The development of Digital Twin Technology, with a focus on addressing environmental concerns, has elevated the priority of Industry 4.0-based solutions. The study aimed to design a simulation model to optimize the electricity consumption of the electric bus fleet at Arlanda Airport as a subproject of the main Digital Twin project. The study found that there was no current model designed to simulate electricity consumption by formal methods, Z notation.  The research is guided by four primary objectives find power management strategies for e-buses, identify critical parameters affecting their energy consumption, create a Z Notation simulation model, and assess this model. Through a thorough review of the literature and methodical application, power management strategies were defined, and significant energy consumption parameters were identified. The model's usefulness in modelling and optimizing electricity usage was demonstrated by its careful construction using Z Notation and evaluation with Spivey's Fuzz Checker. The paper demonstrates the use of Design Science Research in creating a digital twin-based simulation, which has important implications for transportation systems as well as theoretical advances in simulation methodologies. Throughout the developed Z notations, it provide a proper insight into operational efficiency and sustainability in energy consumption.  The study also emphasizes the drawbacks of using Z Notation, such as its steep learning curve and limited community assistance. To improve the accuracy of electricity consumption forecasts, future research should use predictive analytics and fine-tune the model granularity. The thesis demonstrates how design science can be applied for preparing specification of services but not only in software development. This work lays the groundwork for more extensive applications in digital twin technologies and energy optimization, in addition to contributing to our understanding of e-bus power management at Arlanda Airport.

There are serious security risks with the growing use of IoT devices. Historically, manufacturers prioritized profit over security due to high demand, a perspective that has evolved but remains a challenge. With this, the security of IoT devices has been overlooked, especially regarding smart bulbs, as they tend to be bundled with other IoT devices by the research community, and consequently not receive the attentionthey require. This thesis aims to identify and analyze potential threats regarding smart bulbs, and it does so by exploring proactive strategies in order to mitigate vulnerabilities. To understand the challenges smart bulbs face, some of the current applicable legislation, cyber attacks, defense mechanisms, and vulnerabilities were analyzed. Then, a network topology and a data flow diagram of a home network with smart bulbs was developed. Consequently, layers were assigned to the smart bulb, and threat modeling was performed on a each layer using STRIDE. This procedure was then formalized with a framework that encapsulates the stages of analysing the smart bulb’s landscape through threat modeling. This work contributes to the research community’s body of knowledge by providing valuable insights detailing the smart bulb’s landscape, not only through the framework but also through the conducted threat modeling, the data flow diagrams, and the information gathered regarding the threats to smart bulb security.

<p dir="ltr">In my dissertation, I examine the dynamics of digital platforms, starting with the governance practices of established platforms, then exploring innovative design approaches, and finally the integration of advanced AI technologies in platforms. I structure this exploration into three essays: in the first essay, I discuss moderation processes in online communities; in the second, I propose a novel design for a blockchain-based green bond exchange; and in the third, I examine how AI-based decision-making platforms can be enhanced through synthetic data generation.