innovate a professional practice by combining learning, development and research. We have applied the model over the past 10 years in the domain of care and social welfare in the Netherlands. Characteristics of the model are: the interaction between individual and collective learning processes, the development of (new or better) working methods, and the implementation of these methods in daily practice. Multiple knowledge sources are being used: experiential knowledge, professional knowledge and scientific knowledge. Research is serving diverse purposes: articulating tacit knowledge, documenting the learning and innovation process, systematically describing the revealed or developed ways of working, and evaluating the efficacy of new methods. An analysis of 10 different research projects shows that the BPU is an effective model.
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A model for programmatic assessment in action is proposed that optimizes assessment for learning as well as decision making on learner progress. It is based on a set of assessment principles that are interpreted from empirical research. The model specifies cycles of training, assessment and learner support activities that are completed by intermediate and final moments of evaluation on aggregated data-points. Essential is that individual data-points are maximized for their learning and feedback value, whereas high stake decisions are based on the aggregation of many data-points. Expert judgment plays an important role in the program. Fundamental is the notion of sampling and bias reduction for dealing with subjectivity. Bias reduction is sought in procedural assessment strategies that are derived from qualitative research criteria. A number of challenges and opportunities are discussed around the proposed model. One of the virtues would be to move beyond the dominating psychometric discourse around individual instruments towards a systems approach of assessment design based on empirically grounded theory.
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Organizations feel an urgency to develop and implement applications based on foundation models: AI-models that have been trained on large-scale general data and can be finetuned to domain-specific tasks. In this process organizations face many questions, regarding model training and deployment, but also concerning added business value, implementation risks and governance. They express a need for guidance to answer these questions in a suitable and responsible way. We intend to offer such guidance by the question matrix presented in this paper. The question matrix is adjusted from the model card, to match well with development of AIapplications rather than AI-models. First pilots with the question matrix revealed that it elicited discussions among developers and helped developers explicate their choices and intentions during development.
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De paper beschrijft de theoretische onderbouwing van het model Professionaliteit en Persoonlijk Leiderschap zoals dat door Fontys Hogeschool Marketing Management gebruikt wordt in haar onderwijs. De paper is uitgereikt tijdens een presentatie over dit onderwerp op het jaarcongres van de HBO-raad 2009.
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The design of healthcare facilities is a complex and dynamic process, which involves many stakeholders each with their own set of needs. In the context of healthcare facilities, this complexity exists at the intersection of technology and society because the very design of these buildings forces us to consider the technology–human interface directly in terms of living-space, ethics and social priorities. In order to grasp this complexity, current healthcare design models need mechanisms to help prioritize the needs of the stakeholders. Assistance in this process can be derived by incorporating elements of technology philosophy into existing design models. In this article, we develop and examine the Inclusive and Integrated Health Facilities Design model (In2Health Design model) and its foundations. This model brings together three existing approaches: (i) the International Classification of Functioning, Disability and Health, (ii) the Model of Integrated Building Design, and (iii) the ontology by Dooyeweerd. The model can be used to analyze the needs of the various stakeholders, in relationship to the required performances of a building as delivered by various building systems. The applicability of the In2Health Design model is illustrated by two case studies concerning (i) the evaluation of the indoor environment for older people with dementia and (ii) the design process of the redevelopment of an existing hospital for psychiatric patients.
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