Die effiziente Nutzung beschränkter Kapazitäten (z.B. Flugzeugplätze, Hotelzimmer) erweist sich für Anbieter als kritischer Erfolgsfaktor. Zur Steuerung der Buchungsanfragen wird daher Revenue Management angewandt. Um langfristig profitable Kundenbeziehungen aufzubauen, sollten auch kundenwertbezogene Informationen (den langfristigen Wert des Kunden für den Anbieter repräsentierend) einbezogen werden. In der Folge sieht sich der Anbieter vielen Unsicherheiten gegenüber. Da die Berücksichtigung von Unsicherheiten die Effizienz der Steuerungsentscheidungen und damit die Erlöshöhe beeinflusst, widmet sich die Dissertation zunächst der Analyse und Systematisierung der unsicherheitsbasierten Problemfelder und nachfolgend der Erweiterung traditioneller Steuerungsmethoden, die in Simulationsstudien evaluiert werden. Die Intention des Beitrags ist es, das Forschungsvorhaben in seiner Zielstellung und Methodologie nachvollziehbar darzulegen.

abstract: The greatest challenge facing humanity in the twenty-first century is our ability to reconcile the capacity of natural systems to support continued improvement in human welfare around the globe. Over the last decade, the scientific community has attempted to formulate research agendas in response to what they view as the problems of sustainability. Perhaps the most prominent and wide-ranging of these efforts has been sustainability science, an interdisciplinary, problem-driven field that seeks to address fundamental questions on human-environment interactions. This project examines how sustainability scientists grapple with and bound the deeply social, political and normative dimensions of both characterizing and pursuing sustainability. Based on in-depth interviews with leading researchers and a content analysis of the relevant literature, this project first addresses three core questions: (1) how sustainability scientists define and bound sustainability; (2) how and why various research agendas are being constructed to address these notions of sustainability; (3) and how scientists see their research contributing to societal efforts to move towards sustainability. Based on these results, the project explores the tensions between scientific efforts to study and inform sustainability and social action. It discusses the implications of transforming sustainability into the subject of scientific analysis with a focus on the power of science to constrain discourse and the institutional and epistemological contexts that link knowledge to societal outcomes. Following this analysis, sustainability science is repositioned, borrowing Herbert Simon's concept, as a "science of design." Sustainability science has thus far been too focused on understanding the "problem-space"--addressing fundamental questions about coupled human-natural systems. A new set objectives and design principles are proposed that would move the field toward a more solutions-oriented approach and the enrichment of public reasoning and deliberation. Four new research streams that would situate sustainability science as a science of design are then discussed: creating desirable futures, socio-technical change, sustainability values, and social learning. The results serve as a foundation for a sustainability science that is evaluated on its ability to frame sustainability problems and solutions in ways that make them amenable to democratic and pragmatic social action. / Dissertation/Thesis / Ph.D. Sustainability 2011