</p><p dir="ltr">In my first essay, I investigate the role of moderation in online communities, focusing on its effect on users' participation in community moderation. Using data from a prominent online forum, I analyze changes in users' moderation actions (upvoting and downvoting of others' content) after they experience a temporary account suspension. While I find no significant change in their upvoting behavior, my results suggest that users downvote more after their suspension. Combined with findings on lower quality and conformity with the community while downvoting, the results suggest an initial increase in hostile moderation after suspension, although these effects dissipate over time. The short-term hostility post-suspension has the potential to negatively affect platform harmony, thus revealing the complexities of disciplinary actions and their unintended consequences.</p><p dir="ltr">In the second essay, I shift from established platforms to innovations in platform design, presenting a novel hybrid green bond exchange that integrates blockchain technology with thermodynamic principles to address market volatility and regulatory uncertainty. The green bond market, despite its high growth, faces issues like greenwashing, liquidity constraints, and limited retail investor participation. To tackle these challenges, I propose an exchange framework that uses blockchain for green bond tokenization, enhancing transparency and accessibility. By conceptualizing the exchange as a thermodynamic system, I ensure economic value is conserved and redistributed, promoting stability and efficiency. I include key mechanisms in the design to conserve value in the exchange and deter speculative trading. Through simulations, I demonstrate significant improvements in market stability, liquidity, and efficiency, highlighting the effectiveness of this interdisciplinary approach and offering a robust framework for future financial system development.</p><p dir="ltr">In the third essay, I explore the integration of advanced AI technologies, focusing on how large language models (LLMs) like GPT can be adapted for specialized fields such as education policy and decision-making. To address the need for high-quality, domain-specific training data, I develop a methodology that combines agent-based simulation (ABS) with synthetic data generation and GPT fine-tuning. This enhanced model provides accurate, contextually relevant, and interpretable insights for educational policy scenarios. My approach addresses challenges such as data scarcity, privacy concerns, and the need for diverse, representative data. Experiments show significant improvements in model performance and robustness, offering policymakers a powerful tool for exploring complex scenarios and making data-driven decisions. This research advances the literature on synthetic data in AI and agent-based modeling in education, demonstrating the adaptability of large language models to specialized domains.</p>

Im digitalen Zeitalter sind Innovationskraft und eine effiziente Adaption digitaler Technologien für Unternehmen entscheidend, um sich Wettbewerbsvorteile zu sichern. Der Einsatz digitaler Technologien für Innovation verspricht in diesem Zusammenhang nicht nur Produktivitätsvorteile, sondern steigert auch die Kundenzufriedenheit und macht Unternehmen agiler und widerstandsfähiger gegenüber Krisen. Eine zentrale Rolle spielt dabei die Anwendung von Big Data Analytics, jedoch bestehen derzeit erhebliche Forschungsbedarfe, um genauer zu ergründen, wie Big Data Analytics systematisch in Innovationsökosystemen genutzt werden können. Zum einen herrscht ein Mangel an Forschung über die strategischen Beiträge von Big Data Analytics für Innovation, insbesondere im Kontext des Zusammenwirkens verschiedener Akteure. Zum anderen liegt der Fokus bestehender Forschungsarbeiten oft nur auf Teilaspekten der Anwendung von Big Data Analytics und vernachlässigt umfassendere Betrachtungen, aus einer Ökosystem-Perspektive heraus. Für die Praxis liegen die primären Hürden dabei häufig nicht in der Technologie selbst, sondern in deren Adaption innerhalb der wertschöpfenden Strukturen von Unternehmen. Diese Dissertation zielt darauf ab, diese Lücke zu schließen und untersucht die systematische Anwendung von Big Data Analytics in Innovationsökosystemen und nutzt dafür einen Design-Science-Research-Ansatz als übergeordnete Forschungsmethode. Im Dachbeitrag und in den Einzelbeiträgen des kumulativen