Volume 10 Public Administration and Information Technology
Christopher G. Reddick
More information about this series at http://www.springer.com/series/10796
Editors Marijn Janssen, Maria A. Wimmer and Ameneh Deljoo
Policy Practice and Digital Science Integrating Complex Systems, Social Simulation and Public Administration in Policy Research
Marijn Janssen Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands
Maria A. Wimmer Institute for Information Systems Research, University of Koblenz-Landau, Koblenz, Germany
Ameneh Deljoo Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands
ISBN 978-3-319-12783-5 e-ISBN 978-3-319-12784-2 DOI 10.1007/978-3-319-12784-2
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Preface The last economic and financial crisis has heavily threatened European and other economies around the globe. Also, the Eurozone crisis, the energy and climate change crises, challenges of demographic change with high unemployment rates, and the most recent conflicts in the Ukraine and the near East or the Ebola virus disease in Africa threaten the wealth of our societies in different ways. The inability to predict or rapidly deal with dramatic changes and negative trends in our economies and societies can seriously hamper the wealth and prosperity of the European Union and its Member States as well as the global networks. These societal and economic challenges demonstrate an urgent need for more effective and efficient processes of governance and policymaking, therewith specifically addressing crisis management and economic/welfare impact reduction.
Therefore, investing in the exploitation of innovative information and communication technology (ICT) in the support of good governance and policy modeling has become a major effort of the European Union to position itself and its Member States well in the global digital economy. In this realm, the European Union has laid out clear strategic policy objectives for 2020 in the Europe 2020 strategy 1 : In a changing world, we want the EU to become a smart, sustainable, and inclusive economy. These three mutually reinforcing priorities should help the EU and the Member States deliver high levels of employment, productivity, and social cohesion. Concretely, the Union has set five ambitious objectives—on employment, innovation, education, social inclusion, and climate/energy—to be reached by 2020 . Along with this, Europe 2020 has established four priority areas—smart growth, sustainable growth, inclusive growth, and later added: A strong and effective system of economic governance—designed to help Europe emerge from the crisis stronger and to coordinate policy actions between the EU and national levels.
To specifically support European research in strengthening capacities, in overcoming fragmented research in the field of policymaking, and in advancing solutions for ICT supported governance and policy modeling, the European Commission has cofunded an international support action called eGovPoliNet 2 . The overall objective of eGovPoliNet was to create an international, cross-disciplinary community of researchers working on ICT solutions for governance and policy modeling. In turn, the aim of this community was to advance and sustain research and to share the insights gleaned from experiences in Europe and globally. To achieve this, eGovPoliNet established a dialogue, brought together experts from distinct disciplines, and collected and analyzed knowledge assets (i.e., theories, concepts, solutions, findings, and lessons on ICT solutions in the field) from different research disciplines. It built on case material accumulated by leading actors coming from distinct disciplinary backgrounds and brought together the innovative knowledge in the field. Tools, methods, and cases were drawn from the academic community, the ICT sector, specialized policy consulting firms as well as from policymakers and governance experts. These results were assembled in a knowledge base and analyzed in order to produce comparative analyses and descriptions of cases, tools, and scientific approaches to enrich a common knowledge base accessible via www.policy-community.eu .
This book, entitled “Policy Practice and Digital Science—Integrating Complex Systems, Social Simulation, and Public Administration in Policy Research,” is one of the exciting results of the activities of eGovPoliNet—fusing community building activities and activities of knowledge analysis. It documents findings of comparative analyses and brings in experiences of
experts from academia and from case descriptions from all over the globe. Specifically, it demonstrates how the explosive growth in data, computational power, and social media creates new opportunities for policymaking and research. The book provides a first comprehensive look on how to take advantage of the development in the digital world with new approaches, concepts, instruments, and methods to deal with societal and computational complexity. This requires the knowledge traditionally found in different disciplines including public administration, policy analyses, information systems, complex systems, and computer science to work together in a multidisciplinary fashion and to share approaches. This book provides the foundation for strongly multidisciplinary research, in which the various developments and disciplines work together from a comprehensive and holistic policymaking perspective. A wide range of aspects for social and professional networking and multidisciplinary constituency building along the axes of technology, participative processes, governance, policy modeling, social simulation, and visualization are tackled in the 19 papers.
With this book, the project makes an effective contribution to the overall objectives of the Europe 2020 strategy by providing a better understanding of different approaches to ICT enabled governance and policy modeling, and by overcoming the fragmented research of the past. This book provides impressive insights into various theories, concepts, and solutions of ICT supported policy modeling and how stakeholders can be more actively engaged in public policymaking. It draws conclusions of how joint multidisciplinary research can bring more effective and resilient findings for better predicting dramatic changes and negative trends in our economies and societies.
