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- young-laplace equation (1)
This paper sought to identify and analyze what are the barriers towards women career’s development as business leaders in Brazil and Nicaragua when it comes to the country societal variables. In order to comprehend these barriers through women’s perception, qualitative data was chosen for this investigation, which was gathered through one-to-one interviews within businesswomen from Brazil and Nicaragua that have experience in leadership positions. The results of this research confirm that societal, economic, and political factors have great influence at gender equality and in how it affects women’s progress as business leaders. Thus, it can vary considerably between countries, even when they have similar culture backgrounds. Furthermore, it is imperative to comprehend these differences in order to close any gender gap in the field.
The e-commerce market has been growing for years and this trend seems to be continuing. Online stores for clothing are very successful. It seems that hardly any company can afford not to have a digital presence. This goes hand in hand with the fact that the range of products on offer to customers is getting bigger and bigger. But it's not just the range that's getting bigger, it's also the effort customers have to make to find the right product. For this reason, many successful online stores are already relying on AI. In doing so, companies are creating opportunities for customers that an employee could hardly manage. Implemented on the website, AI can check inventory, update it in real time, predict trends and evaluate customer or user data and make suitable recommendations. This is important for the customer because with the huge choice available, for one thing, personalization is increasingly important and being presented with a relevant selection. A central question is whether the recommendations are trustworthy and whether they can be equated with a real salesperson advising the customer. After all, trust is relevant in longterm customer relationships in that it leads to loyalty and satisfaction, which in turn increases the intention to repurchase. The recommendation tools mentioned are also of particular interest for another reason. On the one hand, they help customers to get a relevant selection of the offer and thus to get faster to the desired one. On the other hand, they are relevant for companies not only because of customer satisfaction, but also because of the chance to reduce returns. The large online stores for clothing offer their customers very generous opportunities to return the goods free of charge. In doing so, the companies have responded to customer wishes, because hardly anything is more important to them when it comes to online shopping: free returns. In this way, customers have minimized the risk of having to keep goods that do not fit or please them. This thesis examines whether recommendation tools can help customers to better assess the sizes and properties of clothing, so that they receive more suitable clothing and do not even feel the need to order several sizes of the same item of clothing. It can therefore be assumed that trust in the recommendations of the AI tools reduces uncertainty, which in turn should reduce the intention to return goods. Another assumption to be tested is that of the perceived usefulness of the recommendation tools. As a prerequisite to get an assessment of these assumptions is the usage of the tools. Therefore, a survey was initiated in the DACH region to assess the extent to which usage influences the factors mentioned. It was found by means of a regression analysis that the frequency of online purchases, mediated by perceived usefulness, explains the influence on trust.
Systems are constantly increasing in complexity. This poses challenges to managing and using system knowledge. The Systems Modeling Language (SysML) is a modeling language specifically for systems, while Machine Learning (ML) is a tool to tackle complex problems. Currently, no bridge between systems modelled in SysML and ML regarding said systems has been proposed in literature. This thesis presents an approach that uses Model-driven Software Engineering (MDSE) and Template-based Code Generation (TBCG) to generate a ML IPython Notebook (IPYNB) from a SysML model. A mapping configuration using JavaScript Object Notation (JSON) allows the definition of mappings between SysML elements and template variables, enabling configuration and user-supplied templates. To test the approach, a SysML model describing ML to predict the weather based on data is created. Python ML templates are supplied and template variables mapped with the JSON mapping configuration are proposed in the thesis. The outcome is an executable IPYNB that contains all information from the SysML model and follows the modelled workflow. The findings of the work show that model-driven ML using SysML as a modeling language is beneficial due to the representation of ML knowledge in a general-purpose modeling language and the reusability of SysML model elements. It further shows that TBCG and a mapping configuration allow for more flexible code generation without changing the source implementation.