Dissertationsvorhabens wird dafür gestaltungsorientierte Forschung angewendet, um theoretische Erkenntnisse direkt in die praktische Gestaltung und Entwicklung von Lösungen zu integrieren. Im Ergebnis liefert die Dissertation einen übergeordneten Ordnungsrahmen für die Anwendung von Big Data Analytics in Innovationsökosystemen, der die gesammelten Erkenntnisse aus dem Forschungsprojekt CODIFeY und den Einzelbeiträgen integriert. Damit trägt die Dissertation über den entwickelten Ordnungsrahmen und die IT-Artefakte der Einzelbeiträge dazu bei, ein besseres Verständnis für die strategische Nutzung digitaler Technologien zur Förderung von Innovation und Wettbewerbsvorteilen zu erreichen, was sowohl wissenschaftlich als auch praktisch einen Mehrwert bietet.:Danksagung i Einzelbeiträge iii Inhaltsverzeichnis iv Abkürzungsverzeichnis x Abbildungsverzeichnis xii Tabellenverzeichnis xiv Kurzzusammenfassung 1 Abstract 2 I. Dachbeitrag 3 1 Einleitung 3 1.1 Motivation 3 1.2 Problem- und Fragestellung 5 1.3 Zielstellung 8 1.4 Aufbau des Dachbeitrags 9 2 Forschungsansatz 11 2.1 Wissenschaftstheoretische Grundpositionierung 11 2.2 Forschungsmethode 12 2.2.1 Design Science Research als übergeordnetes Forschungsparadigma 12 2.2.2 Das Projekt Community-basierte Dienstleistungs-Innovation für e-Mobility 14 2.2.3 Aufbau des kumulativen Dissertationsvorhabens 17 3 Stand der Wissenschaft und Forschung 24 3.1 Big Data Analytics 24 3.2 Datengetriebene Innovation 25 3.3 Innovationsökosysteme aus der Perspektive der Service Dominant Logic 27 4 Gestaltung eines Ordnungsrahmens für die Anwendung von Big Data Analytics in Innovationsökosystemen 30 4.1 Das Modell eines Innovationsökosystems aus Sicht der Service Dominant Logic 30 4.2 Ableitung der Dimensionen des Ordnungsrahmens für die Anwendung von Big Data Analytics in Innovationsökosystemen 35 5 Eine Systematisierung von Anwendungsfällen von Big Data Analytics in Innovationsökosystemen 39 5.1 Big Data Analytics als Mittel für Innovation 39 5.2 Big Data Analytics als Ergebnis von Innovation 44 5.3 Demonstration & Evaluation des Ordnungsrahmens 50 6 Fazit 52 II. Research Papers of the Dissertation 55 Paper A – Capturing the Bigger Picture? Applying Text Analytics to Foster Open Innovation 55 A1 Introduction 57 A2 Background and Terminology 60 A2.1 Complexities of Sustainability-Oriented Innovation 60 A2.2 Open Innovation as an Instrument for Participation 62 A2.3 Sustainable-Oriented Innovation and Open Innovation 64 A2.4 Silent Stakeholders 67 A2.5 Research Focus: Text Analytics in Direct Search Methods for Sustainability-Oriented Innovation 69 A3 Action Research Study 72 A3.1 Description of the Action Research Cycle 72 A3.2 Diagnosing the Project Background 73 A3.3 Action Planning and Taking—Application of Text Analytics 77 A4 Results 82 A4.1 Findings from the Overall Discourse Analysis 82 A4.2 Findings from Zooming into Single Topics 84 A4.3 Applicability in the Innovation Process for the Label Development 85 A5 Discussion 87 A6 Implications and Conclusions 88 Paper B – What the Hack? – Towards a Taxonomy of Hackathons 92 B1 Introduction 93 B2 A Process-centric Perspective on Open Innovation and Hackathons 95 B3 Research Approach 97 B3.1 Taxonomy Development 97 B3.2 Literature Review 98 B4 A Taxonomy of Hackathons 101 B4.1 Overview of the Taxonomy 101 B4.2 Strategic Design Decisions 102 B4.3 Operational Design Decisions 104 B5 Discussion 107 B6 Conclusion 109 Paper C – Combining Open Innovation and Knowledge Management in Communities of Practice - An Analytics Driven Approach 110 C1 Introduction 111 C2 Foundations 113 C2.1 Knowledge Management and Innovation 113 C2.2 Communities of Practice 114 C2.3 Analytics domains 114 C3 Research Methodology 117 C4 Conceptual Framework for the Integration of Open Innovation and Knowledge Management 118 C4.1 Conceptual Data Model 119 C5 Implementation & Evaluation of a Pilot Project 122 C5.1 The Research Project CODIFeY 122 C5.2 Evaluation and Preliminary Findings 124 C6 Conclusions 126 Paper D – Entwicklung eines Analytics Framework für virtuelle Communities of Practice 127 D1 Einführung 128 D2 Grundlagen 130 D2.1 Communities of Practice 130 D2.2 Analytics 131 D2.3 Design eines Analytics Frameworks für Communities of Practice 132 D3 