Discussions: InfoTech In A Global Economy (ITS-832)

15 Visual Decision Support for Policy Making 349

Within the time frame of the urbanAPI project, the developed tools are regularly evaluated in depth by users from the partner cities of Bologna (Italy), Ruse (Bulgaria), Vienna (Austria), and Vitoria-Gasteiz (Spain). We were able to derive the following results from these evaluations which we consider key for the success of ICT-enabled tools in participatory urban planning.

• The data quality has to be reasonably high. The 3D visualization has to be ap- pealing in order to improve acceptance by citizens. This is only possible if it is based on high-quality geo-spatial data like textured 3D building models or high- resolution digital terrain models and aerial images. While many European cities already maintain a 3D city model, at the moment they often miss textures or fine geometrical details which would make the visualization more realistic.

• Usability plays an important role for ICT tools that are made available to a large audience. The tools can only gain high acceptance if they can be used easily and without barriers. The user interface has to be clear and understandable. The software should allow stakeholders to participate and contribute without too much effort. Otherwise, the software will not be used and the advantages of participatory urban planning are lost.

• In addition to that, the ICT tools have to be portable in order to run on a wide range of systems from desktop PCs to tablets and mobile devices. This improves the acceptance and lowers the barriers, which stakeholders have to take before they can participate in urban planning.

15.4.4 Summary of Case Studies

Figure 15.9 summarizes the presented case studies with a short task description, the applied modeling techniques, the relevant data types, the implemented visualization techniques, and the involved stakeholder. The table shows that the selected case study differ in nearly all of these characteristics. From this, we conclude that for policy analysis a broad range of scenarios exist that need to be tackled with different strategies. We already stated that a one-fits-all-solution from the field of information visualization does not exist. For each problem addressed in a case study, a specific solution needs to be designed in order to support the users in the best possible way. The heterogeneity of case studies in the field of policy analysis even amplifies this fact. Therefore, we strongly recommend to conduct a precise problem characterization and analysis of tasks to be solved with the technologies prior to their implementation. For this, all relevant stakeholders need to be involved. Design study methodologies in the field of information visualization and visual analytics already address this challenge. However, from our point of view these methodologies need to be adapted to the specific characteristics of policy analysis.

350 T. Ruppert et al.

Fig. 15.9 Summary of case studies

15.5 Conclusion

In this work, we presented a novel approach to tackle the challenges of the policy paradox. This paradox describes the fact that despite the acknowledged importance of scientific evidence for political decision making, the knowledge gained from scientific disciplines is seldom considered in policy making. In our approach, we proposed a concept that addresses this problem by introducing information visualiza- tion technologies to the policy-analysis field. Therefore, we described the disciplines of information visualization and policy analysis. We also identified capabilities provided by information visualization and challenges faced by policy analysis.

Information visualization is defined as “the use of computer-supported interac- tive, visual representations of abstract data to amplify cognition.” Its purpose is the exploration, sensemaking, and communication of knowledge hidden in data. Policy analysis deals with the analysis of societal problems, and alternative policy options to be chosen by policy makers that may serve as solutions to these problems. For the generation of these policy options, scientific advice is proposed. The main challenges of policy analysis lie in an effective exploration, and sensemaking of policy options by the policy analysts, as well as a comprehensible communication of the analysis results to the policy makers who finally decide upon the options to be chosen.

From the capabilities of information visualization on the one hand, and the chal- lenges of policy analysis on the other hand, we identified synergy effects resulting from the combination of these two fields. With this motivation, we proposed a method how to apply information visualization to the field of policy analysis. Therefore, we

15 Visual Decision Support for Policy Making 351

identified relevant stakeholders in the policy-making process. We defined possible collaborations between these stakeholders and hurdles that have to be faced. Finally, we sketched a methodology how to structure the development of such science–policy interfaces supported by information visualization.

As a last facet of our contribution, we presented three case studies that have been conducted in two European research projects dedicated to the field of policy mod- eling. These studies basically implemented the concept described in this approach. In the case studies, technologies from the scientific fields of agent-based simulation, optimization, and geo-spatial data modeling have been applied to the field of policy making in order to generate and analyze policy options for a given societal prob- lem. All case studies provided access to the computational models by information visualization technologies. This enabled even non-IT experts to interact with com- plex models and generate policy options. Moreover, the visualization tools could be used to communicate and discuss the results derived from the policy analysis. The case studies showed that our provided concept can serve as an approach to further explore the synergy effects between information visualization and policy analysis. We believe that our provided concept stimulates and motivates further research and discussions in this new, interesting, and not yet extensively studied interdisciplinary field.

Acknowledgments Research presented here is partly carried out within the project “urbanAPI” (Interactive Analysis, Simulation and Visualisation Tools for Urban Agile Policy Implementation), and “ePolicy”(Engineering the Policy-Making Life Cycle) funded from the 7th Framework Pro- gram of the European Commission, call identifier: FP7-ICT-2011-7, under the grant agreement no: 288577 (urbanAPI), and no: 288147 (ePolicy), started in October 2011.

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Chapter 16 Analysis of Five Policy Cases in the Field of Energy Policy

Dominik Bär, Maria A. Wimmer, Jozef Glova, Anastasia Papazafeiropoulou and Laurence Brooks

Abstract While the twentieth century is considered as the century of population explosion and burning of fossil fuels, environmental policies and the transition to effectively use renewable energy sources have become a priority of strategies in re- gions, countries and internationally. Different projects have been initiated to study the best suitable transition process towards renewable energy. In addition, an increas- ing number of climate change and energy policies is being formulated and released at distinct levels of governments. Many of these policies and projects pursue the aim of switching from energy sources like fossil fuels or nuclear power to renewable energy sources like solar, wind or water. The aim of this chapter is to provide foundations of policy implementation and particular methods as well as to investigate five policy implementation cases through a comparative analysis.

16.1 Introduction

The twentieth century was the century of population explosion and burning of fossil fuels, which led to the highest pollution in history causing climate change and bio- diversity loss (Helm 2000). However, the pollution and its consequences have only been recognised in the recent decades and environmental policies are now of high

M. A. Wimmer (�) · D. Bär University of Koblenz-Landau, Koblenz, Germany e-mail: [email protected]

D. Bär e-mail: [email protected]

J. Glova Technical University Kosice, Kosice, Slovakia e-mail: [email protected]

A. Papazafeiropoulou · L. Brooks Brunel University, Uxbridge, UK e-mail: [email protected]

L. Brooks e-mail: [email protected]

© Springer International Publishing Switzerland 2015 355 M. Janssen et al. (eds.), Policy Practice and Digital Science, Public Administration and Information Technology 10, DOI 10.1007/978-3-319-12784-2_16

356 D. Bär et al.

priority to society, companies and policymakers (Helm 2000). Owing to this, gov- ernments all over the world have launched projects to improve the climate situation. The problem scope dealt with in this chapter concerns climate change and policies dealing with topics like sustainable energy management and the use of renewable energy sources. Many projects pursue the aim of switching from energy sources like fossil fuels or nuclear power to renewable energy sources like solar, wind or water. So on the one hand, the aim of policies is to replace polluting ways of power production with green technologies and, on the other hand, to reduce energy consumption by using innovative technologies.

Climate change affects the whole world and is a very huge organisational, tech- nical and financial challenge, which is why industrial countries are expected to take responsibility and initiatives to counteract the current climate development. In the cause of this, these countries may serve as role models for other countries to join in improving the climate situation.

In this chapter, five projects and cases dealing with policies of climate change and energy use are investigated. First, a theoretical ground is provided about policy implementation like theories of policy implementation or methods of implementa- tion in order to establish a common understanding. Subsequently, the projects are investigated and analysed via comparative analysis, performed in the frame of the eGovPoliNet1 initiative. The selection of the policy cases was based on the authors’ access to information of the cases of policy implementation. A framework2 has been developed for the comparative analysis that supports pointing out major aspects and core information about the projects in order to have a brief overview and to make the projects comparable to each other. The framework provides a set of categories which need to be filled in to describe and analyse the projects, starting from an abstract and objectives, which gives both a brief summary of the policy case under investigation and its context and objectives, followed by a tabular overview structured along (a) metadata providing general information such as name and duration of the project, type of project (piloting case of a project or implementation project), domain (i.e. referring to the particular sector the policy is dealing with) and references; and (b) conceptual aspects of interest in the comparison providing more specific informa- tion such as specific policy domain and particular policy addressed, targeted users and/or stakeholders, an indication of the complexity of the policy case, theories used to develop the policy, methods used, supporting technology frameworks and tools use3, simulation models developed4, project outcome, links to other projects, trans- ferability of solutions and techniques as well as concluding recommendations of the

1 eGovPoliNet—Building a global multidisciplinary digital governance and policy modelling research and practice community. See http://www.policy-community.eu/ (last access: 28 July 2014). 2 The framework is published in Annex I to technical report D 4.2 of eGovPoliNet: Maria A. Wimmer and Dragana Majstorovic (Eds.): Synthesis Report of Knowledge Assets, including Visions (D 4.2). eGovPoliNet consortium, 2014, report available under http://www.policy- community.eu/results/public-deliverables/ (last access: 28 July 2014). 3 A comparative analysis of tools and technologies is provided in Kamateri et al. (2014). 4 A comparative analysis of simulation models is provided in Majstorovic et al. (2014).

16 Analysis of Five Policy Cases in the Field of Energy Policy 357

project or case. Based on the identified information from the comparative analysis, the projects are briefly discussed and compared to each other. Moreover, the results and benefits of the projects are described and the possibility of transferring the used approaches to other domains, projects or cases is investigated.

The following three research questions drive the comparative investigations of projects and cases: (1) what approaches of policy modelling are used in implementing public policies, how do these approaches differ and are these approaches best fit for the purposes of the policy cases? (2) How can the implications of selecting a particular approach to ensure successful policy implementation be measured and what lessons can be drawn from the case analyses? (3) How easily can the approaches of the policy cases investigated in the chapter be adopted to other countries, other policy domains and even other thematic policy areas?

The chapter is structured as follows: In Sect. 16.2, theoretical grounds and definitions about policy implementation are given in order to provide a common understanding and an overview of the purpose of policy implementation as well as of policy instruments used in climate change and renewable energy policy. Thereafter, the comparative analysis framework is introduced regarding its structure and con- tent. Using this framework, projects and cases of the field are analysed in Sect. 16.4 and subsequently discussed and compared to each other, including a brief reflection of research and practice implications, and further research needs (Sect. 16.5). The chapter ends with some concluding remarks in Sect. 16.6.

