Digitaliseringen har blivit en av de viktigaste pågående omvandlingarna som sker i nutida samhället och denna utveckling är viktig inom specifikt detaljhandeln samt modebranschen. Då modebranschen befinner sig på en global marknad har de utvecklat olika försäljnings-strategier på olika plattformar, för att bemöta konsumenters efterfrågan till digitala lösningar. Digitaliseringen har därmed spelat en stor roll inom modebranschen och efter internets uppkomst har digitala transformationer blivit alltmer synligt inom modebranschen. Därmed har denna kvalitativa studie undersökt hur konsumentens kundresa påverkar organisationer till att genomföra digitala transformationer inom modebranschen i Stockholm. Syftet med studien är att undersöka hur företag digitaliserar samt utvecklar sin verksamhet i form av att implementera digitala teknologier för att utveckla marknadsföringsstrategier samt digitala plattformar för att bemöta konsuments behov. För att undersöka studiens forskningsfråga har forskarna använt sig av en kvalitativ forskningsmetod som består av semistrukturerade intervjuer, av totalt fem respondenter från tre olika företag. Ytterligare har tre fokusgruppsintervjuer genomförts där konsumenter bosatta i Stockholm och tillhörande generation Z har deltagit för att berätta kring sina kundresor och hur dessa påverkas av olika företag. En desktopstudie som analyserar ett företags digitala transformation har genomförts. Resultatet visa att konsumenter har en stor efterfrågan på digitala lösningar från företag samt att företag har genomfört digitala transformationer för att bemöta dessa behov. De har utvecklat nya digitala plattformar samt marknadsföringsstrategier för att bemöta konsumenternas önskemål, allt från att skapa samarbeten med influensers till att samarbeta med andra externa partners för att exponeras på fler digitala kanaler och plattformar. Konsumenter kan därmed anses som deltagare utöver kund i företags arbetssystem. Därmed kan slutsatserna dras att digital transformation är essentiellt för alla företag inom modebranschen för att kunna stötta konsumenter i dess kundresa hela vägen. / Digitization has become one of the most important transformations taking place and this development is important in the retail- and the fashion industry. This is due to the fashion industry being located on a global market where different sales strategies have evolved for different platforms, to respond on consumers demand for digital solutions. Digitalization has therefore played a major role in the fashion industry and with the origin of the internet, more companies in the fashion industry have implemented digital transformation. Therefore, this thesis has examined how the consumers’ customer journey affects organizations to implement digital transformation in Sweden’s fashion industry. The purpose of the present study was to examine how companies have digitized and developed their business, by implementing digital technologies to enable development of marketing strategies and digital platforms to meet consumer needs. To answer the thesis research question, the researchers used a qualitative research method consisting of semi-structured interviews, containing a total of five respondents from three different companies. In addition, three focus group interviews were conducted consisting of consumers living in Stockholm and belonging to generation Z. The participants spoke of their customer journey and how it is affected by different companies. The researchers also performed a desktop study consisting of a company’s digital transformation. This has led to the result that consumers are demanding digital solutions from companies as well as companies having to implement digital transformations. They have developed new digital platforms and marketing strategies to meet consumers’ needs. Companies have created collaborations with influencers and with other external partners to be exposed on more digital channels and platforms. Therefore, the studied consumers can be considered as participants in addition to being consumers in companies’ work systems. This has led to the conclusion that digital transformation is essential for companies in the fashion industry to be able to support consumers in their customer journey.

In the digital era and advent of artificial intelligence, digital retailing has emerged as a notable shift in commerce. It empowers e-tailers with data-driven insights and predictive models to navigate a variety of challenges, driving informed decision-making and strategic formulation. While predictive models are fundamental for making data-driven decisions, this thesis spotlights binary classifiers as a central focus. These classifiers reveal the complexities of two real-world problems, marked by their particular properties. Specifically, binary decisions are made based on predictions, relying solely on predicted class labels is insufficient because of the variations in classification accuracy. Furthermore, prediction outcomes have different costs associated with making different mistakes, which impacts the utility. To confront these challenges, probabilistic predictions, often unexplored or uncalibrated, is a promising alternative to class labels. Therefore, machine learning modelling and calibration techniques are explored, employing benchmark data sets alongside empirical studies grounded in industrial contexts. These studies analyse predictions and their associated probabilities across diverse data segments and settings. The thesis found, as a proof of concept, that specific algorithms inherently possess calibration while others, with calibrated probabilities, demonstrate reliability. In both cases, the thesis concludes that utilising top predictions with the highest probabilities increases the precision level and minimises the false positives. In addition, adopting well-calibrated probabilities is a powerful alternative to mere class labels. Consequently, by transforming probabilities into reliable confidence values through classification with a rejection option, a pathway emerges wherein confident and reliable predictions take centre stage in decision-making. This enables e-tailers to form distinct strategies based on these predictions and optimise their utility. This thesis highlights the value of calibrated models and probabilistic prediction and emphasises their significance in enhancing decision-making. The findings have practical implications for e-tailers leveraging data-driven decision support. Future research should focus on producing an automated system that prioritises high and well-calibrated probability predictions while discarding others and optimising utilities based on the costs and gains associated with the different prediction outcomes to enhance decision support for e-tailers. / <p>The current thesis is a part of the industrial graduate school in digital retailing (INSiDR) at the University of Borås and funded by the Swedish Knowledge Foundation.</p>