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Agee, P, Gao, X, Paige, F, McCoy, A and Kleiner, B (2021) A human-centred approach to smart housing. Building Research & Information, 49(01), 84–99.

Erişen, S (2021) Incremental transformation of spatial intelligence from smart systems to sensorial infrastructures. Building Research & Information, 49(01), 113–26.

Fettermann, D C, Borriello, A, Pellegrini, A, Cavalcante, C G, Rose, J M and Burke, P F (2021) Getting smarter about household energy: the who and what of demand for smart meters. Building Research & Information, 49(01), 100–12.

  • Type: Journal Article
  • Keywords: Water consumption; energy consumption; intelligent buildings; stated preference; discrete choice modelling; mixed multinomial logit model;
  • ISBN/ISSN: 0961-3218
  • URL: https://doi.org/10.1080/09613218.2020.1807896
  • Abstract:
    The development of policies promoting smart meter adoption is essential to guide the transition towards sustainable use of resources such as water, electricity and gas, as well as inform smart-city initiatives. This article explores household preferences in terms of different smart meters and identifies the amounts that households are willing to pay for different smart meter configurations to monitor electricity, water and gas based on the features of their home including dwelling type, size and property value. To this aim, we employ a mixed multinomial logit model that accounts for the heterogeneity in customers’ preferences for different smart meters. As a proof of concept, the proposed model is applied to a survey incorporating a discrete choice experiment carried out with 232 respondents in the Florianopolis metropolitan region, located in the south of Brazil. Our approach offers a number of advantages to facilitate the broader implementation of smart grid systems that would otherwise be overlooked using traditional approaches that rely on aggregated estimates for demand and willingness to pay for proposed schemes.

Fu, Y and Zhu, J (2021) Trusted data infrastructure for smart cities: a blockchain perspective. Building Research & Information, 49(01), 21–37.

Ihm, S, Lee, H, Lee, E and Park, Y (2021) A policy knowledge- and reasoning-based method for data-analytic city policymaking. Building Research & Information, 49(01), 38–54.

Kang, L, Liu, S, Zhang, H and Gong, D (2021) Person anomaly detection-based videos surveillance system in urban integrated pipe gallery. Building Research & Information, 49(01), 55–68.

Lee, Y L and Lee, Y (2021) Developing an autonomous psychological behaviour of virtual user to atypical architectural geometry. Building Research & Information, 49(01), 69–83.

Nuhu, B K, Aliyu, I, Adegboye, M A, Ryu, J K, Olaniyi, O M and Lim, C G (2021) Distributed network-based structural health monitoring expert system. Building Research & Information, 49(01), 144–59.

V E, S, Shin, C and Cho, Y (2021) Efficient energy consumption prediction model for a data analytic-enabled industry building in a smart city. Building Research & Information, 49(01), 127–43.

Valks, B, Arkesteijn, M H, Koutamanis, A and den Heijer, A C (2021) Towards a smart campus: supporting campus decisions with Internet of Things applications. Building Research & Information, 49(01), 1–20.