NHH Brage (Norges Handelshøyskole)
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The Price of Information: Evaluating Customer Responses to Information-as-a-service (InaaS) Pricing Models : An explorative case study with three InaaS software firms
Get PDFCompanies have to constantly adjust their data acquisition strategy as new information
sources have become increasingly available. This has made it more complex for InaaS
vendors to configure pricing models that align well with customer expectations. This study
explores how InaaS vendors can configure price in order to maximize customers’ perceived
value in markets with asymmetric information dynamics. By conducting an exploratory
case study with three InaaS vendors, we have been able to interview several Norwegian real
estate industry professionals. Through these interviews, ten parameters where identified
relating to pricing that we suggest affect customers’ perceived value of vendors’ products.
Additionally, we discuss how these parameters affect customers’ perception of value in light
of the different pricing models of our case companies. Our findings indicate a prevalent
preference among interviewees for a subscription-based pricing model, primarily driven by
its simplicity and cost predictability. We also find our interviewees highly prefer trials as
a tool to evaluate a products value. Nonetheless, our research suggest that there is no
single universal pricing model that maximises perceived value for all customers. Therefore,
we recommend that vendors take our proposed parameters into account, as they explore
what pricing configuration aligns best with their customers.nhhma
Fra installering til implementering : En casestudie av hvordan etablerte virksomheter kan lykkes med implementeringen av digitaliseringsinitiativ
Get PDFFlere etablerte virksomheter feiler i dag med implementering av nye digitaliseringsinitiativ.
Dette i form av at digitaliseringsinitiativet ikke blir brukt som tiltenkt og at ønskede gevinster
uteblir. En mulig årsak til dette er at kompleksiteten bak implementeringen undervurderes for
tilsynelatende enkle digitaliseringsinitiativ. Det kan derfor være et behov for, både i litteratur
og i praksis, å forstå mer om hvordan implementeringen av også slike mindre kompliserte
digitaliseringsinitiativ burde foregå. Vi har derfor studert problemstillingen «Hvordan kan
etablerte virksomheter lykkes med implementeringen av digitaliseringsinitiativ?».
For å besvare problemstillingen har vi gjennomført en kvalitativ casestudie med DOF Group
ASA som casevirksomhet, hvor intervjuer har vært vår primære datakilde. Her har vi sett
nærmere på to digitaliseringsinitiativ som i ulik grad har lykkes med implementeringen. Siden
implementeringen av nye digitaliseringsinitiativ er en moderne form for endring har vi tatt
utgangspunkt i litteratur om endringsledelse for å besvare problemstillingen. Her har vi sett
nærmere på teori om endringsreaksjoner og teknologiaksept for å forstå hvordan det er mulig
å oppnå endringsvilje og positiv holdning blant ansatte. I tillegg har vi benyttet oss av teori
om endringsledelse og gevinstrealisering for å forstå hva som skal til for å sikre bruk og videre
gevinstrealisering fra digitaliseringsinitiativene.
Basert på våre funn har vi utviklet en modell ledere kan benytte seg av for å lykkes med
implementeringen av digitaliseringsinitiativ. Vi har her delt implementeringen inn i tre faser.
Den første er utviklingsfasen. Her er det viktig å identifisere hovedgevinstene og effektivt
legge en plan, før ansatte også blir involvert i prosessen. Neste fase er selve innføringsfasen.
Da er det essensielt at nytten av initiativet kommuniseres, i tillegg til at det også gis opplæring
tilpasset behovet. Til slutt kommer bruksfasen hvor ledelsen jevnlig bør følge opp de ansatte,
før de avslutningsvis bør kommunisere de realiserte gevinstene.
Ved hjelp av vår studie vil ledere i etablerte virksomheter få mer kunnskap om hvordan de kan
sikre bruk og gevinstrealisering fra ulike typer digitaliseringsinitiativ gjennom en riktig
implementering. I tillegg vil vi dekke et gap i litteraturen ved å se på suksessfaktorer for også
mindre og enklere digitaliseringsinitiativ. Her bidrar vi også til endringsledelse som fagfelt
ved å gi et ytterligere perspektiv på digital endringsledelse.nhhma
Scheduling Support Vessels In Antarctic Krill Fishing : A Mixed-Integer Linear Programming Model With A Rolling Horizon Approach
Get PDFIncreasing food prices in Europe demands a heightened attention to resource utilisation.