I ett ständigt åldrande samhälle har Sveriges kommuner ideligen utvecklat äldreomsorgen genom välfärdsteknologin, och i synnerhet inom IKT. Denna studie handlar om hur man designar en mockup prototyp till en applikation som riktar sig till att hjälpa äldre människor. Tanken med applikationen "I’m here" är att vara ett digitalt verktyg inom den svenska äldreomsorgen: hemtjänsten - där äldre personer kan använda den för att annonsera/fråga om hjälp. Genom en process av crowdsourcing kan registrerade arbetstagare svara på förfrågningarna och hitta den äldre personen genom sin position på kartan. Genom ett Design Science- tillvägagångssätt gjordes en första mockup prototyp enligt teorin om Pervasive Information Architecture, och evaluerades av 18 äldre deltagare mellan 68-86 år. Deltagarnas design-önskemål implementerades i den andra mockup prototypen. Resultaten av evalueringen kan anses som grundläggande och allmän fast de är kontextuella och hör till en mockup prototyp av en specifik applikation, kan den producerade kunskapen betraktas som grundläggande och allmän. Denna studie bidrar också med idén om en potentiell applikation "I’m here". Ytterligare forskning är nödvändig för att genomföra större studier om design för äldre personer. Detta skulle också bidra till en fullständig utveckling av applikationen "I’m here". / In an ever aging society, Sweden’s municipalities have steadily developed elderly health care through welfare technologies, and within ICT in particular. This study is about how to design a mockup prototype to a mobile application that is targeted towards helping elderly people. The idea of the application ‘I’m here’ is to be a digital tool within the Swedish elderly care ‘hemtjänsten’, where elderly persons are able to use it to announce a request for help. Through a process of crowdsourcing, registered workers are able to answer the requests and find the elderly person by his/her position on the map. Through a Design Science approach, an initial mockup prototype was made according to the theory of Pervasive Information Architecture, and was evaluated by 18 elderly participants between the ages of 68-86. Their design evaluations were considered and implemented in a second mockup prototype. The results are contextual and belong to a mockup prototype of a specific application, the produced knowledge can be considered foundational and general. This study also contributes to the idea of a potential application ‘I’m here’. Further research is need to conduct larger studies on design for elderly persons. Also, this would contribute to the full development of the application ‘I’m here’.

Cybersecurity professionals are in high demand, but the definition of individual interests and the functions that comprise those roles is more complex than it may seem. In the face of a global shortage of cybersecurity professionals, and an often-difficult team dynamic around these individuals, in addition to a dramatic rise in cybercrime and security breaches, it is important to define and understand career success and career performance within an organization. This research uses a design science approach founded on a sociotechnical theoretical framework based on Information Technology (IT) turnover and Human Resources (HR) theories to analyze individual factors of job satisfaction and job performance for cybersecurity roles to design a cybersecurity interest to function career alignment model through the integration of prominent indicators of individual interest. This is accomplished using a mixed methods approach of surveys, interviews, and a focus group that are employed using various techniques of visual, descriptive, correlation, and thematic analysis. Two key findings within this research involves cybersecurity roles and functions and the ability to align an individual's personal interests to those roles. In the former case, cybersecurity roles are poorly defined and are prone to widespread ambiguity, requiring the design of a taxonomy of discrete functions for analysis. In the latter case, individual interests, as analyzed through popular individual profiling solutions are vague and largely irrelevant to cybersecurity professionals. This requires that individual interests be defined and applied to relevant industry functions to provide meaningful alignment to job satisfaction and job performance. Among the implications for IT Turnover Theory, is the refined attribution of individual interests within cybersecurity roles instead of a monolithic interpretation of cybersecurity professionals as a single factor. This is also true for the Intermediate Linkages Model as the job satisfaction-turnover relationship may be further refined to include industry-specific functions for cybersecurity functions and the specific interests of cybersecurity professionals. The implications for design science research could extend beyond the usage of standard guidelines, venturing into this study's process of using design challenges to illuminate hidden design principles. This challenge-principle relationship may provide additional insight to new or existing facets of reasoning. These new viewpoints may uncover otherwise excluded aspects that provide additional insight into this study or topics beyond. For cybersecurity and human resources practitioners, this study provides several implications beyond the foundation for career training for functional guidance. It provides an alternative viewpoint on organizational and departmental design for cybersecurity to business alignment to increase individual job satisfaction and ultimately improve organizational performance. Future research would result in deployed artifact instantiations that promotes general career direction for future and current cybersecurity personnel, while also providing additional guidance to organizations for the proper deployment of cybersecurity teams. Other research could include IT careers beyond cybersecurity to create a standardized method for the alignment of interests to career functions for the improvement of individual job satisfaction and overall organizational performance. / Thesis (PhD (Information Technology))--University of Pretoria, 2020. / Informatics / PhD (Information Technology) / Unrestricted

