The (Post)Pandemic Employment Model

Ana-Maria Ciuhu
Additional contact information
Ana-Maria Ciuhu: Institute of National Economy - Romanian Academy; National Institute of Statistics

Chapter Chapter 7 in The Economic and Social Impact of the COVID-19 Pandemic, 2024, pp 169-182 from Springer

Abstract: Abstract The year 2020 was a historic turning point, shaped by the COVID-19 pandemic and the digital revolution. This chapter explores how these forces have reshaped the employment landscape, with a focus on Romania. Before the pandemic, work was often rigid, with an 8-h workday in physical offices. However, the pandemic brought swift changes, introducing flexibility in where and when work takes place. Teleworking became the norm, challenging the traditional 5-day workweek, with the 4-day workweek gaining traction. Global companies like Unilever and Microsoft had already experimented with the 4-day workweek, proving its potential to boost productivity and employee satisfaction. Its wider adoption could drive post-pandemic recovery, offering benefits for both companies and employees. The pandemic also accelerated automation in Romania, streamlining tasks and optimising resource allocation. Artificial intelligence and artificial general intelligence are reshaping employment. This chapter concludes by examining job transformation due to automation, highlighting both opportunities for upskilling and concerns about job displacement. Insights from an OECD survey shed light on AI’s impact in finance and manufacturing sectors. In summary, this chapter navigates a changing employment landscape influenced by the pandemic and digitalisation, emphasising the need for proactive measures to ensure a fair and productive future of work.

Date: 2024
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:conchp:978-3-031-47780-5_7

Ordering information: This item can be ordered from
http://www.springer.com/9783031477805

DOI: 10.1007/978-3-031-47780-5_7

Access Statistics for this chapter

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