Skiftet från en bensindriven bil till en elbil är ett ämne som drastiskt accelererat under de senaste fem åren med motivation av miljömässiga fördelar. Detta skifte börjar inte bromsa in, utan snarare att fler konsumenter väljer en elbil framför en bil med en förbränningsmotor. I takt med att bilen blir mer avancerad, blir även tekniken inuti bilen mer komplicerad för konsumenter att använda. Syftet med denna studie är att jämföra köpintentioner av en Elbil mellan Tyskland och Storbritannien, med specifik hänsyn till Technology acceptance model (TAM). Studien är genomförd som en kvantitativ undersökning med Polestar som samarbetspartner. För Tyskland respektive Storbritannien är respondenterna 54 respektive 56 styck. Analysering av resultat har gjorts genom en deskriptiv analys samt en korrelationsanalys, för att hitta mönster i de datamaterial som insamlats. Resultatet påvisar att det finns såväl likheter som skillnader i köpintentionerna för såväl Tyskland som Storbritannien. Exempelvis påvisar resultatet att TAM har en likvärdig inverkan på köpintentionerna hos de båda länderna, samtidigt som exempelvis miljö har en större inverkan hos konsumenter i Storbritannien än i Tyskland. / The shift from a petrol-powered car to an electric car is a topic that has accelerated dramatically over the past five years with the intention of environmental benefits. This shift is not starting to slow down, rather more consumers are choosing electric vehicles over cars with internal combustion engines. As the car becomes more advanced, the technology in the car also becomes more complicated for consumers to use. The purpose of this study is to compare the purchase intentions of electric cars in Germany and the United Kingdom, with specific regard to the Technology acceptance model (TAM). The study was conducted as a quantitative study partnered with Polestar. For Germany and the United Kingdom, the respondents are 54 and 56 respectively. Analysis of results has been done through descriptive analysis and correlation analysis, to find patterns in the data material collected. The results show that there are similarities and differences in the purchase intentions for both Germany and the United Kingdom. For example, the results show that TAM has an equal impact on the purchasing intentions of the two countries, while for example, the environment has a greater impact on consumers in the UK than in Germany.

Artificiell intelligens (AI) och i synnerhet maskininlärning (ML) har inom UX-design visat potential att förbättra designprocessen genom att exempelvis identifiera användargrupper från stora datamängder, effektivisera idégenerering och automatisera repetitiva uppgifter. Det råder dock oenighet kring hur tekniken kan integreras i designprocessen. En viktig del av en designers arbete är att konsekvent prioritera användarbehov och därigenom förbättra användartillfredsställelsen. Därför försöker designers empatiskt sätta sig in i användarnas situation genom att identifiera deras behov och noggrant utforska potentiella problemområden. En visualiseringsteknik som ofta används av designers för att utveckla och förstå användarupplevelsen är journey mapping (JM). JM är dock en mycket resurskrävande process då den förutsätter nära samarbete mellan olika avdelningar och team. Trots detta visar forskning att de flesta designers inte integrerar element relaterade till insikter i sina kartor, vilka ofta är avgörande för att omvandla JM från visuell berättelse till handlingsplan. Integreringen av ML i JM-processen skulle potentiellt kunna möjliggöra en snabbare, mer datadriven och anpassningsbar designprocess som fokuserar mer på användarnas behov och önskemål. Utmaningen ligger i att smidigt integrera tekniken utan att förlora mänskliga perspektiv och tolkningar, vilka är grundläggande för användarcentrerad design. Denna studie fokuserar på att utforska sätt att integrera ML i delar av designprocessen för att möta utmaningarna som uppstår vid strävan efter användarcentrerad design i en resurskrävande miljö. För att uppnå en djupgående och strukturerad förståelse av samspelet mellan designprocessen, empatiskapande samt ML valdes en systematisk litteraturgranskning som den primära datainsamlingsmetoden samt tematisk analys som dataanalysmetod för denna studie. Målet är att utifrån detta resultat presentera praktiska rekommendationer, baserat på sammanställning av befintlig forskning, för hur JM-processen kan omformas och göras mer ML-driven. Genom en omfattande litteratursökning inhämtades data, vilken genomgick kvalitetsbedömning. Därefter genomfördes en inkludering- och exkluderingsprocess i enlighet med förutbestämda kriterier. Detta resulterade i 13 utvalda dokument, från vilka mönster och teman extraherades genom en tematisk analys. Resultatet visade på vikten av samskapande mellan människa och maskin för att möjliggöra en ansvarsfull designprocess. I resultaten presenteras även tekniska möjligheter och dilemman, där ML exempelvis kan automatisera repetitiva uppgifter och möjliggöra kontinuerlig övervakning och utvärdering av användarupplevelsen över tid. Dock kräver detta omfattande och representativa träningsdataset för att konstruera ML-modeller med hög generaliseringsförmåga gentemot nya och komplexa data. Resultaten belyser också bristen på förståelse för ML bland UX-designers och betonar vikten av samarbete med datavetare för att skapa en effektiv designprocess. Utifrån dessa resultat presenteras rekommendationer för en ML-driven JM-process. Även om UX-rollen troligtvis behöver omdefinieras, framhåller resultaten att kulturen inom UX-designprocessen snarare är "dataaktiverad" än helt datadriven. Detta perspektiv understryker det fortsatta behovet av mänsklig intuition och förståelse trots den ökade inriktningen på datadrivna metoder. Slutligen diskuteras hur framtida forskning skulle kunna inrikta sig på att utvärdera rekommendationernas praktiska tillämpbarhet. / Artificial Intelligence (AI), particularly Machine Learning (ML), has demonstrated potential within UX design to enhance the design process by identifying user groups from extensive datasets, streamlining idea generation, and automating repetitive tasks. However, there is ongoing debate about the integration of this technology in the design process. A crucial aspect of a designer's work is consistently prioritizing user needs to enhance user satisfaction. Designers strive to empathetically understand user situations by identifying their needs and meticulously exploring potential problem areas. One commonly used visualization technique employed by designers to develop and understand user experiences is Journey Mapping (JM). However, JM is a resource-intensive process, requiring close collaboration across different departments and teams for extensive data collection. Despite this, research indicates that most designers do not integrate elements related to insights into their maps, crucial for transforming JM from a visual narrative to an actionable plan. Integrating ML into the JM process could potentially enable a faster, more data-driven, and adaptable design process, effectively focusing on user needs and desires. The challenge lies in seamlessly integrating the technology without losing the human perspectives and interpretations fundamental to user-centered design. This study focuses on exploring ways to integrate ML into parts of the design process to address challenges in pursuing user-centered design in a resource-intensive environment. A systematic literature review was chosen as the primary data collection method, with thematic analysis employed as the data analysis method. The aim was to present practical recommendations based on a compilation of existing research on the design process, making the JM process more MLdriven. Through an extensive literature search, data was gathered and subjected to quality assessment. Subsequently, an inclusion and exclusion process were conducted according to predetermined criteria, resulting in 13 selected documents. Patterns and themes were extracted through thematic analysis. The results emphasize the importance of co-creation between humans and machines to enable a responsible design process. Technical possibilities and dilemmas are also presented, highlighting ML's ability to automate repetitive tasks and facilitate continuous monitoring and evaluation of user experience over time. However, this requires comprehensive and representative training datasets to construct ML models with high generalization ability to new and complex data. The results also underscore the lack of ML understanding among UX designers and emphasize the importance of collaboration with data scientists for an efficient design process. Recommendations for an ML-driven JM process are presented based on these findings. While the UX role may need redefinition, the results emphasize a "data-activated" culture within the UX design process rather than being entirely data-driven. This perspective underscores the ongoing need for human intuition and understanding despite the increased focus on data-driven methods. Finally, the discussion explores how future research could evaluate the practical applicability of the recommendations.

