In response to growing concerns over the susceptibility of water distribution systems to contamination, this thesis presents the design and evaluation of an ecological display for an intelligent water monitoring system. Work Domain Analysis and Control Task Analysis were used to uncover the information requirements of the display. The work domain model in this thesis is one of a limited number of such models to include a representation of the automation. The resulting ecological display was evaluated in a comparative usability study against an alternative display based on a competitor’s product. Nine certified water operators participated. The displays were compared across three categories of usability measures: effectiveness, efficiency, and satisfaction. No significant differences were observed. The results, however, helped identify design changes for the display. The implications for the design of intelligent automation displays, and the challenge of designing displays in parallel with early development of automation systems, are discussed.

In response to growing concerns over the susceptibility of water distribution systems to contamination, this thesis presents the design and evaluation of an ecological display for an intelligent water monitoring system. Work Domain Analysis and Control Task Analysis were used to uncover the information requirements of the display. The work domain model in this thesis is one of a limited number of such models to include a representation of the automation. The resulting ecological display was evaluated in a comparative usability study against an alternative display based on a competitor’s product. Nine certified water operators participated. The displays were compared across three categories of usability measures: effectiveness, efficiency, and satisfaction. No significant differences were observed. The results, however, helped identify design changes for the display. The implications for the design of intelligent automation displays, and the challenge of designing displays in parallel with early development of automation systems, are discussed.

Process Automation has the potential to yield great benefits for companies and organizations, especially in the financial services industry where companies are information-intensive and experience rich data flows. This has mostly been done through Robotic Process Automation (RPA), but the increased maturity of Machine Learning algorithms has increased the viability of combining classic RPA with Artificial Intelligence, leading to Intelligent Process Automation (IPA). However, there is a set of challenges embedded in the transition from RPA to IPA. These challenges need to be dealt with in order to ensure that the benefits of the new technology can be harvested. The aim of this research was to identify this set of challenges that the companies will face, as well as provide guidance to what preparations that need to be made before IPA can be implemented in full scale. The research was conducted as a theory building case study at a large Swedish bank. An empirical study was conducted, consisting of interviews with researchers, as well as automation professionals and R&D at the case company. The findings of the empirical study and previous research on the area were combined and condensed into a guiding framework for organizations wanting to adopt IPA. / Processautomation har potentialen att ge stora fördelar för företag och organisationer, speciellt i finansbranschen där företag är informationsintensiva och har stora dataflöden. Detta har huvudsakligen gjorts med Robotic Process Automation (RPA) men den ökade mognadsgraden av maskininlärning har snabbt förbättrat möjligheten att kombinera RPA med Artificiell Intelligens (AI) för att därmed möjliggöra Intelligent Process Automation (IPA). I övergången från RPA till IPA uppkommer däremot en del utmaningar och problem som företag måste hanteras innan potentialen med dessa nya tekniker kan förverkligas. Den här forskningen ämnar att identifiera de utmaningar som företagen kommer ställas inför samt ge vägledning för vilka förberedelser som företagen måste genomföra innan IPA kan implementeras fullskaligt i organisationen. Forskningen genomfördes som en teoribyggande fallstudie på en stor svensk bank. Den teoretiska grunden samlades in genom en omfattande litteraturstudie och en empirisk studie bestående av intervjuer med forskare samt automationsutvecklare och FoU på banken. Resultaten från litteraturstudien och empirin kombinerades och kondenserades till ett vägvisande ramverk för organisationer som vill implementera IPA.

