A retail environment can be thought as an environment where customers can buy products, goods or services. The user-experience in physical retail environments is important not only for facilitating the selling of goods and services, but also for providing satisfaction and appealing to retain customers over the long term. The user-experience can be enhanced by adapting aspects of the physical environment such as music, colour, fragrance to the tastes of the customers. In this paper we propose a user-aware approach to adapt physical aspects of a retail environment in order to improve the perceived comfort level. We introduce a model of the user context, which can be used both for representing information about the customers and for driving the adaptation of the environment. The proposed decision system is based on a microservice architecture providing both modularity and flexibility. Real-world examples are also used to show applications of the approach.
User-aware comfort in retail environments / Bicocchi, N.; Boese, S.; Cabri, G.. - 11939:(2019), pp. 14-25. (Intervento presentato al convegno 11th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2019 tenutosi a ita nel 2019) [10.1007/978-3-030-34974-5_2].
User-aware comfort in retail environments
Bicocchi N.;Cabri G.
2019
Abstract
A retail environment can be thought as an environment where customers can buy products, goods or services. The user-experience in physical retail environments is important not only for facilitating the selling of goods and services, but also for providing satisfaction and appealing to retain customers over the long term. The user-experience can be enhanced by adapting aspects of the physical environment such as music, colour, fragrance to the tastes of the customers. In this paper we propose a user-aware approach to adapt physical aspects of a retail environment in order to improve the perceived comfort level. We introduce a model of the user context, which can be used both for representing information about the customers and for driving the adaptation of the environment. The proposed decision system is based on a microservice architecture providing both modularity and flexibility. Real-world examples are also used to show applications of the approach.Pubblicazioni consigliate
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