Dominic Santschi
Last Name
Santschi
First name
Dominic
Email
dominic.santschi@unisg.ch
ORCID
Phone
+41 71 224 7435
15 results
Now showing 1 - 10 of 15
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Item type:Publication, Spekulatives Design in Risk WorkshopsRisk Workshops sind in Unternehmen weit verbreitet. Spekulatives Design kann diese Workshops zukunftsorientiert erweitern, um Risiken besser zu antizipieren und Chancen frühzeitiger zu erkennen. Dafür stellen wir einen 3-Phasen-Leitfaden vor, der traditionelle Methoden mit spekulativen Elementen kombiniert.Type:journal articleJournal:Controlling & Management Review - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Enterprise Risk Management at ABBIn a rapidly evolving industry, the global technology leader ABB Group (ABB) relies on robust enterprise risk management (ERM) to maintain operational excellence and navigate complex challenges. Drawing on first-hand practical insights from ABB, this article highlights practitioners’ ERM challenges and strategies to transform them into opportunities.Type:journal articleJournal:Controlling, Zeitschrift für erfolgsorientierte UnternehmenssteuerungVolume:04Issue:2025 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Die ESG-Wesentlichkeitsmatrix: Wie ist die Korrelation der Achsen zu interpretieren?Die ESG-Wesentlichkeitsmatrix bleibt ein wichtiges Werkzeug für Schweizer Unternehmen, um die Ergebnisse ihrer Wesentlichkeitsanalysen darzustellen. Ein Vergleich der Berichterstattung zeigt, dass die Matrizen unterschiedliche Muster in den Achsenkorrelationen aufweisen. Dieser Artikel liefert praktische Ansätze zur Analyse und Interpretation dieser Korrelationen.Type:journal articleJournal:Expert FocusIssue:April 2025 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Daten- und Technologiegestützte Assistenz für das ESG-ControllingDie sich rasant entwickelnde Technologielandschaft kann die Integration von ESG-Themen in etablierte Führungssysteme unterstützen. Gleichzeitig erfordert diese Integration jedoch geeignete Daten- und Controllingstrukturen, um Risiken bei der externen und internen Berichterstattung zu minimieren. In diesem Beitrag diskutiert das Autorenteam die theoretischen Grundlagen und präsentiert Praktiken zur erfolgreichen Integration von ESG Daten in das Controlling.Type:journal articleJournal:Controller Magazin - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Datenpartnerschaften: Ein Weg zur Steigerung des Unternehmenswerts?Wenn Unternehmen neben ihren internen Daten auch externe Datenpartnerschaften nutzen, können sie häufig ihren Wert steigern. Dieser Artikel sowie der vorgeschlagene Prozess zur Analyse von Datenpartnerschaften sollen Unternehmen dabei unterstützen, potenzielle Chancen zur Wertsteigerung zu identifizieren und diese systematisch zu bewerten.Type:journal articleJournal:Expert Focus - Some of the metrics are blocked by yourconsent settings
Item type:Publication, How Can Speculative Design Help Anticipate Digital Health Intervention Risks?(2025-12); ; Many digital health interventions (DHIs) fail due to limited risk anticipation in early innovation stages. Expanding the scope of risk anticipation by speculating “how things could be” (possible) instead of restricting views to “how they are” (probable) could help. We examine how speculative design can enhance the anticipation of DHI risks by focusing on possible, rather than merely probable, futures. Grounded in construal level theory, we explore how speculative design can support blind spot detection, increase risk accessibility through narratives, and transform abstract risks into tangible artifacts. In a risk workshop, we asked 25 participants to create future scenarios and speculative artifacts for care of older adults, followed by a post-workshop survey in which we collected information about their experience. Initial results of our ongoing work indicate that speculative design may support risk anticipation in the preparation phase of DHIs. We discuss current limitations and outline future research directions.Type:conference paperJournal:ICIS 2025 Proceedings - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Artificial Intelligence to Improve Public Budgeting(2024-12-15); ; ; Accurate public budgeting is essential for efficient resource allocation and societal trust. However, recent studies have shown that public budgets often project deficits but have substantial surpluses. This budgetary slack can lead taxpayers to overpay for services not rendered, delay necessary investments, or distort public perceptions of government efficiency. To avoid such unfortunate outcomes, we study how artificial intelligence (AI) can help decision-makers in the public sector with budgeting. We operationalize our research question using a two-step approach. First, we utilize open data from Swiss financial authorities to train and test an AI model. Our preliminary results validate the potential of AI to predict public accounts better than human experts. Second, we study whether decision-makers effectively utilize the AI model in an experimental scenario. The results of our experimental study indicate that human-AI collaboration could indeed support decision-makers to improve public budgeting by reducing budgetary slack.Type:conference paper - Some of the metrics are blocked by yourconsent settings
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Item type:Publication, Risk Identification in New Product Development: Does Speculative Design Exposure Make a Difference?(2026-05); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Deriving a Stakeholder Consensus Measure to Benchmark and Improve Firm ESG Performance(2025-09); ; This paper examines how unstructured data can be utilized to benchmark and enhance a firm’s sustainability performance. While the integration of environmental, social, and governance (ESG) considerations into management control systems is still developing, new data sources and practices are reshaping how sustainability is measured and managed. Using a three-phase approach, we first determine a stakeholder consensus measure based on ESG materiality matrix disclosures, which reflect both internal and external stakeholders’ ESG priorities. Applying optical character recognition, we extract data from the materiality matrices of a sample of firms based in the United States, revealing significant variation in stakeholder consensus. In the second phase, we test the downside risk hypothesis, which posits that stakeholder consensus could serve as a form of protection against ESG risks. Results from a propensity score matching analysis indicate modest evidence that higher stakeholder consensus is associated with fewer ESG incidents. In the third phase, we test the upside opportunity hypothesis, which views stakeholder consensus as a basis for innovation and value creation. We do not find evidence to support this view. This study introduces a novel method for deriving management accounting measures from unstructured data and highlights the potential and limitations of using stakeholder consensus to inform sustainability-focused control practices.Type:conference contribution