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Willingness to pay and willingness to accept on a two-sided platform - The use case of DoBeeDo
(2019)
It is widely known that especially for technology-based start-ups, entrepreneurs need to set up the boundaries of the business and define the product/service to offer in order to minimize the risk of failure. The goal of this thesis is to not only emphasize the importance of the business model development and evaluation but also show an example customer validation process for an emerging start-up named DoBeeDo, which is a mobile app operating on a two-sided market. During the process of customer validation a survey has been conducted to evaluate the interest of the target groups as well as the fit of their expectations using the Willingness to Pay and Willingness to Accept measures. The paper includes an analysis and evaluation of the gathered results and assesses whether the execution of the Customer Development Model can be continued.
This work describes a novel software tool for visualizing anatomical segmentations of medical images. It was developed as part of a bachelor's thesis project, with a view to supporting research into automatic anatomical brain image segmentation. The tool builds on a widely-used visualization approach for 3D image volumes, where sections in orthogonal directions are rendered on screen as 2D images. It implements novel display modes that solve common problems with conventional viewer programs. In particular, it features a double-contour display mode to aid the user's spatial orientation in the image, as well as modes for comparing two competing segmentation labels pertaining to one and the same anatomical region. The tool was developed as an extension to an existing open-source software suite for medical image processing. The visualization modes are, however, suitable for implementation in the context of other viewer programs that follow a similar rendering approach.
The modified code can be found here: soundray.org/mm-segmentation-visualization.tar.gz.
Current political issues are often reflected in social media discussions, gathering politicians and voters on common platforms. As these can affect the public perception of politics, the inner dynamics and backgrounds of such debates are of great scientific interest. This thesis takes user generated messages from an up-to-date dataset of considerable relevance as Time Series, and applies a topic-based analysis of inspiration and agenda setting to it. The Institute for Web Science and Technologies of the University Koblenz-Landau has collected Twitter data generated beforehand by candidates of the European Parliament Election 2019. This work processes and analyzes the dataset for various properties, while focusing on the influence of politicians and media on online debates. An algorithm to cluster tweets into topical threads is introduced. Subsequently, Sequential Association Rules are mined, yielding wide array of potential influence relations between both actors and topics. The elaborated methodology can be configured with different parameters and is extensible in functionality and scope of application.
Tracking is an integral part of many modern applications, especially in areas like autonomous systems and Augmented Reality. For performing tracking there are a wide array of approaches. One that has become a subject of research just recently is the utilization of Neural Networks. In the scope of this master thesis an application will be developed which uses such a Neural Network for the tracking process. This also requires the creation of training data as well as the creation and training of a Neural Network. Subsequently the usage of Neural Networks for tracking will be analyzed and evaluated. This includes several aspects. The quality of the tracking for different degrees of freedom will be checked as well as the the impact of the Neural Network on the applications performance. Additionally the amount of required training data is investigated, the influence of the network architecture and the importance of providing depth data as part of the networks input. This should provide an insight into how relevant this approach could be for its adoption in future products.
Data visualization is an effective way to explore data. It helps people to get a valuable insight of the data by placing it in a visual context. However, choosing a good chart without prior knowledge in the area is not a trivial job. Users have to manually explore all possible visualizations and decide upon ones that reflect relevant and desired trend in the data, are insightful and easy to decode, have a clear focus and appealing appearance. To address these challenges we developed a Tool for Automatic Generation of Good viSualizations using Scoring (TAG²S²). The approach tackles the problem of identifying an appropriate metric for judging visualizations as good or bad. It consists of two modules: visualization detection: given a data-set it creates a list of combination of data attributes for scoring and visualization ranking: scores each chart and decides which ones are good or bad. For the later, an utility metric of ten criteria was developed and each visualization detected in the first module is evaluated on these criteria. Only those visualizations that received enough scores are then presented to the user. Additionally to these data parameters, the tool considers user perception regarding the choice of visual encoding when selecting a visualization. To evaluate the utility of the metric and the importance of each criteria, test cases were developed, executed and the results presented.
