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The thorny issue of time
(2023)
This study aims to address the research gap surrounding the role of leadership in the formation of high-performance teams within startup companies. While there is existing research on high-performing teams, limited attention has been given to leadership in this environment. To bridge this gap, the study combines a literature review and qualitative analysis through semi-structured interviews with diverse stakeholders in startups, with the goal of providing practical guidance for startup executives based on the research findings. The study uncovers key aspects of leadership in high-performance teams, emphasizing the importance of skills such as motivation and support for team members, fostering psychological safety and trust, and effectively managing uncertainty. In addition to resource constraints and high expectations, the study sheds light on the challenges faced by leaders in startup and high-performance team environments, particularly the blurring of traditional leadership roles as team members seek autonomy and decision-making authority. These findings present opportunities for future research to explore this progressive leadership style. Overall, this study contributes to our understanding of leadership dynamics within high-performance teams operating in the context of startups. It offers valuable insights that can help startup executives navigate the complexities of leadership and foster the development of successful and high-performing teams.
In an oversaturated market, companies are required to use innovative and, above all, creative advertising methods to capture their customers’ attention, and thus differentiate themselves from rival businesses. To this end, companies have been increasingly relying on the use of humor, a phenomenon that remains highly subjective and is perceived differently by each individual. This master’s thesis, which was completed as part of the International Marketing and Sales program at the FH Vorarlberg, focuses on this phenomenon of humor as well as its impact on advertising perception. With the aid of three different theories, the term “humor” is defined. Furthermore, this study explains and researches the so-called vampire effect, wherein various factors (in this case humor) draw attention away from the actual advertising message. In addition, this thesis takes a closer look at involvement, as a person’s involvement or interest in a brand or product can influence brand and product recall and recognition. An online survey was conducted to determine whether the vampire effect caused by humor is able to influence brand and product recall. In other words, this concerns whether the viewer can still remember the brand and product afterward or whether the humor employed triggers the vampire effect. Furthermore, this thesis explored whether the vampire effect caused by humor is able to influence brand and product recognition. Recall is the retrieval of information from memory without direct cues, whereas recognition refers to the recognition of information when it is presented again. Furthermore, within this context, it was discovered that brand and product recall varies with low and high involvement viewers of the advertisement. In other words, this means that the strength of the vampire effect caused by humor changes depending on the strength of the viewer’s involvement. During the course of this research, it was further observed that the humor employed significantly affects the perception of the advertising message, thus confirming the existence of the vampire effect. This effect also influences both brand as well as product recall and recognition. In both cases, participants in the survey were less able to remember the product and brand in the humorous advertising. Furthermore, it was proven that people with low involvement in the advertised product group are more heavily affected by the vampire effect. As such, they are more likely to not remember the product or brand after seeing the advertisement.
The presented master thesis of the study subject International Management and Leadership at the University of Applied Science Vorarlberg in Dornbirn handles the potential future influence of the EU Corporate Sustainability Due diligence on SMEs. First this thesis introduces the most important regulations that might come into place with this Due Diligence Act and gives a theoretical input when and how it will come into place, and also who it will affect directly and who will be affected indirectly. The empirical data resulted of several qualitative expert interviews and a following quantitative research. The expert interviews are split in two different groups, first the topic experts from institutions like chamber of commerce or chamber of labour and second experts from highly successful Austrian companies which are already handling the topic and the future challenges. Expected outcome of the qualitative interviews was a better view on the actual situation especially the impact on small and medium enterprises. On the basis of this results the quantitative survey was produced. In the quantitative survey the goal was to see, how much entrepreneurs and companies in the small and medium sector already are aware of the upcoming legal challenges throughout the supply chain. With all this collected data the practical outcome of this thesis is the Checklist, which helps entrepreneurs to find out if and how much they will be affected by the Act. And finally, the most important part is the Guideline, which introduces first risk assessment tools, that will help companies to prepare for future legislation and bring undoubtedly a certain advantage for the upcoming challenges.
Digital twin as enabler of business model innovation for infrastructure construction projects
(2023)
Emerging technologies and methods are becoming an important element of the construction industry. Digital Twins are used as a base to store data in BIM models and make use out of the data respectively make the data visible. The transparency in all phases of the lifecycle of building and infrastructure assets is crucial in order to get a more efficient lifecycle of planning, construction and maintenance. Whereas other industries increased performance in these phases by making use out of the data, construction industry is stuck in traditional methods and business models. In this paper we propose a concept that focuses on the digital production twin. The comparison of planning data with As-Is production data can empower a data driven continuous improvement process and support the decision making process of future innovations and suitable business models. This paper outlines the possibility to use the data stored in a digital twin with regards to the evaluation of possible business models.
Although workplace climate has been already extensively studied, the research has not led to firm conclusions regarding leadership trainings referring to the awareness of psychological safety in a company and its influence on existing teams and the general work climate. The author used the already existing model of Carr, Schmidt, Ford, & DeShon (2003) and adjusted it with psychological safety as 4th climate item to develop hypothesen which can also be seen as a path analytic model. The model posied that climate affects individual level outcomes through its impact on cognitive and affective states. Therefore, the author wants to show the correlation between the 4 higher order facets of climate affect the individual levels of job performance, psychological well-being and withdrawal through their impact on orangizational commitment and job saitsfaction (Carr, Schmidt, Ford, & DeShon, 2003).
