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The financial crisis of 2007-2010 was probably one of the greatest, most lustrous black-swan events that people of our generation(s) will experience – and at its heart, it was a dynamic phenomenon. It is stated in the vision of the System Dynamics Society that we aspire to transform society by influencing decision-making. Yet, it seems as if system dynamics did not play any significant role in this crisis: we did not examine the markets, we did not provide insights to banks, and we did not warn governments or the people. In our presentation we describe the dynamics involved in a housing bubble, and describe what made the last one different. With the insights gained from this exercise we conclude that, from a system dynamics perspective, the dimension of the financial crisis of 2007-2009 was eminently foreseeable, which will lead us to pose the following question: where were we as a field while this crisis was unfolding, why were we not active players? We present a range of potential answers to this question, hoping to provoke some reflection… and maybe some (re)action.
Why are organizations and markets slow to transform toward sustainability despite the abundant well-recognized opportunities it provides? An important subset of the phenomena this question addresses involves decision-makers recognizing the existence of opportunities but failing to undertake ambitious, effective, sufficient, or timely action. Building on existing research on capability traps, market formation, and managing sustainability, we focus on the forces con-straining organizations from developing the capabilities and market infrastructures required for sustainability transformations. We characterize types of sustainability initiatives and, using causal loop diagramming, visualize structures that enable and constrain how organizations can navigate individually and collectively worse-before-better dynamics resulting from uncertain,nonlinear, and delayed returns. Being under day-to-day pressures and deeply intertwined within their environment, organizational actors find it difficult to recognize, undertake, maintain, and coordinate necessary efforts internally and externally. We discuss research implications and directions for future research on avoiding these traps and accelerating sustainability transformations.
Climate change communication efforts grounded in the information deficit model have largely failed to close the gap between scientific and public understanding of the risks posed by climate change. In response, simulations have been proposed to enable people to learn for themselves about this complex and politically charged topic. Here we assess the impact of a widely-used simulation, World Climate, which combines a socially and emotionally engaging role-play with interactive exploration of climate change science through the CROADS climate simulation model. Participants take on the roles of delegates to the UN climate negotiations and are challenged to create an agreement that meets international climate goals. Their decisions are entered into C-ROADS, which provides immediate feedback about expected global climate impacts, enabling them to learn about climate change while experiencing the social dynamics of negotiations. We assess the impact of World Climate by analyzing pre- and post-survey results from >2,000 participants in 39 sessions in eight nations. We find statistically significant gains in three areas: (i) knowledge of climate change causes, dynamics and impacts; (ii) affective engagement including greater feelings of urgency and hope; and (iii) a desire to learn and do more about climate change. Contrary to the deficit model, gains in urgency were associated with gains in participants' desire to learn more and intent to act, while gains in climate knowledge were not. Gains were just as strong among American participants who oppose government regulation of free
markets - a political ideology that has been linked to climate change denial in the US - suggesting the simulation's potential to reach across political divides. The results indicate that World Climate offers a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed by science.
Background. We describe and provide an initial evaluation of the Climate Action Simulation, a simulation-based role playing game that enables participants to learn for themselves about the response of the climate-energy system to potential policies and actions. Participants gain an understanding of the scale and urgency of climate action, the impact of different policies and actions, and the dynamics and interactions of different policy choices.
Intervention. The Climate Action Simulation combines an interactive computer model, En-ROADS, with a role play in which participants make decisions about energy and climate policy. They learn about the dynamics of the climate and energy systems as they discover how En-ROADS responds to their own climate-energy decisions.
Methods. We evaluated learning outcomes from the Climate Action Simulation using pre- and post-simulation surveys as well as a focus group.
Results. Analysis of survey results showed that the Climate Action Simulation increases participants’ knowledge about the scale of emissions reductions and policies and actions needed to address climate change. Their personal and emotional engagement with climate change also grew. Focus group participants were overwhelmingly positive about the Climate Action Simulation, saying it left them feeling empowered to make a positive difference in addressing the climate challenge.
