Displaying 10 of 89 results for "Caroline Schill" clear search
Inyoung Hwang is an Associate Research Fellow at Korea Institute of Science & Technology Evaluation and Planning (KISTEP), South Korea. He was a visiting scholar in the School of Public Affairs at Arizona State University. He received a B.Sc. in Vocational Education and Workforce Development, an M.P.P. in Public Policy, and a Ph.D. in Public Policy from Seoul National University.
Science & Technology Policy, Collaborative Innovation, Technological Diffusion and Convergence, Agent-Based Modelling, and Social Simulation.
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I am a computational social scientist, engineer, and systems researcher. I work in several aspects of modelling the dynamics of organisational, economic and social systems. I am interested in the link between micro-level rules, structural interdependence and macro-level outcomes in a variety of settings (e.g., organisational dynamics, industry evolution, competitive spatial location, agricultural markets). I am also interested in the use of computational models for better policy design (policy modelling).
I am Professor of Management at Paris School of Business and have held positions at the University of Southern Denmark, Bournemouth University (UK), University of Wisconsin (US), and at the University of Insubria (Italy). My current research efforts are on socially-based decision making, agent-based modeling, cognitive processes in organizations and socially responsible behavior in organizations. With a coauthor network of 50 colleagues located in over 10 different countries, I have published 126 (as of 2025) among articles, book chapters, and books. The monograph Computational organizational cognition (2021, Emerald), and the edited Agent-Based Simulation of Organizational Behavior with M. Neumann (2016, Springer Nature) specifically target computational simulation research in the social sciences. The book How do I Develop an Agent-Based Model? (2022, Elgar) is the first specifically written for business and management scholars.
My simulation research focuses on the applications of ABM to organizational behavior studies. I study socially-distributed decision making—i.e., the process of exploiting external resources in a social environment—and I work to develop its theoretical underpinnings in order to to test it. A second stream of research is on how group dynamics affect individual perceptions of social responsibility and on the definition and measurement of individual social responsibility (I-SR).
Social scientist based in Milan, Italy. Post-doctoral researcher in Sociology at the Department of Social and Political Sciences of the University of Milan (Italy), member of the Behave Lab. Adjunct professor of Social Network Analysis at the Graduate School in Social and Political Sciences of the University of Milan.
Antônio Sousa is a biologist with a background in medical entomology, disease ecology, statistical and computational modeling. Antônio has a Ph.D. (2018) and Master (2014) in Science from the School of Public Health at the University of São Paulo, Brazil. Currently, he is a postdoctoral fellow in the same institution.
My research interest lies in the study of the transmission and dispersal dynamics of vector-borne diseases. I have been working on the development of statistical, mathematical and computational models to understand bioecology of mosquitoes and to predict the transmission dynamics of pathogens transmitted by these insects.
Dr. Dawn Parker is a professor at the University of Waterloo in the School of Planning. Her research focuses on the development of integrated socio-economic and biophysical models of land-use change. Dr. Parker works with agent-based modeling, complexity theory, geographic information systems, and environmental and resource economics. Her current ongoing projects include Waterloo Area Regional Model (WARM) Urban intensification vs. suburban flight, a SSHRC funded development grant that explores the causal relationships between light rail transit and core-area intensification, and the Digging into Data MIRACLE (Mining relationships among variables in large datasets from complex systems) project.
Annie Waldherr is Professor of Computational Communication Science at the Department of Communication at the University of Vienna. She studied Communication Science at the University of Hohenheim and the School of Journalism and Communication at the University of Oregon. She held positions at the Faculty of Social Sciences at the University of Hohenheim and the Institute for Media and Communication Studies at Freie Universität Berlin where she also obtained her PhD in 2011. Before joining the University of Vienna in September 2020, Annie Waldherr was Assistant Professor at the Department of Communication at the University of Münster.
Her research focuses on public spheres, social movements and political communication under the conditions of digitalization, datafication and artificial intelligence.
The big picture question driving my research is how do complex systems of interactions among individuals / agents result in emergent properties and how do those emergent properties feedback to affect individual / agent decisions. I have explored this big picture question in a number of different contexts including the evolution of cooperation, suburban sprawl, traffic patterns, financial systems, land-use and land-change in urban systems, and most recently social media. For all of these explorations, I employ the tools of complex systems, most importantly agent-based modeling.
My current research focus is on understanding the dynamics of social media, examining how concepts like information, authority, influence and trust diffuse in these new media formats. This allows us to ask questions such as who do users trust to provide them with the information that they want? Which entities have the greatest influence on social media users? How do fads and fashions arise in social media? What happens when time is critical to the diffusion process such as an in a natural disaster? I have employed agent-based modeling, machine learning, geographic information systems, and network analysis to understand and start to answer these questions.
I am a Reader in the Centre for Health Economics, conducting interdisciplinary research aimed at tackling healthcare challenges and improving decision-making and implementation in healthcare policy. My research is centred around using systems thinking and modelling approaches in health economics evaluation and draws on tools and methods from mathematical epidemiology, economics, management science, and computer science, among other fields.
My main body of work involves systems modelling and simulation, and it involves integrating disease and economic models for policy impact evaluation and prioritisation. I am interested in both infectious disease and non-communicable disease modelling. From a methodological standpoint, I am particularly interested in strengthening rigour in agent-based modelling and hybrid models, which integrate modelling methods when this simplifies analyses. I have applied my research to studying and conducting knowledge-exchange activities addressing global health challenges. This includes conducting healthcare intervention and policy evaluations, studying health systems strengthening in low- and middle-income countries, studying antimicrobial resistance policy globally and in the UK, evaluating COVID-19 policy and interventions, investigating how behaviour and social structure affect health and diseases, and exploring the role of incentives in healthcare policy design.
I hold a PhD in Management Science, specialising in modelling for healthcare policy, from the University of Strathclyde and an MA in economics and BA honours economics from McGill University, in Montreal.
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