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Senast inlagda
Strategic Evaluation in Biopharma An adapted Balanced Scorecard for Late-Stage R&D Governance at AstraZeneca
(2025) Essunger, Hampus; Holm, Olle; Ladenvall, Adam; Farhad, Hanno; Kolovos, Raphael; Rutberg, Elias
The biopharmaceutical industry is characterized by long, uncertain and expensive R&D processes.
Investment decisions in late-stage R&D projects, which often involve financial projections and
strategic judgments, are therefore critical for companies’ success. The aim of this thesis has been to
develop an adapted Balanced Scorecard specifically tailored for evaluating late-stage R&D projects at
AstraZeneca, one of the largest biopharmaceutical companies in the world. The study addresses the
challenge of integrating both quantitative financial parameters and qualitative parameters, such as
strategic and competitive insights, into a comprehensive framework relevant for evaluating R&D
projects. Through combining a theoretical framework through a systematic literature review on
project evaluation methods in the biopharmaceutical industry, with a case study of AstraZeneca’s
R&D evaluation process in the late-stage governance, based on interviews with relevant employees at
the company and quantitative data from 12 projects, the study identifies and validates important
evaluation parameters essential for R&D decision making in the biopharmaceutical sector. Some
example parameters include metrics such as Net Present Value (NPV), Probability of Technical and
Regulatory Success (PTRS), Portfolio Gaps within Resource Capabilities, and Product Area
Dominance. These evaluation parameters have been synthesized into three overarching categories -
Financial Impact, Strategic Fit and Competition, which when combined result in the AstraZeneca
adapted Balanced Scorecard.
The study finds that AstraZeneca in the past had difficulties integrating the Balanced Scorecard in
their ways of working, due to its perceived complexity, and it was therefore phased out. To address
these challenges, the adapted Balanced Scorecard presented in this thesis was developed to be
simpler, more intuitive, and better aligned with AstraZeneca’s existing R&D evaluation practices. The
simplification of the tool was achieved by including perspectives relevant to R&D project decision
making and metrics already used by AstraZeneca. The study also presents and discusses in further
detail how the adapted Balanced Scorecard is designed, discusses its application and what value it
provides.
The Impact of Capital Intensity on Private Equity Returns A Multiple Regression Analysis
Antmar, Inez; Gustavsson, Oscar; Sand Uhlén, Simon
This study examines how capital intensity in acquired companies influences return
on investments (ROI) for private equity firms. The analysis is based on a dataset of
171 European private equity transactions completed between 2000 and 2025. The
analysis employs an Ordinary Least Squares (OLS) regression model to test whether
target firms’ capital intensity levels significantly influence ROI for the private equity
firm. Capital intensity is measured as the ratio of net property, plant, and equipment
to sales and categorized into low, medium, and high groups. The results demonstrate
a statistically significant negative relationship between capital intensity and ROI,
with investments in low capital intensity firms yielding higher ROI. Several control
variables, including holding period, buy value, and macroeconomic indicators, were
included in the model to account for other factors influencing ROI.
The findings contribute to the literature by providing quantitative evidence that
capital intensity affect investment performance and offer practical insights for in-
vestment strategy development.
Strategiska vägval för västsvensk petroleumraffinering: En studie av hur utsläppens karaktär utgör en drivkraft för grön omställning
(2025) Drougge, Isak; Furby, Oscar; Jacobsson, Oscar; Johansson, Melvin; Olofsson, Jonathan
Problem
Allt större klimatförändringar innebär förändrade konsumtionsmönster för fossila bränslen, till
följd av strängare regulatoriska krav och en växande efterfrågan på förnybara energikällor.
Detta hotar petroleumraffineringsindustrins framtida existensberättigande, trots att branschens
produkter i många fall är icke-substituerbara. Om framtida efterfrågan ska tillgodoses hållbart,
måste petroleumraffinaderier förändra sina strategier för att förbli långsiktigt och
klimatmässigt konkurrenskraftiga.
Syfte
Syftet med studien är att förklara och analysera hur västsvenska petroleumraffinaderier
anpassar sina strategier för att förbli konkurrenskraftiga, samtidigt som de påverkas av den
gröna omställningen och föränderliga marknadsförhållanden. Studien syftar till att kartlägga
de strategiska åtgärder och investeringar som vidtas för att anpassa petroleumraffinaderiers
kärnverksamhet när deras fossilbaserade produkter riskerar att bli förlegade och irrelevanta.
Teoretiskt ramverk
Studiens huvudsakliga forskningsområden är affärsutveckling och strategi samt institutionell
teori. Inom dessa för studien relevanta forskningsområden utgörs det teoretiska ramverket av
vetenskapliga artiklar, böcker och branschspecifika publikationer. Källornas tillförlitlighet
bedömdes med hänsyn till de fyra källkritiska kriterierna och studien har premierat artiklar
publicerade av välrenommerade och tillförlitliga universitet, tidskrifter och myndigheter.
Metod
Fallstudien var utforskande till sin natur och avgränsades till att undersöka fyra västsvenska
petroleumraffinaderier, verksamma inom samma huvudsakliga bransch men inom olika
delbranscher. Primärdata från de undersökta företagen samlades in genom intervjuer med
anställda med strategisk insikt och kompletterades med sekundärdata från främst företagens
års- och hållbarhetsredovisningar. Teoretiska modeller, analysverktyg och tidigare forskning
användes för att analysera insamlade data samt för att underbygga diskussion och slutsatser.