This thesis investigates the role of leadership behaviours of C-level executives in the context of post-M&A integration processes. The primary focus is on understanding the impact of specific leadership behaviours on inspiring desirable follower effects and facilitating emotional acceptance during organizational change. Drawing on the frameworks presented in “Six- Dimension Integrative Model of Leadership” and "The Six Domains of Leadership" developed by Sitkin et al., the study conducts expert interviews with managers from middle management who have recently experienced M&A integration. The answers are analysed in depth to identify the most effective leadership behaviours, highlighting those mentioned most frequently and those capable of triggering multiple follower effects simultaneously. The result is a list of behaviours that can serve as a guideline for C-level executives who want to foster desirable follower effects throughout the M&A integration journey.
Through mandatory ESG (environmental, social, governance) reporting large companies must disclose their ESG activities showing how sustainability risks are incorporated in their decision-making and production processes. This disclosure obligation, however, does not apply to small and medium-sized enterprises (SME), creating a gap in the ESG dataset. Banks are therefore required to collect sustainability data of their SME customers independently to ensure complete ESG integration in the risk analysis process for loans. In this paper, we examine ESG risk analysis through a smart science approach laying the focus on possible value outcomes of sustainable smart services for banks as well as for their (SME) customers. The paper describes ESG factors, how services can be derived from them, targeted metrics of ESG and an ESG Service Creation Framework (business ecosystem building, process model, and value creation). The description of an exemplary use case highlighting the necessary ecosystem for service creation as well as the created value concludes the paper.
The role of entrepreneurs and intrapreneurs in the current zeitgeist is to drive innovation, re-shape rigid, established processes in business as well as for consumers. They use new viewpoints to pioneer new (business) models which focus on ‘smartness’ rather than the purely monetary and short-sighted models of yesteryear. Fostering and supporting the culture of this current zeitgeist is a mayor challenge for entre- and intrapreneurial support infrastructures, namely startup centres and innovation hubs of universities and other public institutions as well as innovation centres of private companies. Hereby, support may range from access to funding over provision of resources such as offices or computing hardware to coaching in the development of business ideas and strategic roadmaps for product and service deployment. In this paper, we focus on describing the status-quo of afore- mentioned support infrastructures in Vorarlberg and the Lake Constance region, then extend the scope to existing (international) approaches for aiding founders and inno- vators in the development of smart services. An analysis of success stories of the Vorarlberg startup centre ‘startupstube’ and other initiatives including their compar- ison to international counterparts builds the basis for a methodological framework for (service science) coaching in entre- and intrapreneurial support infrastructures. The paper is concluded by the description of a framework for choosing the right methods and tools to create service value in entre-/intrapreneurship based upon tested, proven know-how and for defining support infrastructure needs based upon pre-defined stakeholder and target groups as well as the (industry) sectors of the innovators.
In this paper, a 256-channel, 10-GHz arrayed waveguide gratings demultiplexer for ultra-dense wavelength division multiplexing was designed using an in-house developed tool called AWG-Parameters. The AWG demultiplexer was designed for a central wavelength of 1550 nm and the structure was simulated in PHASAR tool from Optiwave. Two different AWG designs were developed and the influence of the design parameters on the AWG performance was studied.
Design, simulation, and optimization of the 1×4 optical three-dimensional multimode interference splitter using IP-Dip polymer as a core and polydimethylsiloxane (PDMS) Sylgard 184 as a cladding is demonstrated. The splitter was simulated by using beam propagation method in BeamPROP simulation module of RSoft photonic tool and optimized for an operating wavelength of 1.55 μm . According to the minimum insertion loss, the dimensions of the splitter were optimized for a waveguide with a core size of 4×4 μm2 . The objective of the study is to create the design for fabrication by three-dimensional direct laser writing optical lithography.
The control measures for the COVID-19 pandemic, early 2020, caused a chain reaction that eventually led to a shortage of components in the electronic manufacturing industry. A lack of components meant that the production and sales were interrupted or even stopped. For many electronic manufacturing firms, this was seen as a crisis. A crisis is mostly divided into three phases called the pre-crisis phase, crisis management and post-crisis phase. The pre-crisis phase involves an environmental assessment and setting up of crisis management teams, and plan. The crisis management phase has to do with the collection and interpretation of information and the mitigation of the crisis. The post-crisis phase looks at learnings from the crisis. In this paper it was investigated how the electronic manufacturing firms in Vorarlberg managed the crisis in the period between 2020 and 2022. The overall aim was to get a full understanding of how it affected the operations regarding the respective crisis teams and which factors were considered most important for setting up the teams. Two basic criteria which had to be over-come was the uncertainty and lack of time. It was seen that even though the fundamental structure did not change, crisis teams were added in the form of a crisis management team and task forces. The task forces played a major role in getting an understanding of the problem and the effect it has on the business. The crisis management team, which includes high level managers from all affected functional areas, had to re-evaluate the high level strategy and decide what needs to be done, and who will be doing it. In order to do so, they needed to understand what the priorities are regarding components and products and then decide on the priorities regarding affected business. The new strategy was then handed down to the task forces for implementation. A major focus of this paper was also on decision making and how everything contributed to making decisions that had the right effect in resolving the financial crisis for the organizations.
