Innovative financial instruments in the Czech Republic and their hypothetical use in the field of energy efficiency are analysed and assessed in this thesis. We address lim- ited awareness about multiple benefits of energy efficiency improvements and also emerging innovative financial instruments that are promoted by the European Com- mission as a way to multiply impacts of limited public budgets. Then we identify a suitable segment, Czech residential housing stock and public support of insulation, and compare several forms of possible public support in this field. As the main driver of space heating costs, we predict the future development of heat prices, and assess po- tential energy savings resulting from renovations. Finally, we assess and also simulate the potential of such an initiative and identify four suitable settings of the innovative financial instrument for a majority of stakeholders. Our findings support an idea that this innovative financial instrument offers a valuable alternative to traditional grants. It also suggests that such an initiative can be interesting for a private sector as well as a public sector, with benefits to public budgets, equity investors, households and many other stakeholders. Moreover, this initiative can be sustainable in the long run. JEL Classification G23,...

The main objective of the thesis is to seek insights into the theory, and provide empirical evidence of rebound effects. Rebound effects reduce the environmental benefits of environmental policies and household behaviour changes. In particular, win-win demand side measures, in the form of energy efficiency and household consumption pattern changes, are seen as ways for households and businesses to save money and the environment. However, these savings have environmental impacts when spent, which are known as rebound effects. This is an area that has been widely neglected by policy makers. This work extends the rebound effect literature in three important ways, (1) it incorporates the potential for variation of rebound effects with household income level, (2) it enables the isolation of direct and indirect effects for cases of energy efficient technology adoption, and examines the relationship between these two component effects, and (3) it expands the scope of rebound effect analysis to include government taxes and subsidies. MACROBUTTON HTMLDirect Using a case study approach it is found that the rebound effect from household consumption pattern changes targeted at electricity is between 5 and 10%. For consumption pattern changes with reduced vehicle fuel use, the rebound effect is in the order of 20 to 30%. Higher income households in general are found to have a lower total rebound effect; however the indirect effect becomes relatively more significant at higher household income levels. In the win-lose case of domestic photovoltaic electricity generation, it is demonstrated that negative rebound effects can occur, which can potentially amplify the environmental benefits of this action. The rebound effect from a carbon tax, which occurs due to the re-spending of raised revenues, was found to be in the range of 11-32%. Taxes and transfers between households of different income levels also have environmental implications. For example, a more progressive tax structure, with increased low income welfare payments is likely to increase greenhouse gas emissions. Subsidies aimed at encouraging environmentally friendly consumption habits are also subject to rebound effects, as they constitute a substitution of government expenditure for household expenditure. For policy makers, these findings point to the need to incorporate rebound effects in the environmental policy evaluation process.’

The aim of the thesis is to determine why there are set wrong conditions of public expenditure programs to improve energy efficiency in the Czech Republic. The thesis analyzes conditions of funding and planning of specific projects funded by the Operational Environment program. The main criterion for evaluating projects is the consideration of energy efficiency. Methodologically, the research is based on an analysis of secondary data and the concept of cost-effectiveness. Based on the analysis, recommendations are made for changes in processes and parameterization of public expenditure programs in order to take account of higher energy efficiency criteria in the design and selection of supported projects, and thus be the energy efficiency target for 2020 by 20% could be achieved.

Energy efficiency has developed into an important objective for industrial enterprises. However, there is still a need for systematic approaches to reduce energy consumption in factories. Existing methods focus on the optimization of manufacturing processes and lack upon considering the entire factory system. Additionally, they are based on a detailed quantitative analysis of processes and thus, they need a high effort during the phase of data acquisition. Therefore, an approach for reducing energy consumption by providing energy efficiency measures to factory planning participants was developed in order to overcome these barriers. The general approach is described in this paper and supported with a use case that demonstrates the required information and possible outcomes in terms of energy efficiency information. Main advantages of this approach are reducing the effort to acquire energy data and the possibility to consider the factory system holistically.