Offline speech to text engine for delimited context in combination with an offline speech assistant
(2022)
The inatura museum in Dornbirn had planned an interactive speech assistant-like exhibit. The concept was that visitors could ask the exhibit several questions that they would like to ask a flower. Solution requirements regarding the functionalities were formulated, such as the capacity to run offline because of privacy reasons. Due to the similarity of the exhibit, open-source offline Speech To Text (STT) engines and speech assistants were examined. Proprietary cloud-based STT engines associated with the corresponding speech assistants were also researched. The aim behind this was to evaluate the hypothesis of whether an open-source offline STT engine can compete with a proprietary cloud-based STT engine. Additionally, a suitable STT engine or speech assistant would need to be evaluated. Furthermore, analysis regarding the adaption possibilities of the STT models took place. After the technical analysis, the decision in favour of the STT engines called "Vosk" was made. This analysis was followed by attempts to adapt the model of Vosk. Vosk was compared to proprietary cloud-based Google Cloud Speech to Text to evaluate the hypothesis. The comparison resulted in not much of a significant difference between Vosk and Google Cloud Speech to Text. Due to this result, a recommendation to use Vosk for the exhibit was given. Due to the lack of intent parsing functionality, two algorithms called "text matching algorithm" and "text and keyword matching algorithm" were implemented and tested. This test proved that the text and keyword matching algorithm performed better, with an average success rate of 83.93 %. Consequently, this algorithm was recommended for the intent parsing of the exhibit. In the end, potential adaption possibilities for the algorithms were given, such as using a different string matching library. Some improvements regarding the exhibit were also presented.
Startups usually have high growth ambitions but only limited resources. Therefore, they are looking for efficient and effective methods to grow their business. However, if they go interna-tional, challenging changes will likely be made if the company is not focused on the global market. The aim of this work is therefore to support startups in the internationalization of their business and to provide guidance from the beginning by using strategic marketing elements to facilitate this process. To achieve this, a qualitative method of analysis was chosen. First, a literature review was conducted on the relevant topics of a startup, strategic marketing, and internationalization. Five success factors emerged from the literature: commitment, strategy, research, marketing mix adaptation, and organization and network. These were then ana-lyzed in more detail in expert interviews. The analysis of the interview results shows that for the internationalization of startups, the commitment to internationalization and a global mindset is of great importance from the very beginning. This is because they influence all supporting and strategic marketing elements.
The number of electric vehicles will increase rapidly in the coming years. Studies suggest that most owners prefer to charge their electric vehicle at home, which will fuel the need for charging stations in residential complexes where vehicles can be charged overnight. Currently, there already are over 100 such residential complexes, with another 70 added every year in Vorarlberg alone. In most existing residential complexes, however, the grid connections are not sufficient to charge all vehicles at the same time with maximum power. In addition, it is also desirable for grid operators and electricity producers that the power demand be as smooth and predictable as possible. To achieve this, ways to manage flexible loads need to be found, which can operate within the technical constraints. Therefore, the most common scenarios how the load can be made grid-friendly with the help of optional battery storage and/or photovoltaics using optimization methods of linear and stochastic programming were examined. At the same time, the needs of the vehicle owners for charging comfort - namely to find their vehicles reliably charged at the time of their respective departure - were addressed by combining both objectives using suitable weights. The algorithms determined were verified in practice on an existing Vlotte prototype installation. For this purpose, the necessary programs were implemented in Python, so that the data obtained during the test operation, which lasted one month, could be subjected to a well-founded analysis. In addition, simulation studies helped to further reveal the influence of PV and BESS sizing on the achievable optimums and confirm that advanced optimization algorithms such as the ones discussed are a vital contribution in reducing the charging stations’ peak load while at the same time maintaining high satisfaction levels.
The demand for managing data across multiple domains for product creation is steadily increasing. Model-Driven Systems Engineering (MDSE) is a solution for this problem. With MDSE, domain-specific data is formalized inside a model with a custom language, for example, the Unified Modelling Language (UML). These models can be created with custom editors, and specialized domains can be integrated with extensions to UML, e.g., the Systems Modeling Language (SysML). The most dominant editor in the open-source sector is Eclipse Papyrus SysML 1.6 (Papyrus), an editor to create SysML diagrams for MDSE.
In the pursuit of creating a model and diagrams, the editor does not support the user appropriately or even hinders them. Therefore, paradigms from the diagram modelling and Human Computer Interaction (HCI) domains, as well as perceptual and design theory, are applied to create an editor prototype from scratch. The changes fall into the categories of hierarchy, aid in the diagram composition, and navigation. The prototype is compared with Papyrus in a user test to determine if the changes have the effect of improving usability.
The study involved 10 participants with different knowledge levels of UML, ranging from beginners to experts. Each participant was tested on a navigation and modelling task in both the newly created editor, named Modelling Studio, and Papyrus. The study was evaluated through a questionnaire and analysis of the diagrams produced by the tasks.
The findings are that Modelling Studio’s changes to the hierarchical elements improved their rating. Furthermore, aid for diagram composition could be reinforced by changes to the alignment helper tool and adjustments to the default arrow behaviour of a diagram. Lastly, model navigation adjustments improve a link’s visibility and rating of a specialized link (best practice). The introduction of breadcrumbs had limited success in bettering navigation usability. The prototype deployed a broad spectrum of changes that found improvement already, which can, however, be further improved and tested more thoroughly.