Supply shortages faced in products and resources from semiconductors to natural gas in recent years have had impact massive on global economy, but such challenges are not new for supply chain professionals. Many major events in the past have disrupted supply chains: 9/11 attack in New York, Tsunami in Japan to name a few, but COVID19 have had the biggest and widespread impact in the modern times. Even though supply chain resilience being a term coined in early 2000’s, its usage and importance has increased since then. With the curiosity of assessing the current state of sup-ply chain resilience literature and finding a resilience measurement method which is a one-fit for all supply chains in the manufacturing industry of Vorarlberg, the following research project was undertaken. Research is carried out with mixed methods, using a systematic literature review followed by expert interviews. In the conclusion of the research the author argues that there is a significant difference in the understanding of the term resilience within industry, there is a lack on the need for a meas-ure for resilience. The ways in which the structure of an organization impacts the level of resilience, foreseen benefits of digitalization and technologies for resilience are also dis-cussed. A comparative analysis on the SCR measurement methods discovered in literature, resulted in recommending Resilience index for on-time delivery proposed by Carvalho et al for the mentioned industry.
Having autonomy in the workplace can have a positive impact on employees’ performance, which in turn can benefit the organization’s competitive advantages. While previous researches have primarily focused on the psychological effects of job autonomy on employee performance and has been limited to certain domains, the relationship between job autonomy and organizational design is an important area of study for organizations seeking to improve their competitiveness. This thesis proposes a conceptual model for designing an organization structure that promotes employee performance in manufacturing companies by removing obstacles towards obtaining job autonomy. The focus is on ambitious employees who seek growth and development opportunities within their organization. The model is based on a review of existing literature on job autonomy and organizational design. Exploratory qualitative research was conducted with selected ambitious employees from different industries by means of one-on-one semi-structured interviews. Overall, the proposed model has practical implications for manufacturing companies looking to motivate their employees, as well as for researchers seeking to advance their understanding of organizational design in our times.
The advent of autonomous and self-driving cranes represents a significant advancement in industrial automation. One critical prerequisites for achieving this long-term goal is the accurate and reliable detection of tools guided by ropes in real-world environments. Since the tool is suspended by ropes, the tool pose cannot be controlled directly. This master’s thesis addresses the challenges of pose estimation for rope-guided tools using point cloud measurements. The proposed algorithm utilizes constraints imposed by the crane kinematics and information extracted during the segmentation process to efficiently infer the pose of the hook, therefore enabling the use of the pose for decision making in real-time critical applications. RANSAC (Random Sample and Consensus) is deployed in the segmentation process to extract geometric primitives from the point cloud which represent the ropes and distinctive parts of the tool. Since the point cloud is often to sparse for feature matching a bounding box is used to estimate the initial position of the tool. Two different methods are presented to improve the initial pose. A computationally expensive method with a high level of confidence, integrating the ICP (Iterative Closest Point) algorithm is used as a benchmark. A linear Kalman filter is used in the second method which is real-time capable. The benchmark is then used to evaluate the real-time capable approach. The core contributions of this research lie in the innovative utilization of bounding boxes for pose estimation. The findings and methodologies presented herein constitute an advancement towards the realization of autonomous and self-driving cranes.
The Fast Average Current Mode control methodology is a novel method for the implementation of a current compensator in a switched-mode power supply. It does not require compensation against sub-harmonic instability and is inductor independent. In this work, the digital implementation of this topology is compared against an analog implementation using simulation. Additionally, a hardware prototype is created to validate the digital simulation's results. In a Simulink environment, parameters of the digital implementation, such as the digital-to-analog converter resolutions and the delay counter frequency are varied to research their impact on system performance. The simulations show that a digital current compensator has similar performance as an analog implementation when designed tailored to the application. When evaluating the whole control loop the digital system is inferior due to added delays caused by digital to analog conversion. By operating the Buck converter hardware implementation as a current source, the functionality of the current mode control implementation in a FPGA was proven. Voltage control cannot be validated due to hardware issues. Due to the successful simulation of the source code with a mixed signal model of the converter, it can be assumed that it is functional. Apart from performance, a digital implementation shows many benefits compared to an analog solution, such as configurability of control parameters and easy compensation of component variations and aging.
