1,720,971 research outputs found

    The second extended model of consumer trust in cryptocurrency payments, CRYPTOTRUST 2

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    Cryptocurrencies’ popularity is growing despite short-term fluctuations. Peer-reviewed research into trust in cryptocurrency payments started in 2014. While the model created then, is based on proven theories from psychology and supported by empirical research, a-lot has changed in the past 10 years. This research finds that the original model is still valid, but it is extended to capture the current situation better. A quantitative methodology is used to validate the updated model proposed. The results from the quantitative survey show that (1) personal innovativeness in technology and (2) finance, influence (3) disposition to trust. Disposition to trust influences six variables from the specific context of the payment. Three variables related to the cryptocurrency itself are (4) stability in the value, (5) transaction fees, and (6) reputation. Institutional trust is influenced by (7) regulation, and (8) payment intermediaries. The last contextual factor is (9) trust in the retailer. The six variables from the context influence (10) trust in the payment which, finally, influences (11) the likelihood of making the cryptocurrency payment

    Re-evaluating trust and privacy concern when purchasing a mobile app: Re-calibrating for the increasing role of Artificial Intelligence

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    Mobile apps utilize the features of a mobile device to offer an ever-growing range of functionalities. This vast choice of functionalities is usually available for a small fee or for free. These apps access the user’s personal data, utilizing both the sensors on the device and big data from several sources. Nowadays, Artificial Intelligence (AI) is enhancing the ability to utilize more data and gain deeper insight. This increase in the access and utilization of personal information offers benefits but also challenges to trust. Using questionnaire data from Germany, this research explores the role of trust from the consumer’s perspective when purchasing mobile apps with enhanced AI. Models of trust from e-commerce are adapted to this specific context. A model is proposed and explored with quantitative methods. Structural Equation Modeling enables the relatively complex model to be tested and supported. Propensity to trust, institution-based trust, perceived sensitivity of personal information, and trust in the mobile app are found to impact the intention to use the mobile app with enhanced AI

    Investigating the individual trust and school performance in semi-virtual collaboration groups

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    Purpose: the purpose of this paper is to investigate the relationship between individual trust of students in computer supported semi-virtual collaboration groups and student’s performance in school. Design/methodology/approach – Longitudinal questionnaires and interviews are conducted during the case study. By analyzing the data from the questionnaires and the grade earned by the students, the sample students are ranked with respect to the trust level and individual performance. Furthermore, the Wilcoxon signed-rank test is used to compare individual trust level and performance in the computer supported semi-virtual collaborative environment.Findings: the distribution of an individual’s trust level is roughly consistent with the distribution of the individual’s performance in the collaboration. Besides, the relationship between a student’s trust level and the student’s performance is positively correlated.Research limitations/implications: this study integrates the issues of trust, school performance, and collaboration in an educational context. Furthermore, the conclusions drawn from this paper extend the literature of multiple disciplines including education, management, and psychology.Practical implications: the conclusions could apply in the fields of education and management since the analysis revealed the relationship between an individual’s trust level and their performance. Originality/value – This study contributes to the field of trust and collaboration research with a link to trust development and performance. The study also provides an insight into how to successfully improve the performance of student semi-virtual collaboration groups.<br/

    Investigating individual trust in semi-virtual collaboration of multicultural and unicultural teams

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    © 2016 Elsevier Ltd. All rights reserved. This study aims to investigate individual's trust development for semi-virtual collaboration teams with multicultural and unicultural background. We aim to explore whether the trust levels in multicultural and unicultural semi-virtual groups will be the same, how trust develops over time and what the corresponding factors to the trust development are. In order to answer the questions, a longitudinal case study was conducted in unicultural and multicultural teams. We have taken survey for 144 participants over three stages, as well as interviewed 64 participants. Results of the analysis of the survey data firstly show that no significant difference exists between multicultural and unicultural groups. Then, two factors, collaboration process and clear task help explain this phenomenon. However, the trust development of multicultural groups shows instability and keeps decreasing over time, while unicultural groups behave differently. We found that language, values and habitual behavior lead to the differences in these two types of groups

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

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