As the wireless communication technologies evolve and the demand of wireless services increases, spectrum scarcity becomes a bottleneck that limits the introduction of new technologies and services. Spectrum sharing between primary and secondary users has been brought up to improve spectrum efficiency. In underlay spectrum sharing, the secondary user transmits simultaneously with the primary user, under the constraint that the interference induced at the primary receiver is below a certain threshold, or a certain primary rate requirement has to be satisfied. Specifically, in this thesis, the coexistence of a multiple-input single-output (MISO) primary link and a MISO/multiple-input multiple-output (MIMO) secondary link is studied. The primary transmitter employs maximum ratio transmission (MRT), and single-user decoding is deployed at the primary receiver. Three scenarios are investigated, in terms of the interference from the primary transmitter to the secondary receiver, namely, weak interference, strong interference and very strong interference, or equivalently three ranges of primary rate requirement. Rate splitting and successive decoding are deployed at the secondary transmitter and receiver, respectively, when it is feasible, and otherwise single-user decoding is deployed at the secondary receiver. For each scenario, optimal beamforming/precoding and power allocation at the secondary transmitter is derived, to maximize the achievable secondary rate while satisfying the primary rate requirement and the secondary power constraint. Numerical results show that rate splitting at the secondary transmitter and successive decoding at the secondary receiver does significantly increase the achievable secondary rate if feasible, compared with single-user decoding at the secondary receiver. In overlay spectrum sharing, different from underlay spectrum sharing, the secondary transmitter can utilize the knowledge of the primary message, which is acquired non-causally (i.e., known in advance before transmission) or causally (i.e., acquired in the first phase of a two-phase transmission), to help transmit the primary message besides its own message. Specifically, the coexistence of a MISO primary link and a MISO/MIMO secondary link is studied. When the secondary transmitter has non-causal knowledge of the primary message, dirty-paper coding (DPC) can be deployed at the secondary transmitter to precancel the interference (when decoding the secondary message at the secondary receiver), due to the transmission of the primary message from both transmitters. Alternatively, due to the high implementation complexity of DPC, linear precoding can be deployed at the secondary transmitter. In both cases, the primary transmitter employs MRT, and single-user decoding is deployed at the primary receiver; optimal beamforming/precoding and power allocation at the secondary transmitter is obtained, to maximize the achievable secondary rate while satisfying the primary rate requirement and the secondary power constraint. Numerical results show that with non-causal knowledge of the primary message and the deployment of DPC at the secondary transmitter, overlay spectrum sharing can achieve a significantly higher secondary rate than underlay spectrum sharing, while rate loss occurs with the deployment of linear precoding instead of DPC at the secondary transmitter. When the secondary transmitter does not have non-causal knowledge of the primary message, and still wants to help with the primary transmission in return for the access to the spectrum, it can relay the primary message in an amplify-and-forward (AF) or a decode-and-forward (DF) way in a two-phase transmission, while transmitting its own message. The primary link adapts its transmission strategy and cooperates with the secondary link to fulfill its rate requirement. To maximize the achievable secondary rate while satisfying the primary rate requirement and the primary and secondary power constraints, in the case of AF cooperative spectrum sharing, optimal relaying matrix and beamforming vector at the secondary transmitter is obtained; in the case of DF cooperative spectrum sharing, a set of parameters are optimized, including time duration of the two phases, primary transmission strategies in the two phases and secondary transmission strategy in the second phase. Numerical results show that with the cooperation from the secondary link, the primary link can avoid outage effectively, especially when the number of antennas at the secondary transceiver is large, while the secondary link can achieve a significant rate. Power is another precious resource besides spectrum. Instead of spectrum efficiency, energy-efficient spectrum sharing focuses on the energy efficiency (EE) optimization of the secondary transmission. The EE of the secondary transmission is defined as the ratio of the achievable secondary rate and the secondary power consumption, which includes both the transmit power and the circuit power at the secondary transmitter. For simplicity, the circuit power is modeled as a constant. Specifically, the EE of a MIMO secondary link in underlay spectrum sharing is studied. Three transmission strategies are introduced based on the primary rate requirement and the channel conditions. Rate splitting and successive decoding are deployed at the secondary transmitter and receiver, respectively, when it is feasible, and otherwise single-user decoding is deployed at the secondary receiver. For each case, optimal transmit covariance matrices at the secondary transmitter are obtained, to maximize the EE of the secondary transmission while satisfying the primary rate requirement and the secondary power constraint. Based on this, an energy-efficient resource allocation algorithm is proposed. Numerical results show that MIMO underlay spectrum sharing with EE optimization can achieve a significantly higher EE compared with MIMO underlay spectrum sharing with rate optimization, at certain SNRs and with certain circuit power, at the cost of the achievable secondary rate, while saving the transmit power. With rate splitting at the secondary transmitter and successive decoding at the secondary receiver if feasible, a significantly higher EE can be achieved compared with the case when only single-user decoding is deployed at the secondary receiver. Moreover, the EE of a MIMO secondary link in overlay spectrum sharing is studied, where the secondary transmitter has non-causal knowledge of the primary message and employs DPC to obtain an interference-free secondary link. Energy-efficient precoding and power allocation is obtained to maximize the EE of the secondary transmission while satisfying the primary rate requirement and the secondary power constraint. Numerical results show that MIMO overlay spectrum sharing with EE optimization can achieve a significantly higher EE compared with MIMO overlay spectrum sharing with rate optimization, at certain SNRs and with certain circuit power, at the cost of the achievable secondary rate, while saving the transmit power. MIMO overlay spectrum sharing with EE optimization can achieve a higher EE compared with MIMO underlay spectrum sharing with EE optimization. / Aufgrund der rasanten Entwicklung im Bereich der drahtlosen Kommunikation und der ständig steigenden Nachfrage nach mobilen Anwendungen ist die Knappheit von Frequenzbändern ein entscheidender Engpass, der die Einführung neuer Funktechnologien behindert. Die gemeinsame Benutzung von Frequenzen (Spektrum-Sharing) durch primäre und sekundäre Nutzer ist eine Möglichkeit, die Effizienz bei der Verwendung des Spektrums zu verbessern. Bei der Methode des Underlay-Spektrum-Sharing sendet der sekundäre Nutzer zeitgleich mit dem primären Nutzer unter der Einschränkung, dass für den primären Nutzer die erzeugte Interferenz unterhalb eines Schwellwertes liegt oder gewisse Anforderungen an die Datenrate erfüllt werden. In diesem Zusammenhang wird in der Arbeit insbesondere die Koexistenz von Mehrantennensystemen untersucht. Dabei wird für die primäre Funkverbindung der Fall mit mehreren Sendeantennen und einer Empfangsantenne (MISO) angenommen. Für die sekundäre Funkverbindung werden mehrere Sendeantennen und sowohl eine als auch mehrere Empfangsantennen (MISO/MIMO) betrachtet. Der primäre Sender verwendet Maximum-Ratio-Transmission (MRT) und der primäre Empfänger Einzelnutzerdecodierung. Für den sekundären Nutzer werden außerdem am Sender eine Datenratenaufteilung (rate splitting) und am Empfänger entweder eine sukzessive Decodierung – sofern sinnvoll – oder andernfalls eine Einzelnutzerdecodierung verwendet. Im Unterschied zur Methode des Underlay-Spektrum-Sharing kann der sekundäre Nutzer beim Verfahren des Overlay-Spektrum-Sharing die Kenntnis über die Nachrichten des primären Nutzers einsetzen, um die Übertragung sowohl der eigenen als auch der primären Nachrichten zu unterstützen. Das Wissen über die