Projects, in which software products, services, systems and solutions are developed, all rely on the right requirements to be established. Software requirements are the expression of user wants or needs that have to be addressed, business objectives that have to be met, as well as capabilities and functionality that has to be developed. Meanwhile, practice shows that very often incorrect, unclear or incomplete requirements are established, which causes major problems for such projects. It could lead to budget overruns, missed deadlines and overall failure in worst-case scenarios.
The field of requirements engineering emerged as an answer to these shortcomings, aiming to systematize and streamline the process that
establishes requirements. Requirements elicitation is a key component of this process, and one of its starting points. The current thesis attempts to outline best practices in requirements elicitation, as well as what issues, obstacles and challenges are currently faced, and then present this through the lens of national culture. In this way its effects on the practice, if any, could be highlighted and studied further. The way this was achieved was by interviewing practitioners from two nations, which are shown to be
culturally different, and then comparing and contrasting the findings.
Meanwhile, the validity of those findings was enhanced by comparisons with existing literature.
Even though the findings were not compelling enough to form generalizations or concrete conclusions about the effects of national culture on requirements elicitation, these findings revealed patterns that could be worth exploring further. When it comes to requirements elicitation itself, it was observed to benefit from a structured and systematic approach, and be
most effective with one-on-one, instead of group interactions. The main pain points of the process stem from the complexity of communication, but are not always obvious. Practitioners are also advised to carefully plan the gathering of requirements, as the source may not have them readily available, and could even be unclear about what exactly is needed. Overall, this thesis research could be considered successful in its goal to shed a modicum of light on the issue at hand from a different, underexplored angle. By following a systematic and methodical approach, this research has also been made easier to expand or replicate.
Observing the ratios of the rail usage in terms of passenger travelled per km and per capita, we see that there are huge differences between countries, so some railway systems are performing better in catching passengers than others. By analysing the factors that make the railways attractive for users, and setting standard values for these factors, we can analyse how well a system is performing. This paper has investigated those factors and developed an assessment tool that will inform about the required improvements, so in a later stage specific strategies can be developed to increase the performance in order to attract more passengers. Spain will be used as case study, since the country has specially low passenger rail usage compared to other countries even though the large investments in high speed lines the country undertook in the last decades.
Nowadays, online marketing is becoming increasingly important not only in the B2C but also in the B2B sector, as evidenced by marketing budget expenditures. Companies pursue overarching goals involving visibility and attention from prospective customers in order to raise brand awareness and as a result, outperform increasing market competition. This begs the question of whether online marketing is appropriate for increasing brand awareness.
The master´s thesis topic developed from both a personal as well as a professional perspective. Private research increased the author´s interest in the topic of online marketing. Furthermore, brands, whose level of awareness needs to be improved, are becoming a more common topic of professional debates. In this way, the research of the current master´s thesis was created.
The aim of this master's thesis was to discover how online marketing can be used to increase awareness of a brand. This will be analyzed by using the brand turn to zero, which offers consulting services for B2B customers in the sustainability industry. In this context, suitable and visible online marketing channels for increasing brand awareness are to be identified. In addition to this, suitable content for the company´s own as well as paid online marketing channels need to be collected. Furthermore, the influence that online marketing has on creating brand image awareness is to be presented.
Research questions are defined in order to achieve the described objectives. Within the scope of the master thesis, one main research question, as well as three sub-research questions, are to be answered based on the literature as well as the generated output resulting from the empirical part. Eight existing B2B customers of turn to zero, originating from com-mercial and industrial sectors, were interviewed in the empirical part. The interview findings were evaluated by using qualitative content analysis according to Mayring.
Research results showed that targeted combinations of online marketing channels are contributing to increase brand awareness. In addition, the research succeeded in determining suitable communication content for various online marketing channels. Furthermore, the in-fluence of online marketing could be investigated more closely in terms of brand image.
