1,720,954 research outputs found
AI in the Real Estate Industry – A Threat or an Asset?
No full textSyfte: Syftet med denna studie är att analysera hur kundernas förtroende påverkas av AI-genererade fastighetsvärderingar samt vilka faktorer som påverkar förtroendet. Metod: Studien har genomförts med en kvantitativ ansats i form av en enkätundersökning. Respondenterna fick ta ställning till fiktiva fastighetsvärderingar, där vissa var märkta som AI-genererade och andra som utförda av fastighetsmäklare. Totalt deltog 184 respondenter. Data analyserades med hjälp av deskriptiv statistik. Resultat och slutsats: Resultaten visar att respondenter generellt har lägre förtroende för AI-genererade värderingar än för dem som utförts av en fastighetsmäklare, trots identiskt innehåll. De faktorer som påverkar tilliten mest är transparens, förståelse för hur värderingen tagits fram samt upplevelsen personlig kontakt. Examensarbetets bidrag: Studien bidrar till forskningen om tillit till AI genom att applicera Solberg m.fl. (2022) utvecklade tillitsmodell samt förklarbar AI (XAI) i ett praktiskt sammanhang inom fastighetsbranschen. Resultaten fördjupar förståelsen av begrepp som transparens och Black Box-problematiken ur ett kundperspektiv. Förslag till fortsatt forskning: Framtida forskning bör genomföras med kvalitativa metoder för att fördjupa förståelsen för varför kunder upplever minskat förtroende för AI-genererade fastighetsvärderingar. Det vore även relevant att inkludera fastighetsmäklare och branschaktörer för att få ett bredare perspektiv på AI:s roll i värderingsprocessen.Aim: The aim of this study is to examine how customer trust is affected by AI-generated property valuations and to identify the factors that influence that trust. Method: The study was conducted using a quantitative research approach through a structured online survey. Participants were presented with fictional property valuations, where some were labeled as AI-generated and others as conducted by real estate agents. In total, 184 respondents participated. The data were analyzed using descriptive statistics. Results and conclusions: The results indicate that respondents generally have lower trust in AI-generated valuations compared to those conducted by real estate agents, despite identical content. The most influential factors affecting trust were transparency and understanding of how the valuation was produced, and the perceived presence of personal interaction. Contribution of the thesis: This study contributes to existing research on trust in AI by applying Solberg et al. (2022) developed trust model and concepts from explainable AI (XAI) to a practical context within the real estate sector. The findings provide a deeper understanding of transparency and the Black Box issue from a customer’s perspective. Suggestions for further research: Future research should be conducted using qualitative methods to deepen the understanding of why customers experience reduced trust in AI-generated property valuations. It would also be relevant to include real estate agents and industry stakeholders to gain a broader perspective on the role of AI in the valuation process
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
AI in the Real Estate Industry – A Threat or an Asset?
No full textSyfte: Syftet med denna studie är att analysera hur kundernas förtroende påverkas av AI-genererade fastighetsvärderingar samt vilka faktorer som påverkar förtroendet. Metod: Studien har genomförts med en kvantitativ ansats i form av en enkätundersökning. Respondenterna fick ta ställning till fiktiva fastighetsvärderingar, där vissa var märkta som AI-genererade och andra som utförda av fastighetsmäklare. Totalt deltog 184 respondenter. Data analyserades med hjälp av deskriptiv statistik. Resultat och slutsats: Resultaten visar att respondenter generellt har lägre förtroende för AI-genererade värderingar än för dem som utförts av en fastighetsmäklare, trots identiskt innehåll. De faktorer som påverkar tilliten mest är transparens, förståelse för hur värderingen tagits fram samt upplevelsen personlig kontakt. Examensarbetets bidrag: Studien bidrar till forskningen om tillit till AI genom att applicera Solberg m.fl. (2022) utvecklade tillitsmodell samt förklarbar AI (XAI) i ett praktiskt sammanhang inom fastighetsbranschen. Resultaten fördjupar förståelsen av begrepp som transparens och Black Box-problematiken ur ett kundperspektiv. Förslag till fortsatt forskning: Framtida forskning bör genomföras med kvalitativa metoder för att fördjupa förståelsen för varför kunder upplever minskat förtroende för AI-genererade fastighetsvärderingar. Det vore även relevant att inkludera fastighetsmäklare och branschaktörer för att få ett bredare perspektiv på AI:s roll i värderingsprocessen.Aim: The aim of this study is to examine how customer trust is affected by AI-generated property valuations and to identify the factors that influence that trust. Method: The study was conducted using a quantitative research approach through a structured online survey. Participants were presented with fictional property valuations, where some were labeled as AI-generated and others as conducted by real estate agents. In total, 184 respondents participated. The data were analyzed using descriptive statistics. Results and conclusions: The results indicate that respondents generally have lower trust in AI-generated valuations compared to those conducted by real estate agents, despite identical content. The most influential factors affecting trust were transparency and understanding of how the valuation was produced, and the perceived presence of personal interaction. Contribution of the thesis: This study contributes to existing research on trust in AI by applying Solberg et al. (2022) developed trust model and concepts from explainable AI (XAI) to a practical context within the real estate sector. The findings provide a deeper understanding of transparency and the Black Box issue from a customer’s perspective. Suggestions for further research: Future research should be conducted using qualitative methods to deepen the understanding of why customers experience reduced trust in AI-generated property valuations. It would also be relevant to include real estate agents and industry stakeholders to gain a broader perspective on the role of AI in the valuation process
Variations on the Author
Full text link“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
Full text linkWe 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
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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