The Use of Affective Computing in the Conceptual Design Stage of New Products View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Agustín Job Hernández-Montes , Guillermo Cortés-Robles , Giner Alor-Hernández , Jorge Luis García-Alcaraz

ABSTRACT

The innovation process, seen as a set of problem-solving activities needs novel approaches to assist decision-making in the evaluation of different potential solutions. Typical perspective as the Analytic Hierarchy Process, similarity-based techniques, and essential performance indicators find their limits when it is necessary to take into account a crucial factor: emotions. The emotional response to unique product attributes is in fact, a determinant element to succeed in a market. The affective computing paradigm is a recent technology that allows knowing the person’s mood by using different strategies: the use of the camera to recognize an image, the tone voice of a person, and the use of different sensors and wearable devices. Some common features are the use of sensors that measure heart rate, the excitement of an individual, and the detection of the bioelectric activity of the brain at the instant of someone sees something specific. The affective computing has become more relevant in the past years. Emotions are fundamental to human experience, influencing cognition, perception, and everyday tasks such as learning, communication, and even rational decision-making. Industry asks for a different effective mechanism to select the best alternative during design and evaluation of products or services, particularly in the conceptual design stage. Decisions at this stage will determine the primary attributes of a product. The affective computing paradigm can show what characteristics of the product are more attractive to the design stakeholder and allow a review before launching a product. More... »

PAGES

207-228

References to SciGraph publications

Book

TITLE

Managing Innovation in Highly Restrictive Environments

ISBN

978-3-319-93715-1
978-3-319-93716-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-93716-8_10

DOI

http://dx.doi.org/10.1007/978-3-319-93716-8_10

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105326394


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