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When and who leaves matters: emerging results from an empirical study of employee turnover
Örebro universitet, Handelshögskolan vid Örebro Universitet. Blekinge Institute of Technology, Karlskrona, Sweden. (CERIS)ORCID-id: 0000-0002-0311-1502
Blekinge Institute of Technology, Karlskrona, Sweden.
Delft University of Technology, Delft, Netherlands.
2018 (engelsk)Inngår i: Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM, 2018, Oulu, Finland, IEEE Computer Society, 2018Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
IEEE Computer Society, 2018.
Serie
International Symposium on Empirical Software Engineering and Measurement, ISSN 1949-3770, E-ISSN 1938-6451
Emneord [en]
Software Engineering, GSD, Turnover, Project management
HSV kategori
Forskningsprogram
Informatik; Informationsteknologi
Identifikatorer
URN: urn:nbn:se:oru:diva-72563DOI: 10.1145/3239235.3267431Scopus ID: 2-s2.0-85061513487ISBN: 978-1-4503-5823-1 (tryckt)OAI: oai:DiVA.org:oru-72563DiVA, id: diva2:1289920
Konferanse
12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2018), Oulu, Finland, October 11-12, 2018
Tilgjengelig fra: 2019-02-19 Laget: 2019-02-19 Sist oppdatert: 2019-02-21bibliografisk kontrollert

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