Background – During the autumn semester, students Elin Carnebrink and Ylva Rehnholm conducted a study as part of the course "Project 2" within the master’s programme Digital Construction Management at Linköping University. The aim of the study was to map educational levels and identify training needs within the construction sector, as part of the development of a scalable and digitalised model for lifelong learning. The project was carried out on behalf of Proteqta Sverige AB and Mikroinvest Sverige AB. One of the main challenges within the construction and civil engineering sector is the verification of formal and practical skills. Although several educational programmes lead to certifications for specific tasks, the assessment of actual competence is often insufficient. In certain cases, fraud occurs, where workers receive certifications without possessing adequate knowledge, which constitutes a significant safety risk at construction sites. Purpose – The aim of this study is to investigate the need for, or whether it can be seen as a solution, to introduce a digital model for verifying practical skills related to working at height in the construction and civil engineering sector. The focus is on how such a model can help identify risks, promote occupational health and safety, and ensure that and ensure that appropriate competencies are used in high-risk tasks during production Method – The study has been conducted using an abductive research approach, where data collection was carried out through method triangulation. Both qualitative and quantitative methods were employed, including a literature review, document analysis, benchmarking, semi-structured interviews, and participant observation. The qualitative data were analysed using thematic analysis. Results/Conclusions – The results indicate a clear and substantial need for a digital and standardized verification model. Current systems are found to be insufficient in ensuring actual competence and compliance with safety requirements. The conclusion is that the implementation of a digital verification model is not only technically desirable but also necessary to meet future demands for safety, quality, and traceability in construction production. Further research is recommended on practical implementation, contractors’ perspectives, responsibility interfaces, and the impact of digitalization on safety culture.

Interpersonal Psychotherapy (IPT), originally developed for depression, is recommended in Sweden’s national treatment guidelines as an option for binge eating disorder and bulimia nervosa. Despite documented efficacy, IPT has primarily been studied as a comparison treatment in eating disorder research. There remains limited knowledge about the method’s functioning in Swedish clinical settings, the mechanisms of change, and how therapeutic work unfolds in practice. This thesis, using a mixed method design, examines the applicability of IPT for individuals with eating disorders and co-occurring depression. The results indicate that IPT is a promising treatment for patients within the bulimic spectrum, showing significant improvements in both eating disorder and depressive symptoms. Notably, improvements in depression preceded symptom relief in the eating disorder – but not the other way around – suggesting a potentially change-driving association. Symptom improvement occurred more rapidly when treatment explicitly and consistently linked current symptoms to emotionally charged relational themes. The qualitative findings demonstrate that this connection – the so-called mood-event connection – is co-created through a collaborative process, in which therapist and patient jointly develop an understanding of what is meaningful and what the next step in therapy should be. Patients with a more restrictive symptomatology showed no improvement. This may possibly be explained by patients’ descriptions of living with the eating disorder as something ever-present in the relating to themselves, others, and life as a whole. The findings suggest that treatment should support the externalisation of the eating disorder as an ego-dystonic condition, foster more functional ways of relating to self and others, and facilitate motivation for a new social role beyond the illness. This thesis supports IPT as a credible and independent treatment for eating disorders, especially in cases involving binge eating, compensatory behaviours, and co-occurring depression.

Agonistic behaviour encompasses both aggressive and passive or avoidant behaviours. In wild boars and domestic pigs, this has mainly been studied in piglet-directed contexts. Research on antagonistic behaviours between sows around farrowing is limited despite potentially affecting social relationships, physical and mental health of sows and piglets. While one study reported a decline after farrowing, another reported no significant changes but had limited consideration of individual variance. We addressed this gap using generalised linear mixed models on previously collected data to account for within-individual variance in sows' tendency to perform agonistic behaviours in connection with farrowing, and whether it was influenced by habitat selection. We hypothesised that agonistic interactions would decline after farrowing, aligning with suggestions that isolation is a counter-adaptation against non-maternal infanticide. Significant declines were observed for all agonistic behaviours after farrowing, with one or both of the isolation and sociality phases affecting the behaviour regardless of habitat. Threatening, biting, and butting decreased over a longer timeframe, which could indicate an adaptive value to maintain social bonds, allowing benefits such as communal care. In contrast, responding defensively declined more rapidly, reflecting a temporary shift, allocating resources by reducing defensive behaviour, when non-maternal infanticide risk is reduced by isolation. However, for wild boars in captivity, small enclosure sizes limit such preventive strategies, possibly making the trait maladaptive as the threat of conspecifics remains, potentially reducing maternal success and fitness. We suggest stricter regulation of wild boars' enclosures to ensure better animal welfare standards supporting behavioural needs.

Cloud technologies have advanced rapidly in the last decade, enabling a wide range of services through various cloud service providers. These advancements have been adopted and leveraged by modern applications, influencing their functionality and development processes. Meanwhile, food waste remains a significant environmental issue, contributing to 8% of global greenhouse gas emissions, with households being the main contributor. This thesis explores how cloud-native applications can reduce food waste through smart inventory management and timed notification systems. A review of the recent literature reveals a limited number of comparative studies regarding cloud-native architectures, with most research focusing on individual architectures. This thesis presents a literature review that summarizes and compares different cloud-native architectures in terms of performance, scalability, and cost. The findings of the literature review serve as a foundation for selecting an appropriate architecture to implement a food waste reduction application. The results show trade-offs, benefits, and weaknesses between the different architectures and that choosing a suitable architecture depends on the scale, workload, traffic, and features of the application. In the case of the food waste reduction application, a combination of a serverless and event-driven architecture proved most suitable, as notifications are inherently event-driven and irregular workloads may occur, therefore benefiting from the automatic scaling of a serverless architecture.

Fact-checking labels are widely used on social media to combat misinformation; how-ever, their effectiveness remains debated. Research has shown that factors such as label coverage, trust, and confirmation bias determine their effectiveness. This thesis uses a multi-agent Active Inference model to investigate how these factors affect the opinion dynamics in a social network. The model simulates agents updating beliefs and actions based on Bayesian principles and expected free energy minimization, with warning labels in-troduced as a non-social observational signal. Through systematic parameter sweeps, theresults show that increased trust (κ) in the warning labels consistently increases label effectiveness in reducing misinformation. Increased warning label coverage (ptrigger) has a weaker, non-linear effect. Furthermore, epistemic confirmation bias (γ) significantly influences belief dynamics. Finally, the results show that introducing warning labels did not have any significant effect on the polarization level in the network. While conclusions about real-world phenomena are difficult to draw due to simplistic modeling assumptions, these findings highlight the critical need for future research into how psychological factors and cognitive processes influence global opinion dynamics and the efficacy of misinformation interventions.

In the Swedish welfare state municipalities are central actors responsible for ensuring that both public and private providers meet the requirements of the legislation and politically decided goals. On behalf of municipalities many private actors today operate homes for care or accommodation (HVB) for children and young people, which places high demands on the municipalities' monitoring process and auditing. According to the law, municipalities have a clear mandate to carry out systematic follow-ups to ensure good quality in these activities. Despite this, the supervisory authority IVO's reports show serious shortcomings in the quality of care within HVB, where abuse and threats occur, and that important routines such as risk analyses and documentation of serious incidents are often missing. Due to this background, this study aims to examine how municipalities carry out follow-ups of private HVB activities. The study is based on a qualitative case study of four municipalities, Finspång, Norrköping, Mjölby and Huddinge. The analysis is based on theories of governance (network-based steering) and New Public Management. The results illustrate that municipalities have structures for monitoring at both individual and operational levels, but that there is variation in the division of responsibilities, documentation and methodology. The municipalities collaborate internally with the staff and externally with other municipalities and authorities. The challenges are mainly related to lack of information due to strict confidentiality rules. However, there are opportunities to improve the monitoring process through increased collaboration, national governance and more lenient confidentiality rules.