Recent years have been commanded by a cascade of unpredictable incidents, that have redefined new standards in our private, but also in our professional life. Events like the financial crisis, the COVID-19 pandemic, the energy crisis in Europe, resource scarcity and so forth have caused instability, forcing companies towards flexibility, constantly adapting their operative structures according to the needs of the moment. The effective adaptation to this environment is the key for reacting the dynamism of the market, and for guaranteeing future success. However, the introduction of these crucial changes on a stable company organisation is challenging. Furthermore, due to digitalisation, boundaries between countries have been removed, and the daily cooperation with co-workers and customers all around the globe became the new standard. The establishment of a good corporate culture where diverse people can work in harmony and, is a difficulty that comes ahead.
This master thesis developed from a professional perspective. The topics of change management and corporate culture where combined, and the relationship between these two concepts was studied. This master thesis aims utilising corporate culture as an instrument in managements favour, to implement strategical changes easily and successfully in a more efficient way. The relation between corporate culture and the resistance to change, focusing on the initiation of the change process, was the main area of study. Research questions and hypothesis, formulated with a solid theoretical background, are to be answered based firstly on literature, and secondly on the results of empirical quantitative re-search. To conclude, a set of recommendations for corporates were suggested with the intention of guiding companies how to use corporate culture as an instrument for change management.
This thesis focuses on implementing and testing communication over a private 5G standalone network in an industrial environment, with a specific emphasis on communication between two articulated robots. The main objective is to examine machine-to-machine communication behavior in various test scenarios. Initially, the 5G core and radio access network components are described, along with their associated interfaces, to establish foundational knowledge. Subsequently, a use case involving two articulated robots is implemented, and essential metrics are defined for testing, including round-trip time, packet and inter-packet delay, and packet error rate. The tests investigate the impact of 5G quality of service, packet size, and transmission interval on communication between the robots, focusing on the effects of network traffic. The results highlight the significance of prioritizing network resources based on the assigned quality of service identifier (5QI), demonstrate the influence of packet sizes on communication performance, and underscore the importance of transmission intervals for automation purposes. Additionally, the study examines how network disturbances influence the movements of a robot controlled via 5G, establishing a direct relationship between network metrics and the resulting deviations in the robot’s trajectory. The work concludes that while machine-to-machine communication can be successfully implemented with 5G SA, tradeoffs must be carefully considered, especially concerning packet error rate, and emphasizes the importance of understanding the required resources before implementation to ensure feasibility. Future research directions include investigating network slicing, secure remote control of robots, and exploring the use of higher frequency bands. The study highlights the significance of aligning theoretical standards with practical implementation options in the evolving landscape of 5G Networks.
Lack of transparency and traceability of products and their raw materials means that most products can only be thrown away or not properly recycled due to a lack of relevant data. This conflicts with the circular economy principles, which are demanded by several initiatives, including the European Union. The aim of this master thesis is to analyze this conflict and to propose a technical solution based on Distributed Ledger Technology that enables transparency and traceability of products and their materials. Therefore, the thesis addresses two central research questions: 1. How can traceability and transparency be enabled by integrating a DLT solution? 2. How would a prototype with the integration of smart contracts and DLT look like? To answer these questions, a blockchain solution is implemented using Hyperledger Fabric. The solution uses the immutability and decentralized nature of DLT to record and track the movement of products and their materials throughout their life cycle in the Circular Economy. Furthermore, with private data collections, confidentiality, and privacy are granted while ensuring transparency. The thesis contributes to the Circular Economy field by exploring the principles, models, and challenges of the Circular Economy and the circularity goals of a Digital Product Passport to develop a suitable technical solution. The chosen blockchain framework, Hyperledger Fabric, is presented, and its key components and features are highlighted. The thesis also delves into the design decisions and considerations behind the Digital Product Passport platform, explaining the architecture and transaction flow together with the prototype implementation and demonstration to showcase the functionality of the solution. Results and analysis provide insights into the challenges of the Circular Economy, sustainable resource management, and the Digital Product Passport, resulting in recommendations for future improvements and enhancements. Overall, this thesis offers a practical solution utilizing DLT to enable transparency and traceability in the Circular Economy, contributing to the realization of sustainable and efficient resource management practices to ultimately contribute to the set Circular Economy initiatives.
A rapid change to remote work during the beginning of the Covid-19 pandemic allowed many organizations to roll out new collaboration platforms to rapidly digitalize their workflows and processes in order to continue operation. This sudden shift to remote work revealed to employees the potential benefits of working remotely in the form of additional flexibility and also showed the challenges and barriers organizations could face by introducing such a strategy. This thesis aims to uncover the key considerations that the organizations of the industrial sector in Vorarlberg need to consider establishing a remote work strategy. According to the results from the research, the Covid-19 pandemic was as a paradigm change for the interviewed decision makers about how they thought about remote work and how they transformed their respective organizations too continue to operate. After the initial phase of Covid-19 restrictions organizations started to experiment with a remote work strategy of their own, based on their past experiences. For now, most of the interviewed organizations use already different remote work concepts and evaluate which one suits best their needs. The main considerations as to why an organization introduced a remote work strategy are to be an attractive employer and to stay ahead in the search for new talent. Further by introducing a remote work strategy, organizations need to change their rules of collaboration, adapt their core values to fit a remote workplace and to introduce collaboration platforms which are designed to support a remote workforce.
