We designed a wine recommendation robot and deployed it in a small supermarket. In a study aimed to evaluate our design we found that people with no intent to buy wine were interacting with the robot rather than the intended audience of wine-buying customers. Behavioural data, moreover, suggests a very different evaluation of the robot than the surveys that were completed. We also found that groups were interacting more with the robot than individuals, a finding that has been reported more often in the literature. All of these findings taken together suggest that a novelty effect may have been at play. It also suggests that field studies should take this effect more seriously. The main contribution of our work is in identifying and proposing a set of indicators and thresholds that can be used to identify that a novelty effect is present. We argue that it is important to focus more on measuring attitudes towards robots that may explain behaviour due to novelty effects. Our findings also suggest research should focus more on verifying whether real user needs are met.
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Digitalization is the core component of future development in the 4.0 industrial era. It represents a powerful mechanism for enhancing the sustainable competitiveness of economies worldwide. Diverse triggering effects shape future digitalization trends. Thus, the main research goal in this study is to use sustainable competitiveness pillars (such as social, economic, environmental and energy) to evaluate international digitalization development. The proposed empirical model generates comprehensive knowledge of the sustainable competitiveness-digitalization nexus. For that purpose, a nonlinear regression has been applied on gathered annual data that consist of 33 European countries, ranging from 2010 to 2016. The dataset has been deployed using Bernoulli’s binominal distribution to derive training and testing samples and the entire analysis has been adjusted in that context. The empirical findings of artificial neural networks (ANN) suggest strong effects of the economic and energy use indicators on the digitalization progress. Nonlinear regression and ANN model summary report valuable results with a high degree of coefficient of determination (R2>0.9 for all models). Research findings state that the digitalization process is multidimensional and cannot be evaluated as an isolated phenomenon without incorporating other relevant factors that emerge in the environment. Indicators report the consumption of electrical energy in industry and households and GDP per capita to achieve the strongest effect.
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Onderzoekers van het MOVES-onderzoeksprogramma hebben een vierde whitepaper uitgebracht. In deze publicatie is de belangrijkste kennis over maatschappelijke effecten van topsportevenementen bij elkaar gebracht. Ook zijn er kennishiaten benoemd die richting geven aan vervolgonderzoek. De thema’s die worden behandeld zijn: sportdeelname, welzijn, sociale cohesie, trots en geluk. Daarnaast is beschreven op welke manier topsportevenementen als hefboom (‘podium’) gebruikt kunnen worden en hoe dat tot impact en legacy kan leiden. Dit whitepaper maakt deel uit van werkpakket 4.
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