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Employers’ Revelation of Decision-making Keys for Employing People with Visual Impairment: Mixed-method Analysis of Employers’ Motivations

By:
Open Access
|Oct 2022

Abstract

Background: People with visual impairment or blindness (PWVIB) face many barriers related to employment. Although literature explores employers’ concerns regarding the employment of PWVIB, stating the concern and developing a solution are different.

Objectives: Employers’ solutions to concerns regarding hiring PWVIB have not been surveyed. This study addresses the gap by surveying employers to determine practical solutions and developing the Solutions for Improving Employment of People with Visual Disabilities (SIEPVD) model.

Methods: We employed a mixed-method design based on the 975 completed surveys from employers with hiring authority. We also identified and tagged major themes and developed an empirical model. Structural Equation Modelling (SEM) was employed to test the model’s goodness of fit.

Results: Findings highlight the need for evidence of job capabilities such as financial incentives, information provision, and adequate job vacancies. Evidence or financial incentives directly and positively affect employers’ attitudes toward hiring PWVIB. Financial incentives also mediate information provision and job match with employers’ attitudes toward hiring PWVIB.

Conclusions: This is the first study to perform employers’ integration by creating solutions to increase PWVIB’s employment rate. Results may help PWVIB in its employment efforts. Thus, the approach when applying for jobs or attending interviews should be reviewed. Practical contributions are discussed.

DOI: https://doi.org/10.2478/bsrj-2022-0007 | Journal eISSN: 1847-9375 | Journal ISSN: 1847-8344
Language: English
Page range: 104 - 119
Submitted on: Feb 16, 2021
Accepted on: Nov 22, 2021
Published on: Oct 15, 2022
Published by: IRENET - Society for Advancing Innovation and Research in Economy
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2022 Eyal Eckhaus, published by IRENET - Society for Advancing Innovation and Research in Economy
This work is licensed under the Creative Commons Attribution 4.0 License.