Individual adaptive performance in computer-mediated work: A migration perspective

Edgardo R. Bravo, Jhony Ostos

Research output: Contribution to journalArticle in a journalpeer-review

7 Scopus citations


Purpose: In dynamic environments, employees should respond to changing demands carrying out actions to achieve proper knowledge of the information systems (IS) that they use (individual adaptation). However, few studies have investigated the determinants of this behaviour. This study proposes and empirically evaluates a cognitive-attitudinal model grounded in migration theory, which considers push, pull and mooring factors. Design/methodology/approach: Data collected from ERP users were analysed using partial least squares. Findings: Coherent with migration theory, the results show that the individual adapts influenced by push factors (dissatisfaction with their current command of the IS), pull factors (expected benefits from improving their command) and mooring factors (attitude to the adaptation process). Also, inertia and cost of adaption impact on attitude. Research limitations/implications: This study introduces migration theory to the IS literature as a basis for comprehensively explaining adaptation in organisational settings. Practical implications: The results suggest that management should: exhibit the instrumental benefits of a solid command of the IS; show the current gap in employee knowledge to revert it and, introduce changes to move employees out of their comfort zone to encourage ongoing learning and reduce resistance. Originality/value: While previous studies have focused on the implementation stage and the emotional factors to explain adaptation, this study intends to bridge this gap by investigating cognitive-attitudinal factors that trigger the intention to adapt in the post-adoption stage. The findings of this study are useful to researchers in adaptation behaviour, and to managers to promote IS learning for their staff.

Original languageEnglish
Pages (from-to)123-146
Number of pages24
JournalInformation Technology and People
Issue number1
Early online date25 Feb 2020
StatePublished - 22 Jan 2021

Bibliographical note

Publisher Copyright:
© 2019, Emerald Publishing Limited.

Copyright 2021 Elsevier B.V., All rights reserved.


  • Adaptation
  • Adaptive performance
  • Information systems
  • Learning
  • Migration theory


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