<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Complexity is generally perceived to be a desirable attribute as far as the design/delivery of food and beverage experiences is concerned. However, that said, there are many different kinds of complexity, or at least people use the term when talking about quite different things, and not all of them are relevant to the design of food and drink experiences nor are they all necessarily perceptible within the tasting experience (either in the moment or over time). Consequently, the consumer often needs to infer the complexity of a tasting experience that is unlikely to be perceptible (in its entirety) in the moment. This paper outlines a number of different routes by which the chef, mixologist, and/or blender can both design and signal the complexity in the tasting experience.
mixture perception, menu design, Chemical technology, recipe, TP1-1185, Review, complexity
mixture perception, menu design, Chemical technology, recipe, TP1-1185, Review, complexity
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 17 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |