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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.
Modeling the dynamic of breath methane concentration profiles during exercise on an ergometer
(2015)
Smart services disrupt business models and have the potential to stimulate the circular economy transition of regions, enabling an environmentally friendly atmosphere for sustainable and innovation-driven growth of regions. Although smart services are powerful means for deploying circular economy goals in industrial practices, there is little systematic guidance on how the adoption of smart services could improve resource efficiency and stimulate smart regional innovation-driven growth, enabled through circular design. Implemented in the scope of Vorarlberg’s smart specialization strategy, this paper contributes to the literature on the circular economy and regional innovation-driven growth by assessing critical factors of the value creation and value capture implemented within the scope of the quadruple helix system. By identifying the main challenges and opportunities of collaborative value creation and value capture in setting-up smart circular economy strategies and by assessing the role of innovation actors within the quadruple helix innovation system, the study provides recommendations and set of guidelines for managers and public authorities in managing circular transition. Finally, based on the analysis of the role of actors in creating shared value and scaling-up smart circular economy practices in the quadruple helix innovation systems, the paper investigates the role of banks as enablers of circular economy innovation-driven regional growth and smart value creation.
Complementarities and synergies of quadruple helix innovation design in smart city development
(2020)
Increased urbanization trends are stimulating regional needs to support transitions from urban environments to smart cities, using its holistic perspective as a source to innovation. Strong relations between smart cities, urban and regional development, are getting increased attention both at policy and implementation level, providing fertile ground for execution of the new European policy frameworks that supports quadruple helix approaches to innovation. Smart specialization strategies (RIS3) encompass such initiatives, placing ICT and collaboration between academia, industry, government, and citizen at the center of urban innovation. However, there is still lack of research on effects of such approaches to innovation, involving both quadruple helix clusters and ICT in utilizing innovation potentials for developing smart cities. This study aims to increase the understanding on how quadruple helix urban innovation strengthens competitiveness of regions by improving its local smart areas – RIS3. We identified smart specialization patterns and applied comparative benchmark between nine smallmedium sized urban regions in Central Europe. Building on these results, the study provides an overview of the effects of RIS3 strategies implemented through quadruple helix innovation clusters on competitiveness of regions and Smart City development.
A covariance matrix self-adaptation evolution strategy for optimization under linear constraints
(2018)
A multi-recombinative active matrix adaptation evolution strategy for constrained optimization
(2019)
Analysis of the (μ/μI,λ)-CSA-ES with repair by projection applied to a conically constrained problem
(2019)
Why do some countries assign a major role to wind energy in decarbonizing their electricity systems, while others are much less committed to this technology? We argue that processes of (de-)legitimation, driven by discourse coalitions who strategically employ certain storylines in public debates, provide part of the answer. To illustrate our approach, we comparatively investigate public discourses surrounding wind energy in Austria and Switzerland, two countries that differ strongly in wind energy deployment. By combining a qualitative content analysis and a discourse network analysis of 808 newspaper articles published 2010–2020, we identify four distinct sets of storylines used to either delegitimize or legitimize the technology. Our study indicates that low deployment rates in Switzerland can be related to the prominence of delegitimizing storylines in the public discourse, which result in a rather low socio-political acceptance of wind energy. In Austria, by contrast, there is more consistent support for wind energy by discourse coalitions using a broad set of legitimizing storylines. By bridging the related but separate literatures of technology legitimacy and social acceptance, our study contributes to a better understanding of socio-political conflict and divergence in low-carbon technological pathways.
The usage of data gathered for Industry 4.0 and smart factory scenarios continues to be a problem for companies of all sizes. This is often the case because they aim to start with complicated and time-intensive Machine Learning scenarios. This work evaluates the Process Capability Analysis (PCA) as a pragmatic, easy and quick way of leveraging the gathered machine data from the production process. The area of application considered is injection molding. After describing all the required domain knowledge, the paper presents an approach for a continuous analysis of all parts produced. Applying PCA results in multiple key performance indicators that allow for fast and comprehensible process monitoring. The corresponding visualizations provide the quality department with a tool to efficiently choose where and when quality checks need to be performed. The presented case study indicates the benefit of analyzing whole process data instead of considering only selected production samples. The use of machine data enables additional insights to be drawn about process stability and the associated product quality.
With Cloud Computing and multi-core CPUs parallel computing resources are becoming more and more affordable and commonly available. Parallel programming should as well be easily accessible for everyone. Unfortunately, existing frameworks and systems are powerful but often very complex to use for anyone who lacks the knowledge about underlying concepts. This paper introduces a software framework and execution environment whose objective is to provide a system which should be easily usable for everyone who could benefit from parallel computing. Some real-world examples are presented with an explanation of all the steps that are necessary for computing in a parallel and distributed manner.
Stability of selected volatile breath constituents in Tedlar, Kynar and Flexfilm sampling bags
(2013)