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Internet of Things (loT) is the next wave of industry revolution that generates signifieant amount of various serviees, such as personal health care and green energy monitoring, which people may subscribe for their convenience. These services may have different featu res, such as fixed or mobile, scalable or non scalable, portable or non-portable. Thus, recommending loT services to users based on objects they own will become very important for the success of loT. In this preliminary work, we introduce the concept of service recommender systems in loT by a formal model for loT recommendation. We propose a graph based recommender system that takes into account the unique structure ofIoT.

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Purpose Smart homes are recent Internet of Things applications that aim to improve residents’ quality of life. Despite its potential, the adoption of smart homes, in general, and its devices and appliances, in specific, is not reaching a mass market yet. This study aims to investigate the factors that influence residents’ intention to buy smart homes devices in Jordan. Design/methodology/approach This paper proposes a novel model to study users’ intention to buy smart homes devices by following a quantitative method. Responses were collected and statistically analyzed from 375 households using structural equation modeling. Findings Results show that user awareness, perceived cost, perceived enjoyment, personalization, user trust and social influences significantly influence the intention to buy smart home devices. Originality/value To the best of the authors’ knowledge, this paper is the first study attempts to predict intention to buy smart home devices in Jordan. The findings provide meaningful implications for smart home devices providers.