Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
Despite near universal adoption by medium and large organizations, evidence regarding the effectiveness of information technology (IT) in human resource management (HRM) is mixed. The present study examines why these potential inconsistencies might exist and provides remedies to overcome these potential inconsistencies. To do this, we first develop a framework that categorizes outcomes associated with the use of IT in HRM by the level of organizational functioning (e.g., operational, managerial, and strategic) as well as the functional are of HRM of interest to the researcher. Using this framework, we classify the dependent variables from 332 studies and identify three potential explanations for the seemingly inconsistent findings. We then present three potential remedies to advance research in this domain. Insights from this research should provide suggestions for research that will help develop a richer understanding of how IT supports HRM.
Recommended Citation
Johnson, Richard and Kuhn, Kristine, "Information Technology and Human Resource Management: Revisiting the Past to Inform the Future" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 5.
https://aisel.aisnet.org/hicss-57/os/digitization/5
Information Technology and Human Resource Management: Revisiting the Past to Inform the Future
Hilton Hawaiian Village, Honolulu, Hawaii
Despite near universal adoption by medium and large organizations, evidence regarding the effectiveness of information technology (IT) in human resource management (HRM) is mixed. The present study examines why these potential inconsistencies might exist and provides remedies to overcome these potential inconsistencies. To do this, we first develop a framework that categorizes outcomes associated with the use of IT in HRM by the level of organizational functioning (e.g., operational, managerial, and strategic) as well as the functional are of HRM of interest to the researcher. Using this framework, we classify the dependent variables from 332 studies and identify three potential explanations for the seemingly inconsistent findings. We then present three potential remedies to advance research in this domain. Insights from this research should provide suggestions for research that will help develop a richer understanding of how IT supports HRM.
https://aisel.aisnet.org/hicss-57/os/digitization/5