The status of Business Process Management (BPM) recommender systems is not quite clear as research states. The use of recommenders familiarized itself with the world during the rise of technological evolution in the past decade.Ever since then, several BPM recommender systems came about. However, not a lot of research is conducted in this field. It is not well known to what broad are the technologies used and how are they used. Moreover, this master’s thesis aims at surveying the BPM recommender systems existing. Building on this, the recommendations come in different shapes. They can be positionbased where an element is to be placed at an element’s front, back or to autocomplete a missing link. On the other hand, Recommendations can be textual, to fill the labels of the elements. Furthermore, the literature review for BPM recommender systems took place under the guides of a literature review framework. The framework suggests 5stages of consecutive stages for this sake. The first stage is defining a scope for the research. Secondly, conceptualizing the topic by choosing key terms for literature research. After that in the third stage, comes the research stage.As for the fourth stage, it suggests choosing analysis features over which the literature is to be synthesized and compared. Finally, it recommends defining the research agenda to describe the reason for the literature review. By invoking the mentioned methodology, this master’s thesis surveyed 18 BPM recommender systems. It was found as a result of the survey that there
are not many different technologies for implementing the recommenders. It was also found that the majority of the recommenders suggest nodes that are yet to come in the model, which is called forward recommending. Also, one of the results of the survey indicated the scarce use of textual recommendations to BPM labels. Finally, 18 recommenders are considered less than excepted for a developing field therefore as a result, the survey found a shortage in the number of BPM recommender systems. The results indicate several shortages in several aspects in the field of BPM recommender systems. On this basis, this master’s thesis recommends the future work on it the results.
Student misbehavior and its treatment is a major challenge for teachers and a threat to their well-being. Indeed, teachers are obliged to punish student misbehavior on a regular basis. Additionally, teachers’ punishment decisions are among the most frequently reported situations when it comes to students’ experiences of injustice in school. By implication, it is crucial to understand teachers’ treatment of student misbehavior vis-à-vis students’ perceptions. One key dimension of punishment behavior reflects its underlying motivation and goals. People generally intend to achieve three goals when punishing misbehavior, namely, retribution (i.e., evening out the harm caused), special prevention (i.e., preventing recidivism of the offender), and general prevention (i.e., preventing imitation of others). Importantly, people’s support of these punishment goals is subject to hierarchy and power, implying that teachers’ and students’ punishment goal preferences differ. In this dissertation, I present three research projects that shed first light on teachers’ punishment and its goals along with the students’ perception of classroom intervention strategies pursuing these goals. More specifically, I first examined students’ (i.e., children’s) general support of each of the three punishment goals sketched above. Furthermore, I applied an attributional approach to understand and study the goals teachers intend to achieve when punishing student misbehavior. Finally, I investigated teachers’ and students’ support of the punishment goals regarding the same student misbehavior to directly compare their views on these goals and reactions pursuing them. In sum, the findings show that students generally prefer retribution and special prevention to general prevention, whereas teachers prefer general prevention and special prevention to retribution. This ultimately translates into a "mismatch" of teachers and students in their preferences for specific punishment goals, and the findings suggest that this may indeed enhance students’ perception of injustice. Overall, the results of the present research program may be valuable for the development of classroom intervention strategies that may reduce rather than enhance conflicts in student-teacher-interactions.
This paper describes the robots TIAGo and Lisa used by
team homer@UniKoblenz of the University of Koblenz-Landau, Germany,
for the participation at the RoboCup@Home 2019 in Sydney,
Australia. We ended up first at RoboCup@Home 2019 in the Open Platform
League and won the competition in our league now three times
in a row (four times in total) which makes our team the most successful
in RoboCup@Home. We demonstrated approaches for learning from
demonstration, touch enforcing manipulation and autonomous semantic
exploration in the finals. A special focus is put on novel system components
and the open source contributions of our team. We have released
packages for object recognition, a robot face including speech synthesis,
mapping and navigation, speech recognition interface, gesture recognition
and imitation learning. The packages are available (and new packages
will be released) on http://homer.uni-koblenz.de.