Group work assessment is described by teachers as challenging, especially assessing individual students’ knowledge developed in group work (i.e. individual group work assessment) since it entails a procedure of discerning each student’s knowledge from the group’s collective process. The aim of this study is to increase knowledge of how upper secondary teachers’ actions enable or hinder their collection of evidence for individual group work assessment of students. Particularly, the study investigates how individual oral cross-group presentations can be used to assess students’ individual knowledge developed in group work. Data consists of 23 video recordings from upper secondary teachers’ assessment of oral presentations in cross-groups followed by six interviews with the participating teachers. Data has been analysed using reflexive thematic analysis in which three themes were constructed: (a) Teachers’ frames that enable or hinder collection of evidence, (b) interactions that enable or hinder teachers’ collection of evidence, and (c) students’ behaviours that hinder collection of evidence. The results illustrate the importance of interaction by implementing the method of cross-group presentations by being active as a teacher, asking questions, and giving reflections. Interaction may enable reliable evidence that goes beyond students’ boundness to manuscripts. Potential hinders for teachers to collect evidence of students’ individual knowledge using cross-group presentations are aspects such as having enough time for presentations and interactions to enable sufficient evidence or students’ nervousness and silence that may hinder students from demonstrating their knowledge.

This thesis presents a model for estimating worst-case end-to-end latency in 5G vehicular offloading scenarios using Deterministic Network Calculus (DNC). By decomposing the 5G network into functional layers and service components in the Radio Access Network (RAN) and in the Core Network, the work defines arrival and service curves that model per-layer delay contributions under deployment-specific conditions.

Three representative scenarios are analyzed: (1) MEC-based edge offloading near the Core edge (MEC@CN), (2) centralized offloading via a long-haul core and Internet path, and (3) ultra-low latency local breakout through a UPF at the gNB site (MEC@gNB). Each scenario is instantiated with realistic parameter values and compared against empirical and simulated results reported in existing literature.

The model captures how RAN dominates the delay budget in most cases and consistently identifies the RLC layer as the bottleneck due to its segmentation and reordering behavior. Despite its conservative nature, the DNC model provides valuable insights into architectural trade-offs and delay bounds for safety-critical vehicular applications. Limitations, including the difficulty of modeling mobility-triggered handovers and dynamic traffic patterns, are discussed. The work concludes with a critical discussion of the model's relevance, limitations, and opportunities for future extension toward hybrid, stochastic, and empirically tuned frameworks.

Det du nu läser är en guide tänkt att användas som ett stöd och en vägledning för att stödja och förbättra facklig partssamverkan i arbetsplatsers förnyelse och arbetsmiljöarbete vid snabba förändringar i verksamheter. Den syftar till att stödja ledare och medarbetare i att skapa förändringsberedskap och hållbar utveckling i organisationer när omständigheter snabbt förändras.

Guiden bygger på resultat från flera forskningsprojekt som studerat möjligheter och utmaningar när organisationer utmanas av kriser och snabb utvecklingstakt.

En viktig del av guiden är att belysa hur partssamverkan förändras under krissituationer, baserat på konkreta exempel från COVID-19 pandemin. Detta är särskilt viktigt eftersom oväntade situationer såsom kriser stör normala arbetssätt och rutiner. Nya problem uppstår och det ställs nya krav på arbetet och förutsättningar förändras på arbetsplatser. Samtidigt uppstår nya situationer som skapar potential för lärande och förnyelseförmåga.

Guiden innehåller scenarier som illustrerar förändrade förutsättningar och kan användas som ett dialogverktyg med diskussionsfrågor på arbetsplatser för att förbereda sig för oväntade situationer.

Guiden vänder sig i första hand till ledare och medarbetare som arbetar partsgemensamt med verksamhetsutveckling, förbättringsarbete och arbetsmiljöarbete.

Guiden kan ses som en palett av scenarier med utmaningar och angreppssätt som underlag för diskussion i syfte att ta fram egna, skräddarsydda arbetssätt. Använd den som inspiration och hjälpmedel för att utveckla det egna lokala förbättringsarbetet.

A large part of the total response time in case of an emergency is the travel time between the location where the emergency vehicle is stationed and the emergency location. Having a reliable estimate of travel time will give good conditions for the planning of emergency calls, which in turn can help to reduce total response time and reduce operating costs. This thesis investigates what factors influence emergency vehicle travel time using historical vehicle data and publicly available information such as road characteristics and weather. The vehicle position data available for this thesis span across all regions of Sweden. The positions were made into routes that were map matched to the existing road network from the national road database. An automatic route validation algorithm was implemented to remove poorly map matched routes. Routes were given a variety of properties describing them, for example, time of day, average speed limit, and precipitation. With the routes and their properties, a variety of speed estimation models were developed using methods such as linear regression and decision trees with different variable selections, which were then used for travel time estimation. The models were evaluated with mean absolute percentage error (MAPE) and root mean squared error (RMSE). A baseline model consisting only of the average speed limit was used for reference, the performance was 21.82% MAPE and 202.07 seconds RMSE with a decision tree. The thesis concluded that some of the most important variables for emergency vehicle travel time estimation were total distance, average speed limit, and response status. One of the best-performing models included a decision tree with variables that included total distance, average speed limit, hour of day, response status, visibility, and more, which had MAPE 16.21% and RMSE 181.81 seconds. A regression-based model with only four input variables in use with interaction terms and variable transformations also showed a relatively high prediction accuracy of 17.40% MAPE and 187.65 seconds RMSE.

This study investigates the usability and functionality of playlist management features within mobile music streaming platforms, focusing on Spotify, Apple Music, and SoundCloud. While playlists are a core component of user interaction with streaming services, limited research has examined how users engage with these features from an interface design perspective. The research adopts a Research through Design (RtD) approach, wherein Design Thinking serves as a guiding method for the design process. By combining a pilot survey, precedent analysis, design proposal, and user evaluation, the study aims to explore the relationship between design and functionality in playlists. The pilot survey identified playlists as a highly valued feature, guiding the analysis of the three selected platforms. A precedent analysis was conducted to compare each platform’s playlist interface and identify usability challenges related to playlist management. Based on the analysis, a design proposal was developed to address the identified limitations. Key improvements included a clearer visual hierarchy, enhanced user control, and improved visibility of the system. A second survey was conducted to evaluate the proposed design in comparison to Spotify’s current interface. The findings indicate that enhanced functionality alone is insufficient to improve the user experience if not paired with an intuitive and visually appealing design. The study is limited in sample size, lowering the amount of collected data and reducing the generalizability of the results. Despite these limitations, this study contributes to the field of Human-Computer Interaction by offering insights into playlist design and highlighting the importance of balancing usability, functionality, and aesthetic appeal for user experience design.   

The growing complexity of urban airspace due to increasing drone operations requires novel approaches to traffic management and coordination. This thesis investigates the role of the air traffic controller in future drone coordination with a focus on cognitive demands during conflict management in urban drone traffic. The study aims to identify the tasks performed by controllers, the cognitive processes involved, and how future Unmanned Traffic Management (UTM) systems can support human decision-making in such scenarios. A qualitative and abductive research approach was applied. Data were collected through semi-structured group interviews with experienced air traffic controllers using scenarios in the UTM City simulator. The data were analyzed through thematic analysis and further examined using Cognitive Task Analysis (CTA) and the Joint Control Framework (JCF). These methods enabled an in-depth mapping of tasks and cognitive levels activated during conflict resolution. The findings highlight several recurring challenges for drone coordinators, including maintaining situational awareness, prioritizing between operations, and managing conflicting airspace demands. The analysis identified high cognitive load particularly at the “implementation” and “frame” levels of the JCF model. The results also suggest that future UTM systems should provide timely information, clear visualizations of airspace conflicts, and adaptive support for decision-making to avoid cognitive overload and Automation Surprise. This study contributes to the design of human-centered UTM systems by offering insights into the human role in future drone traffic management.

