Topics for master theses

Topics for master theses

The Department of Business and Management Science can offer the following Master Theses topics:

Investments, Insurance and Household Finance

  • Linking results from text analysis of mutual fund newsletters to returns, costs, and active fund management

    Linking results from text analysis of mutual fund newsletters to returns, costs, and active fund management

    Use textual analysis to identify if the information in mutual fund newsletters and/or prospects are reflected in returns or level of active management, or if this is just marketing to attract investors and assets under management. This topic requires skills in programming and/or experience with textual analysis. We have some of the text data, but some further work will be required, and we can provide data on returns and active share to link to the text data.

    Supervisors: Andreas Ørpetveit and Trond M. Døskeland.

  • Performance evaluation for mutual funds

    Performance evaluation for mutual funds

    Supervisor: Trond M. Døskeland.

  • Identifying financial behavioral biases for households

    Identifying financial behavioral biases for households

    Supervisor: Trond M. Døskeland.

  • Risk Management

    Risk Management

    Analyze a given company or a given line of business exposed to price risk from commodities/services sold or bought. May also be combined with currency risk. What is the level of risk, how do we measure it, which instruments are available to deal with this risk and how successful is the risk-reducing strategy, using these instruments. Hedging strategies are based on a combination of risk-reduction and expected values, so both components may be included in the analyses.

    Supervisor: Øystein Gjerde.

  • How did the US Tax Bill affect M&As?

    How did the US Tax Bill affect M&As?

    The 2017 TCJA may significantly change the pattern of corporate M&As. For instance, it has lifted the original use requirement for immediate depreciation of acquired assets. That makes it much more attractive to structure deals as asset purchases rather than stock acquisitions.

    Furthermore, net operating losses before and after January 1, 2018 are treated differently. An empirical analysis could use either Zephyr or SDC Platinum to explore early signs of these changes. 

    Supervisor: Maximilian Todtenhaupt.

  • Common ownership and tax avoidance

    Common ownership and tax avoidance

    Corporate tax planning is high on the agenda of both tax practitioners and policy makers. While some firms certainly try to avoid paying taxes, we know very little about how firms learn about different tax avoidance mechanisms. An important channel may be via common owners. Do firms engage in similar levels of tax avoidance if they are owned by the same investors? This project will investigate this question using balance sheet information and ownership details of large corporations.

    Supervisor: Maximilian Todtenhaupt.

  • Shipping & Finance: How do risk capital and risk limits affect the chartering policy of a ship operator?

    Shipping & Finance: How do risk capital and risk limits affect the chartering policy of a ship operator?

    Using: freight rates timeseries, optimal portfolio theory.

    Company: Western Bulk.

    Supervisor: Professor Roar Ådland

  • Shipping & Finance: Machine learning models for FFA trading

    Shipping & Finance: Machine learning models for FFA trading

    Using spatial AIS data for ship positions, open-source weather and macro data – can you develop a machine learning model to generate profitable trading signals? Requires knowledge of Python, implementation of machine learning models.

    Supervisor: Roar Ådland and Haiying Jia

  • Finansiell økonomi (finansmarkeder/opsjoner/skatt): Er leterefusjonsordningen subsidiering?

    Finansiell økonomi (finansmarkeder/opsjoner/skatt): Er leterefusjonsordningen subsidiering?

    Den norske leterefusjonsordningen har i det siste vært under offentlig debatt. Ordningen går ut på at oljeselskaper som er utenfor skatteposisjon får skatterefusjon for leteutgifter. Ifølge myndighetene innebærer ordningen ikke subsidiering fordi den gir likebehandling mellom selskaper som er utenfor skatteposisjon og selskaper som er i skatteposisjon.

    Utfordring: Belyse denne problemstillingen ut fra økonomisk teori.

    Se: Kjell-Børge Freiberg og Siv Jensen: «Oljeleting gir millarder til statskassen». Innlegg i Dagens Næringsliv, 8. februar 2019.

    https://www.dn.no/innlegg/okonomi/energi/leterefusjonsordningen/oljeleting-gir-milliarder-til-statskassen/2-1-537307

    Supervisor: Petter Bjerksund.

  • Finansiell økonomi (kapitalforvaltning/personlig økonomi): Seniorlån – en melkeku for bankene på arvingenes bekostning?

    Finansiell økonomi (kapitalforvaltning/personlig økonomi): Seniorlån – en melkeku for bankene på arvingenes bekostning?

    Aktuelle spørsmål:

    1. Hvordan er lånene priset?
    2. Hvordan er konkurransen i dette markedet?
    3. Hva er praksis internasjonalt?
    4. Er det greit å friste til forbruk som går på arven løs?

    https://www.bnbank.no/person/lan/seniorlan/

    https://www.klp.no/bank-og-lan/vare-boliglan/seniorlan

    Supervisor: Petter Bjerksund.

  • Finansiell økonomi (kapitalforvaltning/opsjoner): Asymmetrisk honorar for aktiv forvalting

    Finansiell økonomi (kapitalforvaltning/opsjoner): Asymmetrisk honorar for aktiv forvalting

    Mandag 4. februar lanserte DNB en ny modell for prising av aktiv forvalting som ventes å revolusjonere fondsbransjen i Norge. Ideen bak modellen er en asymmetrisk honorarstruktur hvor fondskunden betaler et lavere fast forvaltningshonorar mot at DNB får en andel av oppnådd meravkastning (suksesshonorar). I økonomisk forstand kan vi kan oppfatte suksesshonoraret som en opsjon.
    Aktuelle spørsmål:

    1. Hvordan fungerer modellen egentlig?
    2. Hva er de internasjonale erfaringene men en slik modell?
    3. Hvilken honorarstruktur er kunden best tjent med
    4. Hvordan påvirker den nye modellen forvalters insentiver?

    https://www.dnb.no/privat/sparing-og-investering/fond/ny-prismodell.html?WT.ac=zapy

    Supervisor: Petter Bjerksund.

  • Using Textual Analysis to identify whether there is a gender gap in financial white collar crime

    Using Textual Analysis to identify whether there is a gender gap in financial white collar crime

    There is very little systematic evidence on the gender gap in crime. In particular, it is difficult to quantify it for financial white collar crime, as they do not find their way into police statistics and as there is little female presence on the top levels of companies.

    In this project, we can use textual analysis tools to collect data from the Securities and Exchange Commission (SEC) on insider trading and other frauds. We can match the name of the defendant to a gender, and quantify what is the difference between males and females.

    Then, we can correlate the gap, as well as the fraud itself, to past financial statements of involved companies in terms of gender representation in the board of the company and other indicators of company culture. Finally, we can compare the gap to other measures of female participation in the boardroom and determine whether white collar females seem more or less likely to commit crimes than white collar males. We can provide a partial answer to the question: Are companies going to become more responsible (do less criminal rule-breaking) if there are more females on the board?

    Methods: Textual analysis, web crawling, R

    Supervisor: Evelina Gavrilova-Zoutman.

  • What do companies hide? Geographic disclosures, tax haven presence and earnings statements

    What do companies hide? Geographic disclosures, tax haven presence and earnings statements

    Using textual analysis on earnings statements from the Securities and Exchange Commission EDGAR database, we can determine what do companies disclose about their operations in tax havens.

    On one hand, it is common knowledge that companies, who have affiliates in tax havens, do not actually conduct any real economic activity in these tax havens. They use these affiliates to avoid taxation through profit shifting. Through textual analysis, we can determine in what context are tax havens mentioned in financial statements and whether there is real activity associated with them. We can compare that to actual company statements and determine whether there is a difference between claims and reality.

    On the other hand, we can correlate the presence in tax havens to earnings. Companies with lower earnings could try to use tax havens as a way to keep cash offshore and maintain liquidity. If companies with persistent lower earnings go for tax havens, then the event of opening new affiliates in tax havens can be used to forecast lower future company performance.

    Methods: Textual analysis, web crawling, R

    Supervisor: Evelina Gavrilova-Zoutman.

Business Taxation

  • Dividend taxation, Cum-Cum Trading and Ex-Dividend Pricing

    Dividend taxation, Cum-Cum Trading and Ex-Dividend Pricing

    A common tax planning strategy among investors is to sell their stocks the day before dividends are due, and buy them back on the ex-dividend day. This strategy, known as cum-cum trading, allows investors to avoid paying dividend taxes. The Norwegian tax authorities are considering to implement policies that make cum-cum trading less attractive in order to generate more dividend tax revenue. Your task will be to see how cum-cum trading relates to taxation and other policy variables, using international stock market data. Questions that you could answer in this topic are: Do stock market experience excess trade around the dividend day? Does excess trade relate to the dividend tax rate? Do stock prices reflect the level of the dividend tax? Are policies aimed at combatting cum-cum trading effective in other countries?

