Knowledge management and the strategy surrounding it has been highlighted as keys for achieving and maintaining competitive advantage, particularly for knowledge-intensive firms. Consulting firms are knowledge-intensive firms that generate revenue solely through offering the knowledge of their consultants, arguably making knowledge management even more crucial in their competitive fields. In some cases, consultants do not collaborate with their consultancy colleagues in their everyday work, but rather meet only in team activities and social contexts, making the sharing and maintaining of knowledge an even tougher challenge. It is thereby of interest to investigate various types of consulting firms to evaluate how they manage knowledge and how important it is. The purpose of this study is to enhance the understanding of knowledge management in consulting firms through analysing the case of a technical consulting firm. The study focused particularly on two dimensions: knowledge sharing activities and knowledge management strategy. Fifteen interviews were conducted, and the data was analysed through thematic analysis supported with models and frameworks from the knowledge management literature. The findings of the study point out that whilst not having stated a clear knowledge management strategy, the firm utilises a personalization strategy with a focus on encouraging knowledge sharing in personal contexts whilst putting less effort into documenting knowledge. Supporting the strategy, the firm houses a helpful and learning culture where seeking support from colleagues is encouraged and teaching your colleagues is part of personal development plans. The consulting teams’ collective meetings were seen as important boosters of knowledge sharing along with structured learning from colleagues, whilst the time constraints from client obligations were mutually deemed the main inhibitor. The suggested improvements for the firm were to first make a clear strategy regarding the knowledge management. Furthermore, an increasedcodification and to document highly demanded, novel knowledge was suggested, as well as simplifying the search for the right competence within the firm when a colleague needed help. Lastly, it was suggested that they look at improving the utilization of senior’s experience to support new recruits and reinforce their competence development.

Slutsatsen av denna studie är att en mängd varierande faktorer påverkar en konsuments attityd, både vad gäller artificiell intelligens (AI) men också attityder gentemot företagen som brukar den sagda teknologin. I enlighet med The Technology Acceptance Model (Davies, 1989) är konsumentens uppfattning om huruvida AI personligen kommer gynna dem av yttersta vikt. Såvida ingen vinning uppfattas kommer attityden gentemot AI påverkas negativt. Ytterligare har även faktorer som riskbenägenhet, annonsrelevans och subjektiva normer betydelse i vad som är en konsuments attityd gentemot AI och företag. / The conclusion of this study is that a number of varying elements are affecting the consumer attitude, against artificial intelligence (AI) –but also towards the specific companies who utilize AI. Corresponding with The Technology Acceptance Model (Davies, 1989), the perception of whether AI will benefit the consumer or not is essential. Should no gain be perceived, the attitude towards AI will be affected negatively. Furthermore, aspects such as risk beliefs, ad relevance and subjective norms are elements to consider regarding consumer attitude towards AI and subsequently retail companies.

Individualized teaching in schools with children with learning disabilities is a prerequisite, in order to be able to convey knowledge and teaching in an educational and developing way. The purpose of this study is to explore how musical communication can be used in school's with children with learning disabilities in different ways and how teachers can create an individualized teaching through this, during the music lessons. The study's result describes the interviews that have been conducted that have occurred in varied locations around Sweden with teachers in the subject area music in learning disabilities. The result presents how teachers use musical communication in their teaching and in what way the teaching is tailored to the needs of the students to become developing. The discussion that is linked to the subject of the study focuses on individual adaptation and alternative ways in which the teacher can make use of it in order to obtain an educational teaching, in which the students are given the opportunity for an in-depth understanding and a developed knowledge.