Process Automation has the potential to yield great benefits for companies and organizations, especially in the financial services industry where companies are information-intensive and experience rich data flows. This has mostly been done through Robotic Process Automation (RPA), but the increased maturity of Machine Learning algorithms has increased the viability of combining classic RPA with Artificial Intelligence, leading to Intelligent Process Automation (IPA). However, there is a set of challenges embedded in the transition from RPA to IPA. These challenges need to be dealt with in order to ensure that the benefits of the new technology can be harvested. The aim of this research was to identify this set of challenges that the companies will face, as well as provide guidance to what preparations that need to be made before IPA can be implemented in full scale. The research was conducted as a theory building case study at a large Swedish bank. An empirical study was conducted, consisting of interviews with researchers, as well as automation professionals and R&D at the case company. The findings of the empirical study and previous research on the area were combined and condensed into a guiding framework for organizations wanting to adopt IPA. / Processautomation har potentialen att ge stora fördelar för företag och organisationer, speciellt i finansbranschen där företag är informationsintensiva och har stora dataflöden. Detta har huvudsakligen gjorts med Robotic Process Automation (RPA) men den ökade mognadsgraden av maskininlärning har snabbt förbättrat möjligheten att kombinera RPA med Artificiell Intelligens (AI) för att därmed möjliggöra Intelligent Process Automation (IPA). I övergången från RPA till IPA uppkommer däremot en del utmaningar och problem som företag måste hanteras innan potentialen med dessa nya tekniker kan förverkligas. Den här forskningen ämnar att identifiera de utmaningar som företagen kommer ställas inför samt ge vägledning för vilka förberedelser som företagen måste genomföra innan IPA kan implementeras fullskaligt i organisationen. Forskningen genomfördes som en teoribyggande fallstudie på en stor svensk bank. Den teoretiska grunden samlades in genom en omfattande litteraturstudie och en empirisk studie bestående av intervjuer med forskare samt automationsutvecklare och FoU på banken. Resultaten från litteraturstudien och empirin kombinerades och kondenserades till ett vägvisande ramverk för organisationer som vill implementera IPA.

I följande studie undersöks vad nästa steg i Digital Transformation är för svenska organisationer samt hur deras olika digitala strategi ser ut för att nå dit. Vidare undersöks hur och om dessa digitala strategier arbetar mot FN:s Globala mål som är uttalade genom handlingsplanen Agenda 2030 för hållbar utveckling. Följande studie är relevant eftersom att organisationer har stor möjlighet att bidra till att infria de globala målen genom att inkludera mer hållbarhet i sina arbetssätt. Forskningsfrågan besvaras utifrån en kvalitativ forskningsmetod. Den metod som tillämpas för datainsamlingen i denna studie består av semistrukturerade intervjuer. Följt av en innehållsanalys för att få en djupgående förståelse av intervjudata. Därefter genomfördes en sambandsanalys för att finna samband som kan vara av nytta för studien. Resultatet av studien visar på att respondenterna har liten insikt i Agenda 2030, men att dess strategier har innehåll som kopplas till globala mål. Resultatet visar att organisationer får positiva effekter på både miljö och internt av att implementera globala mål i sin digitala strategi. Framtida forskning kan studera ett bredare urval samt fler aspekter av de globala målen. / The following study examines what the next step in Digital Transformation is for Swedish organizations and what their different digital strategies look like to get there. Furthermore, it examines how and whether these digital strategies work towards the UN's Global Goals, which are stated through the action plan Agenda 2030 for sustainable development. The following study is relevant because organizations have a great opportunity to contribute to fulfilling the global goals by including more sustainability in their working methods. The research question is answered based on a qualitative research method. The method used for data collection in this study consists of semi-structured interviews. Followed by a content analysis to gain an in-depth understanding of the interview data. A correlation analysis was then carried out to find correlations that could be useful for the study. The results of the study show that the respondents have little insight into Agenda 2030, but that its strategies have content that is linked to global goals. The result shows that organizations get positive effects on both the environment and internally by implementing global goals in their digital strategy. Future research could study a wider sample as well as more aspects of the global goals.

We are currently living in a society that is undergoing a rapid digitalization, spurring organizations to adapt and evolve their ways of operating through technology. But is it realistic to accept that all these technological changes come without some form of resistance? Technological resistance is not a new term, tracking back several centuries it is considered to be one of the side-effects that has followed the development of technology. The study utilizes a case study to investigate a department in the swedish public sector that is currently being introduced to intelligent automation (IA). By collecting insights through interviews from the perspectives of essential parties connected to the automation-project, we came to the understanding that the perceptions of a resistance can differ between actors. In this case, the technological resistance boiled down to a fear of technology’s limitations. It also became clear that the organizational form, the implementation, confusion about roles/responsibilities and the system itself were contributing factors to the technological resistance experienced in the case. The study shows the multifacetedness of technological resistance as well as how factors connected to an organization can impact the perception of the phenomenon.