    Supervisor: Floris Zoutman.

  • How did the US Tax Bill affect M&As?

    How did the US Tax Bill affect M&As?

    The 2017 TCJA may significantly change the pattern of corporate M&As. For instance, it has lifted the original use requirement for immediate depreciation of acquired assets. That makes it much more attractive to structure deals as asset purchases rather than stock acquisitions.

    Furthermore, net operating losses before and after January 1, 2018 are treated differently. An empirical analysis could use either Zephyr or SDC Platinum to explore early signs of these changes. 

    Supervisor: Maximilian Todtenhaupt.

  • Common ownership and tax avoidance

    Common ownership and tax avoidance

    Corporate tax planning is high on the agenda of both tax practitioners and policy makers. While some firms certainly try to avoid paying taxes, we know very little about how firms learn about different tax avoidance mechanisms. An important channel may be via common owners. Do firms engage in similar levels of tax avoidance if they are owned by the same investors? This project will investigate this question using balance sheet information and ownership details of large corporations.

    Supervisor: Maximilian Todtenhaupt.

  • Inventors and tax havens

    Inventors and tax havens

    Inventors are an important source of innovation for any country. At the same time they are highly mobile and respond to tax incentives. Furthermore, the intellectual property they create (e.g. patents) can be used shift income to tax havens. How many inventors are involved in such tax avoidance behavior? This project will assess the importance of inventors in tax havens by combining data on international inventors with the Panama papers which have recently become available.

    Supervisor: Maximilian Todtenhaupt.

  • Detection of tax evasion by unsupervised learning

    Detection of tax evasion by unsupervised learning

    Unsupervised learning is the study of patterns in a dataset when there is no explicit response variable one would like to explain the variation of. Can unsupervised learning techniques be used to detect tax evasion with any precision? Are tax authorities exploiting such techniques when they lack an explicit response variable? Is there a reason to use unsupervised learning if only an error-ridden response variable is available? The questions can be answered by a combination of a literature study, an investigation of how tax authorities use unsupervised learning and comparison of supervised and unsupervised methods on simulated and real data.

    Data source: Tax returns and other sources from Tax Norway

    In cooperation with Skatteetaten.

    Supervisor: Jonas Andersson.

  • Topics on procurement and procurement strategies

    Topics on procurement and procurement strategies

    Eksempler på temaer kan være anbudsevaluering I praksis, konsekvensene av en utestenging av Huawei, analyse av en kommunes innkjøpsstrategi, hvordan ta miljøhensyn (eller sosiale hensyn) i innkjøp, evaluering av kompetanse og komptansebehov hos innkjøpere, etc.

    Supervisor: Malin Arve.

  • Quantify and explain the black/white gaps in reports, arrests and earnings in US crime

    Quantify and explain the black/white gaps in reports, arrests and earnings in US crime

    Recent focus on police brutality with respect to the black racial minority in the US has highlighted an anecdotal gap between races in crime. In its most common form, police officers feel that they are more likely to capture criminals if they stop and frisk black citizens. This leads to blacks and Hispanics experiencing on average more contacts with the police than whites. On the other hand, the majority of crimes (70%) are committed by whites.

    When we look at arrest probabilities, we observe that reported black perpetrators have a lower likelihood of arrest than reported white perpetrators. There is a need to draw the overall picture of white-black criminality and how discrimination and racial profiling influences these outcomes. A novel feature of this analysis can be the discussion of criminal earnings, together with a detailed analysis on how reporting, earnings and arrest are inter-related.

    Data: National Incident Based Reporting System, US

    Starting point: Knowles, J., Persico, N. and Todd, P., 2001. Racial bias in motor vehicle searches: Theory and evidence. Journal of Political Economy, 109(1), pp.203-229.
    Fryer Jr, R.G., 2016. An empirical analysis of racial differences in police use of force (No. w22399). National Bureau of Economic Research

    Supervisor: Evelina Gavrilova-Zoutman.

  • Correcting witness reports through Machine Learning

    Correcting witness reports through Machine Learning

    It is well known that witness accounts on crime are often unreliable. The effects of stress or poor light on the victim can create a skewed perception of how the perpetrator looked. This, coupled with an unconscious discriminatory bias, leads to the victim reporting that the perpetrator was unknown or from the black racial minority. Often the witness report is based on an estimate – e.g. “ the perp looked black, around 25 years”.

    Comparing actual arrests to reports, we can try to put a number on the amount of witness error. This can impact the computation of statistics on black/white, male/female and young/old crime gaps. What if blacks are actually responsible for a very small fraction of crimes? What if females are responsible for more crimes? This could lead us to rethink current racial profiling strategies in crime detection.

    Data: National Incident Based Reporting System, US

    Starting point: Imbens, G.W. and Lemieux, T., 2008. Regression discontinuity designs: A guide to practice. Journal of econometrics, 142(2), pp.615-635.
    Fryer Jr, R.G., 2016. An empirical analysis of racial differences in police use of force (No. w22399). National Bureau of Economic Research

    Supervisor: Evelina Gavrilova-Zoutman.

  • When the police is cheating

    When the police is cheating

    Police agencies get funding based on the amount of crime in their jurisdiction. This gives them the incentive to manipulate crime statistics. This can mean that for e.g. aggravated assaults are downgraded to simple assaults, or simple crimes are elevated to felonies. The police can add drug charges, in order to appear as being successful against organized crime. All this behaviour is hidden behind crime statistics.

    Through a combination of machine learning and local linear estimates we can try to determine how police agencies cheat. With the use of election outcomes as instrumental variables, we can try to find a causal effect. The findings of this project could have a strong impact on how crime figures are viewed. With corrected crime figures we can replicate previous analyses and determine whether well known policies actually impact crime or not.

    Data: National Incident Based Reporting System, US

    Supervisor: Evelina Gavrilova-Zoutman.

  • En kritisk evaluering av Statens Innkjøpssenter

    En kritisk evaluering av Statens Innkjøpssenter

    Statens innkjøpssenter ble opprettet i 2016 som en fireårig prøveordning, og skal inngå og forvalte fellesavtaler på vegne av sivile virksomheter i statlig sektor. Målet med innkjøpssenteret er mer profesjonelle, effektive og enkle innkjøpsprosesser, samt bedre og gunstigere innkjøp.

    For staten ventes sentrale rammeavtaler å gi lavere priser, reduserte transaksjonskostnader, økt bruk av elektronisk handel og bedre regelverksetterlevelse. I januar kom den offisielle evalueringen. Den har jeg kritisert i DN. Denne masteroppgaven vil evaluere hvor god evalueringen var og bygge videre på/forbedre den.

    Kilder

    Supervisor: Malin Arve.

  • Den offentlige innkjøper som en viktig samfunnsaktør

    Den offentlige innkjøper som en viktig samfunnsaktør

    Norge bruker over 500 mrd. kroner årlig på offentlige anskaffelser. En offentlig innkjøper sitter således med store muligheter til å bidra i arbeidet mot arbeidslivskriminialtet og sosial dumping/svart økonomi. Allerede i formålsparagrafen i lov om offentlige anskaffelser (LOA) er innkjøper forpliktet til å i vareta samfunnsmessige hensyn. I sin behandling påpekte Stortinget at dette også betydde kampen mot arbeidslivskriminalitet.  Regelverket gir et stort handlingsrom for innkjøper. Spørsmålet blir hvordan kommunale og fylkeskommunale enheter i Norge bruker dette handlingsrommet. Ledelsesforankring er et viktig stikkord her. Uten en forankring på alle plan (politiske vedtak osv.) vil innkjøper møte større utfordringer. 