Software systems have an increasing impact on our daily lives. Many systems process sensitive data or control critical infrastructure. Providing secure software is therefore inevitable. Such systems are rarely being renewed regularly due to the high costs and effort. Oftentimes, systems that were planned and implemented to be secure, become insecure because their context evolves. These systems are connected to the Internet and therefore also constantly subject to new types of attacks. The security requirements of these systems remain unchanged, while, for example, discovery of a vulnerability of an encryption algorithm previously assumed to be secure requires a change of the system design. Some security requirements cannot be checked by the system’s design but only at run time. Furthermore, the sudden discovery of a security violation requires an immediate reaction to prevent a system shutdown. Knowledge regarding security best practices, attacks, and mitigations is generally available, yet rarely integrated part of software development or covering evolution.
This thesis examines how the security of long-living software systems can be preserved taking into account the influence of context evolutions. The goal of the proposed approach, S²EC²O, is to recover the security of model-based software systems using co-evolution.
An ontology-based knowledge base is introduced, capable of managing common, as well as system-specific knowledge relevant to security. A transformation achieves the connection of the knowledge base to the UML system model. By using semantic differences, knowledge inference, and the detection of inconsistencies in the knowledge base, context knowledge evolutions are detected.
A catalog containing rules to manage and recover security requirements uses detected context evolutions to propose potential co-evolutions to the system model which reestablish the compliance with security requirements.
S²EC²O uses security annotations to link models and executable code and provides support for run-time monitoring. The adaptation of running systems is being considered as is round-trip engineering, which integrates insights from the run time into the system model.
S²EC²O is amended by prototypical tool support. This tool is used to show S²EC²O’s applicability based on a case study targeting the medical information system iTrust.
This thesis at hand contributes to the development and maintenance of long-living software systems, regarding their security. The proposed approach will aid security experts: It detects security-relevant changes to the system context, determines the impact on the system’s security and facilitates co-evolutions to recover the compliance with the security requirements.
To construct a business process model manually is a highly complex and error-prone task which takes a lot of time and deep insights into the organizational structure, its operations and business rules. To improve the output of business analysts dealing with this process, different techniques have been introduced by researchers to support them during construction with helpful recommendations. These supporting recommendation systems vary in their way of what to recommend in the first place as well as their calculations taking place under the hood to recommend the most fitting element to the user. After a broad introduction into the field of business process modeling and its basic recommendation structures, this work will take a closer look at diverse proposals and descriptions published in current literature regarding implementation strategies to effectively and efficiently assist modelers during their business process model creation. A critical analysis of presentations in the selected literature will point out strengths and weaknesses of their approaches, studies and descriptions of those. As a result, the final concept matrix in this work will give a precise and helpful overview about the key features and recommendation methods used and implemented in previous research studies to pinpoint an entry into future works without the downsides already spotted by fellow researchers.
