University of Applied Sciences of the Grisons FHGR (Fachhochschule Graubünden)
Recent publications
Large-scale energy storage is viewed as a key complementary technology in a power system fed by a large share of intermittent renewable energies (RE). However, subsidies for RE – a well-intended market intervention – may distort price signals, thereby adversely undermining the profitability of energy storages, and thus, adequate investment incentives. This study provides novel causal estimates supporting this notion, using an econometric instrumental-variables framework and data on Austrian pumped storages, operating in the German–Austrian electricity market, characterized by a large share of generously subsidized RE. The findings show that RE significantly depress storage profitability and that further deployment of RE will intensify this effect. This may pose an obstacle against adequate investment in bulk energy storage capacity. Moreover, the results indicate that intensifying carbon pricing would significantly counteract the problem via a market-based price signal. This study contributes to the general debate on the design and effects of environmental regulation and particularly shows that a non-market-based policy for a green technology may adversely affect complementary technologies.
Nature-based health tourism is experiencing a resurgence. To determine its potential as a development opportunity for alpine destinations, it is necessary to analyse both the demand and supply side. Two surveys were conducted: a representative survey of the population of six countries of the Alpine Space exploring the perception of the Alps as a healthy destination in general and on the personal assessment of the health effect of natural resources in particular and an exploratory survey of tourism stakeholders in destination management, accommodation and gastronomy as well as (health) tourism services with a focus on the expected economic developments and the relevance of individual target groups for nature-based health tourism. The results demonstrate the need for a strategic development process which aligns perceptions with destination strategy and pre-existing offers. Two potential strategies are briefly outlined: 1. destinations with non-locally specific alpine natural health resources can develop broad tourism experiences for health conditions that occur across society with health a secondary aspect in marketing. 2. destinations featuring locally specific natural health resources with proven evidence can develop offers for a specific condition and are thus able to target a very specific group.
IntroductionIn the current COVID-19 pandemic, clinicians require a manageable set of decisive parameters that can be used to (i) rapidly identify SARS-CoV-2 positive patients, (ii) identify patients with a high risk of a fatal outcome on hospital admission, and (iii) recognize longitudinal warning signs of a possible fatal outcome.Methods This comparative study was performed in 515 patients in the Maria Skłodowska-Curie Specialty Voivodeship Hospital in Zgierz, Poland. The study groups comprised 314 patients with COVID-like symptoms who tested negative and 201 patients who tested positive for SARS-CoV-2 infection; of the latter, 72 patients with COVID-19 died and 129 were released from hospital. Data on which we trained several machine learning (ML) models included clinical findings on admission and during hospitalization, symptoms, epidemiological risk, and reported comorbidities and medications.ResultsWe identified a set of eight on-admission parameters: white blood cells, antibody-synthesizing lymphocytes, ratios of basophils/lymphocytes, platelets/neutrophils, and monocytes/lymphocytes, procalcitonin, creatinine, and C-reactive protein. The medical decision tree built using these parameters differentiated between SARS-CoV-2 positive and negative patients with up to 90–100% accuracy. Patients with COVID-19 who on hospital admission were older, had higher procalcitonin, C-reactive protein, and troponin I levels together with lower hemoglobin and platelets/neutrophils ratio were found to be at highest risk of death from COVID-19. Furthermore, we identified longitudinal patterns in C-reactive protein, white blood cells, and D dimer that predicted the disease outcome.Conclusions Our study provides sets of easily obtainable parameters that allow one to assess the status of a patient with SARS-CoV-2 infection, and the risk of a fatal disease outcome on hospital admission and during the course of the disease.
As advances in science and technology, crisis, and increased competition impact labor markets, reskilling and upskilling programs emerged to mitigate their effects. Since information on continuing education is highly distributed across websites, choosing career paths and suitable upskilling options is currently considered a challenging and cumbersome task. This article, therefore, introduces a method for building a comprehensive knowledge graph from the education providers’ Web pages. We collect educational programs from 488 providers and leverage entity recognition and entity linking methods in conjunction with contextualization to extract knowledge on entities such as prerequisites, skills, learning objectives, and course content. Slot filling then integrates these entities into an extensive knowledge graph that contains close to 74,000 nodes and over 734,000 edges. A recommender system leverages the created graph, and background knowledge on occupations to provide a career path and upskilling suggestions. Finally, we evaluate the knowledge extraction approach on the CareerCoach 2022 gold standard and draw upon domain experts for judging the career paths and upskilling suggestions provided by the recommender system.