16.2 Theoretical Grounds of Policy Implementation

Buse et al. argue that policy implementation refers to the execution of a formulated policy, which means turning theory into practice. When turning policy into practice, it is common to observe a gap between formulated and implemented policy as the policymakers hand over the responsibility for the implementation to policy imple- menters who may have a different understanding of the policy (Buse et al. 2012). The policy formulation is seen as a political activity and the implementation as techni- cal, administrative or managerial activity. The gap between policymakers and policy implementers causes a lack of control from the policymaker view regarding the way the policy is implemented.

Implementation of public policy is always serving a purpose and is put in place in order to change things for the better and improve situations that seem to be problem- atic. There are different ways that decisions for a policymaking process to start take place (Lindblom 1968). An obvious but not always the most common way is through public demands. These are demands from the general public (known as “bottom up” initiatives) and can be very influential especially for important issues such as public health and safety. Nowadays, the general public is educated and informed at a level that gives them the power to be able to mobilize and in some cases demand changes at a public policy level. Another reason that policy implementation is starting to for- mulate is pressure from special interest groups that can influence policies promoting

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public welfare. For example, chambers of commerce are typically supporting interest of their business members, while Green Peace will express concerns and will try to address environmental issues, promoting the implementation of public policies for environmental protection (Portney and Stavins 2000).

According to the policy cycle, the implementation of a policy follows some basic steps such as agenda setting (problem identification), policy formulation, decision- making, implementation and evaluation (Nakamura 1987). The first stage of this cycle where the problem is identified is the stage where the purpose of the policy is formulated and is recognised as the starting point of the cycle. During this agenda setting, all stakeholders are or need to be participating and voicing concerns as well as possible remedies for the problem at hand. This stage was typically initiated in the past by government agencies but latest studies show that a number of other entities influence this stage (Young and Mendizabal 2009). These could be the media, think tanks, policy research institutes and other academic or business organisations.

The final outcome of the agenda setting stage is a purpose statement where poli- cymakers state the problem as well as the desired outcome of the proposed strategy. Examples of such statements can be details of a costal policy and its desired out- comes (NZPCS 2010). The desired outcomes of policymaking are always aiming at improving the problem area in question and ultimately improve the welfare of citizens at large.

An important but not always well-executed stage of the policy implementation cycle is that of the evaluation of the policy outcomes. This is the time when the designers of a public policy have finalised the implementation and are in a posi- tion to evaluate whether the actions taken improved the situation and contributed to the welfare of the target population. Evaluation is a retrospective assessment of government initiatives, and it usually measures the success of activities that they are still taking place and are ongoing. Evaluation seems to be a controversial and hard-to-implement strategy that needs to be based on peoples’ perceptions, opinions and judgments while at the same time needs to be objective enough to provide some insights into the complexities of public interventions (Vedug 1997).

As this chapter focuses on policy cases of climate change and renewable energy policies, the next two sections introduce instruments used in these two policy domains for steering and governing.

16.2.1 Instruments for Climate Change Policy

For the implementation and application of climate and energy policies, Oikonomou and Jepma present different instruments. They acknowledge that categorizations of policies differ within literature and therefore they make use of general studies from OECD, IPCC, etc. They have identified the following policy instruments (Oikonomou and Jepma 2007):

16 Analysis of Five Policy Cases in the Field of Energy Policy 359

Table 16.1 Typology of policy instruments for global climate change summarised from Stavins (1997)

Types of instruments Categories

Command-and-control (and voluntary in domestic)

Market-based

Domestic Energy efficiency standards Charges, fees and taxes (carbon taxes, taxes on fossil fuels, other energy taxes)

Product prohibitions Tradable rights (tradable carbon rights, tradable “emission reduction” credits)

Voluntary agreements

International Uniform energy efficiency standards

Charges, fees and taxes (harmonized domestic taxes, uniform international tax)

Fixed national emission limits Tradable rights (international tradable permits, joint implementation)

• Financial measures, where the government can change the cost of energy through taxation and subsidy policies. The following types of taxation are distinguished: emission charges/taxes, user charges, and product charges/taxes.

• Legal or regulatory instruments, where governments can set legal requirements with financial penalties for non-compliance.

• Organisational measures are commitments undertaken by power producers or industries in consultation or negotiation.

• Certificates or marketable (tradable) permits or quotas.

Stavins identifies two distinct categories of policy instruments that are particular in global climate change: The first category—domestic policy instruments—enables individual nations to achieve their specific national or local targets and goals. The second category—bilateral, multilateral or global (or in general international) instruments—can be employed jointly by groups of nations (Stavins 1997). The au- thor developed a typology of these two categories of policy instruments for global climate change which is summarised in Table 16.1.

16.2.2 Policy Instruments for Renewable Energy

Energy policy is closely linked to climate change as the energy sector has high potential for reducing greenhouse gas (GHG) emissions. There is no universal policy prescription for supporting renewable energy. Particular nations are typically unique. The most suitable policy instruments in one country may not be appropriate for another country. Instead of a single policy to achieve all of the policy objectives, it is more useful to consider a policy portfolio approach or a policy toolkit. Policy instruments are means by which policy objectives are pursued (Howlett 2009). Azuela

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and Barroso (2011) and IPCC (2012) put forward in the following five categories of policy instruments for renewable energy:

• Regulations and standards can promote renewable energy via direct support (with policy objectives in removal of non-economic barriers and in increasing demand for renewable energy) and indirect support (with policy objective in restrictions on fossil fuel power).

• Quantity instruments—market-based instruments that define a specific target or absolute quantity for renewable energy production.

• Price instruments—reduce cost- and pricing-related barriers by establishing favourable price regimes for renewable energy relative to other sources of power generation, e.g. fiscal incentives (production/investment tax credits, public invest- ment, loans or grants; capital subsidy, grant or rebate; increase in taxes on fossil fuels; reductions in sales, energy, CO2, value-added tax (VAT) or other taxes) and feed-in tariffs (a preferential tariff; guaranteed purchase of the electricity produced for a specified period; guaranteed access to the grid).

• Public procurement—governments are often a very large energy consumer, whereby their purchasing and procurement decisions affect the market.

• Auction—an auction is a selection process to allocate goods and services compet- itively, based on a financial offer. Specifically in a “reverse auction”, electricity generators bid their supply to distribution companies and the process is designed to select the lowest prices. Auctions can be a very attractive mechanism for attracting new renewable energy supply.

16.3 Approaches to Policy Implementation

Policies can be implemented in different ways. Subsequently, four approaches of pol- icy implementation are presented: top-down approach, bottom-up approach, macro- and micro-implementation and principal–agent theory. They exemplarily point out how policies can be implemented, what actors are involved along the implementation process and how they affect the policy, its implementation and outcome.

16.3.1 Top-Down Approach

The top-down approach was developed between the 1960s and 1970s by policy ana- lysts in order to provide policymakers with a better understanding of how to minimise the gap between the formulated and the implemented policy (Buse et al. 2012). This approach describes a linear process from policy formulation to implementa- tion, where policies are communicated from policymakers to executing entities like authorities, which turn the policy into practice. To successfully implement a pol- icy, the policy goals need to be clearly described and understood by all involved

16 Analysis of Five Policy Cases in the Field of Energy Policy 361

actors. Moreover, the required resources for the implementation need to be avail- able, a communication and command chain needs to be established and the whole implementation process needs to be controlled (Pressman and Wildavsky 1984).

The top-down approach may be criticised as it focuses mainly on the decision and on policymakers while it does not sufficiently include other involved actors and factors that are part of the policy implementation process. The implementation is seen as an administrative process and does not include the expertise of local experts who eventually implement the policy. Thus, the approach is difficult to apply in situations that are not driven by a single leading actor but where multiple actors participate in the policy implementation process (Buse et al. 2012). For this approach, Gunn formulated ten pre-conditions which should be fulfilled to successfully implement a policy (Gunn 1978 and Hogwood and Gunn 1984). However, Buse et al. criticize that hardly all pre-conditions could be fulfilled at once and that policy implementation in reality is too complex and thus cannot be covered with the top-down approach and its pre-conditions (Buse et al. 2012).

16.3.2 Bottom-Up Approach

The bottom-up approach was developed from the criticism of the top-down approach, which focuses on policymakers and neglects the other actors involved in the imple- mentation process. The bottom-up approach focuses on policy implementers as they play an important role in the policy implementation process as active participants who give feedback to the policymakers and have high influence on the actual pol- icy implementation (Buse et al. 2012). Lipsky studied the behaviour of “street-level bureaucrats” (teachers, doctors, nurses, etc.) in relation to their clients in the 1970s (Lipsky 1980). In his studies, Lipsky showed that even people in highly rule-bound environments could reshape parts of public central policy for their own ends (Buse et al. 2012). In consequence of these findings, researchers found that even if all pre-conditions for the top-down approach (see Gunn 1978) were fulfilled, policies could still be implemented in a way which was not planned by the policymakers (Buse et al. 2012).

16.3.3 Macro- and Micro-implementation

When governments execute policies in order to influence local authorities, it is called macro-implementation (Berman 1978). However, local authorities need to transfer governmental policies into their own local policies, which is then called micro- implementation. This approach can be understood as a two-phase implementation method. In the first phase, the overall policy is made by governmental policymakers in order to address certain issues and to pursue defined goals. Local authorities and policymakers then need to adopt the overall policy and transform it into a policy that

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is manageable and suited for local application. This transformation process may lead to a gap between the formulated governmental policy and the executed local policy, which makes this approach quite similar to the bottom-up and top-down approaches respectively. All these approaches carry the risk of a mismatch between formulated and implemented policy as is extensively elaborated, e.g. in James et al. (1999).

16.3.4 Principal–Agent Theory

According to Buse et al., the principal–agent theory argues an “implementation gap” as the inevitable consequence of the governmental institution structure. Policy- and decision-makers (“principals”) delegate responsibility for the implementation of policies to their officials (“agents”), whom they cannot completely monitor and control. These “agents” have discretion in how they work on implementing the policy and may also see themselves from a different view than the policymakers. Thereby policy implementers may interpret the policy in a different way than the policy formulators which leads to implementing the policy in a different way than it was actually meant to be implemented (Buse et al. 2012).

Policy implementation is a complex process that is influenced by many actors (Turnpenny et al. 2005). From its formulation until its implementation, the policy passes through different levels of authorities and is handled by different actors. It is formulated by governmental policymakers and then passed on to local policymakers and authorities who have to adapt the overall policy in order to implement it suc- cessfully in their local structures. Along this implementation process, governmental policymakers are not completely able to monitor and control the implementation, as local policymakers need to take care of local policy peculiarities. Moreover, the local policymakers may understand the overall policy in a different way than it is meant to be understood. These factors, often inevitable, lead to a so-called implementation gap (James et al. 1999). This gap is the consequence of the different understandings and backgrounds of the actors who are involved in the implementation process of the policy. This issue needs to be addressed in order to minimise the gap between formulated and implemented policy, so that policies are implemented the way they are meant to be implemented.

In the next section, five different cases of policy implementation are being studied and compared to investigate the three research questions formulated in the introduc- tory chapter. The theoretical foundations presented in Sect. 16.2 and the distinct approaches introduced in this section provide the underlying understanding for the comparative analysis of cases of climate change and renewable energy policy.

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16.4 Investigating Five Cases of Climate Change and Renewable Energy Policy

Based on the research foundations and investigation of distinct approaches to policy implementation, the projects and cases introduced in this section provide examples of how policies are being implemented or how the implementation process of policies concerning climate change and energy matters is supported. In order to analyse the projects and cases and to describe them in detail, the framework developed in eGovPoliNet as outlined in the introductory section is used (i.e. describing the cases along abstract and objectives, metadata and relevant conceptual aspects). This framework offers the possibility to point out major aspects and characteristics of the projects and cases and to make them comparable along those aspects. The five cases chosen and analysed via the comparative analysis template are:

• Assessing the EU policy package on climate change and renewables • German nuclear phase-out and energy transition policy • KNOWBRIDGE: Cross-border knowledge bridge in the renewable energy

sources (RES) cluster in East Slovakia and North Hungary • Kosice Self-governing Region’s (KSR’s) strategy for the use of renewable energy

resources • MODEL: Management of domains related to energy in local authorities

The projects and cases have been selected on the basis of relevance for the domain of study of this chapter and of sufficient access to information to carry out the comparative analysis.

16.4.1 Assessing the EU Policy Package on Climate Change and Renewables

Abstract: As stated by Capros et al., the EU aims to reduce GHG emissions at least by 20 % in 2020 compared to 1990. Likewise, 20 % of energy needs should be covered through renewable energy sources—see EU (2007). The research of Capros et al. developed an energy model to assess the range of policy options that were debated to meet the two targets of the EU policy. Options of the energy policy explore and assess trading of renewable targets, carbon trading in power plants and industry and the use of the Clean Development Mechanism to improve cost-efficiency. In the research assessment of the EU energy policy, the authors also examined fairness by analysing the distribution of emission reduction in the non-emission trading sector, the distribution of CO2 allowances in the emission trading sector and the reallocation of renewable targets across Member States. The authors assess the overall costs of meeting both targets being in the range of 0.4–0.6 % of gross domestic product (GDP) in 2020 for the EU as a whole. It is also argued that the redistribution mechanisms

364 D. Bär et al.

employed would significantly improve fairness compared to a cost-effective solution (Capros et al. 2011).

The main objectives of the EU policy package on climate change and renewables contain (Capros et al. 2011; EU 2007):

• Reducing unilaterally GHG by 20 % in 2020 compared to 1990 levels (including an offer to increase this target to −30 % given a sufficiently ambitious international agreement)

• Supplying 20 % of energy needs by 2020 from RES, including the use of 10 % renewable energy in transport

• Giving priority to energy efficiency in all energy domains

The assessment study of Capros et al. aimed at developing and testing an energy model to assess the range of policy options discussed to meet the two targets of the EU policy (Capros et al. 2011). Table 16.2 outlines the main aspects of the EU policy package and the respective assessment study of Capros et al. (2011).

16.4.2 German Nuclear Phase-Out and Energy Transition Policy

Abstract: Following the Fukushima disaster in Japan in March 2011, the German chancellor Merkel declared a 3-month moratorium on nuclear power plants, in which checks took place and nuclear policy was reconsidered. Subsequently, all eight nu- clear power reactors which began operation in 1980 or earlier were immediately shut down. Although the Reactor Safety Commission reported that all German reactors were basically safe with regard to natural or man-made dysfunction, the government decided to shut down the nine remaining reactors until 2022 and approved construc- tion of new coal and gas-fired plants despite retaining its CO2 emission reduction targets, as well as expanding wind energy. Germany was expected to be dependent on energy imports after the shutdown of the first eight reactors but it still kept exporting energy as the energy production from wind, solar and hydro keeps growing. So far, the use of renewable sources is quite expensive and shouldered by tax payers and consumers. Moreover, it is dependent on wind and sunlight which are not always available (Moore 2013).5

The main objectives of Germany’s nuclear phase-out and energy transition policy can be summed up as:6

• To accelerate the transformation of Germany’s energy system to RES (nuclear power serving only as “bridging technology” to transform)

5 See also the following two websites (last access: 30 July 2014): http://www.dw.de/power-exports- peak-despite-nuclear-phase-out/a-16370444 and http://energytransition.de/. 6 See also the following two websites (last access: 30 July 2014): http://www.dw.de/power-exports- peak-despite-nuclear-phase-out/a-16370444 and http://energytransition.de/.

16 Analysis of Five Policy Cases in the Field of Energy Policy 365

Table 16.2 Analysis of metadata and conceptual aspects of the study assessing the EU policy package on climate change and renewables

Metadata

Name Assessment of EU policy package on climate change and renewables

Duration EU policy package: 2007–2020

Domain Climate change and energy sectors

Project type Policy implementation (of EU policy package) and assessment (for the research study)

Reference(s) For the EU climate and energy policy package: EU (2007, 2008) and online under: http://ec.europa.eu/clima/policies/package/index_ en.htm (last access: 30 July 2014) For the assessment study: Capros et al. (2011), PRIMES model of NTUA (http://www.e3mlab.ntua.gr/index.php?option=com_content &view=category&id=35%3Aprimes&Itemid=80&layout=default& lang=en, last access 30 July 2014), GAINS model of IIASA (http://www.iiasa.ac.at/rains/C&E_package.html?sb=19, last access 30 July 2014)

Conceptual aspects

Implementing which policy

Energy policy (emissions and renewable energy sources)

Users/Stakeholders European Commission, EU Member States, industry, general public

Complexity Very high due to involvement of different actors and dependency of many interrelated factors

Theory(s) useda Macro-modelling with PRIMES energy system model, which implements partial equilibrium (energy system and markets); and with GAINS model of IIASA, which models non-CO2 GHGs and derives emissions of non-CO2 GHGs from a series of activity indicators, referring among others to agriculture and to specific industrial processes

Method(s) useda Scenario modelling and simulation modelling (cross-modelling of interacting targets) 150 energy scenarios with different carbon and RES values were investigated by using the PRIMES model for the period 2005–2030 for all EU Member States

Supportive technology frameworks and tools useda

PRIMES energy system model of NTUA GAINS model of IIASA

Model(s) generateda PRIMES model, GAINS (greenhouse gas—air pollution interactions and synergies) model

Project outcomea Eleven scenarios with different starting positions and influences Analysis of the different scenarios

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Table 16.2 (continued)

Conceptual aspects

Transferability of solutions and techniquesa

Partially given as the models can serve as blueprints for similar models and as source for exploring further aspects of climate change and energy policy. The transferability is, however, restricted to the very policy domain

Concluding recommen- dations of the projecta

Meeting the targets in the EU is an ambitious effort and requires considerable adjustments in how energy is consumed and produced Energy efficiency improvement is clearly the most cost-effective way for meeting the targets and must be the main driver of changes RES are of crucially important to implement the policy The compliance costs to meet both targets is estimated to be in a range between 0.4 and 0.6 % of GDP of the EU in 2020

GAINS Greenhouse Gas and Air Pollution Interactions and Synergies, GHGs greenhouse gases, IIASA International Institute for Applied Systems Analysis, NTUA National Technical University of Athens, RES renewable energy sources aThese entries provide analysis data regarding the assessment study but not for the EU policy package itself

• To shut down all nuclear power plants in Germany by 2022. The shutdown dates for the remaining reactors are: by 2015, Grafenrheinfeld; by 2017, Gundremmingen B; by 2019, Philippsburg 2; by 2021, Grohnde, Gundremmingen C and Brokdorf; and by 2022, the three youngest nuclear power stations, Isar 2, Emsland and Neckarwestheim 2.

• To find reliable alternative energy sources to coal power plants, which are still needed to close energy gaps

• To switch to renewable energy (sources; solar, wind, hydro)

Table 16.3 sums up the major metadata and conceptual aspects of the German nuclear phase-out and energy transition policy.

16.4.3 KNOWBRIDGE: Cross-Border Knowledge Bridge in the RES Cluster in East Slovakia and North Hungary

Abstract: The KNOWBRIDGE project is one of the three agreed initiatives of the cross-border Hungarian–Slovakian region, and it aims to increase and strengthen the capacity of the research potential of two cross-border and convergence re- gions: the KSR in Slovakia and the Borsod–Abaúj–Zemplén region in Hungary. KNOWBRIDGE is supporting the development of a new innovative cross-border research-driven cluster in the area of RES and associating research entities, en- terprises and regional authorities. The major activities in the project are analysis, mentoring and integration of research agendas and the definition of a Joint Action Plan in order to support regional authorities and at the same time take account of the

16 Analysis of Five Policy Cases in the Field of Energy Policy 367

Table 16.3 Analysis of metadata and conceptual aspects of the German nuclear phase-out and energy transition policy

Metadata

Name German nuclear phase-out and energy transition policy

Duration 06/2011–2022

Domain Energy sector

Project type Policy implementing

Reference(s) http://www.dw.de/power-exports-peak-despite-nuclear-phase-out/a- 16370444 (last access: 30 July 2014) http://energytransition.de/ (last access: 30 July 2014) http://www.bundesregierung.de/Content/DE/StatischeSeiten/Breg/ Energiekonzept/05-kernenergie.html (last access: 30 July 2014) http://www.greenpeace.de/themen/energiewende (last access: 30 July 2014) (Moore 2013; Morris and Pehnt 2012)

Conceptual aspects

Implementing which policy

Energy policy (nuclear phase-out and transition to renewable energy sources)

Users/Stakeholders German politicians, energy providers and energy service sector, industry, general public

Complexity Very high due to the involvement of many different actors and the complexity of providing a balanced as well as target oriented implementation of the nuclear phase-out and transition to renewable energies The high complexity requires very extensive and accurate planning