Urban Air Mobility (UAM) necessitates management methods beyond traditional Air Traffic Management (ATM), to ensure safe and efficient airspace in urban areas. This new approach is termed Unmanned aircraft systems Traffic Management (UTM). However, it has not emerged without challenges. A key issue in this shift is understanding how groundbased events, both scheduled and unscheduled, affect decision-making in UAS Traffic Controllers (UTCOs). This study aims to identify which ground-based constraints are influencing UTM and how information about these constraints should be managed within a future UTM database. To achieve this, data were collected through scenario-centered workshops and semi-structured interviews with air traffic controllers and police representatives. The findings were analyzed through the Joint Control Framework (JCF), particularly the Levels of Autonomy in Cognitive Control (LACC), to understand how ground-based information is integrated into UTM. The results indicate that not all events are equally important for UTCOs. Instead, the informational value depends on context, event type, and operational complexity. Informational requirements for a future database include data about time, location, stakeholders, restrictions, and mission type. This structured data could constitute a foundation to visualize information for UTCOs, and thereby support their decision-making process. The study contributes to the development of socially sustainable UAM by highlighting the need for selective and contextualized data management in UTM systems.

High-performance computing (HPC) has expanded beyond traditional on-premise systems, increasing the need to secure sensitive data and proprietary algorithms. Confidential Computing addresses this need by securing data in use through hardware-based Trusted Execution Environments (TEEs). Combining HPC with Confidential Computing can facilitate broader and more secure access to HPC resources, particularly in cloud environments. However, the additional confidentiality added by Confidential Computing comes at a performance cost.

This thesis extends previous research on the performance impact of AMD Secure Encrypted Virtualization-Secure Nested Paging (SEV-SNP) on HPC workloads. It provides new benchmarking results for workloads utilizing Message Passing Interface (MPI) and explores strategies to mitigate the performance overhead introduced by AMD SEV-SNP.

The results show that AMD SEV-SNP's baseline overhead can reach up to 13%. Profiling reveals decreased translation lookaside buffer (TLB) utilization, increased cache misses, and both higher frequency and longer resolve time for VMEXIT events. Optimization strategies such as the use of huge pages and paravirtualization demonstrate potential methods for reducing this overhead and improving performance.

This thesis explores the role and potential of rapid prototyping as a tool in the product developmentprocess. Through a combination of literature review, interviews, and a case study conducted incollaboration with Saab Aeronautics, the thesis addresses three main research questions: (1) In what wayis rapid prototyping utilized during the product development process? (2) How can rapid prototyping beimplemented when performing a product development project? (3) How can rapid prototyping beintegrated into Saab’s currently used product development methodology?

The theoretical study examines traditional product development models together with the usage of rapidprototyping methodologies. It discusses the benefits and drawbacks of rapid prototyping, such asincreased iteration speed, reduced development time, enhanced design flexibility, and limitations relatedto mechanical performance and material constraints.

A practical case study was conducted to evaluate the implementation of rapid prototyping in a real-worldscenario. The case study involved the development of a deployment mechanism for releasing a firstperson view drone from an unmanned aerial vehicle. Multiple design iterations were carried out using 3Dprinting and laser cutting to rapidly develop, test, and refine prototypes. The process emphasized earlystage concept evaluation, mechanical testing, and system integration. The results demonstrated thatrapid prototyping contributed to speed and efficiency of design iterations while enabling evaluation ofconcepts at an early stage in development.

Based on insights gained from the case study and empirical interviews with Saab personnel, the thesisproposes an approach of integrating rapid prototyping into Saab’s product development process. Thisapproach emphasizes the strategic use of rapid prototyping in early design phases to validate criticalfunctions and interfaces, enabling Saab to meet increasing demands for faster and more agiledevelopment cycles. The study concludes that while rapid prototyping is not a replacement for traditionalmethods, it is a valuable complement that can enhance design quality and responsiveness when appliedsystematically within a structured development process.

This master’s thesis presents the development of a lightweight and manufacturable plastic expansion tank foran off-highway vehicle application, aiming to replace the current welded stainless steel design. The existing metal tank design suffers from fatigue-related weld failures and geometric limitations due to manufacturing constraints. To address these issues, the project investigates suitable plastic materials and manufacturing methods and develops a new design tailored to the operational and structural requirements specified by theoff-highway vehicle manufacturer (OHVM).The methodology follows a structured product development process using the double-diamond model. Initial stages involved unstructured interviews, customer requirement gathering, and the creation of a detailed specification of requirements. Concept generation was supported by mind mapping and braindrawing techniques. Material exploration was conducted using the Ashby method in combination with Ansys Granta EduPack, while manufacturing methods were evaluated through a weighted concept selection matrix. Iterative design development was carried out in CAD, followed by structural validation using Finite Element Method simulations. Selective Laser Sintering was ultimately selected as the most suitable manufacturing method, with PA2200 (a PA12-based material) chosen for its mechanical properties and compatibility. The final design reduced the tank volume from 25 to approximately 14 liters, achieving significant weight savings while meeting mechanical and functional performance targets. In addition, the thesis proposes a set of design guidelines to facilitate future development of plastic tanks at the OHVM.The result is a robust, lightweight expansion tank concept with practical design knowledge applicable to future product developments at the OHVM.

This thesis investigates the development of a flexible and interactive design configurator using NVIDIA Omniverse, with a focus on modular design integration, usability, and simulation validation. The study explores the platform's capabilities in building customizable 3D configurations through Python scripting and the Universal Scene Description (USD) format. Two distinct configuration systems were developed: one for train components and another for fixtures. These systems demonstrate the adaptability of a modular codebase and user interface design within Omniverse.

The research further evaluates Omniverse’s physics simulation tools by implementing a three-point bending test. While the visual representation of simulations is effective, the platform falls short in delivering scientifically accurate results. These findings suggest that Omniverse is more appropriate for visual prototyping and scene assembly than for engineering-level analysis or detailed design automation.

Despite certain limitations, such as the lack of parametric modeling and precise assembly tools, the project concludes that Omniverse is well-suited for complex, modular visualization tasks and collaborative design environments. The thesis delivers not only configurators but also a structured development workflow and a manual to support future users in similar applications.

This master's thesis was conducted at Linköping University in collaboration with a Swedish photography and cinematic light developing company. This thesis investigates the development of Ingress Protection (IP) rated products tailored for the film industry, with a focus on enhancing sealing solutions for specified common critical interfaces. It explores the application of Rapid Validity Testing (RVT) as a practical and efficient tool to support the design and validation of these solutions. A mixed methods approach, including literature review, interviews, industry benchmarking and hands on testing was employed to identify current challenges and best practices. Custom test rigs were designed for evaluating dust and water ingress, enabling real world RVT applications that revealed optimal sealing strategies. The research highlights RVT's value in scenarios where datasheet information is insufficient or where high risk design concepts would typically be dismissed. The findings demonstrate that RVT could accelerate decision making, promote innovation, and enhance reliability in product development. The thesis concludes with actionable recommendations for integrating RVT into Company X’s workflow, including optimized cable entry designs, proposed sealing solutions for future products and general guideline for designing IP rated products.

SAAB currently uses sandwich structures in the construction of aircraft rudders. While the existing method performs well, it presents challenges in terms of weight, cost, and producibility. With the rise of additive manufacturing (AM), this thesis investigates how a generic side rudder, lighter or equal in weight to today’s design, can be produced using 3D printing while maintaining structural performance.

nTopology, a software tailored for AM, was used to evaluate a wide range of lattice unit cell types through simulations and polymer SLS printing. Several optimization techniques were applied to both the internal lattice and the outer shell. The most promising designs were 3D printed in metal and tested under simulated flight loads.

Gyroid and TPMS Diamond were identified as the best-performing structures. The most effective optimization strategy was Field Optimization, which adjusts geometry based on simulation data. The Diamond lattice proved especially suitable due to its symmetry and powder removal capabilities.

Testing showed that actual failure loads were significantly higher than predicted, mainly due to limitations in linear simulations that did not capture plastic deformation or stress redistribution. Smaller cells improved buckling resistance and strength. Despite some manufacturing imperfections, optimized prototypes met performance expectations.

This work demonstrates the feasibility of using AM for aerospace sandwich structures and serves as a foundation for future work, including the possibility of printing entire rudder or wing sections as single parts, reducing assembly while slightly increasing cost.

A printed circuit board (PCB) mounted inside of a housing will experience more thermal strain when subjected to temperature compared to a non-mounted PCBs. This is due to a mismatch of the coefficient of thermal expansion (CTE) between the aluminium housing and FR-4 used in the PCB. This is a common problem in the automotive industry as the temperature intervals the PCB is expected to endure are large. In this report, f inite element analysis was used for simulating how the strain induced by CTE-mismatch spreads in the PCB relative to its temperature cycle. The concept of using slots were investigated further as a way to reduce the strains. Different slot designs were analysed using multi-disciplinary design optimization and then simulated to verify their effectiveness. It was discovered that the optimization algorithm favours slots that separates the PCB corner as much as possible from the rest of the PCB. Each slot was then analysed further, by incorporating each design into the created finite element model, and using different metrics, determine which slot preforms the best and why. The conclusions were that optimization could be a useful tool to investigate different slot designs, where some design parameters were favoured more than others. Furthermore, the use of slots indicated that strain can be significantly reduced, upwards of 27% near corner screw holes, depending on measurement.

This master’s thesis was conducted at Linköping University in collaboration with Toyota Material Handling Europe (TMHE), at their Research and Innovation (R&I) department, with the aim of developing innovative design solutions to improve safety for operators using motorized stackers and pallet trucks. The primary aim of this thesis was to gain a deeper understanding of the most common injuries affecting forklift operators, as well as how these injuries occur. The aim was achieved by addressing the following research questions: What are the most common injuries and injury risks for forklift operators? and What design solutions for safety systems on motorized stackers and pallet trucks can reduce the risk of accidents and/or mitigate the consequences in the event of a potential accident?.

The study found that foot injuries are the most common, followed by injuries to the hands, legs, shoulders, back, and head. Repetitive strain injuries in the neck, shoulders and back are also prevalent, primarily due to monotonous tasks and static postures. Frequent accident types include collisions, falling loads, falls from heights and crush injuries. These incidents are often caused by insufficient maintenance, inadequate training, loss of control, or slip and trip incidents. Moreover, the underreporting of minor incidents results in missed warning signs, which hinders preventive action and increases the risk of more severe accidents.

The thesis also presents design solutions for motorized stackers and pallet trucks, emphasizing that safety solutions must be complemented by operator training, behavioral awareness, and a strong safety culture. The phenomenon of risk compensation further underscores the need for ongoing engagement and consistent safety practices. Furthermore, the study highlights that safety and productivity are not mutually exclusive; rather, a well-implemented safety framework contributes positively to long-term efficiency and profitability.

As a practical outcome, the project resulted in the development of a collision warning system utilizing haptic technology to improve the safety of forklift operators. The system alerts operators through vibrations in the tiller arm with handle and foldable platform, making it effective in noisy and visually distracting environments. Haptic feedback helps reduce cognitive load, improves spatial awareness, and acts as a nudge toward safer behaviour. Various vibration frequencies, amplitudes and pulse patterns signalling different levels of urgency were tested in the user test. In the design of the vibrations, ergonomic factors, glove use, and user differences were considered. This is an aspect that should be considered in any potential future implementation. It is also important to acknowledge that forklift and material handling operations vary significantly, requiring the vibrations to be tailored to the specific needs of each operation. The technology is novel in the forklift industry and shows strong potential for broader applications across other forklifts and use cases.

At Linköping University, students studying to become engineers in mechanical engineering, construction technology, have a course called "Construction technology - project work", with the course codeTMMI53. The students there have an assignment - to design and manufacture a radio-controlledvehicle that will participate in a competition. For the competition, a device is used to start thevehicles simultaneously, called starting device. The starting device is not visually appealing and itsfunctions have room for improvement. Therefore, improvement possibilities of the starting devicewere investigated in the thesis.

The aim of the thesis was to improve the starting device that would be more impressive for thespectators of the competition and more user-friendly for the students. The goal of the thesis was todesign an improved starting device in a CAD program and then manufacture it in real life, whereit would work as it was intended in the beginning.

The thesis was based on a combination of product development methods from Ulrich & Eppingerand Liedholm. First, a concept was chosen that helped to get an idea of how the improved startingdevice would be constructed. After that, the starting device was divided into several different unitsand designed with respect to the parts being 3D printed.

The result of the thesis was a starting device consisting of four different units. This starting devicewas able to start the vehicles wirelessly and had several other functions that eased and improvedthe experience. 

VTI, the Swedish National Road and Transport Research Institute, is an independent and internationally recognized research institute within the transport sector. Its primary mission is to conduct research and development in infrastructure, traffic, and transport to continuously improve knowledge and contribute to achieving Sweden’s transport policy goals. One of the research areas focuses on how standing passengers in public transportation fall and the injuries they may sustain in such events.

This bachelor’s thesis aims to develop a concept for a test device that enables safe fall and balance recovery tests for standing passengers in public transportation on VTI’s existing crash test track. The background of the project lies in the need for experimental data to calibrate a simulation model used to predict passenger injuries resulting from falls caused by perturbations in public transportation, particularly during sudden braking or acceleration.

The work was carried out using established product development methods and included needs analysis, concept generation, and validation through failure modes and effects analysis. Several concepts were developed and evaluated with a focus on safety, realism, and practical feasibility. The most promising solutions enable natural fall movements with minimal risk of injury.

The result is a well-developed concept that can serve as a foundation for future development and realization of a test device. The concept includes systems that allow both fall and balance testing, as well as several features enabling these tests to be conducted on the crash track. These features ensure that maximum allowable speed and acceleration limits are not exceeded and include the development of an extension for an existing carriage to facilitate use within the crash test track. In addition to visualizations of the concept’s various solutions, a failure modes and effects analysis is also presented as the result.

The project aims to create a new casting magazine for one of the presses at Hydro Extrusion SwedenAB in Finspång. The purpose is to create a more efficient and safer workplace, and the goal is todevelop an overall concpet for the casting handling as well as an overall layout, then go into detailon casting scrap magazine. The concept development was carried out using classical constructionmethodology, after which the winning concept for the casting scrap magazine was modeled usingCAD software. Parts of the CAD model were then taken and placed into a FEM program tostudy various load cases to ensure the structure could handle the task. After that, manufacturingdocumentation for the casting scrap magazine was created.

This project, conducted on behalf of the Swedish Defence Research Agency, FOI, aims to investigate the feasibility of using lasers to neutralize buried explosive devices such as landmines and unexploded ordnance, UXO. The work combines a literature review with practical experiments in which a continuous CW laser and a Nd:YAG pulsed laser were tested on soil and sand as ground materials.

The results show that low-porosity soil can be effectively penetrated by laser, enabling the heating of a simulated mine to temperatures above the autoignition temperature of common explosives. In soil, tunnel and glass formation were observed, while sand proved more difficult to penetrate due to its high porosity and poor thermal conductivity. The combination of CW and pulsed lasers did not yield any significant improvement compared to the CW laser alone.

The project demonstrates that laser-based mine clearance has potential but requires further development and optimization of laser power, beam profiles, and adaptation to different soil types in order to become a practical solution in the field.

Windshield stone-chips are a common problem for drivers, potentially causing accidents by impairing visibility and contributing to environmental damage if not treated properly. This thesis investigates whether stone-chips can be detected using microphones mounted inside a car, and how accurately their impact positions can be estimated. To this end, 40 stone-chip audio files were recorded while throwing gravel at a moving car, and over 11 hours of robustness data during ordinary driving conditions were collected. Based on this dataset, a signal processing pipeline for simultaneous detection and localization is proposed. The pipeline consists of an adaptive energy detector based on a Kalman filter (KF), a sound source localization step utilizing a time difference of arrival (TDOA)-based sensor fusion framework, and a geometrical model to convert the source position estimate into a binary decision. The proposed method demonstrates promising performance on the gathered data, achieving an F1 score of 0.861 for detection and root mean squared errors (RMSEs) of 1–4 dm for localization. A sensitivity analysis indicates that decent performance can be expected even under more challenging conditions.

