User acceptance of Internet of things(IoT) devices and services

Abstract

ICT markets around the world have become more competitive and continue to grow. Specifically, in recent years, ubiquitous connectivity has realized with the advancements in, and decreasing costs of sensors, storage, and bandwidth have paved the way for a rapidly rising new segment of Information Technology ？ the Internet of Things (IoT). The market forecast for IoT is very promising. According to Gartner (2014), 4.9 billion of connected things will be in use in 2015, up 30 percent from 2014, and will reach 25 billion by 2020. Machina research (2011, 2013) forecasted 25 billion of connected things in 2020 with $ 948 billion market size. The main driving force behind these positive prospects is declining cost. Fairview Capital (2015) reported that the cost of computing power measured by price per million transistors is nearly 4,000 times lower today comparing two decades ago. Deloitte (2013) said the costs of storage and internet bandwidth have fallen dramatically ？ storing one gigabyte of data now costs no more than a couple of cents and internet bandwidth costs have fallen by 98% in just over a decade. Also, technological progress such as a dramatic increase in processing power, storage and bandwidth has contributed to initial IoT market formation. This study investigates user acceptance of wearable devices and smart home services by an extended perspective of traditional theories through empirical analysis. Wearable devices and smart home services are two representative business areas in IoT industry. Vision mobile (2015) showed smart home and wearables are most targeted market of IoT developers. IoT Analytics (2015) presented ‘The 10 most popularity Internet of Things applications’ based on web analytics and revealed smart home ranked the highest popularity followed by wearable devices. The first essay develops a research model for adopting wearable devices from the perspective of customers’ perceived value. The study investigates the impact of each component of perceived benefit and risk on the perceived value of the wearable devices and explores how its attributes affect customers’ perceived benefits. This study verified that perceived value is a clear antecedent of adoption intention. This study investigates the relationships between the value of wearable devices (i.e., perceived usefulness, enjoyment, social image) and the product characteristics (i.e., functionality, compatibility, visual attractiveness, and brand name). Perceived benefit including perceived usefulness, enjoyment, and social image seems to have a greater impact on perceived value than the level of perceived risk. For the potential user group, perceived usefulness was shown to have a slightly stronger effect on perceived value than perceived enjoyment. But for the actual user group, unlike potential users, perceived enjoyment seems to play the most influential role in affecting perceived value. This study also demonstrated that perceived risk is only an significant factor for potential users but not for actual users. All components reflecting wearable device characteristics positively affect perceived benefit both for potential and actual users. The second essay proposes and examines a research model that can explain the potential customers’ behavioral intentions to adopt and use smart home services. this study employed the theory of planned behavior (TPB) and enhanced by proposing six exogenous variables which reflect the funtionality of smart home services such as automaion, mobility, and interoperability, risk factors (i.e., security/privacy risk, physical risk), and trust in service providers. This study confirmed three components of the TPB (i.e., attitude, subjective norm, and perceived behavioral control) as key factors to influence the behavioral intention to use smart home services. This study verified mobility was shown to have a stronger effect on attitude than interoperability. It can be inferred that potential users would recognize more value in remote access functionalities such as remote control, management, and monitoring without time and location restriction based on networking between mobile devices and home appliances than in ubiquitous service from different vendors. Automation, the long standing dream of proactively helping their residents in a smart home, had a significant influence on attitude only for single-family house residents, not for apartment/multi-family house residents. This result may be caused by the difference of house architecture. Furthermore, this study verified security/privacy risk was a negatively affected the attitude for both single-family house and apartment/multi-family house residents, but physical risk was not. This dissertation aims to propose a new technology adoption model for new devices and services of the new emerging ICT market, IoT. Theoretically, this study contributes to a more systematic understanding of wearable device and smart home service adoption based on the extended theoretical models. Furthermore, this study provides meaningful insights for the wearable device manufacturers and smart home service providers in terms of marketing and R&D considering consumer segmentation.