The bachelor thesis aims to explore whether students perceive the usage of self-service technology (SST) as positive, neutral or negative, which occurs before, under and after a visit at the library of University of Borås. In this paper, a qualitative user diary was used as a method to gather empirical data. An established UX method, customer journey mapping (CJM), was selected to analyze the empirical findings. The findings were further analyzed with a theoretical framework of the predecessor David Benyon to gain a deeper understanding of user experience in a cross-channel context. The study shows that students are overall positive to the usage of SST, but a deficiency of information affects the positive experience throughout the library.

The aviation industry has some tough years behind it due to the COVID-19 pandemic and the emergence of low cost carriers. In the competition of retaining and attracting passengers, the importance of the passenger's airport experience has been discovered. This thesis investigates how digitalising of airports can lead to an enhanced airport experience for passengers. With the use of a digital transformation model and the field of service design a research design of four phases has been assembled. Through in-depth interviews, participation in a vision seminar and shadowing of passengers, the current state of digitalisation at airports has been assessed and goals for a future digital airport has been defined. This laid the foundation for the developed vision for future digital airports presented in this thesis. The results indicated that digitalisation can have a great impact on passengers' airport experience if properly designed. In fact, simply digitising is not enough, the airports must undergo a digital transformation to reach the full potential of digitalisation. The digital maturity of passengers is also found as a key point to successfully change the way airports operate.

Metoden Kundresekartläggning har använts i årtionden för att kartlägga målgruppers upplevelser, exempelvis kunders upplevelse av en organisations tjänster. I vetenskaplig litteratur saknas beskrivning av hur datainsamling och analys går till i kundresekartläggnings-projekt. För att öka förståelsen för hur metoden går till har kunskap samlats in, främst genom intervjuer med praktiker (user experience designers och tjänstedesigners) erfarna av metoden. Resultatet blev en guide fylld av tips som kan vara bra för praktiker att tänka på inför och under den här typen av projekt, samt hur man kan engagera organisationen (beställaren av kundresekartan) i projektet så att insikterna används vidare även efter leveransen av kundresekartan. I slutet av guiden finns dessutom fem exempel på kundresekartor som praktiker delat med sig av och berättar om.

