Organizational adoption of e‐HRM in Europe: An empirical exploration of major adoption factors
Abstract
Purpose: The purpose of this paper is to examine which factors influence the cross‐national organizational adoption of electronic human resource management (e‐HRM) in Europe. Design/methodology/approach: Major general and contextual influence factors are derived and tested based on a large‐scale survey with a sample of 2,336 organizations in 23 European countries using logistic regression. Findings: The findings first reveal that e‐HRM is a common practice throughout Europe since two‐thirds of all organizations have already adopted e‐HRM. Major general determinants of e‐HRM adoption are size, work organization, and configuration of HRM. In addition, there are major cross‐national differences in e‐HRM adoption, unexpectedly revealing Eastern post‐communist countries to lead e‐HRM adoption. Research limitations/implications: Abundance of general and scarcity of contextual factors imply that there should be further important factors of adoption not considered in this paper. Owing to its cross‐sectional character, the paper is not able to reveal findings of convergence or divergence of adoption over time. Practical implications: HR professionals should be informed about the advanced state of e‐HRM adoption, while some general insights are offered which kind of organizations should take an adoption of e‐HRM into consideration. Originality/value: This paper is a large‐scale sample‐based evaluation of cross‐national influence factors that drive organizational adoption of e‐HRM in Europe.
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Prior literature focusing on technology-driven HRM has considered TOP factors for understanding adoption, which reinforces the importance of TOP framework in identifying the antecedents of HRM (AI) assimilation in an organisation.
“Prior literature focusing on technology-driven HRM (i.e., e-HRM, HRIS) has considered TOP factors for understanding adoption (see, e.g., Bondarouk et al., 2017a; Burbach & Royle, 2014; Strohmeier & Kabst, 2009; Troshani et al., 2014), which reinforces the importance of TOP framework in identifying the antecedents of HRM (AI) assimilation in an organisation.”
From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Strohmeier & Kabst, 2009
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Electronic HRM: four decades of research on adoption and consequences
Bondarouk, T., Parry, E., & Furtmueller, E. (2017) · The International Journal of Human Resource Management · doi:10.1080/09585192.2016.1245672 · Cited by 423 · see citing works
“While some authors claim the size of an organization to be insignificant (Haines & Petit, 1997; Hussain et al., 2007), others describe it as a determining factor (Ball, 2001; Haines & Lafleur, 2008; Strohmeier & Kabst, 2009).”
BackgroundInfluentialAI-augmented HRM: Antecedents, assimilation and multilevel consequences
Prikshat, V., Malik, A., & Budhwar, P. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2021.100860 · Cited by 200 · see citing works
Whether and when e-HRM improves organizational performance: A meta-analysis
Cheng, Y., & Zou, Y. (2021) · Academy of Management Proceedings · doi:10.5465/ambpp.2021.133 · Cited by 3 · see citing works
- Authors
- Strohmeier, S., & Kabst, R.
- Affiliations
- Saarland University (DE)
- Justus-Liebig-Universität Gießen (DE)
- Venue
- Journal of Managerial Psychology
- Publisher
- Emerald
- Published
- 2009-08-14
- Volume
- 24
- Issue
- 6
- Pages
- 482-501
- ISSN
- 0268-3946 (ISSN-L)
- OpenAlex
- W1516325905
- Cited by
- 142
- References
- 5
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 10 · 2023: 15 · 2022: 5 · 2021: 14 · 2020: 3 · 2019: 11 · 2018: 7 · 2017: 8 · 2016: 5 · 2015: 10 · 2014: 15 · 2013: 9 · 2012: 10
- FWCI
- 10.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Managerial Psychology (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Human Resource and Talent Management
- Keywords
- e-HRM, electronic human resource management, organizational adoption, cross-national differences, technology adoption factors, organizational size, work organization, post-communist states, Europe
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