114,787 research outputs found
Double Whammy - How ICT Projects are Fooled by Randomness and Screwed by Political Intent
The cost-benefit analysis formulates the holy trinity of objectives of
project management - cost, schedule, and benefits. As our previous research has
shown, ICT projects deviate from their initial cost estimate by more than 10%
in 8 out of 10 cases. Academic research has argued that Optimism Bias and Black
Swan Blindness cause forecasts to fall short of actual costs. Firstly, optimism
bias has been linked to effects of deception and delusion, which is caused by
taking the inside-view and ignoring distributional information when making
decisions. Secondly, we argued before that Black Swan Blindness makes
decision-makers ignore outlying events even if decisions and judgements are
based on the outside view. Using a sample of 1,471 ICT projects with a total
value of USD 241 billion - we answer the question: Can we show the different
effects of Normal Performance, Delusion, and Deception? We calculated the
cumulative distribution function (CDF) of (actual-forecast)/forecast. Our
results show that the CDF changes at two tipping points - the first one
transforms an exponential function into a Gaussian bell curve. The second
tipping point transforms the bell curve into a power law distribution with the
power of 2. We argue that these results show that project performance up to the
first tipping point is politically motivated and project performance above the
second tipping point indicates that project managers and decision-makers are
fooled by random outliers, because they are blind to thick tails. We then show
that Black Swan ICT projects are a significant source of uncertainty to an
organisation and that management needs to be aware of
Predicting Software Revision Outcomes on Github Using Structural Holes Theory
Many software repositories are hosted publicly online via social platforms. Online users contribute to the software projects not only by providing feedback and suggestions, but also by submitting revisions to improve the software quality. This study takes a close look at revisions and examines the impact of social media networks on the revision outcome. A novel approach with a mix of different research methods (e.g., ego-centric social network analysis, structural holes theory and survival analysis) is used to build a comprehensible model to predict the revision outcome. The predictive performance is validated using real life datasets obtained from GitHub, the social coding website, which contains 32,962 pull requests to submit revisions, 20,399 distinctive software project repositories, and a social network of 234,322 users. Good predictive performance has been achieved with an average AUC of 0.84. The results suggest that a repository host's position in the ego network plays an important role in determining the duration before a revision is accepted. Specifically, hosts that are positioned in between densely connected social groups are likely to respond more quickly to accept the revisions. The study demonstrates that online social networks are vital to software development and advances the understanding of collaboration in software development research. The proposed method can be applied to support decision making in software development to forecast revision duration. The result also has several implications for managing project collaboration using social media
Benefits of Computer Based Content Analysis to Foresight
Purpose of the article: The present manuscript summarizes benefits of the use of computer-based content
analysis in a generation phase of foresight initiatives. Possible advantages, disadvantages and limitations of
the content analysis for the foresight projects are discussed as well.
Methodology/methods: In order to specify the benefits and identify the limitations of the content analysis
within the foresight, results of the generation phase of a particular foresight project performed without
and subsequently with the use of computer based content analysis tool were compared by two proposed
measurements.
Scientific aim: The generation phase of the foresight is the most demanding part in terms of analysis duration,
costs and resources due to a significant amount of reviewed text. In addition, the conclusions of the foresight
evaluation are dependent on personal views and perceptions of the foresight analysts as the evaluation is
based merely on reading. The content analysis may partially or even fully replace the reading and provide an
important benchmark.
Findings: The use of computer based content analysis tool significantly reduced time to conduct the foresight
generation phase. The content analysis tool showed very similar results as compared to the evaluation
performed by the standard reading. Only ten % of results were not revealed by the use of content analysis tool.
On the other hand, several new topics were identified by means of content analysis tool that were missed by
the reading.
Conclusions: The results of two measurements should be subjected to further testing within more foresight
projects to validate them. The computer based content analysis tool provides valuable benchmark to the
foresight analysts and partially substitute the reading. However, a complete replacement of the reading is not
recommended, as deep understanding to weak signals interpretation is essential for the foresight
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