Theory(s) used Not successful in retrieving relevant information

Method(s) used Not successful in retrieving relevant information

Supportive technology frameworks tools and used

Monitoring system to monitor the policy implementation (annual reports on progress and examination by expert commission)

Model(s) generated Various by distinct institutions, yet no insights to what kinds of models were generated as only the results are shown and discussed in the various literature studied

Project outcome Germany will become one of the world’s most efficient, most innovative and greenest economies Shutdown of all nuclear reactors by 2022 Growing engagement in renewable energy (source) development, which also contributes to jobs and economic growth Germany is setting standards with its energy concept for the EU and globally

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Table 16.3 (continued)

Conceptual aspects

Transferability of solutions and techniques

Germany serves as a role model for other countries (in Europe and worldwide) on the way to a cleaner and more sustainable energy system

Concluding recommen- dations of the project

Morris and Pehnt (2012) conclude the following nine key findings of implementing the nuclear phase-out and the energy transition in German in their report, which serve also as overall recommendations in this comparison: The German energy transition is an ambitious, but feasible undertaking The German energy transition is driven by citizens and communities The energy transition is Germany’s largest post-war infrastructure project. It strengthens its economy and creates new jobs With the energy transition, Germany aims to not only keep its industrial base, but make it fit for a greener future Regulation and open markets provide investment certainty and allow small business to compete with large corporations Germany demonstrates that fighting climate change and phasing out nuclear power can be two sides of the same coin The German energy transition is broader than often discussed. It not only includes renewable electricity, but also changes to energy use in the transportation and housing sectors The German energy transition is here to stay The energy transition is affordable for Germany, and it will likely be even more affordable for other countries

interest of the private companies operating in the RES branch and of the research and development institutions. Therewith, a good basis for a triple helix concept is promoted.7

The objectives of KNOWBRIDGE are as follows8:

• To increase the overall capacities of regional players in northern Hungary and eastern Slovakia in enhancing science and technology-based development in cross-border context

• To improve links between regional authorities, research entities and local business community in two cross-border regions

• To promote development of specific goals for regional and cross-border research and technological development (RTD) policies

• To enhance common partnership of regional authorities, research entities and business community in national and European initiatives

7 See http://www.knowbridge.eu/index.php (last access: 29 July 2014) and http://cordis.europa. eu/result/report/rcn/54725_en.html (last access: 29 July 2014). 8 See http://www.knowbridge.eu/index.php (last access: 29 July 2014) and http://cordis.europa. eu/result/report/rcn/54725_en.html (last access: 29 July 2014).

16 Analysis of Five Policy Cases in the Field of Energy Policy 369

• To foster trans-national (cross-border) cooperation between regional partners • To further develop the research-driven cluster in the area of RES • To develop joint action plans in order to increase regional economic competitive-

ness through research and technological development activities in the defined area of RES

• To exploit synergies between regional national and Community programmes for research and economic development in cross-border environment

• To promote the reduction of CO2 emissions in two cross-border regions

Table 16.4 provides insights into the KNOWBRIDGE project along the analysis framework of eGovPoliNet.

16.4.4 KSR’s Strategy for the Use of Renewable Energy Sources

Abstract: The KSR (Slovakia) aims at supporting the utilisation of renewable energy sources, at achieving a better energy efficiency and at decreasing the energy con- sumption overall. In order to support these policy goals, KSR has participated in the Open Collaboration for Policy Modelling (OCOPOMO) project9 as a case study to explore innovative approaches to policy modelling and exploration, and especially to explore the views and attitudes of the various stakeholders in this sensitive pol- icy context. OCOPOMO’s Kosice policy model focuses on stakeholder views, on different alternative renewable sources of energy, as well as on the traditional en- ergy production and consumption culture in the region. A particular focus is put on policy instruments and patterns for promoting the use of renewable energy, for best assessing the perceived market potential of each specific kind of energy source, for understanding the contractual, social and technical barriers hindering a specific kind of technology for energy generation in the Kosice region, and for understanding the motivating factors for citizens and companies to use RES while at the same time in- creasing energy efficiency by e.g. better insulation of buildings (Scherer et al. 2013; Wimmer et al. 2012).

In order to achieve a widely accepted energy policy, KSR argues that regional energy development should prioritise the development of renewable energy sources, and policies should in particular focus on building infrastructures that particularly support these goals.

In Table 16.5, we analyse the policy formulation case along the eGovPoliNet framework to provide further details.

9 www.ocopomo.eu (last access: 31 July 2014).

370 D. Bär et al.

Table 16.4 Analysis of metadata and conceptual aspects of KNOWBRIDGE in the RES Cluster in East Slovakia and North Hungary

Metadata

Name KNOWBRIDGE: The Cross-border Knowledge Bridge in the RES Cluster in East Slovakia and North Hungary

Duration 2009–2012

Domain Energy sector

Project type EC co-funded project case study supporting policy formulation through a new way of innovative collaboration among key actors of governments, energy industry and research institutions

Reference(s) http://www.knowbridge.eu/index.php (last access: 29 July 2014) http://cordis.europa.eu/result/report/rcn/54725_en.html (last access: 29 July 2014)

Conceptual aspects

Implementing which policy

Supporting the research potential and the collaboration of governments with relevant actors of the energy sector and of research institutions of two cross-border and convergence regions in order to better exploring synergies and building up of capacities in the domain of renewable energy sources

Users/Stakeholders Regional governments and politicians of the East Slovakian Košice Self-governing Region and of the North Hungarian Borsod–Abaúj–Zemplén region, energy providers, researchers

Complexity Rather high due to the involvement of different actors with their specific interests and due to the complexity of the RES domain

Theory(s) used Not successful in retrieving relevant information

Method(s) used Desk research and participatory methods to develop and evaluate a research-driven cluster in the RES sector Joint framework with toolbox for analysis and benchmarking of the local RES sector and the cross-border cluster as well as for developing the Joint Action Plan and Business Plans Guidelines and reports SWOT analyses

Supportive technology frameworks and tools used

Not successful in retrieving relevant information

Project outcome Reports on best practices and trends in the areas of (1) national and regional economic and technological development focused on RES, (2) RTD support policies and (3) knowledge creation, transfer between business entities through networking Methodological toolbox for Joint Action Plan and Business Plan preparation

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Table 16.4 (continued)

Conceptual aspects

Financial tools and approaches for RTD funding Report on energy efficient technologies and technological development in RES Report on energy solution responding to SMEs specific energy demands in the region SWOT analyses in local RES Joint Action Plan for cross-border cluster in RES Mutual learning models elaboration

Links to other projects Relevant related projects of policy implementation in the domain of climate change and RES are: http://www.arr.sk/?projekty&gid=19 (last access: 29 July 2014) http://www.cogitaproject.eu/index.php/en/ (last access: 29 July 2014) http://www.huskroua-cbc.net/en/ (last access: 29 July 2014)

Transferability of solutions and techniques

Methodological toolbox for analysis and benchmarking and methodological toolbox for Joint Action Plan and Business Plan is adoptable and adjustable for other cross-border activities in the area of RES

Concluding recommen- dations of the project

The project serves as a good blueprint of (1) cross-border collaborations of regions and (2) of collaboration of different actors in policy planning The methodological toolboxes can serve similar projects in their planning It is yet to be monitored and evaluated how the policy plans, joint action plan and business plan will be implemented in order to maintain and keep the network of actors sustainably active and successful, especially as EC-funding is in general a temporary investment

RES renewable energy sources, RTD research and technological development, SWOT strengths, weaknesses, opportunities and threats

16.4.5 MODEL: Management of Domains Related to Energy in Local Authorities

Abstract: MODEL stands for “Management of Domains Related to Energy in Local Authorities”. The project aims at reducing the energy gap in the EU and beyond by helping volunteer local authorities become models for their own citizens and other municipalities. MODEL has started in 2007 with the support of the Intelligent Energy Europe programme and has set up a common methodology that was implemented in 43 pilot cities from new EU Member States and Candidate Countries so far. The main objective is that cities become models for citizens and other municipalities regarding energy management.

372 D. Bär et al.

Table 16.5 Analysis of metadata and conceptual aspects of KSR’s strategy for the use of RES

Metadata

Name Kosice Self-governing Region’s strategy for the use of renewable energy sources

Duration 2010–2013

Domain Energy sector

Project type Pilot case of policy formulation of the OCOPOMO project

Reference(s) http://www.ocopomo.eu/ (last access: 29 July 2014), (Scherer et al. 2013; Wimmer et al. 2012) An analysis of the software modelling approach of OCOPOMO and the Kosice case is also provided in Majstorovic et al. (2014)

Conceptual aspects

Implementing which policy

Energy policy with focus on the increased use of RES as well as a better insulation of buildings

Users/Stakeholders Government officials of the Self-governing Region of Kosice, energy provider, owners of houses and buildings, citizens and companies as energy consumers

Complexity Rather complex because of the involvement of distinct actors and policy objectives

Theory(s) used Complexity theory, agent-based modelling, stakeholder engagement theory, design research and meta-modelling

Method(s) used Online consultation and engagement of stakeholders, scenario building, conceptual modelling, agent-based modelling, qualitative data analysis and coding through ontology development, provenance information conveyed from narrative scenarios to formal simulation models through a traceability concept using text annotation and UUID

Supportive technology frameworks and tools used

Eclipse modelling framework Collaboration and scenario editing tool (CSET) based on Alfresco Web content management system Consistent conceptual description tool (CCD Tool), CCD2DRAMS Tool, declarative rule-based agent-modelling system (DRAMS)—all based on eclipse modelling framework Simulation analysis tool

Model(s) used Conceptual model as domain ontology, meta-models of conceptual model and simulation model, simulation models of Kosice policy via DRAMS Various conceptual models using UML modelling techniques

16 Analysis of Five Policy Cases in the Field of Energy Policy 373

Table 16.5 (continued)

Conceptual aspects

Project outcome The project explored policy alternatives generated by stakeholders in scenarios in order to understand the behavioural aspects of the stakeholders involved towards policy options. Policy options explored were among others: generating clean power using regional resources; reducing CO2, generating new job opportunities if investments in renewables are being made, increasing energy efficiency and decrease energy consumption through: (1) integration of new heating technologies (cogeneration, heat pumps), (2) better insulation of buildings, (3) switching to a natural gas fuel for public transportation by bus, (4) investment in municipal boiler house with integrated cogeneration unit fuelled by biomass, (5) advisory services for citizens and their awareness raising, (6) cooperation with private companies and local actors on the development and (7) the implementation of a city energy strategy