The financial sector is transforming as a result of PSD2 and open banking. The traditional retail banks face new competition from FinTechs and BigTechs. 78 percent of Nordic banks are concerned by the threat of disruption and 88 percent think that they need to rethink their business model. Customer experience and customer journeys are crucial as customer expectations is one of the major driving forces for the changing industry.Generation Y (1989 2000) is often defined as early adopters and digital natives which makes them an important but challenging customer segment. According to the Millennial Disruption Index, the banking industry is at the highest risk of disruption from generation Y. This study focus on how traditional Swedish retail banks can manage digital transformation and the needs and behavior of the Swedish generation Y. To identify the needs and demands of generation Y, four focus groups was conducted with 31 participants and four semi-structured interviews. The results was analyzed and related to a customer journey framework and the concept of platform banking.The results indicate that the Swedish generation Y demands personalized services and products as well as tailored Omni-channel experiences. They demand an expansion of financial services in the form of a “one-stop-shop”. In order to meet these demands, traditional Swedish retail banks must utilize their customer data and weight the Swedish generation Y´s trust in their security. This will enable them to develop superior customer experiences as well as extending their context and establish themselves as banking platforms. / Den finansiella sektorn förändras till följd av PSD2 och open banking. De traditionella bankerna möter ny konkurrens från FinTechs och BigTechs. 78 procent av de nordiska bankerna är oroade av förändringarna och 88 procent tycker att de behöver ompröva sin affärsmodell. Kundupplevelser och kundresor är avgörande eftersom kundernas förväntningar är en av de viktigaste drivkrafterna för den föränderliga industrin.Generation Y (1989 2000) definieras ofta som digitala pionjärer vilket gör dem till ett viktigt men utmanande kundsegment. Enligt studien ”Millennial Disruption Index” har banksektorn den högsta risken för störningar från Generation Y. Denna studie fokuserar på hur traditionella svenska banker kan hantera digital transformation och den svenska generation Ys behov och beteende. För att identifiera behov och krav från generation Y genomfördes fyra fokusgrupper med 31 deltagare samt fyra semi-strukturerade intervjuer. Resultaten analyserades och relaterades till en kundrese teori samt konceptet om plattformsbanker.Resultaten indikerar att den svenska generation Y kräver personliga tjänster och produkter samt skräddarsydda Omni-kanalupplevelser. De kräver en expansion av finansiella tjänster i form av en "one-stop-shop". För att möta dessa krav måste traditionella svenska banker använda deras kunddata och utnyttja den svenska generation Ys förtroende för deras säkerhet. Detta kommer att göra det möjligt för dem att utveckla överlägsna kundupplevelser såväl som att utvidga sitt sammanhang och etablera sig som bankplattformar.

Sättet människor konsumerar musik har förändrats genom historien och i samband med digitaliseringen har nya möjligheter att lyssna på musik uppstått. I samband med denna övergång har även fler algoritmbaserade tillvägagångssätt för musiklyssnande uppkommit. Syftet med studien är att undersöka unga vuxnas upplevelser av den algoritmbaserade Radiofunktionen på musikstreamingtjänsten Spotify. Studien har även undersökt huruvida de algoritmbaserade förslagen eventuellt påverkar användarnas upplevelser och musikbeteenden.Undersökningen är baserad på sju respondenters upplevelser inom åldersspannet 20-30 år, i denna studie definierat som unga vuxna. Studien har genomförts via kvalitativa metoder däribland en inledande dagboksstudie, med syfte att förbereda respondenternas reflektiva tänkande vilket följdes upp med semistrukturerade intervjuer. Därefter transkriberades intervjuerna för att senare kodas och en tematisk analys genomfördes. Resultatet av studien påvisar att det finns en variation i användandet av radiofunktionen samt att majoriteten av respondenterna uttryckt en positiv upplevelse av Radio på Spotify. Studien bidrar med nya insikter kring algoritmbaserade upplevelser hos användare i relation till musikstreaming och framförallt funktionen radio, samt hur användandet kan skilja sig beroende på situation och anledning till användande. / The streaming of music has during the last two decades become a new standard for how people acquire and listen to music. In correlation with this shift, other possibilities for listening to music have been on the rise. The purpose of this study is to investigate the experience for young adults of algorithm-based playlist ”Radio” on the streaming service platform Spotify. The investigation will determine whether or not these algorithm-based suggestions potentially affect the users' experience of listening to music and overall music behavior.The study is based on the experience of seven respondents of ages ranging between 20-30 years old - through this study referred to as "young adults." The qualitative methods this research has followed consists of a simple initial diary study, in order to prepare the respondents reflective thinking before the following semi-structured interviews. The interviews were then transcribed and followed by coding as well as a thematical analysis. The results of the study show that there is a variation in the use of the ”Radio” phenomenon on Spotify and that the vast majority of the respondents participating in the investigation expressed an overall positive experience. Furthermore, this study indicates that the respondents utilize the feature on different occasions and for different purposes.