    Hvilke strategidokumenter har innkjøper utarbeidet, og blir disse fulgt? Vi har fått mange ulike modeller som er politisk vedtatt (f.eks. Oslomodellen). Er det mulig å se noen resultater av disse? Hva med ""10 gode grep"" som ble utarbeidet. Er denne blitt brukt, og hvordan? Noen kommuner og offentlige organisasjoner har hatt problemer i forbindelse med mulig arbeidslivskriminalitet og sosial dumping (f.eks. måtte en kontrakt lyses ut på nytt av Helse Bergen etter at leverandør kastet inn kortene. I dette tilfelle hadde Helse Bergen allerede blitt advart om at det valgte tilbudet «luktet» social dumping. En daglig leder i et malerfirma måtte for noen måneder siden møte i retten, tiltalt for å ha organisert svart arbeid på Stortinget) Har disse hendelsene gitt noen endringer/forbedringer i organisasjonen og dens innkjøpsstrategi?

    Data: Casebasert oppgave.

    Starting Point: Ta kontakt med relevante aktører (Difi, Bergen (eller annen) kommunes innkjøpsavdeling, Helse Bergen, KS,…) Bjørnstad, Winger Eggen og Tofteng, 2016. Samlet vurdering av satsingene mot sosial dumping og arbeidslivskriminalitet, Rapport nr. 54-2016, Samfunnsøkonomisk analyse AS

    In cooperation with Skatteetaten.

    Supervisor: Malin Arve.

  • Sentralisering vs. desentralisering av innkjøp

    Sentralisering vs. desentralisering av innkjøp

    Difi ved Statens innkjøpssenter har inngått fem nasjonale rammeavtaler som den offentlige sektoren i Norge kan benytte. Difi snakker om store besparelser og estimerer besparelsen til å være cirka 230 millioner kroner i året. Samtidig advarer Konkurransetilsynet og Lars Sørgård for at sentraliserte innkjøp kan slå feil og at det er fare for svekket konkurranse.

    Hva er fordeler og ulemper ved sentralisering av innkjøp (i staten men også i bedrifter og organisasjoner)? I lys av teori og forskning på området, hvor store besparelser kan vi egentlig snakket om i Statens innkjøpssenter?

    Data: Innkjøpsavtaler inngått gjennom Statens innkjøpssenter, intervju av innkjøpere (både sentralt i Difi og ute i offentlige institusjoner i Norge)

    Starting Point:

    Fra media:

    Staten sparer stort på felles innkjøp – hittil om lag 230 mill.

    Stordriftsfordeler som blir ulemper

    Hvordan vet Difi hva din virksomhet vil spare på felles innkjøpsavtaler?

    Analyser og forskning:

    Centralised and decentralized public procurement, OECD

    When Should Procurement Be Centralized? Dimitri, Dini and Piga, in Handbook of Procurement (available in Malin’s office)

    Flexible  Strategies  for  Centralized  Public Procurement, by Albano and Sparro (2010), Review of Economics and Institutions

    Assessing the efficiency of centrliazed public procurement in the Brazilian ICT sector

    Supervisor: Malin Arve.

  • Sivilrettslig inndragning av utbytte fra kriminelle handlinger

    Sivilrettslig inndragning av utbytte fra kriminelle handlinger

    JD nå jobber med forslag til lov om sivilrettslig inndragning (etter en utredning av prof. Jon Petter Rui). Tidligere er det blitt foreslått en nasjonal enhet som skal sikre fratagelse av verdier gjennom både sivilrettslige og strafferettslige verktøy. Disse to tiltakene ble utredet parallelt. Regjeringen sa nylig at dette hadde noen praktiske hindre, uten å gå nærmere inn på hva disse er. Er sivilrettslig inndragning et effektivt virkemiddel? Kan det bøte på det ofte rapporterte problemet om manglende kapasitet og/eller kompetanse i politidistriktet? Hva er de praktiske hindringene regjeringen refererer til? Hva er erfaringene i andre land som har brukt dette, hva er potensielle fallgruver og hva har hatt best effekt? Hvor stor er den preventive effekten av å ramme utbyttet/profitten fra den kriminelle virksomheten? Samarbeidsforum kan bidra som diskusjonspartner.

    In cooperation with Skatteetaten.

    Supervisor: Evelina Gavrilova-Zoutman.

  • Formuesforvaltere og finansrådgivere med norske kunder som målgruppe

    Formuesforvaltere og finansrådgivere med norske kunder som målgruppe

    Hvem er aktørene? Oversikt over formuesforvaltere og finansrådgivere for norske privatkunder.

    • Er det forskjellige aktører som gir råd, tilbyr konto, investeringer, eiendom, stråselskaper, utenlandske betalingskort o.l.? Hvem samarbeider om hva? Hvem er kontaktpunktet til kunden?
    • Hvor store verdier forvalter de for norske kunder
    • Markedsføringsstrategier
    • Hvem er kunder og hvordan de rekrutteres
    • Hva selger de og til hvem?
    • Hvor mye skatt sparer kundene på tjenestene?
    • Er det mulig å si noe om det er skattemotivert eller andre årsaker til bruk?
    • Kan studentene se hvordan produktene som blir solgt til norske kunder eventuelt kan bli misbrukt til skatteunndragelse? Hvordan? Hvor er smutthullene?

    In cooperation with Skatteetaten.

    Supervisor: Floris Zoutman.

Data Science and Analytics

  • Detection of tax evasion by unsupervised learning

    Detection of tax evasion by unsupervised learning

    Unsupervised learning is the study of patterns in a dataset when there is no explicit response variable one would like to explain the variation of. Can unsupervised learning techniques be used to detect tax evasion with any precision? Are tax authorities exploiting such techniques when they lack an explicit response variable? Is there a reason to use unsupervised learning if only an error-ridden response variable is available? The questions can be answered by a combination of a literature study, an investigation of how tax authorities use unsupervised learning and comparison of supervised and unsupervised methods on simulated and real data.

    Data source: Tax returns and other sources from Tax Norway

    In cooperation with Skatteetaten.

    Supervisor: Jonas Andersson.

  • Nonlinear econometrics

    Nonlinear econometrics

    A large portion of empirical research within economics and finance is based on linear models, of which the linear regression is by far the most prominent. Is this because we live in a linear world, or at least an approximately linear world, or is it the case that we implicitly close our eyes to important features i our data by not considering nonlinear methods on equal footing as traditional ones?

    Questions like this may take your master project in several directions, such as (listed from least to most statistical/mathematical maturity recommended to complete the project, all of them benefit from programming skills):

    1. To what degree is linear regression the main vehicle for measuring marginal effects of explanatory variables X to a response variable Y within economic research (within a certain field/ in Norway/ at NHH or otherwise suitably limited)? Why do researchers choose this method (convenience/interpretability of coefficients/easy presentation/theoretical foundations/...)?  Then, figure out to which degree such concerns can be addressed by a corresponding nonlinear model. A nice touch would be to re-do a recent linear study nonlinearly and see if there indeed are effects that were missed.

    2. A bit more technical version of the point above is to write a thesis that revolves around the systematical development of a tool in your programming language of choice (such as R or Python) that implements as many needs as possible of the linearly oriented researcher in a nonlinear framework, with pre-work consisting of providing a theoretical foundation, and as post-work perhaps testing your «product» by trying to «sell it» to an experienced researcher.

    3. Financial time series are typically nonlinear in the sense that the correlation coefficient does not, in general, give good descriptions of dependencies across time and space. This has naturally lead to the development of nonlinear methods to model financial processes. For example, the classical theory for portfolio allocation that Harry Markowitz introduced in the 1950s balances expected return (as measured by means) and risk (as measured by standard deviations and correlations) in order to provide the optimal distribution of wealth across different assets.

    The Markowitz portfolio theory is very simple and easy to implement. But, it explicitly assumes that dependence between assets is linear, so the decades following its introduction have seen many attempts to improve the Markowitz method by modelling dependencies nonlinearly. Many authors note, however, that it is actually quite hard to attain higher returns using modern methods compared to the classical approach. This project may contain a survey of modern portfolio selection methods (which will require the ability to read fairly technical research papers), and a discussion part where we try to answer the question whether beating the classical approach indeed is «hard», and if so, why?

    Supervisor: Håkon Otneim.

  • Predicting patent litigation

    Predicting patent litigation

    The aim of the topic is to use state-of-the-art machine learning techniques to predict which patents will be pursued at court. Such a model could help big technology companies managing their patent portfolio or insurance companies to price litigation insurance contracts.

    Supervisor: Steffen Juranek.