Erosion due to cavitation is a common problem for any kind of water turbine. Most of the currently used techniques to detect cavitation are using an Acoustic Emission (AE) sensor and highspeed cameras during operation. For the pelton wheel which is subject of this thesis it is impossible to take pictures during operation, because of the splashing water and the mist. Therefore this thesis aims to explore possibilities in detecting erosion on the buckets of the pelton wheel on images taken during manual inspections. Since the provided images are snapshots taken with a mobile phone camera without a tripod, a lot of effort was invested in the preprocessing of the images. For the main task, the classification of the erosion, two methods were evaluated: Local Binary Patterns (LBP) + kN-earest neighbor classification and the classification with a Convolutional Neural Network (CNN). The given 2405 images, contained 4810 buckets on which the erosion was graded from zero to four. This means the baseline for the classification accuracy is 20%. LBP + kNearest neighbor classification scored 32.03%. The chosen CNN model, a light version of the Xception architecture outperformed the LBP + kNearest classification with 58,29%. The biggest issue found during research is the variance of the erosion grading by the maintainance personnel. Reasons for this are: no objective grading critera like the area of erosion in mm2, classification by different employees, a shift in grading from overall bucket condition to erosion from cavitation and too many classes for grading. The mentioned reasons were confirmed by the manual classification experiment were an IllwerkeVKW employee had to perform the grading on images of the dataset. The contestants accuracy score was 36% for this task. The result of 58,29% classification accuracy indicates that an automated grading of erosion by cavitation is feasible.
Today, industrial B2B manufacturers face a rapidly changing environment, exacerbated by increasing globalization and associated shifts in the competitive landscape. Digital transformation and the emergence of new innovations and technologies are forcing companies to rethink their business models and offerings to integrate digital services to strengthen competitive advantages. Suppliers are becoming more deeply involved in customer processes through digital after-sales services, with the aim of exploiting efficiencies. Following the servitization transformation, companies intend to change their purpose from focusing on the pure physical product to becoming a service provider with emphasis on value creation and the capture of the customer.
To investigate how customer and supplier perspectives agree and what requirements each side has for digital after-sales services, exploratory qualitative research was conducted with customers and suppliers by means of one-on-one interviews. The thesis aimed to assess the status, progress, and future possibilities of implementing digital after-sales services and business models based on them. Research shows that the far-reaching establishment of product-accompanying services with strong connectivity and customer-centricity is primarily relevant. Disruptive business models still require a mind-shift and organizational readiness on the part of both customers and suppliers. In principle, digitization in after-sales interaction is beneficial and should be steadily advanced to make customer processes as well as further developments at the supplier level more efficient and well-founded through the analysis of real data. Overall, this thesis outlines important aspects that need to be considered while developing digital service innovations to deal with customer demands appropriately.
Keywords: Servitization, Digital After-Sales Services, Predictive Maintenance, Remote Monitoring, Digital Interaction, Digital Service Innovation, Digital Service Innovation Process
The presented master thesis of the study subject International Marketing and Sales at the Fachhochschule Vorarlberg in Dornbirn deals with the influence of emotions on the attitude toward hydrogen cars and their purchase intention. For this purpose, an empirical analysis with a correlation analysis was conducted in order to be able to determine the correlations of the individual parameters.
At the beginning of the thesis the hydrogen technology was presented in more detail and by means of suitable criteria it was shown that the hydrogen car represents a certain potential, however, in comparison to the combustion cars and electric cars, the hydrogen car is currently in third place. The relatively long range, the fast-refueling and the sustainability were identified as advantages, while the current high price and the poorly developed refueling station network are currently the biggest ob-stacles to a hydrogen car. It can be seen that research and development of hydrogen cars is being driven forward in many countries around the world, including by the gov-ernment side through the provision of various subsidies. For this reason, the future development of the driving technology remains exciting and simultaneously uncertain.
In the second step of the work, emotions were examined in more detail. The aim was to find out which emotions exist and which of them are predominant when buying a car, and then to find out what influence emotions have on the cognitive process, the attitude, and the purchase intention. It turned out that the majority of the population is highly involved in the purchase of a car and therefore tries to make rational decisions, which makes the influence of emotions more difficult, but not impossible.
By presenting suitable marketing tools for measuring emotions, it was shown that measuring emotions is a difficult undertaking. Measurement is often difficult or expen-sive and involves a great deal of effort. For this reason, beside the presentation of marketing tools, the strategic approach for a marketing campaign was also presented.
Based on the conducted empirical analysis, the influence of emotions on attitude and purchase intention could not be significantly confirmed but it could be proven that the knowledge about hydrogen cars is currently low. One inside is that an increase in awareness increases the purchase intention of hydrogen cars. Furthermore, a signifi-cant correlation between the sustainable attitude and the purchase intention could be proven. In addition, people who like to follow new trends are more likely to buy a hy-drogen car than others. This paper concludes with a brief summary of the findings and an outlook on the potential for improvement of the hydrogen car market.
Keywords: Hydrogen Cars, Sustainability, Emotions in Marketing, Purchase Inten-tion, Attitude, Marketing Tool
In recent years, more and more companies have become aware that a brand also has a social dimension, and with the advent of social media platforms, brand communities have experienced a shift from a traditional offline to more of an online presence. Brands of innovative consumer durables have also recognized social media brand communities as a very significant marketing strategy. It is therefore important to understand the influence of these communities on members' purchase intentions.