Links to other projects Campania regional knowledge transfer case: http://www.ocopomo.eu/in-a-nutshell/piloting-cases/campania- region-italy (last access: 29 July 2014) London housing policy case: http://www.ocopomo.eu/in-a- nutshell/piloting-cases/greater-london-authority-gla (last access: 29 July 2014) Use of OCOPOMO tools in GLODERS: http://www.gloders.eu (last access: 31 July 2014)

Transferability of solutions and techniques

Basic approach transferable to different policy environment where stakeholder engagement is important, conceptual modelling shall facilitate the transformation of narrative text inputs of evidences to inform policy simulation models, and simulation models in DRAMS can serve as blueprints for new policy simulation models based on DRAMS

Concluding recommen- dations of the project

The lessons from the project case are that clear priorities (heat energy savings, refurbishment of public buildings, use of local renewable energy sources etc.) are of prime importance Also a strong focus should be built on more intensively caring about the energy savings in order to care for climate change issues Cooperation with experts from the energy domain is important to develop suitable policy models City membership in the Association of Sustainable Energy Municipalities—CITENERGO—facilitated the exchange of experiences and cooperation with other Slovak cities active in the energy field

CCD consistent conceptual description, CSET collaboration and scenario editing tool, DRAMS declarative rule-based agent-modelling system, KSR Kosice Self-governing Region, OCOPOMO Open Collaboration for Policy Modelling, RES renewable energy sources

374 D. Bär et al.

Table 16.6 provides insights into the metadata and conceptual particularities of this project.

16.5 Comparison and Lessons from Analysis

The five projects and cases described in Sect. 16.5 are mainly focused on renewable energy sources. Besides, the change from fossil fuels and nuclear power to renew- able energy sources is a topic, as well as the responsible handling and consumption of energy. The central aim of the projects and policy implementation cases is the advancement of the use of renewable energy sources, the simultaneous decrease of energy consumption and thereby the improvement of the overall energy efficiency. These aims are pursued on the one hand by developing concepts and strategies on a policymaking level and on the other hand by actively supporting cities and com- munities in improving their energy efficiency. Some projects clearly defined goals with dates and figures to be accomplished, like shutting down all nuclear reactors in Germany until 2022, or reducing CO2 emission by 20 % until 2020 while increasing green energy production by 20 % simultaneously (cf. Sect. 16.4.1). Other projects like OCOPOMO’s KSR case or the MODEL project developed and evaluated long- term strategies for the continuous improvement of energy efficiency and change of energy sources, which are actively carried out for interested communities and guided via frameworks for the practical application. The projects selected vary between ones that aim to pursue precise goals and projects that investigate issues and possible sce- narios and policy alternatives to solve these problems. Based on these simulations and analysis, new action plans can be elaborated to achieve formulated goals.

The comparative analysis template proves to be well suited to analyse and compare projects and cases implementing policies. It provides a quick and compact overview and the essential facts can be compared to each other in an easy way. However, it turned out that in some cases, relevant information cannot be retrieved for some element of comparison, hence the fields were left with no information.

In terms of research and practice implications, the analysis shows that nowadays there are various alternatives for environment-friendly energy production like solar, water or hydro. Unfortunately, the awareness of the benefit that these technologies offer seems to be too small so that many governments, authorities and policymakers are not convinced to foster the use of them. A reason for that is may be that these technologies are very expensive so far and the way to lower the costs and thereby make these technologies more attractive for use needs yet to be figured out. Accordingly, there is still quite a field of research and more examples of the KNOWBRIDGE cluster should be fostered.

A big step in bringing about a progress in the counteraction of climate change is to involve the consumers, i.e. the citizens, governments and the industry sector more strongly in order to create awareness about the situation of energy production and consumption as well as the contribution of certain energy technologies to climate change.

16 Analysis of Five Policy Cases in the Field of Energy Policy 375

Table 16.6 Analysis of metadata and conceptual aspects of the MODEL project

Metadata

Name MODEL: management of domains related to energy in local authorities

Duration 2007–2010

Domain Energy sector

Project type Policy implementation

Reference(s) http://www.energymodel.eu/spip.php?page=index_en (last access: 29 July 2014) http://www.energymodel.eu/IMG/pdf/List_of_MODEL_pilot_ cities_2009.12.02.pdf (last access: 29 July 2014)

Conceptual aspects

Implementing which policy

Energy sustainability policy

Users/Stakeholders 43 pilot cities from 10 new EU Member States and Croatia Association Municipal Energy Efficiency Network EcoEnergy, Bulgaria Center for Energy Efficiency (EnEffect), Bulgaria Energetski Institut HrvojePozar (EIHP), Croatia PORSENNA o.p.s., Czech Republic SocialasEkonomikasFonds, Latvia Kaunas Regional Energy Agency, Lithuania, Norway Association of Municipalities Polish Network “EnergieCités” (PNEC), Poland AsociatiaOra_eEnergieRomânia, Romania RazvojnaAgencijaSinergijad.o.o., Slovenia

Complexity Complexity is rather high due the complexity of energy resource management

Theory(s) used Not successful in retrieving relevant information

Method(s) used Process management in supporting planning, implementing and evaluating activities to improve local energy efficiency Common framework methodology (CFM) for the development, implementation and evaluation of municipal energy programmes Municipal energy programmes and annual action plans Guidelines for the preparatory phase, the development phase and the implementation/ monitoring and evaluation phase

Supportive technology frameworks and tools used

Not successful in retrieving relevant information

Project outcome Common framework methodology (CFM) implemented by participating cities in order to adopt energy programmes

376 D. Bär et al.

Table 16.6 (continued)

Conceptual aspects

Raised awareness and engagement in sustainable energy management amongst all pilot cities

Links to other projects http://ec.europa.eu/energy/intelligent/ (last access: 29 July 2014) http://www.energy-cities.eu/spip.php?page=index_en (last access: 29 July 2014)

Transferability of solutions and techniques

The common framework methodology (CFM) is adoptable and adjustable for interested cities. It provides a guideline to implement sustainable energy management

Concluding recommend It is important to convince responsible representatives of the benefits sustainable energy management can provide, since it may be difficult to realise and it may be time-consuming

CFM common framework methodology

16.6 Conclusions

Climate change and the transition to renewable energy sources has become a serious policy issue that affects all forms of life on earth. While the awareness of this situation is continuously growing, big measures are needed to counteract pollution, global warming and the resulting climate change. Policymakers and researchers, together with the industry sector and the citizens, need to develop strategies, programmes and policies that support a greener energy production and consumption.

As indicated in the EU policy package on climate change and renewables as well as in the German energy transition policy, the plan is to switch from fossil fuels and nuclear power to greener energy production, which can be realised by using renewable energy sources such as wind and water for example. There are projects thatare role models like the German nuclear phase-out or, the MODEL project or the KNOWBRIDGE project, showing that switching to renewable energy sources is possible and sustainable. Unfortunately, this development goes on rather slowly and is not accepted in many parts of the world. Therefore, there is still a great necessity to carry out the dialogue about climate change and possibilities to counteract it across the whole world. Moreover, the financial issue concerning greener energy production and consumption needs to be handled. So far, the use of renewable energy sources is very expensive and funded by taxpayers and consumers, which might also be a reason for the slow progress.

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Chapter 17 Challenges to Policy-Making in Developing Countries and the Roles of Emerging Tools, Methods and Instruments: Experiences from Saint Petersburg

Dmitrii Trutnev, Lyudmila Vidyasova and Andrei Chugunov

Abstract Informational and analytical activities, as well as forecasting for the pro- cesses of socioeconomic development, should be an important element of all levels of governmental administration.

This chapter describes the development of information-analytical systems and situational centres in Russia in chronological order. The most ambitious Russian project concerning the implementation of effective analytics in the public sector— the system “Administration”—is described in detail, including its advantages and disadvantages. The management of territorial development necessitates the develop- ment of regional information-analytical systems. The authors gave as an example an algorithm used in information analysis, used in the Saint Petersburg administration.

17.1 Introduction

Informational and analytical activities, as well as forecasting for the processes of socioeconomic development, should be an important element at all levels of govern- mental administration. The development of methods and tools to support government decision-making on the basis of the analysis of information has a long history and their use has traditionally been included as a component of national development pro- grammes, including the programme for the development of the information society in Russia, its regions and, in particular, Saint Petersburg.

This chapter presents a brief overview of the history, and the current state of the implementation of information processing techniques and practices for the purpose of public administration in the Russian Federation. The purpose of this chapter is to de- scribe the chronology of information-analytical systems use in Russia and to identify the key challenges and the developments that will be faced by the government.

D. Trutnev (�) · L. Vidyasova · A. Chugunov ITMO University, St. Petersburg, Russia e-mail: [email protected]

© Springer International Publishing Switzerland 2015 379 M. Janssen et al. (eds.), Policy Practice and Digital Science, Public Administration and Information Technology 10, DOI 10.1007/978-3-319-12784-2_17

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The chapter consists of five sections. Section 17.1 describes the development of analytical centres in the Russian Federation over time. Section 17.2 includes data about the implementation of situational administration theory in Russia. Sec- tion 17.3 consists of the information about the functions of the information system, “Administration”. Section 17.4 explains the regional aspects of the implementation of information-analytical systems. The section “Conclusions” outlines the challenges and the developments that are faced by the government.

17.2 Analytical Centres in the Russian Federation

It is believed that the first theoretical approaches and practical developments related to the implementation of socioeconomic processes information-analytical system were implemented in the early 1970s by Beer Stafford—the father of management cybernetics. Viable system model (VSM) was described in the book, Brain of the Firm (Stafford 1994). A special section in the book is devoted to the project “Cybersyn”, implemented in Chile during the Allende government. B. Stafford was invited as a research director and chief designer of the operations room.

The control programme for established system (Cyberstrider) was written by Chilean experts in collaboration with the British scientists. With the telex system, 500 enterprises were connected into the network Cybernet. All the information in real-time situational came in the centre located at the Presidential Palace “La Mon- eda” (Santiago). The system has been implemented on the mainframe IBM360, and associated peripheral equipment. The system was provided for four levels of ad- ministration: the enterprise, industry, economy and global, and it had a functioning feedback. In the logic of the system, the algorithm that determines the sequence of solutions emerging organizational problems was laid. If the problem was not resolved at the lowest level for a certain period of time, then it was automatically escalated to a higher level of decision making (to global—the level of the President).