  • Sports Analytics

    Sports Analytics

    Due to its massive popularity and often large availability of data, sports present great opportunities for the application of analytics techniques. I have dedicated a great share of my research to topics related to sports analytics, including tournament scheduling, referee assignment, fairness, and ranking design. These are only examples from the broad range of topics in the agenda of sports analytics nowadays. There is a lot of literature about it. I would be open to discuss your specific interests and to provide you with references that could set the basis for a potentially fun and relevant master thesis.

    Supervisor: Mario Guajardo.

  • Using Textual Analysis to identify whether there is a gender gap in financial white collar crime

    Using Textual Analysis to identify whether there is a gender gap in financial white collar crime

    There is very little systematic evidence on the gender gap in crime. In particular, it is difficult to quantify it for financial white collar crime, as they do not find their way into police statistics and as there is little female presence on the top levels of companies.

    In this project, we can use textual analysis tools to collect data from the Securities and Exchange Commission (SEC) on insider trading and other frauds. We can match the name of the defendant to a gender, and quantify what is the difference between males and females.

    Then, we can correlate the gap, as well as the fraud itself, to past financial statements of involved companies in terms of gender representation in the board of the company and other indicators of company culture. Finally, we can compare the gap to other measures of female participation in the boardroom and determine whether white collar females seem more or less likely to commit crimes than white collar males. We can provide a partial answer to the question: Are companies going to become more responsible (do less criminal rule-breaking) if there are more females on the board?

    Methods: Textual analysis, web crawling, R

    Supervisor: Evelina Gavrilova-Zoutman.

  • What do companies hide? Geographic disclosures, tax haven presence and earnings statements

    What do companies hide? Geographic disclosures, tax haven presence and earnings statements

    Using textual analysis on earnings statements from the Securities and Exchange Commission EDGAR database, we can determine what do companies disclose about their operations in tax havens.

    On one hand, it is common knowledge that companies, who have affiliates in tax havens, do not actually conduct any real economic activity in these tax havens. They use these affiliates to avoid taxation through profit shifting. Through textual analysis, we can determine in what context are tax havens mentioned in financial statements and whether there is real activity associated with them. We can compare that to actual company statements and determine whether there is a difference between claims and reality.

    On the other hand, we can correlate the presence in tax havens to earnings. Companies with lower earnings could try to use tax havens as a way to keep cash offshore and maintain liquidity. If companies with persistent lower earnings go for tax havens, then the event of opening new affiliates in tax havens can be used to forecast lower future company performance.

    Methods: Textual analysis, web crawling, R

    Supervisor: Evelina Gavrilova-Zoutman.

Energy Markets, Resource Management and Sustainability

  • Topics on Energy Economics

    Topics on Energy Economics

    Potential topics

    • Hvordan dele verdier i en felles oljeproduksjon (borerigg) hvor ulik og usikker oljekvalitet samles fra satellittfelt med ulike eiere? (Mulig nytt KPN, Kompetanse Prosjekt i Næringslivet)
    • Can Norway capture more of the value chain of energy by not committing to be Europe’s green battery?
    • Hydrogen: which part is failing: cars, hydrogen or filling and logistics?
    • Solar power: if a leap lies ahead, what can trigger it?
    • Decentralized power generation in Norway: Framework and business analysis
    • A role for Norway as a battery for Europe’s intermittent power
    • A business analysis of Norway’s three proposed carbon capture and storage projects (cement, fertilizer, waste dump)
    • Empiriske analyser av norske sluttbrukermarkeder for elektrisitet
    • Risikoaversjon i sluttselgermarkedet

    Supervisor: Leif K. Sandal.

  • Topics on Environmental Economics

    Topics on Environmental Economics

    Potential topics are:

    • Zero emissions (in shipping/buildings/road veh/airplanes): too much, or just right?
    • Certificates of Origin for Electricity; Stepchild or rising star?
    • A carbon cap for Norwegian farmers: Let forests do what cows and farmers cannot?
    • Carbon footprint and economic analysis for a firm/sector
    • Hydrogen: which part is failing: cars, hydrogen or filling and logistics
    • A new look at biomass and biofuels: can photosynthesis propel transport
    • Oceans in a sustainability strategy
    • Solar power: if a leap lies ahead, what can trigger it
    • Decentralized power generation in Norway: framework and business analysis
    • Renewable power in Norway: shall it expand, and with what instruments
    • A role for Norway as a battery for Europe’s intermittent power
    • A business analysis of Norway’s three proposed carbon capture and storage projects (cement, fertilizer, waste dump)
    • Analysis of emission reduction prospects in Norwegian transport
    • Econometric analysis of demand for energy (or carbon) intensive goods, transport
    • Forests: More wood and biomass in buildings: Economic analysis of climate prospects
    • Financial markets: is there evidence of ‘sin portfolios’ or ‘virtue’ (or green/fossil)? The value of fossil assets / promises in financial markets
    • Analysis of CO2 markets
    • Modeling energy exchange in Northern Europe

    Supervisor: Gunnar S. Eskeland.

  • The petroleum industry in the Barents Sea and other vulnerable areas: environmental and economic analysis of the activity

    The petroleum industry in the Barents Sea and other vulnerable areas: environmental and economic analysis of the activity

    Supervisor: Stein Ivar Steinshamn.

  • Fossil fuel markets and management: Should the transition to renewable go through natural gas?

    Fossil fuel markets and management: Should the transition to renewable go through natural gas?

    Supervisor: Stein Ivar Steinshamn.

  • Need for nuclear power to replace fossil fuel: New nuclear power

    Need for nuclear power to replace fossil fuel: New nuclear power

    Supervisor: Stein Ivar Steinshamn.

  • Electricity in the transport sector: Economic and environmental effects

    Electricity in the transport sector: Economic and environmental effects

    Supervisor: Stein Ivar Steinshamn.

  • Develop a business model for compact carbon capture and storage

    Develop a business model for compact carbon capture and storage

    Supervisor: Stein Ivar Steinshamn.

  • Waste Management

    Waste Management

    New waste pipelines are built below the surface in the city center. How can BIR improve the efficiency and increase the utilization of the pipelines?

    Topic 1

    Use optimization, simulation and tools from supply chain management to improve the waste management in BIR.

    Topic 2

    BIR can only collect data from garbage handling for the owner of a house or an apartment. Many of the houses in the city center are divided in several apartment that are rented to students or other inhabitants. How BIR can increase individuals (renters) incentives to sort garbage when BIR only can collect aggregate data from all the apartment in the house? If BIR could track the for each household, which impact would that have on the individual willingness to sort their garbage?

    Supervisor: Sigrid Lise Nonås.

  • Emission Abatement Technology for a Shipping Company - is the Uncertainty of Fuel Prices Important?

    Emission Abatement Technology for a Shipping Company - is the Uncertainty of Fuel Prices Important?

    Is the uncertainty of fuel prices important to be considered when a shipping company selects its emission abatement technology for the compliance of ECA regulation.

    Supervisor: Yewen Gu.

  • Waste problems in the fashion industry in Norway: Oleana case

    Waste problems in the fashion industry in Norway: Oleana case

    In cooperation with Oleana.

    Supervisor: Gunnar Eskeland.

  • The future of fashion sustainability, customer behavior

    The future of fashion sustainability, customer behavior

    In cooperation with Oleana.

    Supervisor: Gunnar Eskeland.

  • Are there any economical/political motivations for sustainability in the fashion industry?

    Are there any economical/political motivations for sustainability in the fashion industry?

    In cooperation with Oleana.

    Supervisor: Gunnar Eskeland.

  • Shared economies: is there a future for the fashion industry?

    Shared economies: is there a future for the fashion industry?

    In cooperation with Oleana.

    Supervisor: Gunnar Eskeland.

  • Development and implementation of textile waste recycling, project case

    Development and implementation of textile waste recycling, project case

    In cooperation with Oleana.

    Supervisor: Gunnar Eskeland.

  • Insentiver for, og konsekvenser av off grid løsninger

    Insentiver for, og konsekvenser av off grid løsninger

    Ny teknologi for lokal kraftproduksjon og lagring (eksempelvis solceller og batteriløsninger), gjør det mulig for forbrukere å klare seg uten det nasjonale energisystemet som er bygget opp de siste hundre årene. Hvilke privatøkonomiske insentiver finnes for slike løsninger, hvilke fordelingsvirkninger kan det ha, og hvilke samfunnsøkonomiske og bedriftsøkonomiske konsekvenser kan dette få?

    In cooperation with BKK

    Supervisors: Endre Bjørndal and Mette Bjørndal.