Small headwater streams comprise most of the total channel length and catchment area in fluvial networks. They are tightly connected to their catchments and, thus, are highly vulnerable to changes in catchment hydrologic budgets and land use. Although these small, often fishless streams are of little economic interest, they are vital for the ecological and chemical state of larger water bodies. Although numerous studies investigate the impact of various anthropogenic stressors or altered catchment conditions, we lack an in-depth understanding of the natural conditions and processes in headwater streams. This natural state, however, largely affects how a headwater stream responds to anthropogenic or climatic changes. One of the major threats to aquatic ecosystems is the excessive anthropogenic input of nutrients leading to eutrophication. Nutrients exert a bottom-up effect in the food web, foremost affecting primary producers and their consumers, i.e. periphyton and benthic grazers in headwater streams. The periphyton-grazer link is the main path of autochthonous (in-stream) production into the stream food web and the strength of this link largely determines the effectiveness of this pathway. Therefore, this thesis aims at elucidating important biological processes with the explicit focus on periphyton-grazer interactions. I assessed different aspects of periphyton-grazer interactions using laboratory experiments to solve methodological problems, and using a field study to compare the benthic communities of three morphologically similar, phosphorus-limited, near-natural headwater streams. With the results of the laboratory experiments, I was able to show that periphyton RNA/DNA ratios can be used as proxy for periphyton growth rates in controlled experiments and that the fatty acid composition of grazing mayfly nymphs responds to changes in fatty acids provided by the diet after only two weeks. The use of the RNA/DNA ratio as a proxy for periphyton growth rate allows a comparison of these growth rates even in simple experimental set-ups and thereby permits the inclusion of this important process in ecotoxicological or ecological experiments. The observed fast turnover rates of fatty acids in consumer tissues show that even short-term changes in available primary producers can alter the fatty acid composition of primary consumers with important implications for the supply of higher trophic levels with physiologically important polyunsaturated fatty acids. With the results of the field study, I revealed gaps in the understanding of the linkages between catchment and in-stream phosphorus availability under near-natural conditions and demonstrated that seemingly comparable headwater streams had significantly different benthic communities. These differences most likely affect stream responses to environmental changes.
Over the past few decades society’s dependence on software systems has grown significantly. These systems are utilized in nearly every matter of life today and often handle sensitive, private data. This situation has turned software security analysis into an essential and widely researched topic in the field of computer science. Researchers in this field tend to make the assumption that the quality of the software systems' code directly affects the possibility for security gaps to arise in it. Because this assumption is based on properties of the code, proving it true would mean that security assessments can be performed on software, even before a certain version of it is released. A study based on this implication has already attempted to mathematically assess the existence of such a correlation, studying it based on quality and security metric calculations. The present study builds upon that study in finding an automatic method for choosing well-fitted software projects as a sample for this correlation analysis and extends the variety of projects considered for the it. In this thesis, the automatic generation of graphical representations both for the correlations between the metrics as well as for their evolution is also introduced. With these improvements, this thesis verifies the results of the previous study with a different and broader project input. It also focuses on analyzing the correlations between the quality and security metrics to real-world vulnerability data metrics. The data is extracted and evaluated from dedicated software vulnerability information sources and serves to represent the existence of proven security weaknesses in the studied software. The study discusses some of the difficulties that arise when trying to gather such information and link it to the difference in the information contained in the repositories of the studied projects. This thesis confirms the significant influence that quality metrics have on each other. It also shows that it is important to view them together as a whole and suppose that their correlation could influence the appearance of unwanted vulnerabilities as well. One of the important conclusions I can draw from this thesis is that the visualization of metric evolution graphs, helps the understanding of the values as well as their connection to each other in a more meaningful way. It allows for better grasp of their influence on each other as opposed to only studying their correlation values. This study confirms that studying metric correlations and evolution trends can help developers improve their projects and prevent them from becoming difficult to extend and maintain, increasing the potential for good quality as well as more secure software code.
Grapevine growers have struggled with defending their crops against pests and diseases since the domestication of grapevine over 6000 ears ago. Since then, new growing methods paired with a better nderstanding of the ecological processes in the vineyard ecosystem continue to improve quality and quantity of grape harvests. In this thesis I am describing the effects of two recent innovations in viticulture on pest and beneficial arthropods in vineyards; Fungus-resistant grapevine cultivars (PIWIs) and the pruning system semi-minimal pruned hedge (SMPH). The SMPH pruning system allows for a drastic reduction of manual labor in the vineyard, and PIWIs are resistant to two of the most common fungal diseases of grapevine and therefore allow a drastic reduction of fungicide applications compared to conventional varieties. Heavy use of pesticides is linked to a number of problems, including pollution of waterways, negative effects on human health, and biodiversity loss. Here, I studied the effects of fungicide reduction and minimal pruning on arthropods that are beneficial for natural pest suppression in the vineyard ecosystem such as predatory mites, spiders, ants, earwigs, and lacewings. All of these groups either benefitted from the reduction of fungicide sprayings or were not significantly affected. Structural changes in the canopy of SMPH grapevines altered the microclimate in the canopy which in turn influenced some of the arthropods living in it. Overall, my findings suggest that PIWIs and SMPH, both in combination or separately, improve conditions for natural pest control. This adds to other advantages of these innovative management practices such as a reduction in production cost and a smaller impact on the environment.