It is my great pleasure to provide the preface to the book resulting from the eGovPoliNet project. This book presents stimulating research by researchers coming from all over Europe and beyond. Congratulations to the project partners and to the authors!—Enjoy reading!
Thanassis Chrissafis Project officer of eGovPoliNet European Commission DG CNECT, Excellence in Science, Digital Science
1 Introduction to Policy-Making in the Digital Age Marijn Janssen and Maria A. Wimmer
2 Educating Public Managers and Policy Analysts in an Era of Informatics Christopher Koliba and Asim Zia
3 The Quality of Social Simulation: An Example from Research Policy Modelling Petra AhrweilerGilbert and Nigel Gilbert
4 Policy Making and Modelling in a Complex World Wander Jager and Bruce Edmonds
5 From Building a Model to Adaptive Robust Decision Making Using Systems Modeling Erik Pruyt
6 Features and Added Value of Simulation Models Using Different Modelling Approaches Supporting Policy-Making: A Comparative Analysis
Dragana Majstorovic, Maria A. Wimmer, Roy Lay-Yee, Peter Davis and Petra Ahrweiler
7 A Comparative Analysis of Tools and Technologies for Policy Making Eleni Kamateri, Eleni Panopoulou, Efthimios Tambouris, Konstantinos Tarabanis, Adegboyega Ojo, Deirdre Lee and David Price
8 Value Sensitive Design of Complex Product Systems Andreas Ligtvoet, Geerten van de Kaa, Theo Fens, Cees van Beers, Paulier Herder and Jeroen van den Hoven
9 Stakeholder Engagement in Policy Development: Observations and Lessons from International Experience
Natalie Helbig, Sharon Dawes, Zamira Dzhusupova, Bram Klievink and Catherine Gerald Mkude
10 Values in Computational Models Revalued Rebecca Moody and Lasse Gerrits
11 The Psychological Drivers of Bureaucracy: Protecting the Societal Goals of an Organization
Tjeerd C. Andringa
12 Active and Passive Crowdsourcing in Government Euripidis Loukis and Yannis Charalabidis
13 Management of Complex Systems: Toward Agent-Based Gaming for Policy
Wander Jager and Gerben van der Vegt
14 The Role of Microsimulation in the Development of Public Policy Roy Lay-Yee and Gerry Cotterell
15 Visual Decision Support for Policy Making: Advancing Policy Analysis with Visualization
Tobias Ruppert, Jens Dambruch, Michel Krämer, Tina Balke, Marco Gavanelli, Stefano Bragaglia, Federico Chesani, Michela Milano and Jörn Kohlhammer
16 Analysis of Five Policy Cases in the Field of Energy Policy Dominik Bär, Maria A. Wimmer, Jozef Glova, Anastasia Papazafeiropoulou and Laurence Brooks
17 Challenges to Policy-Making in Developing Countries and the Roles of Emerging Tools, Methods and Instruments: Experiences from Saint Petersburg
Bershadskaya Lyudmila, Chugunov Andrei and Trutnev Dmitrii
18 Sustainable Urban Development, Governance and Policy: A Comparative Overview of EU Policies and Projects
Diego Navarra and Simona Milio
19 eParticipation, Simulation Exercise and Leadership Training in Nigeria: Bridging the Digital Divide
Tanko Ahmed National Institute for Policy and Strategic Studies (NIPSS), Jos, Nigeria
Petra Ahrweiler EA European Academy of Technology and Innovation Assessment GmbH, Bad Neuenahr- Ahrweiler, Germany
Chugunov Andrei ITMO University, St. Petersburg, Russia
Tjeerd C. Andringa Institute of Artificial Intelligence and Cognitive Engineering (ALICE), University College Groningen, University of Groningen, Groningen, the Netherlands
Dominik Bär University of Koblenz-Landau, Koblenz, Germany
Tina Balke University of Surrey, Surrey, UK
Cees van Beers Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, The Netherlands
Stefano Bragaglia University of Bologna, Bologna, Italy
Laurence Brooks Brunel University, Uxbridge, UK
Yannis Charalabidis University of the Aegean, Samos, Greece
Federico Chesani University of Bologna, Bologna, Italy
Gerry Cotterell Centre of Methods and Policy Application in the Social Sciences (COMPASS Research Centre),, University of Auckland, Auckland, New Zealand
Jens Dambruch Fraunhofer Institute for Computer Graphics Research, Darmstadt, Germany
Peter Davis Centre of Methods and Policy Application in the Social Sciences (COMPASS Research Centre), University of Auckland, Auckland, New Zealand
Sharon Dawes Center for Technology in Government, University at Albany, Albany, New York, USA
Trutnev Dmitrii ITMO University, St. Petersburg, Russia
Zamira Dzhusupova Department of Public Administration and Development Management, United Nations Department of Economic and Social Affairs (UNDESA) NewYork, NewYork, USA
Bruce Edmonds Manchester Metropolitan University, Manchester, UK
Theo Fens Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, The Netherlands
Marco Gavanelli University of Ferrara, Ferrara, Italy
Nigel Gilbert University of Surrey, Guildford, UK
Jozef Glova Technical University Kosice, Kosice, Slovakia