Nachrichten erhält er entweder nicht-kausal, d.h. vor der Übertragung, oder kausal, d.h. während der ersten Phase einer zweistufigen Übertragung. In der Arbeit wird speziell die Koexistenz von primären MISO-Funkverbindungen und sekundären MISO/MIMO-Funkverbindungen untersucht. Bei nicht-kausaler Kenntnis über die primären Nachrichten kann der sekundäre Sender beispielsweise das Verfahren der Dirty-Paper-Codierung (DPC) verwenden, welches es ermöglicht, die Interferenz durch die primären Nachrichten bei der Decodierung der sekundären Nachrichten am sekundären Empfänger aufzuheben. Da die Implementierung der DPC mit einer hohen Komplexität verbunden ist, kommt als Alternative auch eine lineare Vorcodierung zum Einsatz. In beiden Fällen verwendet der primäre Transmitter MRT und der primäre Empfänger Einzelnutzerdecodierung. Besitzt der sekundäre Nutzer keine nicht-kausale Kenntnis über die primären Nachrichten, so kann er als Gegenleistung für die Mitbenutzung des Spektrums dennoch die Übertragung der primären Nachrichten unterstützen. Hierfür leitet er die primären Nachrichten mit Hilfe der Amplify-And-Forward-Methode oder der Decode-And-Forward-Methode in einer zweitstufigen Übertragung weiter, währenddessen er seine eigenen Nachrichten sendet. Der primäre Nutzer passt seine Sendestrategie entsprechend an und kooperiert mit dem sekundären Nutzer, um die Anforderungen an die Datenrate zu erfüllen. Nicht nur das Spektrum sondern auch die Sendeleistung ist eine wichtige Ressource. Daher wird zusätzlich zur Effizienz bei der Verwendung des Spektrums auch die Energieeffizienz (EE) einer sekundären MIMO-Funkverbindung für das Underlay-Spektrum-Sharing-Verfahren analysiert. Wie zuvor wird für den sekundären Nutzer am Sender eine Datenratenaufteilung (rate splitting) und am Empfänger entweder eine sukzessive Decodierung oder eine Einzelnutzerdecodierung betrachtet. Weiterhin wird die EE einer sekundären MIMO-Funkverbindung für das Overlay-Spektrum-Sharing-Verfahren untersucht. Dabei nutzt der sekundäre Nutzer die nicht-kausale Kenntnis über die primären Nachrichten aus, um mittels DPC eine interferenzfreie sekundäre Funkverbindung zu erhalten.

This thesis uses innovative approaches to analyse energy policy interventions aimed at enhancing the environmental sustainability of energy use as well as its consequential welfare implications. First, we examine the relationship between energy efficiency improvement and CO2 emissions at the macro level. We use the Index Decomposition Analysis to derive energy efficiency by separating out the impact of shifts in economic activity on energy intensity. We then employ econometric models to relate energy efficiency and CO2 emissions accounting for non-economic factors such as consumers lifestyle and attitudes. The applications for 13 OPEC and 30 OECD countries show that at the country-group and individual country level, increase in energy intensity for OPEC is associated with both deteriorations in energy efficiency and shifts towards energy-intensive activities. The model results suggest that the reduction in energy efficiency in general go in tandem with substantial increases in CO2 emissions. The decline in energy intensity for OECD can be attributed mainly to improvements in energy efficiency which is found to compensate for the impact on CO2 emissions of income changes. The results confirm the empirical relevance of energy efficiency improvements for the mitigation of CO2 emissions. The method developed in this chapter further enables the separate assessment of non-economic behavioural factors which according to the results exert a non-trivial influence on CO2 emissions. Secondly, having empirically confirmed the relationship between energy efficiency improvements and CO2 emission at the macro level in Chapter 2, we investigate potential underlying drivers of energy efficiency improvements taking into account potential asymmetric effects of energy price change in Chapter 3. This is crucial for designing effective and efficient policy measures that can promote energy efficiency. In addition to the Index Decomposition Analysis used to estimate the economy-wide energy efficiency in Chapter 2, we also use Stochastic Frontier Analysis and Data Envelop Analysis as alternative methods. The driving factors are examined using static and dynamic panel model methods that account for both observed and unobserved country heterogeneity. The application for 32 OECD countries shows that none of the three methods leads to correspondence in term of ranking between energy efficiency estimates and energy intensity at the country level corroborating the criticism that energy intensity is a poor proxy for energy efficiency. The panel-data regression results using the results of the three methods show similarities in the impacts of the determinants on the energy efficiency levels. Also, we find insignificant evidence of asymmetric effects of total energy price but there is proof of asymmetry using energy specific prices. Thirdly, in Chapter 4 we offer an improved understanding of the impacts to expect of abolishing fuel price subsidy on fuel consumption, and also of the welfare and distributional impacts at the household level. We develop a two-step approach for this purpose. Key aspect of the first step is a two-stage budgeting model to estimate various fuel types elasticities using micro-data. Relying on these estimates and the information on households expenditure shares for different commodities, the second step estimates the welfare (direct and indirect) and distributional impacts. The application for Nigeria emphasises the relevance of this approach. We find heterogeneous elasticities of fuel demand among household groups. The distributional impact of abolishing the kerosene subsidy shows a regressive welfare loss. Although we find a progressive loss for petrol, the loss gap between the low- and high-income groups is small relative to the loss gap from stopping kerosene subsidy, making the low-income groups to suffer a higher total welfare loss. Finally, from the highlighted results, we draw the following concluding remarks in chapter 5. Energy efficiency appears a key option to mitigate CO2 emissions but there is also a need for additional policies aiming for behavioural change; energy specific prices and allowing for asymmetry in analysing the changes in energy efficiency is more appropriate and informative in formulating reliable energy policies; the hypothesis that only the rich would be worse-off from fuel subsidy removal is rejected and the results further suggest that timing of the fuel subsidy removal would be crucial as a higher international oil price will lead to higher deregulated fuel price and consequently, larger welfare loss.

Cooperative relay systems have emerged as promising techniques to boost the performance of wireless systems. Recent studies have confirmed that interferences, co-channel interferences (CCIs) and self-interferences, have a huge impact on cooperative relay systems and can cause significant performance degradation. Two problems were observed in this research. Firstly, previous studies on performance analysis of Amplify-and-Forward (AF) relay systems in presence of CCIs have only focused on a specific interference channel model. However, in practical design scenarios, such an assumption is not a realistic proposition. Secondly, analyses of overheads introduced by a time-based relay selection protocol in distributed cooperative systems have been based on an over-pessimistic assumption where all packets involved in a collision are destroyed. Nevertheless, collisions due to the protocol overheads cause the system performance to be degraded but this does not mean that the failure of end-to-end transmission certainly occurs. The thesis aims to analyse the performance of practical cooperative relay systems in the presence of CCIs and self-interferences, by developing exact mathematical methods. A new unified mathematical method for AF relay systems in presence of a random number of arbitrary non-identical CCIs was developed. The obtained new approach derived in terms of a moment generating function of the aggregate interferences' power led to the derivation of new explicit expressions. The new results greatly simplify evaluation of average error rates over diverse practical interference scenarios. Moreover, a new exact mathematical analysis for distributed cooperative relay systems employing a time-based relay selection protocol based on an accurate interference model was presented. This approach led to the derivation of new exact expressions for the spectral efficiency which accounts for both self-interferences and the protocol overheads as well as for different fading scenarios and arbitrary relay locations. This approach provided several advantages over direct approaches, one of which is that it significantly simplified averaging-out the joint random variables involved.

Purpose – This investigation aims to reframe the sizeable literature on barriers and drivers for energy efficiency measures and the phenomenon of the energy efficiency gap. We identified a gap between academic methods and industrial needs as well as a neglect of the cultural di-mension, despite its considerable impact. Based on this insight, the purpose of this paper is to integrate all of the various influences on industrial energy behavior previously identified in the literature in a refined energy cultures framework. Design/methodology/approach – This paper includes a systematic literature review of re-search in the field of energy management, energy efficiency, and cultural aspects within barri-ers and drivers of energy behavior. We selected and refined an existing energy cultures framework for the industrial context. To meet industrial needs, we applied an ontology map-ping of its core elements onto an international standard common for industrial energy man-agement practice. Findings – First, we present a refined framework for industrial energy cultures incorporating past barriers and drivers as factors. The framework enables an evaluation of attitude and be-havioral aspects, underlying technologies, organizational culture and actions related to energy as a system of interdependencies. Second, the factors are ranked based on number of appear-ances and empirical metadata. Economic aspects such as ‘Purchase, installment, and hidden costs’, ‘General investment and risk behavior’, and ‘Regulatory conditions’ are the highest ranked factors, but ‘Existing knowledge about EEM’, ‘Hierarchy approach: Top down’, and ‘Environmental concerns’ follow closely and represent cultural aspects which are still under-rated. Third, while illustrating a successful mapping onto a standardized process of continuous improvement, we also argue for heightened an academia-practice efforts. Social implications – Targeting the energy efficiency gap is an essential part of the sustainable development goals. The refined energy cultures framework allows for a better understanding of the industrial energy behaviors that are responsible for a significant share of a company’s success. The introduction of energy cultures serves as a starting point for future scholarly re-search within sustainability management accounting. Originality/value – The investigation combines existing research streams, their concepts, and their results about cultural aspects related to energy efficiency for both academics and practi-tioners. This review is the first to capture all of the various factors analyzed in academic litera-ture using the energy cultures framework as a basis. We add to the theoretical development of that framework with its application to the industrial context. This was identified as a gap. Its refinement helps to holistically understand barriers and drivers of industrial energy efficiency measures in order to support its practical implementation.

The aim of the master thesis is the assessment of the economic effectivity of thermal insulation with the state incentives in the Czech Republic and Slovak Republic. In the master thesis, the issue of investment, the possibilities of state funding of the construction industry, a detailed analysis of national funding programs aimed at promoting thermal insulation and the characteristics of thermal insulation contact system will be discussed with the focus on the design, realization management of the building and material possibilities. The output of the master thesis will be a proposal of a possible solution of thermal insulation contact system on a reference object. The financing of the investment will be compared in case of investment based on own resources or a bank loan, with the final assessment of economic efficiency with the use of insulation subsidy programs in the Czech Republic and Slovak Republic.

Die vorliegende Arbeit untersucht wie rationale Entscheidungsfindungen in Transformationsländern katalysiert werden können, indem durch den Fokus auf die internationale Wertschöpfungskette Synergieeffekte zwischen den Unternehmen genutzt und in deren Folge die Transaktionskosten, für Investitionsentscheidungen in energieeffiziente Technologien und Prozesse zur Erfüllung der Emissionsreduktionen, gesenkt werden können. Es wird das Wirken der Marktmechanismen analysiert und der Fokus auf die Transformationstheorie sowie die Ingenieurwissenschaften gelegt. Das Supply Chain Management, als anwendungsorientierte Realwissenschaft mit expliziter Ausrichtung auf Wertschöpfungsprozesse, wird in Bezug auf strategische Investitionsentscheidungen im Allgemeinen und Investitionen in Energieeffizienzmaßnahmen im Speziellen, weiterentwickelt. Mit Hilfe einer empirisch basierten Fallstudie werden die abgeleiteten Erkenntnisse einer kritischen Prüfung unterzogen und beispielhaft dargestellt, wie das entwickelte Entscheidungsmodell eingesetzt werden kann.:Inhaltsverzeichnis Geleitwort ................................................................................................................ III Danksagung ............................................................................................................ IV Inhaltsverzeichnis ...................................................................................................... V Formelverzeichnis .................................................................................................... XI Abkürzungsverzeichnis............................................................................................. XII Teil A Konzeption der Arbeit...................................................................................... 