Demonstration und Evaluation im Projekt CODIFeY 136 D4 Fazit 138 Paper E – Teaching Data Driven Innovation – Facing a Challenge for Higher Education 139 E1 Introduction 140 E2 Foundations and Theoretical Underpinning 142 E2.1 Data Driven Innovation 142 E2.2 Teaching Data-Driven Innovation 142 E2.3 Pedagogical Approach 143 E3 Research Method 145 E3.1 General Morphological Analysis 145 E3.2 Data Collection and Empirical Analysis 146 E4 Design of the Morphological Box 148 E4.1 Teaching Method 148 E4.2 Course Setting 149 E4.3 Course Content 149 E4.4 Innovation Approach 150 E4.5 Morphological Box for Teaching Data Driven Innovation 151 E5 Teaching Cases 153 E5.1 Case A: Data Driven Value Generation for the Internet of Things 153 E5.2 Case B: Data Driven Innovation Project in the Field of E-mobility 154 E6 Conclusion 156 Paper F – Cross-Disciplinary Collaboration for Designing Data-Driven Products and Services 157 F1 Introduction 158 F2 Foundations and Theoretical Background 161 F2.1 Data Literacy as a Foundation for the Design of Data-Driven Product and Services 161 F2.2 Collaborative Processes and Knowledge Transfer 162 F2.3 Knowledge Boundaries 162 F2.4 Boundary Objects 163 F2.5 Boundary Objects for Collaboration Processes and Knowledge Integration 164 F3 Research Approach 166 F4 Design of the Data Vignette 169 F4.1 Thematic View 169 F4.2 Structural View 173 F5 Evaluation of the Artifact 178 F5.1 Artificial Evaluation Using the Guidelines of Modelling 178 F5.2 Application of the DV - A First Pilot 179 F6 Conclusion 182 Paper G – Towards the Development of a Typology of Big Data Analytics in Innovation Ecosystems 184 G1 Introduction 185 G2 Foundations 187 G2.1 The Role of Technology for Innovation Ecosystems 187 G2.2 Big Data Analytics in Innovation Ecosystems 188 G3 Research Approach 189 G4 Towards a Typology of Big Data Analytics in Innovation Ecosystems 190 G5 Further research 192 Paper H – Hackathons als Gestaltungswerkzeug für plattform-basierte digitale Ökosysteme 193 H1 Einleitung 194 H2 Grundlagen 196 H2.1 Plattform-basierte digitale Ökosysteme 196 H2.2 Hackathons als Gestaltungswerkzeug 197 H3 Forschungsmethode 199 H4 Hackathons für die Gestaltung plattform-basierter Ökosysteme 202 H4.1 Markt-orientierte Plattform-Hackathons 202 H4.2 Technologie-orientierte Plattform-Hackathons 204 H5 Fazit 206 Literaturverzeichnis xv Anhang li Anhang 1 li / In the digital age, the ability to innovate and the efficient adoption of digital technologies are crucial for companies to gain competitive advantages. The use of digital technologies for innovation promises not only productivity gains but also increases customer satisfaction and makes companies more agile and resilient to crises. The focus here is on the application of big data analytics, but there is currently still a considerable need for research to understand how big data analytics can be used systematically in innovation ecosystems. On the one hand, there is a lack of research on the strategic contributions of big data analytics to innovation, particularly in the context of the interaction of various actors. On the other hand, the focus of existing research often only addresses partial aspects of the application of big data analytics and neglects broader considerations from an ecosystem perspective. For practice, the primary hurdles often lie not in the technology itself but in its adaptation within the value-creating structures of companies. This dissertation aims to close this gap and examines the systematic application of big data analytics in innovation ecosystems, using a design science research approach as the overarching research method. In the summary and in the individual papers of the cumulative dissertation project, design-oriented research is used to integrate theoretical insights directly into the practical design and development of solutions. As a result, the dissertation provides an overarching framework for the application of big data analytics in innovation ecosystems, integrating the insights gathered from the CODIFeY research project and the individual contributions. The dissertation on the developed framework and the IT artifacts of the individual contributions contributes to a better understanding of the strategic use of digital