Natalie Helbig Center for Technology in Government, University at Albany, Albany, New York, USA
Paulier Herder Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, The Netherlands
Jeroen van den Hoven Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, The Netherlands
Wander Jager Groningen Center of Social Complexity Studies, University Groningen, Groningen, The Netherlands
Groningen Center of Social Complexity Studies, University of Groningen, Groningen, The Netherlands
Marijn Janssen Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, The Netherlands
Geerten van de Kaa Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, The Netherlands
Eleni Kamateri Information Technologies Institute, Centre for Research & Technology—Hellas, Thessaloniki, Greece
Bram Klievink Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands
Jörn Kohlhammer GRIS, TU Darmstadt & Fraunhofer IGD, Darmstadt, Germany
Christopher Koliba University of Vermont, Burlington, VT, USA
Michel Krämer Fraunhofer Institute for Computer Graphics Research, Darmstadt, Germany
Roy Lay-Yee Centre of Methods and Policy Application in the Social Sciences (COMPASS Research Centre), University of Auckland, Auckland, New Zealand
Roy Lay-Yee Centre of Methods and Policy Application in the Social Sciences Research Centre, University of Auckland, Auckland, New Zealand
Deirdre Lee INSIGHT Centre for Data Analytics, NUIG, Galway, Ireland
Andreas Ligtvoet Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, The Netherlands
Euripidis Loukis University of the Aegean, Samos, Greece
Bershadskaya Lyudmila ITMO University, St. Petersburg, Russia
Dragana Majstorovic University of Koblenz-Landau, Koblenz, Germany
Michela Milano University of Bologna, Bologna, Italy
Simona Milio London School of Economics, Houghton Street, London, UK
Catherine Gerald Mkude Institute for IS Research, University of Koblenz-Landau, Koblenz, Germany
Rebecca Moody Department of Public Administration, Erasmus University Rotterdam, Rotterdam, The Netherlands
Diego Navarra Regent’s University, Inner Circle, Regent’s Park, London, UK
Adegboyega Ojo INSIGHT Centre for Data Analytics, NUIG, Galway, Ireland
Eleni Panopoulou Information Technologies Institute, Centre for Research & Technology—Hellas, Thessaloniki, Greece
Anastasia Papazafeiropoulou Brunel University, Uxbridge, UK
David Price Thoughtgraph Ltd, Somerset, UK
Erik Pruyt Faculty of Technology, Policy, and Management,, Delft University of Technology, Delft, The Netherlands Netherlands Institute for Advanced Study, Wassenaar, The Netherlands
Tobias Ruppert Fraunhofer Institute for Computer Graphics Research, Darmstadt, Germany
Efthimios Tambouris Information Technologies Institute, Centre for Research & Technology—Hellas, Thessaloniki,
Greece University of Macedonia, Thessaloniki, Greece
Konstantinos Tarabanis Information Technologies Institute, Centre for Research & Technology—Hellas, Thessaloniki, Greece University of Macedonia, Thessaloniki, Greece
Gerben van der Vegt Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands
Lyudmila Vidyasova ITMO University, St. Petersburg, Russia
Maria A Wimmer University of Koblenz-Landau, Koblenz, Germany
Maria A. Wimmer University of Koblenz-Landau, Koblenz, Germany
Asim Zia University of Vermont, Burlington, VT, USA
Footnotes Europe 2020 http://ec.europa.eu/europe2020/index_en.htm
eGovPoliNet is cofunded under FP 7, Call identifier FP7-ICT-2011-7, URL: www.policy-community.eu
© Springer International Publishing Switzerland 2015 Marijn Janssen, Maria A. Wimmer and Ameneh Deljoo (eds.), Policy Practice and Digital Science, Public Administration and Information Technology 10, DOI 10.1007/978-3-319-12784-2_1
1. Introduction to Policy-Making in the Digital Age
Marijn Janssen1 and Maria A. Wimmer2
Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, The Netherlands University of Koblenz-Landau, Koblenz, Germany
Marijn Janssen Email: firstname.lastname@example.org
Abstract The explosive growth in data, computational power, and social media creates new opportunities for innovating governance and policy-making. These These information and communications technology (ICT) developments affect all parts of the policy-making cycle and result in drastic changes in the way policies are developed. To take advantage of these developments in the digital world, new approaches, concepts, instruments and methods are needed, which are able to deal with societal complexity and uncertainty. This field of research is sometimes depicted as e- government policy, e-policy, policy informatics or data science. Advancing our knowledge demands that different scientific communities collaborate to create practice-driven knowledge. For policy-making in the digital age disciplines such as complex systems, social simulation and public administration need to be combined.