Complexity and uncertainty have long been problems for organizations of all types. Organizational members do not do a very good job of dealing with the complexity and uncertainty as research shows that when faced with complex situations humans often turn to the same sources of information repeatedly (a practice that will eventually betray them), and/or reduce the amount of scanning that they do (Weick 1995; Boyd and Fulk 1996). Organizations often turn to information systems to help them deal with the complexity, but they often take a techno-centric view of knowledge that does not incorporate the human qualities needed for unstructured decisions (Malhotra 1997; Courtney 2001; Malhotra 2001). Additionally, there are times when the information systems that we are using may hinder the processes of dealing with the complexity (Weick and Meader 1993). Weick's (1995) concept of sensemaking is believed to help us to deal with this complexity. In his work with Meader (1993) he wonders what the effects of a sensemaking support system would have, but he does not have the answer because they state that it has not been asked. This dissertation answers the call of Weick and Meader as well as other scholars that have called for sensemaking and human intuition to be included in our information systems. This is accomplished by viewing sensemaking from an inquiring systems perspective (Churchman 1971) to develop a kernel theory that will be used in the context of design science to develop design requirements and principles for a sensemaking system. These design principles are then used to build an instantiation of the system in the form of SenseMan, a system designed to help a local government agency deal with complexity in the context of software updates. Finally the design is evaluated for its effectiveness in dealing with the complexity of in this context using both quantitative and qualitative methods.

Artificial intelligence (AI) has made astonishing breakthroughs in recent years and achieved comparable or even better performance compared to humans on many real-world tasks and applications. However, it is still far from reaching human-level intelligence in many ways. Specifically, although AI may take inspiration from neuroscience and cognitive psychology, it is dramatically different from humans in both what it learns and how it learns. Given that current AI cannot learn as effectively and efficiently as humans do, a natural solution is analyzing human learning processes and projecting them into AI design. This dissertation presents three studies that examined cognitive theories and established frameworks to integrate crucial human cognitive learning elements into AI algorithms to build human learning–augmented AI in the context of text analytics. The first study examined compositionality—how information is decomposed into small pieces, which are then recomposed to generate larger pieces of information. Compositionality is considered as a fundamental cognitive process, and also one of the best explanations for humans' quick learning abilities. Thus, integrating compositionality, which AI has not yet mastered, could potentially improve its learning performance. By focusing on text analytics, we first examined three levels of compositionality that can be captured in language. We then adopted design science paradigms to integrate these three types of compositionality into a deep learning model to build a unified learning framework. Lastly, we extensively evaluated the design on a series of text analytics tasks and confirmed its superiority in improving AI's learning effectiveness and efficiency. The second study focused on transfer learning, a core process in human learning. People can efficiently and effectively use knowledge learned previously to solve new problems. Although transfer learning has been extensively studied in AI research and is often a standard procedure in building machine learning models, existing techniques are not able to transfer knowledge as effectively and efficiently as humans. To solve this problem, we first drew on the theory of transfer learning to analyze the human transfer learning process and identify the key elements that elude AI. Then, following the design science paradigm, a novel transfer learning framework was proposed to explicitly capture these cognitive elements. Finally, we assessed the design artifact's capability to improve transfer learning performance and validated that our proposed framework outperforms state-of-the-art approaches on a broad set of text analytics tasks. The two studies above researched knowledge composition and knowledge transfer, while the third study directly addressed knowledge itself by focusing on knowledge structure, retrieval, and utilization processes. We identified that despite the great progress achieved by current knowledge-aware AI algorithms, they are not dealing with complex knowledge in a way that is consistent with how humans manage knowledge. Grounded in schema theory, we proposed a new design framework to enable AI-based text analytics algorithms to retrieve and utilize knowledge in a more human-like way. We confirmed that our framework outperformed current knowledge-based algorithms by large margins with strong robustness. In addition, we evaluated more intricately the efficacy of each of the key design elements. / Doctor of Philosophy / This dissertation presents three studies that examined cognitive theories and established frameworks to integrate crucial human cognitive learning elements into artificial intelligence (AI) algorithm designs to build human learning–augmented AI in the context of text analytics. The first study examined compositionality—how information is decomposed into small pieces, which are then recomposed to generate larger pieces of information. Design science research methodology has been adopted to propose a novel deep learning–based framework that can incorporate three levels of compositionality in language with significantly improved learning performance on a series of text analytics tasks. The second study went beyond that basic element and focused on transfer learning—how humans can efficiently and effectively use knowledge learned previously to solve new problems. Our novel transfer learning framework, which is grounded in the theory of transfer learning, has been validated on a broad set of text analytics tasks with improved learning effectiveness and efficiency. Finally, the third study directly addressed knowledge itself by focusing on knowledge structure, retrieval, and utilization processes. We drew on schema theory and proposed a new design framework to enable AI-based text analytics algorithms to retrieve and utilize knowledge in a more human-like way. Lastly, we confirmed our design's superiority in dealing with knowledge on several common text analytics tasks compared to existing knowledge-based algorithms.

