Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
When and who leaves matters: Emerging results from an empirical study of employee turnover
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Delft University of Technology, NLD.
2018 (English)In: PROCEEDINGS OF THE 12TH ACM/IEEE INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT (ESEM 2018), Association for Computing Machinery (ACM), 2018, article id a53Conference paper, Published paper (Refereed)
Abstract [en]

Background: Employee turnover in GSD is an extremely important issue, especially in Western companies offshoring to emerging nations. Aims: In this case study we investigated an offshore vendor company and in particular whether the employees' retention is related with their experience. Moreover, we studied whether we can identify a threshold associated with the employees' tendency to leave the particular company. Method: We used a case study, applied and presented descriptive statistics, contingency tables, results from Chi-Square test of association and post hoc tests. Results: The emerging results showed that employee retention and company experience are associated. In particular, almost 90% of the employees are leaving the company within the first year, where the percentage within the second year is 50-50%. Thus, there is an indication that the 2 years' time is the retention threshold for the investigated offshore vendor company. Conclusions: The results are preliminary and lead us to the need for building a prediction model which should include more inherent characteristics of the projects to aid the companies avoiding massive turnover waves. © 2018 ACM.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018. article id a53
Keywords [en]
GSD, Project management, Software engineering, Turnover, Job satisfaction, Offshore oil well production, Statistical tests, Contingency table, Descriptive statistics, Empirical studies, Employee retention, Employee turnover, Inherent characteristics, Prediction model
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-17702DOI: 10.1145/3239235.3267431ISI: 000469776800053Scopus ID: 2-s2.0-85061513487ISBN: 9781450358231 (print)OAI: oai:DiVA.org:bth-17702DiVA, id: diva2:1294320
Conference
12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2018, Oulu, 11 October 2018 through 12 October
Available from: 2019-03-07 Created: 2019-03-07 Last updated: 2019-06-20Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Chatzipetrou, PanagiotaŠmite, Darja

Search in DiVA

By author/editor
Chatzipetrou, PanagiotaŠmite, Darja
By organisation
Department of Software Engineering
Software Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 26 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf