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Journal ArticleDOI

Energieeffizienznetzwerke – beschleunigte Emissionsminderungen in der mittelständischen Wirtschaft

11 Mar 2010-Vol. 34, Iss: 1, pp 21-28
TL;DR: In this paper, a Netzwerk-Managementsystem erlaubt einen Mindeststandard zum Aufbau und Betrieb derartiger Netzwerke, regelmasigen moderierten Treffen der Energiebeauftragten zum Erfahrungsaustausch sowie einem jahrliche monitoring uberwindet viele dieser Hemmnisse and fuhrt zu einer Verdopplung des energietechnischen Fortschritt
Abstract: Die Verminderung der energiebedingten CO2-Emissionen in der mittelstandischen Wirtschaft durch effizientere Nutzung von Energie ist eine der rentabelsten Optionen. Dennoch werden diese Chancen wegen vielfaltiger Hemmnisse und Marktversagen kaum realisiert. Hierbei spielen hohe Transaktionskosten und Entscheidungsroutinen bei Investitionen und beim Einkauf der Betriebe eine erhebliche Rolle. Ein in der Schweiz entwickeltes Netzwerkkonzept mit Eingangsberatung jedes teilnehmenden Betriebes, Zielsetzungen fur das gesamte Netzwerk, regelmasigen moderierten Treffen der Energiebeauftragten zum Erfahrungsaustausch sowie einem jahrlichem Monitoring uberwindet viele dieser Hemmnisse und fuhrt zu einer Verdopplung des energietechnischen Fortschrittes relativ zum Effizienzfortschritt der Industrie insgesamt. Dieses Netzwerkkonzept kann weitestgehend von der Wirtschaft selbst durchgefuhrt werden. Die jahrliche durchschnittliche Energiekostenersparnis ist rd. 100.000 € je Betrieb und Jahr und die CO2-Emissionsminderung rd. 500 t CO2. Bei einem Gesamtpotential von rd. 700 Netzwerken waren fur 2020 Emissionsminderungen bis zu 10 Mio. t CO2 moglich. Ein Netzwerk-Managementsystem erlaubt einen Mindeststandard zum Aufbau und Betrieb derartiger Netzwerke fur Beratende Ingenieure und Moderatoren.

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Citations
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Journal ArticleDOI
TL;DR: LEEN can be indicated as a policy instrument enabling informed decisions on efficiency measures and supporting their implementation and tailoring the programme to different target groups and aiming at dismantling other barriers directly in addition to tackling information deficits could be undertaken to improve the process.

24 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the factors that contribute to the success of EH networks by drawing on unique data from two pilot projects involving 34 energy efficiency networks in Germany and found support for the first, the third, and the fourth explanations, i.e., the audits make profitable potentials visible and networks function as a training course to increase knowledge.
Abstract: Energy efficiency networks have received increasing attention over the last few years, not only from national governments (Austria, China, Germany, Sweden, and Switzerland) but also from utilities, consulting engineers, chambers of commerce, and city councils. This paper examines the factors that contribute to the success of such networks by drawing on unique data from two pilot projects involving 34 energy efficiency networks in Germany. The objective is to explain why the companies participating in such networks are much faster at reducing their energy costs than the average in similar businesses. Possible explanations for the success of energy efficiency networks include the following: (1) energy audits make profitable potentials visible; (2) the joint network targets for efficiency and emissions increase the motivation of energy managers, decision-makers, and other staff members; (3) the meetings and site visits of the network participants act like an intensive training course to increase the knowledge of efficient solutions, change decision routines, and lead to trust among the participants; and (4) network participation reduces transaction costs. In our data, we find support for the first, the third, and the fourth explanations, i.e. the audits make profitable potentials visible and networks function as a training course to increase knowledge. And, from the point of view of participants, transaction costs are reduced. The impact of network goals, on the other hand, appears to have both up- and downsides. We conclude that there is the need for further research in order to capture these mechanisms in more detail.

10 citations

Journal ArticleDOI
TL;DR: In this article, the authors analyzed monitoring data of 263 enterprises of the Learning Energy Efficiency Networks LEEN in Germany and found that financial barriers are most prevalent, but there was no general correlation with company size, while financial restrictions are not necessarily caused by a lack of money, but also by risk aversion or unlikely payback periods.
Abstract: The improvement of energy efficiency in industrial companies plays a crucial role for the energy transition. Although significant economic potentials have been identified, the concerned actors are still struggling to realize them fully. To support the implementation of energy efficiency measures by passing policies, a deeper understanding of the barriers affecting different kinds of companies is necessary to better match the options to their needs and requirements. This paper considers companies’ characteristics and barriers to draw conclusions on energy efficiency policies and specific recommendations on energy efficiency measures. It recommends compromises for policies between high administrative efforts to design individual solutions for companies and too generic approaches, which are not tackling the specific barriers and companies’ characteristics. Our analysis assesses monitoring data of 263 enterprises of the Learning Energy Efficiency Networks LEEN in Germany. The LEEN support energy audits, company networking and assesses implemented energy efficiency measures. Lack of information combined with unfavourable reasoning in decision-making impedes the adoption of profitable measures. Thus, financial policy instruments should aim at promoting long-term decision-making. Audits turned out to be an effective information tool and are more common in LEs than in SMEs. Accordingly, the number of implemented measures and the choice of specific measures relate to company size. Regarding barriers to energy efficiency measures, we found financial barriers most prevalent, but there was no general correlation with company size. Moreover, financial restrictions are not necessarily caused by a lack of money, but also by risk aversion or unlikely payback periods. LEs are stronger affected by motivational barriers, especially if the expected organizational effort is high. Reducing transaction costs can increase the willingness to invest greater efforts in energy efficiency measures.

8 citations


Cites background from "Energieeffizienznetzwerke – beschle..."

  • ...A large share of companies (about 85%; Schröter et al. 2009) base decisions on short payback rates and therefore often reject profitable measures that would have been adopted if the internal rate of return had been taken as the decision criterion (Jochem et al. 2010)....

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Posted Content
TL;DR: In this paper, the authors show that less than half of the energy savings credited to the networks are additional, implying that more than 2.5 million tonnes of CO2 counted towards national energy efficiency goals would have to be compensated by additional policies.
Abstract: In energy efficiency networks, groups of firms exchange experiences on energy conservation in regular meetings over several years. The companies implement energy efficiency measures in order to reach commonly agreed energy savings and CO2 reduction goals. Existing evaluations of such voluntary regional networks claim that participants improved energy efficiency at twice the speed of the industry average. Based on comprehensive data from the German manufacturing census, this paper shows that this claim is overstated: Likely less than half of energy savings credited to the networks are additional, implying that more than 2.5 million tonnes of CO2 counted towards national energy efficiency goals would have to be compensated by additional policies. However, although statistically insignificant, estimates of the network effects are still substantial, pointing to 1,400 MWh of energy savings and 600 tonnes of CO2 reduction for the average participant. These estimates suggest a high cost-effectiveness of energy efficiency networks compared to similar energy efficiency policies, even if actual energy savings are likely lower than previous research suggested.

3 citations


Cites background or methods from "Energieeffizienznetzwerke – beschle..."

  • ...Energy efficiency networks typically focus on energy savings from cross-cutting technologies such as process heat and process cooling, ventilation or lighting, since these are used in a wide range of industrial sectors (Jochem et al. 2010; Köwener et al. 2014; Rohde et al. 2015)....

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  • ...2 In energy efficiency network types not using the LEEN standard, a participation with annual energy costs above EUR 150,000 is also possible (Jochem et al. 2010)....

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  • ...Moreover, EENs may influence energy conservation through socio-psychological mechanisms (Stern 1992; Jochem et al. 2010): The participation of company representatives in a group structure like an energy efficiency network can lead to a higher intrinsic motivation for participants (Köwener et al.…...

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  • ...2 energy savings compared to a baseline energy consumption) by around two percent each year, or double the speed of the industrial sector as a whole (Jochem et al. 2010; Köwener et al. 2014; Rohde et al. 2015)....

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  • ...Since network participants can trust each other due to the absence of a commercial interest among network peers, this sharing of experiences may be particularly valuable (Jochem et al. 2010; Köwener et al. 2014)....

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01 Dec 2012
TL;DR: Off4Firms as mentioned in this paper is an applied research and innovation project aiming at reducing greenhouse gas emissions and energy consumption of private households, where firms can evaluate measures aiming at reductions in energy use and CO2 emissions in their employees' private lives.
Abstract: .................................................................................................................................................................. 5 Introduction .................................................................................................................................................... 6 1. Evaluation criteria for reduction activities ...................................................................................................... 7 2. 2.1. Technical reduction potential ................................................................................................................ 8 2.2. Cost efficiency of the reduction activities ........................................................................................... 12 2.3. Verifiability of the CO2 emissions and energy consumption reductions ............................................. 13 2.4. Implementation barriers ..................................................................................................................... 15 2.5. Concluding remarks ............................................................................................................................. 18 Exemplary evaluation of reduction activities in transportation.................................................................... 19 3. 3.1. Purchase of new cars ........................................................................................................................... 19 3.1.1. Baseline definition ........................................................................................................................... 20 3.1.2. Technical reduction potential ......................................................................................................... 21 3.1.3. Cost efficiency ................................................................................................................................. 24 3.1.4. Verifiability ...................................................................................................................................... 27 3.1.5. Implementation barriers ................................................................................................................. 29 3.1.6. Results ............................................................................................................................................. 31 3.2. Choice of transportation means .......................................................................................................... 32 3.2.1. Baseline definition ........................................................................................................................... 32 3.2.2. Technical reduction potential ......................................................................................................... 34 3.2.3. Cost efficiency ................................................................................................................................. 36 3.2.4. Verifiability ...................................................................................................................................... 38 3.2.5. Implementation barriers ................................................................................................................. 40 3.2.6. Results ............................................................................................................................................. 42 3.3. Results and qualitative rating of reduction activities in the transport sector ..................................... 43 Conclusion ..................................................................................................................................................... 46 4. Acknowledgements ....................................................................................................................................... 47 5. References .................................................................................................................................................... 48 6. Annex .................................................................................................................................................................... 55 Off4Firms Working Paper D1.1. Off4Firms in a Nutshell 4 Off4Firms in a Nutshell Off4Firms – Employer-led incentives for households’ reductions in CO2 emissions and energy consumption Off4Firms is an applied research and innovation project aiming at reducing greenhouse gas emissions and energy consumption of private households. The project is led by ETH Zurich (Chair of Economics, Prof. Renate Schubert) and involves project partners from academia and business: Wageningen University, South Pole Carbon, Swiss Re, and EWZ. Partially financed by EIT Climate-KIC, the project runs from April 2012 until March 2014. Being one of the world’s largest emitters, households in aggregate bear an enormous potential for reducing emissions and energy consumption. Off4Firms starts from the premise that one effective way of triggering change in households is through household members’ employers. Off4Firms creates a win-win situation for households and firms: both profit from employees saving energy and reducing CO2 in their households. Employees benefit because they change their energy-related behaviour with the support of their employer. This change pays for – for example through lower energy costs. Companies, on the other hand, benefit from reputation gains as employers and in the public. In addition, under specific conditions – they may profit from offsetting their emissions by their employees’ emission reductions. Off4Firms develops a comprehensive programme for firms to use this great potential in an efficient way. This project enables firms to evaluate measures aiming at reductions in energy use and CO2 emissions in their employees’ private lives. Evaluation criteria are the effectiveness, cost efficiency, verifiability and acceptability of measures for the employees. Best practice measures will be identified and a tool kit will be provided, enabling the development of company-tailored CO2 or energy reduction measures. These measures will be brought to scale by a dedicated business unit. In addition, the policy framework making such measures a win-win strategy for households and for firms will be depicted. Off4Firms Working Paper D1.1. Abstract

3 citations


Cites background from "Energieeffizienznetzwerke – beschle..."

  • ...Yet, there seem to be several important barriers such as lacking awareness, large administrative hurdles, and missing information that impede the success of such activities (Epper, Fehr-Duda, & Schubert, 2011; Farsi, 2010; Jaffe & Stavins, 1994; Jakob, 2007; Jochem et al., 2010)....

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  • ...This inertia may at least partially be caused by either a lack of awareness and acceptability of new technologies or by continuing a traditional or common behaviour or habit (Abou-Zeid et al., 2012; Jakob, 2007; Jochem et al., 2010)....

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  • ...The energy-efficiency gap implies that specific implementation barriers exist that hinder private households from realizing cost efficient reduction activities (Eichhammer et al., 2009; Jochem et al., 2010)....

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References
More filters
Journal ArticleDOI
TL;DR: Ajzen, 1985, 1987, this article reviewed the theory of planned behavior and some unresolved issues and concluded that the theory is well supported by empirical evidence and that intention to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior.

65,095 citations

Book
30 Dec 1991
TL;DR: In this article, the development of social network analysis, tracing its origins in classical sociology and its more recent formulation in social scientific and mathematical work, is described and discussed. But it is argued that the analysis of social networks is not a purely static process.
Abstract: This paper reports on the development of social network analysis, tracing its origins in classical sociology and its more recent formulation in social scientific and mathematical work. It is argued...

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30 Dec 1991
TL;DR: Networks and Relations The Development of Social Network Analysis Handling Relational Data Lines, Direction and Density Centrality and Centralization Components, Cores, and Cliques Positions, Roles and Clusters Dimensions and Displays Appendix Social Network Packages
Abstract: Networks and Relations The Development of Social Network Analysis Handling Relational Data Lines, Direction and Density Centrality and Centralization Components, Cores, and Cliques Positions, Roles, and Clusters Dimensions and Displays Appendix Social Network Packages

5,638 citations

MonographDOI
01 Jan 2012
TL;DR: Social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals achieve their goals.
Abstract: This book introduces the non-specialist reader to the principal ideas, nature and purpose of social network analysis. Social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals achieve their goals. Social network theory maps these relationships between individual actors. Though relatively new on the scene it has become hugely influential across the social sciences. Assuming no prior knowledge of quantitative sociology, this book presents the key ideas in context through examples and illustrations. Using a structured approach to understanding work in this area, John Scott signposts further reading and online sources so readers can develop their knowledge and skills to become practitioners of this research method. A series of Frequently Asked Questions takes the reader through the main objections raised against social network analysis and answers the various queries that will come up once the reader has worked their way through the book.

5,439 citations