With the appearance of modern virtual reality (VR) headsets on the consumer market, there has been the biggest boom in the history of VR technology. Naturally, this was accompanied by an increasing focus on the problems of current VR hardware. Especially the control in VR has always been a complex topic.
One possible solution is the Leap Motion, a hand tracking device that was initially developed for desktop use, but with the last major software update it can be attached to standard VR headsets. This device allows very precise tracking of the user’s hands and fingers and their replication in the virtual world.
The aim of this work is to design virtual user interfaces that can be operated with the Leap Motion to provide a natural method of interaction between the user and the VR environment. After that, subject tests are performed to evaluate their performance and compare them to traditional VR controllers.
Nanotemplates for the combined structural and functional analysis of membrane-associated proteins
(2019)
Plasma membranes are essential for life because they give cells an identity. Plasma membranes are almost impermeable to fluids and substances. Still, transport between inside and outside needs to be possible. An important transport way is endocytosis. This mechanism relies on membrane-associated proteins that sense and induce curvature to the plasma membrane. However, the physics and structural dynamics behind proteins acting on membranes is not well understood. There is a standard method in vitro to investigate membrane-associated proteins sensing spherical geometries: They are incubated on unilamellar vesicles. This procedure allows to analyze these proteins in their bound state. This approach is inappropriate for GRAF1 (GTPase Regulator Associated with Focal Adhesion Kinase-1), a key player in endocytosis because it senses tubular geometries instead. However, GRAF1 extrudes lipid tubes from vesicles that can be analyzed. Still, this is a limited method because these tubes suffer from inhomogeneity and they do not enable the observation of intermediate and lower concentration binding states. To overcome this issue they can be incubated on pre-tubular structures called nanotemplates. There have been studies using carbon nanotubes and Galactosylceramide lipid tubes as nanotemplates. These approaches require complex chemical modifications or expensive components and they are not necessarily flexible. In this work we present a simple and easy new approach to prepare nanotemplates using Folch lipid mixture. We show on the basis of BPG, a truncate of GRAF1, that our nanotemplates are suitable for Cryo-EM and that it is possible to use IHRSR (Iterative Helical Real Space Reconstruction) to analyze the structure of BPG in its bound state. Moreover, the qualification for Cryo-EM allows to use plunge freezing to interrupt the incubation on our nanotemplates abruptly. This enables the analysis of intermediate binding states to understand the binding process.
The bio-insecticide Bacillus thuringiensis israelensis (Bti) has worldwide become the most commonly used agentin mosquito control programs that pursue two main objectives: the control of vector-borne diseases and the reduction of nuisance, mainly coming frommosquitoes that emerge in large quantities from seasonal wetlands. The Upper Rhine Valley, a biodiversity hotspot in Germany, has been treated withBti for decades to reduce mosquito-borne nuisance and increase human well-being.Although Btiis presumed to be an environmentally safe agent,adverse effects on wetland ecosystems are still a matter of debate especially when it comes to long-term and indirect effects on non-target organisms. In light of the above, this thesis aims at investigating direct and indirect effects of Bti-based mosquito control on non-target organisms within wetland food chains.Effects were examinedin studies with increasingeco(toxico)logical complexity, ranging from laboratory over mesocosm to field approaches with a focus on the non-biting Chironomidae and amphibian larvae (Rana temporaria, Lissotriton sp.).In addition, public acceptance of environmentally less invasive alternative mosquito control methods was evaluated within surveys among the local population.
