Accelerating sustainability in companies: A taxonomy of information systems for corporate carbon risk management

For increasing sustainability and mitigating climate change, corporate carbon risk management (CCRM) can be a key enabler. As we outline in this paper, companies currently lack processes and approaches in practice to actively manage complex risks caused by carbon emissions in the form of a comprehensive CCRM. To address this issue and to bridge the gap of lacking digital solutions for CCRM, we develop a taxonomy that illustrates characteristics of information system solutions that foster CCRM. While our taxonomy builds on a systematic literature review, we evaluate our results with eleven semi-structured expert interviews. We conclude that CCRM is a complex field in which information systems can provide significant support at many stages. Thereby, our taxonomy also contributes to Green IS research and may act as guidance for practitioners. Moreover, we discuss how digital technologies like Blockchains and Artificial Intelligence can pave the way towards a target-oriented CCRM in companies

How to trade electricity flexibility using artificial intelligence - An integrated algorithmic framework

In course of the energy transition, the growing share of Renewable Energy Sources (RES) makes electricity generation more decentralized and intermittent. This increases the relevance of exploiting flexibility potentials that help balancing intermittent RES supply and demand and, thus, contribute to overall system resilience. Digital technologies, in the form of automated trading algorithms, may considerably contribute to flexibility exploitation, as they enable faster and more accurate market interactions. In this paper, we develop an integrated algorithmic framework that finds an optimal trading strategy for flexibility on multiple markets. Hence, our work supports the trading of flexibility in a multi-market environment that results in enhanced market integration and harmonization of economically traded and physically delivered electricity, which finally promotes resilience in highly complex electricity systems

The Failure of the Strong Pumping Lemma for Multiple Context-Free Languages

International audienceSeki et al. (Theoretical Computer Science 88(2):191–229, 1991) showed that every m-multiple context-free language L is weakly 2m-iterative in the sense that either L is finite or L contains a subset of the form $\{u_0 w_1^i u_1 \dots w_{2m}^i u_{2m} \mid i \in \mathbb{N}\}$, where $w_1 \dots w_{2m} \neq \epsilon$. Whether for every m-multiple context-free language L is 2m-iterative, that is to say, whether all but finitely many elements $z$ of L can be written as $z=u_0 w_1 u_1 \dots w_{2m} u_{2m}$ with $w_1 \dots w_{2m} \neq \epsilon$ and $\{u_0 w_1^i u_1 \dots w_{2m}^i u_{2m} \mid i \in \mathbb{N}\} \subseteq L$ has been open. We show that there is a 3-multiple context-free language that is not k-iterative for any k