IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Assistive Technology and Human Capital for Workforce Diversity

Assistive Technology and Human Capital for Workforce Diversity
View Sample PDF
Author(s): Ben Tran (Alliant International University, USA)
Copyright: 2019
Pages: 12
Source title: Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7368-5.ch018

Purchase

View Assistive Technology and Human Capital for Workforce Diversity on the publisher's website for pricing and purchasing information.

Abstract

The purpose of this chapter is not on the varieties of the availability of assistive technologies (AT) and their usages based on individuals' specified disability, so that individuals who require the usage of ATs can be of equal playing field compared to those individuals who do not require the usage of ATs. For information regarding AT and the state of AT in the past, present, and future in the United States, ADA and the like refer to Tran's article titled “Assistive Technology.” The purpose of this chapter is beyond the coverage of Tran's “Assistive Technology” article, such that the purpose of this article is on the end results that AT could provide and contribute to the diverse workforce, and the role AT play in relations to workforce development—from an international perspective.

Related Content

Aline Bossi Pereira da Silva, Celmar Guimarães da Silva, Regina Lúcia de Oliveira Moraes. © 2020. 26 pages.
Maria Alciléia Alves Rocha, Gabriel de Almeida Souza Carneiro. © 2020. 23 pages.
Saulo Silva, Mariana Carvalho, Orlando Belo. © 2020. 22 pages.
Vivian Varnava, Aurora Constantin, Cristina Adriana Alexandru. © 2020. 23 pages.
Werner Walder Marin, Pollyana Notargiacomo. © 2020. 18 pages.
Ehm Kannegieser, Daniel Atorf. © 2020. 9 pages.
Hao Wang, Chien-Wen Ou Yang, Chun-Tsai Sun. © 2020. 24 pages.
Body Bottom