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The fact that services have emerged a driving force and the fastest growing sector in international trade attracts researchers to follow the changes taking place in the service industry. This study extends the scientific discussion on internationalization of service firms. Unlike previous research that examined factors that influence a single firm’s decision to internationalize, I acknowledge the heterogeneity of services, and based on the results obtained from secondary analysis of primary qualitative data sets, answer the main research question how internationalization motives differ between people-processing services, possession-processing services, and information-based services. This research goes beyond identification of variation in internationalization motives and analyses the service characteristics that might be responsible for the differences. In addition, I assess the key trends in the service sector and predict the possible future internationalization motives that are likely to emerge from the current trends.
Findings of this study reveal two major issues. First, it is evident that reasons for internationalization differ among hotel, retail firms and Higher education institutions representing people-processing services, possession-processing services, and information-based services respectively. Second, a few motives are common across sub-sectors, however the significance of the motives vary from sub-sector to sub-sector. I conclude that the differences in underlying structures of the respective service sub-sectors is the fundamental cause for the variation in internationalization motives among service sub-sectors. Other factors such as distinctive characteristics of service, firm’s competitive strategies, income elasticity of demand, and life-cycle stage of the service sub-sector also contribute to the differences in internationalization motives.
This paper also presents three different factors, which are likely to emerge as significant factors that influence service firm internationalization decision in future. (1) Company’s urge to be socially responsible and the need to contribute towards the environmental well-being (2) The need to sell regional products and services to neighbouring nations and respond to consumers’ demand for sustainable consumerism (3) Decision to penetrate foreign markets facilitated by the low risks and low cost of internationalization.
In recent years, ultrashort pulsed lasers have increased their applicability for industrial requirements, as reliable femtosecond and picosecond laser sources with high output power are available on the market. Compared to conventional laser sources, high quality processing of a large number of material classes with different mechanical and optical properties is possible. In the field of laser cutting, these properties enable the cutting of multilayer substrates with changing material properties. In this work, the femtosecond laser cutting of phosphor sheets is demonstrated. The substrate contains a 230 micrometer thick silicone layer filled with phosphor, which is embedded between two glass plates. Due to the softness and thermal sensitivity of the silicone layer in combination with the hard and brittle dielectric material, the separation of such a material combination is challenging for both mechanical separation processes and cutting with conventional laser sources. In our work, we show that the femtosecond laser is suitable to cut the substrate with a high cutting edge quality. In addition to the experimental results of the laser dicing process, we present a universal model that allows predicting the final cutting edge geometry of a multilayer substrate.
The purpose of an energy model is to predict the energy consumption of a real system and to use this information to address challenges such as rising energy costs, emission reduction or variable energy availability. Industrial robots account for an important share of electrical energy consumption in production, which makes the creating of energy models for industrial robots desirable. Currently, energy modeling methods for industrial robots are often based on physical modeling methods. However, due to the increased availability of data and improved computing capabilities, data-driven modeling methods are also increasingly used in areas such as modeling and system identification of dynamic systems. This work investigates the use of current data-driven modeling methods for the creation of energy models focusing on the energy consumption of industrial robots.
For this purpose, a robotic system is excited with various trajectories to obtain meaningful data about the system behavior. This data is used to train different artificial neural network (ANN) structures, where the structures used can be categorized into (i) Long Short Term Memory Neural Network (LSTM) with manual feature engineering, where meaningful features are extracted using deeper insights into the system under consideration, and (ii) LSTM with Convolutional layers for automatic feature extraction. The results show that models with automatic feature extraction are competitive with those using manually extracted features. In addition to the performance comparison, the learned filter kernels were further investigated, whereby similarities between the manually and automatically extracted features could be observed. Finally, to determine the usefulness of the derived models, the best-performing model was selected for demonstrating its performance on a real use case.
This study deals with the energy situation in Ny-Ålesund, an Arctic research station on the archipelago Svalbard, and aims at analysing the technical feasability of a transition to renewable energies by taking into consideration both the environmental and climatic impediments.
The analysis is based on a 27 year long collection of authentic meteorological data with all its strong fluctuations, seasonal as well as yearly. Great emphasis was put on the discussion of tried-and-tested renewable technologies that were compared to a new wind-based energy device that has yet to be tested for its reliability in the harsh environment of notably the Arctic winter. Meticulous calculations lead to the result that bifacial solar modules are an efficient means even in months when the sun stands low and their combination with wind-based devices prove to generate a maximum output. Geothermal energy seems to be promising in the region, but could not be evaluated due to a crucial lack of relevant data.
The study comes to the conclusion that the research station of Ny-Ålesund could well rely on a combination of renewable energy devices to cover its energy load, but needs to keep a back-up system of diesel run generators to bridge short periods of possible dysfunctions or standstills due to meteorological circumstances. Battery storage could only contribute to solve the problem of an unfortunate interruption of the energy supply, but it cannot serve as the entire back-up system since, at present, the need would go beyond all possible dimensions.
Packaging has important functions, such as the marketing function or protecting the product from spoilage. However, the supply in the supermarket must be viewed critically, as the majority of packaging is designed for single use. The question of how producers and retailers can increase customer acceptance of sustainable packaging in supermarkets has particular relevance in terms of the environmental impact of packaging waste. Although more and more customers are interested in the topic of sustainability, a gap between their attitude and behavior is apparent. This is addressed in more detail on the basis of two product categories. Expert interviews with international producers and retailers as well as a consumer survey allow the views of these three decision-makers to be taken into account. At the end, concrete recommendations for action are presented. These show that, among other things, information and transparency are essential in order to be able to influence consumers' purchasing decisions. In addition, the responsibility of all decision-makers is seen as the key to success.