This master’s thesis has the goal of demonstrating to enterprises what aspects of a social media brand community will influence the purchase intention of its members and what should be considered in order to enhance it. This will ultimately lead to the following research question: How do social media brand communities influence the diffusion process of innovative consumer durables in the DACH region?
To answer this, a quantitative study has been conducted that has targeted people who are participating in a social media brand community of innovative consumer durables in the DACH region. This involved testing various criteria of a social media brand community and their impact on the diffusion process (purchase intention).
The findings of the study revealed that increased positive electronic word-of-mouth leads to enhanced purchase intention of members. Furthermore, the research has shown that higher identification with a social media brand community, greater engagement, increased entertainment value, faster corporate responsiveness, and reduced occurrence of social spam, do not have a positive effect on the diffusion process of innovative consumer durables.
The detection of glucose is an essential part of diabetes management and can help to prevent secondary diseases, that can occur as a result of diabetes. For this reason, it is important to improve the current glucose monitoring by developing novel sensors with high efficiency, low cost and compact design. The use of microelectrodes with interdigitated array (IDA) structures reduces the total detector size while providing benefits such as large currents, high sensitivity, and fast response. The aim of this thesis is to develop a novel sensor based on platinum interdigitated array (IDA) electrodes and to investigate which method is most effective for the detection of glucose. This work is divided into two parts. The first part is focused on the design and the fabrication of the sensor chips. The second part is concerned with the electrochemical characterisation of the sensors. Two distinct sensor designs are created, each consisting of a four-electrode system arranged as an interdigitated array. For the fabrication of the sensors, two different manufacturing processes are used. A lift-off process is used to fabricate the 2 μm-Gap sensor chips, whereas a lift-off free process is applied to produce the nanogap sensor chips. The electrochemical characterisation of both sensor chips is achieved by the immobilisation of the enzyme glucose oxidase (GOx) on the electrode surface. This thesis investigates the immobilisation of GOx by reduction of diazonium salts and the direct immobilisation of GOx by cyclic voltammetry. As a result of this work, it has been demonstrated that glucose detection by reduction of diazonium salts is error-prone due to modification with a multi-step procedure and is not suitable for our sensors based on platinum IDA electrodes. The direct immobilisation of GOx by cyclic voltammetry, by contrast, demonstrates the successful detection of glucose. In glucose solutions ranging from 5 mM to 20 mM, a direct correlation between the glucose concentration and the measured current is obtained. The reproducibility of direct immobilization is demonstrated by repeated performance with various sensors.
The rapidly evolving nature of Industry 4.0 has confronted corporates with the challenge of being able to react rapidly and nimbly (Van Solingen, 2020). Hence, many corporates need to embark on a journey of adaptation toward becoming agile organisations (Schmitz, 2018). However, this adaptation can only be achieved if employees fully commit to changing to an agile posture, and the required commitment is simply not forthcoming without proper corporate initiatives (Neves & Caetano, 2009). As there is no holistic summary of corporate initiatives required to boost employees' commitment to change when approaching an agile transformation, this study supplements the current research. The initiatives are derived from the existing literature and from unique insights given into a European automotive supplier that is currently managing a global agile transformation. Employees’ perceptions of the transformation in Austria and China were recorded and conclusions regarding what drives employees’ commitment to change and what led to job terminations were determined.
This master thesis investigates drivers and barriers of innovation workshops for an intercultural participant group. Actively dealing with innovation management is considered vital for companies which are acting on competing markets. An innovation workshop is a useful tool in order to foster innovation ability, develop innovative ideas and drive innovation forward. Intercultural participant groups are not only a common challenge in today's business world but also entail several benefits as they incorporate diverse knowledge bases and perspectives and hence contribute to the ideation and innovation process. Within the master thesis a broad variety of barriers and drivers are evaluated. Main barriers of innovation workshops for an intercultural participant group are high conflict potential, miscommunication, language barriers, a lack of management support, no agreement on workshop objectives as well as poor workshop preparation, organization and facilitation. Main drivers of innovation workshops for an intercultural participant group are a heterogeneous group composition, intercultural competence of the facilitator, the opening up of mindset silos, an intensive workshop preparation and empathetic facilitation. These drivers and barriers build the basis for the determination of success factors and recommendations for action for organizers and facilitators of an innovation workshop for an intercultural participant group. In the further course of the paper an exemplary workshop design will be presented as a guideline and framework for managerial practice