Databases store data electronically, and the data can be both sensitive and nonsensitive. The more sensitive the data is, the more secure the database needs to be. Data for different national security organizations is considered to be extra sensitive, and protecting this data is very important because a leak could affect national security. It is easy to implement more security measures for databases, but every new security implementation should be carefully considered in terms of how much it affects work efficiency with the database. The purpose of this study is to find security implementations for a database with the help of theories, previous research, and data collections. These security implementations should be sufficient for a database that stores data for national security organizations. The study resulted in a prototype consisting of a limited database with hypothetical security implementations. The implementations assigned to the database were based on theories, previous research, and data from interviews. The proposed implementations were perceived by the respondents as not negatively affecting work efficiency with the database.

Utveckling av planeringssystem är ett komplext designproblem som kräver både en hög grad av flexibilitet men även struktur. I samband med planering är det ett flertal aktörer, aktiviteter och resurser som måste beaktas. Kunnandet när det gäller planering finns ofta koncentrerad till ett fåtal nyckelpersoner. Det är därför ingen tillfällighet att många företag, organisationer och även universitet idag bedriver sin planering i beprövade enanvändarsystem som Excel fast att det finns starkt behov för standardiserat fleranvändarsystem. Uppsala universitet är inget undantag trots dess storlek med över 40 000 studenter, 6 200 anställda, 130 utbildningsprogram och 2000 fristående kurser. Kursplaneringen bedrivs med hjälp av enanvändarsystem där man är beroende av ett antal nyckelpersoner för att planeringen skall fungera. Uppsatsens syfte är att undersöka och belysa den problematik som finns i samband med utveckling av planeringssystem genom att utveckla en prototyp för ett kursplaneringssystem. Den forskningsstrategi som används är Design Science och den utvecklingsmetodik som används är Scrum. Prototypen har utvärderats regelbundet under utvecklingen genom formativ utvärdering. Uppsatsens kunskapsbidrag utgörs av metodkunskap som visar hur Scrum och Design Science kan kombineras samt modellkunskap som visar den grundläggande strukturen för ett kursplaneringssystem. / Development of planning system is a complex design problem that requires both a high degree of flexibility but also structure. In the context of planning, there are several actors, activities and resources that must be considered. Expertise in planning is often concentrated in a few key individuals. It is therefore no coincidence that many businesses, organizations and even universities currently conducts its planning in proven single-user system like Excel even though there is a strong need for standardized multi-user system. Uppsala University is no exception, despite its size, with over 40,000 students, 6,200 employees, 130 programs and 2000 courses. Course planning is conducted using single-user system and which is dependent on a number of key individuals to plan to work. The essay aims to investigate and illustrate the problems that are associated with the development of the planning system by developing a prototype of a course scheduling system. The research strategy used is Design Science and the development methodology that is used is Scrum. The prototype has been evaluated regularly during development through formative evaluation. The essays knowledge contribution is methodological knowledge that shows both how Scrum and Design Science can be combined and model knowledge, which shows the basic structure of a course scheduling system.