technologies to promote innovation and competitive advantages, which offers added value both scientifically and practically.:Danksagung i Einzelbeiträge iii Inhaltsverzeichnis iv Abkürzungsverzeichnis x Abbildungsverzeichnis xii Tabellenverzeichnis xiv Kurzzusammenfassung 1 Abstract 2 I. Dachbeitrag 3 1 Einleitung 3 1.1 Motivation 3 1.2 Problem- und Fragestellung 5 1.3 Zielstellung 8 1.4 Aufbau des Dachbeitrags 9 2 Forschungsansatz 11 2.1 Wissenschaftstheoretische Grundpositionierung 11 2.2 Forschungsmethode 12 2.2.1 Design Science Research als übergeordnetes Forschungsparadigma 12 2.2.2 Das Projekt Community-basierte Dienstleistungs-Innovation für e-Mobility 14 2.2.3 Aufbau des kumulativen Dissertationsvorhabens 17 3 Stand der Wissenschaft und Forschung 24 3.1 Big Data Analytics 24 3.2 Datengetriebene Innovation 25 3.3 Innovationsökosysteme aus der Perspektive der Service Dominant Logic 27 4 Gestaltung eines Ordnungsrahmens für die Anwendung von Big Data Analytics in Innovationsökosystemen 30 4.1 Das Modell eines Innovationsökosystems aus Sicht der Service Dominant Logic 30 4.2 Ableitung der Dimensionen des Ordnungsrahmens für die Anwendung von Big Data Analytics in Innovationsökosystemen 35 5 Eine Systematisierung von Anwendungsfällen von Big Data Analytics in Innovationsökosystemen 39 5.1 Big Data Analytics als Mittel für Innovation 39 5.2 Big Data Analytics als Ergebnis von Innovation 44 5.3 Demonstration & Evaluation des Ordnungsrahmens 50 6 Fazit 52 II. Research Papers of the Dissertation 55 Paper A – Capturing the Bigger Picture? Applying Text Analytics to Foster Open Innovation 55 A1 Introduction 57 A2 Background and Terminology 60 A2.1 Complexities of Sustainability-Oriented Innovation 60 A2.2 Open Innovation as an Instrument for Participation 62 A2.3 Sustainable-Oriented Innovation and Open Innovation 64 A2.4 Silent Stakeholders 67 A2.5 Research Focus: Text Analytics in Direct Search Methods for Sustainability-Oriented Innovation 69 A3 Action Research Study 72 A3.1 Description of the Action Research Cycle 72 A3.2 Diagnosing the Project Background 73 A3.3 Action Planning and Taking—Application of Text Analytics 77 A4 Results 82 A4.1 Findings from the Overall Discourse Analysis 82 A4.2 Findings from Zooming into Single Topics 84 A4.3 Applicability in the Innovation Process for the Label Development 85 A5 Discussion 87 A6 Implications and Conclusions 88 Paper B – What the Hack? – Towards a Taxonomy of Hackathons 92 B1 Introduction 93 B2 A Process-centric Perspective on Open Innovation and Hackathons 95 B3 Research Approach 97 B3.1 Taxonomy Development 97 B3.2 Literature Review 98 B4 A Taxonomy of Hackathons 101 B4.1 Overview of the Taxonomy 101 B4.2 Strategic Design Decisions 102 B4.3 Operational Design Decisions 104 B5 Discussion 107 B6 Conclusion 109 Paper C – Combining Open Innovation and Knowledge Management in Communities of Practice - An Analytics Driven Approach 110 C1 Introduction 111 C2 Foundations 113 C2.1 Knowledge Management and Innovation 113 C2.2 Communities of Practice 114 C2.3 Analytics domains 114 C3 Research Methodology 117 C4 Conceptual Framework for the Integration of Open Innovation and Knowledge Management 118 C4.1 Conceptual Data Model 119 C5 Implementation & Evaluation of a Pilot Project 122 C5.1 The Research Project CODIFeY 122 C5.2 Evaluation and Preliminary Findings 124 C6 Conclusions 126 Paper D – Entwicklung eines Analytics Framework für virtuelle Communities of Practice 127 D1 Einführung 128 D2 Grundlagen 130 D2.1 Communities of Practice 130 D2.2 Analytics 131 D2.3 Design eines Analytics Frameworks für Communities of Practice 132 D3 Demonstration und Evaluation im Projekt CODIFeY 136 D4 Fazit 138 Paper E – Teaching Data Driven Innovation – Facing a Challenge for Higher Education 139 E1 Introduction 140 E2 Foundations and Theoretical Underpinning 142 E2.1 Data Driven Innovation 142 E2.2 Teaching Data-Driven Innovation 142 E2.3 Pedagogical Approach 143 E3 Research Method 145 E3.1 General Morphological Analysis 145 E3.2 Data Collection and Empirical Analysis 146 E4 Design of the Morphological Box 148 E4.1 Teaching Method 148 E4.2 Course Setting 149 E4.3 Course Content 149 E4.4 Innovation Approach 150 E4.5 Morphological Box for Teaching Data Driven Innovation 151 