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The paper presents a comprehensive model of a banking system that integrates network effects, bankruptcy costs, fire sales, and cross-holdings. For the integrated financial market we prove the existence of a price-payment equilibrium and design an algorithm for the computation of the greatest and the least equilibrium. The number of defaults corresponding to the greatest price-payment equilibrium is analyzed in several comparative case studies. These illustrate the individual and joint impact of interbank liabilities, bankruptcy costs, fire sales and cross-holdings on systemic risk. We study policy implications and regulatory instruments, including central bank guarantees and quantitative easing, the significance of last wills of financial institutions, and capital requirements.
During the Corona-Pandemic, information (e.g. from the analysis of balance sheets and payment behavior) traditionally used for corporate credit risk analysis became less valuable because it represents only past circumstances. Therefore, the use of currently published data from social media platforms, which have shown to contain valuable information regarding the financial stability of companies, should be evaluated. In this data e. g. additional information from disappointed employees or customers can be present. In order to analyze in how far this data can improve the information base for corporate credit risk assessment, Twitter data regarding the ten greatest insolvencies of German companies in 2020 and solvent counterparts is analyzed in this paper. The results from t-tests show, that sentiment before the insolvencies is significantly worse than in the comparison group which is in alignment with previously conducted research endeavors. Furthermore, companies can be classified as prospectively solvent or insolvent with up to 70% accuracy by applying the k-nearest-neighbor algorithm to monthly aggregated sentiment scores. No significant differences in the number of Tweets for both groups can be proven, which is in contrast to findings from studies which were conducted before the Corona-Pandemic. The results can be utilized by practitioners and scientists in order to improve decision support systems in the domain of corporate credit risk analysis. From a scientific point of view, the results show, that the information asymmetry between lenders and borrowers in credit relationships, which are principals and agents according to the principal-agent-theory, can be reduced based on user generated content from social media platforms. In future studies, it should be evaluated in how far the data can be integrated in established processes for credit decision making. Furthermore, additional social media platforms as well as samples of companies should be analyzed. Lastly, the authenticity of user generated contend should be taken into account in order to ensure, that credit decisions rely on truthful information only.
Nowadays, problems related with solid waste management become a challenge for most countries due to the rising generation of waste, related environmental issues, and associated costs of produced wastes. Effective waste management systems at different geographic levels require accurate forecasting of future waste generation. In this work, we investigate how open-access data, such as provided from the Organisation for Economic Co-operation and Development (OECD), can be used for the analysis of waste data. The main idea of this study is finding the links between socioeconomic and demographic variables that determine the amounts of types of solid wastes produced by countries. This would make it possible to accurately predict at the country level the waste production and determine the requirements for the development of effective waste management strategies. In particular, we use several machine learning data regression (Support Vector, Gradient Boosting, and Random Forest) and clustering models (k-means) to respectively predict waste production for OECD countries along years and also to perform clustering among these countries according to similar characteristics. The main contributions of our work are: (1) waste analysis at the OECD country-level to compare and cluster countries according to similar waste features predicted; (2) the detection of most relevant features for prediction models; and (3) the comparison between several regression models with respect to accuracy in predictions. Coefficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), respectively, are used as indices of the efficiency of the developed models. Our experiments have shown that some data pre-processings on the OECD data are an essential stage required in the analysis; that Random Forest Regressor (RFR) produced the best prediction results over the dataset; and that these results are highly influenced by the quality of available socio-economic data. In particular, the RFR model exhibited the highest accuracy in predictions for most waste types. For example, for “municipal” waste, it produced, respectively, R2 = 1 and MAPE = 4.31 global error values for the test set; and for “household” waste, it, respectively, produced R2 = 1 and MAPE = 3.03. Our results indicate that the considered models (and specially RFR) all are effective in predicting the amount of produced wastes derived from input data for the considered countries.