It can be assumed that the project “Cybersyn” was the first experience of the le- gitimate use of “e-participation” methods across the state. This information system was an important element of the Allende’s political reforms. It allowed citizens to participate in shaping public policies, see the feedback and have a sense of their involvement in the processes of formation of political and economic reforms. The sub-system “Cyberfolk” provided citizens the opportunity to have real-time com- munication with groups of decision makers, thereby ensuring the participation in this process. This experiment, which can be termed as the implementation of direct democracy experiment, was conducted in urban Tome and Mejillones. Municipalities of both cities were connected with people and houses, indoor TV allowed to view information-sharing session of the Municipal Council and to participate in them. Residents were allowed to vote during the meeting by placing them in analogue devices.

The “Cybersyn” has proved itself as a very effective. For example, in 1972 only through the actions of the Situation Centre was organized food supply to Santiago

17 Challenges to Policy-Making in Developing Countries 381

during a large-scale strike of truck drivers. After the coup in 1973 and the overthrow of Allende system’s control centre, “Cybersyn” was eliminated.

At the same time in the Soviet Union, a similar plan for basic task—going devel- opment of national accounting systems and automated data processing (OGAS—the nationwide automated system—more detail below) was implemented. It was a sys- tem focused on automated management of the economy of the USSR. The system was based on the principles of cybernetics and included computer network linking the data collection centres located in all regions of the country. The magnitude of these two systems (even in the number of business entities), of course, is difficult to compare, but OGAS did not aim to provide an interactive cooperation between authorities and the population.

In 1965, in the USSR, the transition from territorial economic management system in the industry took place. The need for a combination of sectoral and territorial principles set challenges to the authorities responsible for planning and ensuring the supply of industrial enterprises and organizations of various products. Complex tasks associated with the functions of operational planning and management of the current material flows between the entities of industrial activity through the territorial system were successfully carried out by OGAS. The establishment of production and economic ties between enterprises was one of the main tasks for OGAS. It allowed to form an optimal structure for marco technology production process throughout the USSR and exercised operational control over its implementation.

Tasks associated with the forecasting and management of the socioeconomic de- velopment of the country (region, city, industry, enterprise, etc.) with the use of information technologies were already established in the Soviet Union in the 1970– 1980s. The concept of the National Automated System (NAS) was designed under the guidance of the well-known Soviet researcher and expert on the implementation of sophisticated computer systems, Glushkov (1987a). NAS was implemented as a distributed hierarchically organized (vertically and horizontally integrated) sys- tem of data centres that provide access to databases through various communication channels (Kiriyenko 2012). The components of this system included major insti- tutional entities, such as the State Automated System of Scientific and Technical Information (SASSTI), uniting branches of institutes of scientific and technical in- formation, and regional centres of scientific and technical information (CSTI). A telecommunications infrastructure, uniting institutions of the USSR Academy of Sciences (“Academset”) and other programmes dealing with administration tasks, was created and developed in the 1980s. In particular, at that time, automated sys- tems of information processing for policy makers (ASIPPM) established within the Union, as well as the Republican automated administration systems (RAAS), were actively developed. All these works were conducted within the NAS concept and were technically implemented in systems based on the mainframes of the EC and EM series (Russian names of IBM360 and PDP11 analogues). The system worked successfully and its results were widely used to control the USSR’s planned econ- omy, but its operations came to a halt in the early 1990s during the break-up of the Soviet Union’s administrative system and the transition to a market economy. In the same period, due to the collapse of the USSR, many international creative teams

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involved in the creation and development of the methodological and mathematical support for these systems also collapsed. However, the theories and practices of the development and operation of large analytical information systems that had been de- veloped formed the basis for many regional and municipal informatization projects implemented in the 1990s and 2000s (Mikheyev 2001).

It should also be noted that in the 1970s and 1980s, the Soviet Union built a mul- tilevel hierarchic system for the collection and processing of data on various aspects of the socioeconomic development of the country. For example, the total amount of economic data was 120–170 billion units a year (and only 7 % of these were national statistics data). In the USSR State Planning Committee, the total amount of indi- cators reached 2 million in the 1970s (Maiminas 1971). These data and indicators were used in economic administration systems and the organization of planning not only at the union, sectoral and regional levels but also in the design of international programmes by the Council for Mutual Economic Assistance (COMECON—a coor- dinating inter-governmental body of the socialist bloc). Of course, the main objective of the indicator systems was to provide information support for directive planning in the Soviet Union, however, in the 1970 and 1980s scientific research was also carried out by focussing on the creation of a system of integral and functional lifestyle social indicators, with a view to forecasting social processes (Afanasiev 1975).

The history of the establishment of most of the think tanks in the public adminis- tration started in the mid-1990s. The first structures which served as the basis for the formation of the institutional and personnel capacity of the centres, as a part of the system of providing analytical support to the Russian President, were created in 1990 (Timofeyeva 2004). From the second half of the 1980s to the first part of 1990s, the necessity of basing administration on planning, and not of a historical and directive nature, but instead involving forecasting was quite acute. In the spring of 1990, study groups were formed to provide advice to the government on economic issues by peo- ple close to Boris Yeltsin (at that time he was the chairman of the State Committee for Cconstruction and Architecture of the USSR). Sometime later (in the summer of 1990), Boris Yeltsin (who by that time had become the chairman of the Supreme Soviet of the Russian Soviet Federative Socialist Republic (RSFSR)) formed a po- litical advisory council (which later came to be known as the Supreme Coordination and Consultation Council), which analysed political information, developed plans to counter the Union Centre and forged ties with the regions.

These analytical groups became a part of the Russian President’s administration in August 1991. The Information and Analytical Centre, operated as a part of the Russian President’s administration from March 1992 to February 1993, was transformed into various structures from February 1993 to April 1994: the Analytical Centre on General Policy and the Analytical Centre on Social and Economic Policy (Handbook of Analytical Centers 1994). This was followed by several more transformations from 2000 to 2004, whereby these structures were finally transformed into the expert department and the department for press services and information, which provide up-to-date informational and analytical functions to the President’s administration.

17 Challenges to Policy-Making in Developing Countries 383

Among the expert and analytical groups, the Analytical Centre of the Government of the Russian Federation has the longest history. It was established in December 2005 and became the successor of the previous governmental centres of expertise: the Working Centre of Economic Reforms and the Centre on Prevailing Economic Situation and Forecasting which, in its turn, was formed on the basis of the Main Computing Centre of the USSR State Planning Committee (operated from 1959 to 1991).

The system providing analytical support to the government authorities also in- cludes informational and analytical structures of the legislative bodies: the Federation Council and the State Duma of the Federal Assembly of the Russian Federation.

The activities, which may be attributed to this type of task, are also carried out at the municipal level. Municipal information and analysis centres focus on the tasks of managing the development of territories and, in some cases, also carry out projects related to the forecasting of some areas of such developments.

In addition to the analytical centres of the government’s supreme bodies, in- dependent analytical structures which can be roughly divided into two groups, analytical centres specializing in forecasting of electoral outcomes and other types of forecasting, are also engaged in political forecasting.

Currently, in the sphere of state and municipal administration, the tasks associated with the provision of informational and analytical support to the decision-making process are often associated with the creation and use of situational centres, which have become quite popular in recent years.

17.3 Situational Centres and the Development of the Theory of Situational Administration

Obvious successes in the fields of the computer processing of texts of natural language, high-quality functions for searching documents, tracking dynamic man- agement objects, solving problems of pattern recognition, simulation modelling, statistical data processing and solving transport tasks were evident in Russia in the late 1980s. Developers increasingly focused on studying the adaptive properties of information systems using simulations of human mental activity during discourse and decision making. (Raykov 2009) notes that in the early 1990s, in Russia, “seeds of the theory of situational administration fell on fertile corporate soil and gave abundant shoots in the form of systems of strategic management, information technologies for resource planning, re-engineering, situational centers”. In the mid-1990s, the business actively introduced intellectual information technologies of analytical pro- cessing of large volumes of information and decision support technologies which came from abroad (Novikova and Demidov 2012).

The first prototype for a situational centre in the Soviet Union was the operational headquarters established to mitigate the Chernobyl disaster in 1986. The situational centre of the Ministry of Emergency Situations was created on the basis of so- lutions and techniques of information collection and processing developed in this

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centre. One more situational centre, the Security Council for the Russian President, was created in 1994, and the Russian President’s Situational Centre was opened in February 1996. The system of situational centres was created in all representative offices of the president in the federal districts and information sharing between the federal and regional levels of governance was organized in the 2000s. Some regions created situational centres; however, not all of them have a well-developed system of informational and analytical support for decision-making processes and are often used for video conferencing with both federal agencies and, in some regions, with local self-administration authorities.

In 2009, the Russian President approved, with Decree No. 536 of 12.05.2009, “The Basics of Strategic Planning in the Russian Federation” providing for the es- tablishment in the Russian state authorities of a distributed system of situational centres interacting under a single set of regulations.

An important area in the development of the functionality of the situational centres is the geographic information systems (GIS) that provide the possibility for visu- alizing various information, its analysis (understanding and highlighting the main factors, causes and possible consequences) and forecasts drawn up on the basis of the completed analyses, and subsequent developments with strategic decision planning (Novikova and Demidov 2012).

One of the major problems which services, which provide informational and analytical support to the decision-making process, face is the effect of “big data”: They are often so big that they are difficult to handle. Experts estimate that up to 90 % of the data stored in modern information systems are not used. It is no coincidence that there is a demand for data scientists who establish relationships and transform data into useful information; the ability of modern systems to process both structured data (mainly from relational database management systems) and semi-structured data (text, audio and video) is quite important. Decision makers at any time should be able to request information about the current state of affairs: interactively or in the form of a report. Consequently, the situational centre is transformed into an analytical one, which operates on a permanent basis. In addition, it is not so important where information systems are stored, in the data centre or in the cloud. Thus, the effectiveness of decisions made largely depends on the availability of analytical services in the situational centre. However, its creation, the training of its personnel, methodological support to activities and the acquisition of informational and analytical systems would cost much more than a well-equipped conference room (Situational Centers at the Service of the State 2012).

17.4 State Automated System “Administration”

The state automated system “Administration” (Site SAS “Administration” 2003) is positioned as one of the most ambitious projects to implement analytical systems in the Russian public sector.

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SAS “Administration” is a unified distributed state information system for col- lecting, recording, processing and analysing data contained in state and municipal information resources, the official state statistics data and any other information needed to support administrative decisions in the sphere of public administration.