E5 Teaching Cases 153 E5.1 Case A: Data Driven Value Generation for the Internet of Things 153 E5.2 Case B: Data Driven Innovation Project in the Field of E-mobility 154 E6 Conclusion 156 Paper F – Cross-Disciplinary Collaboration for Designing Data-Driven Products and Services 157 F1 Introduction 158 F2 Foundations and Theoretical Background 161 F2.1 Data Literacy as a Foundation for the Design of Data-Driven Product and Services 161 F2.2 Collaborative Processes and Knowledge Transfer 162 F2.3 Knowledge Boundaries 162 F2.4 Boundary Objects 163 F2.5 Boundary Objects for Collaboration Processes and Knowledge Integration 164 F3 Research Approach 166 F4 Design of the Data Vignette 169 F4.1 Thematic View 169 F4.2 Structural View 173 F5 Evaluation of the Artifact 178 F5.1 Artificial Evaluation Using the Guidelines of Modelling 178 F5.2 Application of the DV - A First Pilot 179 F6 Conclusion 182 Paper G – Towards the Development of a Typology of Big Data Analytics in Innovation Ecosystems 184 G1 Introduction 185 G2 Foundations 187 G2.1 The Role of Technology for Innovation Ecosystems 187 G2.2 Big Data Analytics in Innovation Ecosystems 188 G3 Research Approach 189 G4 Towards a Typology of Big Data Analytics in Innovation Ecosystems 190 G5 Further research 192 Paper H – Hackathons als Gestaltungswerkzeug für plattform-basierte digitale Ökosysteme 193 H1 Einleitung 194 H2 Grundlagen 196 H2.1 Plattform-basierte digitale Ökosysteme 196 H2.2 Hackathons als Gestaltungswerkzeug 197 H3 Forschungsmethode 199 H4 Hackathons für die Gestaltung plattform-basierter Ökosysteme 202 H4.1 Markt-orientierte Plattform-Hackathons 202 H4.2 Technologie-orientierte Plattform-Hackathons 204 H5 Fazit 206 Literaturverzeichnis xv Anhang li Anhang 1 li

This thesis explores the design and implementation of an API using the Design Science Research (DSR) methodology, aimed at bridging proprietary systems for sustainable lighting solutions. The project addresses the urgent need to replace mercury-based lamps in Sweden with environmentally friendly alternatives due to upcoming EU regulations. The developed API facilitates integration and automation between two distinct systems controlling lighting and power supply. Key research questions include identifying factors critical for a successful API and assessing its impact on client-specific problems and consequences of web automation. The research begins with identifying core problems through stakeholder engagement, followed by iterative design and development of the API. The solution's objectives were derived from practical constraints and stakeholder feedback, ensuring a focused and relevant artifact. The API was partially demonstrated and evaluated through simulations, theorizing its ability to meet the intended goals and providing insights into good practices for web automation. This work contributes to the field of information systems by providing a practical example of API development through DSR, highlighting the challenges and solutions in web automation and system integration. The findings suggest that a well-designed API relies on understanding end-use cases, good communication with minimal assumption and good adaptability. Relying on web automation can also result in post-release complications or pose ethical dilemmas.

Posters are intended to spark scientific dialogue and are omnipresent at biological conferences. Guides and how-to articles help life scientists in preparing informative visualizations in poster format. However, posters shown at conferences are at present often overloaded with data and text and lack visual structure. Here, I surveyed life scientists themselves to understand how they are currently preparing posters and which parts they struggle with. Biologist spend on average two entire days preparing one poster, with half of the time devoted to visual design aspects. Most receive no design or software training and also receive little to no feedback when preparing their visualizations. In conclusion, training in visualization principles and tools for poster preparation would likely improve the quality of conference posters. This would also benefit other common visuals such as figures and slides, and improve the science communication of researchers overall.

