Myrtveit is Professor of Business Economics at BI Norwegian Business School. She has a Dr Oeceon in Economics from NHH.
Her main areas of research is at the intersection of economics, management of information system and behaviour economics. This is a result of interdisiplinary work with the business community, i.e. Accenture and Telenor
She has published in top journals such as IEEE Transactions on Software engineering and Empirical Software engineering.
Myrtveit has been Head of Department of Economics at BI Norwegian Business School from 1998-2003, and Head of department of Accounting and Operations Management from 2015-2022, and Provost Academic Resources since 2022.
Deep Neural Networks (DNN) are used for image recognition in safety-critical functions of autonomous cars and ships. Car accidents have exposed DNN's lack of robustness to irregular events like unusual image objects and scenes. A misclassification with a high score, which we term a high confidence mistake, is of a particular concern to autonomous ships where we foresee a remote, land-based human operator in the loop who can intervene if warned. A high confidence mistake will not generate a warning to the human operator. To assess the safety of the classifier, we need as a minimum to understand why the classifier fails. This study evaluates the Layer-Wise Relevance Propagation (LRP) heat mapping method, applied to maritime image scenes. The method is evaluated on a classifier, trained using transfer learning to classify marine vessels into one of four different vessel categories. As a part of this, test images have been manipulated to deliberately provoke failures in the classification module. The resulting heat maps have then been used to investigate the cause of the failures. The results suggest that heat maps help us better understand what features are relevant for the classification which is an important first step. Further research is however required to provide an assurance framework to assess the safety level or to assist in debugging a DNN.
Stensrud, Erik & Myrtveit, Ingunn (2019)
The Problem of High Confidence Mistakes of Deep Learning in Safety-critical Functions
, s. 98- 102.
Stensrud, Erik & Myrtveit, Ingunn (2019)
The problem of High Confidence Mistakes of Deep Learning in Safety-critical functions
Myrtveit, Ingunn; Bakke, Alexander & Stensrud, Erik (2008)
Measurement of User Satisfaction with Enterprise Portals: An Empirical Study
Stensrud, Erik & Myrtveit, Ingunn (2008)
An empirical study of software development productivity in C and C++
Haugland, Sven A.; Haugland, Sven A., Nygaard, Arne & Myrtveit, Ingunn (2007)
Market orientation and performance in the service industry: A data envelopment analysis
60(11) , s. 1191- 1197.
Myrtveit, Ingunn & Stensrud, Erik (2005)
Do Arbitrary Function Approximators Make Sense as Software Prediction Models?
, s. 3- 10.
Myrtveit, Ingunn; Stensrud, Erik & Shepperd, Martin (2005)
Reliability and validity in comparative studies of software prediction models
31(5) , s. 380- 391.
Empirical studies on software prediction models do not converge with respect to the question "which prediction model is best?" The reason for this lack of convergence is poorly understood. In this simulation study, we have examined a frequently used research procedure comprising three main ingredients: a single data sample, an accuracy indicator, and cross validation. Typically, these empirical studies compare a machine learning model with a regression model. In our study, we use simulation and compare a machine learning and a regression model. The results suggest thatit is the research procedure itself that is unreliable. This lack of reliability may strongly contribute to the lack of convergence. Our findings thus cast some doubt on the conclusions of any study of competing software prediction models that used this research procedure as a basis of model comparison. Thus, we need to develop more reliable research procedures before we can have confidence in the conclusions of comparative studies of software prediction models.
Lothe, Solveig & Myrtveit, Ingunn (2003)
Compensation Systems for Green Strategy Implementation: Parametric and non-parametric approaches
12, s. 191- 203.
Foss, Tron; Myrtveit, Ingunn, Stensrud, Erik & Kitchenham, B. (2003)
A Simulation Study of the Model Evaluation Criterion MMRE
29(11) , s. 985- 995.
Stensrud, Erik & Myrtveit, Ingunn (2003)
Identifying High Performance ERP Projects. Reprint from
29(5) , s. 398- 416.
Foss, Tron; Myrtveit, Ingunn, Stensrud, Erik & Kitchenham, B. (2003)
A replicated Empirical Investigation of MMRE
8(2) , s. 139- 161.
Stensrud, Erik; Foss, Tron, Kitchenham, B. & Myrtveit, Ingunn (2002)
An Empirical Validation of the Relationship Between the Magnitude of Relative Error and Project Size
, s. 3- 12.