This leads to a great potential to better utilize one of the most abundant biomasses on
earth: krill. These tiny crustaceans consist of more than 25% lipids containing omega-3
fatty acids and more than 60% high quality proteins (Tou et al., 2007). Today krill products
are produced both for pets and humans, and it is especially popular in aquaculture feed.
There is, however, still a great potential for this resource to be utilized better and in an
even more effective way.
This thesis aims to optimize the supply chain, and more specifically the fishing operation in
the Antarctic krill fishing business. A case study of the Aker BioMarine fishing operation
is conducted for a single season where a schedule is created for their support vessel, a
vessel used to transport krill, crew, fuel, and equipment between the fishing vessels in the
Antarctic Ocean and the shore of South America, to maximize the total krill harvested
while keeping costs down. This was done using a mixed integer linear programming model
with a rolling horizon approach. In addition to using the numbers from the 2021 season,
the model was also tested on two scenarios: one where the fishing rates were increased by
50%, and one where the travelling times between all locations were increased. This was to
see the model’s performance under more lucrative seasons, and seasons with bad weather.
The base case findings show that the MILP approach effectively schedules the season so
that the support vessel has as few trips as possible, while allowing the fishing vessels
to have no ineffective days. This was also the case in the scenario with the increased
travelling times. The results for the scenario with increased fishing rates were slightly
worse. The support vessel still had no problem managing to deliver all krill while keeping
the fishing vessels active every day. It used unnecessarily many trips to do so. We allocate
this inefficiency to problems related to the rolling horizon approach.
This study shows the effectiveness in using mathematical modelling to schedule support
vessels in fishing operations to keep the operation effective while cutting unnecessary
costs.nhhma
The Influence of Monetary Policy on Bank Profitability : A Study of Scandinavian and Central European Banks
Get PDFIn this thesis, we find support for the notion that interest rate hikes improve bank profitability. Our results imply that monetary policy might have had a more profound impact on bank profitability from 2021 onwards compared to the preceding decade. When decomposing bank profitability into its components, our analysis suggests that the effect of interest rates on bank profits comes through strong positive effects on net interest income and muted effects on non-interest income and loan loss provisions. Further, in a comparison of the effects in different countries, our findings indicate that the impact of interest rates on balance-sheet bank profitability might be stronger in Eurozone countries and Sweden than in Norway. Lastly, our estimations signal a potential negative impact of sudden interest rate hikes on Eurozone banks’ stock prices and that sudden interest rate changes might not impact Norwegian and Swedish bank stock prices.nhhma
Assessing the Impact of Sustainability Reporting on Organizational Processes and Outcomes : An Exploratory Case Study
Get PDFThe number of companies that have started disclosing their performance with respect to environmental, social and governance (ESG) themes has been growing rapidly in the last two decades. Sustainability reporting, considered as a valuable instrument for reducing the business world’s adverse impacts on the environment and society, has been the object of increasing regulation and standards. This thesis is aimed at advancing the present knowledge on the impacts of corporate sustainability reporting on organizational learning, growth and change, on the one hand, and the roles played by the different parts and features of the reporting process, on the other.
This research makes use of a qualitative case study, performed on an established firm in the Italian local public transport industry. While experts and regulators emphasize the relevance of sustainability reporting in the transition of the business world toward more sustainable ways of being, consensus on the effects of reporting is lacking. The existing literature does not provide clear agreement for arguing for the potential of the practice.
The findings of this study are twofold. Firstly, it finds that reporting can act as a catalyst for organizational learning, growth and change, while strengthening relationships with those stakeholders that demonstrate a high level of engagement. Because each of these processes in turn affects the strategic dimension, improvements in economic performance may well be an indirect, significant consequence.
