Consumers' Willingness to Invest in Smart Home Technologies Using Machine Learning: A Survey-Based Analysis in Qatar

Abstract

This paper investigates the consumers' willingness to invest in smart home technologies and the savings they expect by using machine learning. Data is gathered using questionnaires from 2,014 consumers who participated in a smart home technology-related survey in Qatar. Variable importance ranking based on decision tree models is carried out to identify the most critical questions in the survey and the daily aspects that affect consumers' willingness to invest in smart home technologies. The findings show that demographics, especially education level and cultural backgrounds, greatly impact consumers' decisions concerning smart homes. Moreover, consumers with programmable household appliances are more likely to invest in smart home technologies.