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Internet of Things: A Quantitative S...
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Rivera La Torres, Jose Luis.
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Internet of Things: A Quantitative Study of Forces Affecting Adoption of Innovation in Colorado Springs.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Internet of Things: A Quantitative Study of Forces Affecting Adoption of Innovation in Colorado Springs./
作者:
Rivera La Torres, Jose Luis.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:
204 p.
附註:
Source: Dissertations Abstracts International, Volume: 81-10, Section: A.
Contained By:
Dissertations Abstracts International81-10A.
標題:
Computer science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27743148
ISBN:
9781658469722
Internet of Things: A Quantitative Study of Forces Affecting Adoption of Innovation in Colorado Springs.
Rivera La Torres, Jose Luis.
Internet of Things: A Quantitative Study of Forces Affecting Adoption of Innovation in Colorado Springs.
- Ann Arbor : ProQuest Dissertations & Theses, 2020 - 204 p.
Source: Dissertations Abstracts International, Volume: 81-10, Section: A.
Thesis (D.C.S.)--Colorado Technical University, 2020.
This item must not be sold to any third party vendors.
Innovative technology has been evolving the world and effectiveness of man since the dawn of humanity. The earliest inventions have one thing in common with the latest inventions that we are currently experiencing. That commonality is described as the evolution of technology to allow for tasks to become more natural. The latest attempt in the realm of technology is the Internet of Things (IoT). IoT enabled the integration of machines and humanity while supporting and increasing mobility, streamlining processes, jobs, tasks, and cultivating an environment tailored to humanity. Currently, IoT is evolving, but it is ages away from a perfect system. A significant challenge is that developers are concentrating on improving IoT while ignoring the human factor, which creates gaps of knowledge since no study discovers the variables affecting diffusion of the system. The study addresses the issues that are affecting adoption in Colorado Springs residents. The research surveyed participants using an online survey instrument to measure the perception of IoT from participants. The online survey was engineered using a structured pattern to capture the experience, knowledge, and perceptions of each participant with guidance from Diffusion of Innovation (DOI), Planned Behavior (PB), Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT2), and Theory for Acceptance and Use of Pervasive Information Technology (TAUPIT) theories. Analysis of frequency demographic data revealed that out of the 97 participants, only 53 have knowledge of IoT, and regression analysis suggests that all behavior-characteristic variables have a positive correlation, thus impacting adoption.
ISBN: 9781658469722Subjects--Topical Terms:
523869
Computer science.
Subjects--Index Terms:
Adoption
Internet of Things: A Quantitative Study of Forces Affecting Adoption of Innovation in Colorado Springs.
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Innovative technology has been evolving the world and effectiveness of man since the dawn of humanity. The earliest inventions have one thing in common with the latest inventions that we are currently experiencing. That commonality is described as the evolution of technology to allow for tasks to become more natural. The latest attempt in the realm of technology is the Internet of Things (IoT). IoT enabled the integration of machines and humanity while supporting and increasing mobility, streamlining processes, jobs, tasks, and cultivating an environment tailored to humanity. Currently, IoT is evolving, but it is ages away from a perfect system. A significant challenge is that developers are concentrating on improving IoT while ignoring the human factor, which creates gaps of knowledge since no study discovers the variables affecting diffusion of the system. The study addresses the issues that are affecting adoption in Colorado Springs residents. The research surveyed participants using an online survey instrument to measure the perception of IoT from participants. The online survey was engineered using a structured pattern to capture the experience, knowledge, and perceptions of each participant with guidance from Diffusion of Innovation (DOI), Planned Behavior (PB), Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT2), and Theory for Acceptance and Use of Pervasive Information Technology (TAUPIT) theories. Analysis of frequency demographic data revealed that out of the 97 participants, only 53 have knowledge of IoT, and regression analysis suggests that all behavior-characteristic variables have a positive correlation, thus impacting adoption.
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