Adaptive Performance: Unlocking the Human Side of Digital Transformation

André Escórcio Soares (), Alessandro Toma () and Ruth Gaunt ()
Additional contact information
André Escórcio Soares: University of Lincoln
Alessandro Toma: University of Lincoln
Ruth Gaunt: University of Lincoln

Chapter Chapter 6 in Humanizing the Digital Workspace, 2025, pp 129-149 from Springer

Abstract: Abstract The digital transformation driven by the fourth industrial revolution has the potential to increase productivity by deploying technologies that can support production flexibility and efficiency (Bai et al., 2020). However, it is also accompanied by challenges that may jeopardise the efforts of organisations aiming to embark on this process. Discussions around the challenges organisations face are dominated by the view that there is a need for upskilling and reskilling the workforce. Yet this may not explain why new digital technology does not always come with increased productivity. This chapter explores the role of adaptive performance in the success of digital transformation. It focusses on how people adapt to technology implementation, from a job performance viewpoint. It does it by explaining how the concept of adaptive performance emerges from existing literature on job performance and by distinguishing it from other related concepts. Nonetheless, the concept of adaptive performance is not always clear, with different perspectives being covered by the literature about the topic. This chapter discusses different perspectives on adaptive performance, namely, adaptive performance as a behaviour, as an ability or as a process. Finally, this chapter aims to offer some insights on how organisations can promote adaptive performance.

Keywords: Adaptive performance; Digital transformation; Human factors; Workplace skills (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-76902-3_6

Ordering information: This item can be ordered from
http://www.springer.com/9783031769023

DOI: 10.1007/978-3-031-76902-3_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().