The support and promotion of public Technical and Vocational Education and Training (TVET) Colleges is fundamental in addressing South Africa’s intermediate-level and artisanal skills as shortages in these areas contribute to considerable unemployment in South Africa. These institutions have been earmarked by the South African government for extensive growth. Therefore, efficient and effective management and accurate decision-making within these institutions are essential. The evaluation of the management information systems (MISs) within these institutions, which provide data and information to inform institutional short-term and long-term management decision-making and day-to-day operations, should take place on a regular basis to so enhance the reliability and accuracy of the data and information. The problem is that no evidence of a methodology (artefact) for the evaluation of MISs at public TVET Colleges in South Africa could be found in the literature. Therefore, the rationale for this study is to develop a methodology for the evaluation of MISs at public TVET Colleges in South Africa. Hence the main research question for the study was formulated as: What are the components that constitute a methodology for the evaluation of a MIS at a public TVET College in South Africa? The study was conducted according to a design science paradigm. Design science is underpinned by a pragmatic philosophical paradigm which considers thought as a tool for prediction, problem solving and action. The Design Science Research Process (DSRP) model informed the research process utilised to develop the artefact for this problem centred initiated study. The iterated activities of the DSRP model which include: design, demonstrate, evaluate and and communicate, contributed to the refinement of the methodology (artefact). The artefact mainly underwent experimental evaluation to demonstrate its applicability. The methodology (artefact) was empirically evaluated at three cluster-random selected public TVET Colleges after all colleges, with similar MIS maturity levels, were clustered into groups.The study contributed to the extant knowledge base of: theory building, on different levels. The main theoretical contribution is the final evaluated methodology (DSR artefact) which enables IT practitioners and MIS managers at public TVET Colleges in South Africa to evaluate their MISs on a regular basis. The methodology (artefact) presents a theory for design and action which satisfies the conditions of importance, parsimony and novelty on a micro-level. The study furthermore contributed to the extant literature on the theory of MIS success evaluation by contributing to theory on the measurement of MIS success constructs and measuring of the relationships between the constructs. Another theoretical contribution is the innovative evidence-based method by which the public TVET Colleges were clustered. The clustering method was used to ensure a more rigorous sample selection technique than purposive or convenient sample selection of cases and is generalisable to other knowledge domain contexts. The research study furthermore produced results of interest to both technology-focused and management-focused audiences. For technology-focused audiences the processes by which the artefact was constructed and evaluated are described, thus establishing repeatability of the study and building the knowledge base for further research extensions by future design science researchers. The rigour of the artefact design process was complemented by a thorough presentation of the experimental design of the artefact’s field test in three public TVET College environments which provides sufficient detail for management audiences to determine if sufficient organisational resources exist for utilisation of the artefact. / Information Science / Ph. D. (Information Systems)

The support and promotion of public Technical and Vocational Education and Training (TVET) Colleges is fundamental in addressing South Africa’s intermediate-level and artisanal skills as shortages in these areas contribute to considerable unemployment in South Africa. These institutions have been earmarked by the South African government for extensive growth. Therefore, efficient and effective management and accurate decision-making within these institutions are essential. The evaluation of the management information systems (MISs) within these institutions, which provide data and information to inform institutional short-term and long-term management decision-making and day-to-day operations, should take place on a regular basis to so enhance the reliability and accuracy of the data and information. The problem is that no evidence of a methodology (artefact) for the evaluation of MISs at public TVET Colleges in South Africa could be found in the literature. Therefore, the rationale for this study is to develop a methodology for the evaluation of MISs at public TVET Colleges in South Africa. Hence the main research question for the study was formulated as: What are the components that constitute a methodology for the evaluation of a MIS at a public TVET College in South Africa? The study was conducted according to a design science paradigm. Design science is underpinned by a pragmatic philosophical paradigm which considers thought as a tool for prediction, problem solving and action. The Design Science Research Process (DSRP) model informed the research process utilised to develop the artefact for this problem centred initiated study. The iterated activities of the DSRP model which include: design, demonstrate, evaluate and communicate, contributed to the refinement of the methodology (artefact). The artefact mainly underwent experimental evaluation to demonstrate its applicability. The methodology (artefact) was empirically evaluated at three cluster-random selected public TVET Colleges after all colleges, with similar MIS maturity levels, were clustered into groups. The study contributed to the extant knowledge base of: theory building, on different levels. The main theoretical contribution is the final evaluated methodology (DSR artefact) which enables IT practitioners and MIS managers at public TVET Colleges in South Africa to evaluate their MISs on a regular basis. The methodology (artefact) presents a theory for design and action which satisfies the conditions of