This thesis evaluates the feasibility of conducting visual inspection tests on power industry constructions using object detection techniques. The introduction provides an overview of this field’s state-of-the-art technologies and approaches. For the implementation, a case study is then conducted, which is done in collaboration with the partner company OMICRON Electronics GmbH, focusing on power transformers as an example. The objective is to develop an inspection test using photographs to identify power transformers and their subcomponents and detect existing rust spots and oil leaks within these components. Three object detection models are trained: one for power transformers and sub-components, one for rust detection, and one for oil leak detection. The training process utilizes the implementation of the YOLOv5 algorithm on a Linux-based workstation with an NVIDIA Quadro RTX 4000 GPU. The power transformer model is trained on a dataset provided by the partner company, while open-source datasets are used for rust and oil leak detection. The study highlights the need for a more powerful GPU to enhance training experiments and utilizes an Azure DevOps Pipeline to optimize the workflow. The performance of the power transformer detection model is satisfactory but influenced by image angles and an imbalance of certain sub-components in the dataset. Multi-angle video footage is a proposed solution for the inspection test to address this limitation and increase the size of the dataset, focusing on reducing the imbalance. The models trained on open-source datasets demonstrate the potential for rust and oil leak detection but lack accuracy due to their generic nature. Therefore, the datasets must be adjusted with case-specific data to achieve the desired accuracy for reliable visual inspection tests. The results of the case study have been well-received by the partner company’s management, indicating future development opportunities. This case study will likely be a foundation for implementing visual inspection tests as a product.
Programmable Logic Controller (PLC) modules are used in industrial settings to control and monitor various manufacturing processes. Detecting these modules can be helpful during installation and maintenance. However, the limited availability of real annotated images to train an object detector poses a challenge. This thesis aims to research object detection of these modules on real images by using synthetic data during training. The synthetic images are generated from CAD models and improved with Generative Adversarial Networks (GANs). The CAD models are rendered in different scenes, and perfectly annotated images are automatically saved. A technique called domain randomization is applied during rendering. It renders the modules in different poses with constantly changing backgrounds. As the CAD models do not visually resemble the real modules, it is necessary to improve the synthetic images. This project researches StarGAN and CycleGAN for the task of image-to-image translation. A GAN is trained with real and synthetic images and can then translate between these domains. YOLOv8 and Faster R-CNN are tested for object detection. The best mean Average Precision (mAP) is achieved when training with a synthetic dataset where 50% of the images were improved with StarGAN. When trained with YOLOv8 and evaluated on a real dataset, it achieves a mAP of 84.4%. Overall, the accuracy depends on the quality of the CAD models. Using a GAN improves the detection rate for all modules, but especially for unrealistic CAD models.
Scrum has been a prominent project management framework for managing software development projects. The scrum team embodies values such as commitment, focus, respect, courage, and openness to develop trust, which serves as the foundation of the scrum framework. However, in recent years, scrum teams are shifting towards a work-from-home environment which is relatively new to most of them and known to present various challenges. Looking at the benefits of adhering to scrum values, this study aims to investigate the challenges scrum teams experience in adhering to scrum values while operating virtually, as well as to explore practical strategies to overcome the identified challenges, particularly during the storming stage of team development. This research employed a qualitative methodology using semi-structured interviews with scrum team members who have experience working in a virtual environment. Through qualitative content analysis of semi-structured interviews, this research identifies significant challenges within five main categories: communication, collaboration, interpersonal dynamics, the virtual work environment, and personal workspace issues. However, beyond the challenges, the study reveals practical strategies as well for successful team dynamics and higher efficiency. The strategies derived from team members' experiences are categorized into six categories: enhanced meeting management, leveraging in-person engagements, optimizing tools & technology, effective communication strategies, team-building, and nurturing a positive work culture.
