… What can we learn from these early adopters? The analysis offered here begins by defining
BE. The definition turns out to be important, both to highlight potential misconceptions and to …

… The studies of Set I also examine major challenges for companies when investigating
potential use cases for machine learning and during implementation. The most frequent …

The Platform for Privacy Preferences (P3P), developed by the World Wide Web Consortium (W3C),
provides a standard computer-readable format for privacy policies and a protocol that …

… An overview of supervised learning In this study, one of our objectives is to train a machine
learning model that can accurately classify EV adopters and non-adopters based on …

… Several market studies were reviewed to determine best practices for conducting this
study and developing an early adopter product survey: 2012 Connecticut Efficient Lighting …

… We present four cases in which the role of older adults in innovation processes is examined:
as early adopters (case 1); in playing an active role in deviating from technology companies…

… of machine learning algorithms in … of machine learning in industry. We develop a framework
for factors and attributes that contribute towards the decision of adoption of machine learning …

… For several months I have been speaking with the firms and organizations that signed on to
Watson deals at a relatively early stage. Since most of the earliest adopters of the technology …

… Indeed, BenchSci found that if scientists took advantage of machine learning that read, …
early can often be a big plus, but it’s not the whole story. As we discuss, late adopters of the …

… The purpose of this paper is to provide a decision support system for managers to predict
an organization's probability of successful blockchain adoption using a machine learning …