The SAS “Administration” structure includes classic business intelligence tools and data discovery modules (online analytical processing (OLAP), scheduled report- ing), and an advanced analytics unit: modelling, forecasting, time series analysis and score cards. Units at the technological level include a data store designer, units to retrieve data from external sources (extract, transform, load, ETL), records of norma- tive and reference information, an application development environment (software development kit, SDK), units dealing with business graphics, metadata management modules, administration and information security, an application server and web services.

In 2009 and 2010, the Federal Target Programme “Electronic Russia” allocated 550 million rubles for the development of SAS “Administration”; in 2011, 75 mil- lion rubles were spent on updating the system, and in 2012 about 70 million rubles more. Despite quite substantial investments, the project is far from complete, and the basic problems lie rather at the institutional level: who will fill the system with data and how reliable will they be? Sceptics have also questioned whether this decision will be claimed by functional customers, which are the first persons of the govern- ment. CNews Analytics (Analytics in Government Structures 2013) says that this is a common problem for all analytical systems in the public sector: they are created according to the interests of the senior management and should be a tool for decision making. However, to do this, the user (i.e. the decision makers) should have ap- propriate professional skills and the profession of an analyst is objectively different from the profession of a manager. However, all analysis reports have one substantial drawback: They provide information about the past that has already happened, while managers have to make decisions about the future.

The aims and objectives of SAS “Administration” are defined in the Decree of the government of the Russian Federation dated December 25, 2009, No. 1088 (SAS Administration 2003). Its objectives include:

1. The provision of informational and analytical support to the decision-making processes of the supreme bodies of state power on issues related to public administration, as well as the planning of the activities of these bodies.

2. The monitoring, analysis and control of the execution of decisions made by these bodies, the implementation of the main activities of the government of the Russian Federation, the implementation of priority national projects, the implementation of measures to rehabilitate the Russian economy, processes occurring in the real sector of the economy, finance and banking and social spheres, the social and eco- nomic development of the regions of the Russian Federation and the effectiveness of the regional state authorities.

SAS “Administration” is a set of information systems and information resources implemented as a three-level structure:

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1. The first level (central information system): a set of information systems which collect, process, store and disseminate information which comes from the second and third levels of SAS “Administration”.

2. The second level (departmental): information systems of the federal bodies of the executive power which are a part of SAS “Administration”, and whose in- formation resources are designed to be used in making management decisions in the sphere of public administration, and the information resources of other information systems, which need to be integrated into SAS “Administration” in accordance with the functional requirements given to it.

3. The third level (regional): information resources of information system of bodies of state power of the regions of the Russian Federation, which need to be integrated into SAS “Administration” in accordance with the functional requirements that it has been set.

SAS “Administration” provides the following functions:

1. Collection of data for administrative decision making in the public administra- tion from departmental and regional information systems and other information systems, which need to be integrated into SAS “Administration” in accordance with the functional requirements that it has been set.

2. Systematization and analysis: (a) Information about the level of the socioeconomic development of the Russian

Federation and its regions, including comparisons with world statistics. (b) Information about the efficiency of the activities of the federal bodies of state

power and the bodies of state power of the regions of the Russian Federation. (c) Information about the implementation of programmes, projects and activities

implemented at the expense of the federal budget. (d) Information about budgetary forecasts and the use of the federal budget,

including information about the use of cash of the federal budget and fiscal reports on the main spending units of the federal budget.

(e) State official statistical information collected in accordance with the federal plan of statistical work.

(f) Cartographic information and related data, about regions and resources in the Russian Federation.

(g) Reference data in departmental information systems. (h) Other information which users of SAS “Administration” need.

It is no exaggeration to call SAS “Administration” the most controversial information technology (IT) system ever created in Russia. It is based on a simple and nice idea, to monitor from Moscow indicators of the activities of officials all over the country, and has faced quite a number of problems. The system is now in its 8th year, yet still there have been no visible results.

Speaking about SAS “Administration”, in November 2010 at the CNews Forum, Konstantin Noskov, Director of the government IT department, stated that “so far, the work has been at the level of departmental systems or such topical systems as the Olympics project, priority national projects, and we have failed to reach the level of

17 Challenges to Policy-Making in Developing Countries 387

inter-departmental integration”. Rostelecom launched gas-u.ru portal in the spring of 2011. However, there was not much information on the portal: Only five federal agencies provided data from their information systems to SAS “Administration”. An expanded meeting of the Government Commission in April 2012 represented a milestone event, which brought together more than 100 officials. The event was chaired by Aleksey Polyakov, head of the government IT department. In the minutes of the meeting, there were a number of interesting points:

1. The federal authorities were advised to immediately appoint persons responsible for SAS “Administration” at the level of deputy heads and submit to the Ministry of Economic Development technological maps of inter-departmental interactions (TMIDI, describing the data which departments should provide to the system).

2. Some departments, among which were the developers of SAS “Administration”, the Ministry of Communications, the Federal Treasury and the Federal Guard Service, said they had no need for the information from the system.

3. The commission pointed out that it was impossible to receive information from other authorities bypassing SAS “Administration”.

However, all activity waned in May. A new government appeared in Russia and the system was forgotten for almost half a year.

A new concept of SAS “Administration” 2012 summarized the results of the previous period. In particular, it was noted that not all of the declared plans had been implemented. The objectives of SAS “Administration” were achieved, in that a limited list of the functional tasks of the supreme bodies of power was ensured. Prototypes of the information systems to support the activities of the prime minister and the head of the government office required a deeper individual development. A universal tool for the collection and analysis of data in the area of public adminis- tration to support decision making, and to support the monitoring and control of the making of decisions, etc. was not designed.

According to the authors of the document, the creation of a fully functional system was hampered by a lack of universally approved data formats, standards and proto- cols, unified normative and technical requirements for public information systems, regulations on inter-departmental documents and information sharing, established deadlines, mechanisms and the responsibility for the provision of data of the executive bodies to the “Administration” system.

Thus, at the end of 2012, information and analytical support of the activities of state bodies still had “a number of systemic weaknesses and pending issues: the in- formation flow between federal and regional authorities was repeatedly duplicated, data updates and degree of detail were low, which, in its turn, made it difficult to apply modern methods of data processing and analysis, project management”. The variety of technologies for collecting, processing and storing data by various gov- ernment agencies significantly increased barriers to inter-departmental information exchanges, and the exchange between the authorities themselves existed only on paper.

The authors divided the concept of the further development of the system into three phases. In 2012, a system for data collection for providers that do not have the

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technical ability to provide them (primarily, in regions with low levels of information its necessary to provide data form via Internet browser) was to be created, the pro- cedures for maintenance of a unified registry database were to be regulated, and an exchange mechanism via SAS “Administration” using inter-departmental electronic interaction systems (SIDEIS), etc. was to be established.

In 2013, an expansion of the composition of information resources that interact with the system and the composition of its users was planned, and the automation of data uploading from SAS “Administration” into Contour sub-system was planned, designed for use by senior persons in the state apparatus. It was created by the federal guard system (FGS).

Finally, in 2014, the connection of non-governmental sources of information to SAS “Administration” was planned to ensure the possibility of embedding third- party developer software into the system portal. Upon completion of these phases, the authors promised to create a register of state databases, increase the share of state systems integrated into SAS “Administration” to at least 70 % and to decrease by the same number the duplication of information flows. The authors of the concept do not promise to connect all the regions to the system, only “to provide for the possibility of access”.

Experts, with whom Journal CNews discussed the prospects of SAS “Administra- tion”, are largely sceptical. “The functional customer of this resource is unknown”, says an IT head of one of the federal agencies. “It was planned to take some data from agencies and put them up onto some panels for the first persons. But, do they need it? The first persons do not have the time to use these panels. In addition, it is not possible to determine the accuracy of the data as there is no mechanism of verification. Regions may submit any figures that are of benefit to them, and every- one will be sure, that’s true”. “Before you upload data to SAS “Administration” it is necessary to establish order in source information systems”, adds another source of CNews. “Regions and federal agencies with high-quality databases can be counted on one hand”. (Why SAS “Administration” did not take off 2013).

17.5 Other Policy-Making Tools and Techniques

All of the above apply to the forms of tools designed to support the administrative decisions of federal authorities, the creation of which was financed from the national budget. Solutions, centrally generated up to the 1990s, were designated to carry out the reporting and planning tasks of practically all levels of state, municipal and district administration. After the collapse of the Soviet Union, in the process of the transition to a market economy, and the provision to municipalities of all levels of some economic freedom and administration powers, the need to implement and use tools and techniques to enhance the effectiveness of administration solutions arose but there was a failure to develop and actively create and use these. In the 2000s, Russia began the systematic construction of the “vertical power structure”, resulting in the practical loss of freedom of choice in political and economic decision making

17 Challenges to Policy-Making in Developing Countries 389

Fig. 17.1 Number of crimes

on the part of the regional and local authorities. For this reason, one may count, among 83 constituent entities of the Federation and more than 23,000 municipalities of all levels, only a few dozen examples of analytical IT tools used for policy-making.

One of the examples is the use of simulation tools in drug trafficking to generate programmes to counter crime in this area.

In relation to the task of evaluating processes such as drug addiction or drug trafficking, it is important to understand that the absolute values of the indicators of departmental statistics rarely reflect the process itself. Thus, the number of recorded crimes characterizes rather the registration and response system than the actual crime rate. Therefore, an important task is to model and estimate the value of the so-called latency of crimes, i.e. the number of hidden and unregistered crimes. This allows us to come closer to a real assessment of the situation in a region and to identify the factors which affect changes in crime rates.

For the purpose of assessing the actual number of drug users, a mathematical model was created, taking into account the interdependence of such indicators as information concerning seizures of illicit trafficking, registered cases of drug ad- diction, opinion polls data and the intensity of the debate on drug-related topics in social networks. As a result, estimates were obtained which show that the actual number of persons taking drugs at least once in their lifetime exceeds the registered number by 50 times. This discrepancy describes the process as highly latent, which is an obstacle to obtaining a high accuracy of modelling and forecasting when using the above-mentioned sources of information, therefore, measures were proposed to reduce latency, for example, compulsory testing for drug traces in pupils, students, drivers and public employees. However, these measures have not been taken, pos- sibly because of fears that the reported cases of drug consumption are indirectly punishable under the criminal code and the very fact of such a discovery may lead to negative consequences for the system of identification and apprehension.

