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Cost and schedule overrun in Government IT projects. An empirical analysis

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IT projects form an essential part of the ongoing transition towards increased digitalization in the public sector. However, according to the extant literature, IT projects in both the public and private sector frequently experience cost and schedule overruns, and some fail altogether. In contrast to the private sector, the scientific knowledge on IT projects in the public sector is limited in several ways. To contribute to this knowledge gap, we present the results of an empirical analysis of 48 completed central government IT projects. Our study analyses data on projects completed from 2011 – 2018, which have been submitted to The Danish Council for ICT following established guidelines and a mandated IT project model. Our study offers empirical and methodological contributions. We present up-to-date valid empirical data about cost and schedule overruns in government IT projects at the national level submitted to the Danish Council for ICT for risk assessment. We find that these IT projects, on average, experience much lower cost overruns than those reported in previous studies. Moreover, we find that these projects, on average, do experience schedule overruns, but lower than those reported in previous studies. At the methodological level, we demonstrate how sampling bias can be addressed in an analysis of IT projects through the application of the Heckman correction method. This sampling bias is an acknowledged, but unaddressed issue in previous project management research.
Original languageEnglish
Publication date29 Jan 2020
Number of pages19
Publication statusPublished - 29 Jan 2020
EventScandinavian Workshop on E-government - Gothenburg University, Gothenburg, Sweden
Duration: 29 Jan 202030 Jan 2020
https://ait.gu.se/sweg2020

Workshop

WorkshopScandinavian Workshop on E-government
LocationGothenburg University
CountrySweden
CityGothenburg
Period29/01/202030/01/2020
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    Research areas

  • Government IT projects, Cost overrun, Schedule overrun

ID: 84865878