Transferring knowledge in an organization is argued to be the basis for firms to have a competitive advantage. Even if knowledge transfer can lead to significant performance improvements, achieving successful knowledge transfer remains challenging. There is a clear gap in understanding what barriers and enablers influence knowledge transfer in an organization with geographically dispersed projects. Therefore, this thesis aims to address this gap through a single case study conducted at the construction and project development company Skanska Sweden AB, in the region Hus Norr. In this region, large geographical distances separate projects. The case study is conducted to be able to answer the research question of this study: \textit{What barriers and enablers can influence knowledge transfer in organizations with geographically dispersed projects?}

This study adopts a qualitative research approach, based on a single case study. The theoretical framework led to a synthesis and a list of barriers and enablers to knowledge transfer in geographically dispersed projects. This list was used as a model for analyzing the empirical data. Data was collected through multiple methods to ensure triangulation. Semi-structured interviews, observations, and archival research were all conducted.

The findings of this thesis resulted in a framework that extends the list developed based on the theoretical framework with enablers and barriers to knowledge transfer for organizations with geographically distributed projects. The framework includes barriers and enablers divided into the factors: \textit{Knowledge Mechanisms, Organizational Factors, Resource Factors, Individual Psychological Factors, Communication Factors, and Relationship Factors}. 

This study offers both theoretical and practical contributions, as the framework presents a novel approach to addressing knowledge transfer in geographically dispersed PBOs. It extends existing research by providing new insights into how geographical distance affects knowledge transfer in dispersed projects and by identifying additional barriers and enablers. By integrating prior research with empirical findings into a unified framework, the study offers a comprehensive overview of the factors that influence effective knowledge transfer. The framework also enables organizations to critically assess their current practices and systematically identify areas for improvement.

This thesis explores the potential of reducing travel time through sophisticated routing methods utilizing traffic speed forecasting models. The current solution used by Triona relies on a naive static model, which assumes that traffic always flows at the speed limit for all roads. While this approach yields reasonable results, it does not account for spatial or temporal variations in traffic conditions, leaving room for improvement. To address this, we develop and evaluate more advanced forecasting models including statistical approaches such as autoregressive integrated moving average and machine learning models such as LSTM and traffic graph convolutional LSTM. The methodology involves collecting historic traffic data from the Stockholm metropolitan area, preprocessing the data, adapting traffic speed forecasting models, implementing routing algorithms and evaluating generated routes. The routing algorithms, based on a modified Dijkstra's algorithm, solve the time-dependent shortest path and time-dependent traveling salesman problem. The evaluation shows that utilizing the LSTM model instead of the naive static model for routing reduces the difference from optimal routing from 4.37% to 1.18% for time-dependent shortest paths and from 5.40% to 1.52% for time-dependent traveling salesman problems. This thesis contributes a framework for applying and evaluating traffic speed forecasting methods to real traffic data, highlighting the potential increase in transportation efficiency through intelligent routing.

Selecting suitable software components in complex domains such as healthcare requires

careful evaluation based on multiple criteria. The study focuses on comparing two multi-

criteria decision-making methods, the Analytic Hierarchy Process (AHP) and the Pugh

matrix, to determine which is the most effective and suitable for guiding selection of a

subcomponent in a professional software development context. The study focuses on the

case of prioritizing web-based text editors within medical reporting, in collaboration with

Sectra Imaging IT Solutions AB. Seven editors were evaluated using 25 different criteria.

The methodology involved gathering and prioritizing evaluation criteria through semi-

structured interviews with Sectra employees and a survey. Based on these criteria, a selec-

tion of web-based text editors was identified and systematically tested in a controlled test

environment developed using React and TypeScript. The results from the tests, combined

with survey data, were then used to evaluate the editors with AHP, along with the basic

version of the Pugh matrix, and the Pugh matrix with weighted criteria.

Both AHP and the Pugh matrix were applied independently using the same dataset, allow-

ing for a direct comparison of their methodological strengths and limitations. The results

from AHP and the weighted Pugh matrix were consistent, identifying TipTap (commercial

version) and Lexical as the most suitable editors for radiological reporting within Sectra’s

products. The unweighted Pugh matrix also pointed to TipTap (commercial version) as

the best option, but its results were less nuanced. All three methods consistently identified

TinyMCE and Slate as the least suitable alternatives, primarily due to performance issues,

licensing restrictions, and implementation complexity.

The comparison of methods showed that AHP is a more structured and detailed approach,

particularly useful for scenarios involving numerous criteria with varying importance. The

Pugh matrix is simpler and faster to use, but the unweighted version lacks sensitivity to

prioritized criteria.

The study proposes a beneficial combination of the two methods: utilizing the Pugh mat-

rix for an initial screening to eliminate less suitable options, followed by AHP for a more

detailed comparison of the highest-ranked alternatives. This hybrid method can optim-

ize decision-making efficiency while ensuring high decision quality. Finally, the study

provides a framework for software component evaluation that can be applied to similar

professional contexts.

Modern CI/CD systems produce vast streams of events that reflect the state and progression of software development processes. Aggregating these events is essential for enabling automation and traceability. In this context, aggregation refers to the process of detecting and grouping sequences of events into higher-level constructs based on predefined rules. This thesis investigates alternative mechanisms for event aggregation, with a focus on graph-based approaches within the Eiffel framework.

By representing events and their relationships as a property graph, our proposed system enables declarative specification of patterns and supports incremental detection using trigger-based mechanisms in graph databases. The work implements and evaluates multiple aggregation systems, including graph databases and a complex event processing engine, and compares them based on throughput and resource efficiency under high workloads, using historical Eiffel data.

The evaluation includes three different potential event aggregation systems: Neo4j, Memgraph, and Apache Flink. The results show that both Memgraph and Flink exhibit significant limitations in terms of performance and functionality for the use case, and are ultimately deemed unsuitable. Neo4j, on the other hand, provide a more promising foundation for implementing graph-based pattern matching. The findings show that Neo4j enables flexible event aggregation whilst simplifying rule definition. However, performance degrades significantly when the number of active triggers increase. Addressing this scalability limitation remains an open challenge.

Inflation and currency risks constitute two major threats to value stability in long-term investments. As traditional assets are increasingly challenged and interest in alternative investments grows, the question arises: can Bitcoin play a role in this? This study examines whether Bitcoin can serve as an effective hedge against inflation and currency risks within the framework of the Swedish pension system. Using regression analyses, VAR models and portfolio optimizations, Bitcoin’s role across different market environments is evaluated. The results show that, despite its reputation as "digital gold," Bitcoin does not function as a reliable hedge. Instead, Bitcoin is characterized by high volatility and speculative behavior, creating significant risks for long-term investors. At the same time, the findings indicate that a small allocation to Bitcoin can improve a portfolio’s return, but only under specific market conditions and if the associated risk is accepted. The study also highlights the legal and practical barriers that must be overcome before Bitcoin can naturally be incorporated into pension savings. Bitcoin may be exciting, but it falls short as a stable hedge, volatility remains high, and the risks substantial.

The European Union’s Emission Trading System (EU ETS) is the EU’s primary decarbonisation instrument. The carbon emissions, referred to as European Union Allowances (EUA), are auctioned and subsequently traded between firms on a secondary market. We analyse how EUA prices react to fundamental (oil, gas, coal, economic activity, electricity) and uncertainty-related (Economic Policy Uncertainty, Climate Policy Uncertainty, Oil Price Uncertainty, Energy-related Uncertainty) variables, and whether there are discernible differences between the third (2012–2020) and fourth (2021–2025) phases. To examine these relationships, the study employed a two-variable Vector Autoregression (VAR) model and Impulse Response Function (IRF) to examine the relationships. Our findings indicate that the price of gas had a significant positive impact on the price of EUAs, while the price of coal had an insignificant effect. This suggests that the relative cost of emissions plays a crucial role in fuel switching an occurrence where companies transition between coal and gas. Oil price shocks had a positive impact on EUA prices during the third phase, but a negative effect during the fourth. We attribute this shift to the inclusion of maritime and transport sector in the fourth phase, and the reduction of free allowances for the aviation sector. These sectors rely heavily on oil, which strengthened the direct link between oil prices and EUA prices. Our findings also demonstrate that uncertainty variables can significantly affect EUA prices. These findings have important implications for policymakers seeking to design an effective system to support green transitions, as well as for firms and investors aiming to mitigate risks in the carbon market.

This study examines the relationship between macroeconomic factors and food inflation in Sweden, with a particular focus on how different shocks affect the producer and consumer price indices for food (PPI-L and CPI-L). Using a structural VAR-model, the effects of money supply, interest rates, exchange rates, energy shortages, and unemployment on food prices is studied, with the sample period 2000–2024, based on monthly data. The results show that exchange rate fluctuations have immediate effects on both PPI-L and CPI-L, while energy shortages affect producer prices in the longer term and subsequently consumer prices. Monetary policy variables have more limited effects, suggesting that traditional tools such as interest rate adjustments have low accuracy in this sector. The findings indicate that exchange rate changes and energy shortages are the primary drivers of food inflation, while monetary policy tools have limited impact. These insights have important implications for economic policy, as traditional rate hikes may be ineffective against cost driven inflation in the food sector. The study therefore suggests that inflation management could benefit from include measures for currency stability, energy investment, and strengthened food supply. By highlighting these connections, this thesis contributes to a deeper understanding of how food prices can be managed in practice, thereby reinforcing Swedish inflation policy in a globally uncertain time.

The aim of this thesis has been to examine whether the labor market initiative Arbetshoppet can be considered cost-beneficial for society. The project was implemented in seven municipalities in Östergötland and aimed to facilitate the entry into the labour market for individuals who were far from employment, with a focus on the health and social care sector. To assess whether the project was cost-beneficial for society a cost-benefit analysis (CBA) was implemented. In the analysis the benefits were quantified based on the number of participants who transitioned to employment or education, while qualitive outcomes such as improved integration and mental well-being were reported but not assigned monetary values. Sensitivity analyses were carried out to account for uncertainties in assumptions, including employment and time horizon. The thesis examines whether Arbetshoppet was cost-beneficial for society by considering both monetised outcomes and effects that are difficult to quantify. It also addresses limitations in evaluating labor market initiatives using cost-benefit analysis and discusses the finding in relation to CBA and the project’s stated objectives. The result in the baseline scenario indicate that Arbetshoppet was not economically profitablewithin a five-year period. The project may have a positive net present value if, for instance, theanalysis extends over a longer time frame or if the value of work contributions is increased. However, the result remains uncertain, as several variables has not been assigned monetary value.

The Swedish pharmacy market has undergone significant changes during the 2000s. It transitioned from a state-owned monopoly to a market open to competition. Today, the competitive landscape is shaped not only by a larger number of physical actors but also by a growing presence of e-commerce. Access to pharmacies varies geographically, with differences in pharmacy density between rural areas and bigger cities. This raises questions about how competition is manifested in practice, especially regarding pricing, product range and the impact on consumers.  The aim of this study is to examine the state of competition in the pharmacy market. To gain a deeper understanding, observations were conducted at pharmacies in Linköping and Åtvidaberg, representing both an urban and a rural area. Online pharmacy actors were also included to explore how their presence affects market competition. A strategic selection of pharmacies and products was made to ensure relevance. The theoretical framework is based on economic models and concepts related to competition and market structures, which served as the foundation for the analysis of the results. The observations yielded valuable results. It was found that online pharmacies consistently offered the lowest prices on the market. The results also indicated a degree of centralized pricing among the actors, particularly within physical pharmacies. Furthermore, the study showed that the rural pharmacy in Åtvidaberg, despite holding a local monopoly, did not demonstrate monopolistic behavior regarding pricing or product assortment. The study also revealed certain limitations in the range of products available at both physical and online pharmacies. The study shows that the Swedish pharmacy market, despite its high concentration and limited number of actors, displays clear signs of effective competition, especially through pricing. The market structure aligns well with the theory of Bertrand oligopoly, where a few firms offering homogeneous products compete primarily on price. The results suggest that individual actors possess limited market power, which helps keep prices low even in geographic areas with a local monopoly. Altogether, this indicates that the competition in practice functions relatively well, despite market concentration and the presence of structural entry barriers.  

This study evaluates the integration of two data-driven, time-sliced OD-matrices, representing the morning and afternoon peak hours, into an existing 24-hour-based macroscopic traffic model used for traffic planning in the municipality of Norrköping. The purpose is to examine how GPS data and traffic measurements can be utilized for calibration and validation, and how simulations using time-sliced OD-matrices compare to those using a traditional 24-hour OD-matrix estimation. The background of the study lies in recent advancements in the collection of mobility data through the mobile network and GPS, as explored in the CODE PROBE and CODE FLOW projects. The work is also placed within the context of the project Störningsfri Stad, which aims to support strategic traffic and logistics planning during urban development and large-scale construction projects such as the relocation of Norrköping’s central station. The methodology follows a process involving calibration, validation, and analysis of simulation results using both types of OD-matrices. The analysis focuses on identifying differences in model output and potential impacts on decision making, particularly for peak hour traffic and in case study scenarios. The results show that time-sliced OD-matrices offer valuable additional perspectives by capturing temporal variations in travel demand that are not visible in daily aggregates. This enables a more detailed assessment of traffic impacts and supports improved strategic traffic planning. However, the study also identifies certain limitations in the time-sliced models, primarily related to the integration and calibration of the time-sliced OD-matrices. Although the time-sliced OD-matrices captured general travel patterns, they both overestimated and underestimated demand in specific areas, which in turn affected route choice realism during simulation. In several cases, the routes deviated from expected travel paths, revealing inconsistencies between the OD-matrix structure and the observed travel times. Although adjustments of the capacity and volume delay function (VDF) in the models improved travel time accuracy and flow alignment, some remaining discrepancies point to the model’s sensitivity to how the OD-matrices are constructed and how well they reflect the transport network characteristics. These issues, especially noticeable in case study scenarios with substantial traffic pressure during peak hours and potentially misclassified road segments for the analysis, highlight the need to refine OD-matrix estimation methods and broaden the scope of calibration in future work.

The first step to reduce greenhouse gas (GHG) emissions is to detect and track the emissions sources as well as measuring how efficient are the mitigation actions implemented. Thus, GHGs need to be monitored. This can be done either with large instruments that are very accurate and precise, but expensive and stationary, or it can be done with small sensors of lower cost and easier to carry and use for in situ measurements. The drawback of these small sensors is that they are less accurate and need periodic calibrations. For the latter, reference equipment such as gas mixing systems (GMSs) are used.

In this thesis a brand new GMS was calibrated using a gas chromatograph as a reference. This GMS will in turn be used to calibrate low-cost sensors used at TEMA M in research projects related to detect, monitor, and reduce GHG emissions. The original research questions were: (i) can the GMS deliver mixtures with less than 2 % error in concentration?; and (ii) can the GMS deliver mixtures with a relative standard deviation of less than 5 %?

It was found that the system could rarely deliver mixtures with less than 2 % error (which is the inherent error of its main components), but the relative standard deviation was found to be below 5 % for introduced concentrations higher than 12 ppm. Because of the higher errors found when mixing flows with large differences, a third research question appeared during the work: (iii) can higher accuracy results be achieved by exchanging t-connections for a turbulent mixer? The reason for this was that the t-connection, where the two gases get mixed, was thought to discriminate against the gas with significantly lower flow. This resulted in the fabrication and testing of what is commonly called a static mixer. The results of this thesis help to understand the capabilities of the GMS and show a possible path on how to further improve the GMS.

