An increased competitive climate has enhanced the importance for companies to differentiate from other companies. Today, the customer support within service organizations are often disregarded as a source of value due to the focus on costs. Further, it has become more important to leverage the contact with the customer at all encounters. New technological advancements within Business Intelligence have also enabled companies to increase their competitiveness through improved decision support. The objective of this thesis is through a case study investigate how an insurance company could leverage its customer support as a source of creating shareholder value as well as how to apply trends within Business Intelligence for increased decision support. This was done through developing a conceptual model based on academic theory in order to provide a tool for analysis and development of a customer support. The research questions intends to investigate how an customer support can contribute to, and balance a focus on service quality, costs and sales in order to enhance shareholder value. A business driven approach was further used in order to understand how a customer support could leverage the emerging trends of Business Intelligence. This since the thesis also aims to provide some first insights into how to leverage the trends of mobile- and Self-Service- Business Intelligence within the customer support within insurance companies. The research emphasizes the need to have a holistic view of what drives value and costs with regard to the retention, growth and acquisition of customers when viewing the customer support as a source of value. The thesis concludes that both the trends of mobile- and Self-Service- Business Intelligence could enable an insurance company to gain new insights through utilizing existing internal as well as external data in order to conduct a more continuous and flexible analysis of important matters. / Insurance industry, Customer Support, Call-Centre, Business Intelligence, Self-Service Business Intelligence, Mobile Business Intelligence, Shareholder Value, Value creation, Value drivers, Lean Service, Systems Thinking, Strategic Management, Operational Strategy, Outside-in thinking, Performance Management, Customer Retention, Customer Satisfaction, Service Quality.

Humankind is becoming increasingly dependent on algorithms in their everyday life. Algorithmic decision support has existed since the entrance of computers but are becoming more sophisticated with elements of Articial Intelligence (AI). Though many decision support systems outperform humans in many areas, e.g. in forecasting task, the willingness to trust and use algorithmic decision support is lower than in a corresponding human. Many factors have been investigated to why this algorithm aversion exists but there is a gap in research about the eects of scenario characteristics. Results provided by this study showed that people prefer recommendations from a human expert over algorithmic decision support. This was also re ected in the self-perceived likelihood of keeping a choice when the decision support recommended the other option, where the likelihood was lower for the group with human expert as the decision support. The results also showed that the decision supports, regardless of type, are more trusted by the user in an acquisition framed scenario than in a forfeiture framed. However, very limited support was found for the hypothesized interaction between decision support and scenario type, where it was expected that algorithm aversion would be stronger for forfeiture than acquisition scenarios. Moreover, the results showed that, independent of the experimental manipulations, participants with a positive general attitude towards AI had higher trust in algorithmic decision support. Together, these new results may be valuable for future research into algorithm aversion but must also to be extended and replicated using dierent scenarios and situations.

In recent years emphasis has been placed on opening up governments and empowering and engaging citizens in governmental activities: this view of e-government is referred to as government 2.0. Government 2.0 focuses on governments becoming more transparent, accessible, and responsive, and on governments promoting increased collaboration and participation.  There is also an increasing demand from citizens to interact and gain access to government services through mobile devices. Adopting mobile and wireless technology within the public sector is referred to as mobile government (m-government) and this new phenomenon is expected to become an important part of the development of e-government. By combining government 2.0 and m-government, The Organisation for Economic Co-operation and Development (OECD) and the research community envisages benefits and calls for action within this field. This research answers this call, and addresses the research problem of how to design an m-government solution for complaint and problem management that enables government 2.0. Challenges that inhibit Swedish municipalities from adopting and utilizing such a solution are also identified in this research. Citizens in Sweden can submit complaints and problems concerning a community, such as broken streetlights, to municipalities. By enabling complaints and problems to be reported through mobile devices it facilitates reporting at the point and time of discovery of the issue. Complaint and problem reporting is therefore a suitable m-government service. The m-government solution for complaint and problem management was designed and evaluated within a research project. This compilation thesis builds on and communicates research performed within the research project. By following a design science research methodology, the complaint and problem management solution is designed and evaluated. The solution (Munizapp) comprises a mobile application (app) and an integration platform (ePlatform). The app is the front-end that enables citizens to report complaints and problems to municipalities. The ePlatform facilitates seamless two-way communication between the app and back-end case management system in municipalities. A theoretical evaluation shows that the solution has functionalities that enable all aspects of government 2.0. Additional evaluations indicate evidence of citizens finding the solution valuable and easy to use. There is willingness among municipalities to adopt and utilize the designed m-government solution, but there are challenges that inhibit them from realizing the full potential of the solution. The challenges identified in this research are described and related to business process management and to government 2.0. Future research should investigate how to overcome these challenges.

Generative AI is a hot topic as of 2023, with huge financial investments in the industry. The areas of use for it are rapidly expanding. One potential benefit of generative AI could be in the field of UX design.For this master's thesis, a Stable Diffusion model has been fine-tuned to create pictures of login screens based on text prompts written by a user. A set of these pictures have been used in a prototype and the concept has been evaluated through user tests. The prototype and the concept of using generative AI in UX design received a positive reception from testers. It was established that further work on the fine-tuned model and how to use it as a tool is required for it to be effectively integrated into the design process of user interfaces.

Corporate bankruptcy prediction is an important topic in accounting and finance, having significant relevance for many stakeholders, including investors, creditors, suppliers, and other key entities within the financial ecosystem who have an interest in the financial health of a company. This paper adds to the literature on comparing newer methods with older traditional methods in bankruptcy classification. The study uses a large dataset of American public companies listed on the New York Stock Exchange and NASDAQ, consisting of accounting data from 8,262 different companies spanning the period from 1999 to 2018. Logistic regression, randomForest, XGBoost, and Altman’s Z-Score models are compared with and without the application of SMOTE (Synthetic Minority Oversampling Technique). The results show that the application of SMOTE significantly improves classification accuracy with regard to sensitivity and balanced accuracy for all models. The best performing model is XGBoost with a balanced accuracy of 60.83% without using SMOTE and 70.33% when using SMOTE. The results provide evidence that newer machine learning-based approaches outperform traditional methods and that SMOTE is an effective way to improve model performance.

