Studien behandlar fenomenet personaliserad marknadsföring, som har avancerats i dess tillämpning på senare år och har kommit att bli en hyperanpassad upplevelse för mottagaren. Individens informationsutlämnande är centralt för företagens möjlighet att tillämpa marknadsföringsstrategin och därav har det konstaterats att det finns både fördelar och risker med personaliserad marknadsföring, vilket belyses av personalisering- och integritetsparadoxen. Studiens syfte är att undersöka vilken påverkan identifierade fördelar och risker med informationsutlämnande har på konsumentens upplevda värde av personaliserad marknadsföring samt hur en tidigare positiv respektive negativ varumärkesimage kan påverka det upplevda värdet. En enkätundersökning används som forskningsmetod och vid dataanalys tillämpas stegvis modellering samt multipel linjär regressionsanalys. Resultatet visar att preferensmatchning, söktid och positiv varumärkesimage har en positiv påverkan på upplevt värde medan personlig integritet har en negativ påverkan. Därav accepteras hälften av studiens hypoteser. Slutsatsen är att marknadsföring som är anpassad efter konsumentens intressen och preferenser har störst påverkan på konsumentens upplevda värde av personaliserad marknadsföring samt att en tidigare positiv varumärkesimage har en positiv påverkan på det upplevda värdet.

Digital marketing is constantly adapting and evolving in line with technological advances. One of these advances is the digitalization, which has given rise to Programmatic Advertising (PA). In order to practice PA, the companies need to collect data about consumers' preferences and personal interests. On the other hand, consumers have a need to protect their privacy. The needs of these two parties cross each other which creates the tension, called the Personalization-privacy paradox. In this study, we intend to investigate consumers' attitudes towards PA and whether personalization gives rise to improved browsing experiences or evenviolates their privacy. A quantitative study was conducted, where the independent variable was called Personalization and the dependent variables - Attractiveness, Annoyance, Invasiveness and Trade-off. The results of bivariate regression analysis showed that all of the dependent variables of the study were statistically significant. The results also illustrated that the majority of the respondents experienced PA ads as beneficial, but also invasive. These results are in line with the Utility maximization theory, as PA ads were considered both beneficial and risky. Therefore, consumers would have incentives to disclose their personal information as long as the percieved benefits would outweigh perceived risks, generated by PA. We concluded that there are no clear, predetermined answers to what attitudes consumers have towards PA, but this can vary from case to case, which is in line with both the Privacy calculus theory and the Utility maximization theory. This involves a risk-benefit analysis, performed by consumers, where perceived benefits exceeding perceived risks would generate positive attitudes and vice versa

Yes / Location-based advertising is an entrepreneurial and innovative means for advertisers to reach out through personalised messages sent directly to mobile phones using their geographic location. The mobile phone users' willingness to disclose their location and other personal information is essential for the successful implementation of mobile location-based advertising (MLBA). Despite the potential enhancement of the user experience through such personalisation and the improved interaction with the marketer, there is an increasing tension between that personalisation and mobile users' concerns about privacy. While the privacy calculus theory (PCT) suggests that consumers make privacy-based decisions by evaluating the benefits any information may bring against the risk of its disclosure, this study examines the specific risks and benefits that influence consumers' acceptance of MLBA. A conceptual model is proposed based on the existing literature and a standardised survey was developed and targeted at individuals with known interests in the subject matter. From these requests, 252 valid responses were received and used to evaluate the key benefits and risks of MLBA from the users' perspectives. While the results confirmed the importance of internet privacy concerns (IPC) as an important determinant, they also indicate that monetary rewards and intrusiveness have a notably stronger impact on acceptance intentions towards MLBA. Intrusiveness is the most important risk factor in determining mobile users' intentions to accept MLBA and therefore establishing effective means of minimising the perceived intrusiveness of MLBA can be expected to have the greatest impact on achieving effective communications with mobile phone users.

This research explores the role of blockchain technology in advanced information sharing systems with the applications of energy systems and healthcare. Essay 1 proposes a blockchain application to improve resilience in smart grids by addressing cyber security and peer-to-peer trading potentials. The results show that blockchain-based smart contracts are positively related to smart grid resilience. The findings also show that blockchain-based smart contracts significantly contribute to zero trust cybersecurity, which results in a better capability to mitigate cyber-attacks. Essay 2 proposes a blockchain application to improve electronic health record (EHR) systems by increasing patient's empowerment. Confirmatory factor analysis is used for the validity and reliability tests of the model. The results show that blockchain-based information systems can empower patients by providing the perception of control over their health records. The usage of blockchain technology motivates patients to share information with healthcare provider systems and has the advantage of reducing healthcare costs and improving diagnosis management. Essay 3 contributes to the existing literature by using a multimethod approach to propose three new mediators for blockchain-based healthcare information systems: digital health care, healthcare improvement, and peer-to-peer trade capability. Based on the findings from the text analysis, we propose a research model drawing upon stimulus-organism-response theory. Through three experimental studies, we test the research model to explain the patient's willingness to share their health records with others, including researchers. A post hoc analysis is conducted to segment patients and predict their behavior using four machine learning algorithms. The finding was that merely having peer-to-peer trade capability by ignoring healthcare improvement does not necessarily incentivize patients to share their medical reports.