The current case study served to investigate roles, uses, attitudes, and future implications of a collaborative artificial intelligence system [CAIS] at a user experience and service design firm. Due to the shortage in the body of literature for human machine co-creative collaboration, this study obliged in expanding on it from a qualitative and conceptual level. Findings from a thematic analysis on design practitioners, indicated three main themes: Attitudes, Attributes, and Awareness. Main findings indicate that negative attitudes affect how much autonomy is ascribed to CAIS; There is a lack of actuating design with this type of technology, partly due to lack of knowledge but also a central authority in the community; CAIS is perceived to foster creativity, but not truly collaboratively; Finally, ethical considerations towards designing with such intelligent systems are discussed both regarding the designer and the design process, but also towards the end-user.

<p dir="ltr"><b>Background</b></p><p dir="ltr">Recent developments in cancer therapeutics have allowed increased use of Oral Anticancer Medications (OAMs), including in the treatment of breast cancer. Breast cancer is the most common cancer among women in the United States. Patients with breast cancer may face key barriers in managing their OAMs at home. These challenges can lead to sub-optimal adherence and lower the overall quality of life. Designing interventions that enhance the patient experience with use of OAMs requires a deeper understanding of barriers faced by patients as they navigate their cancer care journey. The objective of this study was to identify the unmet medication management needs of patients with breast cancer who are receiving OAMs and co-design an early prototype intervention with patients to support medication management needs of patients with breast cancer.</p><p dir="ltr"><b>Methods</b></p><p dir="ltr">Two phases comprise this study. Phase 1 involved patient-journey mapping to characterize the longitudinal experience of OAMs use among patients diagnosed with breast cancer. In phase 2, we conducted participatory design (PD) workshops to develop a prototype tool to address OAM needs identified in phase 1. All participants were recruited from an outpatient breast cancer clinic in Indianapolis. Eligible participants were: 18 years of age or older, diagnosed with breast cancer, and currently receiving an OAM. All participants completed a brief sociodemographic and health information questionnaire. In phase 1, enrolled persons participated in a journey mapping exercise through semi-structured interviews. Interviews were conducted either in-person or remotely via Zoom, based on participant preference. For each interview, two researchers and the participant collaborated to create individual patient journey maps to generate a concise visual storyboard focused on medication use experiences related to OAMs. The journey maps helped capture treatment timelines, key markers of medication use, and specific barriers faced by patients. Individual journey maps were consolidated to generate personas representing groups of patients with related characteristics, treatment types, goals, and unmet needs. In phase 2, three rounds of PD workshops were conducted using the focus group format to develop an early prototype intervention. In round one (inspiration stage), participants defined the problem space and prioritized a list of challenges amenable to solutions; in round two (ideation stage), participants generated multiple possible solutions and design ideas; and in round three (convergence stage), two design concepts were selected and evaluated by participants.</p><p dir="ltr"><b>Results</b></p><p dir="ltr">In phase 1, 12 interviews (11 females and 1 male) were completed. The median age of participants was 65.5 years (range, 37-75). Participants were divided into two groups based on their prescribed medication types: (1) specialty medication (palbociclib or ribociclib; n=4 patients) and (2) traditional medication (tamoxifen, anastrozole, or exemestane; n=8 patients). We defined ‘Specialty’ medications as those that require specialty pharmacies and ‘traditional’ medications as those obtainable in local community pharmacies. To represent participants across these two broad categories of medications, two personas were created. Participants who had been prescribed specialty medication reported difficulty navigating the insurance process during medication fills, while participants who prescribed traditional medication did not. Notably, the word “prior authorization” was not used by participants to explain the issues they experienced. While all participants reported having side effects from their medications, sub-optimal adherence (n=2) was reported among the traditional medication group only. Other participants taking traditional medications either found their own ways to manage side effects or simply reported: “dealing with side effects as I don’t want cancer.” Participants expressed coping with side effects by enduring them. Participants had few strategies to manage their side effects, often stating that “they didn’t think of reaching out to the doctor,” when asked. Additionally, participants mentioned needing more financial and emotional support during their treatment journey. In phase 2, each PD session was conducted with 4-5 participants and 2 researchers (the design panel). Participants identified key challenges including difficulties navigating resources and information as well as managing medication side effects. The design panel prioritized two design concepts, which were subsequently developed into two prototypes: 1) a physical breast cancer handbook; and 2) an interactive treatment navigation app for use on tablet and smartphone devices. Our team plans to consolidate, further develop, and evaluate these prototypes in subsequent work as a follow up to this pilot study.</p><p dir="ltr"><b>Conclusion</b></p><p dir="ltr">This study provides insight into the patient experience with OAMs. The personas created can be applied in designing interventions tailored to breast cancer patients’ needs and goals, while the consolidated journey maps identify potential areas for improvement. Adequate patient education and enhanced tools and processes are necessary to manage medication side effects effectively, ultimately leading to improved medication outcomes and assisting patients in navigating their treatment. The two design concepts require further revision prior to implementation and pilot testing.</p>