Secondly, this research draws attention to the relevance during the sustainability reporting process of an initial self-assessment of organizational identity, strategic priorities and resource allocation choices, as well as of measuring results and outcomes. Moreover, the significance of the materiality analysis’ insights is highlighted.
Overall, this thesis provides novel insights to both academics and managers, highlighting that reporting has the potential to strongly influence organizations. Because of the increasing importance of the role it will play in a world that is quickly changing, it is suggested that future research further explores the impacts of sustainability reporting.nhhma
Crossing Borders, Shaping Futures : An empirical study of migration’s influence on Mexican educational paths.
Get PDFThis study aims to answer the question: "Can migration from Mexico to the United States
have a causal effect on educational attainment in Mexico?". We examine the impact of
residing in Mexican households where at least one member has migrated to the United
States. Specifically, we look into the educational outcomes of individuals aged 12-22 who
live in migrant households but did not migrate themselves. Employing an Instrumental
Variables (IV) approach, we utilize migration rates from 1987 to address the endogenous
nature of migration conditions for Mexican households in 2018. We leverage national-level
survey data from Mexico, combined with information from INEGI and CONEVAL, to
conduct the IV approach. Additionally, our study explores the specific effects of migration
on the educational journeys of males and females.
Our analysis uncovers a statistically significant causal relationship, indicating that
migration is associated with lower completion rates among Junior High and High School
males. With an extension of our model, we identify statistically significant results
concerning the impact of migration on school completion rates for females aged 15-19 as
well. Despite recent advancements in Mexico, our findings suggest a persistent adverse
effect on educational attainment associated with migration, particularly regarding the
completion of Junior High and High School levels. We conclude our analysis by discussing
the potential educational effects of incentivizing individuals to remain in Mexico instead
of seeking employment in the US.nhhma
Hedging strategies within the aluminum market An analysis of forecast adjusted strategies with the persepctive of a Norwegian entity
Get PDFThis thesis examines the effectiveness of static and selective hedging strategies in the
aluminum market. Additionally, the thesis highlights the outcome from the perspective of a
Norwegian entity, particularly focusing on the impact of the USD/NOK exchange rate. By
applying forecast adjustments to static strategies such as MVHR and Naive HR, we develop
selective strategies. We then analyze these to determine whether they provide any additional
benefits. Employing a quantitative analytical framework, the study uses regression analysis to
calculate the HR and adjust the MVHR and NHR based on three forecast types: analyst
predictions, naive forecasts, and seasonal and trend variation forecasts. This methodology is
thoroughly tested for data validity, including tests for stationarity, cointegration, and normal
distribution.
The research reveals that hedging strategies adjusting for analytics market forecasts offer the
best risk-adjusted returns, as indicated by higher Sharpe ratios. Additionally, the research
presents that selective strategies does not necessarily improve hedging effectiveness, when
compared to static strategies. We also find that the results differ when considering the impact
of currency exchange rates. This variation is notable in terms of both the Sharpe ratio and
hedging effectiveness, underscoring the significant role currency fluctuations play in
determining the optimal approach for hedging.
This thesis contributes to the field by presenting a novel approach to hedging strategy
formulation, incorporating forecast-based adjustments and currency fluctuations. It provides
empirical evidence on the effectiveness of these adjusted strategies in managing market risks.
This research underscores the importance of incorporating dynamic forecast adjusted
strategies, particularly for entities in the aluminum market operating across different
currencies. It presents a comprehensive view of how tailored hedging approaches can
effectively manage the inherent risks in commodity trading. The research offers valuable
insights for both theoretical understanding and practical application in risk management.nhhma
Overheating, Bubbles and Stagflation in the Norwegian Economy : An empirical study of crisis anatomy.