Chironomids were the most severely affected non-target aquatic invertebrates. Bti substantially reduced larval and adult chironomid abundances and modified their species composition. Repeated exposures to commonly used Bti formulations induced sublethal alterations of enzymatic biomarkers activityin frog tadpoles. Bti-induced reductions of chironomid prey availability indirectly decreased body size of newts at metamorphosis and increased predation on newt larvae in mesocosm experiments. Indirect effects of severe reductions in midge biomassmight equally be passed through aquatic but also terrestrial food chains influencing predators of higher trophic levels. The majority ofaffectedpeople in the Upper Rhine Valley expressed a high willingness to contributefinancially to environmentally less harmful mosquito control.Alternative approaches could still include Bti applications excepting treatment of ecologically valuable areas. Potentially rising mosquito levels could be counteracted with local acting mosquito traps in domestic and urban areas because mosquito presence was experienced as most annoying in the home environment.
As Bti-based mosquito control can adversely affect wetland ecosystems, its large-scale applications, including nature conservation areas, should be considered more carefully to avoid harmful consequences for the environmentat the Upper Rhine Valley.This thesis emphasizesthe importance to reconsiderthe current practice of mosquito control and encourage research on alternative mosquito control concepts that are endorsed by the local population. In the context ofthe ongoing amphibian and insect declinesfurther human-induced effects onwetlands should be avoided to preserve biodiversity in functioning ecosystems.
The goal of this master thesis was to develop a CRM system for the Assist team of CompuGroup Medical that is aiding in integrating open innovation into the development of the Minerva 2.0 software. To achieve this, CRM methodology has been combined with Social Networking Systems, following the research of Lin and Chen (2010, pp. 11 – 30). To achieve the predefined goals literature has been analyzed on how to successfully im- plement a CRM system as well as an online community. Subsequently the results have been applied to the development of the Minerva Community according to the guidelines of Design Science suggested by Hevner et al. (2004, pp. 75 – 104). The finished product is designed based on customer and management requirements and evaluated from a customer and company perspective.
Lakes and reservoirs are important sources of methane, a potent greenhouse gas. Although freshwaters cover only a small fraction of the global surface, their contribution to global methane emission is significant and this is expected to increase, as a positive feedback to climate warming and exacerbated eutrophication. Yet, global estimates of methane emission from freshwaters are often based on point measurements that are spatio-temporally biased. To better constrain the uncertainties in quantifying methane fluxes from inland waters, a closer examination of the processes transporting methane from sediment to atmosphere is necessary. Among these processes, ebullition (bubbling) is an important transport pathway and is a primary source of uncertainty in quantifying methane emissions from freshwaters. This thesis aims to improve our understanding of ebullition in freshwaters by studying the processes of methane bubble formation, storage and release in aquatic sediments. The laboratory experiments demonstrate that aquatic sediments can store up to ~20% (volumetric content) gas and the storage capacity varies with sediment properties. The methane produced is stored as gas bubbles in sediment with minimal ebullition until the storage capacity is reached. Once the sediment void spaces are created by gas bubble formation, they are stable and available for future bubble storage and transport. Controlled water level drawdown experiments showed that the amounts of gas released from the sediment scaled with the total volume of sediment gas storage and correlated linearly to the drop in hydrostatic pressure. It was hypothesized that not only the timing of ebullition is controlled by sediment gas storage, but also the spatial distribution of ebullition. A newly developed freeze corer, capable of characterizing sediment gas content under in situ environments, enabled the possibility to test the hypothesis in a large subtropical lake (Lake Kinneret, Israel). The results showed that gas content was variable both vertically and horizontally in the lake sediment. Sediment methane production rate and sediment characteristics could explain these variabilities. The spatial distribution of ebullition generally was in a good agreement with the horizontal distribution of depth-averaged (surface 1 m) sediment gas content. While discrepancies were found between sediment depth-integrated methane production and the snapshot ebullition rate, they were consistent in a long term (multiyear average). These findings provide a solid basis for the future development of a process-based ebullition model. By coupling a sediment transport model with a sediment diagenetic model, general patterns of ebullition hotspots can be predicted at a system level and the uncertainties in ebullition flux measurements can be better constrained both on long-term (months to years) and short-term (minutes to hours) scales.
