A database for publications published by researchers and students at SimulaMet.
Status
Research area
Journal articles
Realizing benefits in public IT projects: A multiple case study
a journal (2022).Status: Submitted
Realizing benefits in public IT projects: A multiple case study
IT investments in the public sector are large, and it is essential that they lead to benefits for the organizations themselves and for the wider society. While there is evidence suggesting a positive connection between the existence of benefits management practices and benefits realization, less is known about how to implement such practices effectively. The paper aims to provide insights into when benefits are most likely to be realized, and how benefits management practices and roles should be implemented in order to have a positive effect on the projects’ success in terms of realizing benefits. The authors collected data relating to ten Norwegian public IT projects. For each project, they collected data on benefits management from project documents, by interviewing the project owners and benefits owners, and follow-up surveys. The benefits internal to the organization were those with the highest degree of realization, while the societal benefits were those with the lowest degree. Projects assessed to have more specific, measurable, accountable, and realistically planned benefits were more successful in realizing benefits. Benefits owners were most effective when they were able to attract attention towards the benefits to be realized, had a strong mandate, and had domain expertise.
| Afilliation | Software Engineering |
| Project(s) | EDOS: Effective Digitalization of Public Sector |
| Publication Type | Journal Article |
| Year of Publication | 2022 |
| Journal | a journal |
| Publisher | x |
Online Missing Data Imputation of Edge Flows
IEEE Signal Processing Letters (2022).Status: Submitted
Online Missing Data Imputation of Edge Flows
A novel online algorithm for missing data imputation for networks with signals defined on the edges is presented in this paper. Leveraging the prior knowledge intrinsic to most real-world networks, we propose a bi-level optimization scheme that includes (i) a sparse line graph identification strategy by solving a group-Lasso-based optimization framework via composite objective mirror descent to exploit the causal dependencies among the signals and (ii) a Kalman filtering-based signal reconstruction strategy developed using simplicial complex (SC) formulation to exploit the flow conservation. To the best of our knowledge, this is the first SC-based attempt for time-varying signal imputation, whose advantages have been demonstrated through numerical experiments conducted using EPANET models of both synthetic and real water distribution networks.
| Afilliation | Machine Learning |
| Project(s) | Signal and Information Processing for Intelligent Systems |
| Publication Type | Journal Article |
| Year of Publication | 2022 |
| Journal | IEEE Signal Processing Letters |
| Publisher | IEEE |
Journal articles
Backsourcing of Information Technology - A Systematic Literature Review
Information Systems Research (2021).Status: Submitted
Backsourcing of Information Technology - A Systematic Literature Review
Context: Backsourcing is the process of insourcing previously outsourced activities. When companies experience environmental or strategic changes, or challenges with outsourcing, backsourcing can be a viable alternative. While outsourcing and related processes have been extensively studied in information technology, few studies report experiences with backsourcing.
Objectives: We intend to summarize the results of the research literature on the backsourcing of IT, with a focus on software development. By identifying practical relevance experience, we aim to present findings that may help companies considering backsourcing. In addition, we aim to identify gaps in the current research literature and point out areas for future work.
Method: Our systematic literature review (SLR) started with a search for empirical studies on the backsourcing of IT. From each study we identified the contexts in which backsourcing occurs, the factors leading to the decision to backsource, the backsourcing process itself, and the outcomes of backsourcing. We employed inductive coding to extract textual data from the papers identified and qualitative cross-case analysis to synthesize the evidence from backsourcing experiences.
Results: We identified 17 papers that reported 26 cases of backsourcing, six of which were related to software development. The cases came from a variety of contexts. The most common reasons for backsourcing were improving quality, reducing costs, and regaining control of outsourced activities. The backsourcing process can be described as containing five sub-processes: change management, vendor relationship management, competence building, organizational build-up, and transfer of ownership. Furthermore, we identified 14 positive outcomes and nine negative outcomes of backsourcing. Finally, we aggregated the evidence and detailed three relationships of potential use to companies considering backsourcing.
Conclusion: The backsourcing of IT is a complex process; its implementation depends on the prior outsourcing relationship and other contextual factors. Our systematic literature review may contribute to a better understanding of this process by identifying its components and their relationships based on the peer-reviewed literature. Our results may also serve as a motivation and baseline for further research on backsourcing and may provide guidelines and process fragments from which practitioners can benefit when they engage in backsourcing.
| Afilliation | Software Engineering |
| Project(s) | EDOS: Effective Digitalization of Public Sector, Department of IT Management |
| Publication Type | Journal Article |
| Year of Publication | 2021 |
| Journal | Information Systems Research |
| Publisher | Institute for Operations Research and the Management Sciences |
| Keywords | backshoring, Backsourcing, information technology, software development, Software Engineering, systematic literature review |
Experiential Learning Approach for Software Engineering Courses at Higher Education Level
arXiv preprint arXiv:2012.14178 (2021).Status: Submitted
Experiential Learning Approach for Software Engineering Courses at Higher Education Level
Background: Software project management activities help to introducing software process models in Software Engineering courses. However, these activities should be adequately aligned with the learning outcomes and support student's progression.
Objective: Present and evaluate an approach to help students acquire theoretical and practical knowledge and experience real-world software projects' challenges. The approach combines a serious game and a design-implement task in which students develop a controlled-scale software system.
Methods: To evaluate our approach, we analyzed the students' perceptions collected through an online survey, their project plans, and their final reports using thematic analysis.
Results: Results suggest that the approach promotes knowledge acquisition, enables students' progression, reinforces theoretical concepts, and is properly aligned with the course's learning outcomes.
Conclusion: The approach seems to help introducing software process models in Software Engineering courses. Our experience can also be inspiring for educators willing to apply our approach in similar courses.
| Afilliation | Software Engineering |
| Project(s) | Department of IT Management |
| Publication Type | Journal Article |
| Year of Publication | 2021 |
| Journal | arXiv preprint arXiv:2012.14178 |
| Publisher | Springer |
Journal articles
Revealing the State-of-the-Art in Large-Scale Agile Development: A Systematic Mapping Study
arXiv preprint arXiv:2007.05578 (2020).Status: Submitted
Revealing the State-of-the-Art in Large-Scale Agile Development: A Systematic Mapping Study
| Afilliation | Software Engineering |
| Project(s) | Department of IT Management |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Journal | arXiv preprint arXiv:2007.05578 |
| Publisher | arXiv |