importance, parsimony and novelty on a micro-level. The study furthermore contributed to the extant literature on the theory of MIS success evaluation by contributing to theory on the measurement of MIS success constructs and measuring of the relationships between the constructs. Another theoretical contribution is the innovative evidence-based method by which the public TVET Colleges were clustered. The clustering method was used to ensure a more rigorous sample selection technique than purposive or convenient sample selection of cases and is generalisable to other knowledge domain contexts. The research study furthermore produced results of interest to both technology-focused and management-focused audiences. For technology-focused audiences the processes by which the artefact was constructed and evaluated are described, thus establishing repeatability of the study and building the knowledge base for further research extensions by future design science researchers. The rigour of the artefact design process was complemented by a thorough presentation of the experimental design of the artefact’s field test in three public TVET College environments which provides sufficient detail for management audiences to determine if sufficient organisational resources exist for utilisation of the artefact. / Information Science / Ph. D. (Information Systems)

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Submitted by Nadir Basilio (nadirsb@uninove.br) on 2016-07-01T21:32:07Z No. of bitstreams: 1 Roberto Antonio Winter.pdf: 2306529 bytes, checksum: a8d1cdc9ad22f45147be60e7a42ca592 (MD5) / Made available in DSpace on 2016-07-01T21:32:07Z (GMT). No. of bitstreams: 1 Roberto Antonio Winter.pdf: 2306529 bytes, checksum: a8d1cdc9ad22f45147be60e7a42ca592 (MD5) Previous issue date: 2016-02-22 / Organizational learning process is part of the quest for competitiveness and it is also present on the project’s results, summing up together with several organization projects in order to make up its result. The learned lessons support managers in their projects with the successful and unsuccessful experiences through the registry stored and provided in a centralized and organized way. The learned lessons registry in any project stage helps the project members to meditate about the process, achievements, stimulating the sharing of tacit and explicit knowledge created. On this process of storing and retrieving learned lessons, the web’s 2.0 collaborative tools are present, and in this context the wiki platform is one of the most cited when storing and retrieving learned lessons. Add up the fact that there are no process on the most used references (PMBOK-PMI and ICB-IPMA) to these factors and it is identified a gap on the studies. This scenario motivates the quest for a model that helps the learned lessons management in Information Technology projects and Information Systems. This dissertation aims to evaluate a learned lesson management model on IT/IS project utilizing web 2.0 tools. This model supports the management of learned lessons: gathering, verification, dissemination and reusing. This study has an explanatory and prescriptive approach using an abductive, inductive and deductive method. The Design Science Research is the research’s approach. This study looks for contributing towards the project’s practice and its results and creating academic knowledge with the accuracy that the study requires in its method. The Target 2.0 was instantiated in the implementation phase of an IT project, demonstrating that the model achieved its expected results, solving while searching the company's problem with the GLA. The result emerged evidence of the sociomaterial relations, the quality of relations between people and the model, under present social theory. The research contributes to the GLA practice in projects, helps with project managers in GLA, besides contributing to the Administration allowing expand the use of the organization's knowledge management model. The research contributes to the theory and use of GLA model in the implementation phase of an IT project, in a small business, with improvements in GLA. / O resultado dos diversos projetos de uma empresa contribui para o resultado estratégico do negócio, para a aprendizagem nos projetos, e para o processo de aprendizagem organizacional. Em adição a aprendizagem em projetos, com as lições aprendidas, apoiam os gestores em seus projetos, com o registro das experiências bem sucedidas e de fracassos, coletando e reutilizando as experiências de forma organizada e centralizada. Esta pesquisa explora a gestão de lições aprendidas (GLA), com apoio de uma plataforma wiki, em uma empresa de médio porte, no ramo de TI, especializada em sistemas de logística e transporte. Na relevância do tema, encontram-se as necessidades das empresas, a pouca atenção ao tema nos guias mais utilizados em projetos (PMBOK-PMI e ICB-IPMA). Esse cenário motiva a busca de um modelo que auxilie a GLA em projetos de Tecnologia da Informação e Sistemas de Informação (TI/SI). Essa dissertação tem como objetivo avaliar a instanciação de um modelo de gestão de lições aprendidas em projetos de TI/SI, utilizando uma wiki. Este modelo suporta os processos de GLA: conscientização; coleta; verificação; armazenamento; disseminação e reuso. Este estudo adota o paradigma Design Science Research e o método Technical Action Research, têm uma abordagem exploratória e prescritiva, com uso dos métodos abdutivo, indutivo e dedutivo. A pesquisa instanciou o modelo Target 2.0 na fase de execução de um projeto de TI, demonstrando que o modelo atingiu seus resultados, contribuindo durante a pesquisa para a solução do problema da empresa com a GLA. No resultado emergiu evidências da relação sócio material, na qualidade das relações entre as pessoas e o modelo, sob uma presente teoria social. A pesquisa contribui para a prática de GLA em projetos, contribui com gestores de projetos na GLA, além de contribuir com a Administração permitindo expandir o uso do modelo gestão do conhecimento da empresa. A pesquisa contribui na teoria com uso do modelo na GLA da fase de execução de um projeto de TI, apresentando melhorias na GLA. As seis proposições elaboradas pelo pesquisador, foram confirmadas pela análise dos resultados da pesquisa de campo, sendo que uma possui ressalva que sugere melhorias na elaboração das páginas wiki.