Myrtveit, Ingunn (2001)
Eierskap og lederlønninger i norsk næringsliv - spiller det egentlig noen rolle?
4(3) , s. 108- 113.
Myrtveit, Ingunn; Stensrud, Erik & Olsson, Ulf Henning (2001)
Analysing data sets with missing data: an empirical evaluation of imputation methods and likelihood-based methods
27(11) , s. 999- 1013.
Nygaard, Arne & Myrtveit, Ingunn (2000)
Moral Hazard, Competition and Contract Design: Empirical Evidence from Managerial, Franchised and Entrepreneurial Businesses in Norway
32(3) , s. 0- 0.
Myrtveit, Ingunn & Stensrud, Erik (1999)
A controlled Experiment to Assess the Benefits of Estimating with Analogy and Regression Models
Compensation Systems for Improving Environmental Performance
8, s. 313- 321.
Myrtveit, Ingunn & Torsvik, G. (1998)
Information Problens and Organization of the Norwegian Gasoline Market
Myrtveit, Ingunn & Nygaard, Arne (1998)
Kontrollkostnader, konkurranseforhold og valg av ulike lederkontrakter
(1)
Hall, Tracy; Counsell, Steve & Myrtveit, Ingunn (2015)
Editorial for the special section on Empirical Studies in Software Engineering Selected, and extended papers from the Eighteenth International Conference on Evaluation and Assessment in Software Engineering, May 13th-14th 2014, London, UK
The effect of mindfulness training on employees in dynamic organizational setting
[Conference Lecture]. Event
Myrtveit, Ingunn & Paoli, Donatella Maria De (2009)
Leading and manageing creative projects – transferring competence between arts and business
[Conference Lecture]. Event
Myrtveit, Ingunn & Stensrud, Erik (2009)
User Satisfaction with Search-driven Enterprise portals
[Conference Lecture]. Event
Myrtveit, Ingunn & Stensrud, Erik (2005)
Identifying High Performance Construction Projects
[Conference Lecture]. Event
Haugland, Sven A.; Haugland, Sven A., Myrtveit, Ingunn & Nygaard, Arne (2005)
Market Orientation, Customer Satisfaction and Productivity in the Service Industry: A Data Envelopment Analysis Approach
[Conference Lecture]. Event
Haugland, Sven A.; Haugland, Sven A., Myrtveit, Ingunn & Nygaard, Arne (2005)
Market Orientation and Productivity in the Hotel Industry
[Conference Lecture]. Event
A crucial cornerstone in the market orientation literature is the relationship between market orientation and performance. However, we still lack knowledge whether the most market-oriented firms are the most productive and profitable, as few empirical studies have used objective performance measures. By applying data envelopment analysis (DEA), we develop a measure of relative productivity, and test the market orientation model with productivity as performance measure. Based on data from the hotel industry, our results indicate that market orientation has only modest effect on productivity.
Haugland, Sven A.; Haugland, Sven A., Myrtveit, Ingunn & Nygaard, Arne (2004)
Market Orientation, Customer Satisfaction and Productivity in the Service Industry: A Data Envelopment Analysis
[Report Research].
A crucial cornerstone in the market orientation literature is the relationship between market orientation and performance. Products and services should be designed, developed and offered to customers based on market knowledge, and human and physical assets should be combined to satisfy customers. However, we still lack knowledge whether the most market-oriented firms are the most productive and profitable, as few empirical studies have used objective performance measures. By applying data envelopment analysis (DEA), we develop a measure of relative productivity, and test the market orientation model with productivity as performance measure. Based on data from the hotel industry, our results indicate that market orientation has only modest effect on productivity. However, DEA-productivity analyses can be used to identify best practice in an industry, and if used properly, it can be a useful instrument in the process of designing products and services and be a valuable input into the market orientation of the firm.
Myrtveit, Ingunn & Stensrud, Erik (2004)
Do arbitrary function approximators make sense as software prediction models?