Purpose: In this thesis the viable system model (VSM) is used as a framework to develop a model for the management of a business alliance that contains the necessary and sufficient conditions for maintaining synergy of its constituent organisations and for adapting to a changing environment so that it can remain a long-term viable alliance. In addition, a model is developed that makes explicit the inherent link between the VSM and the core elements of knowledge management theory. Based then on the alliance management model and the link established between the VSM and knowledge management, an application framework is developed to guide practitioners in defining necessary alliance management functions and relationships, the knowledge required by that management to fulfill those functions, and the processes that need to be in place to manage that knowledge. Design/strategy: The research has been divided into four phases: theoretical construction, refinement with practitioners, real-world application, and evaluation of test case and toolset. The researcher has worked closely with practitioners actively involved in the formation of a new international alliance to develop a VSM model and application framework for the alliance management. Formally, the research strategy has been defined as an action research and the research philosophy as one of pragmatism. Findings/limitations: The developed application framework, has been successfully used to identify absent and incomplete roles, actions, and interactions within the management of the specific alliance test case. This has helped to demonstrate how the application framework and VSM model can be used to diagnose and, most importantly, to articulate and visualise management deficiencies to facilitate clear and unambiguous discussions. The timing of this cross-sectional research did not allow the application framework to be utilised from the outset of the alliance formation as an organisational planning tool and also not to its full extent to support the development of knowledge processes for the alliance management. However, the step-by-step approach used in developing the toolset and then explaining its application will allow the reader to judge its credability and generalisability for other practical applications. Practical implications: The developed toolset consists of a VSM for an alliance management, job descriptions for that management (responsibilities, interfaces, and core competencies), a visual model illustrating the link between the VSM and knowledge management, and an application framework to guide the filling of the alliance management job descriptions in phases of recruitment, onboarding, and development (of interfaces and activities processes). Overall, one could say that the conditions prescribed by the VSM are rather obvious and yet, as seen by the specific alliance test case, many of these conditions have been completely overlooked by a management that was more than capable, willing, and empowered to enact those conditions. This gives a good indication that the toolset which has been compiled in a visual and tabular systematic fashion may well be useful to practitioners for the organisational planning of an alliance management. The visual representation of a management role in the VSM as a set of knowledge episodes put forward by this research is significant. It forces the express recognition that knowledge management is an integral part of every interaction that takes place and every action performed that, according to the VSM, are necessary and altogether are sufficient for viability. It means that knowledge management cannot be considered as some abstract topic or unnecessary overhead or afterthought – it is entirely necessary, practical and forms a natural course of events during design of action/interaction processes. In other words, if an organisation is viable then, by definition, it does knowledge management whether or not it is formally recognised as such. The VSM, by defining necessary and sufficient actions and interactions for its roles, therefore provides a focus for relevant knowledge and serves as a tool for structured knowledge management. Originality/value: This research addresses a general academic call for hands-on insights of VSM applications by sharing real-world insights, artifacts and reflections generated by a practical and relevant organisational management application. It also addresses the potential, recognised by academics, for VSM as a framework for knowledge management by developing an intuitive model linking those theories and then using that model as part of a framework to guide its application. The introduction to aspects of knowledge management theory relevant to the model developed as well as the meticulousness and comprehensive explanation of the VSM provides a solid theoretical foundation for practitioners. The developed toolset is based on existing theories from multiple fields of research that have been logically linked and extended in an original and novel manner with a strong focus on practical application. This researcher’s hope is that this will stimulate interest for future research and practical application from academics and practitioners alike.
The implementation of direct-to-consumer (D2C) business models has become more important for companies trying to develop a competitive edge and improve consumer engagement in today's rapidly expanding e-commerce market. This master's thesis investigates the important success elements and problems of deploying D2C models in the e-commerce business. The research question focuses on identifying the factors that contribute to the successful transition to D2C models and the obstacles businesses encounter along the way. Through qualitative research using the Eisenhardt method and in-depth case studies with industry experts, this study provides valuable insights into key success factors for direct-to-consumer (D2C) business models in e-commerce.The findings highlight that businesses that effectively implement D2C models utilize key success factors such as a clear value proposition, customer engagement and relationship build- ing, seamless online experiences, targeted marketing and digital advertising, brand identity and storytelling, and flexibility and adaptability. However, they also face challenges related to operational adjustments, marketing and branding investments, competition, and market saturation. Based on these research outcomes, this thesis provides recommendations for businesses seeking to switch to or implement D2C models in e-commerce. These recommendations emphasize embracing a customer-centric mindset, developing digital capabilities, foster- ing strong leadership commitment, leveraging data and analytics, establishing direct customer relationships, optimizing operational processes, building brand trust and credibility, and allocating resources wisely. This master's thesis provides a comprehensive analysis of the key success factors and challenges associated with the transition to or implementation of D2C business models in the e-commerce industry. It provides advice to help companies successfully transition to D2C models.
This thesis aims to determine how banks can prepare for fulfilling and implementing the IFRS S1 requirements, which have been published by the International Sustainability Standard Board. It also examines the extent to which banks in Liechtenstein and Switzerland have already implemented the existing regulatory requirements in the area of sustainability transparency and integrated them into their financial reporting. The focus is to determine whether, and to what extent, these requirements enable banks to disclose relevant information on sustainability aspects in their financial reports. In order to answer the research question appropriately, a qualitative research method according to Mayring was used, which included conducting expert interviews. In this context, it is important to analyze the possibilities of IFRS S1 concerning the identification, assessment, and disclosure of sustainability risks and opportunities. The thesis also analyzes the impact of the regulatory requirements on banks, including the challenges of implementing IFRS S1 and the potential benefits and opportunities for banks of complying with the sustainability transparency requirements. The results are intended to develop a better understanding of how the regulatory requirements for sustainability transparency can be effectively used by banks to improve the quality and comparability of sustainability-related financial information under IFRS S1.