Sustainable tourism is a niche market that has been growing in recent years. At the same time, companies in the mass tourism market have increasingly marketed themselves with a “green” image, although this market is not sustainable. In order to successfully market sustainability, targeted marketing tactics are needed.
The aim of this research is to establish appropriate marketing tactics for sustainable tourism in the niche market and in the mass market. The purpose is to uncover current marketing tactics for both the mass tourism market and the sustainable tourism niche market. It also intends to explore how consumers who are more interested in sustainability differ from consumers with less interest in sustainability in terms of their perception of sustainability in tourism. Furthermore, this research paper will assess the trustworthiness of sustainable travel offers and the trustworthiness of quality seals in sustainable tourism. For this purpose, an online survey was conducted, which was addressed at German-speaking consumers. The survey showed, that consumers with more general interest in sustainability also consider sustainability to be more relevant in tourism. Offers for sustainable travel and quality seals were perceived as not very trustworthy. Moreover, no link could be found between the interest in sustainability and the perception of trustworthiness.
On the basis of the above, it is advisable to directly advertise sustainability in the niche market and to mention sustainability in the mass market only as an accompaniment or not at all. Further research could be undertaken to identify which factors influence the trustworthiness of offers, and trustworthiness of quality seals in sustainable tourism.
Delphi is a frequently used research method in the information systems (IS) field. The last fifteen years have seen many variants of the Delphi Method proposed and used in IS research. However, these variants do not seem to be properly derived; while all variants share certain characteristics, their reasoning for differentiation inconsistently varies. It seems that researchers tend to create “new” Delphi Method variants, although the underlying modification of the Delphi Method is, in fact, minor. This leads to a heterogeneity of Delphi Method variants and undermines scientific rigor when using Delphi. The study addresses this deficit and (1) identifies different variants of Delphi and determines their characteristics, (2) critically reflects to what extent a clear distinction between these variants exists, (3) shows the clearly distinguishable Delphi Method variants and their characteristics, (4) develops a proposed taxonomy of Delphi Method variants, and (5) evaluates and applies this taxonomy. The proposed taxonomy helps clearly differentiate Delphi Method variants and enhances methodological rigor when using the Delphi Method.
This document concerns IT security in production facilities. It is intended for small and medium-sized enterprises that are looking for a simple procedural model for ensuring IT security in production areas.
In order to raise readers’ awareness of IT security in production facilities, security incidents are presented in section 2. It is clear that cyber attacks on production facilities in this day and age are not random, but are instead based on a targeted process.
An overview of the most important standards and recommendations on the topic of “IT security in production” then follows in section 3.
Section 4 develops a concept for setting up an IT security system for small and medium-sized enterprises (SMEs) on the basis of a ten-point plan. The focus is not only on technical measures, but also in particular on the most frequently neglected organizational measures.
Section 5 then describes the outlook for future requirements and solutions in the context of Industry 4.0.
Cradle to Cradle – An analysis of the market potential in the German outdoor apparel industry
(2016)
The purpose of this study is to investigate the market potential in the German outdoor apparel industry by focusing on sustainable production in terms of environmental and human health. A literature study of the Cradle to Cradle (C2C) design concept is provided, as it represents a solution for pollution, waste and environmental destruction caused by the current industrial design and waste management. The data for the subsequent market- and competitive analysis of the German outdoor apparel industry was collected through secondary research in order to identify several key market indicators for the assessment of the market potential. The outcome of this research is the identification of a positioning strategy for outdoor apparel according to the C2C design concept. The results show stagnant growth rates in recent years in the German outdoor apparel market and strong rivalry among the competitors. However, a significant market potential was calculated and beneficial trends for sustainable outdoor brands were recognised. These findings reveal the existence of a market potential for an outdoor apparel brand according to the C2C design concept. By following a positioning strategy of transparency and full commitment to a sustainable production, the company might be able to gain market shares from its competitors, as future predictions indicate slow growth rates in the market. The results of this analysis can be of great interest for entrepreneurs that plan to enter the German outdoor apparel industry.