In the last decade, marketing automation, a tool for automatic personalization, has been gaining significant traction among marketing professionals. In parallel with the growing adoption trend, many marketing automation platform providers have been extending their offers to include AI features. However, there is a lack of research regarding how AI can enhance the process of marketing automation in a way that creates value, which is the studied topic in this thesis. A qualitative and exploratory case study has been conducted in collaboration with the global B2B company Atlas Copco, a manufacturer of industrial equipment. Digital marketing practitioners were presented with two use cases of AI, segmentation and cross-selling, for personalization and asked about the marketing automation process and the expected impact on value. The findings reveal what would be required in the marketing automation process for the use cases in terms of data needs, learning about customer insights, marketing output and evaluation. In our findings value creation strongly revolve around the value types: ‘excellence’, ‘efficiency’ and ‘privacy’. To conclude, AI will enable more advanced personalization and value creation can be substantial if customer sacrifices are addressed in an appropriate way. Depending on relevance, tone of voice, time and use of channel, different feelings of value are perceived, which are factors that AI can help to determine / Under det senaste årtiondet har verktyg för automatisk marknadsföring blivit populära bland marknadsförare. Automatiska marknadsföringsplattformar fungerar som ett verktyg för att automtiskt leverera personaliserade marknadsföring. Många leverantörer av automatiska marknadsföringsplattformar har utökat sina erbjudanden till att innefatta AI-tjänster. Den befintliga forskningen kring hur sådana AItjänster ska utnyttjas på ett sätt som skapar värde är begränsad och därav behandlas ämnet i den här uppsatsen. En explorativ och kvalitativ fallstudie har genomförts i samarbete med Atlas Copco som är ett globalt b2b-företag. Vid varje intervju presenterades antingen merförsäljning eller kundsegmentering sedan ställdes frågor om den automatiska marknadsföringsprocess och värde. Resultaten indikerar vad som skulle krävas för de undersökta användningsfallen i den automatiska marknadsföringsprocessen samt att värdeskapande är starkt kopplat till värdetyperna excellens, effektivitet, privatliv och datasäkerhet. Slutsatserna indikerar att AI kommer göra den personalisering som uppstår till följd av automatisk marknadsföring mer avancerad. Värdeskapandet från nya AI lösningar kan vara signifikant om implementeringen tar hänsyn och adresserar uppoffringar kunder behöver göra.

In this essay, we have studied whether the Swedish newspaper Sportbladet reporting on the French football league (Ligue 1) is different from the season before to season after Zlatan Ibrahimovic’s arrival at Paris Saint-Germain FC in the summer of 2012. The teories that we applied were news values, framing and personalization. In order to complete our investigation, we used two different methods: a quantitative content analysis and critical discourse analysis to see if the news valuation and framing are different, but also to see what impact Zlatan Ibrahimovic’s arrival has on the media coverage of the league. The result of the quantitative content analysis and the critical discourse analysis shows huge differences between 2011/12 and 2012/13 seasons. Sportbladet published ten times as many articles during Zlatan’s debut season in the league in comparasion with the previous season. The articles became generally larger, better placed in the newspaper and contained more columns about the subject. We could also note more focus on individuals in the articles. This change is mainly explained by the increased geographical and cultural proximity during the 2012/13 season, which arose in connection with Ibrahimovic’s transfer from Milan to Paris Saint-Germain. The result was pretty much as we had expected. The 2012/13 season was way more covered with a particular focus on Zlatan and his team in the articles. That shows what kind of importance a national super star like Zlatan Ibrahimovic has on the reporting from the French league.

Personalization constitutes the mechanisms and technologies necessary to customize information access to the end-user. It can be defined as the automatic adjustment of information content, structure, and presentation. The central thesis of this dissertation is that modeling interaction explicitly in a representation, and studying how partial information can be harnessed in it by program transformations to direct the flow of the interaction, can provide insight into, reveal opportunities for, and define a model for personalized interaction. To evaluate this thesis, a formal modeling methodology is developed for personalizing interactions with information systems, especially hierarchical hypermedia, based on program transformations. The predominant form of personalized interaction developed in this thesis is out-of-turn interaction, a technique which empowers the user to take the initiative in a user--system dialog by providing unsolicited, but relevant, information out-of-turn. Out-of-turn interaction helps flexibly bridge any mismatch between the user's model of information seeking and the system's hardwired hyperlink structure in a manner fundamentally different from extant solutions, such as multiple faceted browsing classifications and search tools. This capability is showcased through two interaction interfaces using alternate modalities to capture and communicate out-of-turn information to the underlying system: a toolbar embedded into a traditional browser for out-of-turn textual input and voice-enabled content pages for out-of-turn speech input. The specific research issues addressed involve identifying and developing representations and transformations suitable for general classes of hierarchical hypermedia, providing supplemental interactions for improving the personalized experience, and studying user's (out-of-turn) interactions with resulting systems. / Ph. D.