Activation of heat pump flexibilities is a viable solution to support balancing the grid via Demand Side Management measures and fulfill the need for flexibility options. Aggregators as interface between prosumers, distribution system operators and balance responsible parties face the challenge due to data privacy and technical restrictions to transform prosumer information into aggregated available flexibility to enable trading thereof. Thereby, literature lacks a generic, applicable and widely accepted flexibility estimation method for heat pumps,which incorporates reduced sensor and system information, system- and demand-dependent behaviour. In this paper, we adapt and extend a method from literature, by incorporating domain knowledge to overcome reduced sensor and system information. We apply data of five real-world heat pump systems, distinguish operation modes, estimate power and energy flexibility of each single heat pump system, proof transferability of the method, and aggregate the flexibilities available to showcase a small HP pool as a proof of concept.
Open tracing tools
(2023)
Background: Coping with the rapid growing complexity in contemporary software architecture, tracing has become an increasingly critical practice and been adopted widely by software engineers. By adopting tracing tools, practitioners are able to monitor, debug, and optimize distributed software architectures easily. However, with excessive number of valid candidates, researchers and practitioners have a hard time finding and selecting the suitable tracing tools by systematically considering their features and advantages. Objective: To such a purpose, this paper aims to provide an overview of popular Open tracing tools via comparison. Methods: Herein, we first identified 30 tools in an objective, systematic, and reproducible manner adopting the Systematic Multivocal Literature Review protocol. Then, we characterized each tool looking at the 1) measured features, 2) popularity both in peer-reviewed literature and online media, and 3) benefits and issues. We used topic modeling and sentiment analysis to extract and summarize the benefits and issues. Specially, we adopted ChatGPT to support the topic interpretation. Results: As a result, this paper presents a systematic comparison amongst the selected tracing tools in terms of their features, popularity, benefits and issues. Conclusion: The result mainly shows that each tracing tool provides a unique combination of features with also different pros and cons. The contribution of this paper is to provide the practitioners better understanding of the tracing tools facilitating their adoption.
Flexibility estimation is the first step necessary to incorporate building energy systems into demand side management programs. We extend a known method for temporal flexibility estimation from literature to a real-world residential heat pump system, solely based on historical cloud data. The method proposed relies on robust simplifications and estimates employing process knowledge, energy balances and manufacturer's information. Resulting forced and delayed temporal flexibility, covering both domestic hot water and space heating demands as constraints, allows to derive a flexibility range for the heat pump system. The resulting temporal flexibility lay within the range of 24 minutes and 6 hours for forced and delayed flexibility, respectively. This range provides new insights into the system's behaviour and is the basis for estimating power and energy flexibility - the first step necessary to incorporate building energy systems into demand side management programs.
Hot water heat pumps are well suited for demand side management, as the heat pump market faced a rapid growth in the past years with the trend to decentralized domestic hot water use. Sales were accelerated through wants and needs of energy conservation, energy efficiency, and less restrictive rules regarding Legionella. While in literature the model predictive control potential for heat pumps is commonly shown in simulations, the share of experimental studies is relatively low. To this day, experimental studies considering solely domestic hot water use are not available. In this paper, the realistic achievable model predictive control potential of a hot water heat pump is compared to the standard hysteresis control, to provide an experimental proof. We show for the first time, how state-of-the-art approaches (model predictive control, system identification, live state estimation, and demand prediction) can be transferred from electric hot water heaters to hot water heat pumps, combined, and implemented into a real-world hot water heat pump setup. The optimization approach, embedded in a realistic experimental setting, leads to a decrease in electric energy demand and cost per unit electricity by approximately 12% and 14%, respectively. Further, an increase in efficiency by approximately 13% has been achieved.
Immersive educational spaces
(2023)
"If only we had had such opportunities to grasp history like this when I was young" – words by an almost 80-year-old woman holding an iPad on which both, the buildings in the background and a tower in the form of a virtual 3D object, appear within reach. To "grasp" history - what an apt use of this action-oriented word for an augmented reality application built on considerations of thinking and acting in history. This telling image emerged during the first test run of the app i.appear which will be the focus of this article's considerations on the use of immersive learning environments. The application i.appear has been used in the city of Dornbirn (Austria) for a year now to teach historical content through location-based augmented reality and other interactive and multimedia technologies. After a brief description of the potential of such applications, the epistemological structure of the hosting app i.appear and its functionality will be outlined. This article will focus on the “Baroque Master Builders” tour of the hosting app that was created and tested as part of the current research.
This paper presents design, simulation, and optimization of the three-dimensional 1×4 optical multimode interference splitter using IP-Dip polymer as a core and polydimethylsiloxane (PDMS) Sylgard 184 as a cladding. The splitter was simulated by using beam propagation method in BeamPROP simulation engine of RSoft photonic tool and optimized for an operating wavelength of 1.55 µm. According to the minimum insertion loss, the dimensions of the MMI coupler and the length of the whole MMI splitter structure were optimized applying a waveguide with a core size of 4×4 µm2. The objective of the study is to create a design for fabrication by three-dimensional direct laser writing optical lithography.