Even with the low accuracy of the model, the forecast of the development of the level of crime based on retrospective data provides the possibility of identifying trends and offers explanations of changes in dynamics (Fig. 17.1). For example,

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Reflection of the problem situation in reports of the response system, in the Internet (including the

blogosphere and social media)

PROBLEM SITUATION IN THE FIELD OF

PROLIFERATION OF DRUG ADDICTION

Presentation of the study paper (regular

or extraordinary)

Monitoring of problem situation

Governor of Saint Petersburg

Government

Modeling and forecasting

The Anti-Drug Commission

of Saint Petersburg

Response system

The State Program “Combating Proliferation of Drugs” (2013-2016)

Policy

Federal structures: ▪ The Federal Service of the Russian

Federation for Control Over the Circulation of Narcotics

▪ The Ministry of Internal Affairs, the Federal Security Service

District structures: ▪ Education ▪ Healthcare ▪ Other

Impact (influence) on the situation (of the event)

St. Petersburg Informational and Analytical Center

Fig. 17.2 Organizational tools for decision making and the response system according to results of informational and analytical activities on topics related to combating spread of drug addiction in Saint Petersburg

increases in recorded crime until 2011 were caused by increased migration from Central Asia and the reduction is a consequence of a series of municipal anti-drug programmes implemented in Saint Petersburg. The forecast predicting a growth in crime in 2013–2014 was due to a delay in the implementation of further anti-drug programmes.

The place of modelling and forecasting in the overall system of organizational tools to combat the spread of drug addiction in Saint Petersburg is shown in Fig. 17.2.

This example is one of the few successful examples of the practical application of the tools for modelling social or economic processes used for the purpose of policy formation and operational decision making.

17 Challenges to Policy-Making in Developing Countries 391

17.6 Conclusions

Analysis of the literature and projects’ performance in the field of information- analytical systems application in Russian for the improvement of socioeconomic processes leads to the following conclusions:

1. Systems of situational centres and federal vertically oriented systems (“Adminis- tration”) are actively developing in the last 5 years, but they are not integrated into decision-making procedures. These systems are used in crisis situations and for “brainstorming” in the elaboration and adoption of government programmes (or report generation), but their abilities are still clearly underestimate by decision makers.

2. The existing resources and capabilities of situational centres are not fully lever- aging. According to expert opinion, 90% of the existing situation centers are used only as a space for video conferencing. Only occasionally it used as a multidimen- sional view of data and multivariate analysis, as well as methods of situational modelling and forecasting.

3. There are serious problems with the financing for research (related to the de- velopment of situational forecasting and modeling), rarely to solving external experts. Meanwhile, in the USA, a separate budget line is allocated to finance the development of situational centres. Special federal contract system for the man- agement of intellectual property used in the management decisions also operates separately.

As a recommendation, which can alleviate these problems and gradually increase the effectiveness of the functioning of information and analytical systems in government in the Russian Federation, the experts include the following:

1. To link the problem of information-analytical systems in government with the priorities of the state policy to improve the functioning of the state and municipal government.

2. More active involvement in the development associated with situational modeling and prediction, network expert community building.

3. The inclusion of information systems of this class in the list of public information resources, denoting requirements as to the actual system, and to a set of informa- tion sources and operational updates related to this activity with the development of open government data (Open Gov Data).

4. Maintaining up-to-date bank of simulation results and ensuring the coordination of research in the field of simulation, in order to improve linkages between the models for the authorities, industries and regions (the Russian Federation, the industry, the Federal District, the subject of the Federation, the municipality).

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Chapter 18 Sustainable Urban Development, Governance and Policy: A Comparative Overview of EU Policies and Projects

Diego Navarra and Simona Milio

Abstract This chapter will provide a comparative overview of existing policies and projects to achieve energy efficiency in the European Union (EU) region delivering a concise overview of the contribution of e-government to energy efficiency in view of climate change. A system dynamics (SD) model is also presented to show how good urban policy and governance can support extant as well as future information and communications technology (ICT) projects in order to reduce energy usage, rehabil- itate the housing stock and promote sustainable urban development. An additional contribution of the chapter is to show the role and significance of the cadastre to sustainable urban development e-government projects and the key characteristics of future policy and projects towards the European 2050 Agenda.

18.1 Introduction

What are the key characteristics of successful European initiatives in sustainable ur- ban governance? And how can e-government projects encourage sustainable urban development in view of climate change? This chapter will identify the multidis- ciplinary dimensions of e-government projects in energy efficiency and present representative cases and experiences from different areas of the European Union (EU) in order to identify the key characteristics of future policy (including fund- ing policy) that should be considered in practical developments and sustainability projects linked to the European 2050 policy agenda in different areas of the highly diverse European region. We find that, for the vast majority, existing and previous projects taking place in the EU (see Appendix 1) have been primarily centred around what we might consider as monodisciplinary approaches (i.e. approaches used from

D. Navarra (�) Studio Navarra, 25 Cleveland Gardens, London W2 6DE, UK e-mail: [email protected]

S. Milio London School of Economics, Houghton Street, London WC2A 2AE, UK e-mail: [email protected]

© Springer International Publishing Switzerland 2015 393 M. Janssen et al. (eds.), Policy Practice and Digital Science, Public Administration and Information Technology 10, DOI 10.1007/978-3-319-12784-2_18

394 D. Navarra and S. Milio

a scientific discipline or subdisciplines without consulting any other discipline), em- phasizing IT solutions as tools to reduce energy consumption, or information and communications technology (ICT) systems and energy efficiency management sys- tems in buildings to monitor and transmit consumption data, rarely integrated or interoperable. At the same time energy and ICT systems (such as in energy trad- ing and performance management) have become increasingly interdependent and complex.

Greenhouse gases (GHGs) emissions (which are a major determinant of climate change) typically come from energy supply, transport and industry in urban areas (Parry and IPPC 2007). Urban and industrial energy use in particular accounts for 80 % of all GHG emission in the EU and it is at the root of climate change and most air pollution. ‘About 30–40 % of the total energy consumption in western countries is assigned to buildings. About 50 % of these refer to the energy consumption for indoor air conditioning (heating and cooling)’ (Pulselli et al. 2009). Regarding the effects of climate change on the built environment Roberts (2008) clarifies that build- ings play an important role in both adaptation and mitigation. Therefore, we argue that sustainable urban development, governance and policies informed by interdis- ciplinary approaches addressing future integrated energy monitoring and production needs can greatly contribute not only to improvements in energy efficiency but also facilitate mitigation and adaptation of urban areas to climate change.

18.2 Literature Review on EU Energy Security and ICT Policy

The point of departure of the EU’s (European Commission 2007) energy policy is threefold: combating climate change, limiting the EU’s external vulnerability to imported hydrocarbons, and promoting growth and jobs, thereby providing secure and affordable energy to consumers. The main focus of the EU’s policy is to move towards a single global regime and the mainstreaming of climate into other policies, which will be assigned 20 % of the entire 2014–2020 EU budget. The focus at the urban level is to produce the greatest results in energy efficiency integrating three sectors:

1. Urban energy production and use, by supporting policies aimed at establishing standards for increasing the efficiency of existing buildings, supporting new en- ergy efficient developments and conservation plans so as to minimize the use and production of fossil fuel-based electricity generation (OECD 1995).

2. Urban transport and mobility, by strengthening and implementing green transport policies aimed at increasing the share of cleaner transport options, such as public transportation for urban travel, zero-emissions vehicles (such as bicycles) and car sharing schemes (European Commission 1996).

3. Urban ICT, potentially affecting both of the sectors above and also the over- all potential contribution to the reduction of urban CO2 emissions in electricity production, use as well as in the construction of a dedicated city-wide ICT infrastructure for the evaluation of energy efficiency.

18 Sustainable Urban Development, Governance and Policy 395

The EU has also developed a methodology to evaluate energy efficiency, relying on Internet-based ICT: the eeMeasure. The methodology is based on experimental projects carried out in public buildings and social dwellings. eeMeasure provides a first example of a European e-government policy aiming to increase energy efficiency using a common data collection approach and a single software system to collect and accommodate energy savings data across the pilot projects in both residential as well as nonresidential buildings. According to the eeMeasure website (eeMeasure 2014b) there are currently two ICT methodologies to measure energy efficiency: the residential methodology and the nonresidential methodology.

Both methodologies are based on the International Performance Measurement and Verification Protocol, a framework used to determine water and energy costs associated with energy conservation measures (IPMVP 2002). eeMeasure method- ologies are developed from the experience of current and previous ICT projects which include approximately 10,000 social dwellings and 30 public buildings (such as hos- pitals and schools). The residential methodology is applicable only to dwellings and generally assumes a monthly measurement period. The main objectives of the eeMeasure methodologies are to: allow EU and related project parties to collect data in a centralized database, to produce better quantitative analyses of the energy sav- ing potential of ICT solutions in residential and nonresidential buildings, to facilitate the evaluation of behavioural changes occurring due to ICT solutions, and to better public awareness about energy efficiency and ICT solutions (eeMeasure 2014a).

It is possible to distinguish between three main areas of data collection to measure energy efficiency in the pilot projects. Data collected to measure energy efficiency statistically (i.e. estimation, calculation, parameters, demand response and avoided CO2 emissions) data collected to measure and quantify impact assessment (energy savings vs. socioeconomic status, energy savings vs. nationality, energy savings vs. cost of energy, physical and mental perception of comfort, perceived usabil- ity/usefulness of ICT solution) and finally qualitative data collected to understand behaviour: such as changes in energy use and habits. Reinforcing factors are those consequences of actions that give individuals positive or negative feedback for contin- uing their behaviour. These include information about the impacts of past behaviour (e.g. lower energy bill), feedback of peers, advice, and feedback by powerful actors. Enabling factors are the external constraints on behaviour. These factors allow new behaviour to be realized.

eeMeasure also collects data with respect to: (a) socio-demographic characteris- tics of tenants, (b) energy consumption behaviour, (c) ecological awareness: attitudes and knowledge, (d) user acceptance concerning consumption feedback services, (e) interest in the service and reasons for non-usage of passive users. The above are con- sidered together with behaviour and motivation influencing factors. These factors are awareness, knowledge, social influence, attitude, perceived capabilities and inten- tion. For people to intentionally change their energy behaviour, they must become aware of their energy use, pay notice to it, and be informed about the consequences. They must then be motivated to use the available information and instruments to control their energy use (International Energy Agency 2008; European Commission 2005; Hildyard 2011; Social Market Foundation 2003; United Nations 2004; World Bank 2013).