Purpose
The purpose of the study is to investigate critical factors affecting individuals’ intention to adopt internet of things (IoT) products in healthcare.
Design/methodology/approach
An integrated model was developed based on technology acceptance model (TAM), innovation diffusion theory (IDT), technological innovativeness (TI), protection motivation theory and privacy calculus theory. The model was tested with 426 respondents (222 females, 204 males) using partial least square structural equation model with all data grouped by gender.
Findings
Based on the results of the complete model, perceived advantage (PA), image and perceived ease of use (PEOU) constructs have a significant effect on intention to adopt IoT healthcare technology products. The results show that for females, compatibility and trialability have more impact on PEOU whereas for males PA has more impact on PEOU. Image, perceived privacy risk, perceived vulnerability have more impact on males when compared to females.
Research limitations/implications
Research conducted only among Turkish people.
Originality/value
This study investigated adoption of future technology, “internet of things”, products in healthcare from a behavioral perspective by integrating various theories. The reason is that before launching any technology into the market, its facilitative factors should be researched for the people who are going to use this in their daily routine.
<span lang="EN-US">The purpose of this study is to investigate performances of some of the data mining approaches while understanding desire and intention to participate in virtual communities and its antecedents. A research model has been developed following the literature review and the model was tested afterwards. In research part of the study, some of the data mining approaches as JRip, Part, OneR Method, Multilayer Perceptron (Neural Networks), Bayesian Networks have been used. Based on the analysis conducted it has been found out that Multilayer Neural Network had the best correct classification rate and lowest RMSE.</span>
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