Bluetooth Low Energy (BLE) devices have become integral to modern wireless com munication, facilitating a wide range of applications in consumer electronics, healthcare, security, and beyond. Their capacity to broadcast signals presents significant opportunities for tracking and localization, which could be helpful in domains such as search and rescue operations. However, privacy mechanisms, particularly randomization of Media Access Control (MAC) addresses, pose substantial challenges to persistent device identification and tracking. This thesis explores methodologies for associating BLE measurements with specific devices and estimating their locations, despite the complexities introduced by privacy preserving techniques. By developing robust association and localization frameworks, this study aims to advance BLE-based tracking applications while addressing the inher ent trade-offs between utility and privacy. The methodological framework is empirical and based on BLE signal measurements collected through scanning equipment deployed in both controlled tests and outdoor field conditions. The process begins with identifying unique MAC addresses and extracting rel evant features. These features feed into an association algorithm that attempts to associate individual measurements with specific physical targets despite the address randomization. Alocalization algorithm is then used to estimate the position of each target by combining Received Signal Strength Indicator (RSSI) data with the known locations of the scanners. Both algorithms are validated against ground truth data using reference devices and RSSI f iltering. Association and localization are central to this tracking method: association ensures that fragmented or randomized measurements are correctly grouped per physical device, while localization estimates where each target was at a given time. The output of the methodisaspatiotemporal trace of each tracked device, providing a sequence of estimated positions that can aid in real-time tracking or retrospective analysis. Theassociation algorithm is capable of grouping signal observations from the same de vice, although its accuracy is affected by timing inconsistencies. Localization, based on sig nal strength data, generally performs well when scanners are spatially distributed but can suffer in certain geometric configurations. Adjustments in scanner placement and tempo ral processing show potential to improve association reliability and localization accuracy. While the approach is promising for static or semi-static scenarios, further adaptation is needed for use in dynamic, real-time search and rescue operations.

This study explores how psychological factors influence individual investment decisions in the stock market, with a particular focus on gender differences. A quantitative survey was conducted among university students to examine five key behavioral finance concepts: overconfidence, herding behavior, confirmation bias, risk aversion, and loss aversion. The results confirm that all these factors significantly affect investment behavior, and notable gender differences were observed. Men generally exhibit higher levels of overconfidence and lower risk aversion, while women tend to be more cautious and emotionally affected by losses. The study supports previous research but adds new insights, most notably that overconfidence increases with educational level, and that confirmation bias appears independent of gender. By integrating gender with variables such as investment experience and preferred investment form, the study presents a nuanced picture of how psychological mechanisms interact in financial decision-making. These findings enhance the understanding of investment psychology among young investors and highlight the importance of tailored financial advice and education. 

Introduction: Digitalisation is a central component of today's societal infrastructure. Auditing is no exception - there has been a shift from manual and traditional auditing to an increasingly digital approach. As digitalization progresses, challenges arise in complying with regulations, standards, and established practices. In line with these developments , it is important for auditors to broaden their knowledge on handling digital tools to ensure high-quality audits. Research on how digital tools are used in auditing, their impact on audit quality and the auditor´s work, as well as the challenges facing the profession, is limited. This thesis aims to contribute further knowledge regarding the implementation of digital tools and AI within the auditing profession.

Purpose: The purpose of this study is to investigate how auditors currently apply AI and other digital tools in the audit process, and how these affect audit quality.

Method: The paper is based on a qualitative research strategy in which semi-structured interviews were conducted to collect the empirical data.The analysis is carried out using a deductive approach with inductive elements.

Conclusion: The results of the thesis show that the audit process is undergoing a significant digital transformation. Empirical evidence indicates that digital tools are utilized throughout the entire audit process, with a particular emphasis on the planning and review stages. Digitalization and AI have positively influenced both the audit process and audit quality through increased standardization, efficiency, and accuracy. The paper also demonstrates that there are challenges, such as continued professional skepticism, technical understanding, and client knowledge.

Megagames have been used within a serious game context as tools to enhance learning. The megagame “Switching the current” (STC) is one such example, which has been designed by researchers collaborating from the Swedish universities Linköping University, Jönköping University and Högskolan i Skövde. The research team uses it as a platform to educate participants about the Swedish power grid, the involved stakeholders and the challenges involved with implementing a green transition. STC has been a multi-year project which has been iterated upon continuously. One important source for rating how effective a megagame has been and which can be used in guiding future iterations of the game, is the debriefing sessions. Due to the large number of participants in megagames these debriefings are done in smaller discussion groups, and as such it can be hard to make general summaries of the contents of these distributed debriefings. While this has been done, it is a time-consuming process which means that any insights gained will be had several days after a concluded game session. As such it has been impossible to give immediate feedback to participants, which could potentially improve the learning potential of the games. One idea, which this thesis explores, is to speed up the process of creating these summaries by using large language models (LLMs), an AI technology which can process language.

The study interviewed members of the STC research team about what importance the debriefings had for different stakeholders. Then an iterative process developed a program and prompt which could generate summaries which fit the criteria outlined in the interviews. As outlined by best practices in prompt engineering and when working with generative AI, it was important that the facilitators would be able to properly validate the contents of the debriefing summaries. Two summaries were created, one participant-oriented and the other oriented towards the game design team. To test the quality of the summaries a survey was sent out to people who had experience of facilitating STC.

It is important to note the limitations of the study, with a small number of participants and only looking at one specific megagame. It is also noteworthy that the program has not been tested in connection to an actual megagame session. However, the results of the study indicate that the summaries could be a useful addition to the facilitation of megagames and could enhance the learning of participants, as well as being a potent tool for the game design team in iterating upon the game.

This thesis analyzes the volatility behavior of two cryptocurrencies, Bitcoin (BTC) and Ethereum Classic (ETC), across three phases surrounding the COVID-19 pandemic: pre-pandemic, duringpandemic, and post-pandemic. We assess differences in return volatility and downside risk using GARCH (1,1) models and a modified Value-at-Risk (VaR) approach based on the CornishFisher expansion. We find that BTC, as a large-cap asset, displays more structured volatility patterns and stabilizes more quickly, whereas ETC, a small-cap coin, exhibits more erratic and sentiment-driven volatility. These differences are most pronounced during crisis conditions, where BTC may act as a volatility transmitter and ETC as a volatility amplifier. The findings support the hypothesis that market capitalization plays a key role in determining both persistence and systemic transmission of volatility. Offering practical insights for investors, risk managers, and policymakers navigating crypto-related risks.

Title: Can Repair Services be Revived in a Consumption-Driven Society? A Quantitative Study Examining the Relationship Between Individuals’ Attitudes Toward Fast Fashion and Their Willingness to Repair Clothes and/or Shoes.

Level: Bachelor’s Thesis in Business Administration, 15 ECTS

Date: 15 June 2025

Authors: Sara Karlsson and Kajsa Lindahl

Purpose: The purpose of this study is to investigate how individuals’ attitudes, subjective norms and perceived behavioral control regarding fast fashion influence their willingness to repair clothes and/or shoes. To explore this, the Theory of Planned Behavior (TPB) is applied.

Method: The study is based on a quantitative study using a web-based survey to collect data from Swedish consumers regarding fast fashion and repair services. The survey consists of statements rated on a seven-point Likert scale and includes items reflecting the three components of the Theory of Planned Behavior: attitudes, subjective norms, and perceived behavioral control. Additionally, the survey contains questions about Swedish consumers’ intention to consume fast fashion and use repair services, as well as how likely they are to engage in these behaviors within the next three months. The data has been analyzed using a regression analysis.

Conclusion: The results of the study indicate that the factor with the greatest influence on respondents´ willingness to repair clothes and/or shoes is their attitude toward the behavior. The three independent variables had varying effects on individuals’ willingness to engage in repair behaviors. A positive attitude toward fast fashion had a negative effect on both the intention and likelihood of repairing clothes and/or shoes, while it had a positive effect on the likelihood of purchasing fast fashion. Subjective norms showed that the more positively the individual's social environment viewed fast fashion, the greater the individual’s intention to repair clothes and/or shoes. However, this did not affect the actual likelihood of performing the repair behavior. Regarding the variable of perceived behavioral control, the study found a positive correlation indicating that individuals who perceive fast fashion as accessible, time-efficient, and affordable were more likely to purchase fast fashion within the next three months.