Business Process Querying (BPQ) is a discipline in the field of Business Process Man- agement which helps experts to understand existing process models and accelerates the development of new ones. Its queries can fetch and merge these models, answer questions regarding the underlying process, and conduct compliance checking in return. Many languages have been deployed in this discipline but two language types are dominant: Logic-based languages use temporal logic to verify models as finite state machines whereas graph-based languages use pattern matching to retrieve subgraphs of model graphs directly. This thesis aims to map the features of both language types to features of the other to identify strengths and weaknesses. Exemplarily, the features of Computational Tree Logic (CTL) and The Diagramed Modeling Language (DMQL) are mapped to one another. CTL explores the valid state space and thus is better for behavioral querying. Lacking certain structural features and counting mechanisms it is not appropriate to query structural properties. In contrast, DMQL issues structural queries and its patterns can reconstruct any CTL formula. However, they do not always achieve exactly the same semantic: Patterns treat conditional flow as sequential flow by ignoring its conditions. As a result, retrieved mappings are invalid process execution sequences, i.e. false positives, in certain scenarios. DMQL can be used for behavioral querying if these are absent or acceptable. In conclusion, both language types have strengths and are specialized for different BPQ use cases but in certain scenarios graph-based languages can be applied to both. Integrating the evaluation of conditions would remove the need for logic-based languages in BPQ completely.
The Internet of Things (IoT) is a fast-growing, technological concept, which aims to integrate various physical and virtual objects into a global network to enable interaction and communication between those objects (Atzori, Iera and Morabito, 2010). The application possibilities are manifold and may transform society and economy similarly to the usage of the internet (Chase, 2013). Furthermore, the Internet of Things occupies a central role for the realisation of visionary future concepts, for example, Smart City or Smart Healthcare. In addition, the utilisation of this technology promises opportunities for the enhancement of various sustainability aspects, and thus for the transformation to a smarter, more efficient and more conscious dealing with natural resources (Maksimovic, 2017). The action principle of sustainability increasingly gains attention in the societal and academical discourse. This is reasoned by the partly harmful consumption and production patterns of the last century (Mcwilliams et al., 2016). Relating to sustainability, the advancing application of IoT technology also poses risks. Following the precautionary principle, these risks should be considered early (Harremoës et al., 2001). Risks of IoT for sustainability include the massive amounts of energy and raw materials which are required for the manufacturing and operation of IoT objects and furthermore, the disposal of those objects (Birkel et al., 2019). The exact relations in the context of IoT and sustainability are insufficiently explored to this point and do not constitute a central element within the discussion of this technology (Behrendt, 2019). Therefore, this thesis aims to develop a comprehensive overview of the relations between IoT and sustainability.
To achieve this aim, this thesis utilises the methodology of Grounded Theory in combination with a comprehensive literature review. The analysed literature primarily consists of research contributions in the field of Information Technology (IT). Based on this literature, aspects, solution approaches, effects and challenges in the context of IoT and sustainability were elaborated. The analysis revealed two central perspectives in this context. IoT for Sustainability (IoT4Sus) describes the utilisation and usage of IoT-generated information to enhance sustainability aspects. In contrast, Sustainability for IoT (Sus4IoT) fo-cuses on sustainability aspects of the applied technology and highlights methods to reduce negative impacts, which are associated with the manufacturing and operation of IoT. Elaborated aspects and relations were illustrated in the comprehensive CCIS Framework. This framework represents a tool for the capturing of relevant aspects and relations in this context and thus supports the awareness of the link between IoT and sustainability. Furthermore, the framework suggests an action principle to optimise the performance of IoT systems regarding sustainability.
The central contribution of this thesis is represented by the providence of the CCIS Framework and the contained information regarding the aspects and relations of IoT and sustainability.