This paper examines what types of databases that could be useful in clearing house systems, focusing on one of Nasdaq's clearing house systems. To determine this, the reports start by looking at what characteristics are important for the database used in a clearing house system. Based on this information, databases that fit these characteristics, like SQLite, MongoDB, Couchbase lite, and Nasdaq's own database, were used in tests to give an overview of their performances related to both latency and throughput. The test results are then analyzed to determine what database has the best performance under different conditions. This paper concluded that Nasdaq's current database is a good fit for this specific system and that the other databases would most likely not result in the same or similar performances. While the other databases, in general, performed worse compared to the current solution, H2 did have better results in some of the tests.

Calls for more responsible companies, have led to initiatives and legislations of sustainability reporting, in order to improve corporate transparency and accountability regarding companies economic, environmental and social impact. The aim of the research was to explore records roles in corporate sustainability reporting, which is discussed from an archives and information science perspective. Records are regarded as evidence of business activities and therefore crucial to accountability and decision-making processes. A sustainability report is a record, and records are also used to create a sustainability report. The thesis is based on a qualitative explorative methodology with interviews as data gathering technique. Interviews were carried out with four employees at three different companies who work with sustainability reporting, a sustainability consultant who works with sustainability reporting, and an auditor who assesses the  companies´ annual and sustainability reports. The interviews have addressed records’ role in different aspects of sustainability reporting, exploring how sustainability reports are created, used and pluralized. As well as how the records, generated as an effect of the reporting process, are used, what impact they have on the business and efficiency of the process. The thesis also explore respondents´ perspectives on reliability and credibility of the reports in relation to records qualities. Results from the interviews have been analysed with the lens of Records Continuum Model and the ISO standard for records management, ISO 15489-1:2016. Results show that records are key assets that provide evidential information that enables different functions and benefits –both to companies that report and to stakeholders. Primary benefits of the reporting that have been emphasized are that it enables transparency and accountability, informed decision-making, management of risks, compliance with legislation, ability to demonstrate corporate responsibility and meeting sustainability goals, greater business efficiency, evidence-based analysis and development activities, formation of business culture and identity, and protection of corporate and collective memory about the corporates’ work regarding sustainability. Records are also valuable assets for governance and continuous improvements. It enables to monitor trends and assessment on how the company meets its targets. The thesis gives an increased understanding of records’ role in a socio-economic context. It also suggests some areas for further research and development in order for sustainability reporting to further support a sustainable development. One of the major tasks would be to make pluralization of sustainability-related records more efficient, in order to facilitate further utilization of the information. This may enhance corporate accountability and decision making based on sustainability criteria, and would make the work more efficient for companies. The global records governance environment can be improved further, in order to support  global sustainable development. Important is also to raise awareness about the role of trustworthy records.

How do air traffic controllers, or ATCos, distribute visual attention and can it vary between controllers? In this study, using primarily eye-tracking data and a couple of on-site interviews, these questions are explored. Two ATCos, with the most similar landings, had their eye-movements recorded with Tobii pro glasses 2 and further analysed by categorizing every fixation into different areas of interest during four landings. Two more ATCos were interviewed briefly during an observational visit to the control tower. The results showed that the ATCos distributed their attention fairly equally between the outside of the control tower and the inside. When attending to something outside the runway was the focus and when attention was inside the control tower the radar was usually the focus. The ATCos differed in their attention distribution by the presumably more experienced ATCo distributing their attention more outside the control tower than the presumably less experienced ATCo.  A large number of fixations were not categorized bringing the method of dividing the ATCos eye-tracking view into areas of interest into question.

There is currently little research about how the aesthetics of a game affects the perceived PX. Especially, the aesthetics of the individual 3D game components, such as characters, enemies and environmental objects. This thesis project studies different design principles and approaches to create 3D game components. These are used in practice to create 3D game components for a video game. The 3D game components are evaluated with qualitative and quantitative methods, with the intention to find a method for creating 3D game components that evoke a certain PX. The results show that it is possible to create 3D game components that evoke positive emotions, by using color psychology, animation theory and by designing from the developers own feelings and experiences.

Sharing a large amount of data between many mobile devices can lead to scalability problems. One of these scalability problems is that the data becomes too large to store on mobile devices and that many updates are sent to each device. In this thesis, Couchbase is evaluated as a tool to solve this problem where the data has a geographical position. The scalability problem is solved by partitioning the data with the help of Couchbase channels and Google’s tile-based mapping system. Synchronising and storing only data of interest for each user has been in focus. The result showed that it was effective to use a Couchbase solution together with Google’s tile-based mapping system to reduce the amount of data that was required to be stored for each user. It was shown to be more effective to store objects encoded as base64 data instead of their binary data representation for the data set used in this study. The reason for this is because Couchbase stores Binary Large Objects (BLOBs) as separate files and the BLOBs in the data set had much smaller file size than what the disk sector size was. A test to find how the synchronisation time was affected by the number of channels was conducted. It showed that the synchronisation time increased linearly with an increasing number of channels when the objects were stored in separate files. When the objects were encoded as base64 data, the number of channels used had a minor effect on the synchronisation time. The conclusion is that the approach presented in this study has been effective. However, the results are data dependent and therefore it is recommended to rerun similar tests in order to decide the number of channels to use when partitioning the data.