16 1 Einführung – Integrierte Klima- und Energiepolitik und Entscheidungstheorie .. 16 2 Problemstellung...................................................................................... 25 3 Zielsetzung der Arbeit.............................................................................. 27 4 Wissenschaftstheoretische Fundierung und Methodischer Aufbau der Arbeit .. 30 4.1 Zur wissenschaftlichen Fundierung der Arbeit ................................................... 30 4.2 Aufbau der Arbeit und Beitrag zum wissenschaftlichen Erkenntnisfortschritt .......... 34 Teil B Theoretischer Bezugsrahmen........................................................................... 40 5 Basale Begriffe und Definitionen ............................................................... 40 5.1 Kohlenstoffdioxid und andere Treibhausgase .................................................... 40 5.2 Der Effizienzbegriff ........................................................................................ 44 5.3 Energie-Effizienz-Indikatoren .......................................................................... 47 5.4 Unternehmensrelevante Normen..................................................................... 52 5.5 Theoretischer Ansatz des Supply Chain Managements ...................................... 55 5.6 Transformationsländer und Systemtransformation ............................................. 62 5.6.1 Zum Begriff des Transformationslandes ..................................................... 62 5.6.2 Ökonomische Systemtransformation in Transformationsländern.................... 66 5.6.3 Bedeutung der Energieeffizienz in der polnischen Industrie im Rahmen des Transformationsprozesses ....................................................................... 71 5.6.4 Die Industrie Rumäniens unter energetischem Gesichtspunkt ....................... 74 5.7 Transaktionskostentheorie.............................................................................. 78 5.7.1 Die Transaktionskostentheorie im Rahmen der Neuen Institutionentheorie ..... 78 5.7.2 Transaktionskosten im Rahmen des Emissionshandels................................ 83 5.8 System -und Entscheidungstheorie.................................................................. 85 5.8.1 Grundlagen der System– und Entscheidungstheorie.................................... 85 5.8.2 Betriebswirtschaftliche Entscheidungstheorie.............................................. 90 5.8.2.1 Zum Problembegriff....................................................................................90 5.8.2.2 Alternativenkonfiguration............................................................................92 5.8.2.3 Präferenzmodellierung ...............................................................................94 5.8.3 Unternehmenspolitische Entscheidungsansätze.......................................... 96 5.8.3.1 Argumentenbilanz ......................................................................................96 5.8.3.2 Nutzwertanalyse.........................................................................................97 5.8.3.3 Portfolioanalyse..........................................................................................99 VI 5.8.4 Die Entscheidungsorientierte Betriebswirtschaftslehre................................ 102 5.8.5 Modellklassen ...................................................................................... 109 5.8.6 Entscheidungsregeln............................................................................. 112 5.8.6.1 Entscheidungsregeln bei Unsicherheit .....................................................116 5.8.6.1.1 Minimax-Entscheidungsregel.............................................................116 5.8.6.1.2 Maximax- Entscheidungsregel...........................................................116 5.8.6.1.3 Hurwicz-Entscheidungsregel (Pessimissmus-Optimismus-Regel) .....117 5.8.6.1.4 Savage-Niehans-Entscheidungsregel................................................118 5.8.6.1.5 Laplace-Entscheidungsregel .............................................................119 5.8.6.2 Entscheidungsregeln bei Risiko ...............................................................121 5.8.6.2.1 Erwartungswert-Regel .......................................................................121 5.8.6.2.2 μ -σ -Regel.......................................................................................121 5.8.6.2.3 Bernoulli-Regel..................................................................................122 5.8.6.2.4 Entscheidungsbaum..........................................................................123 5.8.7 Anforderungen an ein Entscheidungsmodell ............................................. 