Library standards for low-resource countries are intended to make it easier to set up and run a library even with few resources. The client for this thesis is COERESO (Cooperation, Equality, Respect), an association active in Rwanda. In order to develop an understanding of the conditions in low-resource countries, relevant sociological terms are defined. Then, based on the literature and on statements from school officials and students, criteria are created which serve as a basis for library standards. In addition, the standards and manifestos of IFLA and UNESCO were used as a source of inspiration.
Customer relationship management and marketing analytics have become critical for non-life insurers operating in highly competitive markets. As it is easier to develop an existing customer than to acquire a new one, cross-selling and retention are key activities. In this research, we focus on both car and household-liability insurance products and consider the time a customer owning only a single product takes before buying the other product at the same insurer. Based on longitudinal consumer data from a Swiss insurance company covering the period from 2011 to 2015, we aim to study the factors driving the duration to cross-selling. Given the different dynamics observed in both products, we separately study the car and household-liability insurance customer cohorts. Considering the framework of survival analysis, we provide descriptive statistics and Kaplan–Meier estimates along major customer characteristics, contract history and distribution channel usage. For the econometric analysis of the duration, we compare the results from Cox and accelerated failure time models. We are able to characterize the times related to the buying behavior for both products through several covariates. Our results indicate that the policyholder age, the place of residence, the contract premium, the number of contracts held, and the initial access channel used for contracting influence the duration to cross-selling. In particular, our results underline the importance of the tied agent channel and the differences along the geographic region and the urbanicity of the place of residence. By quantifying the effects of the above factors, we extend the understanding of customer behavior and provide a basis for developing models to time marketing actions in insurance companies.
In recent years, trade-control laws and regulations such as embargoes and sanctions have gained importance. However, there is limited empirical research on the ways in which small- and medium-sized enterprises (SMEs) respond to such coercive economic measures. Building on the literature on organizational responses to external demands and behavioral ethics, this study addresses this issue to better understand how external pressures and managerial decision-making are associated with the scope of trade-control compliance programs. Based on a sample of 289 SMEs, the findings show that the organizational responses of SMEs reflect proportionate adjustments to regulatory pressures but only if decision-makers are well informed and aware of the prevailing rules and regulations. Conversely, uninformed decision-making leads to a disproportionate response resulting in an inadequately reduced scope of the compliance program. In addition, the results indicate that SMEs that are highly integrated into supply chains are susceptible to passing-the-buck behavior.
Since the late 1990s, a legal paradigm shift has occurred regarding the acceptability of corruption in international business transactions. Today, foreign corruption is legally and ethically reprehensible, but the figures prove that for a long time it was part of what was considered common practice in international business, and corruption is still widespread around the globe. Against this background, the question arises as to what contribution international leaders can offer in the fight against corruption. In this context, this article describes combatting corruption as a leadership task and discusses the concept, importance and limitation of ethical leadership in anti-corruption efforts. Furthermore, it presents a selection of direct and indirect management tools international leaders can apply to mitigate and manage corruption risks. Finally, it discusses the context in which international leaders act to prevent corruption, specifically the organisational culture and the influence that leaders have upon it as individual agents.KeywordsInternational leadershipInternational managementEthical leadershipCompliance managementRisk managementCorruption
In machine learning, the presumably best model is selected from a variety of model candidates generated by testing different model types, hyperparameters, or feature subsets. The advent of deep learning has made model selection even more challenging due to the huge parameter search space. Relying on a single metric to select the best model does not consider class imbalances or the different costs of misclassifications. We argue that incorporating human knowledge to interactively analyse the per-class errors and class confusions over all model candidates enables a more efficient training process and yields better models for given applications. This paper proposes the model-agnostic approach ConfusionVis which allows to comparatively evaluate and select multi-class classifiers based on their confusion matrices. This contributes to making the models’ results understandable, while treating the models as black boxes. Therefore, we propose a novel method to measure and visualise distances between confusion matrices and an interactive query interface to incorporate all composition levels of class errors. The approach is evaluated in a user study and the applicability is shown by a case study where marine biologists investigate the conservation efforts of baleen whales by classifying whale species in acoustic recordings. ConfusionVis is available online:
