Sustainable technology: Antecedents and outcomes of households' adoption

被引:4
|
作者
Mateus, Raquel Alexandra Soeiro [1 ]
Oliveira, Tiago [1 ]
Neves, Catarina [1 ]
机构
[1] Univ NOVA Lisboa, NOVA Informat Management Sch NOVA IMS, Campus Campolide, P-1070312 Lisbon, Portugal
关键词
Household sustainable technology adoption; Smart home; Smart thermostats; Energy Efficiency; Structural Equation Modeling; SMART HOME; ENVIRONMENTAL SUSTAINABILITY; PERCEIVED RISK; BEHAVIOR; ENERGY; DETERMINANTS; ACCEPTANCE; RECOMMEND; INTENTION; BENEFITS;
D O I
10.1016/j.enbuild.2023.112846
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
With the development of cities, environmental concerns have increased with the adoption and develop-ment of measures to reduce environmental devastation becoming important. The use of sustainable tech-nologies as a solution, more specifically, smart homes, have gained special attention in reducing energy consumption as one of the sectors with the biggest impact on the environment. Few studies have been done to understand the consumer perspective on the household adoption of sustainable technologies, specifically regarding smart thermostats. Based on a sample of 327 responses and using a quantitative approach through structural equation modelling (SEM), this study aims to understand the relevant dimensions that influence households to adopt smart thermostats, as well as the outcomes of that adop-tion. The model was estimated using the partial least squares method, and final results suggest the rel-evance of internal and external motivators, privacy risks, and comfort to the adoption. Moreover, the adoption of sustainable technologies positively impacts two major outcomes: perceived well-being and intention to recommend. Comfort and pro-environmental behaviour also act as moderators for these two outcomes. The model revealed that 10 out of 13 hypotheses were supported, and the findings allow us to understand households' motivation for sustainable technologies adoption, emphasizing their importance in the topic of energy efficiency.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页数:15
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