Marketing is one of the industries most impacted by the rapid development of AI and its applications. This study, in particular, illuminates the significant field of content personalization, which is a highly successful marketing strategy. In a world where content personalization is increasingly implemented by e-commerce websites, movie platforms, music platforms, and even news websites, the practice of collecting personal information for content personalization has raised concerns among consumers, leading many to reject such practices. Individuals' beliefs and cultural characteristics play a significant role in their attitudes toward content personalization. Therefore, this study aims to explore the drivers that would lead someone to share their personal information for content personalization. However, rather than just examining this trade-off, the study seeks to gain a deeper understanding of the issue by exploring how these drivers are related to individual cultural characteristics. To explore consumers' opinions and the drivers that would motivate someone to share their personal information for content personalization, interviews were conducted with individuals from Northern Europe and Greece, who have different cultural characteristics. By examining the topic through personal experiences and perspectives, the study revealed that certain drivers are considered regardless of culture, while others are culturally specific, thus creating specific patterns for how individuals of different cultures think. This information can guide marketers, policymakers, and professionals in the field to align their practices with the diverse cultural characteristics of individuals.

Trust is the cornerstone of success in any relationship between two or more parties. Generally, we do not socialize, seek advice, consult, cooperate, buy or sell goods and services from/to others unless we establish some level of mutual trust between interacting parties. When e-commerce was merging infancy, the concept of trusting an entity in a virtual world was a huge obstacle. Gradually, increasingly-sophisticated, largely generic reputation scoring and management systems were embedded into the evolving marketplaces. Current technologies to include cloud computing, social networking, and mobile applications, coupled with the explosion in storage capacity and processing power, are evolving large-scale global marketplaces for a wide variety of resources and services, such as Amazon.com, BitTorrent, WebEx and Skype. In such marketplaces, user entities, or users for short; namely, consumers, providers and brokers, are largely autonomous with vastly diverse requirements, capabilities and trust profiles. Users' requirements may include service quality levels, cost, ease of use, etc. Users' capabilities may include assets owned or outsourced. Trustors' profiles may include what is promised and commitments to keep these promises. In such a large-scale heterogeneous marketplace, the trustworthy interactions and transactions in services and resources constitute a challenging endeavor. Currently, solving such issues generally adopts a "one-size fits all" trust models and systems. Such approach is limiting due to variations in technology, conflicts between users' requirements and/or conflicts between user requirements and service outcomes. Additionally, this approach may result in service providers being overwhelmed by adding new resources to satisfy all possible requirements, while having no information or guarantees about the level of trust they gain in the network. Accordingly, we hypothesize the need for personalizable customizable Trust Management Systems (TMSs) for the robustness and wide-scale adoption of large-scale marketplaces for resources and services. Most contemporary TMSs suffer from the following drawbacks: • Oblivious to diversities in trustors' requirements, • Primarily utilize feedback and direct or indirect experience as the only form of credentials and trust computations, • Trust computation methodologies are generally hardcoded and not reconfigurable, • Trust management operations, which we identify as monitoring, data management, analysis, expectation management, and decision making, are tightly coupled. Such coupling impedes customizability and personalization, and • Do not consider context in trust computations, where trust perspectives may vary from a context to another. Given these drawbacks and the large scale of the global marketplace of resources and services, a reference architecture for trust management systems is needed, which can incorporate current systems and may be used in guidance and development of a wide spectrum of trust management systems ranging from un-personalized to fully personalized systems. Up to our knowledge, no TMS reference architecture exists in the literature. In this dissertation, we propose a new Reference Architecture for Trust Management (RATM). The proposed reference architecture applies separation of concern among trust management operations; namely, decision expectation, analytics, data management and monitoring. RATM defines trust management operations through five reconfigurable components which collectively can be used to implement a wide spectrum of trust management systems ranging from generic to highly personalized systems. We used RATM for trust personalization, where we propose a Personalized Trust Management System (PTMS) based on RATM. We evaluated PTMS's scalability and demonstrated its effectiveness, efficiency and resilience by contrasting against a Generic Trust Management System (GTMS). We used two case studies for our evaluations; namely, BitTorrent and a video conferencing application. Intellectual Merit In this work, we propose RATM, a reference architecture for trust management systems that can be used to implement a wide variety of trust management systems ranging from generic systems (un-personalized) to highly personalized systems. We assume service-based environment where consumers, brokers and service providers are interacting and transacting in services and resources to satisfying their own trust requirements. We used RATM to implement a personalized trust management system (TMS). The main contributions of this work are as follows: • Proposing RATM for the guidance and development of a wide spectrum of TMSs ranging from un-personalized to fully personalized systems, and • Utilizing our RATM to propose and implement a personalized, scalable TMS with varying trust computation models. Broader Impact RATM provides reference architecture for trust management which can be used to develop and evaluate a wide spectrum of TMSs. Personalization, in general, paves the road for reaching high levels of satisfaction, where interacting parties' requirements are individually considered and thus consumers are served the best suited service(s). Hence, we claim that PTMS would largely enhance large-scale heterogeneous systems offering services and resources. This could lead to more cooperation, more transactions, more satisfaction, less malicious behavior and lower costs. / PHD / Trust is the cornerstone of success in any relationship between two or more persons. Generally, we do not socialize, seek advice, consult, cooperate, buy or sell goods and services from/to others unless we establish some level of mutual trust between interacting parties. When ecommerce was firstly used, the concept of trusting a service delivered by someone who is not physically in the same place was a huge obstacle. Gradually, more sophisticated, largely generic reputation scoring and management systems were used into the new internet marketplaces. A reputation scoring and management system is a system which collects feedback from different users about service providers in a certain marketplace on the internet and uses them to anticipate future behavior of these providers. Current computer technologies to include cloud computing, social networking, and mobile applications, coupled with the explosion in computer and mobile devises’ storage capacity and processing power, are evolving large-scale global marketplaces offering a wide variety of resources and services to consumers across the globe. Examples include Amazon.com, BitTorrent, WebEx and Skype. In such marketplaces, consumers, providers and brokers, are largely autonomous with vastly diverse requirements, capabilities and trust profiles. By autonomous we mean acting in accordance with one's moral duty rather than one's desires. Users’ requirements may include service quality levels, cost, ease of use, etc. Users’ capabilities may include assets owned or leased from others. Trustors’ profiles may include what is promised and commitments to keep these promises. In such a large-scale marketplace, the trustworthy interactions and transactions in services and resources constitute a challenging endeavor. By trustworthy interaction we mean transactions which deliver results that are accepted by all parties. Currently, solving such issues of trust generally adopts a “one-size fits all” trust models and systems. By trust models and systems we mean computer programs which perform the reputation scoring and management. i.e. select a single service which can serve all requirements. Such approach is limiting due to variations in technology, conflicts between users’ requirements and/or conflicts between user requirements and service outcomes. Additionally, this approach may result in service providers being overwhelmed by adding new resources to satisfy all possible requirements, while having no information or guarantees about the level of trust they gain in the eye of their consumers. Accordingly, we hypothesize the need for personalizable customizable Trust Management Systems (TMSs) for the robustness and wide-scale adoption of large-scale marketplaces for resources and services. In other words, we assume the need for a trust management system which can select services satisfying transaction parties’ requirements. Most contemporary TMSs suffer from the following drawbacks: • Select one size fits all service, • Utilize one and only one type of data for calculating the score used for anticipating the future behavior of a party, • Utilize one and only one method to calculate the score value used for anticipating the future behavior of a party, • Trust scoring calculation method does cannot be reprogrammed, • Trust scoring calculation method does not consider the context in which the data was collected. Given these drawbacks and the large scale of the global marketplace of resources and services, a reference architecture for trust management systems is needed, which can incorporate current systems and may be used in guidance and development of a wide spectrum of trust management systems ranging from un-personalized to fully personalized systems. Up to our knowledge, no TMS reference architecture exists in the literature. In this dissertation, we propose a new Reference Architecture for Trust Management (RATM), which overcomes the drawbacks of current systems. It proposes evaluating trust by number of flexible operations namely, decision expectation, analytics, data management and monitoring. These operations collectively can be used to implement a wide spectrum of trust management systems ranging from generic to highly personalized systems. We used RATM for trust personalization, where we propose a Personalized Trust Management System (PTMS) based on RATM. We evaluated PTMS’s ability to sustain the increasing number of users and demonstrated its effectiveness, efficiency and its ability to resist attacks. We achieved that by contrasting experimentation results against that of a Generic Trust Management System (GTMS). We used two case studies for our evaluations; namely, BitTorrent and a video conferencing application.