Modelling Research Policy: Ex-Ante Evaluation of Complex Policy Instruments

Ahrweiler, Petra; Schilperoord, Michel; Pyka, Andreas; Gilbert, Nigel

doi:10.18564/jasss.2927

Cited by 22 publications

(14 citation statements)

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“…Agent-based modelling is possible in all scientific areas in which systems can be seen as comprised of a large number of interacting entities. Especially in the social sciences, agent-based modelling is a prominent tool and used for various applications such as tax evasion [29], holiday trips [30] and transport choices [31], and evaluation of policy decisions [32].…”

Section: Agent-based Modellingmentioning

confidence: 99%

Threat and Anxiety in the Climate Debate—An Agent-Based Model to Investigate Climate Scepticism and Pro-Environmental Behaviour

Kapeller

Jäger

2020

Sustainability

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In order to meet the challenges of sustainable development, it is of utmost importance to involve all relevant decision makers in this process. These decision makers are diverse, including governments, corporations and private citizens. Since the latter group is the largest and the majority of decisions relevant to the future of the environment is made by that group, great effort has been put into communicating relevant research results to them. The hope is that well-informed citizens make well-informed choices and thus act in a sustainable way. However, this common but drastic simplification that more information about climate change automatically leads to pro-environmental behaviour is fundamentally flawed. It completely neglects the complex social-psychological processes that occur if people are confronted with threatening information. In reality, the defence mechanisms that are activated in such situations can also work against the goal of sustainable development, as experimental studies showed. Based on these findings, we propose an agent-based model to understand the relation between threatening climate change information, anxiety, climate change scepticism, environmental self-identity and pro-environmental behaviour. We find that the exposure to information about climate change, in general, does not increase the pro-environmental intent unless several conditions regarding the individual's values and information density are met.

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Section: Agent-based Modellingmentioning

confidence: 99%

Threat and Anxiety in the Climate Debate—An Agent-Based Model to Investigate Climate Scepticism and Pro-Environmental Behaviour

Kapeller

Jäger

2020

Sustainability

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“…научных исследований Дальнейшее развитие исследований в области выявления более совершенного и справедливого способа распределения финансовых средств на научные исследования представлено в работе [7], посвященной агенториентированной модели «INFSO-SKIN», разработанной с целью обеспечения генеральной дирекции по информационному обществу и средствам массовой информации Европейской комиссии (DGINFSO -Directorate General for the Information Society and Media) инструментом для предварительной оценки возможных стратегий финансирования в рамках проекта «Horizon 2020». На основе большого набора данных, фиксирующих детали финансируемых проектов, была создана имитационная модель для воспроизведения и оценки стратегий финансирования организаций и проектов, а также результирующих сетевых структур программы «Commission's Framework 7» (FР7).…”

Section: модель распределения финансированияunclassified

“…Рисунок 5. Блок-схема кооперационных процессов [7] Figure 5. A block diagram of the cooperation processes [7] Результаты обозначенных имитационных экспериментов показали некоторые вероятные сценарии развития политики финансирования проектов в рамках программы «Horizon 2020» [7].…”

Section: модель распределения финансированияunclassified

Application of social modeling using agent based approach in scientific and technical development, implementation of R&D and maintenance of innovative potential

Abramov

Кудинов

Evdokimov

2019

Vestn. Voronež. gos. univ. inž. tehnol.