Im Zuge der zunehmenden Digitalisierung von Unternehmens- und Finanzdaten war es ein Industriekonsortium, das auf Basis der eXtensible Markup Language (XML) die Sprache eXtensible Business Reporting Language (XBRL) entwickelte und damit die Finanzberichterstattung in ein neues Zeitalter versetzte. Internetbasiert, plattform-unabhängig, vergleichbar, transparent und in Echtzeit sollen Geschäftsdaten mittels der XBRL übertragen werden und zur Verfügung stehen. Die kumulative Dissertation untersucht dazu den Spannungsbogen zwischen Flexibilität und Automatisierbarkeit im Rahmen der XBRL-basierten Finanzberichterstattung. Neben der wissenschaftstheoretischen Auseinandersetzung mit Standards gibt die Dissertation einen systematischen Überblick von wissenschaftlichen Publikation zur XBRL-Forschung. Im Detail erbringt die Arbeit einen umfassenden und systematischen empirischen Nachweis zur Verwendung von erweiterten Berichtskonzepten sowie den empirischen Nachweis der Ausprägungen von einzelnen Konflikttypen in XBRL-basierten Finanzberichten und erweitert somit die bestehende wissenschaftliche Literatur um die gewonnenen Ergebnisse und Erkenntnisse. Die darauf aufbauende Methode steigert die Vergleichbarkeit der Finanzberichte und verwendet Techniken, welche Konflikte erkennen und diese nach Konflikttypen unterscheiden. Gleichzeitig werden die Möglichkeiten und Grenzen der Arbeit verdeutlicht und zukünftige Forschungsthemen aufgeführt.

À STMicroelectronics, l'équipe de Business Intelligence est confrontée à exploiter quotidiennement des données et des informations pour créer des rapports d'activité afin de superviser la production. Dans une telle organisation industrielle, les produits changent régulièrement et les données peuvent rapidement devenir obsolètes. Par conséquent, au fil du temps, le nombre de rapports crées est de plus en plus important, tandis que les connaissances sur leur création sont perdues. Ceci est illustré dans une évaluation qualitative et quantitative de la partie principale du système de connaissances à STMicroelectronics.Ainsi, des problèmes d'obsolescence, de duplication, de non-centralisation et de prolifération continuent à surgir. Ce travail doit, donc, répondre à la question de recherche générale suivante:Comment assurer une capitalisation continue des connaissances métier?Pour répondre à cette question, un cycle d'amélioration continue pour la capitalisation des connaissances est proposé. Son objectif est de capitaliser efficacement et en permanence les connaissances, tout en ciblant les besoins métier et assurant une solution évolutive. Un système de Business Intelligence pour la Business Intelligence (BI4BI) est proposé. Comme la connaissance est intégrée non seulement dans les systèmes et les outils, mais aussi détenue par les humains et leurs pratiques, notre solution de capitalisation de connaissances proposée implique aussi les utilisateurs et les organisations: elle propose de recueillir les points de vue des utilisateurs pour les intégrer dans la représentation des connaissances et dans notre système BI4BI. / At STMicroelectronics, the Business Intelligence team is daily confronted to exploit data and information to create reports about manufacturing activities in order to supervise it. In such an industrial organization, products change regularly and data can quickly become obsolete. Consequently, over time, the number of created reports is highly growing, while knowledge about their creation is lost. This is shown in a qualitative and quantitative evaluation of the main part of the STMicroelectronics' knowledge system.As a result, problems related to knowledge obsolescence, duplication, non-centralization and proliferation continuously arise. Therefore, this work addresses the general following research question:How to ensure a continuous expert knowledge capitalization?To answer this question, a continuous improvement cycle for knowledge capitalization is proposed. Its objective is to effectively and continuously capitalize expert knowledge while targeting business needs and providing an evolving solution. It is based on a Business Intelligence for Business Intelligence system (BI4BI). Since knowledge is embedded not only in systems and tools, but also in human minds and practices, our proposed knowledge capitalization solution also involves people and organizations: it proposes to collect users' feedbacks and insights to integrate them in knowledge representation and in our BI4BI tool.