In recent years, numerous studies around the world have examined the environmental potential of biochar to determine whether it can help address climate challenges. Several of these studies have used the Life Cycle Assessment (LCA) method to evaluate the environmental impacts of biochar systems. However, studies focus mainly on biochar obtained from pyrolysis, while the number of studies on biochar from gasification is small.
To contribute to the current state of LCA research on biochar from gasification, LCA was performed for biochar, electricity, and heat from a wood gasification plant in Vorarlberg, Austria. Woodchips from local woods are used as biomass feedstock to produce energy, i.e., electricity and heat. Thereby, biochar is obtained as a side product from gasification. The production of syngas and biochar takes place in a floating fixed-bed gasifier. Eventually, the syngas is converted to electricity in a gas engine and fed to the power grid. Throughout different stages within the gasification process, heat is obtained and fed into local heat grid to be delivered to customers. The biochar produced complies with the European Biochar Industry (EBI) guidelines and is used on a nearby farm for manure treatment and eventually for soil application. Thereby, the effect of biochar used for manure treatment is considered to reduce emissions occurring from manure, i.e., nitrogen monoxide (N2O). Further, the CO2 sequestration potential of biochar, i.e., removal of CO2 from the atmosphere and long-term storage, is considered. Several constructions, such as the construction of the gasification system and the heating grid, are included in the evaluation.
As input related reference flow, 1 kg of woodchips with water content of 40 % is used. Three functionals units are eventually obtained, i.e., 0.17 kg of biochar applied to soil, 4.47 MJ of heat and 2.82 MJ of electricity, each per reference flow. The results for Global Warming Potential (GWP) for biochar is – 274.7*10 - 3 kg CO2eq per functional unit, which corresponds to – 1.6 kg CO2eq per 1 kg biochar applied to soil. The GWP for heat results in 17.1*10 - 3 CO2eq per functional unit, which corresponds to 3.6*10 - 3 kg CO2eq per 1 MJ. For electricity, a GWP of 38.1*10 - 3 kg CO2eq per functional unit is obtained, which is equivalent to 13.5*10 - 3 kg CO2eq per 1 MJ.
The calculation was performed using SimaPro Version 9.1 and the ReCiPe method with hierarchist perspective.
Today, optics and photonics is widely regarded as one of the most important key technologies for this century. Many experts even anticipate that the 21st century will be century of photon much as the 20th century was the century of electron. Optics and photonics technologies affect almost all areas of our life and cover a wide range of applications in science and industry, e.g. in information and communication technology, in medicine, life science engineering as well as in energy and environmental technology. However even so attractive, the photonics is not well known by most people. To motivate especially young generation for optics and photonics we worked out a lecture related to the “light” for children aged eight to twelve years. We have prepared many experiments to explain the nature of light and its applications in our everyday life. Finally, we focused on the optical data transmission, i.e. how modern communication over optical networks works. To reach many children at home we recorded this lecture and offered it as a video online in the frame of children’s university at Vorarlberg University of Applied Sciences. By combining the hands-on teaching with having a fun while learning about the basic optics concepts we aroused interest of many children with a very positive feedback.
In this paper, low-loss Y-branch splitters up to 128 splitting ratio are designed, simulated, and optimized by using 2D beam propagation method in OptiBPM tool by Optiwave. For an optical waveguide, a silica-on-silicon material platform is used. The splitters were designed as a planar structure for a telecommunication operating wavelength of 1.55 m. According to the minimum insertion loss and minimum non-uniformity, the optimum length for each Y-branch is determined. The influence of the pre-defined S-Bend waveguide shapes (Arc, Cosine, Sine) and of the waveguide core size reduction on the splitter performance has been also studied. The obtained simulation results of all designed splitters with different S-Bend shape waveguides together with the different waveguide core sizes are discussed and compared with each other.
This paper analyses an electrical test tower of the OMCIRON electronics GmbH and evaluates whether a Predictive Maintenance (PdM) strategy can be implemented for the test towers. The company OMICRON electronics GmbH performs unit tests for its devices on test towers. Those tests consist of a multitude of subtests which all return a measurement value. Those results are tracked and stored in a database. The goal is to analyze the data of the test towers subtests and evaluate the possibility of implementing a predictive maintenance system in order to be able to predict the RUL and quantify the degradation of the test tower.
By assuming that the main degradation source are the relays of the test tower, a reliability modelling is performed which is the model-driven approach. The data-driven modelling process of the test tower consists of multiple steps. Firstly, the data is cleaned and compromised by removing redundances and optimizing for the best subtests where a subtest is rated as good if the trendability and monotonicity metric values are above a specific threshold. In a second step, the trend behaviours of the subtests are analyzed and ranked which illustrates that none of the subtests contained usable trend behaviour thus making an implementation of a PdM system impossible.
By using the ranking, the data-driven model is compared with the reliability model which shows that the assumption of the relays being the main error source is inaccurate.
An analysis of a possible anomaly detection model for a PdM is evaluated which shows that an anomaly detection is not possible for the test towers as well. The implementability of PdM for test towers and other OMICRON devices is discussed and followed up with proposals for future PdM implementations as well as additional analytical analyses that can be performed for the test towers.