Keywords e-policy – Policy-making – Data science – Policy informatics – Big data – Open data – Data science – Simulation – Gaming
We are running the 21st century using 20th century systems on top of 19th century political structures…. John Pollock, contributing editor MIT technology review
1.1 Introduction Policy-making and its subsequent implementation is necessary to deal with societal problems. Policy interventions can be costly, have long-term implications, affect groups of citizens or even the whole country and cannot be easily undone or are even irreversible. New information and communications technology (ICT) and models can help to improve the quality of policy-makers. In particular, the explosive growth in data, computational power, and social media creates new opportunities for innovating the processes and solutions of ICT-based policy-making and research. To take advantage of these developments in the digital world, new approaches, concepts, instruments, and methods are needed, which are able to deal with societal and computational complexity. This requires the use of knowledge which is traditionally found in different disciplines, including (but not limited to) public administration, policy analyses, information systems, complex systems, and computer science. All these knowledge areas are needed for policy-making in the digital age. The aim of this book is to provide a foundation for this new interdisciplinary field in which various traditional disciplines are blended.
Both policy-makers and those in charge of policy implementations acknowledge that ICT is becoming more and more important and is changing the policy-making process, resulting in a next generation policy-making based on ICT support. The field of policy-making is changing driven by developments such as open data, computational methods for processing data, opinion mining, simulation, and visualization of rich data sets, all combined with public engagement, social media, and participatory tools. In this respect Web 2.0 and even Web 3.0 point to the specific applications of social networks and semantically enriched and linked data which are important for policy-making. In policy-making vast amount of data are used for making predictions and forecasts. This should result in improving the outcomes of policy-making.
Policy-making is confronted with an increasing complexity and uncertainty of the outcomes which results in a need for developing policy models that are able to deal with this. To improve the validity of the models policy-makers are harvesting data to generate evidence. Furthermore, they are improving their models to capture complex phenomena and dealing with uncertainty and limited and incomplete information. Despite all these efforts, there remains often uncertainty concerning the outcomes of policy interventions. Given the uncertainty, often multiple scenarios are developed to show alternative outcomes and impact. A condition for this is the visualization of policy alternatives and its impact. Visualization can ensure involvement of nonexpert and to communicate alternatives. Furthermore, games can be used to let people gain insight in what can happen, given a certain scenario. Games allow persons to interact and to experience what happens in the future based on their interventions.
Policy-makers are often faced with conflicting solutions to complex problems, thus making it necessary for them to test out their assumptions, interventions, and resolutions. For this reason policy-making organizations introduce platforms facilitating policy-making and citizens engagements and enabling the processing of large volumes of data. There are various participative platforms developed by government agencies (e.g., De Reuver et al. 2013; Slaviero et al. 2010; Welch 2012). Platforms can be viewed as a kind of regulated environment that enable developers, users, and others to interact with each other, share data, services, and applications, enable governments to more easily monitor what is happening and facilitate the development of innovative solutions (Janssen and Estevez 2013). Platforms should provide not
only support for complex policy deliberations with citizens but should also bring together policy- modelers, developers, policy-makers, and other stakeholders involved in policy-making. In this way platforms provide an information-rich, interactive environment that brings together relevant stakeholders and in which complex phenomena can be modeled, simulated, visualized, discussed, and even the playing of games can be facilitated.