Equalization reserves is an insurance liability with features of own capital. By law, Swiss reinsurance and non-life undertakings must hold equalization reserves within their statutory accounts. Regarding Swiss solvency modeling, the equalization reserves are set to zero. Swiss reinsurance and non-life undertakings define the upper limit and the corresponding transfer rule to the equalization reserves; however, this information is not disclosed. The goal of the study is to find a relationship between the equalization reserves and the publicly available technical account items, applying a generalized additive model (GAM). Thereafter, we transform the continuous variables into discrete ones, and we apply a generalized linear model (GLM). The study is based on published data from 1997 to 2018, whereby we restate the implicitly published equalization reserves. For reinsurance undertakings, the GAM model captures the relationship better than the GLM one; for non-life undertakings, the GLM model performs better. For reinsurance undertakings, the equalization reserves depend on the equalization reserves of the previous year, on the calendar year, on the legal form, on the technical result, on the administration and commission costs and on other costs. For non-life undertakings, the equalization reserves depend on the net claims payments, on the equalization reserves of the previous year, on the net change in claims reserves without change in equalization reserves, on the calendar year and on the net earned premium. Furthermore, we look at the need for equalization reserves: do the undertakings accumulate and release the equalization reserves? Further, the impact of taxes on the equalization reserves is looked at. The concept of equalization reserves avoids the misuse of tax optimization. We conclude that the discussion about disclosure of equalization reserves will restart. In addition, the definition of the upper limit of the equalization reserves could be widened by linking the equalization reserves to the insurance/reserving risk from the capital modeling.
Do Syrian civil war victims living in exile treat other Syrian refugees more favorably compared to members of the hosting society? We answer this question by analyzing cooperation decisions in a prisoner’s dilemma with a second stage including punishment among Syrian refugees, Germans, and Jordanians, in two host countries, Germany and Jordan. We find that Syrian refugees are more likely to cooperate when they are interacting with another refugee than when they are interacting with a German or a Jordanian participant. We find opposite results for both Germans and Jordanians who cooperate more when playing with Syrians than within their own group. Self-reported feelings of refugees suggest that in-group favoritism rather than out-group hostility drives this result, while punishment of defecting in-group and out-group members does not differ significantly for all groups. Thus, in-group favoritism seems to be a selective inclination that disappears when it clashes with other characteristics like reciprocity.
Clients may feel trapped into sharing their private digital data with insurance companies to get a desired insurance product or premium. However, private insurance must collect some data to offer products and premiums appropriate to the client’s level of risk. This situation creates tension between the value of privacy and common insurance business practice. We argue for three main claims: first, coercion to share private data with insurers is pro tanto wrong because it violates the autonomous choice of a privacy-valuing client. Second, we maintain that irrespective of being coerced, the choice of accepting digital surveillance by insurers makes it harder for the client to protect his or her autonomy (and to act spontaneously and authentically). The violation of autonomy also makes coercing customers into digital surveillance pro tanto morally wrong. Third, having identified an economically plausible process involving no direct coercion by insurers, leading to the adoption of digital surveillance, we argue that such an outcome generates further threats against autonomy. This threat provides individuals with a pro tanto reason to prevent this process. We highlight the freedom dilemma faced by regulators who aim to prevent this outcome by constraining market freedoms and argue for the need for further moral and empirical research on this question.
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963 members
Albert Weichselbraun
  • Swiss Institute for Information Science (SII)
Andreas Nicklisch
  • Centre for Economic Policy Research (ZWF)
Jan Mosedale
  • Institute for Tourism and Leisure (ITF)
Urs Dahinden
  • Swiss Institute for Information Science (SII)
Franz Kronthaler
  • Centre for Economic Policy Research (ZWF)
Pulvermühlestrasse 57, 7004, Chur, Grisons, Switzerland
Head of institution
Jürg Kessler, Prof., dipl. Ing. ETH, lic. oec. publ., Rektor
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