دانلود رایگان مقاله انگلیسی بررسی تمایل به انتخاب اینترنت اشیا در محصولات فن آوری بهداشت و درمان - امرالد 2017

Abstract

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.

6.4 Concluding remarks

This research study proposed an integrated model that examines the outstanding factors of adoption intention toward IoT healthcare technology products from four different and complementary (of each other) theories: technology acceptance model, innovation diffusion theory, protect motivation theory and privacy calculus theory. How these factors differently affect individuals’ intention to adopt in terms of gender is also provided. This study has pointed to understanding individuals’ adoption intention of any emerging IoT-enabled product in healthcare. The majority of the developed hypotheses has been supported by the data. With our knowledge, this study is among the first that comprehensively investigates intention to adopt IoT healthcare technology issue from a behavioral perspective. On that sense, this study is a great example and theoretical foundation for future studies to investigate consumers’ intention to adopt IoT-enabled products in healthcare.

Main finding of this study is that mostly the factors related to technology acceptance and innovation diffusion significantly affect individuals’ decision to adopt IoT enabled products in healthcare. This information may help product designers to pay attention to all these factors when they design an IoT enabled healthcare product.