125 Teil C Energieeffizienzstrategien: Europäische Union versus Transformationsländer ...... 128 6 Integrierte Ansätze zur Energieeffizienzsteigerung in Transformationsländern128 6.1 Emissionshandel als marktorientierter Mechanismus zur Effizienzerhöhung ........ 128 6.2 Ordnungspolitik versus Marktmechanismen – Kohlenstoffdioxidsteuer und Handel mit Emissionsrechten............................................................................................... 131 6.3 Die flexiblen Mechanismen des Kyoto -Protokolls ............................................ 136 6.3.1 Clean development mechanism.............................................................. 141 6.3.2 Joint Implementation ............................................................................. 143 6.4 Unternehmensstrategien unter cap – and trade Regulierung ............................. 152 Teil D Energieeffizienzinvestitionen entlang der Wertschöpfungskette........................... 156 7 Herausarbeitung des Handlungsbedarfes für Investitionen in Energieeffizienztechnologien – das ENEFFTECH-Entscheidungsmodell ....................... 156 7.1 Anforderungen an das ENEFFTECH-Entscheidungsmodell............................... 156 7.2 Das ENEFFTECH-Strukturmodell .................................................................. 157 7.3 Datenmodellierung im ENEFFTECH-Strukturmodell......................................... 158 7.3.1 Grundsätze der Datenmodellierung im ENEFFTECH-Strukturmodell............ 158 7.3.2 Informationsarchitektur und Prozessgestaltung für Strategisches Supply Chain Management ........................................................................................ 160 7.3.3 Datenmodell – Informationsebene ........................................................... 166 7.3.4 Datenmodell - Datenerfassungebene....................................................... 169 7.3.5 Datenmodell - Entscheidungsebene ........................................................ 171 7.3.5.1 Vorgaben zur Berechnung........................................................................171 7.3.5.2 Investitionsalternativen.............................................................................172 7.3.5.3 Umweltzustände.......................................................................................173 7.4 Abgrenzung von Bilanzräumen...................................................................... 174 7.5 Formulierung des Entscheidungsproblems...................................................... 178 7.6 Identifizierung von Handlungsalternativen auf Unternehmensebene ................... 183 7.7 Ableitung von Aussagen auf Branchenebene .................................................. 190 VII 7.7.1 Mikro-Makro-Link (MML) ........................................................................ 190 7.7.2 Erfassung relevanter Daten zur Ableitung von Branchenaussagen............... 194 7.7.3 Erweiterung des Ansatzes auf Emissionsreduzierende Energieeffizienzsteigerung ..................................................................... 199 7.7.4 Bewertung des ENEFFTECH-Entscheidungsmodell und Vergleich mit anderen Entscheidungsmethoden........................................................................ 203 8 Modelltest: Fallstudie zum ENEFFTECH-Entscheidungsmodell ................... 205 8.1 Energieeffizienzinvestionen entlang der Supply Chain am Beispiel eines mittelständischen Energieversorgers..................................................................... 205 8.1.1 Allgemeine Informationen und Rahmenbedingungen ................................. 205 8.1.2 Auswahl des Kooperationspartners der Stadtwerke ENEFFTECH-Stadt GmbH... .......................................................................................................... 206 8.1.3 Rahmenbedingungen hinsichtlich des Emissionshandels............................ 208 8.1.4 Auswahl der Wertschöpfungspartner ....................................................... 211 8.2 Lösungsansätze unter Nutzung des Supply Chain Managements ...................... 212 8.2.1 Systematisierung der Investitionsalternativen............................................ 212 8.2.2 Ableitung der Investitionsentscheidung .................................................... 217 Teil E Zusammenfassung und Schlussbetrachtungen ................................................. 220 9 Zusammenfassung und Fazit der Arbeit ................................................... 220 9.1 Zusammenfassende Einschätzung ................................................................ 220 9.2 Quo Vadis? - Ableitung des weiteren Forschungsbedarfes................................ 225 Symbole, Einheiten und Umrechnungen ................................................................... 227 Glossar ................................................................................................................ 229 Literatur- und Quellenverzeichnis............................................................................. 244 Anhang ................................................................................................................ 276