The Confederation of Swedish Enterprise’s annual ranking of Swedish municipalities’ business climates has become an influential tool in local strategic planning, despite recurring criticism. One key driver of the ranking’s impact is the extensive coverage it receives in the local press. This study examines how local newspapers report on the ranking and whether their coverage fulfils journalism’s democratic functions: informing citizens, scrutinising power, and facilitating public debate. The investigation draws on a content analysis of 570 articles from 2008, 2014, and 2024, complemented by theories of political communication and democratic ideals. The findings show that local media often relay the ranking with limited critical distance, meaning journalism acts more as an amplifier than as democracy’s watchdog. Concepts such as agenda-setting, priming, and hegemony are employed to demonstrate how the media help legitimise a narrow definition of what constitutes a “good” business climate. A normative assessment based on three models of democracy—elite, institutional, and deliberative—suggests that the media’s handling of the ranking falls short of realising its full democratic potential.

Diffusion models have emerged as a powerful class of generative models, achieving state-of-the-art performance in continuous data domains such as image synthesis and video generation. Their core mechanism involves a forward diffusion process thatgradually transforms structured data into a Gaussian-like distribution, followed by a learned reverse diffusion process that reconstructs the data. While this framework has proven effective for continuous modalities, its application to discrete data-particularly natural language-remains a challenging and active area of research. Key obstacles include the complexity of modeling discrete token dependencies and the lack of a naturally defined generation order.This thesis investigates the feasibility and performance of discrete diffusion models in the context of natural language generation. In particular, we examine the Discrete Denoising Diffusion Probabilistic Model (D3PM) and compare its performance against traditional autoregressive (AR) language models. To evaluate and compare the generative capacity of both models, we utilize common metrics such as Bits Per Token (BPT), Negative Log-Likelihood (NLL), Perplexity (PPL), and Batch Processing Speed.Experimental results show that the best-performing D3PM model achieves a BPT of 5.72, with a mean value of 8.05 across runs. In contrast, the AR model demonstrates a lower mean BPT of 4.59, indicating better compression and generative efficiency. However, D3PM models achieve higher batch processing speeds, with a maximum of 3.97 batches per second, highlighting their potential for parallel generation.All evaluations were conducted under consistent conditions-generating 100,000 tokens per model with a fixed batch size of four-to ensure fairness and comparability. This research contributes a detailed comparative analysis of diffusion-based and autoregressive models, offering insights into their respective trade-offs. Ultimately, the findings underscore both the promise and the current limitations of applying diffusion models to discrete sequence modeling, and provide a foundation for future exploration in non-autoregressive language generation frameworks.The source code used in this research is available at the following GitHub repository: \url{https://github.com/AshenWELI/Discrete-Diffusion-Models-for-Language-Genaration}.

The foundation of Swedish democracy rests on the principles of openness and transparency. In practice, a framework of laws and control mechanisms has been established to ensure adherence to these principles. Simultaneously, concerns regarding security and integrity have gained prominence as measures to safeguard Swedish democracy from undesirable influences seeking to destabilize Swedish society. This study consists of a comparative analysis of how official institutions manage to reconcile the competing values of security and transparency – through the unique constitutional right known as ‘handlingsoffentligheten’, which guarantees the public's access to important state information. Through the study I find some serious structural shortcomings, in that authorities’struggle to handle their democratic responsibilities, sometimes conflicting the law. The findings also reveal that significant disparities persist in how authorities comply with the requirements set to ensure uniform adherence to democratic objectives. For example one statement that can be made through this study is that almost one out of five authorities did not disclose public documents as rapidly as required. Seven out of ten sent the documents via e-mail, ten percent through ordinary mail whilst four percent sent encrypted files. Also twelve percent of the authorities censored information in the documents. The results thus underscore the need for explicit guidelines in order to assist public authorities in balancing the competing values of of security and transparency. Such harmonization could enhance public trust in both the authorities and the state. Moreover, the findings indicate that the use of encryption systems can facilitate public access to information in a manner that is both responsible and secure. It should therefore be recommended that all public authorities implement such practices in a unified manner.

Denna studie undersöker hur ett kommunalförbund organiserar ansvar och styrning i ett mellankommunalt samarbete kring digitalisering. Genom en fallstudie av ITSAM, ett kommunalförbund som hanterar IT-verksamheten åt fem mindre svenska kommuner, analyseras hur styrningsmodeller och ansvarsfördelning utvecklas i praktiken. Studien utgår från teorin om adaptive governance och relaterar även till New Public Governance och New Public Management, vilket möjliggör en fördjupad förståelse för samverkansstyrning i komplexa och föränderliga sammanhang. 

Med hjälp av processpårning analyseras två situationer i ITSAM:s utveckling, en medlemskommuns utträde och organiseringen av en gemensam fiberutbyggnad. Resultatet visar att tydlig ansvarsfördelning, flexibilitet och tillit är avgörande faktorer för ett fungerande samarbete. Studien belyser också utmaningar med oklara ansvarsförhållanden och behovet av anpassningsbara styrformer i digitaliseringsprojekt. Slutsatsen är att adaptive governance utgör ett värdefullt ramverk för att förstå och förbättra styrningen inom kommunal samverkan. Uppsatsen bidrar därmed med ny kunskap om digitaliseringens organisatoriska implikationer i mindre kommuner och hur dessa kan hanteras genom strategisk samverkan. 

This study investigates how governance processes around public space developments

in Berlin have been discursively shaped, with particular attention to the redevelopment

of Potsdamer Platz in the 1990s and Tempelhofer Feld in the early 200s around the

time of the former airport’s closure in 2008. The study employs a Critical Discourse

Analysis to examine how language, narratives, and framing strategies have been used

to legitimise urban development and reflect broader tensions concerning publicness,

privatisation, and urban democracy.

The findings demonstrate that the redevelopment of Potsdamer Platz was

characterised by investor-influenced governance, urgency narratives, and the

marginalisation of public participation. In contrast, the discourse around Tempelhofer

Feld was centred on social justice, and collective rights, fostering more participatory

planning forms while remaining contested under neoliberal pressure. Across both

cases, discursive strategies emerge as central instrument of governance, showing who

is involved in urban development and how the city is imagined, negotiated, and

claimed. The study underscores the political nature of urban planning, highlighting the

need of critical research on whose visions shape urban areas and for whom the city is

made.

The Swedish market for milk has undergone increased competition and significant structural changes following EU accession, leading to stricter demands for sustainable agriculture. Against this background, the question arises whether sustainability, profitability, and the strategies of various milk actors can be studied to better understand the transition toward sustainable milk production in Sweden. The Swedish milk market has been outlined, where the findings highlight an oligopolistic structure dominated by large actors. Furthermore, this thesis aims to analyze how the EU's new agricultural subsidies have influenced the strategies of Swedish milk actors, and whether these subsidies serve as an effective policy instrument for achieving a sustainable and profitable Swedish milk production.

Based on a qualitative analysis grounded in secondary data from public authorities, companies, and the EU, we apply the SCP-model to better understand and analyze the Swedish milk market and the strategies of the key actors. Additionally, we compare the strategies of Arla and Skånemejerier based on their reports, public statements, and performance in relation to their stated goals.

The results show that the EU has a significant influence on the Swedish milk market, and that agricultural subsidies play a vital role in maintaining profitability. However, it is too early to evaluate the impact of the new subsidy schemes, as sustainability is inherently complex to measure and environmental effects are delayed. Arla and Skånemejerier pursue strategic efforts toward sustainable dairy production, with visions including fossil-free and climate-neutral operations. Respective sustainability strategies are questionable, as organic production has declined since 2020, despite the positive externalities it provides. We are unable to conclusively determine whether sustainability aligns with profitability in their operations. Further research is needed to fully understand the relationship between sustainability and profitability in Swedish milk production.