Hostname: page-component-848d4c4894-pjpqr Total loading time: 0 Render date: 2024-06-22T19:54:49.140Z Has data issue: false hasContentIssue false
  • English
  • Français

Conceptual technology frameworks offer timelier and more influential research

Published online by Cambridge University Press:  09 September 2022

Neil Morelli  and
Renee Davis
Neil Morelli*
Affiliation:
Codility
Renee Davis
Affiliation:
talentDAO
*
*Corresponding author. Email: neil.morelli@codility.com
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. 479 - 483
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

Arthur, W. Jr, Keiser, N. L., & Doverspike, D. (2018). An information-processing-based conceptual framework of the effects of unproctored internet-based testing devices on scores on employment-related assessments and tests. Human Performance, 31(1), 1–32. https://doi.org/10.1080/08959285.2017.1403441 Google Scholar
Diep, N. (2020, January 16). Big data analytics: Apache Spark vs. Apache Hadoop. Towards Data Science. https://towardsdatascience.com/big-data-analytics-apache-spark-vs-apache-hadoop-7cb77a7a9424 Google Scholar
Ethereum.org. (2021, September 7). Decentralized autonomous organizations. Ethereum.org.https://ethereum.org/en/dao/ Google Scholar
Feitosa, J., & Salas, E. (2020). Today’s virtual teams: Adapting lessons learned to the pandemic context. Organizational Dynamics, 50(1). https://doi.org/10.1016/j.orgdyn.2020.100777 Google Scholar
Hassan, S., & De Filippi, P. (2021). Decentralized autonomous organization. Internet Policy Review, 10(2), 1–10.Google Scholar
Hertel, G., Geister, S., & Konradt, U. (2005). Managing virtual teams: Areview of current empirical research. Human Resource Management Review, 15(1), 69–95.CrossRefGoogle Scholar
Hoch, J. E., & Kozlowski, S. W. J. (2014). Leading virtual teams: Hierarchical leadership, structural supports, and shared team leadership. Journal of Applied Psychology, 99(3), 390–403. https://doi.org/10.1037/a0030264.Google ScholarPubMed
Hsieh, Y. Y., Vergne, J. P., Anderson, P., Lakhani, K., & Reitzig, M. (2018). Bitcoin and the rise of decentralized autonomous organizations. Journal of Organization Design, 7(1), 1–16.Google Scholar
Jentzsch, C. (2016, November). Decentralized autonomous organization to automate governance [White paper]. https://lawofthelevel.lexblogplatformthree.com/wp-content/uploads/sites/187/2017/07/WhitePaper-1.pdfGoogle Scholar
Landers, R., & Behrend, T. (2017). When are models of technology in psychology most useful? Industrial and Organizational Psychology: Perspectives on Science and Practice, 10(4), 668–675.CrossRefGoogle Scholar
Liao, C. (2017). Leadership in virtual teams: Amultilevel perspective. Human Resource Management Review, 27(4), 648–659.CrossRefGoogle Scholar
Mesmer-Magnus, J. R., DeChurch, L. A., Jiménez-Rodriguez, M., Wildman, J., & Shuffler, M. (2011). A meta-analytic examination of virtuality and information sharing in teams. Organizational Behavior and Human Decision Processes, 115(2), 214–225.CrossRefGoogle Scholar
Morelli, N., Potosky, D., Arthur, W., & Tippins, N. (2017). A call for conceptual models of technology in I-O psychology: An example from technology-based talent assessment. Industrial and Organizational Psychology: Perspectives on Science and Practice, 10(4), 634–653.CrossRefGoogle Scholar
Orlikowski, W. J., & Scott, S. V. (2008). Sociomateriality: Challenging the separation of technology, work, and organization. Academy of Management Annals, 2(1), 433–474.Google Scholar
Potosky, D. (2008). A conceptual framework for the role of the administration medium in the personnel assessment process. Academy of Management Review, 33(3), 629–648.CrossRefGoogle Scholar
Saks, A. M. (2006). Antecedents and consequences of employee engagement. Journal of Managerial Psychology, 21(7), 600–619.CrossRefGoogle Scholar
Soda, G., & Zaheer, A. (2012). A network perspective on organizational architecture: Performance effects of the interplay of formal and informal organization. Strategic Management Journal, 33(6), 751–771. https://doi.org/10.1002/smj.1966 CrossRefGoogle Scholar
White, J. C., Ravid, D. M., Siderits, I. O., & 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).Google Scholar