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Agent based models (ABM) and multiagent systems (MAS) can be used to solve problems in many fields of research - from natural and computer to economics and social sciences. Many natural and social phenomena can be represented in form of complex simulations so over time agent models and multi-agent systems have proven to be a really powerful tool in areas such as economics and trade, health, urban planning and social sciences. In addition multi-agent systems can be represented as an artificial society similar to a human one and consisting of entities with characteristics similar to human ones, for example in terms of autonomy and intelligence. ABM are based on the principle of objective orientation as well as the evolution (training) of agents in the process of modeling various variants of the proposed events. Despite the apparent simplicity of the rules of interaction between agents the results are usually non-obvious and quite meaningful. ABM can be developed both at the micro level and represent models with multiple agents at the macro level. The concept of multi-agent systems which immediately gained followers and support in both scientific circles and industrial communities, first started talking in the mid-1980s. Over the past thirty years, the methodology of IAU creation has been constantly improved: technologies and tools for its promotion and use in the management of large-scale network structures (such as defense systems, energy, health, transport, logistics, urban management, collective robotics, etc.) have been actively developed. The scope of application of MAS is very wide. The analysis of implemented MAS proves that currently the tool is the most advanced technology for managing any objects built on the principles of self-organization. However, despite all the evidence of positive prospects for the introduction of AOM technology the number of examples of its successful application to date is small. In this regard creation of new platforms for discussion of international experience and improvement of the approach to simulation modeling in general is especially important for further dissemination of AMB and MAS. Creation of an open consortium for agent-oriented modeling as well as promotion of development, communication and dissemination of research results as well as implementation of educational activities together will contribute to the development of agent based modeling. The analysis and review of existing methodology of social modeling with use of agent based approach in the application to scientific and technical development, implementation of R&D and maintenance of innovative potential showed that models characterized by complex multi-level processes and interactions of agents have more capacious software structures which depend more on the "fine" tuning of the agents themselves. Such models can contain and use a voluminous set of data, and in the field of economic research tend to focus on the analysis and forecasting of various socio-economic processes at the macro level.

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“…The following paragraphs briefly illustrate the application of agent-based models in so-called policy laboratories, which are an innovative approach to improve our understanding of complex innovation processes and help to improve policy designs by offering the opportunity to test the impact of various instruments in complex adaptive systems. For several years, policy laboratories have been considered as valuable tools to inform policy makers in complex decision-making processes (e.g., [6,30,31]). The policy laboratory notion stems from the possibility to use these models experimentally together with decision makers from innovation policy, to study the dynamics of complex systems and the possibility of governing their development [32].…”

Section: Agent-based Models Policy Laboratories and Regional Develomentioning

confidence: 99%

Regional Innovation Systems in Policy Laboratories

Pyka

Mueller

Kudic

2018

Journal of Open Innovation: Technology, Market, and Complexity

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Innovation policy and business strategy often expect that investing in private and public research and development will immediately produce a flow of products and processes with high commercial and social returns. Policymakers and managers implicitly follow the logic underlying most linear innovation models assuming a well-defined and uni-directional relationship between R&D spending as input and innovation rents as output of the innovation process. Modern innovation economics dismisses the simplified approximation of knowledge by R&D investment and, instead, considers complex knowledge generation and diffusion processes in innovation networks. From this angle, the disappointing performance of traditional approaches is traced back to strong limits of conventional steering, control, and policy instruments. In this paper, we show that the new view of knowledge generation and diffusion in innovation networks allows for an alternative and has led to systemic approaches in innovation analyses. Combined with computational approaches like agent-based modeling, this new view enables today innovative tools in policy consulting. Using the example of regional innovation policy, we introduce a policy laboratory in which innovation processes can be analyzed in depth to see the impact of different innovation policy instruments in-silico. This ex-ante evaluation helps considerably to improve the understanding of innovation processes and with it the performance of innovation policy.

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Modelling Research Policy: Ex-Ante Evaluation of Complex Policy Instruments

Cited by 22 publications

References 0 publications

Threat and Anxiety in the Climate Debate—An Agent-Based Model to Investigate Climate Scepticism and Pro-Environmental Behaviour

Threat and Anxiety in the Climate Debate—An Agent-Based Model to Investigate Climate Scepticism and Pro-Environmental Behaviour

Application of social modeling using agent based approach in scientific and technical development, implementation of R&D and maintenance of innovative potential

Regional Innovation Systems in Policy Laboratories

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