  • Lønnsomhet og investeringsinsentiver

    Lønnsomhet og investeringsinsentiver

    Inntektsrammene for selskapene fastsettes med utgangspunkt i innrapporterte data fra selskapene, samt data om selskapenes naturgitte rammevilkår. NVE gjør i utgangspunktet effektivitetsanalyser ved hjelp av metoden DEA, og disse analysene justeres også for naturgitte rammevilkår før inntektsrammene beregnes. For å sikre tilstrekkelig lønnsomhet for gjennomsnittsselskapet, kalibreres inntektsrammene slik at et gjennomsnittlig effektivt selskap vil få dekket sine kostnader. Per i dag gjøres kalibreringen med utgangspunkt i bokført kapital, men NVE har foreslått å endre kalibreringsmetodikken slik at den gjøres med utgangspunkt i totale kostnader. Denne oppgaven vil se på hvordan endring i kalibreringsmetodikken vil påvirke lønnsomhet og investeringsinsentiver i bransjen, og den vil se på andre andre kalibreringsalternativer enn de som er nevnt i forslaget fra NVE.

    Supervisors: Endre Bjørndal and Mette Bjørndal.

  • Strategiske tilpasninger til reguleringen

    Strategiske tilpasninger til reguleringen

    Mange av de økonomiske insentivene I NVEs inntektsregulering av nettselskaper påvirker eiernes avkastning. Samtidig har ledelsen i nettselskapet en ikke ubetydelig innflytelse på drifts- og investeringsbeslutninger, og hvor valgt løsning vil kunne påvirke selskapets inntektsramme, og dermed også eiernes avkastning. Burheim & Dahl (2016) gjorde i sin masteroppgave en spørreundersøkelse blant ansatte i selskapene for å kartlegge de ansattes kunnskap om og selskapenes tilpasninger til reguleringen, og oppgaven til Dahl & Faugstadmo (2018) så på styrets rolle og ansvar. Den nye oppgaven skal belyse om og i tilfelle hvordan selskapene kan påvirke sin lønnsomhet gjennom strategiske tilpasninger innenfor det reguleringsregimet de er underlagt. Har selskapenes frihetsgrader for tilpasning økt de siste årene, og er dette i så fall noe som bør tas hensyn til i reguleringen?

    Supervisors: Endre Bjørndal and Mette Bjørndal.

  • Nye oppgavevariabler i reguleringsmodellen

    Nye oppgavevariabler i reguleringsmodellen

    NVE har satt i gang et arbeid med å utrede en ny oppgavevariabel som bedre fanger opp det arbeidet som gjøres av nettet, både med hensyn til avstand og volum (energi/effekt). Thema Consulting gjennomfører for tiden et prosjekt for NVE, og de tar utgangspunkt i en metode som beregner «optimalt» antall effekt-/energikilometer. Når dette arbeidet er ferdig i november 2019 vil det være aktuelt for Elbench-forskere og masterstudenter å se nærmere på det, både hvordan man kan lage en god kostnadsdrivervariabel som fanger opp både avstand og volum, samt hvordan en slik variabel eventuelt bør brukes i en normkostnadsmodell basert på effektivitetsanalyser (DEA, SFA eller lignende).

    Supervisors: Endre Bjørndal and Mette Bjørndal.

Incentives, Contracts and Firm Behaviour

  • Economics of organization and management control

    Economics of organization and management control

    Including the use of bonus pay (case studies or across companies), how to measure performance, balanced scorecard (or alternative ways to use key performance indicators for management control purposes), drivers of profitability in an industry or a company, beyond budgeting, transfer pricing, and organizational boundaries.

    Supervisor: Iver Bragelien and Malin Arve.

  • Topics on Organizational Economics and Industrial Organization

    Topics on Organizational Economics and Industrial Organization

    Some examples from the past:

    • Om kontrakter og incentiver i ERP-implementering
    • En teoretisk analyse av innovasjonsinsentivene i Posten Norge AS
    • Digitalisering i Bygg- og anleggsnæringen
    • Kundelojalitetsprogrammer i det norske dagligvaremarkedet
    • Utviklingen av markedsstrukturen i den norske dagligvarebransjen
    • Lønnsomhetsforskjeller i større foretak (norsk møbelbransje)

    Supervisor: Trond E. Olsen and Malin Arve.

  • Women and innovation in Europe

    Women and innovation in Europe

    It can be empirically observed that women are underrepresented in science and research. This is likely to have negative consequences for firm productivity and economic growth because talent is not used efficiently. The aim of the Master Theses is to analyze the female share among inventors within Europe. What is the female share in Europe today? How did it develop over time? How does it differ across Europe? Why does it differ? How can it be increased?

    Supervisor: Steffen Juranek.

  • Predicting patent litigation

    Predicting patent litigation

    The aim of the topic is to use state-of-the-art machine learning techniques to predict which patents will be pursued at court. Such a model could help big technology companies managing their patent portfolio or insurance companies to price litigation insurance contracts.

    Supervisor: Steffen Juranek.

  • How did the US Tax Bill affect M&As?

    How did the US Tax Bill affect M&As?

    The 2017 TCJA may significantly change the pattern of corporate M&As. For instance, it has lifted the original use requirement for immediate depreciation of acquired assets. That makes it much more attractive to structure deals as asset purchases rather than stock acquisitions.

    Furthermore, net operating losses before and after January 1, 2018 are treated differently. An empirical analysis could use either Zephyr or SDC Platinum to explore early signs of these changes. 

    Supervisor: Maximilian Todtenhaupt.

  • Common ownership and tax avoidance

    Common ownership and tax avoidance

    Corporate tax planning is high on the agenda of both tax practitioners and policy makers. While some firms certainly try to avoid paying taxes, we know very little about how firms learn about different tax avoidance mechanisms. An important channel may be via common owners. Do firms engage in similar levels of tax avoidance if they are owned by the same investors? This project will investigate this question using balance sheet information and ownership details of large corporations.

    Supervisor: Maximilian Todtenhaupt.

  • Sivilrettslig inndragning av utbytte fra kriminelle handlinger

    Sivilrettslig inndragning av utbytte fra kriminelle handlinger

    JD nå jobber med forslag til lov om sivilrettslig inndragning (etter en utredning av prof. Jon Petter Rui). Tidligere er det blitt foreslått en nasjonal enhet som skal sikre fratagelse av verdier gjennom både sivilrettslige og strafferettslige verktøy. Disse to tiltakene ble utredet parallelt. Regjeringen sa nylig at dette hadde noen praktiske hindre, uten å gå nærmere inn på hva disse er. Er sivilrettslig inndragning et effektivt virkemiddel? Kan det bøte på det ofte rapporterte problemet om manglende kapasitet og/eller kompetanse i politidistriktet? Hva er de praktiske hindringene regjeringen refererer til? Hva er erfaringene i andre land som har brukt dette, hva er potensielle fallgruver og hva har hatt best effekt? Hvor stor er den preventive effekten av å ramme utbyttet/profitten fra den kriminelle virksomheten? Samarbeidsforum kan bidra som diskusjonspartner.

    In cooperation with Skatteetaten.

    Supervisor: Evelina Gavrilova-Zoutman.

  • Topics on procurement and procurement strategies

    Topics on procurement and procurement strategies

    Eksempler på temaer kan være anbudsevaluering I praksis, konsekvensene av en utestenging av Huawei, analyse av en kommunes innkjøpsstrategi, hvordan ta miljøhensyn (eller sosiale hensyn) i innkjøp, evaluering av kompetanse og komptansebehov hos innkjøpere, etc.

    Supervisor: Malin Arve.

  • En kritisk evaluering av Statens Innkjøpssenter

    En kritisk evaluering av Statens Innkjøpssenter

    Statens innkjøpssenter ble opprettet i 2016 som en fireårig prøveordning, og skal inngå og forvalte fellesavtaler på vegne av sivile virksomheter i statlig sektor. Målet med innkjøpssenteret er mer profesjonelle, effektive og enkle innkjøpsprosesser, samt bedre og gunstigere innkjøp.

    For staten ventes sentrale rammeavtaler å gi lavere priser, reduserte transaksjonskostnader, økt bruk av elektronisk handel og bedre regelverksetterlevelse. I januar kom den offisielle evalueringen. Den har jeg kritisert i DN. Denne masteroppgaven vil evaluere hvor god evalueringen var og bygge videre på/forbedre den.

    Kilder

    Supervisor: Malin Arve.

