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The proposed research model was empirically validated using data collected from 392 respondents in China. The data was analyzed using the partial least squares method, a statistical analysis technique based on structural equation modeling.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The results indicate that performance expectancy, effort expectancy, social influence, habit, compatibility and innovativeness have significant direct and indirect effects on FWT adoption and the intention to recommend it. The significance of people\u2019s intention to recommend FWT to others in social networking sites (e.g. Facebook, Weibo, and WeChat) is also confirmed.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>The findings may facilitate the design and implementation of FWT products, applications and functionalities that can achieve high consumer acceptance and positive recommendations in social networks.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This study is among the first to investigate FWT adoption from behavioral, social and environmental perspectives. It also highlights the importance of social marketing campaigns and suggests directions of future wearable technology adoption research.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/imds-01-2018-0009","type":"journal-article","created":{"date-parts":[[2018,8,17]],"date-time":"2018-08-17T05:41:08Z","timestamp":1534484468000},"page":"170-188","source":"Crossref","is-referenced-by-count":176,"title":["Acceptance and use predictors of fitness wearable technology and intention to recommend"],"prefix":"10.1108","volume":"119","author":[{"given":"Md 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