Get PDFSince the turn of the millennium, a lasting period of mostly strong national economic growth has persisted. In the autumn of 2021, the Norwegian Central Bank began increasing the policy rate and has since increased it 13 times. This rapid increase in policy rate came about due to increasing inflation and a weakened currency. This thesis aims to assess if the economy is headed towards a crisis by conducting an empirical analysis of the present-day economy and a comparative analysis of past crises. The primary conclusion drawn is that the Norwegian economy shows strong signs of having been slowly overheated and is now perhaps headed towards stagflation,
The empirical analysis involved estimating the Taylor rule and Tobin’s Q as well as using the Hodrick-Prescott filter to estimate the long-term trend in various macro indicators. The Taylor Rule was used to assess the central bank’s recent historical interest rate decisions, while Tobin’s Q was used to check for deviation from fundamental values in the stock market.
The results from Taylor Rule and Tobin’s Q indicate that the Norwegian economy has had the necessary foundations to become overheated through an artificially low policy rate and actual overheating in the stock market. Combined with the strong growth in macro indicators such as GDP, consumption, and household leverage, it seems quite clear that there has been at least some overheating.
With unemployment creeping upwards, inflation rising swiftly, and GDP slightly plateauing, it is tempting to speculate on the potential of incoming stagflation. Many fundamental factors are also in place compared to historical incidents, such as increased prices for global input factors and a long period of previous overheating.nhhma
Exploiting the Index Effect on OSEBX using Machine Learning : Trading on predictions made by GLM and XGBoost with a conditional posterior probability threshold
Get PDFIn March and September of each year, Euronext decide which companies should be
included on the Oslo Stock Exchange Benchmark Index (OSEBX). OSEBX consists of
50-80 companies, all selected from the approximately 200 companies on the Oslo Stock
Exchange All Shares Index (OSEAX). We find that new additions and deletions to OSEBX
experience significant price effects leading up to the actual date these changes take place,
the effective date (ED). These price effects are named the index effect.
We use the machine learning (ML) models eXtreme Gradient Boosting (XGBoost) and
Generalised Linear Model (GLM ) to predict index composition to OSEBX in the months
leading up to ED. We find that both XGBoost and GLM can predict index composition
with accuracy higher than 94%, 30, 60, and 100 days in advance of ED.
Next, we simulate portfolios from 2010 to 2022, buying predicted additions and selling
predicted deletions. We find that GLM models predict few, but high-yielding companies.
XGBoost models predict more additions and deletions and create more diverse portfolios.
The best GLM and XGBoost portfolios outperformed OSEBX by respectively 0.95% and
0.32% per month (11.4% and 3.84% per year) in the period from 2010 to 2022. Even after
adjusting for risk in a Fama-French 3 Factor Model (FF3), the same portfolios showed
significant alphas at a 95% confidence level.
Lastly, we investigate if the same active trading strategy can yield excess returns in an
enhanced index portfolio. In practice, we did this by combining the already simulated
portfolios with OSEBX, where we optimised the active share of the portfolio to give the
combined portfolio a tracking error of 2%. For the enhanced index portfolios, the best
GLM and XGBoost portfolios outperformed OSEBX by respectively 0.05% and 0.06%
per month (0.6% and 0.72% per year). However, after adjusting for risk factors in FF3
only one of the XGBoost portfolios showed a significant alpha (�-value < 0.1).
In short, we find that ML models can predict upcoming changes to OSEBX with high
accuracy and that exploiting the index effect using ML can yield excess returns.nhhma
Gender-biased technological change: Milking machines and the exodus of women from farming
Get PDFThis paper studies the link between gender-biased technological change in the agricultural sector and structural transformation in Norway. After WWII, Norwegian farms began widely adopting milking machines to replace the hand milking of cows, a task typically performed by women. Combining population-wide panel data from the Norwegian registry with municipality-level data from the Census of Agriculture, we show that the adoption of milking machines triggered a process of structural transformation by displacing young rural women from their traditional jobs on farms in dairy-intensive municipalities. The displaced women moved to urban areas where they acquired a higher level of education and found better-paid employment. These findings are consistent with the predictions of a Roy model of comparative advantage, extended to account for task automation and the gender division of labor in the agricultural sector. We also quantify significant inter-generational effects of this gender-biased technology adoption. Our results imply that the mechanization of farming has broken deeply rooted gender norms, transformed women’s work, and improved their long-term educational and earning opportunities, relative to men