  • Den offentlige innkjøper som en viktig samfunnsaktør

    Den offentlige innkjøper som en viktig samfunnsaktør

    Norge bruker over 500 mrd. kroner årlig på offentlige anskaffelser. En offentlig innkjøper sitter således med store muligheter til å bidra i arbeidet mot arbeidslivskriminialtet og sosial dumping/svart økonomi. Allerede i formålsparagrafen i lov om offentlige anskaffelser (LOA) er innkjøper forpliktet til å i vareta samfunnsmessige hensyn. I sin behandling påpekte Stortinget at dette også betydde kampen mot arbeidslivskriminalitet.  Regelverket gir et stort handlingsrom for innkjøper. Spørsmålet blir hvordan kommunale og fylkeskommunale enheter i Norge bruker dette handlingsrommet. Ledelsesforankring er et viktig stikkord her. Uten en forankring på alle plan (politiske vedtak osv.) vil innkjøper møte større utfordringer. 

    Hvilke strategidokumenter har innkjøper utarbeidet, og blir disse fulgt? Vi har fått mange ulike modeller som er politisk vedtatt (f.eks. Oslomodellen). Er det mulig å se noen resultater av disse? Hva med ""10 gode grep"" som ble utarbeidet. Er denne blitt brukt, og hvordan? Noen kommuner og offentlige organisasjoner har hatt problemer i forbindelse med mulig arbeidslivskriminalitet og sosial dumping (f.eks. måtte en kontrakt lyses ut på nytt av Helse Bergen etter at leverandør kastet inn kortene. I dette tilfelle hadde Helse Bergen allerede blitt advart om at det valgte tilbudet «luktet» social dumping. En daglig leder i et malerfirma måtte for noen måneder siden møte i retten, tiltalt for å ha organisert svart arbeid på Stortinget) Har disse hendelsene gitt noen endringer/forbedringer i organisasjonen og dens innkjøpsstrategi?

    Data: Casebasert oppgave.

    Starting Point: Ta kontakt med relevante aktører (Difi, Bergen (eller annen) kommunes innkjøpsavdeling, Helse Bergen, KS,…) Bjørnstad, Winger Eggen og Tofteng, 2016. Samlet vurdering av satsingene mot sosial dumping og arbeidslivskriminalitet, Rapport nr. 54-2016, Samfunnsøkonomisk analyse AS

    In cooperation with Skatteetaten.

    Supervisor: Malin Arve.

  • Sentralisering vs. desentralisering av innkjøp

    Sentralisering vs. desentralisering av innkjøp

    Difi ved Statens innkjøpssenter har inngått fem nasjonale rammeavtaler som den offentlige sektoren i Norge kan benytte. Difi snakker om store besparelser og estimerer besparelsen til å være cirka 230 millioner kroner i året. Samtidig advarer Konkurransetilsynet og Lars Sørgård for at sentraliserte innkjøp kan slå feil og at det er fare for svekket konkurranse.

    Hva er fordeler og ulemper ved sentralisering av innkjøp (i staten men også i bedrifter og organisasjoner)? I lys av teori og forskning på området, hvor store besparelser kan vi egentlig snakket om i Statens innkjøpssenter?

    Data: Innkjøpsavtaler inngått gjennom Statens innkjøpssenter, intervju av innkjøpere (både sentralt i Difi og ute i offentlige institusjoner i Norge)

    Starting Point:

    Fra media:

    Staten sparer stort på felles innkjøp – hittil om lag 230 mill.

    Stordriftsfordeler som blir ulemper

    Hvordan vet Difi hva din virksomhet vil spare på felles innkjøpsavtaler?

    Analyser og forskning:

    Centralised and decentralized public procurement, OECD

    When Should Procurement Be Centralized? Dimitri, Dini and Piga, in Handbook of Procurement (available in Malin’s office)

    Flexible  Strategies  for  Centralized  Public Procurement, by Albano and Sparro (2010), Review of Economics and Institutions

    Assessing the efficiency of centrliazed public procurement in the Brazilian ICT sector

    Supervisor: Malin Arve.

  • Lønnsomheten i kollektivnæringen

    Lønnsomheten i kollektivnæringen

    In cooperation with Skyss.

    Skyss har i dag en rekke operatører som drifter buss-, båt- og ferjerutene i Hordaland. Prisene på de ulike kontraktene bestemmes på forhånd i anbudsprosesser, og det er ikke gitt at operatørene vil tjene penger på kontraktene. Er det bestemte kjennetegn på de operatørene som tjener penger og de som taper penger? Er det forskjell i lønnsomhet hos store og små operatører? Finnes det for eksempel stordriftsfordeler i kollektivnæringen som gir større operatører en fordel? Og er det forskjeller i lønnsomhet for små og store kontrakter? Dette er noen av spørsmålene som kan besvares ved å velge å skrive en oppgave om lønnsomheten til selskaper i kollektivnæringen.

    Merk! Vi i Skyss har informasjon om kontraktskostnader og rapporterte kontraktsregnskap fra operatør. Vi har også tilgang til nøkkeltallsrapporter, regnskaps- og balansetall for operatør levert fra kredittvurderingsselskap. Her kan det være aktuelt å innhente mer informasjon ved å samarbeide med operatører i bransjen.

    Contact: Malin Arve.

  • Prissegmentering

    Prissegmentering

    In cooperation with Skyss.

    Store aktører innen transport som SAS, Norwegian og VY driver aktivt med prissegmentering på billetter. Er dette noe Skyss også burde innføre i større grad enn i dag? Store deler av passasjerene benytter seg av kollektivtransport i rushtiden. Vil ulike priser i og utenfor rushtiden føre til at reisestrømmen i løpet av en dag jevnes ut? Vil det være lønnsomt å senke billettprisene i tidsrommene svært få benytter kollektivtransport for å øke antall reisende? Bør prisene for eksempel senkes i sommerferien? Hva slags segmenteringsstrategi bør i så fall Skyss benytte? Hva er de økonomiske effektene av prissegmentering på Skyss sine kostnader og inntekter?

    Contact: Malin Arve.

  • Kost-nytte analyse knyttet til kollektivtransporten i Bergen

    Kost-nytte analyse knyttet til kollektivtransporten i Bergen

    In cooperation with Skyss.

    Er det samfunnsmessig lønnsomt å tilby kollektivtransport? Hvilke samfunnsmessige kostnader kan knyttes til utvikling og drift av kollektivtransport og hvilken samfunnsøkonomisk nytte blir generert? Hvilke aktører betaler for kollektivtransporten og hvem drar nytte av den?

    Contact: Malin Arve.

  • Sikring av drivstoffkostnader i Skyss

    Sikring av drivstoffkostnader i Skyss

    In cooperation with Skyss.

    Skyss har ansvar for å følge opp ulike transportkontrakter på flere hundre millioner kroner. En av de viktigste kostnadsdriverne i kontraktene er drivstoffkostnader, der prisutviklingen kan gi store millionbeløp i utslag på de totale kostnadene. Hvordan kan Skyss sikre drivstoffkostnadene? Hvordan bør man rigge seg til for å sikre drivstoffkostnader på en strukturert måte og hvilke verktøy, rutiner, strategier og beslutninger fungerer best? Skyss vil i fremtiden ha en drivstoffmiks bestående av elektrisk drivstoff, biodiesel, biogass, autodiesel og marinegass/olje. Det kan derfor velges om studentene vil konsentrerer seg om én eller flere av disse variantene.

    Contact: Malin Arve.

  • Økonomisk analyse knyttet til konkurrerende transportformer i Bergen

    Økonomisk analyse knyttet til konkurrerende transportformer i Bergen

    In cooperation with Skyss.

    Kostnader, reisetid og komfort er blant faktorene som påvirker individers valg av transportmiddel. Et bredt flertall på Stortinget har gjennom Nasjonal Transportplan blitt enige om et felles mål om at veksten i persontrafikken skal tas med miljøvennlige transportformer som kollektivtransport, sykkel og gange. Det er vedtatt ambisiøse mål for veksten i kollektivtrafikken og dermed også for Skyss, og det vil være interessant og kartlegge utviklingen i både kollektivtransporten og de konkurrerende transportformene. Hvordan har konkurranseevnene til de enkelte transportformene i Bergen utviklet seg de siste 5-10 årene og hvordan ser utsiktene ut fremover?

    Contact: Malin Arve.