We present design of planar 16-channel, 100-GHz multi-mode polymer-based AWG. This AWG was designed for central wavelength of 1550 nm applying AWG-Parameters tool. The AWG structure was created and simulated in the commercial photonic tool PHASAR from Optiwave. Achieved transmission characteristics were evaluated by AWG-Analyzer tool. For the design, multi-mode waveguides having a cross-section of (4x4) µm2 were used. The simulated results show strong worsening of the transmission characteristics in comparison when using single-mode waveguides. Nevertheless, the transmitting channels are clearly separated. The reason for using thicker multi-mode waveguides in the design is possibility to fabricate the AWG structure on polymer basis using direct laser writing lithography.
Coupling is one of the most frequently mentioned metric in software systems. However, to measure logical coupling between microservices, runtime information is needed or the availability of service-log files to analyze the calls between services is required. This work presents our emerging results, in which we propose a metric to statically calculate logical coupling between microservices based on commits to versioning systems. We performed an initial validation of the proposed metric with a dataset containing 145 open-source microservices projects. The results illustrate how logical coupling affects every system and increases overtime. However, we did not find a correlation between the number of commits or the number of developers and the introduction of logical coupling. In future, we investigate why, how, and when logical coupling is introduced in a system.
The paper deals with designing and numerical modelling a 2 x 2 optical switch for photonic integrated circuits based on 2 x 2 MMI elements and phase modulators. The 2 x 2 optical switch was modelled in the RsoftCAD with the simulation tool BeamPROP. The 2 x 2 optical switch is a common element for creating more complex 1 x N or N x N optical switches in all-optical signal processing.
In this paper, the design of three-dimensional configuration of Y-branch splitter is compared with Multimode Interference splitter. Both splitters use the IP-Dip polymer as a standard material for 3D laser lithography. The optical properties of the splitters for both approaches are discussed and compared.
In this work, we investigated the influence of different etch depths of the rib waveguides on the performance of SiN-based AWGs. For this purpose, an 8-channel 100 GHz AWG was designed for a center wavelength of 850 nm. The design parameters entered were calculated using the AWG-Parameters tool. The simulations were performed with a commercial photonic tool PHASAR from Optiwave. The simulated performance was evaluated using the AWG-Analyzer tool. For the AWG design, we used three identical rib waveguides with different etch depths to simulate possible etch imperfection. The simulations show the wavelength shift and degradation of the AWG performance.
Optoelectronic system based on photonic integrated circuits to miniaturize spectral domain OCT
(2023)
We present a miniaturized optical coherence tomography (OCT) setup based on photonic integrated circuits (PIC) for the 850 nm range. We designed a 512-channel arrayed waveguide grating (AWG) on a PIC for spectral domain OCT (SD-OCT) that is co-integrated with PIN-photodiodes and analog-to-digital-converters on one single chip. This image sensor is combined with all the necessary electronics to act as a camera. It is integrated into a fiber-based OCT system, achieving a sensitivity of >80dB and various samples are imaged. This optoelectronic system will allow building small and cost-effective OCT systems to monitor retinal diseases.
Semiconducting metal oxides are widely used for solar cells, poto-catalysis, bio-active materials and gas sensors. Besides the material properties of the used semiconductor,the specific surface topology of the sensor determines the device performance. We investigate the preparation and transfer suitable metals onto LIPPS structures on glass for gas sensing applications.
Deep etched structures in GaAs with high aspect ratio have promising applications in optoelectronics and MEMS devices. The key factors in their fabrication process are the choosing of proper mask material and etching conditions which results in high selectivity and an anisotropic etch profile with smooth sidewalls. In this work, we studied several types of mask materials (Al, Ni, Cr, SiO2) for deep reactive ion etching of GaAs using inductively coupled plasma system. Thus, several sets of experiments were performed with varying gas mixture, pressure and ICP/RF power. As a result, we find optimized conditions and minimal thickness of mask material for achieving deep etched (>140 m) GaAs structures.
Various carbon (nano-) forms, so-called allotropes, have become one of the most supporting activities in fundamental and applied research trends. Therefore, a universal deposition process capable of “adjusting” system parameters in one “deposition chamber” is highly demanding. Here, we present a low-pressure large area deposition system combining radiofrequency (RF) and microwave (MW) plasma in one chamber in different configurations, which offers a wide deposition window for the growth of sp2 carbon (carbon nanotubes, amorphous carbon), a mixture of sp2 and sp3 (diamond-like films) and pure sp3 carbon represented by diamond films. We will show that not only the type of plasma source (RF vs. MW) but also the gas mixture and plasma chemistry are crucial parameters for the controllable and reproducible growth of these allotropes at temperatures from 250 to 800 °C.
The properties of SiC and diamond make them attractive materials for MEMS and sensor devices. We innovated specific laser ablation techniques to fabricate membranes and cantilevers made of SiC or nano-(micro-) crystalline diamond films grown on Si/SiO2 substrates by microwave chemical vapour deposition (MWCVD). We started research to generate surface moulds to grow corrugated diamond films for membranes and cantilevers. A software tool was developed to support the design of micromechanical cantilevers. We can measure deformation and resonant frequency of diamond cantilevers and identify the global mechanical properties. A benchmark against finite element simulations enables an inverse identification of the specific system parameters and simplifies the characterization procedure.