Resultat och implikationer
Studien bidrar teoretiskt till forskningsområdena affärsutveckling och strategi samt
institutionell teori, med förståelse för hur västsvenska petroleumraffinaderier agerar strategiskt
när de hotas av externa faktorer. Studiens praktiska bidrag utgörs av en kartläggning av
hållbarhetsinriktade strategiförändringar som är relevanta för aktörer och regulatorer inom
petroleumraffineringsindustrin under en grön omställning. Drivmedelsproducenternas
strategiförändring utgörs främst av investeringar för en diversifiering av produktportföljen med
förnybara insatsvaror som reducerar konsumtionsrelaterade utsläpp. Producenterna av
specialiserade petrokemiska produkter gör endast marginella investeringar i förnybara
alternativ, till förmån för att energieffektivisera produktionsprocessen och för att skapa
cirkulära flöden för fossila produkter. Konsumtionsrelaterade utsläpp resulterar i faktorer som
innebär att drivmedelsproducenterna genomför mer omfattande strategiska förändringar än
producenterna av specialiserade petrokemiska produkter.
AI’s Impact on Companies’ Intellectual Property Strategies A Qualitative Study on how the Technological Shift of AI Impacts Creation and Management of Intellectual Properties
(2025) Bergström, Evelina; Gustafsson, Hanna; Hallsten, Elsa; Mosslin, Sebastian; Wiberg, Sofia; Ågren, Amanda<
Problem
There is an ongoing technological shift driven by artificial intelligence (AI), making
machines more human-like, in abilities such as problem solving and creation of new works.
Prior research has identified that AI is a potential source of change in the field of intellectual
property (IP) and IP strategy. The technological shift might already have changed the
environment for companies and may further impact the companies’ work with IP and IP
strategy. Although previous studies have acknowledged this impact regarding AI and IP,
there is a lack of qualitative studies exploring how this technological change has affected or
will affect companies’ work with IP or their IP strategies.
Aim
This study aims to explore, analyze and understand whether companies’ work with securing
intellectual property rights (IPRs) and their IP strategies has been, or is expected to be,
affected by the technological shift with AI. Further, this study intends to create a better
understanding of how technology interacts with the legal field when companies strive to stay
competitive.
Theoretical Framework
The theory fundamentally describes the technological shift of AI as of today. Moreover, the
theory includes the field of innovation, IP, IPRs and IP strategy as well as the intersection of
AI and IP.
Method
The study used a qualitative method with an abductive approach. The data was collected
through semi-structured interviews with 20 respondents, selected through analysis and
ranking of research and development (R&D) heavy companies operating in Sweden. Further,
the interview data was transcribed and analyzed using coding.
Results and Implications
The findings indicate that, so far, the companies’ IP strategies have not yet been directly
impacted by the technological shift of AI. The companies’ IP strategies are closely linked to
the overall business strategies, which have not yet been impacted by the technological shift of
AI. However, the findings can be divided into operational, legal and strategical changes.
Legally, the changes are primarily connected to the change of the IP landscape.
Operationally, companies have started to automate some day-to-day tasks. Strategically, AI
has for some made collaborations more complicated, some companies find trade secrets more
valuable now and there are also concerns regarding decreased entry barriers.
The study also highlights potential future opportunities and challenges. Future opportunities
include increased efficiency, cost reductions and enhanced strategic flexibility. Expected
future challenges include legal uncertainty regarding the protection of AI-generated works, a
growing number of patents that make the definition of prior art more complicated, and the
increasing threat of patent trolls. The challenges may necessitate more advanced and adaptive
IP strategies, suggesting potential for significant changes within the area of AI and IP.
Implementing Optimization Algorithms in Swedish Healthcare AI-Based Simulation and Optimization of Internal Patient Trans- ports at Sahlgrenska University Hospital
(2025) Deer, Ahmed; Thulin, Victoria; Furborg, Sara; Westerlind, Marius
Artificial Intelligence (AI) is increasingly being integrated into the field of medicine
to improve treatment outcome, enhance efficiency and streamline internal hospi-
tal transports. This study investigates the application of AI to optimize patient
transport at Sahlgrenska University Hospital. The goal is to identify different meth-
ods that can help to improve patient flow and resource allocation. Interviews at
Sahlgrenska along with an expert within AI were conducted to gain a better un-
derstanding of how AI can be altered and used. Anonymous important data from
Sahlgrenska with patient transport times, different departments and porter avail-
ability were analyzed over the course of a year’s time. The main challenge was creat-
ing an AI-based simulation system that accurately represents Sahlgrenska and also
showcases a model of how the porters transport patients throughout the hospital.
This was done with genetic algorithms (GA) as well as integer linear programming
(ILP) and for the systems to give valid data the hospital transport data must closely
replicate the actual size and operations of the hospital.
The results show that the AI-based system could substantially improve hospital
transports in regards to distributing the workload more equitably, maximizing ef-
ficiency and reducing cost as well as preventing further financial losses. Finally
a conclusion that an AI-based system for coordinating patient transport could be
drawn. Challenges for implementations include system integration, data privacy and
ethical task allocation. Nevertheless, strategic planning along with investments, AI
offers considerable potential when it comes to modernizing hospital logistics and
fostering a more efficient and patient-oriented healthcare system.
Keywords: Artificial Intelligence (AI), Patient Transport Optimization, Healthcare
Logistics, Simulation Modeling, Genetic Algorithms (GA), Integer Linear Program-
ming (ILP), Workload Balancing, Resource Allocation, Efficiency Improvement,
Sahlgrenska University Hospital