Many scientific reports have warned about the catastrophic consequences of unchecked climate change, with the latest international report calling for emissions of climate pollutants to reach net zero by around 2050 (IPCC, 2018). Limiting warming to 1.5°C could save more than 100 million people from water shortages, as many as 2 billion people from dangerous heatwaves, and the majority of species from climate change extinction risks (IPCC, 2018; Warren et al., 2018). The actions taken to achieve these climate outcomes would generate benefits of more than $20 trillion while easing global economic inequality (Burke et al., 2018). Scientists make it clear that it is physically possible to meet these goals using today’s technologies (Holz et al., 2018). Yet emissions of climate pollutants continue to grow, reaching a new record high in 2018 (Jackson et al., 2018). Clearly, scientific evidence has failed to spark needed climate action. The question now is: what can?
Climate change is one of the key challenges of this century due to its impact on society and the economy. Students are asking their business schools to scale up climate change education (CCE) across all disciplines, and employers are looking for graduates ready to work on solutions. This desire for solutions is shared by faculty; however, in a recent survey, many highlighted that they lack knowledge about climate change mitigation and how to integrate CCE into their disciplines.
This chapter supports lecturers, professors and senior management in their journey to get an overview of CCE and, more importantly, to find high-impact climate solutions to be integrated and assessed in their teaching units.
The EAT–Lancet planetary health diet (PHD) provides guidelines on a global scale and calls for red meat consumption to be halved. Operational PHD guidelines at country level have yet to be determined. Here we argue that the biological link between milk and bovine-meat production must be considered when operationalizing the globally calculated PHD to national contexts. Using a stylized computer simulation model rooted in a food system approach, we explore the impact of dietary scenarios on milk and bovine-meat production and show that ignoring this biological link can lead to substantial imbalances between national dietary guidelines and production outcomes and potentially lead to food waste. Furthermore, we assess current national dietary guidelines in Europe and find that most disregard this biological link and are incompatible with the PHD, with implications for policymakers and consumers to consider when adapting the PHD in national contexts.
Real estate markets are known to fluctuate. The real estate market in Stuttgart, Germany, has been booming for more than a decade: square-meter price hit top levels and real estate agents claim that market prices will continue to increase. In this paper, we test this market understanding by developing and analyzing a system dynamics model that depicts the Stuttgart real estate market. Simulating the model explains oscillating behavior arising from significant time delays and endogenous feedback structures – and not necessarily oscillating interest rates, as market experts assume. Scenarios provide insights into the system's behavior reacting to changes exogenous to the model. The first scenario tests the market development under increasing interest rates. The other scenario deals with possible effects on the real estate market if the regional automotive economy suffers from intense competition with new market players entering with alternative fuel vehicles and new technologies. With a policy run we test market structure changes to eliminate cyclical effects. The paper confirms that the business cycle in the Stuttgart real estate market arises from within the system's underlying structure, thus emphasizing the importance of understanding feedback structures.
SF-failure, the inability of people to correctly determine the behavior of simple stock and flow structures is subject of a long research stream. Reasons for SF-failure can be attributed to different reasons, one of them being lacking domain specific experience, thus familiarity with the problem context. In this article we present a continuation of an experiment to examine the role of educational background in SF-performance. We base the question set on the Bathtub Dynamics tasks introduced by Booth Sweeney and Sterman (2000) and vary the cover stories. In this paper we describe how we developed and tested a new cover story for the engineering domain and implemented the recommendations from a prior study. We test three sets of questions with engineering students which enables us to compare the results to a previous study in which we tested the questions with business students. Results mainly support our hypothesis that context familiarity increases SF-performance. With our findings we further develop the methodology of the research on SF-failure.
Strategic alliances have become important strategic options for firms to achieve competitive advantage. Yet, there are many examples of alliance failures. Scholars have studied this phenomenon and identified many reasons for alliance failure, including lack of trust between the partnering firms. Paradoxically, the concept of trust is still not fully understood, specifically how and under what conditions trust comes to break down within the broader process of alliance building. We synthesize a process model that describes the “alliance capability”, including trust, openness, partner contributions, and relational rents. We then translate this framework into a formal simulation model and analyze it thoroughly. In analyzing trust dynamics we identify and explore a tipping boundary, separating a regime of alliance failures and successes. We apply our core findings to openness strategies – decisions about how much knowledge to share with partners. Our analyses reveal that strategies informed by a static mental model of trust, contributions, and openness, under undervalue openness. Further, too little openness risks early failure due to the being trapped in a vicious cycle of trust depletion.