  • Evaluering av prissetting av kvalitet som alternativ til scoring

    Evaluering av prissetting av kvalitet som alternativ til scoring

    Majoriteten av offentlige anbudskonkurranser bruker scoring (dvs. forskjellige dimensjoner som pris og kvalitet blir omgjort til score og anbudet med høyest score vinner), men nyere forskning foreslår prissetting av kvalitet som en bedre alternativ. Sykehusinnkjøp har akkurat begynt med den type evaluering og masteroppgaven vil være i tett samarbeid med de.

    I samarbeid med Sykehusinnkjøp.

    Supervisor: Malin Arve.

  • Prosessorienterte anskaffelser

    Prosessorienterte anskaffelser

    I samarbeid med Sykehusinnkjøp.

    Supervisor: Malin Arve.

  • Telenor-boten

    Telenor-boten

    Konkurransetilsynet gav i juni Telenor 788 mill. i bot. De mener Telenor har misbrukt sin markedsmakt ved å forhindre at et tredje mobilnett ble utbygd, og ilegger selskapet 788 millioner i overtredelsesgebyr. Telenor nekter for å ha gjort noe galt. Hva ligger bak denne boten? Er den korrekt?

    Krav: God bakgrunn i IO. Konkurranserett bra, men ikke nødvendig.

    Supervisor: Øystein Foros.

  • Telia-Get fusjonen

    Telia-Get fusjonen

    Gjøre en konkurranseanalyse av media/telemarkedet.

    Supervisor: Øystein Foros.

  • Konkurransen i mobilmarkedet

    Konkurransen i mobilmarkedet

    Sammenligne f.eks. Norge og Finland som har ulik markedsstruktur. Mye deskriptiv empiri for å bedre forstå markedet og forskjellen mellom landene.

    Supervisor: Øystein Foros.

  • Bokavtalen

    Bokavtalen

    Kulturminister Trine Skei Grande har nylig foreslått å utvide bokavtalen. Det vil gi en lengre fastprisperiode og høyere priser på opptil 65 prosent av bøkene. Den norske bokavtalen, som gir forleggerne rett til å sette en fast pris på nye bøker, er havnet i søkelyset til Efta-landenes overvåkningsorgan Esa. Nylig besvarte Nærings- og fiskeridepartementet (NFD), på vegne av den norske regjeringen, en rekke spørsmål fra Esa om forholdet mellom bokavtalen og EØS-avtalens eksplisitte forbud mot prissamarbeid i artikkel 53. Her kunne det være interessant å sammenligne med kommisjonens sak mot Amazon ift most-favored nation (MFN) klausuler.

    Supervisor: Øystein Foros.

  • Personalisert prising

    Personalisert prising

    Med utgangspunkt i prosjektet Moving towards the market of one? Competition with personalized pricing and endogenous mismatch costs, jobbe med applikasjoner? Kan også knyttet opp mot AI.

    Supervisor: Øystein Foros.

Shipping, Logistics and Operations Management

  • Shipping: Benchmarking charterer/owner performance in the chartering market

    Shipping: Benchmarking charterer/owner performance in the chartering market

    Using public fixture data, to analyze the extent to which company name affects market power in negotiations and freight rates. Requires knowledge of fixed-effects regression models.

    Supervisor: Professor Roar Ådland

  • Shipping: Economic optimization of underwater hull-cleaning intervals

    Shipping: Economic optimization of underwater hull-cleaning intervals

    Using fuel consumption and cost data from individual ships: How often should the company clean the hull of a ship to reduce fuel costs. Advanced – requires some knowledge of optimization, optimal stopping problems, semi-parametric regressions.

    Company: SKS Tankers.

    Supervisor: Professor Roar Ådland

  • Shipping: How can vessel performance data be used to optimize commercial operation?

    Shipping: How can vessel performance data be used to optimize commercial operation?

    Using vessel performance and open-source weather data – show how better fuel cost estimates affect the economics of ship operation. Strong knowledge of econometrics required.

    Company: SKS Tankers or Golden Ocean.

    Supervisor: Professor Roar Ådland

  • Shipping: The economics of IMO 2020

    Shipping: The economics of IMO 2020

    Using updated data on timecharter and/or voyage charter rates, investigate whether freight rates reacted to the new regulations implemented on January 1, 2020.

    Supervisor: Roar Ådland

  • Shipping: Vessel speed analysis using AIS data

    Shipping: Vessel speed analysis using AIS data

    Using AIS data on ship positions, investigating how vessel speeds react to changes in fuel prices and spot freight rates in the short- and long run.
    Requires familiarity with co-integration tests and econometrics.

    Supervisor: Professor Roar Ådland

  • Shipping & Finance: Machine learning models for FFA trading

    Shipping & Finance: Machine learning models for FFA trading

    Using spatial AIS data for ship positions, open-source weather and macro data – can you develop a machine learning model to generate profitable trading signals? Requires knowledge of Python, implementation of machine learning models.

    Supervisor: Roar Ådland and Haiying Jia

  • Shipping & Finance: How do risk capital and risk limits affect the chartering policy of a ship operator?

    Shipping & Finance: How do risk capital and risk limits affect the chartering policy of a ship operator?

    Using: freight rates timeseries, optimal portfolio theory.

    Company: Western Bulk.

    Supervisor: Professor Roar Ådland

  • Blå Bybane (Blue Light Rail)

    Blå Bybane (Blue Light Rail)

    Bergen has built its first light rail line from the city centre to the airport. Other lines are being discussed politically. This thesis covers a related idea, which has been called “Blue Light Rail”, though it is not a rail line at all, but an idea of having scheduled vessels (high speed boats) playing the same role as light rail, and utilizing the fact that Bergen is a coastal city with complicated topology.

    There are several places with a reasonably large transportation need that are more easily reached from Bergen city centre by boat than by car or bus (or rail). The most obvious ones are Askøy, Knarvik (which already have connections) and Ågotnes (Sotra), which has not. It is also possible to imagine routes within the area around the city centre itself.

    A suggestion has been to connect Laksevåg, Dokken, Hegreneset and Sandviken (if you don’t know Bergen, ask Mr Google). This could facilitate a fascinating development of central Bergen by providing clean and efficient transportation to new developments. Typically these vessels will have electrical engines.

    Bergen Chamber of Commerce (Næringsrådet) has established a committee looking into the Blue Light Rail, and this thesis will interact with that committee. The thesis is also placed within a project on autonomous vessels (though autonomy comes later) funded by the Norwegian Research Council, attached to NHH’s Centre for Shipping and Logistics.

    The thesis can take many forms related to such as scheduling relative to other means of public transportation (possibly with a special emphasis on how delays can be handled), the interaction with tourism (it is quite attractive for some groups of tourists to get a trip on the fjord at ordinary, non-touristic prices), and an analysis of the environmental advantages of such a service. But feel free to suggest other perspectives on the problem, as there are others.

    The thesis can fit into many different profiles, particularly BAN, ENE and BUS, depending on the profile of the students.

    NHH contact: Stein W. Wallace

    External contacts: This depends on the profile of the thesis. Possibilities are:

    • Bergen Chamber of Commerce (by its leader Atle Kvamme) and the Chamber’s Blue Light Rail Committee. This covers almost any profile you could possibly choose.
    • CEO Johnny Breivik, Port of Bergen
    • Member of the municipal government (with responsibility for city development) Anna Elisa Tryti and her advisor Tarje Wanvik.
    • Roger Harkestad at TIDE (bus company)
    • Lars Jacob Engelsen at Norled (boat and ferry company)

     

  • Small city logistics

    Small city logistics

    Urban population growth is driving an increase in the amount of freight that goes into and out of cities. That growth poses an increasing challenge to freight transportation in smaller compact cities with difficult topology, which is typical for most Norwegian cities and numerous cities abroad. This transportation challenge is exacerbated by phenomena such as an increase in internet trade, the demand for fast delivery, and a reduction in the ownership of private cars in the city centre which could be used for shopping. The result is an increase in the total volume of freight, and more critically, in the total number of deliveries, normally managed by a large variety of transportation companies. Unless planned for and regulated, a consequence might be increased traffic, with enhanced energy consumption, that competes for available space and may affect living conditions for a growing urban population.

    This project will study small city logistics, with a focus on Bergen, to find the options available for the authorities, as well as business models for a better city logistics setup. Will be done in cooperation with the City of Bergen and Bergen Chamber of Commerce. The project can be qualitative as well as quantitative.

