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When and who leaves matters: Emerging results from an empirical study of employee turnover
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.
Delft University of Technology, NLD.
2018 (engelsk)Inngår i: PROCEEDINGS OF THE 12TH ACM/IEEE INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT (ESEM 2018), Association for Computing Machinery (ACM), 2018, artikkel-id a53Konferansepaper, 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. © 2018 ACM.

sted, utgiver, år, opplag, sider
Association for Computing Machinery (ACM), 2018. artikkel-id a53
Emneord [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
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-17702DOI: 10.1145/3239235.3267431ISI: 000469776800053Scopus ID: 2-s2.0-85061513487ISBN: 9781450358231 (tryckt)OAI: oai:DiVA.org:bth-17702DiVA, id: diva2:1294320
Konferanse
12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2018, Oulu, 11 October 2018 through 12 October
Tilgjengelig fra: 2019-03-07 Laget: 2019-03-07 Sist oppdatert: 2019-06-20bibliografisk kontrollert

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