It is argued that the future of the workforce will be ‘humans and machines’ but not ‘humans vs machines’ due to the drift from ‘workforce planning’ to ‘work planning’. Advances in Artificial Intelligence (AI) and its sub-fields have enabled the development of a new form of automation that is described as Intelligent Automation. It is the application of AI in ways that can learn, adapt and improve over time to automate tasks that were formally undertaken by a human. The purpose of this study is to develop a conceptual framework on the necessity of agility within the capital budgeting process for Intelligent Automations, as the traditional approaches ignore the effects of new or disruptive technologies like Artificial intelligence. This study provides advice to managers on the strategic fit of traditional capital budgeting models vs. alternatives like beyond budgeting in the context of Intelligent Automations for knowledge work (consulting, education, etc.) and service work (retail, cleaning, etc.). The approach to conduct this study will be mixed methods. From the outcomes of qualitative analysis through semi-structured interviews, the conceptual framework is formulated. This framework is tested using the survey responses data and quantitative methods. From the preliminary analysis of the pilot study conducted with 7 participants at the c-suite level, the consistent themes that are observed in this phenomenon are a) lack of data for planning due to non-linearity in the resource models in projects where AI is applied, b) use or misuse of the discretionary pool funding model and c) lack of adoption to new ways of working due to organizational climate. The two conflicting themes are the disagreements on ethics council, whether internal vs external and the expectations on human skills that cause the burden of change in large firms. A survey instrument is developed for data collection to analyze the conceptual model, which results from the qualitative study and literature review. A random sample of 217 respondents is chosen during the period from Nov 2020 to Mar 2021. A structural equation modeling (SEM) analysis is applied to investigate the research model. The measurement model is first examined for instrument validity, followed by an analysis of the structural model for testing associations hypothesized by the research model. The main findings show that – a) relationship between intelligent automation and agility in capital budgeting is positively significant b) the relationship between intelligent automation and agility in capital budgeting is negatively moderated by demand unpredictability. These findings provide advice to practitioners and decision-makers that one size fits all capital budgeting models are not recommended for projects with increased levels of intelligent automation. The novel contribution to theory is that ‘Demand unpredictability’ is a useful decision input parameter, which can be counter-intuitive at times when managers allocate capital or prioritize projects during capital budgeting cycles. This suggests that firms need to adapt to hybrid strategies by picking the best-fit approach to allocate capital towards Intelligent Automations or AI projects. It is not necessary to have one size fits all approach for capital budgeting. / Business Administration/Strategic Management / Accompanied by three files: 1) SurveyResponseData -Excel file 2) SPSS Data Analysis Output.spv 3) Data Analysis (all data) (2).Rmd

Geschäftsprozesstechnologien unterstützen dabei, operative Tätigkeiten effizienter und effektiver durchzuführen. In einem sich dynamisch verändernden Umfeld wird es für Organisationen essenziell, diese Technologien gezielt einzusetzen, um durch schnelle Anpassung weiterhin wettbewerbsfähig zu bleiben. Die derzeitige Forschung hat bisher keine Antwort darauf gefunden, wie Organisationen dies trotz ständig wechselnder Umfeldbedingungen und fortschreitender organisationaler Reife durch gezielte Ressourcenallokation erreichen können. Diese Dissertation adressiert diese Forschungslücke, indem untersucht wird, wie organisationale Fähigkeiten mithilfe von Geschäftsprozesstechnologien innerhalb dynamischer Umfelder ausgebildet und erneuert werden können. / Business process technologies help to improve the efficiency and effectiveness of day-to-day operations. Organizations face the challenge of leveraging these technologies to quickly adapt business processes accordingly to cope with different levels of environmental turbulence. From prior research, we know how organizations apply business process technologies and how they affect performance. We do not fully understand how organizations orchestrate related resources based on changing environmental conditions and evolving organizational maturity. This dissertation addresses this research problem and presents research on how to develop and renew organizational capabilities with business process technologies through turbulent environments.