In general, at smaller companies, decisions are based on the intuition of their experts within their respective areas. The decision processes are dependent on several aspects, such as assumptions and context, and some on data. Over the last year, the increase in data flow has enabled SMEs to make a decision in a systematic and planned process referred to as data-driven decision-making(DDM). Small-medium enterprises (SME) companies have been affected by enabling aspects. However, research shows challenges for SMEs trying to develop their DDM. To address these challenges, this thesis aims to propose a process to assess and develop data-driven decision-making in an SME within the manufacturing industry. The study has been made with a qualitative approach. In addition, a case study of an SME within the manufacturing industry has been done to study the phenomenon in a real-life situation. The data collection was conducted by a literature review, interviews, and planned and unplanned observations. The literature review showed that different aspects affect the development of DDM. The aspects discussed were the decision-making process, technology and organisational factors such as general change, organisational culture, resistance to change, management and the last aspect, Data quality. A maturity assessment model was discussed to introduce the ability to assess a company's current state. The empirical data discussed two main aspects: the current state and the desired future state. The empirical findings showed that there were three main levels of decision-making in the current state: Operator level, Production level, and Management level. The desired state discusses data expectations, which provides a view of the company's perception of what data is and how it is used. In the analysis, there were two main challenging aspects identified from the empirical and theoretical data, and these were organisational and technological factors. The challenges related to technological factors were identified, such as digital adaptation, technological uncertainties and data quality. The challenges related to Organisational factors were the decision-making process, adaptation to change, organisational culture and data quality. Based on these challenges and the evaluation of the maturity model and application process, a different proposed application process was created to help organisations develop their DDM. Some of the challenges identified within the SME company connect to the challenges found in theory, and they bring future support that these challenges are present in real-life situations. An aspect that was identified as both a technological factor and an organization is the need for data quality and evaluation of it within the organisation. It shows that this is a critical aspect that must be considered when developing DDM.Keywords: Data-driven decision-making, Techno

As the COVID-19 pandemic began in 2019 many businesses and institutions had to start pivoting to remote work and remote studying. Remote work and studying has the ability to significantly alter the way that people are used to carry out their work or studies and, in many cases, have done exactly that. Although the area of remote work and remote studying have been explored and researched on prior to this, the scale at which these changes have taken place and the number of people that are affected is unprecedented. This study aims to identify and understand the technological challenges that university students within computer science experience after having gone through this change of environment. This study also aims to understand and identify what the consequences of these challenges are and how they could be solved or mitigated. To find out what these challenges and their consequences are, this study uses a series of semi-structured interviews with students. Through this series of interviews this paper identifies a range of different challenges belonging to previously identified areas of technological challenges such as internet connectivity, communication software, VPN software, and hardware limitations. The interviews also brought forward technological challenges outside of these areas and allowed the participants to explain in detail what consequences these challenges have had on their remote education and to offer their personal opinions on how these challenges and consequences can be solved. A questionnaire was also sent out to students at Malmö University in order to gain further information regarding both social and technological challenges. The interviews and questionnaire carried out in this study and their results can serve as a foundation for further research and to be of help for individuals, institutions or businesses who are interested in the topic of remote education concerning computer science. Through the questionnaire and interviews carried out in this study it is clear that the majority of challenges that computer science students face are social in nature, although technological challenges still exist. The results of the questionnaire in particular also led to the troubling finding that a majority of students believe that the quality of their education has worsened as a result of remote education. The study also provides a number of recommendations and possible solutions to these challenges

New technology, which has emerged as a part of the new industrial revolution, Industry 4.0, is changing the reality ofmanufacturing companies. Manufacturing companies are perplexed on which technologies to adopt in their productionprocesses, and when is the right time. This can be defined as a company’s ability to prepare for the future, andespecially, for these future technological challenges. A large part of being able to adopt these technologies into theproduction processes is related to the company’s ability to be innovative in their production processes. This is known asprocess innovation. Therefore, this thesis investigates how a production unit within a manufacturing company canmanage process innovation to prepare for future technological challenges. This purpose has been achieved by conducting a single case study, where the case company’s process innovation abilitieswere assessed, and combined with necessary tools to prepare the case company for the future. The case company chosenfor this thesis was Scania. They are a world-leading manufacturer of heavy trucks, buses, and engines. The case studyfocused on one of their productions units, which produce gearboxes and axles. The data for the study was collectedthrough qualitative interviews with members of the case company. The results indicate that the case company needs toimprove their process innovation abilities in order for them to be able to adopt new technologies in their productionprocess. They need a definition of innovation, and a strategy that includes innovation so that it is prioritized andviewed as important. Furthermore, management needs to encourage innovation, and increase their level of risk-taking sothat the culture of the case company is compatible with innovation. Finally, the results show that the case companymay need to redefine or reconsider their fundamental management principle “continuous improvement” to further givepriority to innovation in their production process. Furthermore, an overview of the necessary tools for preparing for thefuture are also covered. These are trend analysis, scenario planning, benchmarking, and technological roadmap. Usingthese four tools can help the company when making strategic decisions about the implementation of new technologies. Finally, this thesis contributes to science by providing empirical research on the topic of process innovation and gives aninteresting perspective on how it can be used to prepare for the future.

Higher education institutions in Barbados have introduced blended learning as a strategy to improve students' academic performance and achievement. Despite the implementation of blended learning, the poor student performance and outcomes persist. The purpose of this qualitative case study was to explore how teaching processes and practices at the institution have influenced blended learning to improve student achievement. A social constructivist framework was used to guide the study. The research question addressed the practices and processes used by teachers to increase student learning and performance in a blended learning environment. Data collection involved semistructured interviews with 6 teachers from the study site. Lean coding analysis yielded 4 themes: student engagement, student success, pedagogical and technological challenges, and teacher professional development. Findings were used to create a teacher professional development program for local stakeholders with an emphasis on pedagogical best practices and processes for creating and sustaining an effective blended learning environment. Findings may be used to improve student engagement and academic success at the study site.