1.2 Complexity and Uncertainty in Policy-Making Policy-making is driven by the need to solve societal problems and should result in interventions to solve these societal problems. Examples of societal problems are unemployment, pollution, water quality, safety, criminality, well-being, health, and immigration. Policy-making is an ongoing process in which issues are recognized as a problem, alternative courses of actions are formulated, policies are affected, implemented, executed, and evaluated (Stewart et al. 2007). Figure 1.1 shows the typical stages of policy formulation, implementation, execution, enforcement, and evaluation. This process should not be viewed as linear as many interactions are necessary as well as interactions with all kind of stakeholders. In policy-making processes a vast amount of stakeholders are always involved, which makes policy-making complex.
Fig. 1.1 Overview of policy cycle and stakeholders
Once a societal need is identified, a policy has to be formulated. Politicians, members of parliament, executive branches, courts, and interest groups may be involved in these formulations. Often contradictory proposals are made, and the impact of a proposal is difficult to determine as data is missing, models cannot capture the complexity, and the results of policy models are difficult to interpret and even might be interpreted in an opposing way. This is further complicated as some proposals might be good but cannot be implemented or are too costly to implement. There is a large uncertainty concerning the outcomes.
Policy implementation is done by organizations other than those that formulated the policy. They often have to interpret the policy and have to make implementation decisions. Sometimes IT can block quick implementation as systems have to be changed. Although policy-making is the domain of the government, private organizations can be involved to some extent, in particular in the execution of policies.
Once all things are ready and decisions are made, policies need to be executed. During the execution small changes are typically made to fine tune the policy formulation, implementation
decisions might be more difficult to realize, policies might bring other benefits than intended, execution costs might be higher and so on. Typically, execution is continually changing. Evaluation is part of the policy-making process as it is necessary to ensure that the policy- execution solved the initial societal problem. Policies might become obsolete, might not work, have unintended affects (like creating bureaucracy) or might lose its support among elected officials, or other alternatives might pop up that are better.
Policy-making is a complex process in which many stakeholders play a role. In the various phases of policy-making different actors are dominant and play a role. Figure 1.1 shows only some actors that might be involved, and many of them are not included in this figure. The involvement of so many actors results in fragmentation and often actors are even not aware of the decisions made by other actors. This makes it difficult to manage a policy-making process as each actor has other goals and might be self-interested.
Public values (PVs) are a way to try to manage complexity and give some guidance. Most policies are made to adhere to certain values. Public value management (PVM) represents the paradigm of achieving PVs as being the primary objective (Stoker 2006). PVM refers to the continuous assessment of the actions performed by public officials to ensure that these actions result in the creation of PV (Moore 1995). Public servants are not only responsible for following the right procedure, but they also have to ensure that PVs are realized. For example, civil servants should ensure that garbage is collected. The procedure that one a week garbage is collected is secondary. If it is necessary to collect garbage more (or less) frequently to ensure a healthy environment then this should be done. The role of managers is not only to ensure that procedures are followed but they should be custodians of public assets and maximize a PV.
There exist a wide variety of PVs (Jørgensen and Bozeman 2007). PVs can be long-lasting or might be driven by contemporary politics. For example, equal access is a typical long-lasting value, whereas providing support for students at universities is contemporary, as politicians might give more, less, or no support to students. PVs differ over times, but also the emphasis on values is different in the policy-making cycle as shown in Fig. 1.2. In this figure some of the values presented by Jørgensen and Bozeman (2007) are mapped onto the four policy-making stages. Dependent on the problem at hand other values might play a role that is not included in this figure.
Fig. 1.2 Public values in the policy cycle
Policy is often formulated by politicians in consultation with experts. In the PVM paradigm, public administrations aim at creating PVs for society and citizens. This suggests a shift from talking about what citizens expect in creating a PV. In this view public officials should focus on collaborating and creating a dialogue with citizens in order to determine what constitutes a PV.
1.3 Developments There is an infusion of technology that changes policy processes at both the individual and group level. There are a number of developments that influence the traditional way of policy-making, including social media as a means to interact with the public (Bertot et al. 2012), blogs (Coleman and Moss 2008), open data (Janssen et al. 2012; Zuiderwijk and Janssen 2013), freedom of information (Burt 2011), the wisdom of the crowds (Surowiecki 2004), open collaboration and transparency in policy simulation (Wimmer et al. 2012a,b), agent-based simulation and hybrid modeling techniques (Koliba and Zia 2012) which open new ways of innovative policy-making. Whereas traditional policy-making is executed by experts, now the public is involved to fulfill requirements of good governance according to open government principles. Also, the skills and capabilities of crowds can be explored and can lead to better and more transparent democratic policy decisions. All these developments can be used for enhancing citizen’s engagement and to involve citizens better in the policy-making process. We want to emphasize three important developments.