[Conference Lecture]. Event
Myrtveit, Ingunn & Stensrud, Erik (2004)
SW Cost Estimation:Measuring Model Performance of Arbitrary Function Approximatiors
[Conference Lecture]. Event
Haugland, Sven A.; Haugland, Sven A., Myrtveit, Ingunn & Nygaard, Arne (2004)
Market Orientation, Customer Satisfaction and Productivity in the Service Industry: A Data Envelopment Analysis
[Conference Lecture]. Event
Foss, Tron; Stensrud, Erik, Kitchenham, B. & Myrtveit, Ingunn (2002)
A Simulation Study of the Model Evaluation Criterion MMRE
[Report Research].
The Mean Magnitude of Relative Error, MMRE, is probably the most widely used evaluation criterion for assessing the performance of competing software prediction models. It seems obvious that the purpose of MMRE is to assist us to select the best model. In this paper, we have performed a simulation study demonstrating that MMRE does not select the best model. The consequences are dramatic for a vast body of knowledge in software engineering. The implications of this finding are that the results and conclusions on prediction models over the past 15-25 years are unreliable and may have misled the entire software engineering discipline. We therefore strongly recommend not using MMRE to evaluate and compare prediction models. Instead, we recommend using a combination of theoretical justification of the models we propose together with other metrics proposed in this paper.
Stensrud, Erik & Myrtveit, Ingunn (2002)
SW Cost Estimation: Measuring Model Performance of Arbitrary Function Approximators
[Report Research].
Estimating software development cost with high accuracy is still a largely unsolved problem. Consequently, there is ongoing, high activity in this research field; a large number of different estimation models ranging from mathematical functions to arbitrary function approximators (AFA’s) have been proposed over the last 20+ years. Unfortunately, the studies do not converge with respect to the question “which model is best?” when functions and AFA’s are compared. So far, it has not been understood why this is so. In this empirical study, we show that this is due to inappropriate validation methods as far as the validation of AFA’s is concerned. In fact, the de facto validation method, cross-validation combined with MMRE, will give completely arbitrary results for AFA’s. Obviously, other criteria are called for in order to appropriately assess the performance of AFA’s. This should be a topic of future research
Stensrud, Erik & Myrtveit, Ingunn (2002)
Identifying High Performance ERP Projects
[Report Research].
Learning from high performance projects is crucial for software process improvement. Therefore, we need to identify outstanding projects that may serve as role models. It is common to measure productivity as an indicator of performance. It is vital that productivity measurements deal correctly with variable returns to scale and multivariate data. Software projects generally exhibit variable returns to scale, and the output from ERP projects is multivariate. We propose to use Data Envelopment Analysis Variable Returns to Scale (DEA VRS) to measure the productivity of software projects. DEA VRS fulfils the two requirements stated above, and to our knowledge, it is the only method complying with them. The results from this empirical study of 30 ERP projects extracted from a benchmarking database in Accenture identified six projects as potential role models. These projects deserve to be studied and probably copied as part of a software process improvement initiative. The results also suggest that there is a 50% potential for productivity improvement, on average. Finally, the results support the assumption of variable returns to scale in ERP projects. We recommend DEA VRS be used as the default technique for appropriate productivity comparisons of software projects. Used together with methods for hypothesis testing, DEA VRS is also a useful technique for assessing the effect of alleged process improvements.
Myrtveit, Ingunn; Stensrud, Erik & Olsson, Ulf Henning (2001)
Assessing the Benefits of Imputing ERP Projects with Missing Data
[Conference Lecture]. Event
Foss, Tron; Myrtveit, Ingunn & Stensrud, Erik (2001)
MRE and Heteroscedasticity: An Empirical Validation of the Assumption of Homoscedasticity of the Magnitude of Relative Error
[Conference Lecture]. Event
Foss, Tron; Myrtveit, Ingunn & Stensrud, Erik (2001)
A Comparison of LAD and OLS Regression for Effort Prediction of Software Projects
[Conference Lecture]. Event
Myrtveit, Ingunn & Stensrud, Erik (1999)
The Added Value of Estimation by Analogy: An Industrial Experiment
[Conference Lecture]. Event
Myrtveit, Ingunn & Stensrud, Erik (1999)
Benchmarking COTS Projects Using Data Envelopment Analysis
[Conference Lecture]. Event
Myrtveit, Ingunn & Stensrud, Erik (1999)
Does History Add Value to Project Cost Estimation. An Empirical Validation of a Claim in CMM
[Conference Lecture]. Event
Myrtveit, Ingunn & Stensrud, Erik (1999)
Human Performance Estimating with Analogy and Regression Models: An Empirical Validation