    Supervisor: Stein W. Wallace.

  • How will autonomous vessels change the operations in the shipping industry (including deep-sea shipping, short-sea shipping and local waterway transport)?

    How will autonomous vessels change the operations in the shipping industry (including deep-sea shipping, short-sea shipping and local waterway transport)?

    Background

    If you are a hunter from the Stone Age and one day you are facing an offer to replace you wooden stick with a brand new shotgun, will you still use your new weapon just as a harder stick made of steel to kill your prey, or use it in a better way? Similar challenges are now faced by the shipping companies due to the forthcoming technological evolution, namely the autonomous ship. Obviously, an autonomous ship with no crews on board can significantly reduce a shipping company’s crew cost.

    However, just like the increased hardness of a shotgun in the hunter example, the reduction of crew cost might just be a tiny benefit of the autonomy of our ships. Besides the lower crew cost, what are the fundamental advantages of an autonomous vessel comparing to the conventional manned ship?

    Greater potentials are expected by better utilizing these advantages with innovative ideas in the daily operation of the vessels, such as higher frequency of ferry in the night time, flexible hub location for waterway taxi and multi-functioned vessels with different remote control teams. The world’s first commercial autonomous vessel (Yara Birkeland) will be soon launched in Norway in the end of 2018. And it is a great opportunity for the students here to also take the leading position in the research of the autonomous vessel.

    Potential Reference

    Toth, P., Vigo, D. (2002). The Vehicle Routing Problem. Philadelphia: SIAM Publications Stopford, M. (2009). Maritime Economics. London: Routledge.

    Contact: Yewen Gu

  • Using autonomous vehicles to improve our emergency services

    Using autonomous vehicles to improve our emergency services

    The aim of emergency medical services (EMS) is to provide timely assistance to emergencies in order to save lives. Within this service, quality and capacity have sometimes deteriorated because staffing is not satisfactory and because the organization and directives are not clear. My interest is to work on the use of autonomous vessels to help ameliorate the burden that EMS staffing represents in the case of boat ambulances, and to improve the logistics planning of the system.

    The aim is to analyze the use of autonomous vessels to improve response times and coverage. For example, by combining autonomous vessels with geographic information systems, one may use real time information of potential patients to improve the deployment of the resources. In particular my interest is to explore the following key research topic: designing algorithms with predictive capabilities that can be included in real time systems and capable of managing a continuous feed of data points coming from users’ cell phones and other sources.

    Supervisor: Julio C. Goez.

  • Flexible Transport Scheduling with Autonomous Vessels & Autonomous Buses

    Flexible Transport Scheduling with Autonomous Vessels & Autonomous Buses

    Analyze how autonomous transport can increase the inhabitants use of public transport and move transport from road to see or from road to train. How should the routing be conducted so that people are willing to replace road transport with train/sea transport on the main distance? Discuss parameters, constraints and objectives for the routing model. For example: Autonomous busses picks up passengers in the Voss region transport them to Voss railway station where they can take the train to Bergen railway station.

    Supervisors: Mario Guajardo and Sigrid Lise Nonås.

  • Economics of deep-sea autonomous shipping

    Economics of deep-sea autonomous shipping

    • This thesis aims at identifying and analyzing opportunities created by autonomous vessels in the delivery of services. The focus will be on new opportunities in economics of deep-sea cargo shipping.

      Contact: Siri Pettersen Strandenes

  • Using the Physical Internet Analogy to Design Modern Logistic Networks

    Using the Physical Internet Analogy to Design Modern Logistic Networks

    I am interested in working on exploring new designs for logistics systems. A big problem with our current transport and logistic methods is that they are unsustainable from an economic, environmental, and societal perspective. Inefficiencies can be found thought all the processes, from empty trucks dead-heading to pick up their next loads, to underutilized distribution centers.

    Recently an new paradigm has been propose called the physical internet, which is define in the literature as “an open global logistics system founded on physical, digital and operational interconnectivity through encapsulation, interfaces and protocols”. This aims to fix several of the inefficiencies of the logistics systems introducing ways to move goods using standardized, modular containers. This vision is attracting significant investments especially in the European Union." 

    Supervisor: Julio C. Goez.

  • Optimization and Simulation Models to Improve Efficiency in a Norwegian Refinery

    Optimization and Simulation Models to Improve Efficiency in a Norwegian Refinery

    Develop optimization and/or simulation models to improve the efficiency and increase the production rate in a Norwegian refinery (Elkem Bremanger).

    Supervisor: Sigrid Lise Nonås.

  • Waste Management

    Waste Management

    New waste pipelines are built below the surface in the city center. How can BIR improve the efficiency and increase the utilization of the pipelines?

    Topic 1

    Use optimization, simulation and tools from supply chain management to improve the waste management in BIR.

    Topic 2

    BIR can only collect data from garbage handling for the owner of a house or an apartment. Many of the houses in the city center are divided in several apartment that are rented to students or other inhabitants. How BIR can increase individuals (renters) incentives to sort garbage when BIR only can collect aggregate data from all the apartment in the house? If BIR could track the for each household, which impact would that have on the individual willingness to sort their garbage?

    Supervisor: Sigrid Lise Nonås.

  • Supply Chain Analysis of a Multi-Channel Clothing Company

    Supply Chain Analysis of a Multi-Channel Clothing Company

    Analyze the supply chain configuration for a multi-channel clothing supply chain. Discuss if the current configuration is a good fit for the markets the company serve. Take into account all the dimensions of supply chain performance (facilities, inventory, transportation, data handling and data analysis, sourcing, pricing).

    Based on the result from the analysis, identify in which areas the company have the largest challenges and suggest how they can improve supply chain performance. To narrow the scope of the thesis you could for instance analyze if inventory management and revenue management are in line with the supply chain strategy and the current supply chain configuration (facilities, inventory, transportation, data handling and data analysis, sourcing, pricing) for a company selling children clothes in Norway.

    Supervisor: Sigrid Lise Nonås.

  • The Operational and Economic Impact of Autonomous Ship Application, Comparing to the Traditional Manned Vessels. Wartsila, Fjellstrand, NYK

    The Operational and Economic Impact of Autonomous Ship Application, Comparing to the Traditional Manned Vessels. Wartsila, Fjellstrand, NYK

    Supervisor: Yewen Gu.

  • Repositioning of Empty Vessels in the Dry Bulk Shipping Market

    Repositioning of Empty Vessels in the Dry Bulk Shipping Market

    Aim: find key drivers for decision-making process of repositioning empty vessels - current market conditions, sentiment - repeating patterns, etc.

    Supervisor: Vít Procházka.

  • Emission Abatement Technology for a Shipping Company - is the Uncertainty of Fuel Prices Important?

    Emission Abatement Technology for a Shipping Company - is the Uncertainty of Fuel Prices Important?

    Is the uncertainty of fuel prices important to be considered when a shipping company selects its emission abatement technology for the compliance of ECA regulation.

    Supervisor: Yewen Gu.

  • Operations Research Applications in Tine

    Operations Research Applications in Tine

    Dairy farmers with combined milk and beef production face complex decisions regarding optimum milk yield, slaughter age for bulls, calving age for heifers, disposal of farm land etc. The aim for this topic is to explore how operations research may help farmers improve their decision making process to increase their profitability. In this project the students will interact with TINE, Norway's largest producer, distributor and exporter of dairy products with 11,400 members (owners) and 9,000 cooperative farms.

    Supervisors: Mario Guajardo and Julio C. Goez .

  • Logistics/sharing economy: Analytics for car-sharing models

    Logistics/sharing economy: Analytics for car-sharing models

    Car-sharing provides short-term vehicle access to a group of user members who share the use of a vehicle fleet owned by a car-sharing organization that maintains, manages, and insures the vehicles. An example of this model in Bergen is bildeleringer. Managing the fleet involves decisions such as the size of the fleet, how to position and reposition the vehicles, maintenance schedules, and pricing approaches. Strong background on analytics required

    Supervisors: Julio C. Goez and Mario Guajadaro.

  • Optimization of requirements of cloud computing resources

    Optimization of requirements of cloud computing resources

    The providers of online applications usually need to find the deployment of minimum cost for running it in the cloud. For the deployment, the planner on the application side must consider renting resources from cloud providers. However, there is a service level constraint that must be satisfied to ensure the quality of the service.

    Supervisor: Julio C. Goez.