Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-24T02:32:28.073Z Has data issue: false hasContentIssue false
  • English
  • Français

The importance of representativeness as well as timeliness in studying technology: Three additional suggestions

Published online by Cambridge University Press:  09 September 2022

Jenna A. Van Fossen Open the ORCID record for Jenna A. Van Fossen [Opens in a new window] ,
Rachael H. Pyram ,
Sandra L. Fisher  and
Michael E. Wasserman
Jenna A. Van Fossen*
Affiliation:
Department of Psychology, Michigan State University Münster School of Business, Münster University of Applied Sciences, Germany
Rachael H. Pyram
Affiliation:
Department of Psychology, Michigan State University
Sandra L. Fisher
Affiliation:
Münster School of Business, Münster University of Applied Sciences, Germany
Michael E. Wasserman
Affiliation:
Münster School of Business, Münster University of Applied Sciences, Germany
*
*Corresponding author: Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 15 , Issue 3 , September 2022 , pp. 465 - 468
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the Society for Industrial and Organizational Psychology

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Attaran, M., Attaran, S., & Kirkland, D. (2019). The need for digital workplace: Increasing workforce productivity in the information age. International Journal of Enterprise Information Systems, 15(1), 1–23.CrossRefGoogle Scholar
Balkmar, D., & Mellström, U. (2018). Masculinity and autonomous vehicles: Adegendered or resegregated future system of automobility? Transfers, 8(1), 44–63.CrossRefGoogle Scholar
Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., & Coelho, P. S. (2021). Assessing the role of age, education, gender and income on the digital divide: Evidence for the European Union. Information Systems Frontiers, 23(4), 1007–1021.CrossRefGoogle Scholar
Fisher, S. L., & Howardson, G. N. (2022). Fairness of artificial intelligence in human resources-held to a higher standard? In Strohmeier, Stefan (Ed.), Handbook of research on artificial intelligence in human resource management (pp. 303–322). Edward Elgar Publishing.Google Scholar
Harper, S., & Yesilada, Y. (2012). Emerging technologies and web accessibility: Research challenges and opportunities focusing on vision issues. Disability and Rehabilitation: Assistive Technology, 7(1), 1–19.Google Scholar
Jones, K. S., Newman, D. A., Su, R., & Rounds, J. (2022). Vocational interests and adverse impact: How attraction and selection on vocational interests relate to adverse impact potential. Journal of Applied Psychology, 107(4), 604–627.CrossRefGoogle ScholarPubMed
Lai, J., & Widmar, N. O. (2021). Revisiting the digital divide in the COVID-19 era. Applied Economic Perspectives and Policy, 43(1), 458–464.CrossRefGoogle ScholarPubMed
Li, C. (2021, October 11). Worsening global digital divide as the US and China continue zero-sum competitions. Brookings. https://www.brookings.edu/blog/order-from-chaos/2021/10/11/worsening-global-digital-divide-as-the-us-and-china-continue-zero-sum-competitions/ Google Scholar
Ng, T. W., & Feldman, D. C. (2012). Evaluating six common stereotypes about older workers with meta-analytical data. Personnel Psychology, 65(4), 821–858.CrossRefGoogle Scholar
Ravid, D. M., Tomczk, D. L., White, J. C., & Behrend, T. S. (2020). EPM 20/20: Areview, framework, and research agenda for electronic performance monitoring. Journal of Management, 46(1), 100–126.CrossRefGoogle Scholar
Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328.CrossRefGoogle Scholar
U.S. Census Bureau. (2021, October 8). ASE tables. https://www.census.gov/programs-surveys/ase/data/tables.html Google Scholar
Vogels, E. A. (2021, June 22). Digital divide persists even as Americans with lower incomes make gains in tech adoption. Pew Research Center. https://www.pewresearch.org/fact-tank/2021/06/22/digital-divide-persists-even-as-americans-with-lower-incomes-make-gains-in-tech-adoption/ Google Scholar
White, J., Ravid, D., Siderits, I., & Behrend, T. S. (2022). An urgent call for I-O psychologists to produce timelier technology research. Industrial and Organizational Psychology: Perspectives on Science and Practice, 15(3), 441–459.CrossRefGoogle Scholar